Journal of Personnel Psychology 1/2018

Volume 17 / Number 1 / 2018

Journal of

Personnel Psychology Editor-in-Chief Bernd Marcus Managing Editor Petra Gelléri Associate Editors Tanja Bipp Ian Gellatly Barbara Griffin Jonas Lang Laurenz Meier Sandra Ohly Xin-An Zhang

Integrative perspectives on motivation and volition “This is an excellent and valuable volume. It is a wonderful collection of pieces on motivation that serves as an apt tribute to an unusually creative and generous scholar.”

Andrew J. Elliot, PhD, Professor of Psychology, Department of Clinical & Social Sciences in Psychology, University of Rochester, NY, USA

Nicola Baumann / Miguel Kazén / Markus R. Quirin / Sander L. Koole (Editors)

Why People Do the Things They Do Building on Julius Kuhl’s Contributions to the Psychology of Motivation and Volition 2018, xii + 434 pp.

US $87.00 / € 69.95 ISBN 978-0-88937-540-6 Also available as eBook How can we motivate students, patients, employees, and athletes? What helps us achieve our goals, improve our well-being, and grow as human beings? These issues, which relate to motivation and volition, are familiar to everyone who faces the challenges of everyday life. This comprehensive book by leading international scholars provides integrative perspectives on motivation and volition that build on the work of German psychologist Julius Kuhl.

The first part of the book examines the historical trail of the European and American research traditions of motivation and volition and their integration in Kuhl’s theory of personality systems interactions (PSI). The sec-

www.hogrefe.com

ond part of the book considers what moves people to action – how needs, goals, and motives lead people to choose a course of action (motivation).

The third part of the book explores how people, once they have committed themselves to a course of action, convert their goals and intentions into action (volition). The fourth part shows what an important role personality plays in our motivation and actions. Finally, the fifth part of the book discusses how integrative theories of motivation and volition may be applied in coaching, training, psychotherapy, and education.

This book is essential reading for everyone who is interested in the science of motivating people.

Journal of

Personnel Psychology Volume 17 / Number 1/2018

Editor-in-Chief

Bernd Marcus, Organizational and Personnel Psychology, Institute of Business Administration, University of Rostock, Ulmenstr. 69, 18057 Rostock, Germany. Tel. +49 381 498-4080, Fax +49 381 498-4419, E-mail: bernd.marcus@uni-rostock.de

Managing Editor

Petra Gelléri, Work and Organizational Psychology, Faculty of the Humanities and Social Sciences, University of Hagen, Universitätsstr. 33, 58084 Hagen, Germany, Tel. +49 2331 987-2745, Fax +49 2331 987-2179, E-mail: jpp.editorial.office@gmail.com

Associate Editors

Tanja Bipp, University of Würzburg, Germany Ian Gellatly, University of Alberta, Canada Barbara Griffin, Macquarie University, Australia Jonas Lang, Ghent University, Belgium Laurenz Meier, University of Neuchâtel, Switzerland Sandra Ohly, University of Kassel, Germany Xin-An Zhang, Shanghai Jiao Tong University, China

Editorial Board

Mike Ashton, Canada Arnold Bakker, The Netherlands Gerhard Blickle, Germany Diana Boer, Germany John Campbell, USA Oliver Christ, Germany Neil Christiansen, USA Brian Connelly, Canada Jeremy Dawson, UK Nele de Cuyper, Belgium Filip De Fruyt, Belgium Evangelia Demerouti, The Netherlands Deanne den Hartog, The Netherlands Jörg Felfe, Germany Steffen Giessner, The Netherlands Richard Goffin, Canada Peter Harms, USA Alex Haslam, UK Sarah Hezlett, USA Giles Hirst, Australia Stefan Höft, Germany Astrid C. Homan, The Netherlands Thomas Jønsson, Denmark Rudolf Kerschreiter, Germany Ulla Kinnunen, Finland Martin Kleinmann, Switzerland Cornelius König, Germany Franciska Krings, Switzerland Jonas Lang, Belgium Kibeom Lee, Canada Klaus Melchers, Germany Bertolt Meyer, Germany John P. Meyer, Canada

Publisher

Hogrefe Publishing, Merkelstr. 3, 37085 Göttingen, Germany, Tel. +49 551 99950-0, Fax +49 551 99950-425, E-mail publishing@hogrefe.com, Web http://www.hogrefe.com North America: Hogrefe Publishing, 7 Bulfinch Place, Suite 202, Boston, MA 02114, USA, Phone (866) 823-4726, Fax (617) 354-6875, E-mail publishing@hogrefe.com

Production

Christina Sarembe, Hogrefe Publishing, Merkelstr. 3, 37085 Göttingen, Germany, Tel. +49 551 99950-0, Fax +49 551 99950-425, E-mail publishing@hogrefe.com

Subscriptions

Hogrefe Publishing, Herbert-Quandt-Str. 4, 37081 Göttingen, Germany, Tel. +49 551 99950-900, Fax +49 551 99950-998

Advertising/Inserts

Marketing, Hogrefe Publishing, Merkelstr. 3, 37085 Göttingen, Germany, Tel. +49 551 99950-423, Fax +49 551 99950-425, E-mail marketing@hogrefe.com

ISSN

ISSN-L 1866-5888, ISSN-Print 1866-5888, ISSN-Online 2190-5150

Copyright Information

Ó 2018 Hogrefe Publishing. This journal as well as the individual contributions and illustrations contained within it are protected under international copyright law. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without prior written permission from the publisher. All rights, including translation rights, reserved.

Publication

Published in 4 issues per annual volume.

Subscription Prices

Calendar year subscriptions only. Rates for 2018: Institutions: US $324.00/ 249.00; Individuals: US $159.00/ 114.00. Postage and handling: US $16.00/ 12.00. Single copies: US $81.00/ 62.50 + postage and handling.

Payment

Payment may be made by check, international money order, or credit card, to Hogrefe Publishing, Merkelstr. 3, 37085 Göttingen, Germany, or, for North American customers, to Hogrefe Publishing, 7 Bulfinch Place, Suite 202, Boston, MA 02114, USA.

Abstracting Services

Abstracted/indexed in Social Sciences Citation Index (SSCI), Social SciSearch, Current Contents/Social and Behavioral Sciences (CC/S&BS), PsycINFO, PsyJOURNALS, PSYNDEX, Scopus, IBZ, IBR, ERIH.

Electronic Full-Text

The full-text of the Journal of Personnel Psychology is available online at www.econtent.hogrefe.com and also in PsycARTICLES.

Karin S. Moser, UK Klaus Moser, Germany Peter Muck, Germany Laetitia Mulder, The Netherlands Cornelia Niessen, Germany Ioannis Nikolaou, Greece Lisa Penney, USA Deborah Powell, Canada Floor Rink, The Netherlands Ann Marie Ryan, USA Paul R. Sackett, USA Jesus F. Salgado, Spain Niclas Schaper, Germany Bert Schreurs, The Netherlands Sebastian Schuh, China Birgit Schyns, UK Meir Shemla, The Netherlands Christiane Spitzmüller, USA Daan Stam, The Netherlands Thomas Staufenbiel, Germany Sebastian Stegmann, Germany H. Canan Sümer, Turkey Klaus J. Templer, Singapore Robert Tett, USA Christian Vandenberghe, Canada Beatrice van der Heijden, The Netherlands Rolf van Dick, Germany Chockalingam Viswesvaran, USA S. Arzu Wasti, Turkey Juergen Wegge, Germany Despoina Xanthopoulou, Greece Ingo Zettler, Denmark

Impact Factor (2016): 1.098

Journal of Personnel Psychology (2018), 17(1)

Ó 2018 Hogrefe Publishing

Contents Original Articles

News and Announcements

Ó 2018 Hogrefe Publishing

When Are Individuals Innovative? Three-Way Interaction Among Openness to Experience, Innovative Climate, and Job Complexity Ho Hwan Park, Youjia Zhou, and Myungweon Choi

1

Practical Considerations for Conducting Job Analysis Linkage Exercises Erika J. Robinson-Morral, Cheryl Hendrickson, Sarah Gilbert, Tara Myers, Kaila Simpson, and Andrew C. Loignon

12

When Is Task Conflict Translated Into Employee Creativity?

The Moderating Role of Growth Need Strength Yan Li, Baiyin Yang, and Lin Ma

22

Employees’ Critical Thinking, Leaders’ Inspirational Motivation, and Voice Behavior: The Mediating Role of Voice Efficacy Jing Jiang, Ang Gao, and Baiyin Yang

33

Is Emotional Engagement Possible in Emotionally Demanding Jobs?

The Role of Leader-Member Exchange (LMX) Long W. Lam, Angela J. Xu, and Raymond Loi

42

Awards for Outstanding Achievements as Authors and Reviewers 2017

53

Call for Proposals: 2020 and 2021 Special Issues of the Journal of Personnel Psychology

54

Journal of Personnel Psychology (2018), 17(1)

Original Article

When Are Individuals Innovative?

Three-Way Interaction Among Openness to Experience, Innovative Climate, and Job Complexity Ho Hwan Park,1 Youjia Zhou,2 and Myungweon Choi1 1

Department of Business Administration, Ajou University, Suwon, South Korea

2

HR Department, Hunan Communications Research Institute CO., LTD, China

Abstract: This study aims to explain: (a) what types of individuals are likely to exhibit innovative behavior and (b) when they are more likely to do so. For this purpose, the study uses trait activation theory (Tett & Burnett, 2003; Tett & Guterman, 2000) as a theoretical framework and simultaneously examines the characteristics of the individual performing the job (openness to experience), the context within which the job is performed (innovative climate), and the nature of the job (job complexity). An analysis of survey data collected in China suggests that innovative climate and job complexity have a joint moderating effect on the relationship between openness to experience and innovative behavior. Based on the results, implications for research and practice are discussed.

Keywords: openness to experience, innovative climate, job complexity, innovative behavior

Many stories of successful businesses suggest that ongoing innovation is required for organizations to perform well and survive in today’s rapidly changing business environment.

The commonality in these success stories may be that employees’ proactive participation in the innovation process ranging from the generation of novel and useful ideas to the implementation of those ideas – which we call “innovative behavior” – is the key to innovation. Thus far, an extensive body of research has been conducted to investigate the factors facilitating employees’ innovative behavior. In particular, researchers have focused on personal and contextual characteristics and the interactions among them, arguing that individual dispositions relevant to innovative behavior can manifest themselves when the context supports them (e.g., George & Zhou, 2001; Raja & Johns, 2010; Shalley, Gilson, & Blum, 2009; Shalley, Zhou, & Oldham, 2004; Yuan & Woodman, 2010). These studies stress that an individual’s creative and innovative behaviors at work results from a complex interaction between the individual and the work situation.

Building on this interactionist perspective, the current study investigates (a) what types of individuals are likely to exhibit innovative behavior and (b) when they are more likely to do so. Most researchers would agree that an employee’s uniqueness is a prerequisite of innovative behaviors at work. In particular, previous research has identified several individual traits predictive of innovative Ó 2018 Hogrefe Publishing

behaviors, such as openness to experience, growth need strength, and proactive personality (Anderson, Potočnik, & Zhou, 2014). Among these, focusing on openness to experience, the extent to which individuals are broadminded, curious, imaginative, and original (Feist, 1998; McCrae, 1987), has advantages given the extant discussion concerning the big five personality traits and their relationship to performance at work. Thus, in this study, we focus on openness to experience, which has received the most attention with consistent empirical support for its effect on innovative behavior, to elaborate our understanding of the conditions that let those with creative and innovative potentials demonstrate innovative behavior.

According to the trait activation theory (Tett & Burnett, 2003; Tett & Guterman, 2000), an individual’s trait relevant behavior is expressed as a response to trait relevant situational cues, and one’s standing in that trait determines the responses. Thus, to be innovative, individuals need to be provided with relevant situational cues or conditions.

Concerning the conditions that interact with one’s traits to lead him/her to be engaged in innovative behavior, the current study focuses on job complexity and work climate supportive of innovation. Drawing on the job demandsresources model (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001), we consider the former as job demands and the latter as job resources. Although work climate has been identified as a key precursor of innovative behavior Journal of Personnel Psychology (2018), 17(1), 1–11 https://doi.org/10.1027/1866-5888/a000190

2

H. H. Park et al., Interaction Between Openness to Experience, Innovative Climate, and Job Complexity

at work (e.g., Shalley et al., 2009), its effect has not been examined thoroughly in combination with the nature of the job. However, this line of study warrants further attention given that individuals exhibit innovative behavior on the job in a given work context and that both work climate and jobs differ widely across organizations, work units, and individual employees. By taking work climate, job complexity, and individuals’ personality traits into consideration simultaneously, this study purports to help broaden our understanding of the factors that facilitate or impede innovative behavior.

Literature Review and Hypotheses Though “creativity” and “innovation” are sometimes used interchangeably, researchers differentiate the two conceptually. While both creativity and innovation concern the generation of novel and useful ideas, innovation also involves the implementation of those ideas (Anderson et al., 2014). Creative and innovative behaviors are thus complementary, with the latter representing broader roles played by employees. Innovative behavior, the focus of this study, can be defined as employees’ overall participation in the innovation process – specifically, their behaviors in generating new ideas, disseminating their and others’ new ideas, and implementing those ideas themselves or helping others to do so (Axtell et al., 2000; Ng & Feldman, 2010, 2013; Ng, Feldman, & Lam, 2010).

Openness to experience has received extensive attention in the creativity and innovation literature. According to the literature, those high in openness to experience are more flexible in absorbing and combining information and tend to have access to a wide range of ideas and perspectives. Thus, not only do they feel more comfortable in situations providing new experiences, but are also more motivated to seek new and varied experiences. As a result, they are likely to be more innovative. In fact, the research has consistently identified openness to experience as the personality trait that leads to innovative behavior (Feist, 1998; King, Walker, & Broyles, 1996; LePine, Colquitt, & Erez, 2000; Scratchley & Hakstian, 2000; Shalley et al., 2004; Wolfradt & Pretz, 2001).

On the other hand, relatively less attention has been paid to the other big five personality traits. Some studies have reported a positive relationship between extraversion and innovative behavior; and a nonsignificant relationship between agreeableness and neuroticism and innovative behaviors (Feist, 1998; Furnham & Bachtiar, 2008; Silvia, Nusbaum, Berg, Martin, & O’Connor, 2009; Sung & Choi, 2009). The relationship between conscientiousness and innovative behavior has been reported to be negative.

Journal of Personnel Psychology (2018), 17(1), 1–11

Conscientious individuals tend to follow rules, conform to norms, be cautious and risk averse, and strictly adhere to standards; thus, they are less likely to come up with new ideas and change the status quo (Costa, McCrae, & Dye, 1991; Feist, 1998; George & Zhou, 2001; Le et al., 2011; LePine et al., 2000; Raja & Johns, 2010).

The present study is an attempt to contribute to the literature on innovative behavior by investigating the conditions that make individuals, with different levels of openness to experience, more or less innovative. For this purpose, this study draws on trait activation theory (Tett & Burnett, 2003; Tett & Guterman, 2000). Based on the principles underlying the person-environment fit theories (Pervin, 1968), Tett and colleagues focus on the situational specificity in the linkage between personality traits and job performance. According to them, a given situation provides particular cues, and individuals express their traits when presented with trait-relevant situational cues. Drawing on this theoretical perspective, we discuss two possible aspects of the work situation – innovative climate and job complexity – that provide situational cues to activate individuals’ dispositions relevant to innovative behavior and, thus, support the manifestation of individuals’ personality traits conducive to innovation.

Moderating Effects of Innovative Climate Organizational climate has been defined as organizational members’ “shared perceptions of organizational policies, practices, and procedures, both formal and informal . . . indicative of the organization’s goals and appropriate means to goal attainment” (Reichers & Schneider, 1990, p. 22). Among the conceptualizations of organizational climate (Patterson et al., 2005), we take the psychological climate perspective and define organizational climate as individuals’ cognitive interpretation of the organizational settings that send signals concerning expected behaviors and their potential outcomes. The organizational climate for innovation (or “innovative climate”) can be conceptualized as individuals’ interpretation of the emphasis on and support for innovation in the organization (Scott & Bruce, 1994), which acts as a psychological process linking the organizational setting and individuals’ innovative behavior.

As innovative behavior requires risk-taking and longterm investment, employees need to be provided with support from the organization to undertake such behaviors.

In this respect, innovative climate provides individuals with job resources with which to perform innovative behavior (Bakker & Demerouti, 2007). Innovative climate extrinsically motivates employees to become innovative, as it is instrumental in achieving the work goals of being innovative. At the same time, innovative climate stimulates Ó 2018 Hogrefe Publishing

H. H. Park et al., Interaction Between Openness to Experience, Innovative Climate, and Job Complexity

employees’ growth, learning, and development, thereby motivating them intrinsically to become innovative at work.

In fact, previous studies have shown that individuals are likely to exhibit innovative behavior when they perceive innovation to be rewarded, supported, and expected in the organization (George & Zhou, 2001, 2002; Hirst, Van Knippenberg, & Zhou, 2009; Ng & Feldman, 2013; Scott & Bruce, 1994).

Drawing on this line of research, we propose that innovative climate provides the situational cues to activate individuals’ dispositions relevant to innovative behavior that predispose them to either appreciate or not the opportunities and rewards provided by the situation. Specifically, when the organization has a highly innovative climate, those high in openness to experience are likely to find resources that are provided to meet their needs; or they may find similarities between themselves and the organization and experience consensual validation of their perspectives through the interaction with similar others (KristofBrown, Zimmerman, & Johnson, 2005; Muchinsky & Monahan, 1987; Van Vianen, 2000). Consequently, they are likely to respond to the situational cues by exhibiting innovative behavior. On the other hand, those low in openness to experience tend not to appreciate those cues and respond to them less positively. Supporting this idea, studies have suggested that individuals high in openness to experience tend to be more innovative when they expect the work group to recognize, encourage, and accept innovation (George & Zhou, 2001; Zhou & Oldham, 2001). Thus, we expect that an innovative climate will amplify the positive relationship between openness to experience and innovative behavior.

Hypothesis 1: Innovative climate moderates the relationship between openness to experience and innovative behavior such that the positive relationship between the two is stronger when innovative climate is higher.

Moderating Effects of Job Complexity The nature of a job acts as a proximal work context affecting individuals’ behavior at work. Regarding this, researchers have emphasized the importance of job complexity in relation to innovative behavior at work (Farmer, Tierney, & Kung-McIntyre, 2003; Hatcher, Ross, & Collins, 1989; Raja & Johns, 2010; Shalley et al., 2004; Tierney & Farmer, 2002, 2004). Job complexity increases intrinsic motivation, resulting in positive outcomes such as higher engagement.

At the same time, it also increases job demands that require efforts or skills and, therefore, often results in physiological and psychological costs and disengagement (Bakker & Demerouti, 2007). Ó 2018 Hogrefe Publishing

3

Van den Broeck, De Cuyper, De Witte, and Vansteenkiste’s (2010) idea is helpful in understanding the likely conflicting effects of job complexity. According to them, job demands – the physical, psychological, social, or organizational aspects of the job (e.g., high work pressure, unfavorable physical environment) that require sustained physical, cognitive, and emotional efforts (Bakker & Demerouti, 2007) – do not always result in negative outcomes. Some job demands called job hindrances hinder optimal functioning, thus leading an individual to be exhausted. On the other hand, other job demands called job challenges can stimulate and engage the individual.

Job demands such as workload and cognitive demands, which complex jobs involve, can act as either job hindrances or job challenges (e.g., Bakker, Demerouti, & Schaufeli, 2003, 2005), depending on the characteristics of the context or the person who performs the job. This idea has been supported by other researchers like Bipp (2010) and Judge, Bono, and Locke (2000) who empirically demonstrated the interaction between personality traits and job characteristics to affect work-related outcomes by showing that individuals with a positive self-concept prefer complex jobs, as they seek out opportunities to gain control over the work environment and challenge themselves.

We propose that job complexity provides situational cues (Tett & Burnett, 2003; Tett & Guterman, 2000) to activate individuals’ traits relevant to innovative behaviors and that the effects of job complexity on innovative behavior (i.e., whether it works as a job hindrance or job challenge) depend on the individuals’ traits. When the job is complex, those high in openness to experience are likely to believe that their personality traits meet the needs of the job or that their needs are satisfied by the characteristics of the job, thereby perceiving high person-job fit (Bipp, 2010; Kristof-Brown et al., 2005). Furthermore, they have a strong intellectual curiosity and seek out new experiences and ideas; thus, a complex job provides them with job challenges that appeal to their curiosity, competence, and thoroughness and render them opportunities for growth and development (Van den Broeck et al., 2010). Supporting this idea, previous research shows that those with a higher level of openness to experience are more likely to benefit from a training program (Barrick & Mount, 1991; Salgado, 1997). Thus, job complexity may have a salutary effect on the contribution of openness to experience and innovative behaviors as the fit between the person and the situational cues is enhanced by the opportunities embedded in complex jobs (Raja & Johns, 2010). Based on this reasoning, we propose that those high in openness to experience respond to a job high in complexity by exhibiting innovative behavior, whereas those low in openness to experience tend not to appreciate the complex job and respond to it less positively.

Journal of Personnel Psychology (2018), 17(1), 1–11

4

H. H. Park et al., Interaction Between Openness to Experience, Innovative Climate, and Job Complexity

Hypothesis 2: Job complexity moderates the relationship between openness to experience and innovative behavior such that the positive relationship between the two is stronger when job complexity is higher.

Joint Moderating Effects of Innovative Climate and Job Complexity The effects of job resources and job demands do not exist independently from each other; rather, individuals combine information about job resources and job demands provided by the environment to form work-related attitudes and make decisions. As reviewed by Bakker and Demerouti (2007), research findings indicate that job demands and job resources interact to affect work outcomes such that job resources buffer the impact of job demands on negative work outcomes (Bakker, Demerouti, & Euwema, 2005; Xanthopoulou, Bakker, Demerouti, & Schaufeli, 2007), and that the impact of job resources is more salient in the context of high job demands (Bakker, Hakanen, Demerouti, & Xanthopoulou, 2007; Billings, Folkman, Acree, & Moskowitz, 2000). Considering that innovative climate and job complexity provide job resources and job demands, respectively, we can assume that they also interact with each other to affect the relationship between personality traits and innovative behavior.

In the previous section, we proposed that those high in openness to experience are likely to exhibit more innovative behavior (a) in an innovative climate where they are encouraged to learn and use various new skills and try new ways of performing their tasks (Hypothesis 1) and (b) when the fit between the person and the situational cues is enhanced by the opportunities embedded in complex jobs (Hypothesis 2). Additionally, we propose that the interactive effects of openness to experience and innovative climate on innovative behavior are amplified by job complexity. For those high in openness to experience, job complexity provides job challenges (Van den Broeck et al., 2010) that stimulate their growth, learning, and development and engage them.

Combining the positive effects of innovative climate and job complexity for those high in openness to experience in an additive sense leads us to the proposition that the situational cues most relevant to innovative behavior are presented under the condition of highly innovative climate and complex jobs. That is, openness to experience will make the greatest difference under this condition. Furthermore, under the condition in which only one of the two situational factors (either innovative climate or job complexity) is high, the relevance of situational cues decreases and thus the relationship between openness to experience and innovative behavior is reduced. However, even in this situation, individuals high in openness to experience may find ways to be Journal of Personnel Psychology (2018), 17(1), 1–11

innovative. In addition, a highly innovative climate may compensate for the negative influence of low job complexity or vice versa. Finally, for those high in openness to experience, the situational cues relevant to innovative behavior are not presented under the condition in which both contextual factors are low, and their individual traits conducive to innovation have little influence on the manifestation of innovative behavior; therefore, openness to experience makes little or no significant difference in this situation.

We thus propose the following: Hypothesis 3: There is a three-way interaction among openness to experience, innovative climate, and job complexity in explaining innovative behavior. The positive relationship between openness to experience and innovative behavior is stronger when both innovative climate and job complexity are high and weaker when both innovative climate and job complexity are low than in any other combination of innovative climate and job complexity.

Methods Participants and Data Collection The questionnaire was constructed using measures validated by other researchers. To mitigate social desirability response bias, we included a cover letter in the questionnaire, explaining that participation was voluntary and that the surveys would be anonymous and used only for research purposes (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). The questionnaire was distributed to 400 employees in Hunan province, China; 308 were returned, yielding a response rate of about 77%. The respondents worked in diverse industries, including the financial industry (26%), the service industry (22%), and the manufacturing industry (16%). They held a wide range of jobs such as marketing (22%), production (22%), administration (16%), and finance (11%). About 52% of respondents were female, 45% were in their 20s, and 50% had fewer than 5 years of job tenure. The respondents were highly educated, with about 71% holding a Bachelor’s or more advanced degree.

Measures Openness to experience was measured with 10 items included in the International Personality Item Pool Big Five factor markers (Goldberg, 1992), translated and validated in Chinese (Zheng et al., 2008). Sample items included “I have a vivid imagination” and “I spend time reflecting on things.” Responses were coded using a Likert-type scale ranging from “very inaccurate” (1) to “very accurate” (5). Ó 2018 Hogrefe Publishing

H. H. Park et al., Interaction Between Openness to Experience, Innovative Climate, and Job Complexity

Innovative climate was assessed with three items developed by Bock, Zmud, Kim, and Lee (2005) and validated for the Chinese context (Li, Zhu, & Luo, 2010): “My department encourages suggesting ideas for new opportunities,” “My department puts much value on taking risks even if that turns out to be a failure,” and “My department encourages finding new methods to perform a task.”

Responses were coded using a Likert-type scale ranging from “strongly disagree” (1) to “strongly agree” (5).

Following previous research (e.g., Loher, Noe, Moeller, & Fitzgerald, 1985; Oldham & Cummings, 1996; Shalley et al., 2009), we used the job diagnostic survey (JDS; Hackman & Oldham, 1980) to assess job complexity. In particular, among the 15 items for measuring the five JDS dimensions, those that directly related to the extent to which a job is multifaceted and allows decision latitude were chosen for this study. Responses were coded using a Likert-type scale ranging from “strongly disagree” (1) to “strongly agree” (5).

Self-reported innovative behavior was measured with the six items developed by Scott and Bruce (1994). As the original items were to be completed by supervisors, they were paraphrased so the respondents could report their own innovative behavior. Sample items included “I search out new technologies, processes, techniques, and/or product ideas” and “I develop adequate plans and schedules for the implementation of new ideas.” Responses were coded using a Likert-type scale ranging from “strongly disagree” (1) to “strongly agree” (5). Self-reported measures of innovative behavior may have limitations in that they are subject to biases. However, we decided to use self-reported measures for the following reasons. First, whether one demonstrates innovative behavior or not is often unobservable by others, and respondents are the ones who know best about the subtle cognitive process to make decisions and to actually demonstrate innovative behaviors (Janssen, 2000, 2004; Ng & Feldman, 2012; Shalley et al., 2009). In addition, self-reported measures are better at ensuring anonymity than supervisor- or peer-reported measures. For these reasons, the use of self-reported measures of creativity and innovative behavior is not unusual among researchers. In fact, researchers have shown a significant correlation between individuals’ self-reported innovative behavior and objective measures or third-party evaluations of innovative behavior (Axtell et al., 2000; Janssen, 2000; Moneta, Amabile, Schatzel, & Kramer, 2010), providing support for the use of self-reported measures of innovative behavior.

Controls Researchers interested in the interplay between affect and the cognitive process have provided significant but conflicting evidence concerning the relationship between affect and innovative behavior (e.g., Amabile, Barsade, Mueller, Ó 2018 Hogrefe Publishing

5

& Staw, 2005; George & Zhou, 2002). Though the affectinnovative behavior relationship was not the focus of this study, positive mood and negative mood at work were included in the analyses to control for their potential effects on innovative behavior. These two constructs were measured with the Positive and Negative Affect Schedule (PANAS) scale (Watson, Clark, & Tellegen, 1988), which contains 10 items that are pure markers of positive mood (e.g., excited, enthusiastic, proud) and another 10 items that are pure markers of negative mood (e.g., distressed, scared, nervous). As we intended to control for the respondents’ affective states rather than their traits, we asked them to indicate how they felt at work “during the past week,” a relatively short time period. This one week time frame was suggested by Watson et al. (1988) and has been used by other researchers to assess positive and negative affective states at work (George & Zhou, 2002; Madjar, Oldham, & Pratt, 2002). Responses were coded using a Likert-type scale ranging from “very slightly or not at all” (1) to “extremely” (5).

As researchers have identified that job content and individuals’ interests and skills are significant predictors of their innovative behavior at work (Ng & Feldman, 2012), respondents’ educational level, tenure, job type (i.e., production, marketing, finance, R&D, administration, other), position (i.e., staff, low-level manager, middle-level manager, senior manager), and industry (i.e., financial, education, service, manufacturing, other) were measured for inclusion as controls in the analyses. Additionally, age and gender were included to control for their potential effect on innovative behavior (Conti, Collins, & Picariello, 2001; Moneta et al., 2010; Ng & Feldman, 2013).

Data Analysis To check for construct independence, we conducted confirmatory factor analysis (CFA) of the measurement model containing the abovementioned factors (openness to experience, innovative climate, job complexity, innovative behavior), with appropriate items loading only on their respective factors. As is typical in CFA, the chi-square associated with the model was significant (w2/df = 1,538.284/517, p < .01), indicating a poor fit (Boomsma, 2000). However, the values of other fit indices (RMSEA = .066, CFI = .929, TLI = .914) were all within the recommended ranges suggested by the literature (Kline, 2011). Based on the results, we concluded that the measurement model represented constructs that are distinguishable not only conceptually but also empirically.

Common method variance (CMV) might be an issue in the current study because of its use of single-source, self-report measures. To check for the influence of CMV, we followed Podsakoff et al.’s (2003) suggestion and performed CFA Journal of Personnel Psychology (2018), 17(1), 1–11

6

H. H. Park et al., Interaction Between Openness to Experience, Innovative Climate, and Job Complexity

Table 1. Descriptive statistics and correlations among the study variables Variable

M

SD

1

2

3

4

5

6

7

8

1. Age

1.900

0.955

2. Education

2.810

0.782

.104

3. Tenure

2.600

1.049

.672**

4. Positive mood

2.858

0.734

.077

.048

.037

5. Negative mood

2.081

0.795

.141*

.040

.153**

.323**

6. Openness to experience

3.292

0.466

.020

.056

.029

.386**

.143*

(.738)

7. Innovative climate

3.617

0.729

.022

.064

.076

.403**

.025

.239**

(.814)

8. Job complexity

3.370

0.653

.054

.133*

.059

.272**

.021

.463**

.274**

(.630)

9. Innovative behavior

3.508

0.655

.006

.008

.036

.446**

.038

.526**

.529**

.408**

9

.009 (.889) (.913)

(.873)

Notes. n = 308; reliability coefficients in parentheses. Among the control variables, only the continuous variables are included in Table 1. Others – gender, job type, position, and industry – were recoded as dummy variables. *p < .05; **p < .01.

by adding a latent CMV factor to the CFA model reported above. Specifically, after allowing items to load on a latent CMV factor as well as on their theoretical construct, we compared the model with a CMV factor to the original CFA model without one. Any remarkable changes in the significance of the results would suggest the influence of CMV. The analysis revealed that the CFA model with a CMV factor had an acceptable fit (w2/df = 1,395.533/483, p < .01; RMSEA = .059, CFI = .952, TLI = .932). Even though the CFA model with a CMV factor had a better fit than the original CFA model without a CMV factor (Δw2/df = 142.751/34, p < .01), this improvement in fit was not surprising given that the CFA model with a CMV factor specified more parameters and had fewer degrees of freedom than the original model. We found that specifying a CMV factor underlying all items did not change the patterns of the findings from those observed in the original CFA model without a CMV factor. All the factor loadings in the CFA model were statistically significant and in the expected directions, even when we controlled for the influence of a CMV factor. Thus, despite the use of self-reports, CMV did not appear to be a major threat to the internal validity of the study. Furthermore, based on an extensive Monte Carlo study, Evans (1985) concluded that method variance may inflate the magnitude of the linear effects but will not create artifactual interactions. Given that we are primarily concerned with interaction effects among variables, CMV may not be a serious issue in the current study.

The means, standard deviations, and intercorrelations of the variables, including the control variables measured as continuous variables, are presented in Table 1. To detect the presence of multicollinearity, we conducted the variance inflation factor (VIF) test that measures the inflation of variances of the estimated regression coefficients when the independent variables are linearly related. In the current study, the VIF values ranged from 1.006 to 1.273, indicating that multicollinearity was not a problem in the Journal of Personnel Psychology (2018), 17(1), 1–11

regression models given that a rule of thumb states that there is evidence of multicollinearity if VIF > 10. Additionally, to reduce possible problems associated with multicollinearity and to make the interaction term more directly interpretable, we standardized the predictors and the moderators (Aiken & West, 1991) before conducting hierarchical multiple regression analyses to assess the hypothesized relationships.

Results Table 2 presents the results of hierarchical regression analyses. We begin the examination of our results with the hypotheses concerning the three-way interaction, which are central to our study. Model 5 in Table 2 shows that the three-way interaction among openness to experience, innovative climate, and job complexity is significant (β = .137, p < .05). Figure 1 depicts the nature of this three-way interaction probed following the procedure outlined by Aiken and West (1991). As it shows, the high innovative climate and high job complexity group had the strongest positive relationship between openness to experience and innovative behavior (simple slope = .463). Reduced positive relationships existed for the high innovative climate and low job complexity group (simple slope = .359), the low innovative climate and low job complexity group (simple slope = .201), and the low innovative climate and high job complexity group (simple slope = .059). Thus, Hypothesis 3 was partially supported.

The two-way interaction between openness to experience and innovative climate (Hypothesis 1) and between openness to experience and job complexity (Hypothesis 2) is statistically nested within the three-way interaction; thus, their significance was rendered moot by the presence of the three-way interaction. Nevertheless, for completeness, Ó 2018 Hogrefe Publishing

H. H. Park et al., Interaction Between Openness to Experience, Innovative Climate, and Job Complexity

7

Table 2. Results of hierarchical regression analysis Innovative behavior Predictor

Model 1

Model 2

Model 3

Model 4

Model 5

Positive mood

.464**

.305**

.159**

.148**

.151**

Negative mood

.211**

.100†

.078

.068

.073

.371**

.305**

.314**

.270**

Innovative climate (IC)

.354**

.328**

.288**

Job complexity (JC)

.112*

.105*

.082

O IC

.164**

.168**

O JC

.022

.012

IC JC

.177**

.148**

Openness to experience (O)

O IC JC

.137*

R2 Overall F

.276

.374

.489

.512

.523

6.110**

9.045**

13.058**

12.353**

12.344**

.098

.116

.022

.011

45.091**

32.432**

4.275**

6.430*

ΔR2 F for ΔR

2

Notes. n = 308. Among the control variables, only positive mood and negative mood were significant in affecting innovative behavior. In the table, we omitted the insignificant variables (gender, age, education, tenure, job type, and industry, position) to save space. †p < .10; *p < .05; **p < .01.

5 4.5

Innovative Behavior

4 3.5 3 2.5 2 1.5

(1) High innovative climate, High job complexity

(3) Low innovative climate, High job complexity

(2) High innovative climate, Low job complexity

(4) Low innovative climate, Low job complexity

1 Low openness to experience

High openness to experience

Figure 1. Three-way interaction among openness to experience, innovative climate, and job complexity.

we report a significant two-way interaction between openness to experience and innovative climate (β = .164, p < .01), supporting Hypothesis 1.

Discussion Among the big five factor personality traits, conscientiousness has received much attention in the field of personnel psychology. As highly conscientious individuals Ó 2018 Hogrefe Publishing

are dependable and hardworking, they tend to take the initiative and perform well across many jobs in a variety of organizations (Barrick & Mount, 1991; Judge, Rodell, Klinger, Simon, & Crawford, 2013). On the other hand, openness to experience has been regarded as having lower correlations with performance across criteria than any of the other big five personality traits (Barrick, Mount, & Judge, 2001). However, to contribute to organizational effectiveness in today’s rapidly changing business environment, employees these days are required to perform well in dynamic task contexts striving for innovation, as opposed to stable task contexts where they are expected to pursue efficiency (Miron, Erez, & Naveh, 2004). In this sense, the potential contribution of openness to experience to organizational effectiveness needs to be examined in relation to adaptive performance (Pulakos, Arad, Donovan, & Plamondon, 2000) relevant to situations that require ongoing changes and innovation. This study is an attempt to examine whether those with higher openness to experience are more likely to undertake innovative behavior, a facet of adaptive performance, and under which conditions they are more likely to do so.

Theoretical and Practical Implications The findings of this study confirm the positive linkage between openness to experience and innovative behavior.

Further, the association between openness to experience and innovative behavior changes in strength depending on the combined impact of innovative climate and job complexity. Individuals high in openness to experience can be most innovative when working in a highly innovative Journal of Personnel Psychology (2018), 17(1), 1–11

8

H. H. Park et al., Interaction Between Openness to Experience, Innovative Climate, and Job Complexity

climate and performing a complex job. They can also be innovative even when their job is less complex as long as they are working in a highly innovative climate. In this situation, open people may find ways to be innovative on the job.

On the other hand, the relationship between openness to experience and innovative behavior is the smallest when innovative climate is low and job complexity is high. That is, when required to perform a complex job in a work context not supportive of innovation, open individuals tend not to be more innovative than those who are less open to experience. While this finding is not in line with our expectation, it agrees with the proposition by Bakker and Demerouti (2007). According to them, when job resources are low, individuals’ motivation is lower when job demands are high than when job demands are low, as job demands evoke individuals’ stress and anxiety who are working in the already demanding situation. In a similar vein, the change that openness to experience made to innovative behavior was smaller under the condition of low innovative climate and high job complexity than the condition of low innovative climate and low job complexity.

Contemporary organizations need employees working at all levels and performing various types of jobs to be innovative. Even those whose jobs have not traditionally required them to be innovative are now expected to be. Therefore, organizations try to hire individuals who have the potential to be innovative at work. In this respect, hiring practices focusing on conscientiousness, known to correlate with performance across almost all job categories, may have unintended consequences of decreasing the potential for innovation in the organization (e.g., Feist, 1998; King et al., 1996; Wolfradt & Pretz, 2001). On the other hand, as well established in the literature and confirmed by this study, hiring those with a high level of openness to experience may contribute to fostering innovation within the organization.

This study further suggests that additional actions need to be taken to let innovative behaviors flourish in the organization. The organization needs changes in its attributes such that they can be supportive of innovation. As the findings show, the organization can expect employees to be most innovative when it has an innovative climate and designs the job to be multifaceted and to require flexibility and experimentation. More importantly, it is pointless to hire individuals high in openness to experience if the organization then assigns them complex jobs without providing support for innovation. The organization needs to provide them with proper resources together with complex jobs. Specifically, the organization needs to pay more attention to policies and procedures to encourage innovative behaviors and patterns of interpersonal interaction supportive of innovation (Patterson et al., 2005), if it intends to encourage individuals

Journal of Personnel Psychology (2018), 17(1), 1–11

with creative potential to undertake innovative behaviors at work. When individuals recognize and appreciate the provision of these resources supporting their innovative behaviors, it may produce a felt obligation to help the organization achieve its goal to become innovative (Rhoades & Eisenberger, 2002), as well as activating their traits relevant to innovative behavior, as discussed in this study.

Study Limitations and Suggestions for Future Research This study is not without limitations. First, despite our justification for using self-reported measures of innovative behavior based on the literature (Axtell et al., 2000; Janssen, 2000, 2004; Moneta et al., 2010; Ng & Feldman, 2012; Shalley et al., 2009), the use of self-reports to measure innovative behavior might have lowered the validity of the study. Future studies employing innovative behavior data gathered from not only the individuals themselves but other sources as well will provide valuable insight into the topic itself as well as into the measurement issue of creativity and innovation at the individual level within organizations. Second, based on the literature (Axtell et al., 2000; Ng & Feldman, 2010, 2013; Ng et al., 2010), we defined the dependent variable of the current study, innovative behavior, as employees’ behaviors in generating new ideas, disseminating their and others’ new ideas, and implementing those ideas themselves or helping others to do so.

However, we failed to differentiate the stages of innovative behavior (e.g., idea generation stage, implementation stage) and to clearly define its nature (e.g., incremental innovation, radical innovation). This poses a limitation to the current study given that personality traits have differential effects on different stages of innovation, on the diverse performance outcomes (Miron et al., 2004), and on the nature of tasks involved in the innovation (Reilly, Lynn, & Aronson, 2002). Future studies need to elaborate the nature of innovative behavior to better examine the research questions raised by the current study.

Another limitation in this study is related to the use of cross-sectional research design. The current study did not address changes in each of the variables over the period and, thus, could not make an argument concerning the causal relationships among the variables. Future studies need to address the dynamic relationship by collecting data over a period of time, thereby better handling the issue of reverse causality. By conducting longitudinal studies, researchers will be able to accomplish theoretical and empirical refinement of how individuals’ characteristics and the work environment interact with each other to predict their innovative behavior at work.

Ó 2018 Hogrefe Publishing

H. H. Park et al., Interaction Between Openness to Experience, Innovative Climate, and Job Complexity

Summary and Conclusion Despite the abovementioned limitations, this study suggests the potential contributions that individuals high in openness to experience make to the organization and the conditions in which they can realize and demonstrate the potential to be innovative. Undoubtedly, organizational success hinges on individual members’ innovative behavior. While previous studies have affirmed the relationships between certain individuals’ personality traits and innovative behavior at work, much has to be investigated concerning the conditions that affect the relationships. The current study contributes to the field by expanding our understanding of how the work climate and the nature of a job jointly influence individuals’ innovative behavior at work.

References Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage.

Amabile, T. M., Barsade, S. G., Mueller, J. S., & Staw, B. M. (2005).

Affect and creativity at work. Administrative Science Quarterly, 50, 367–403. https://doi.org/10.2189/asqu.2005.

50.3.367 Anderson, N., Potočnik, K., & Zhou, J. (2014). Innovation and creativity in organizations. Journal of Management, 40, 1297–1333. https://doi.org/10.1177/0149206314527128 Axtell, C. M., Holman, D. J., Unsworth, K. L., Wall, T. D., Waterson, P. E., & Harrington, E. (2000). Shopfloor innovation: Facilitating the suggestion and implementation of ideas. Journal of Occupational and Organizational Psychology, 73, 265–285. https://doi.org/10.1348/096317900167029 Bakker, A. B., & Demerouti, E. (2007). The job demands-resources model: State of the art. Journal of Managerial Psychology, 22, 309–328. https://doi.org/10.1108/02683940710733115 Bakker, A. B., Demerouti, E., & Euwema, M. C. (2005). Job resources buffer the impact of job demands on burnout.

Journal of Occupational Health Psychology, 10, 170–180. https://doi.org/10.1037/1076-8998.10.2.170 Bakker, A. B., Demerouti, E., & Schaufeli, W. B. (2003). Dual processes at work in a call centre: An application of the job demands – resources model. European Journal of Work and Organizational Psychology, 12, 393–417. https://doi.org/ 10.1080/13594320344000165 Bakker, A. B., Demerouti, E., & Schaufeli, W. B. (2005). The crossover of burnout and work engagement among working couples. Human Relations, 58, 661–689. https://doi.org/ 10.1177/0018726705055967 Bakker, A. B., Hakanen, J. J., Demerouti, E., & Xanthopoulou, D. (2007). Job resources boost work engagement, particularly when job demands are high. Journal of Educational Psychology, 99, 274–284. https://doi.org/10.1037/0022-0663.99.2.274 Barrick, M. R., & Mount, M. K. (1991). The big five personality dimensions and job performance: A meta-analysis. Personnel Psychology, 44, 1–26. https://doi.org/10.1111/j.1744-6570.

1991.tb00688.x Barrick, M. R., Mount, M. K., & Judge, T. A. (2001). Personality and performance at the beginning of the new millennium: What do we know and where do we go next? International Journal of Selection and Assessment, 9, 9–30. https://doi.org/10.1111/ 1468-2389.00160

Ó 2018 Hogrefe Publishing

9

Billings, D. W., Folkman, S., Acree, M., & Moskowitz, J. T. (2000).

Coping and physical health during caregiving: The roles of positive and negative affect. Journal of Personality and Social Psychology, 79, 131–142. https://doi.org/10.1037/0022-3514.

79.1.131 Bipp, T. (2010). What do people want from their jobs? The big five, core self-evaluations and work motivation. International Journal of Selection and Assessment, 18, 28–39. https://doi.org/ 10.1111/j.1468-2389.2010.00486.x Bock, G. W., Zmud, R. W., Kim, Y. G., & Lee, J. N. (2005).

Behavioral intention formation in knowledge sharing: Examining the roles of extrinsic motivators, social-psychological forces, and organizational climate. MIS Quarterly, 29, 87–111.

Boomsma, A. (2000). Reporting analyses of covariance structures.

Structural Equation Modeling, 7, 461–483. https://doi.org/ 10.1207/S15328007SEM0703_6 Conti, R., Collins, M. A., & Picariello, M. L. (2001). The impact of competition on intrinsic motivation and creativity: Considering gender, gender segregation and gender role orientation.

Personality and Individual Differences, 31, 1273–1289. https:// doi.org/10.1016/S0191-8869(00)00217-8 Costa, P. T., McCrae, R. R., & Dye, D. A. (1991). Facet scales for agreeableness and conscientiousness: A revision of the NEO personality inventory. Personality and Individual Differences, 12, 887–898. https://doi.org/10.1016/0191-8869(91)90177-D Demerouti, E., Bakker, A. B., Nachreiner, F., & Schaufeli, W. B. (2001). The job demands-resources model of burnout. Journal of Applied Psychology, 86, 499–512. https://doi.org/10.1037/ 0021-9010.86.3.499 Evans, M. G. (1985). A Monte Carlo study of the effects of correlated method variance in moderated multiple regression analysis. Organizational Behavior and Human Decision Processes, 36, 305–323. https://doi.org/10.1016/0749-5978 (85)90002-0 Farmer, S. M., Tierney, P., & Kung-McIntyre, K. (2003). Employee creativity in Taiwan: An application of role identity theory.

Academy of Management Journal, 46, 618–630. https://doi.org/ 10.2307/30040653 Feist, G. J. (1998). A meta-analysis of personality in scientific and artistic creativity. Personality and Social Psychology Review, 2, 290–309. https://doi.org/10.1207/s15327957pspr0204_5 Furnham, A., & Bachtiar, V. (2008). Personality and intelligence as predictors of creativity. Personality and Individual Differences, 45, 613–617. https://doi.org/10.1016/j.paid.2008.06.023 George, J. M., & Zhou, J. (2001). When openness to experience and conscientiousness are related to creative behavior: An interactional approach. Journal of Applied Psychology, 86, 513–524. https://doi.org/10.1037/0021-9010.86.3.513 George, J. M., & Zhou, J. (2002). Understanding when bad moods foster creativity and good ones don’t: The role of context and clarity of feelings. Journal of Applied Psychology, 87, 687–697. https://doi.org/10.1037/0021-9010.87.4.687 Goldberg, L. R. (1992). The development of markers for the bigfive factor structure. Psychological Assessment, 4, 26–42. https://doi.org/10.1037/1040-3590.4.1.26 Hackman, J. R., & Oldham, G. R. (1980). Work redesign. Reading, MA: Addison-Wesley.

Hatcher, L., Ross, T. L., & Collins, D. (1989). Prosocial behavior, job complexity, and suggestion contribution under gainsharing plans. The Journal of Applied Behavioral Science, 25, 231–248. https://doi.org/10.1177/0021886389253002 Hirst, G., Van Knippenberg, D., & Zhou, J. (2009). A cross-level perspective on employee creativity: Goal orientation, team learning behavior, and individual creativity. Academy of Management Journal, 52, 280–293. https://doi.org/10.5465/ AMJ.2009.37308035

Journal of Personnel Psychology (2018), 17(1), 1–11

10

H. H. Park et al., Interaction Between Openness to Experience, Innovative Climate, and Job Complexity

Janssen, O. (2000). Job demands, perceptions of effort-reward fairness and innovative work behaviour. Journal of Occupational and Organizational Psychology, 73, 287–302. https://doi.org/ 10.1348/096317900167038 Janssen, O. (2004). How fairness perceptions make innovative behavior more or less stressful. Journal of Organizational Behavior, 25, 201–215. https://doi.org/10.1002/job.238 Judge, T. A., Bono, J. E., & Locke, E. A. (2000). Personality and job satisfaction: The mediating role of job characteristics. Journal of Applied Psychology, 85, 237–249. https://doi.org/10.1037/ 0021-9010.85.2.237 Judge, T. A., Rodell, J. B., Klinger, R. L., Simon, L. S., & Crawford, E. R. (2013). Hierarchical representations of the five-factor model of personality in predicting job performance: Integrating three organizing frameworks with two theoretical perspectives.

Journal of Applied Psychology, 98, 875–925. https://doi.org/ 10.1037/a0033901 King, L. A., Walker, L. M., & Broyles, S. J. (1996). Creativity and the five-factor model. Journal of Research in Personality, 30, 189–203. https://doi.org/10.1006/jrpe.1996.0013 Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York, NY: Guilford Press.

Kristof-Brown, A. L., Zimmerman, R. D., & Johnson, E. C. (2005).

Consequences of individuals’ fit at work: A meta-analysis of person-job, person-organization, person-group, and personsupervisor fit. Personnel Psychology, 58, 281–342. https://doi. org/10.1111/j.1744-6570.2005.00672.x Le, H., Oh, I. S., Robbins, S. B., Ilies, R., Holland, E., & Westrick, P. (2011). Too much of a good thing: Curvilinear relationships between personality traits and job performance. Journal of Applied Psychology, 96, 113–133. https://doi.org/10.1037/ a0021016 LePine, J. A., Colquitt, J. A., & Erez, A. (2000). Adaptability to changing task contexts: Effects of general cognitive ability, conscientiousness, and openness to experience. Personnel Psychology, 53, 563–593. https://doi.org/10.1111/j.17446570.2000.tb00214.x Li, Z., Zhu, T., & Luo, F. (2010). A study on the influence of organizational climate on knowledge-sharing behavior in IT enterprises. Journal of Computers, 5, 508–515. https://doi.org/ 10.4304/jcp.5.4.508-515 Loher, B. T., Noe, R. A., Moeller, N. L., & Fitzgerald, M. P. (1985). A meta-analysis of the relation of job characteristics to job satisfaction. Journal of Applied Psychology, 70, 280–289. https://doi.org/10.1037/0021-9010.70.2.280 Madjar, N., Oldham, G. R., & Pratt, M. G. (2002). There’s no place like home? The contributions of work and nonwork creativity support to employees’ creative performance. Academy of Management Journal, 45, 757–767. https://doi.org/10.2307/3069309 McCrae, R. R. (1987). Creativity, divergent thinking, and openness to experience. Journal of Personality and Social Psychology, 52, 1258–1265. https://doi.org/10.1037/0022-3514.52.6.1258 Miron, E., Erez, M., & Naveh, E. (2004). Do personal characteristics and cultural values that promote innovation, quality, and efficiency compete or complement each other? Journal of Organizational Behavior, 25, 175–199. https://doi.org/10.1002/ job.237 Moneta, G. B., Amabile, T. M., Schatzel, E. A., & Kramer, S. J. (2010). Multirater assessment of creative contributions to team projects in organizations. European Journal of Work and Organizational Psychology, 19, 150–176. https://doi.org/ 10.1080/13594320902815312 Muchinsky, P. M., & Monahan, C. J. (1987). What is personenvironment congruence? Supplementary versus complementary models of fit. Journal of Vocational Behavior, 31, 268–277. https://doi.org/10.1016/0001-8791(87)90043-1

Journal of Personnel Psychology (2018), 17(1), 1–11

Ng, T. W., & Feldman, D. C. (2010). The impact of job embeddedness on innovation-related behaviors. Human Resource Management, 49, 1067–1087. https://doi.org/10.1002/hrm.20390 Ng, T. W., & Feldman, D. C. (2012). A comparison of selfratings and non-self-report measures of employee creativity.

Human Relations, 65, 1021–1047. https://doi.org/10.1177/ 0018726712446015 Ng, T. W., & Feldman, D. C. (2013). Age and innovation-related behavior: The joint moderating effects of supervisor undermining and proactive personality. Journal of Organizational Behavior, 34, 583–606. https://doi.org/10.1002/job.1802 Ng, T. W., Feldman, D. C., & Lam, S. S. (2010). Psychological contract breaches, organizational commitment, and innovation-related behaviors: A latent growth modeling approach.

Journal of Applied Psychology, 95, 744–751. https://doi.org/ 10.1037/a0018804 Oldham, G. R., & Cummings, A. (1996). Employee creativity: Personal and contextual factors at work. Academy of Management Journal, 39, 607–634. https://doi.org/10.2307/256657 Patterson, M. G., West, M. A., Shackleton, V. J., Dawson, J. F., Lawthom, R., Maitlis, S., . . . Wallace, A. M. (2005). Validating the organizational climate measure: Links to managerial practices, productivity and innovation. Journal of Organizational Behavior, 26, 379–408. https://doi.org/10.1002/job.312 Pervin, L. A. (1968). Performance and satisfaction as a function of individual-environment fit. Psychological Bulletin, 69, 56–68. https://doi.org/10.1037/h0025271 Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies.

Journal of Applied Psychology, 88, 879–903. https://doi.org/ 10.1037/0021-9010.88.5.879 Pulakos, E. D., Arad, S., Donovan, M. A., & Plamondon, K. E. (2000). Adaptability in the workplace: Development of a taxonomy of adaptive performance. Journal of Applied Psychology, 85, 612–624. https://doi.org/10.1037/0021-9010.85.4.612 Raja, U., & Johns, G. (2010). The joint effects of personality and job scope on in-role performance, citizenship behaviors, and creativity. Human Relations, 63, 981–1005. https://doi.org/ 10.1177/0018726709349863 Reichers, A. E., & Schneider, B. (1990). Climate and culture: An evolution of constructs. In B. Schneider (Ed.), Organizational climate and culture (pp. 5–39). San Francisco, CA: Jossey-Bass.

Reilly, R. R., Lynn, G. S., & Aronson, Z. H. (2002). The role of personality in new product development team performance.

Journal of Engineering and Technology Management, 19, 39–58. https://doi.org/10.1016/S0923-4748(01)00045-5 Rhoades, L., & Eisenberger, R. (2002). Perceived organizational support: A review of the literature. Journal of Applied Psychology, 87, 698–714. https://doi.org/10.1037/0021-9010.87.4.698 Salgado, J. F. (1997). The five factor model of personality and job performance in the European community. Journal of Applied Psychology, 82, 30–43. https://doi.org/10.1037/0021-9010.82.

1.30 Scott, S. G., & Bruce, R. A. (1994). Determinants of innovative behavior: A path model of individual innovation in the workplace. Academy of Management Journal, 37, 580–607. https:// doi.org/10.2307/256701 Scratchley, L. S., & Hakstian, A. R. (2000). The measurement and prediction of managerial creativity. Creativity Research Journal, 13, 367–384. https://doi.org/10.1207/S15326934CRJ1334_14 Shalley, C. E., Gilson, L. L., & Blum, T. C. (2009). Interactive effects of growth need strength, work context, and job complexity on self-reported creative performance. Academy of Management Journal, 52, 489–505. https://doi.org/10.5465/AMJ.2009.

41330806

Ó 2018 Hogrefe Publishing

H. H. Park et al., Interaction Between Openness to Experience, Innovative Climate, and Job Complexity

Shalley, C. E., Zhou, J., & Oldham, G. R. (2004). The effects of personal and contextual characteristics on creativity: Where should we go from here? Journal of Management, 30, 933–958. https://doi.org/10.1016/j.jm.2004.06.007 Silvia, P. J., Nusbaum, E. C., Berg, C., Martin, C., & O’Connor, A. (2009). Openness to experience, plasticity, and creativity: Exploring lower-order, high-order, and interactive effects.

Journal of Research in Personality, 43, 1087–1090. https:// doi.org/10.1016/j.jrp.2009.04.015 Sung, S. Y., & Choi, J. N. (2009). Do big five personality factors affect individual creativity? The moderating role of extrinsic motivation. Social Behavior and Personality: An International Journal, 37, 941–956. https://doi.org/10.2224/sbp.2009.37.

7.941 Tett, R. P., & Burnett, D. D. (2003). A personality trait-based interactionist model of job performance. Journal of Applied Psychology, 88, 500–517. https://doi.org/10.1037/0021-9010.

88.3.500 Tett, R. P., & Guterman, H. A. (2000). Situation trait relevance, trait expression, and cross-situational consistency: Testing a principle of trait activation. Journal of Research in Personality, 34, 397–423. https://doi.org/10.1006/jrpe.2000.2292 Tierney, P., & Farmer, S. M. (2002). Creative self-efficacy: Its potential antecedents and relationship to creative performance. Academy of Management Journal, 45, 1137–1148. https://doi.org/10.2307/3069429 Tierney, P., & Farmer, S. M. (2004). The Pygmalion process and employee creativity. Journal of Management, 30, 413–432. https://doi.org/10.1016/j.jm.2002.12.001 Van den Broeck, A., De Cuyper, N., De Witte, H., & Vansteenkiste, M. (2010). Not all job demands are equal: Differentiating job hindrances and job challenges in the job demands-resources model. European Journal of Work and Organizational Psychology, 19, 735–759. https://doi.org/ 10.1080/13594320903223839 Van Vianen, A. E. (2000). Person-organization fit: The match between newcomers’ and recruiters’ preferences for organizational cultures. Personnel Psychology, 53, 113–149. https://doi. org/10.1111/j.1744-6570.2000.tb00196.x

Ó 2018 Hogrefe Publishing

11

Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 Wolfradt, U., & Pretz, J. E. (2001). Individual differences in creativity: Personality, story writing, and hobbies. European Journal of Personality, 15, 297–310. https://doi.org/10.1002/ per.409 Xanthopoulou, D., Bakker, A. B., Demerouti, E., & Schaufeli, W. B. (2007). The role of personal resources in the job demandsresources model. International Journal of Stress Management, 14, 121–141. https://doi.org/10.1037/1072-5245.14.2.121 Yuan, F., & Woodman, R. W. (2010). Innovative behavior in the workplace: The role of performance and image outcome expectations. Academy of Management Journal, 53, 323–342. https://doi.org/10.5465/AMJ.2010.49388995 Zheng, L., Goldberg, L. R., Zheng, Y., Zhao, Y., Tang, Y., & Liu, L. (2008). Reliability and concurrent validation of the IPIP big-five factor markers in China: Consistencies in factor structure between Internet-obtained heterosexual and homosexual samples. Personality and Individual Differences, 45, 649–654. https://doi.org/10.1016/j.paid.2008.07.009 Zhou, J., & Oldham, G. R. (2001). Enhancing creative performance: Effects of expected developmental assessment strategies and creative personality. The Journal of Creative Behavior, 35, 151–167. https://doi.org/10.1002/j.2162-6057.2001.tb01044.x Received February 9, 2016 Revision received May 2, 2017 Accepted May 17, 2017 Published online January 3, 2018 Myungweon Choi Department of Business Administration Ajou University 206 Worldcup-ro Yeongtong-gu Suwon 16499 South Korea mwchoi@ajou.ac.kr

Journal of Personnel Psychology (2018), 17(1), 1–11

Original Article

Practical Considerations for Conducting Job Analysis Linkage Exercises Erika J. Robinson-Morral,1 Cheryl Hendrickson,1 Sarah Gilbert,2 Tara Myers,3 Kaila Simpson,1 and Andrew C. Loignon4 1

Workforce Development and Human Capital, American Institutes for Research, Washington, DC, USA

2

Personnel Selection and Litigation Support Services, DCI Consulting, Washington, DC, USA

3

Measurement Services, American Nurses Credentialing Center, Silver Spring, MD, USA

4

People and Organizations, NEOMA Business School, Reims, France

Abstract: To follow best practices in creating selection tools, an important phase in job analysis is gathering linkage ratings between knowledge, skills, abilities, and other characteristics (KSAOs) and job tasks. However, the literature provides little guidance on best practices for collecting linkage ratings. Two studies were conducted to contribute to the limited research. Study 1 examined the interrater agreement of different types of raters: job incumbents, managers, or job analysts. Results revealed that job analysts have the highest interrater agreement.

Study 2 examined the impact of a frame-of-reference (FOR) training for raters. Results suggested that a brief consensus training session vastly improved agreement among raters. These studies provide more guidance on best practices for obtaining high-quality linkage ratings.

Keywords: job analysis, linkage exercises, rating reliability, interrater agreement

Despite ongoing interest in job analysis and some research attention being given to the general topic of job analysis (e.g., Bobko, Roth, & Buster, 2004; Dierdorff & Morgeson, 2009; Morgeson, Delaney-Klinger, Mayfield, Ferrara, & Campion, 2004), there have been few publications about best practices for conducting a critical step in traditional job analysis methodology: linking requisite knowledge, skills, abilities, and other characteristics (KSAOs) to job tasks (Baranowski & Anderson, 2005; Hughes & Prien, 1989; Vinchur, Prien, & Schippman, 1993). KSAO-task linkage ratings require raters to indicate the extent to which each KSAO is related to each job task (Baranowski & Anderson, 2005). These linkages are considered best practices in job analysis, are recommended for many human capital initiatives (e.g., selection, certification; SIOP, 2003), and reflect some legal requirements (e.g., the US Equal Employment Opportunity Commission, 1978) because they help establish the job-relatedness of specific KSAOs. A 2012 survey of practitioners regarding approaches used for collecting, analyzing, and leveraging linkages further substantiates the lack of clear guidance in the literature (Gilbert, Loignon, Hendrickson, & Myers, 2012). Survey Journal of Personnel Psychology (2018), 17(1), 12–21 https://doi.org/10.1027/1866-5888/a000191

results revealed that, despite recognizing their importance, practitioners reported including linkage exercises in only about half of their job analyses. Respondents often cited challenges such as the time required to complete the exercises, limited access to an appropriate number of raters, the cognitive demand of the task, and the poor quality data that often results from the process. Survey results also suggested there is much variability in the methodologies employed, such as the rating scales used (e.g., dichotomous, 3- or 5-point scales), criteria for defining a “link” between a task and a KSAO, and the types of raters who are most appropriate to make the linkages (e.g., job incumbents, managers, job analysts). Further, existing publications focus on determining which types of raters and rating scales are best (Baranowski & Anderson, 2005; Hughes & Prien, 1989; Myers et al., 2011; Vinchur et al., 1993).

The purpose of the current research is to provide practitioners with more guidance around best practices in gathering linkage ratings. Specifically, the current research sought to empirically examine different methods for collecting KSAO-task linkages. Study 1 examined which type of rater (i.e., incumbents, managers, or job analysts) provides the best interrater agreement for linkage ratings. Study 2 Ó 2018 Hogrefe Publishing

E. J. Robinson-Morral et al., Job Analysis Linkage Exercises

explored methods for further increasing the interrater agreement among raters by examining two methods for collecting linkage ratings (i.e., consensus vs. independent ratings).

Study 1: Linkage Ratings Provided

by Different Rater Types Study 1 expands on existing research by comparing interrater agreement on KSAO-task linkage ratings for three types of raters: incumbents, managers, and job analysts. Findings that suggest a particular type of rater provides more reliable linkage data than another may help job analysts collect higher quality data. In particular, results that support previous findings, described below, that job analysts provide equally or more reliable linkage data than do job experts (i.e., incumbents and managers) could offer important flexibility for data collection.

Literature Review on Sources of KSAO-Task Linkage Ratings The few existing publications on KSAO-task linkages focus on determining whether job analysts or job experts are most appropriate for completing the ratings. However, this research does not distinguish between the type of job expert – incumbents and managers.

Typically, linkage ratings are completed by job experts because they perform (or observe) the work on a daily basis and are most familiar with the work activities and job requirements (Aamodt, 2007). Harvey and Wilson (2000) argued, however, that it is naïve to trust that job experts will provide accurate and reliable data when there are no accountability practices in place. In fact, job experts (particularly incumbents) may be motivated to provide inaccurate ratings if they perceive positive outcomes will result from these inaccuracies (Morgeson & Campion, 1997). Additionally, it can often be difficult to access a large sample of job experts for the length of time typically required of linkage exercises. The costs and scheduling constraints that arise when using job experts make this practice prohibitively expensive for many organizations (Gilbert et al., 2012).

Based on these considerations, some argue that job analysts may be more appropriate raters (Baranowski & Anderson, 2005). In addition to providing an objective perspective, job analysts have more experience studying jobs in terms of tasks and KSAOs, often perform this type of cognitively taxing task, and are more likely to have the time required for completing linkage ratings. Two main

Ó 2018 Hogrefe Publishing

13

studies provide preliminary support for the use of job analysts as raters.

Job Analysts Versus Job Experts Vinchur et al. (1993) examined whether using job analysts or job experts would impact linkage ratings across three separate samples (i.e., bank tellers, firefighters, and semiskilled mill laborers). Results indicated that job analysts made more refined distinctions than did job experts when conducting their ratings as evidenced in the higher number of factors that could be reliably extracted from their ratings.

More recently, Baranowski and Anderson (2005) examined linkages for nine jobs from a state government agency, and compared the linkages provided by job analysts and job experts. In addition, they differentiated between job analysts familiar with the job and naïve job analysts. Results revealed that ratings from the two types of job analysts were more highly correlated than were the ratings from job experts and job analysts, and job analyst ratings evidenced higher reliability coefficients. The authors concluded that these results support the use of job analysts to complete linkage ratings regardless of their familiarity with the job being analyzed.

Incumbents Versus Managers Interestingly, the above-cited empirical research did not distinguish between the types of job expert employed: incumbents or managers. Some researchers theorize that managers may be a preferred source of ratings because they can observe multiple individuals performing the same job over an extended period of time (Baranowski & Anderson, 2005). Additionally, managers may be more objective than incumbents because they are less likely to benefit directly from inflated job analysis ratings. Lastly, managers may have more experience considering jobs in terms of duties, tasks, and KSAOs than do incumbents because of their experience with performance reviews (Morgeson & Campion, 1997). Despite these advantages, some argue that incumbents are more suitable than managers for providing job analytic data (e.g., Morgeson & Campion, 1997) because they actually perform the work on a daily basis.

Study 1 Purpose Study 1 compares interrater agreement of linkage ratings across raters (i.e., incumbents, managers, and job analysts) and in a novel career field (i.e., security). Comparing linkage ratings within this unexplored profession provides conceptual replication and extension of the findings from Vinchur et al. (1993) and Baranowski and Anderson

Journal of Personnel Psychology (2018), 17(1), 12–21

14

(2005). Furthermore, this study expands upon previous research by comparing the interrater agreement of linkage data from incumbents and managers.

Study 1 Method Participants The sample for Study 1 included 22 participants across three rater types: incumbents, managers, and job analysts.

Seven experienced job analysts (M = 8.00 years of experience; SD = 7.70) from a consulting organization who had considerable experience with the target job completed ratings. Eight managers (M = 6.55 years of experience in organization; SD = 2.02) and seven job incumbents (M = 7.65; SD = 1.10), selected based on their experience with and knowledge of the job, also completed ratings.

Materials The linkage matrix used in the current study was a subset of a linkage matrix used in a large-scale, nationwide job analysis conducted on a security-related job. Job analysts generated the task and KSAO lists for the purposes of this job analysis. The original linkage matrix consisted of 110 task statements (covering seven job duties) and 103 KSAO statements. For feasibility purposes, the subset of this matrix used in the current study was comprised of the first 28 task statements (covering three job duties) and all 103 KSAO statements. Both hardcopy and electronic versions of the matrix were used to conduct the research. A handout providing instructions for completion and the rating scale accompanied each matrix.

Procedure Job experts conducted their ratings over the course of a supervised, 2-day workshop. The workshop began with a brief introduction session wherein job experts were given an overview of the project, the purpose of the workshop, and key definitions for duties, tasks, and KSAOs. The workshop facilitator instructed job experts to read each KSAO, think about the job as it is currently performed, and complete ratings task by task. To prevent possible bias, job analysts who were familiar with the job but who did not have access to job expert linkage ratings also completed the linkage ratings. Because the job analysts were familiar with the project and the process of completing KSAO-task linkages, they did not receive formal training. As with the job experts, however, job analysts received written instructions and the rating scale information. All three groups of raters were instructed to conduct their ratings using a 3-point scale (0 = not relevant for performing the task; 1 = helpful for performing the task; 2 = essential for performing the task).

After the introduction and instructions were presented, participants generated their ratings independently.

Journal of Personnel Psychology (2018), 17(1), 12–21

E. J. Robinson-Morral et al., Job Analysis Linkage Exercises

Study 1 Results Interrater Agreement In this research, the quality of the data gathered is evaluated via interrater agreement (i.e., a measure of the extent to which individual raters assign the same value to a given target). Its use as a measure for quality is based, in part, on the fact that the subjective nature of linkage ratings makes a determination of accuracy very difficult (Fleiss, Levin, & Cho Paik, 2003).

The rwg statistic of interrater agreement (James, Demaree, & Wolf, 1984, 1993) was calculated for the incumbent, manager, and job analyst datasets. The rwg statistic is a measure of interrater agreement that accounts for chance agreement between raters by comparing the standard deviation of actual ratings to the expected standard deviation of random ratings (Dunlap, Burke, & Smith-Crowe, 2003). For the purpose of this study, Dunlap et al. (2003)’s conservative approach for evaluating the level of agreement was adopted, including their critical values for establishing the statistical significance of the rwg values (.68 [n = 8] for the managers and .78 [n = 7] for incumbents and job analysts). Then, the percentage of judgments that each group agreed upon beyond chance was calculated. Those percentages were compared using a z-test of two proportions.

Each rater made 2,884 judgments. Job analysts agreed beyond chance on 828 (28.71%) judgments, incumbents on 504 (17.48%) judgments, and managers on 571 (19.80%) judgments. Z-tests for two proportions illustrated the differences between job analysts and job experts, but also highlighted a distinction between managers and incumbents. Job analysts agreed on significantly more judgments than did incumbents (z = 10.09, p < .01). Given the large number of linkage ratings, statistical significance was likely. As such, practical significance was tested and a medium effect size was found (d = 0.49). Job analysts also agreed on significantly more judgments than did managers (z = 7.86, p < .01), which yielded a large effect (d = 0.84).

Managers agreed on significantly more judgments than did incumbents (z = 2.23, p < .05), resulting in a small effect (d = 0.42).

KSAO-Task Linkage Results One purpose for completing KSAO-task linkages is to identify the job-related KSAOs that should be included in a selection system (e.g., those that link to at least one job task and that cannot be trained upon hire). Using results from each group of raters, the researchers identified the KSAOs deemed job-related. First, KSAO-task pairings with an average rating of 1.5 (closer to “essential” rather than to the “helpful” response option on the rating scale) or more were labeled as linked. The decision for determining the Ó 2018 Hogrefe Publishing

E. J. Robinson-Morral et al., Job Analysis Linkage Exercises

15

Table 1. Number of tasks linked to each KSAO by rater group Number of tasks linked to KSAO

Number of tasks linked to KSAO

KSAO ID

Job analysts

Incumbents

Managers

KSAO ID

Job analysts

Incumbents

Managers

1

–

11

19

58

2

8

5

2

16

19

20

59

1

3

4

3

16

19

20

60

5

1

5

4

16

19

20

63

11

6

11

5

3

5

2

64

1

2

1

6

13

6

10

65

–

1

1

7

12

15

20

66

–

2

8 10

8

9

8

13

67

–

–

9

11

11

13

68

–

–

2

10

11

6

7

69

4

1

1

13

2

1

2

70

7

9

8

17

1

–

–

71

1

5

–

23

1

–

–

72

3

6

13

24

10

8

12

73

11

6

11

25

3

6

18

74

13

10

12

26

4

7

17

75

6

10

16

27

–

1

10

76

9

5

10

29

–

1

3

78

1

–

–

30

–

3

5

84

7

3

10

31

–

2

–

85

6

3

14

32

8

16

19

88

3

4

7

33

–

3

–

89

–

4

12

34

–

–

2

90

2

6

14

38

8

12

10

92

14

13

6

39

10

6

4

94

–

1

2

40

10

4

6

95

3

4

5

41

5

5

6

97

2

–

1

49

–

5

3

99

3

15

13

54

5

5

5

100

–

7

13

55

8

9

9

101

1

9

3

56

4

2

2

102

2

–

–

57

1

1

5

Total

305

360

500

Note. Table includes only the KSAOs that linked to at least one task for at least one group of raters.

link threshold is based on the purpose of the job analysis, and can vary depending on if the job analysis is for selection, training, or other initiatives. In this case, the researchers used conservative criteria for identifying links, because the legal defensibility of the job analysis was critical. After identifying links, the researchers counted the number of tasks to which each KSAO linked.

The pattern of results (i.e., the KSAOs ultimately designated as “job-related”) was mostly consistent across rater groups with a few differences. For example, a total of 10 KSAOs would not be considered linked to the job (or included in a selection system) according to the job analysts’ data, that would have been according to the job experts’ data. On the other hand, four KSAOs would be Ó 2018 Hogrefe Publishing

included based on job analysts’ data but not based on job experts’ data. There were also some differences across the two job expert groups. Specifically, three KSAOs linked to the job according to the incumbent data but not the manager data, and four tasks linked according to the manager data but not the incumbent data (see Table 1 for full results).

Study 1 Discussion The KSAO-task linkage process is a critical component of a content-validated selection instrument (SIOP, 2003).

The present study expanded the current body of research Journal of Personnel Psychology (2018), 17(1), 12–21

16

by examining the interrater agreement of linkage ratings from job incumbents, managers, and job analysts using a 3-point rating scale. Overall, job analysts agreed on significantly more ratings when compared to either manager or incumbent job experts. This may be because job analysts are able to further differentiate their ratings using the term “essential” due to their foresight in the need to prioritize particular KSAOs for various human resources solutions (e.g., selection systems, training programs) as well as their knowledge of the legal implications of the term “essential” for the development of selection systems. Further, job analysts may be able to better differentiate between terms such as knowledge, skills, and abilities, whereas managers and incumbents may not fully understand the differentiating factors between each.

Although job analysts demonstrated higher levels of agreement than did incumbents and managers, none of the groups demonstrated an exceptional level of agreement (the percentage of linkages that constituted agreement beyond chance ranged from 17% to 29%). This finding highlights the complexity of the KSAO-task linkage process and suggests there is further room for improvement in the process.

Study 2: Application of Frame-ofReference Training for Job Analysis Linkage Raters Study 1 suggested that job analysts may be a viable alternative to using job experts to gather linkage ratings, but that there is room for improvement in the interrater agreement of ratings regardless of rater type. Study 2 explores methodologies for collecting ratings in an effort to identify a method that yields more reliable ratings among raters. This study sought to empirically explore whether employing a consensus-based frame-of-reference (FOR) training before asking raters to provide their ratings independently results in higher interrater agreement than the independent rating method alone.

Consensus Versus Independent Ratings Though it has not been explored in the context of gathering KSAO-task linkages, the success of consensus ratings in other contexts suggests its possible application to job analysis methodologies. Many researchers have compared performance ratings gathered via consensus to those of independent ratings. In the consensus method, a group of raters is asked to discuss each rating before agreeing upon

Journal of Personnel Psychology (2018), 17(1), 12–21

E. J. Robinson-Morral et al., Job Analysis Linkage Exercises

a single rating that represents the combined opinion of the group. Workplace management literature suggests that, although consensus ratings may be more time-consuming to collect than independent ratings (Pynes & Bernardin, 1992), they can yield superior results due to the breadth and depth of group members’ knowledge and input (e.g., Robbins & Judge, 2013). However, the existing empirical research is equivocal.

For example, Baugher, Weisbord, and Eisner (2011) found no significant difference between consensus ratings and the averages of independent ratings of candidates for job promotions. Similarly, Pynes and Bernardin (1992) evaluated the validity of supervisor ratings and found no significant difference between the results of consensus ratings and the average of independent ratings. In contrast, Pulakos, Schmitt, Whitney, and Smith (1996) evaluated rating methods using supervisor interviewee ratings and found consensus ratings had significantly higher validity than independent ratings. Similarly, when comparing rating methods for evaluating team performance, Kirkman, Tesluk, and Rosen (2001) found that consensus ratings demonstrated incremental validity above the strict average of individual ratings. In summary, whereas consensus ratings have proven superior to independent ratings in some instances, the empirical results are mixed.

To the authors’ knowledge, the consensus method has not been explored empirically as a method for collecting KSAO-task linkage ratings. This may be because, typically, the linkage process requires a large number of ratings.

As such, it was determined for this study that it would be more practical to explore a hybrid approach that capitalizes on the benefits of the consensus method, but is more practical for gathering a large number of ratings.

The researchers hypothesized that the consensus method may lead to improvements in the linkage rating process because an “indirect” FOR training occurs while engaging in the consensus discussion of ratings. FOR training is a method for training raters to calibrate their ratings by forming a common conceptualization for evaluating material (Woehr, 1994), which can lead to improved rating accuracy (Roch, Woehr, Mishra, & Kieszczynska, 2012) and interrater agreement (Melchers, Lienhardt, Von Aarburg, & Kleinmann, 2011). To the authors’ knowledge, the use of FOR training as a method for increasing the quality of linkage ratings collected from raters has not been explored empirically.

Study 2 contributes to the limited body of research in the field of KSAO-task linkage ratings by comparing a hybrid method for collecting linkage data from job experts to the traditional independent rating method. For the purposes of this research, the hybrid method refers to an approach for gathering linkage data that includes a consensus-forming

Ó 2018 Hogrefe Publishing

E. J. Robinson-Morral et al., Job Analysis Linkage Exercises

17

Table 2. Average years of linkage participant tenure by group Tenure in years Independent #1

Independent #2

Hybrid #1

Hybrid #2

M

SD

M

SD

M

SD

M

SD

22.00

9.35

20.67

10.73

23.09

12.48

20.60

7.84

FOR training period (of varying length) before participants begin providing ratings independently. This study examines whether the consensus discussions within the hybrid method lead to better agreement among job expert raters. Further, this study compares the hybrid and independent methods using several criteria, including the resulting interrater agreement, final linkage results, and rater preference.

Study 2 Method Participants The current study included 48 health care professionals selected to participate in a linkage exercise activity due to their expertise and representativeness of the field. Tenure in the field averaged 18.75 years (SD = 11.35). Eleven different practice care settings (e.g., critical care, rehabilitation) and 29 states/US territories were represented. Each participant took part in one of four knowledge-task linkage workshops as part of a national job analysis: Hybrid 1 (n = 10), Hybrid 2 (n = 10), Independent 1 (n = 14), and Independent 2 (n = 14). Average tenure was comparable across the four workshops (see Table 2).

Materials The linkage matrices were comprised of 165 knowledge statements and 286 tasks divided into 11 duties. Job analysts, in conjunction with job experts, generated the task and knowledge lists for the purposes of the job analysis.

Both hardcopy (used in the hybrid method) and electronic (used in the independent method) versions of the matrix were used.

Procedure All participants conducted their ratings over the course of a supervised, 3-day workshop. Each workshop began with an overview of the project, the purpose of the workshop, and definitions of key terms. Participants were then briefly trained on how to conduct their ratings and received an instructional handout, which included the same 3-point scale used in Study 1 (0 = not relevant for performing the task; 1 = helpful for performing the task; 2 = essential for performing the task).

Thereafter, the workshops varied in the amount of time that was afforded to participants to calibrate and form Ó 2018 Hogrefe Publishing

consensus on their ratings (i.e., no time, 1 hr, and 2 days) before working independently to complete their ratings.

In the Hybrid 1 and 2 groups, to establish a FOR via consensus formation, participants spent time completing a subset of independent linkage ratings via hardcopy linkage matrices before discussing them aloud with the goal of reaching consensus. For the purposes of this research, consensus was defined as 70% or more of the group agreeing upon the rating for the knowledge-task pairing.

For each knowledge-task linkage pairing, participants shared their original “round 1” ratings with the group by holding up a paddle displaying their rating, discussed each pairing that did not reach 70% consensus, and then shared their final “round 2” rating that resulted from the group discussion.

In the Hybrid 1 group, participants spent two full days in the consensus-forming process before providing any individual ratings. In the Hybrid 2 group, participants spent 1 hr in the consensus-forming process before providing any individual ratings. In the Independent 1 and 2 administrations, participants did not spend any time in the consensus-forming process; they spent all 3 days completing individual ratings.

Study 2 Results Interrater Agreement Across Methods To determine if the hybrid method resulted in higher interrater agreement among raters than the independent method, the interrater agreement was calculated across the methods using the rwg statistic (James et al., 1984, 1993). For the purpose of this study, the conservative approach proposed by Dunlap et al. (2003) was used, including their critical values for the corresponding sample sizes in our linkage pairings. The analysis revealed that the hybrid groups – who engaged in the consensus-forming process before making autonomous judgments – agreed beyond chance on 46.18% of their individual ratings (i.e., ratings that were not discussed as a group), whereas the independent groups – who did not engage in the consensus-forming process – agreed beyond chance on only 17.35% of ratings. A z-test for two proportions indicated that hybrid method participants were reliable on significantly more judgments than were independent method participants (z = 95.13, p < .05). Given the large number of linkage Journal of Personnel Psychology (2018), 17(1), 12–21

18

ratings, statistical significance was likely. As such, practical significance was tested and a large effect size was found (d = 0.75), further indicating that the agreement in the hybrid method was significantly better than in the independent method. These results demonstrate that the levels of agreement were higher for the job experts who engaged in the consensus-forming process prior to autonomously providing linkage ratings.

Because the hybrid methods were not identical, the differences in agreement among the individual ratings gathered after consensus-forming discussions were also examined. Participants in the Hybrid 1 group – who engaged in the consensus-forming process for 2 days before making autonomous judgments – agreed beyond chance on 60.73% of their judgments. Participants in the Hybrid 2 group – who engaged in the consensus-forming process for 1 hr before making autonomous judgments – agreed beyond chance on 58.01% of their judgments. A z-test for two proportions indicated that the Hybrid 1 method yielded significantly more reliable ratings than the Hybrid 2 method (z = 5.86, p < .05). The practical effect size was small (d = 0.35), supporting the finding that the agreement ratings from the Hybrid 1 method – which involved a significantly longer consensus-forming process – was better than the Hybrid 2 method, albeit marginally.

Knowledge-Task Linkage Results As in Study 1, it was important to examine any differences between the results of each method in terms of the final KSAOs that would be validated for inclusion in a selection system (e.g., those that link to at least one job task). To do so, the same cut-off (i.e., 1.5, half way between “helpful” and “essential”) was applied such that knowledge-task pairings with an average rating of greater than 1.5 were considered linked (i.e., job-related). Job-related knowledge statements (i.e., those that linked to at least one task) were identified and compared across methods.

Of the 165 knowledge statements, 85.45% were validated by both the hybrid and independent groups. However, some differences existed as a result of methodology.

Specifically, the hybrid results did not validate 24 statements (14.55%), whereas the independent results did not validate five of those statements (3.03%). See Table 3 for full results.

Study 2 Discussion Study 2 expanded the current body of research on KSAOtask linkages by examining the quality of knowledgetask linkage ratings for two data collection approaches: (1) hybrid ratings and (2) independent ratings. There were several important findings. First, within the hybrid method, Journal of Personnel Psychology (2018), 17(1), 12–21

E. J. Robinson-Morral et al., Job Analysis Linkage Exercises

participants were more likely to reach the 70% consensus agreement threshold after discussing their ratings aloud, likely because the discussion helped participants to better understand the linkage exercise activity, rating scale, and list of knowledge and tasks. Furthermore, though consensus formation may not always be practical due to time constraints, the comparison of interrater agreement across the two methods suggests that there is value in allowing participants to discuss their judgments and create a FOR rather than simply taking the average of independent ratings.

Results also revealed that participants who engaged in the consensus-forming process agreed beyond chance on nearly 30% more pairings than did the independent group (46.18% and 17.35%, respectively). This suggests that the consensus discussion is not only valuable for reaching consensus, but also serves as an important exercise for clarifying instructions and aligning raters’ FOR completing independent linkages. Although there were significant differences in interrater agreement as a function of consensus-forming length (i.e., 2 days vs. 1 hr), it is noteworthy that the difference in percentage of linkage ratings that met the agreement threshold was only 2.72% between Hybrid 1 and Hybrid 2. This difference is marginal, especially when compared to the nearly 30% difference in agreement between the overall hybrid group and the independent group. When practical concerns such as time constraints of the workshop are introduced, this finding suggests that it is worth spending time, even if it is minimal, to allow raters to review and discuss some linkages before asking them to provide ratings independently.

Because the purpose of completing knowledge-task linkages is often to determine the requirements of the job, which can inform important human capital initiatives such as the development of test specifications for certification or selection tests, it was important to examine the difference in the final list of job-relevant knowledge statements across the two methods. Using our criteria for determining inclusion on the final knowledge list (i.e., knowledge links to at least one task), the hybrid method resulted in far fewer knowledge-task linkages and a shorter list of knowledge than the independent group. In other words, the hybrid participants were less likely to rate a knowledge as required for a task than were independent participants. The practical application of this finding is that the consensus-forming process used in the hybrid method can affect the final list of validated job requirements. In the case of KSAO-task linkage ratings, it may be preferred to have a false negative (i.e., removing a knowledge from the list that should be retained) than a false positive (i.e., retaining a knowledge on the list that should be removed), depending on the purpose of the job analysis (e.g., training, certification, selection). Ó 2018 Hogrefe Publishing

E. J. Robinson-Morral et al., Job Analysis Linkage Exercises

19

Table 3. Hybrid versus independent: number of links to job tasks Number of tasks linked to KSAOs Knowledge ID#

Hybrid group

Independent group

Knowledge ID#

Hybrid group

Independent group

Knowledge ID#

Hybrid group

Independent group

1

0

8

56

0

8

111

4

25

2

12

31

57

1

9

112

14

27

3

2

3

58

2

7

113

1

8

4

4

13

59

2

8

114

24

33

5

30

42

60

0

3

115

22

37

6

14

30

61

4

15

116

28

43

7

8

32

62

3

15

117

21

30

8

0

54

63

0

11

118

16

28

9

5

24

64

0

14

119

2

6

10

5

13

65

3

17

120

6

24

11

69

73

66

2

12

121

8

27

12

29

46

67

3

11

122

9

24

13

5

23

68

1

10

123

3

23

14

2

18

69

2

8

124

3

23

15

1

10

70

3

10

125

4

16

16

26

92

71

3

6

126

7

17

17

60

101

72

3

6

127

4

16

18

16

32

73

3

6

128

14

27

19

16

74

74

3

6

129

4

26

20

6

37

75

2

9

130

2

5

21

20

39

76

2

9

131

4

11

22

27

62

77

3

11

132

6

12

23

12

46

79

2

2

133

9

29

24

14

33

80

1

1

134

10

29

25

16

45

81

4

7

135

1

19

26

21

71

82

3

18

136

1

12

27

2

7

83

4

17

137

1

31

28

25

58

84

5

18

138

6

19

29

6

33

85

27

55

139

1

4

30

4

33

86

25

41

140

2

8

31

1

11

87

8

26

141

3

15

32

5

30

88

3

9

142

4

10

33

4

27

89

7

31

143

2

15

34

3

28

90

7

34

144

6

14

35

2

21

91

9

47

146

2

15

36

8

33

92

1

41

147

0

1

37

1

19

93

58

105

148

8

14

38

7

22

94

10

23

149

4

8

39

3

27

95

2

14

150

0

1

40

8

24

96

3

19

151

4

5

41

6

22

97

1

10

153

0

1

42

2

10

98

1

6

154

1

1

43

5

22

99

0

13

155

1

8

44

2

19

100

2

3

156

5

11

45

4

14

101

1

9

157

0

3

46

0

4

102

1

9

158

2

11

47

0

7

103

3

8

159

0

9

48

3

18

104

2

19

160

0

22

(Continued on next page)

Ă&#x201C; 2018 Hogrefe Publishing

Journal of Personnel Psychology (2018), 17(1), 12â&#x20AC;&#x201C;21

20

E. J. Robinson-Morral et al., Job Analysis Linkage Exercises

Table 3. (Continued) Number of tasks linked to KSAOs Knowledge ID#

Hybrid group

Independent group

Knowledge ID#

49

3

19

105

50

1

7

106

51

1

9

52

0

10

53

3

7

54

0

6

55

1

8

Hybrid group

Independent group

Knowledge ID#

Hybrid group

Independent group

5

8

161

0

3

5

11

162

2

28

107

1

10

163

9

35

108

5

17

164

0

2

110

1

2

Note. Table includes only the KSAOs that linked to at least one task for at least one group of raters.

Overall Summary The current studies sought to expand the literature on KSAO-task linkage ratings to provide practitioners with best practices for gathering these ratings as important legal evidence of the job-relatedness of KSAOs included in selection and on certifications. In Study 1, the type of rater (i.e., job incumbents, managers, and job analysts) was examined. The most notable results of this study offer preliminary support for practitioners to use job analysts as raters if practical considerations preclude the use of job experts. These individuals were more likely to agree when compared to job incumbents and managers regardless of the rating scale that was used and the type of linkage rating that was made.

Coupled with the previous literature that questioned the accuracy of incumbents’ ratings and the feasibility in gathering data from job experts (Harvey & Wilson, 2000; Morgeson & Campion, 1997), the present study should lead practitioners to critically evaluate whether or not to use these types of raters during the KSAO-task linkage process.

In Study 2, the results demonstrate that differences in linkage workshop methodology lead to significantly different interrater agreement and final lists of job requirements. Most notably, findings offer substantial support for a FOR consensus method in which raters discuss a subset of the ratings as a group before providing their independent, individual ratings. Even if the consensus-forming process is minimal in length, it results in higher interrater agreement and a more conservative final list of knowledge requirements.

Limitations and Future Research Several study limitations are important to note. First, given that both studies required collecting ratings from job experts, the sample size for each study was limited due to resource constraints. However, it should be noted that interrater agreement was calculated on all of the linkages (e.g., in Study 2, over 22,000 data points were compared), Journal of Personnel Psychology (2018), 17(1), 12–21

so there was substantial data to analyze. Regardless, it is important that these findings be examined with a broader sample of each rater type. Second, the studies only examined the linkage raters and methods in two industries (security and healthcare), and results should be replicated in other industries. Third, in Study 2, only knowledge ratings were gathered, and were gathered using different modes (hardcopy vs. electronic, respectively).

Future research should aim to replicate these findings using skills, abilities, and/or other characteristics and using the same modalities across administrations, as the consensus-forming process may have a different effect with other job descriptors or across modalities. Future research should also explore the use of FOR training across the different rater types (i.e., managers, incumbents, and job analysts).

Finally, future research may be to explore raters’ rationale when completing KSAO-task linkages to better understand the subtle considerations that may influence ratings.

Through the use of focus groups, researchers may develop a better understanding of how particular rating scales, rating anchors, and wording of KSAO/task statements may influence a rater’s thought process.

Conclusion The current studies provide more guidance for practitioners in terms of best practices for conducting linkage exercises to gather important legal evidence for the job-relatedness of KSAOs as they relate to selection. In particular, the study provides guidance for choosing the type of rater (i.e., managers, incumbents, or job analysts) and the structure for conducting training prior to gathering the linkages to maximize agreement among raters.

References Aamodt, M. G. (2007). Industrial/organizational psychology: An applied approach (5th ed.). Belmont, CA: Wadsworth. Ó 2018 Hogrefe Publishing

E. J. Robinson-Morral et al., Job Analysis Linkage Exercises

Baranowski, L. E., & Anderson, L. E. (2005). Examining rating source variation in work behavior to KSA linkages. Personnel Psychology, 58, 1041–1054. https://doi.org/10.1111/j.17446570.2005.00234.x Baugher, D., Weisbord, E., & Eisner, A. (2011, February). Evaluating training and experience: Do multiple raters or consensus make a difference? Paper presented at the American Society of Business and Behavioral Sciences Annual Conference Las Vegas, NV. Bobko, P., Roth, P. L., & Buster, M. A. (2004). A systematic approach for assessing the currency (“up-to-dateness”) of job analytic information. Public Personnel Management, 37, 261–277.

Dierdorff, E. C., & Morgeson, F. P. (2009). Effects of descriptor specificity and observability on incumbent work analysis ratings. Personnel Psychology, 62, 601–628. https://doi.org/ 10.1111/j.1744-6570.2009.01151.x Dunlap, W. P., Burke, M. J., & Smith-Crowe, K. (2003). Accurate tests of statistical significance for rWG and average deviation interrater agreement indexes. Journal of Applied Psychology, 88, 356–362. https://doi.org/10.1037/0021-9010.88.2.356 Equal Employment Opportunity Commission, Civil Service Commission, Department of Labor, & Department of Justice.

(1978). Uniform guidelines on employee selection procedures.

Federal Register, 43, 38290–38315.

Fleiss, J. L., Levin, B., & Cho Paik, M. (2003). Statistical methods for rates and proportions (3rd ed.). Hoboken, NJ: Wiley.

Gilbert, S., Loignon, A., Hendrickson, C., & Myers, T. (2012, April).

Think about the link: Best practices for collecting KSAO-task linkages. Poster presented at 27th meeting of the Society for Industrial-Organizational Psychology, San Diego, CA. Harvey, R., & Wilson, M. (2000). Yes Virginia, there is an objective reality in job analysis. Journal of Organizational Behavior, 21, 829–854. https://doi.org/10.1002/1099-1379(200011)21:7<829:: AID-JOB30>3.0.CO;2-4 Hughes, G. L., & Prien, E. P. (1989). Evaluation of task and job skill linkage judgments used to develop test specifications. Personnel Psychology, 42, 283–292. https://doi.org/10.1111/j.17446570.1989.tb00658.x James, L. R., Demaree, R. G., & Wolf, G. (1984). Estimating withingroup interrater reliability with and without response bias.

Journal of Applied Psychology, 69, 85–98. https://doi.org/ 10.1037/0021-9010.69.1.85 James, L. R., Demaree, R. G., & Wolf, G. (1993). rwg: An assessment of within-group interrater agreement. Journal of Applied Psychology, 78, 306–309. https://doi.org/10.1037/0021-9010.

78.2.306 Kirkman, B. L., Tesluk, P. E., & Rosen, B. (2001). Assessing the incremental validity of team consensus ratings over aggregation of individual-level data in predicting team effectiveness.

Personnel Psychology, 54, 645–667. https://doi.org/10.1111/ j.1744-6570.2001.tb00226.x Melchers, K. G., Lienhardt, N., Von Aarburg, M., & Kleinmann, M. (2011). Is more structure really better? A comparison of frame-of-reference training and descriptively anchored rating scales to improve interviewers’ rating quality. Personnel Psychology, 64, 53–87. https://doi.org/10.1111/j.1744-6570.

2010.01202.x

Ó 2018 Hogrefe Publishing

21

Morgeson, F. P., & Campion, M. A. (1997). Social and cognitive sources of potential inaccuracy in job analysis. Journal of Applied Psychology, 82, 627–655. https://doi.org/10.1037/ 0021-9010.82.5.627 Morgeson, F. P., Delaney-Klinger, K., Mayfield, M. S., Ferrara, P., & Campion, M. A. (2004). Self-presentation processes in job analysis: A field experiment investigating inflation in abilities, tasks, and competencies. Journal of Applied Psychology, 89, 674–686. https://doi.org/10.1037/0021-9010.89.4.674 Myers, T., Hendrickson, C., Gilbert, S., Loignon, A., Norris, D., Matheson, N., & Willis, R. (2011, April). Back to basics: Who should complete KSAO-task linkages? Poster presented at 26th meeting of the Society for Industrial-Organizational Psychology, Chicago, IL. Pulakos, E. D., Schmitt, N., Whitney, D., & Smith, M. (1996).

Individual differences in interviewer ratings: The impact of standardization, consensus discussion, and sampling error on the validity of a structured interview. Personnel Psychology, 49, 85–102. https://doi.org/10.1111/j.1744-6570.

1996.tb01792.x Pynes, J., & Bernardin, J. H. (1992). Mechanical vs consensusderived assessment center ratings: A comparison of job performance validities. Public Personnel Management, 21, 18–28. https://doi.org/10.1177/009102609202100102 Robbins, S. P., & Judge, T. A. (2013). Organizational behavior (15th ed.). Upper Saddle River, NJ: Pearson Education.

Roch, S. G., Woehr, D. J., Mishra, V., & Kieszczynska, U. (2012).

Rater training revisited: An updated meta-analytic review of frame-of-reference training. Journal of Occupational and Organizational Psychology, 85, 370–395. https://doi.org/ 10.1111/j.2044-8325.2011.02045.x Society for Industrial and Organizational Psychology, Inc. (2003).

Principles for the validation and use of personnel selection procedures (4th ed.). Bowling Green, OH: Author.

Vinchur, A. J., Prien, E. P., & Schippman, J. S. (1993). An alternative procedure for analyzing job analysis results for content-oriented test development. Journal of Business and Psychology, 8, 215–226. https://doi.org/10.1007/BF02230386 Woehr, D. J. (1994). Understanding frame-of-reference training: The impact of training on the recall of performance information.

Journal of Applied Psychology, 79, 525–534.

Received October 11, 2016 Revision received April 10, 2017 Accepted May 25, 2017 Published online January 3, 2018

Erika J. Robinson-Morral Workforce Development and Human Capital American Institutes for Research Workforce Solutions 1000 Thomas Jefferson Street NW Washington, DC 20007 USA erika.morral@gmail.com

Journal of Personnel Psychology (2018), 17(1), 12–21

Managing and nurturing talent in the workplace

“Robert and Marion Edenborough bring research, a wide knowledge of various psychological theories, experience in the field, and wisdom to their discussion of talent... This is a ‘must read’ for anyone interested in hiring or developing staff!”

Christy Hammer, PhD, Former Senior Analyst and Leader of International Development with Gallup

Robert Edenborough / Marion Edenborough

The Psychology of Talent Exploring and Exploding the Myths 2012, viii + 152 pages US $34.80 / € 24.95 ISBN 978-0-88937-396-9 Also available as eBook The core concepts in this book are the idea of talent, how it can be assessed, and how it can be nurtured and put to effective use in the workplace.

Line managers, HR professionals, business or industrial/organizational psychologists, and consultants will find their understanding challenged and extended - and are shown how to improve their professional practices.

The authors explore various psychological tools and approaches that can be pressed into service in connection with talent. Uniquely, they also set

www.hogrefe.com

the psychological assessment of talent in the context of attitudes to talent and various myths and misunderstandings about it. The positive psychology/strengths movement and the relation between psychology and talent management are also explored in a clear and objective manner.

This easy-to-read volume will be of interest to anyone concerned with understanding how talent can be pressed into service to improve performance in the workplace.

New, insightful theory and research concerning reactance processes Topics covered include • Reactance theory in association with guilt appeals • Tests to study the relationship between fear and psychological reactance • The influence of threat to group identity and its associated values and norms on reactance • Benefit of reactance research in health psychology campaigns • Construction and empirical validation of an instrument for measuring state reactance (Salzburger State Reactance Scale) • Motivation intensity theory and its implications for how reactance motives should convert into effortful goal pursuit

Sandra Sittenthaler / Eva Jonas / Eva Traut-Mattausch / Jeff Greenberg (Editors)

New Directions in Reactance Research (Series: Zeitschrift für Psychologie – Vol. 223) 2015, iv + 76 pp., large format US $49.00 / € 34.95 ISBN 978-0-88937-479-9 Psychological reactance theory, formulated by Jack Brehm in 1966, is one of the most popular social psychological theories explaining how people respond to threats to their free behaviors and has attracted attention in both basic and applied research in areas such as health, marketing, politics, and education.

www.hogrefe.com

A review article published 40 years later by Miron and Brehm pointed out several research gaps. That article inspired the editors to develop this carefully compiled collection presenting recent research and developments in reactance theory that both offer new knowledge and illuminate issues still in need of resolution.

Original Article

When Is Task Conflict Translated Into Employee Creativity?

The Moderating Role of Growth Need Strength Yan Li,1 Baiyin Yang,2 and Lin Ma3 1

School of Government, Beijing Normal University, Beijing, China

2

School of Economics and Management, Tsinghua University, Beijing, China School of Economics and Management, Beihang University, Beijing, China

3

Abstract: The literature shows that task conflict plays an important role in the team operation process, but little is known about who exhibits greater creativity when in conflict, leading the team toward greater creativity. To enhance understanding of employee creativity, this study proposed that task conflict has a curvilinear relationship with employee creativity and that employees’ growth need strength moderates the relationship. A cross-level investigation of employee creativity within 59 groups of employees from multiple Chinese companies was conducted. The results showed that task conflict has an inverted U-shaped relationship with employee creativity. Growth need strength was found to have a moderating effect on the relation between task conflict and employee creativity. Theoretical and practical implications were discussed.

Keywords: task conflict, growth need strength, employee creativity

In today’s rapidly changing environment, work becomes increasingly dynamic, uncertain, and knowledge-based, organizations depend more and more on creative ideas from employees (Anderson, Potočnik, & Zhou, 2014). It is well known that “employee creativity can make a substantial contribution to an organization’s competitiveness” (Baer & Oldham, 2006). Not surprisingly, a common theme in creativity research is how to inspire employees’ creativity and how to identify the factors that encourage employees to put forth new and novel ideas about product, process, and procedures (Anderson et al., 2014).

Creativity is defined as “the product of novel and useful ideas concerning products, services, processes, and procedures” (Shin & Zhou, 2007). Amabile, as an influential and representative scholar in creativity research, proposed the componential theory of creativity which posits that there are three major components contributing to individual or small team creativity: expertise, creative-thinking skill, and intrinsic motivation (Amabile, 1983). The componential model of creativity also suggests that informational resources constitute an important building block of individual creativity (Amabile, 1988). Furthermore, information exchange may increase O’Neal creativity (Amevant skills; e.g., divergent thinking; Gong, Cheung, Wang, & Huang, 2012) and creativity often emerges at the crossroads of Journal of Personnel Psychology (2018), 17(1), 22–32 https://doi.org/10.1027/1866-5888/a000192

divergent avenues of knowledge (Amabile, 1996). Later, Amabile further complemented the earlier theory by suggesting that social contexts can influence employees’ creativity and emphasizing the importance of personcontext interactions (Amabile, 1996). Task conflict, as a team-level context, stimulates team members’ exposure to divergent perspectives and provides an opportunity for employees to exchange different opinions and viewpoints with others (Jehn, 1995; Pelled, Eisenhardt, & Xin, 1999).

Due to this important attribute, some scholars began to explore its effect on creativity. However, prior few studies on the effect of task conflict on creativity have focused on the team level, with team creativity or innovation as dependent variable (e.g., De Dreu, 2006b; Farh, Lee, & Farh, 2010; He, Ding, & Yang, 2014). Despite the fact that creative ideas are generated by individuals and that team creativity begins with individual creativity (Pirola-Merlo & Mann, 2004; West & Anderson, 1996), the effect of task conflict on employee creativity has received little attention. We know little regarding how task conflict influences employee creativity, and more importantly, who exhibits greater creativity in task conflict. The latter question is of importance because not all team members contribute equally to team outcomes and certain team members’ creativity is critical for team creativity (Li, Fu, Ó 2018 Hogrefe Publishing

Y. Li et al., Task Conflict and Creativity

Sun, & Yang, 2016). Pirola-Merlo and Mann (2004) distinguished among (a) team creativity as an additive type of task, where each member’s creativity adds to that of the team, (b) team creativity that resembles a disjunctive type of task, where the most creative ideas (which may be produced by a particular individual) are adopted by the team and determine team creativity, and (c) team creativity that lies somewhere between these two types, where each member makes a contribution, but the importance of the contribution to team creativity is weighted in some way (e.g., the most creative member’s contribution is the most important). Group members may play different roles and have different reactions and exhibit diverse behaviors in the face of workplace conflict. Who, then, exhibits greater creativity in team conflicts is a question worthy of study.

To resolve this problem, we intend to take an interactive perspective and investigate the contingent condition whereby task conflict influences employee creativity.

Woodman, Sawyer, and Griffin’s (1993) interactionist account of creativity posits that we need to refine our understanding both of the role of contextual variables and of the way in which they interact with actor characteristics.

Zhou and Hoever (2014) also argued that an interactionist perspective that emphasizes actor-context interactive effects on creativity holds much promise. More specifically, we will investigate the effect of individual difference in growth need strength (GNS) – which refers to the extent to which employees long to grow or develop at work – on task conflict-creativity relationship. Researchers have focused on the roles of global individual differences (e.g., personality, cognitive style, and ability; Shalley, Gilson, & Blum, 2009). However, when considered in organizational contexts, this research has returned some inconsistent and equivocal results (Shalley et al., 2009). In light of these conflicting findings, Shalley et al. (2009) called for future research to examine job-specific individual differences in relation to creativity. In the current study, we chose to examine the effect of GNS because GNS is a variable with high relevance to the work setting (Huang & Iun, 2006) and is more relevant to how people react to their work environment than other variables, such as the Protestant work ethics (Wanous, 1974). We reasoned that employees’ creativity may be enhanced or crippled by task conflict, depending on their GNS. In the following section, we draw on the information processing perspective and argue that task conflict has a curvilinear relationship with employee creativity. We propose that employees who experience an intermediate level of task conflict exhibit greater creativity. Then, we investigate the effect of individual difference in GNS on the task conflict-creativity relationship. We posit that the more employees attach value to personal growth and development, the greater the likelihood that they take advantage Ó 2018 Hogrefe Publishing

23

of opportunities to acquire skills and learn strategies for performing tasks. By examining the moderating effect of GNS, this study attempts to make two contributions to the literature. First, the examination from the perspective of task conflict may deepen the current understanding of the influence of group process on employee creativity and add to the burgeoning literature that examines the antecedents of employee creativity. Second, this study extends the GNS and creativity literature by treating employees’ GNS as a boundary condition in relating task conflict to employee creativity. GNS is an important individual difference variable in employee creativity (Shalley et al., 2009), but little empirical research has explored its effect. To our knowledge, the empirical study

by Shalley et al. (2009) represents the first that related GNS to creativity. In the following section, we discuss the theoretical model in detail.

Literature Review and Hypotheses Task Conflict and Employee Creativity Task conflict often occurs in organizations since organizations are composed of individuals with different disciplines, skills, and experiences. Task conflict emerges when there are disagreements among group members about the content of the tasks being performed, for example, the allocation of resources, procedures, and task interpretation (De Dreu & Weingart, 2003; Shaw et al., 2010). As an important group process, task conflict can expose group members to divergent viewpoints, ideas, and opinions (Farh et al., 2010). In conflicts, group members need to analyze different perspectives, reevaluate the status quo, exchange information, and adjust objectives, strategies, or processes to suit a given task (Hülsheger, Anderson, & Salgado, 2009; West & Richter, 2008), which can lead to higher levels of creativity. In an integrative review article, De Dreu and Weingart (2003) argued that task conflict could spur group members to scrutinize task issues and think more deeply, which could foster learning and the exchange and development of new insights, leading to greater employee creativity. On the contrary, if conflict is absent, employees may not have the opportunity to confront problems.

The above arguments infer that some task conflict is beneficial for employee creativity. However, there is no such thing as an unmitigated good (Grant & Schwartz, 2011). With respect to task conflict, prior research has shown that the divergence of opinions within a team can facilitate the generation of creative ideas on the one hand, but it can also be harmful to the creativity process on the other hand (Chen, 2006). According to this, we postulate Journal of Personnel Psychology (2018), 17(1), 22–32

24

an overall pattern of curvilinearity for the task conflictcreativity association. Theoretical support for the existence of nonlinear effects of task conflict on employee creativity is provided by Broadbent’s information processing theory (Broadbent, 1958). Broadbent (1958) posited that a basic characteristic of human cognitive processing is that people have limited capacity to process information at any given time. When provided with excessive information, people feel overloaded and may experience confusion, delayed decision-making, and decreased motivation that leads to less optimal behavior (Fukukura, Ferguson, & Fujita, 2013). High levels of task conflict produce information overload that exceeds employees’ normal capability and their capacity to perceive, process, and evaluate information may decrease (Farh et al., 2010). De Dreu (2006b) also demonstrated that as conflict intensity increases, an individual’s capacity for complex thinking is altered in a curvilinear fashion. Information overload and distractions resulting from high levels of task conflict will eventually block creativity (Leenders, van Engelen, & Kratzer, 2003).

In addition, a non-negligible issue is that a high level of task conflict may result in relationship conflict. Rispens (2012) argued that it is difficult to enhance task conflict and simultaneously avoid relationship conflicts. That is, one type of conflict can breed another type of conflict (Chen, 2006). When relationship conflict becomes intense, group members may anticipate a competitive, hostile negotiation and refuse to listen to others’ views or exchange relevant information openly, which hampers group members’ cognitive flexibility and distracts them from the problem and thinking creatively (De Dreu, 2006b). Furthermore, relationship conflict may exacerbate and protract task conflict, which hinders the ability of members to gather, integrate, and adequately assess valuable information (Jehn, 1997). de Wit, Jehn, and Scheepers (2013) argued that the presence of relationship conflict will bring damaging effect to task conflict and decision making. In other words, when task conflict spirals out of control and transforms into other types of conflicts, such as relationship conflicts, the benefits of task conflict are quickly lost (De Dreu, 2006b; Sinha, Janardhanan, Greer, Conlon, & Edwards, 2016). At high level of task conflict (where the hypothesized inverted U-shaped curve has a downward trend), employees need not only to deal with the overload information from task conflict, but also with quarrel, disharmony, or interference from relationship conflict. According to the information processing theory, human’s capacity to process information is limited and the overload information will become a burden on people and weaken their creativity.

Following this line of thinking, the current research assumes that the relationship between task conflict and employee creativity is neither positive nor negative. Instead,

Journal of Personnel Psychology (2018), 17(1), 22–32

Y. Li et al., Task Conflict and Creativity

there is an inverted U-shaped relation between them.

That is, an intermediate level of task conflict can trigger a certain amount of stress, promoting employees to scrutinize the problem at hand and generate new ideas and insights (Farh et al., 2010). An increase in task conflict is assumed to be beneficial for creativity, but beyond a certain optimum level an inflection reflective of “too much of a good thing” is reached (Pierce & Aguinis, 2013), employee creativity starts to decline. We, therefore, propose the following hypothesis: Hypothesis 1: Task conflict has an inverted U-shaped relationship with employee creativity.

The Moderating Effect of GNS It has been argued that creativity arises from exposure to different perspectives and from the combination of old and new ways of seeing things (Farh et al., 2010), while task conflict is an important group process that can stimulate group members’ exposure to divergent perspectives (Farh et al., 2010). However, task conflict does not invariably mean creativity. Creativity processes are highly unpredictable and full of uncertainty, paradox, and tension (Baer, 2012; Rosing, Frese, & Bausch, 2011). Thus, creativity at work requires internal, sustaining forces that drive individuals to persevere in the face of challenges, difficulties, and pressures (Shalley, Zhou, & Oldham, 2004; Shalley et al., 2009). Employees differ in terms of their motivation and need to grow and develop within their jobs (Hackman & Oldham, 1980); hence, they respond differently to task conflict. Consequently, the mechanism of the influence of task conflict on employee creativity should be further investigated. Here, we draw on motivated information processing theory and propose that GNS regulated the inverted U-shaped relationship between task conflict and employee creativity.

GNS refers to employee motivation for growth on the job – that is, an employee’s desire for the challenge for new learning (Graen, Scandura, & Graen, 1986). It indicates employees’ internal expectations and desires for what they will obtain from their work (Shalley et al., 2009).

When this desire or need is fulfilled, it can result in “growth satisfaction” (Hackman & Oldham, 1975). This pursuit of growth and competence development implies the willingness to expend effort to achieve a thorough and rich understanding of the task or decision problem at hand. Huang and Iun (2006) argued that GNS is closely related to how people react to their work environment and reflects individuals’ work-related achievement orientation. Furthermore, this orientation is active (e.g., competence in action, learning by doing) rather than passive in nature (Zargar,

Ó 2018 Hogrefe Publishing

Y. Li et al., Task Conflict and Creativity

Vandenberghe, Marchand, & Ayed, 2014). Motivated information processing theory posits that motivations (epistemic motivation and social motivation) shape cognitive processing: employees selectively notice, encode, and retain information that is consistent with their desires (De Dreu, 2006a; De Dreu, Weingart, & Kwon, 2000).

Individual’s epistemic motivation influences the extent to which new information is searched and generated and how deep and deliberately the information is processed (De Dreu, Nijstad, & van Knippenberg, 2008). Thus, when employees have needs for personal accomplishment and growth in their work, their desires to learn new things, stretch themselves, and strive to do better in their jobs will lead them to focus on creative ideas.

Creativity includes two aspects – novelty and usefulness.

With respect to novelty, individuals with higher GNS tend to attach more value to personal growth, development, and achievement and thus gain more pleasure from challenging and intrinsically motivating work (Huang & Iun, 2006; Shalley et al., 2009). These employees do not passively wait for favorable opportunities to come but actively look for opportunities to fulfill their strong desire for growth and development (Huselid & Day, 1991). Shalley et al. (2009) noted that when individuals have a strong need for personal accomplishment, learning, and development, they may attempt to initiate behavior that leads to creative performance. Therefore, based on motivated information processing theory, individuals with a strong need for growth and development are sensitive to opportunities, hope to successfully interact with the environment (Schüler, Sheldon, & Fröhlich, 2010), and perform better while also improving their skills (Brunstein & Heckhausen, 2008).

Faced with different perspectives, they seize the opportunity to stretch themselves, actively exploring alternative ways of doing things; consequently, they are more likely to combine diverse perspectives and produce new and useful approaches to tasks. Although there is no direct empirical evidence that GNS motivates usefulness, we believe that individuals with higher GNS will give consideration to it.1 GNS is an indicator of internal expectations.

When engaged in idea generation, an individual who focuses solely on novelty at the expense of usefulness is less likely to have his or her ideas accepted and implemented, which hampers development. There is some indirect evidence for the association between GNS and usefulness.

Shalley et al. (2009) argued that GNS and intrinsic motivation are related but conceptually distinct. For some tasks, individuals may have an internal, personal drive to strive, learn, and grow (growth need strength is high); however, they may not particularly enjoy working on the tasks

1

25

(intrinsic motivation is low). Zargar et al. (2014) argued that high GNS indicates a greater learning orientation, and employees with higher levels of GNS tend to place more emphasis on feedback at work (Huang & Iun, 2006).

To gain more opportunities to learn and grow, individuals with high GNS balance novelty and usefulness when producing creative ideas. Therefore, when task conflict is controlled within a certain range, employees high in GNS will take advantage of the opportunities, absorb different information or opinions, and exhibit high creativity.

However, as discussed in Hypothesis 1, after the attainment of the optimum level of task conflict, information overload and relationship conflict will follow. Relationship conflict has a positive effect on angry mood and somatic complaints (Meier, Gross, Spector, & Semmer, 2013), which will in turn hamper employees’ creativity. We argue, therefore, that nonlinear relationship is significant for employees with high levels of GNS. However, for employees with low GNS, a different pattern should emerge. Low GNS indicates a weaker learning orientation (i.e., a weak epistemic motivation or low levels of epistemic motivation), and individuals with low GNS are less personally interested in opportunities for growth and development in their jobs (Jha, 2010; Shalley et al., 2009). As Graen et al. (1986) noted, “Those who have high GNS should react positively and those who have low GNS should react apathetically or even negatively to growth opportunities” (1986, p. 485). GNS indicates employees’ internal expectations and desires for what they will obtain from their work (Shalley et al., 2009). When individuals have no internal expectations or desires for growth, they may be indifferent to environmental complexity or changes in the environment (e.g., task conflict) and devote less attention to developing and improving knowledge, skills, and competence. Sometimes, employees with low GNS passively wait other team members to resolve task conflict and to tell them how to do. Therefore, although task conflict provides opportunities for creativity, employees with low GNS are unlikely to take advantage of the diverse information and perspectives provided by task conflict and respond to it in a creative manner. In other words, for employees with low GNS, the potential opportunity provided by task conflict is not likely to result in creative ideas. According to these arguments, we think that the nonlinear relationship may not exist for employees who have low levels of GNS. Furthermore, employees low in GNS do not like much the stimulating and challenging work and even consider task conflict as a distraction or interruption of the work procedure. This negative emotion or evaluation will hamper

We are very grateful to an anonymous reviewer for their advice on this point.

Ó 2018 Hogrefe Publishing

Journal of Personnel Psychology (2018), 17(1), 22–32

26

their creativity. Furthermore, when task conflict spirals out of control and transforms into relationship conflicts, employees are likely to be distracted from task-related activities. Therefore, we expect a negative relationship for employees with low GNS. This leads to the following hypothesis.

Hypothesis 2: GNS moderates the nonmonotonic relationship between task conflict and employee creativity such that there is (a) an inverted U-shaped relationship between these variables among employees with high GNS and (b) a negative relationship among employees with low GNS.

Methods Data Collection We collected data from nine high-technology companies in China. These studied companies engage in software development (N = 6) and network technology (N = 3) in two cities (Beijing and Wuhan). The average age of the companies was 7.11 years (SD = 3.14). We first obtained the permission and support of each company’s director for data collection, and then we met with the companies’ personnel directors. The personnel directors helped us contact team supervisors. After agreeing to participate, each team supervisor received information about the study’s objectives and procedure and then distributed the questionnaires to team members.

To reduce the potential problem of common method variance (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003), we collected data from different sources. Specifically, each subordinate completed a questionnaire about task conflict, relationship conflict, his/her GNS, and his/ her personal information, whereas supervisors rated employee creativity. We used a code on the questionnaire to identify team membership. In addition, to avoid the problem of social desirability and to reduce respondents’ apprehension about the evaluation, we included an envelope with double-sided tape and a cover letter in each questionnaire explaining the purpose of the research and emphasizing that all responses would be anonymous and confidential. Furthermore, we noted that all completed questionnaires should be put into the envelope, which should be sealed.

Eighty-two sets of questionnaires were distributed and a total of 73 teams participated in the survey. The response rate is 89%. Considering the importance of team level in the present study, we eliminated teams in which the majority of members did not respond and included teams in which two out of three members responded. In addition, Journal of Personnel Psychology (2018), 17(1), 22–32

Y. Li et al., Task Conflict and Creativity

the teams with fewer than three members were excluded from the analysis. The average response rate within the teams was 75% (range from 67% to 100%). As a result of these criteria, the number of teams that were eligible for inclusion in the study was 59, consisting of 276 employees.

Actual team sizes ranged between 4 and 12 with a mean of 6.36. Among the final sample, the team supervisors were primarily men (66.1%) with an average age of 35.22 years.

On average, each team supervisor had worked for the company for 6.13 years and the range of tenure spanned from 1 to 14 years. Team supervisors were embedded within their teams as direct leaders of and active participants in their respective teams. Team members had worked with their teams for an average of 2.41 years, with the range of tenure spanning from 0.5 to 9 years, and were between 22 and 45 years old, with an average age of 29.41 years.

Most team members had a college education. The average employee-supervisor relationship length was 2.38 years; 61.2% team members were men.

Measures All the measures we used in the survey were originally written in English and were translated into Chinese. To ensure equivalence of the measure in Chinese language, we used a standard translation and back-translation procedure (Brislin, 1970). Unless otherwise indicated, the response options for all the measures were 6-point Likert scales, ranging from 1 = strongly disagree to 6 = strongly agree.

Task Conflict We measured task conflict using items from the scales of Jehn (1995, 1997). Group members were asked to rate the task conflict of the group on a 5-point scale (1 = never, 5 = always). Sample items include “How often do people in your group disagree about opinions regarding the work being done?” “How frequently are there conflicts about ideas in your group?” “To what extent is there conflict between group members about the work you do?” “To what extent are there differences of opinion in your group?”

Cronbach’s α was .70.

Growth Need Strength Growth need strength was measured using Hackman and Oldham’s (1980) 6-item scale. Sample items include: “I enjoy stimulating and challenging work,” “I would like to have opportunities to be creative and imaginative in my work.” Cronbach’s α was .92.

Employee Creativity We measured employee’s creativity using the 4-item scale reported by Farmer, Tierney, and Kung-McIntyre (2003).

Supervisors rated employees’ creativity. Sample items Ó 2018 Hogrefe Publishing

Y. Li et al., Task Conflict and Creativity

include “Seeks new ideas and ways to solve problems,” “Generates ideas revolutionary to the field”. Cronbach’s α was .75.

Control Variables We controlled for several variables – specifically, gender, age, education, and employee-supervisor relationship length. Gender was coded as 0 = male and 1 = female.

Education level was coded into four categories (1 = High school or lower, 2 = Associate’s, 3 = Bachelor’s, 4 = Master’s or higher). Age and employee-supervisor relationship length were measured by the number of years. At group level, group size and relationship conflict were included as control variables. Group size was the total number of group members who reported on the practice management questionnaire. Relationship conflict was measured by Jehn’s (1995, 1997) 4-item scale, and sample items included “how much friction is there among members of your groups?” “how much emotional conflict is there among members of your group?” Cronbach’s α was .80.

Analytical Strategy Firstly, Confirmatory factor analyses (CFAs) were conducted to test the dimensionality and the discriminant validity of our multi-item measures. Next, given the multilevel nature of the data, we applied hierarchical linear modeling (HLM 6.0; Raudenbush & Bryk, 2002) to test our hypotheses. For HLM analyses, we ran null models with no predictors but employee creativity as the dependent variable. To separate the cross-level from between-group interaction (Hofmann & Gavin, 1998), we used the groupmean-centering technique when testing the cross-level interactive effects of task conflict and GNS on employee creativity. For the rest of the analyses, we applied grand mean centering to reduce potential collinearity between level 2 intercept and slope terms and to model the potential influences of both within- and between-team variance (Mathieu & Taylor, 2007).

The Aggregation of Data Task conflict and relationship conflict were at the group level, we aggregated the individual-level data to the group level by computing the average score among multiple members of each group before testing hypothesis.

We assessed within-group agreement before aggregation by using Rwg and ICC1 and ICC2 (Bliese, 2000). The mean and median Rwg for the two variables of task conflict (.92; .95) and relationship conflict (.95; .96) indicated high inter-rater agreement. The intra-class correlation

Ó 2018 Hogrefe Publishing

27

coefficient (ICC1) values were as follows: task conflict, .34 and relationship conflict, .25. The test statistics (F-ratios) associated with the ICC1 values of the three variables was statistically significant. The intra-class correlation coefficient ICC2 values were as follows: task conflict, .71 and relationship conflict, .60. These results showed that the aggregation of these two variables at team level was justified.

Preliminary Analyses The CFA results with LISREL 8.70 (Jöreskog & Sörbom, 2004) confirmed the discriminant validity of task conflict, GNS, relationship conflict, and employee creativity.

The hypothesized four-factor model was a better fit to the data (w2 = 140.14, df = 129, w2/df = 1.09, RMSEA = .02, CFI = .99, NNFI = .99, SRMR = .04) than all alternative models, such as the three-factor model combining task conflict and relationship conflict into one factor (w2 = 2,177.84, df = 141, w2/df = 15.44, RMSEA = .23, CFI = .53, NNFI = .49, SRMR = .22) with a significant reduction in w2 of 2,037.70 (Δdf = 12, p < .001).

To justify that HLM 2 was appropriate for analyzing our two-level data, we first ran null model. The test results showed significant between-team variances in employee creativity (w2 = 128.57, p < .001; ICC1 = .19; indicating 19% of variance residing in between teams), justifying HLM 2 as the appropriate analytical technique.

Results Table 1 shows the variables’ descriptive statistics, reliabilities, and correlations.

Curvilinear Relationship Between Task Conflict and Employee Creativity Hypothesis 1 predicted that task conflict has a curvilinear relationship with employee creativity. As shown in Model 2 in Table 2, task conflict was not significantly related to employee creativity (γ = .02, ns), while quadratic task conflict has a negative effect on employee creativity (γ = .55, p < .05). The pattern of these results (a nonsignificant linear effect in the presence of a negative and significant curvilinear effect for centered explanatory variables) indicated an inverted U-shaped relationship between task conflict and employee creativity (see Aiken & West, 1991), supporting Hypothesis 1. That is, the relationship between task conflict and employee creativity showed a positive, or upward, trend at lower levels of task conflict,

Journal of Personnel Psychology (2018), 17(1), 22–32

28

Y. Li et al., Task Conflict and Creativity

Table 1. Individual-level descriptive statistics, reliabilities, and correlations among measures Variables

Mean

SD

1

2

3

4

5

6

7

8

1. Gender 2. Age

29.41

4.58

3. Education level

2.67

0.71

.14 .02

.02

4. Employee-supervisor relationship length

2.38

1.62

.01

.41**

.07

5. GNS

3.33

1.07

.05

.04

.02

.07

6. Task conflict

2.10

0.40

.03

.05

.14*

.04

.02

7. Relationship conflict

1.65

0.57

.06

.01

.03

.02

.11

.18**

(.80)

8. Employee creativity

4.61

0.48

.01

.05

.01

.02

.08*

.01

.04

(.92) (.70) (.75)

Notes. N = 276 at the individual level, n = 59 at the group level. Reliabilities of the scales in italics on the diagonal. **p < .01, *p < .05 (two-tailed tests).

Table 2. HLM results: the main and interactive effects of task conflict and GNS on employee creativity

4.8

Variables

Model 1 Model 2 Model 3

1. Intercept

4.60**

4.60**

4.61**

2. Level 1 control and independent Gender

.00

.00

Age

.01

.01

.00

Education level

.01

.02

.02

Employee-supervisor relationship length

.01

.02

.01

GNS

.01

.09*

Employee creativity

Employee creativity

4.6

4.4

3. Level 2 control and independent Group size

.01

.00

.00

Relationship conflict

.15

.14

.15

Task conflict

.02

.02

Task conflict2

.55*

.53

4. Cross-level interaction Task conflict GNS

.01

Task conflict2 GNS

.49*

ΔR2

.06*

High task conflict

Figure 1. The curvilinear relationship between task conflict and employee creativity.

.04*

Notes. N = 276 at the individual level, n = 59 at the group level. **p < .01, *p < .05 (two-tailed tests). R2 is based on the proportional reduction of error variance resulting from predictors (Snijders & Bosker, 1999).

and a negative, or downward, trend at higher levels of task conflict (see Figure 1).

The Contingent Effect of GNS Hypothesis 2 predicted that GNS moderated the curvilinear relationship between task conflict and employee creativity.

To test this hypothesis, we introduced GNS as a moderator in the regression equation in Model 2 in Table 2. Results indicated that GNS interacted significantly with quadratic task conflict (γ = .49, p < .05). An inspection of the interaction plot (see Figure 2) revealed that the relation between task conflict and employee creativity followed an inverted

Journal of Personnel Psychology (2018), 17(1), 22–32

4.2 Low task conflict

U-shaped function for employees who had high GNS. The figure also showed that under conditions of intermediate task conflict, employees scoring high on GNS exhibited greater creativity than those who had lower GNS. For the latter, the slope curve became almost flat, thus losing the inverted-U effect.

To further analyze this quadratic interaction effect, we tested simple slopes of the regression curves. As suggested

by Aiken and West (1991), we estimated simple slopes at three levels of task conflict: low (one standard deviation below the maximum of the regression curve), intermediate (maximum of the regression curve), and high (one standard deviation above the maximum of the regression curve).

The results indicate that when the GNS is high the simple slope of the regression curve: has a positive, significant value for low task conflict (γ = .81, p < .05); significantly differs from zero for intermediate task conflict (γ = .03,

Ó 2018 Hogrefe Publishing

Y. Li et al., Task Conflict and Creativity

4.9

29

to it in a creative manner. These findings have theoretical and practical implications.

LowGNS

Employee creativity

HighGNS

Theoretical Implication 4.6

4.3

4 Low task conflcit

High task conflcit

Figure 2. The interactive effect of task conflict and GNS on employee creativity.

p < .05); and has a significant negative value for high task conflict (γ = .82, p < .05). When the GNS is low, the simple slopes of the regression line do not significantly differ from zero (ps > .05) at low, intermediate, or high levels of task conflict. In addition, the linear simple slope of task conflict on employee creativity was also nonsignificant when GNS was low. These results provide partial support for Hypothesis 2.

Discussion This study examines the possibility of an inverted U-shaped relation between task conflict and employee creativity, and whether GNS moderates this relationship. The result showed that task conflict has an inverted U-shaped relationship with employee creativity (Hypothesis 1). An increase in task conflict is beneficial for creativity.

However, after a certain level, too much task conflict damages employee creativity. Furthermore, employees’ GNS is found to moderate the inverted U-shaped relationship between task conflict and employee creativity (Hypothesis 2). Specifically, employees exhibit relatively high creativity when they experience an intermediate level of task conflict and have a strong need for growth and development. Those with low GNS are unlikely to benefit from the opportunities afforded by intermediate levels of task conflict. In other words, although task conflict provides opportunities for creativity, only employees with high GNS are able to take advantage of the diverse information and perspectives provided by intermediate levels of task conflict and respond Ó 2018 Hogrefe Publishing

First, the current study complements the creativity literature by examining its antecedents from the perspective of task conflict. The oldest theory of creativity and innovation in organizations (i.e., the componential model; Amabile & Pratt, 2016) emphasizes the importance of information resources, which have been referred to in the creativity literature as a necessary precondition for creative performance (Amabile, 1988; Kanter, 1988; Woodman et al., 1993). Task conflict is an important conduit through which team members can approach diverse information through the exchange with their teammates. However, little research has examined its effect on employee creativity.

We drew on the information processing perspective and proposed that task conflict has an inverted U-shaped relationship with employee creativity. In support of this argument, our results show that intermediate level of task conflict is beneficial to employee creativity, which enriches the creativity literature. These findings enhance the understanding of employee creativity and provide important supplement to previous research.

Second, our two-way interaction analysis demonstrates that as a variable highly related to the work setting, GNS moderates the relationship between task conflict and employee creativity. This finding enriches the GNS and creativity literature. GNS is an important individual factor for employees’ creativity, and it contributes to creativity over and above creative personality, intrinsic motivation, and cognitive style (Shalley et al., 2009); however, few studies have explored its effect. The study by Shalley et al.

(2009) found that GNS has a positive main effect on creativity and an interactive effect with context. If an employee does not have the inner drive to succeed, creative performance will be low. Shalley et al. (2009) advise that future research on creativity should examine the effects of individual differences more deeply and broadly. This study answers this call by treating employees’ GNS as a boundary condition in relating task conflict to employee creativity.

The result for the two-way interaction effect provides empirical evidence that employees with high GNS can benefit more from task conflict. Our findings offer important insights into the moderating effect of individual differences on the relationship between context and creativity.

Practical Implication Our findings have important implications for management practice. First, our study shows that an intermediate level of Journal of Personnel Psychology (2018), 17(1), 22–32

30

task conflict is beneficial to employee creativity. Thus, when group members have different viewpoints about the content of tasks being performed, managers need not worry. Different perspectives are important to new ideas or solutions, especially when the task is closely related to innovation (e.g., the design of new products and new marketing strategies). Therefore, managers should encourage group members to express their ideas and opinions about how the task is to be performed and welcome each member’s viewpoint. However, according to our findings, task conflict and employee creativity are related in a curvilinear fashion; thus, the manager needs to manage conflict and not let it escalate.

Second, our findings highlight the importance of employees’ GNS. Employees with high GNS exhibit greater creativity when encountering intermediate levels of task conflict. This suggests that managers need to attend to their employees’ job-specific growth needs and encourage employees to strengthen their GNS. For instance, they may encourage employees to challenge the status quo and view problems from a new perspective. In addition, managers may reward employees who are willing to accept more responsibility or actively solve problems. Furthermore, to facilitate creativity, the manager may wish to recruit employees with high GNS.

Limitations and Future Research The current study has several limitations that point to future research directions. First, the study used a crosssectional design, and we cannot draw strong causal inference. Future research might use longitudinal designs, measuring task conflict, GNS, and employee creativity over several periods to examine the causality of the relationship.

Second, we conducted a two-level analysis including both team and individual levels in the current study. However, every team leader rated at least three employees on their creativity, which may lead to problems associated with 0nonindependence of observations. This kind of variation produced by the raters may not be completely overlapped with the variation at the team level and there may be three levels of variation. Therefore, future research may expand the range of the sample and conduct three-level analysis to partition the variance into different levels.

Third, although we suggest that GNS moderates the relationship between task conflict and employee creativity, it is likely that other moderators exist. For example, employees in need of cognition tend to engage in and enjoy situations marked by novelty, complexity, and uncertainty and seek to infer out information from their environment (Wu, Parker, & de Jong, 2014). In addition, job autonomy is likely to be a moderator. We believe that to gain a deeper understanding Journal of Personnel Psychology (2018), 17(1), 22–32

Y. Li et al., Task Conflict and Creativity

of the effect of task conflict on employee creativity, future research should explore such potential moderators.

References Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage.

Amabile, T. M. (1983). The social psychology of creativity: A componential conceptualization. Journal of Personality and Social Psychology, 45, 357–376. https://doi.org/10.1037/00223514.45.2.357 Amabile, T. M. (1988). A model of creativity and innovation in organizations. In B. M. Staw & L. L. Cummings (Eds.), Research in organizational behavior (Vol. 10, pp. 123–167). Greenwich, CT: JAI Press.

Amabile, T. M. (1996). Creativity in context. Boulder, CO: Westview.

Amabile, T. M., & Pratt, M. C. (2016). The dynamic componential model of creativity and innovation in organizations: Making progress, making meaning. Research in Organization Behavior, 36, 157–183. https://doi.org/10.1016/j.riob.2016.10.001 Anderson, N., Potočnik, K., & Zhou, J. (2014). Innovation and creativity in organizations: A state-of-the-science review, prospective commentary, and guiding framework.

Journal of Management, 40, 1297–1333. https://doi.org/ 10.1177/0149206314527128 Baer, M. (2012). Putting creativity to work: The implementation of creative ideas in organizations. Academy of Management Journal, 55, 1102–1119. https://doi.org/10.5465/amj.2009.

0470 Baer, M., & Oldham, G. R. (2006). The curvilinear relation between experienced creative time pressure and creativity: Moderating effects of openness to experience and support for creativity.

Journal of Applied Psychology, 91, 963–970. https://doi.org/ 10.1037/0021-9010.91.4.963 Bliese, P. D. (2000). Within-group agreement, non-independence, and reliability: Implications for data aggregation and analysis.

In K. J. Klein & S. W. J. Kozlowski (Eds.), Multilevel theory, research and methods in organizations (pp. 349–381). San Francisco, CA: Jossey-Bass.

Brislin, R. W. (1970). Back-translation for cross-cultural research.

Journal of Cross-Cultural Psychology, 1, 185–216. https://doi. org/10.1177/135910457000100301 Broadbent, D. (1958). Perception and communication. London, UK: Pergamon.

Brunstein, J. C., & Heckhausen, H. (2008). The achievement motive. In H. Heckhausen & J. Heckhausen (Eds.), Motivation and action. Cambridge, UK: Cambridge University Press.

Chen, M. H. (2006). Understanding the benefits and detriments of conflict on team creativity process. Creativity and Innovation Management, 15, 105–116. https://doi.org/10.1111/j.1467-8691.

2006.00373.x De Dreu, C. K. W. (2006a). Rational self-interest and other orientation in organizational behavior: A critical appraisal and extension of Meglino and Korsgaard (2004). Journal of Applied Psychology, 91, 1245–1252. https://doi.org/10.1037/00219010.91.6.1245 De Dreu, C. K. W. (2006b). When too little or too much hurts: Evidence for a curvilinear relationship between task conflict and innovation in teams. Journal of Management, 32, 83–107. https://doi.org/10.1177/0149206305277795 De Dreu, C. K. W., Nijstad, B. A., & van Knippenberg, D. (2008).

Motivated information processing in group judgment and decision making. Personality and Social Psychology Review, 12, 22–49. https://doi.org/10.1177/1088868307304092

Ó 2018 Hogrefe Publishing

Y. Li et al., Task Conflict and Creativity

De Dreu, C. K. W., & Weingart, L. R. (2003). Task versus relationship conflict, team performance, and team member satisfaction: A meta-analysis. Journal of Applied Psychology, 88, 741–749. https://doi.org/10.1037/0021-9010.88.4.741 De Dreu, C. K. W., Weingart, L. R., & Kwon, S. (2000). Influence of social motives on integrative negotiation: A meta-analytic review and test of two theories. Journal of Personality and Social Psychology, 78, 889–905. https://doi.org/10.1037/00223514.78.5.889 de Wit, F. R. C., Jehn, K., & Scheepers, D. (2013). Task conflict, information processing, and decision-making: The damaging effect of relationship conflict. Organizational Behavior and Human Decision Processes, 122, 177–189. https://doi.org/ 10.1016/j.obhdp.2013.07.002 Farh, J. L., Lee, C., & Farh, C. I. C. (2010). Task conflict and team creativity: A question of how much and when. Journal of Applied Psychology, 95, 1173–1180. https://doi.org/1173-1180.10.1037/ a0020015 Farmer, S. M., Tierney, P., & Kung-McIntyre, K. (2003). Employee creativity in Taiwan: An application of role identity theory.

Academy of Management Journal, 46, 618–630. https://doi.org/ 10.2307/30040653 Fukukura, J., Ferguson, M. J., & Fujita, K. (2013). Psychological distance can improve decision making under information overload via gist memory. Journal of Experimental Psychology: General, 142, 658–665. https://doi.org/10.1037/a0030730 Gong, Y., Cheung, S. Y., Wang, M., & Huang, J. C. (2012). Unfolding the proactive process for creativity: Intergration of the employee proactivity, information exchange, and psychological safety perspectives. Journal of Management, 38, 1611–1633. https://doi.org/10.1177/0149206310380250 Graen, G. B., Scandura, T. A., & Graen, M. R. (1986). A field experimental test of the moderating effects of growth need strength on productivity. Journal of Applied Psychology, 71, 484–491. https://doi.org/10.1037/0021-9010.71.3.484 Grant, A. M., & Schwartz, B. (2011). Too much of a good thing: The challenge and opportunity of the inverted U. Perspectives on Psychological Science, 6, 61–76. https://doi.org/10.1177/ 1745691610393523 Hackman, J. R., & Oldham, G. R. (1975). Development of the job diagnostic survey. Journal of Applied Psychology, 60, 159–170. https://doi.org/10.1037/h0076546 Hackman, J. R., & Oldham, G. R. (1980). Work redesign. Reading, MA: Addison-Wesley.

He, Y., Ding, X. H., & Yang, K. (2014). Unpacking the relationships between conflicts and team innovation. Management Decision, 52, 1533–1548. https://doi.org/10.1108/MD-03-2014-0127 Hofmann, D. A., & Gavin, M. B. (1998). Centering decisions in hierarchical linear models: Implications for research in organizations. Journal of Management, 24, 623–641. https://doi.org/ 10.1016/S0149-2063(99)80077-4 Huang, X., & Iun, J. (2006). The impact of subordinate-supervisor similarity in growth-need strength on work outcomes: The mediating role of perceived similarity. Journal of Organizational Behavior, 27, 1121–1148. https://doi.org/10.1002/job.415 Hülsheger, U. R., Anderson, N., & Salgado, J. F. (2009). Team-level predictors of innovation at work: A comprehensive metaanalysis spanning three decades of research. Journal of Applied Psychology, 94, 1128–1145. https://doi.org/10.1037/a0015978 Huselid, M. A., & Day, N. E. (1991). Organizational commitment, job involvement, and turnover: A substantive and methodological analysis. Journal of Applied Psychology, 76, 380–391. https://doi.org/10.1037/0021-9010.76.3.380 Jehn, K. (1995). A multimethod examination of the benefits and detriments of intragroup conflict. Administrative Science Quarterly, 40, 256–282. https://doi.org/10.2307/2393638

Ó 2018 Hogrefe Publishing

31

Jehn, K. (1997). A qualitative analysis of conflict types and dimensions in organizational groups. Administrative Science Quarterly, 42, 530–557. https://doi.org/10.2307/2393737 Jha, S. (2010). Need for growth, achievement, power, and affiliation: Determinants of psychological empowerment. Global Business Review, 11, 379–393. https://doi.org/10.1177/ 097215091001100305 Kanter, R. M. (1988). When a thousand flowers bloom; Structural, collective, and social conditions for innovation in organization. In B. M. Staw & L. L. Gummings (Eds.), Research in organizational behavior (Vol. 10, pp. 169–211). Greenwich, CT: JAI Press.

Leenders, R. Th. A. J., van Engelen, J. M. L., & Kratzer, J. (2003).

Virtuality, communication, and new product team creativity: A social network perspective. Journal of Engineering and Technology Management, 20, 69–92. https://doi.org/10.1016/ S0923-4748(03)00005-5 Li, Y., Fu, F. Y., Sun, J. M., & Yang, B. Y. (2016). Leader-member exchange differentiation and team creativity: An investigation of nonlinearity. Human Relations, 69, 1121–1138. https://doi. org/10.1177/0018726715597481 Jöreskog, K. G., & Sörbom, D. (2004). LISREL 8.7 for Windows [Computer software]. Lincolnwood, IL: Scientific Software International.

Mathieu, J. E., & Taylor, S. R. (2007). A framework for testing meso-mediational relationships in organizational behavior.

Journal of Organizational Behavior, 28, 141–172. https://doi. org/10.1002/job.436 Meier, L. L., Gross, S., Spector, P. E., & Semmer, N. K. (2013).

Relationship and task conflict at work: Interactive short-term effects on angry mood and somatic complaints. Journal of Occupational Health Psychology, 18, 144–156. https://doi.org/ 10.1037/a0032090 Pelled, L. H., Eisenhardt, K. M., & Xin, K. R. (1999). Exploring the black box: Analysis of work group diversity, conflict, and performance. Administrative Science Quarterly, 44, 1–28. https://doi.org/10.2307/2667029 Pierce, J. R., & Aguinis, H. (2013). The too-much-of-a-good-thing effects in management. Journal of Management, 39, 313–338. https://doi.org/10.1177/0149206311410060 Pirola-Merlo, A., & Mann, L. (2004). The relationship between individual creativity and team creativity: Aggregating across people and time. Journal of Organizational Behavior, 25, 235–257. https://doi.org/10.1002/job.240 Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies.

Journal of Applied Psychology, 88, 879–903. https://doi.org/ 10.1037/0021-9010.88.5.879 Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.).

Newbury Park, CA: Sage.

Rispens, S. (2012). The influence of conflict issue importance on the co-occurrence of task and relationship conflict in teams.

Applied Psychology, 61, 349–367. https://doi.org/10.1111/ j.1464-0597.2011.00473.x Rosing, K., Frese, M., & Bausch, A. (2011). Explaining the heterogeneity of the leadership-innovation relationship: Ambidextrous leadership. The Leadership Quarterly, 22, 956–974. https://doi.org/10.1016/j.leaqua.2011.07.014 Schüler, J., Sheldon, K. M., & Fröhlich, S. M. (2010). Implicit need for achievement moderates the relationship between competence need satisfaction and subsequent motivation. Journal of Research in Personality, 44, 1–12. https://doi.org/10.1016/ j.jrp.2009.09.002 Shalley, C. E., Gilson, L. L., & Blum, T. C. (2009). Interactive effects of growth need strength, work context, and job complexity on

Journal of Personnel Psychology (2018), 17(1), 22–32

32

self-reported creative performance. Academy of Management Journal, 52, 489–505. https://doi.org/10.5465/AMJ.2009.

41330806 Shalley, C. E., Zhou, J., & Oldham, G. R. (2004). The effects of personal and contextual characteristics on creativity: Where should we go from here? Journal of Management, 30, 933–958. https://doi.org/10.1016/j.jm.2004.06.007 Shaw, J. D., Zhu, J., Duffy, M. K., Scott, K. L., Shih, H., & Suasnto, E. (2010). A contingency model of conflict and team effectiveness. Journal of Applied Psychology, 96, 391–400. https://doi.org/10.1037/a0021340 Shin, S., & Zhou, J. (2007). When is educational specialization heterogeneity related to creativity in research and development teams? Transformational leadership as a moderator. Journal of Applied Psychology, 92, 1709–1721. https://doi.org/10.1037/ 0021-9010.92.6.1709 Sinha, R., Janardhanan, N. S., Greer, L. L., Conlon, D. E., & Edwards, J. R. (2016). Skewed task conflict in teams: What happens when a few members see more conflict than the rest?

Journal of Applied Psychology, 101, 1045–1055. https://doi.org/ 10.1037/apl0000059 Snijders, T., & Bosker, R. (1999). Multilevel Analysis: An introduction to basic and advanced multilevel modeling. London, UK: Sage.

Wanous, J. P. (1974). Individual differences and reactions to job characteristics. Journal of Applied Psychology, 59, 616–622. https://doi.org/10.1037/h0037337 West, M. A., & Anderson, N. R. (1996). Innovation in top management teams. Journal of Applied Psychology, 81, 680–693. https://doi.org/10.1037/0021-9010.81.6.680 West, M. A., & Richter, A. W. (2008). Climates and cultures for innovation and creativity at work. In J. Zhou & C. E. Shalley

Journal of Personnel Psychology (2018), 17(1), 22–32

Y. Li et al., Task Conflict and Creativity

(Eds.), Handbook of organizational creativity (pp. 211–236).

Hillsdale, NJ: Erlbaum.

Woodman, R. W., Sawyer, J. E., & Griffin, R. W. (1993). Toward a theory of organizational creativity. Academy of Management Review, 18, 293–321. https://doi.org/10.2307/258761 Wu, C. H., Parker, S. K., & de Jong, J. P. J. (2014). Need for cognition as an antecedent of individual innovation behavior.

Journal of Management, 40, 1511–1534. https://doi.org/ 10.1177/0149206311429862 Zargar, M. S., Vandenberghe, C., Marchand, C., & Ayed, A. K. (2014). Job scope, affective commitment, and turnover: The moderating role of growth need strength. Journal of Occupational and Organizational Psychology, 87, 280–302. https://doi. org/10.1111/joop.12046 Zhou, J., & Hoever, I. J. (2014). Research on workplace creativity: A review and redirection. Annual Review of Organizational Psychology and Organizational Behaviors, 1, 333–359. https:// doi.org/10.1146/annurev-orgpsych-031413-091226 Received March 18, 2016 Revision received June 19, 2017 Accepted June 27, 2017 Published online January 3, 2018

Lin Ma School of Economics and Management Beihang University Beijing, 100083 China malinbeijing@126.com

Ó 2018 Hogrefe Publishing

Original Article

Employees’ Critical Thinking, Leaders’ Inspirational Motivation, and Voice Behavior The Mediating Role of Voice Efficacy Jing Jiang,1 Ang Gao,2 and Baiyin Yang3 1

Hospitality Management School, Beijing International Studies University, China

2

School of Management and Economics, Beijing Institute of Technology, China

3

School of Economics and Management, Tsinghua University, Beijing, China

Abstract: This study uses implicit voice theory to examine the influence of employees’ critical thinking and leaders’ inspirational motivation on employees’ voice behavior via voice efficacy. The results of a pretest of 302 employees using critical thinking questionnaires and a field study of 273 dyads of supervisors and their subordinates revealed that both employees’ critical thinking and leaders’ inspirational motivation had a positive effect on employees’ voice and that voice efficacy mediates the relationships among employees’ critical thinking, leaders’ inspirational motivation, and employees’ voice. Implications for research and practice are discussed.

Keywords: voice, critical thinking, inspirational motivation, voice efficacy, implicit voice theory

With the rapid pace of technological and economic growth, more and more enterprises are recognizing the importance of employee-driven initiatives. Examples include giving constructive advice for improving organizational functioning and enhancing the adaptability of the organization (LePine & Van Dyne, 2001). However, voice behavior is inherently risky because it may damage one’s image, threaten interpersonal relationships, offend authority, and negatively influence career development and salary progression (e.g., Ashford, Rothbard, Piderit, & Dutton, 1998; Detert & Edmondson, 2011; Seibert, Kraimer, & Crant, 2001). Due to these undesirable outcomes, employees’ speaking up, to a large extent, is motivated by a sense of sufficient confidence to cope with risky situations.

To overcome risky voice situations, Kish-Gephart, Detert, Treviño, and Edmondson (2009) call for paying more attention to the role of voice efficacy in employees’ voice behavior. Voice efficacy is associated with an individual’s belief in his or her capacity to speak up, and employees with higher voice efficacy will likely appraise a situation as being more controllable than employees with low voice efficacy (Kish-Gephart et al., 2009). Thus, voice efficacy is an important voice-relevant motivation for speaking up in risky situations (Kish-Gephart et al., 2009; Morrison, 2014). Ó 2018 Hogrefe Publishing

Although voice efficacy plays an important role in helping employees to overcome their fear of using their voice, we know little about what factors can promote employees’ voice efficacy and further drive their speaking up. The implicit voice theory may help researchers resolve this puzzle. Implicit theories are schema-like knowledge structures that individuals use to effortlessly process current stimulus cues and choose responses (Ross, 1989, p. 342).

The implicit voice theory indicates the taken-for-granted beliefs about the risk or inappropriateness of speaking up (Detert & Edmondson, 2011). Drawing on the implicit voice theory, employees fear speaking up because they do not have solid data or they encounter unwelcoming leader behaviors (Detert & Edmondson, 2011). Therefore, this study mainly uses the implicit voice theory to investigate what personal abilities and leader behaviors can endow employees with strong confidence to overcome fears, which in turn will inspire them to challenge the status quo and express their opinions.

Given that personal skills are an important source of selfefficacy (Bandura & Schunk, 1981; Kish-Gephart et al., 2009), employees with better cognitive skills to back up their advice may have more positive contributions to voice efficacy. Critical thinking has been conceived of as a mode Journal of Personnel Psychology (2018), 17(1), 33–41 https://doi.org/10.1027/1866-5888/a000193

34

of scientific analytic reasoning or method-centered thinking (Yanchar, Slife, & Warne, 2008), which includes a set of cognitive skills, such as interpretation, analysis, evaluation, inference, explanation, and self-regulation (Facione, 1990).

These cognitive skills can give employees a strong sense of confidence because they are able to explain what they think and how they arrived at their judgments (Facione, 2011).

The implicit voice theory also shows that employees have a taken-for-granted belief that they must have solid data, airtight reasoning, or clear solutions before it is safe to speak (Detert & Edmondson, 2011). Based on the implicit voice theory, critical thinking can bestow upon employees the confidence necessary to manage and successfully handle issues in voice situations, which, in turn, motivates them to express themselves (Detert & Edmondson, 2011; Kish-Gephart et al., 2009). Given this, the first aim of this study is to examine the mediating role of voice efficacy in the relationship between employees’ critical thinking and voice behavior.

Because the implicit voice theory involves leaders as targets (Detert & Edmondson, 2011), leaders’ behaviors are important situational factors that influence speakers’ potential voice efficacy and further determine whether employees speak up or not (Wei, Zhang, & Chen, 2015).

Previous literature has shown that transformational leadership is an important antecedent of employees’ voice (e.g., Detert & Burris, 2007; Liu, Zhu, & Yang, 2010); however, studies, such as the one conducted by Detert and Burris (2007), do not isolate the mediating mechanisms between transformational leadership and supervisor-perceived employee voice. In recent years, a few studies have investigated the mediators that link transformational leadership and employees’ voice (Liu et al., 2010; Wang, Hsieh, Tsai, & Cheng, 2012), but none of them have revealed the psychological process that is motivated by the capability to cope with voice in situations of fear. This study aims to explore how voice efficacy, a voice-relevant motivation, bridges transformational leadership and employees’ voice.

In light of the fact that specific leader behaviors are more effective than generically positive ones (Detert & Burris, 2007), our main focus is on leaders’ inspirational motivation behavior that favors or inhibits employees’ voice via voice efficacy. Compared with the other three dimensions of transformational leadership (idealized influence, intellectual stimulation, and individualized consideration; Bass & Avolio, 1995), leaders’ inspirational motivation behavior is not only change-oriented (Detert & Burris, 2007) but also group-focused (Wang et al., 2012; Wu, Tsui, & Kinicki, 2010). Leaders’ inspirational motivation behavior can give followers a strong sense of group identity and inspire them to put a great deal of effort into their work (Liu et al., 2010).

By working to achieve a thorough understanding of issues

Journal of Personnel Psychology (2018), 17(1), 33–41

J. Jiang et al., Employees’ Critical Thinking and Voice Behavior

in their workplace, employees come to believe that they are capable of expressing their ideas, which inspires them to challenge the existing state of affairs and voice their thoughts.

In the following section, we build our model based on the implicit voice theory. Our model suggests that employees’ critical thinking (personal factor) and inspirational motivation by transformational leadership (situational factor) both have positive effects on voice behavior via voice efficacy. We surveyed samples of employees in China to test our hypotheses.

Theory and Hypotheses Critical Thinking and Employees’ Voice Behavior Critical thinking refers to purposeful, self-regulatory judgment that results in interpretation, analysis, evaluation, and inference, as well as explanation of the evidential, conceptual, methodological, criteriological, or contextual considerations upon which that judgment is based (Facione, 1990, p. 2). Theoretically, we believe critical thinking has positive effects on employees’ voice behavior for three reasons, the first of which is that, according to the implicit voice theory, employees are afraid to speak up at work because they have a taken-for-granted belief that it is risky for subordinates to suggest advice unless they have solid data, polished ideas, or complete solutions (Detert & Edmondson, 2011). Recall that critical thinking refers to an aforementioned set of cognitive skills (Facione, 1990).

These cognitive skills can endow employees with a strong sense that they are capable of handling challenging situations, particularly when questioned about certain aspects of a new idea (Facione, 2011; Kish-Gephart et al., 2009).

Thus, employees who engage in critical thinking become willing to present advice to their leaders. Secondly, employees with strong critical thinking typically embody the spirit of truth-seeking (Facione, 1990, 2011). Truth-seeking, a kind of prosocial motivation for collective interests, demonstrates an internalized desire to commit to the improvement of an organization with objectivity, integrity, and fair-mindedness (Facione, 1990, 2011). Once employees with critical thinking find new ways to improve their work or identify the potential harms to the organization, they will challenge authorities in order to find the truth. Finally, previous empirical research has also shown that critical thinking is positively related to change-oriented and risky behaviors, such as employees’ creative process engagement and creative behavior (Jiang & Yang, 2015). Based on these

Ó 2018 Hogrefe Publishing

J. Jiang et al., Employees’ Critical Thinking and Voice Behavior

findings (Jiang & Yang, 2015), critical thinking is also able to predict employees’ voice behavior. According to the foregoing analysis, this study proposes the following hypothesis: Hypothesis 1: Critical thinking is positively associated with employees’ voice behavior.

Critical Thinking, Voice Efficacy, and Voice Behavior In keeping with the argument that employees need sufficient confidence to overcome their fear of engaging in voice, personal skill has been described as a key source of voice efficacy (Bandura & Schunk, 1981; Kish-Gephart et al., 2009). We therefore hypothesize that the relationship between critical thinking and employees’ voice behavior is mediated by voice efficacy. Initially, critical thinking is positively related to voice efficacy. Critical thinkers can interpret, analyze, evaluate, and make inferences about information (Facione, 1990, 2011).To some extent, critical thinking skills can strengthen employees’ belief that they are able to offer high-quality suggestions (Bandura & Schunk, 1981; Kish-Gephart et al., 2009). Furthermore, critical thinkers with a strong epistemic motivation and inquisitiveness (Facione, 2011; King & Kitchener, 2004; King, Kitchener, & Wood, 1994) exhibit a willingness to expend efforts to achieve a thorough and rich understanding of issues in the workplace. Driven by epistemic motivation and inquisitiveness, critical thinkers can master more new skills and knowledge, which can enhance employees’ belief in their own ability to present useful ideas to their leaders.

In addition, voice efficacy can positively predict employees’ voice behavior, which inherently carries potential risks (Detert & Edmondson, 2011; Liang, Farh, & Farh, 2012; Liu et al., 2010; Morrison, Wheeler-Smith, & Kamdar, 2011).

On the one hand, employees with higher voice efficacy will likely appraise a situation as being more controllable than employees with low voice efficacy (Kish-Gephart et al., 2009), and on the other hand, the existence of higher domain-specific efficacy means employees believe they can successfully express their advice despite the challenges inherent in voice behaviors (Bandura, 1986; Kish-Gephart et al., 2009). In their empirical study, Wei et al. (2015) show that voice efficacy is positively associated with employees’ promotive voice and prohibitive voice. Morrison et al.’s (2011) research also demonstrates that group voice efficacy can predict employees’ voice. Based on these previous studies (Kish-Gephart et al., 2009; Morrison et al., 2011), we argue that voice efficacy is an important antecedent of voice behavior.

Lastly, critical thinking positively affects employees’ voice efficacy, which, in turn, affects their voice behavior. Ó 2018 Hogrefe Publishing

35

Based on the implicit voice theory, employees with good critical thinking skills are able to correctly understand information or problems from different perspectives and present the best possible solutions (Facione, 1990, 2011).

When employees with critical thinking capabilities perceive their ability to manage and successfully handle issues in the workplace, they will be more confident to express new ideas and concerns about work practices. Moreover, employees with strong critical thinking have the spirit of truth-seeking (Facione, 1990, 2011), which can result in a powerful sense of voice efficacy in the face of difficulties and setbacks. Consequently, these critical thinkers are not afraid to challenge authority and express their constructive ideas for the organization’s long-term benefit. In addition, critical thinkers, who engage in in-depth learning to explore the essence of problems, believe that knowledge does not generally involve absolute certainty and is not derived from authority figures (King & Kitchener, 2004; King et al., 1994; Paul & Elder, 2002). Being motivated by in-depth learning gives them the energy and confidence to express their opinions and shape organizational change. Therefore, we predict: Hypothesis 2: Voice efficacy plays a mediating role in the relationship between critical thinking and employees’ voice.

Leaders’ Inspirational Motivation and Employees’ Voice Behavior Leaders’ inspirational motivation refers to leader behaviors that “inspire and motivate followers to reach ambitious goals that may have previously seemed unreachable, by raising followers’ expectations and communicating confidence that followers can achieve ambitious goals” (Wu et al., 2010, p. 92). Because the implicit voice theory involves leaders as targets (Detert & Edmondson, 2011), in this study, we presume leaders’ inspirational motivation as an important contextual factor that exerts a positive effect on employees’ voice for several reasons. Firstly, inspirational motivation by transformational leaders is changeoriented (Detert & Burris, 2007; Dvir, Eden, Avolio, & Shamir, 2002); to be more exact, leaders mainly focus on clarifying collective visions so that employees can reflect on their work from a big-picture perspective, thus coming up with constructive recommendations and advice.

Secondly, leaders’ inspirational motivation behavior is group-focused (Wang et al., 2012; Wu et al., 2010), which creates a strong sense of collective mission. Employees are more likely to focus on organizational interests than worries and fears as they become willing to take on the challenge of voicing their thoughts (Detert & Burris, 2007; Liu et al., 2010). Thirdly, previous empirical findings Journal of Personnel Psychology (2018), 17(1), 33–41

36

J. Jiang et al., Employees’ Critical Thinking and Voice Behavior

Figure 1. The theoretical model.

Employees’ critical thinking Employees’ voice efficacy

Employees’ voice behavior

Leaders’ inspirational motivation

have suggested that inspirational motivation by transformational leadership is the antecedent of employees’ voice behavior (Detert & Burris, 2007; Liu et al., 2010). We therefore predict: Hypothesis 3: Leaders’ inspirational motivation is positively related to employees’ voice behavior.

Leaders’ Inspirational Motivation, Voice Efficacy, and Voice Behavior In this study, we aim to demonstrate that voice efficacy mediates the relationship between leaders’ inspirational motivation and employees’ voice. Leaders’ inspirational motivational behaviors can inspire employees to transcend their own self-interests for the sake of the organization and cultivate a sense of collective mission (Antonakis & House, 2002; Wang et al., 2012; Wu et al., 2010). This shared mission triggers employees’ inner passion and confidence and strengthens their efficacy when engaging in risk behaviors such as anticipating problems and bringing about constructive change (Antonakis & House, 2002; Wang et al., 2012; Wu et al., 2010). In addition, leaders’ inspirational motivational behaviors provide employees with a strong sense of collective identity (Antonakis & House, 2002; Wang et al., 2012; Wu et al., 2010), which creates a strong perception of voice efficacy as a means of withstanding failures and coping with uncertainty (Wang et al., 2012; Wu et al., 2010). Accordingly, employees become more willing to express solutions that protect collective interests (Wang et al., 2012). Moreover, according to the implicit voice theory, when employees strongly identify with a group, they invest more cognitive energy in information processing and make an extra effort to generate creative solutions to problems due to their heightened levels of intrinsic motivation and self-efficacy (Jung, 2000). Thus, they dare to voice their thoughts and challenge the status quo (Wang et al., 2012). Specifically, we predict: Hypothesis 4: Voice efficacy mediates the relationship between inspirational motivation and employees’ voice.

Journal of Personnel Psychology (2018), 17(1), 33–41

Based on the theoretical arguments presented above, we built a conceptual model to understand the inner mechanism in terms of how the personal factor of critical thinking and the situational factor of leaders’ inspirational motivation influence employees’ voice behavior via voice efficacy (see Figure 1).

Methods Sample and Procedure For our field study, we selected a large-scale private company in mainland China. We numbered each of the subordinates and their direct supervisors in pairs, based on the list provided by the director of human resources.

All numbered questionnaires were placed into sealed envelopes in advance. The questionnaires were distributed using the numbers. Each respondent was asked to place the completed questionnaire into the sealed envelope for site collection. To avoid possible common method bias, we collected data from multiple sources in our field study.

Employees completed the questionnaire to evaluate their leaders’ inspirational motivational behavior, their own critical thinking, and their own voice efficacy. Their immediate supervisors evaluated their corresponding subordinates’ voice behavior.

In the field study, we distributed the questionnaire to 350 dyads of supervisors and their subordinates, and the final sample consisted of 273 supervisor-subordinate dyads, yielding a response rate of 78.0%. Across the subordinate sample, male employees accounted for 73.7%, employees with a Bachelor’s degree or higher accounted for 52.4%, and employees’ average age was 28.67 years.

Measures The major variables studied were critical thinking, inspirational motivation, voice efficacy, and employees’ voice behavior. The entire survey was translated from English into Chinese and then back-translated into English by two independent bilingual individuals to ensure equivalency in meaning. Ó 2018 Hogrefe Publishing

J. Jiang et al., Employees’ Critical Thinking and Voice Behavior

Critical Thinking Critical thinking was assessed using a 10-item scale developed by Facione, Facione, and Giancarlo (1997).

Sample items included the following: “I seek clarification of the problem and the terminology used to discuss it” and “I integrate new information and adjust directions to resolve a difficult problem.” Responses were obtained on a scale ranging from 1 (= strongly disagree) to 5 (= strongly agree).

In a pilot study,1 the Cronbach’s α for this measure was .92.

Inspirational Motivation Inspirational motivation was measured using the scale developed by Bass and Avolio (1995). Sample items included “My supervisor expresses his/her confidence that we will achieve our goals.” Responses were obtained on a scale ranging from 1 (= strongly disagree) to 5 (= strongly agree).

Voice Efficacy Voice efficacy was measured using the 6-item scale developed by Morrison et al. (2011). Sample items included “I am capable of effectively speaking up with ideas for new projects or changes in procedures” and “I am capable of effectively developing and making recommendations concerning issues that affect the team.” Responses were obtained on a scale ranging from 1 (= strongly disagree) to 5 (= strongly agree).

Voice Behavior Voice behavior was evaluated using the 10-item scale developed by Liang et al. (2012). Sample items included “He/she proactively develops and makes suggestions for issues that may influence the unit” and “He/she advises other colleagues against undesirable behaviors that would hamper job performance.” Responses were obtained on a scale ranging from 1 (= strongly disagree) to 5 (= strongly agree).

Control Variables Gender was assessed as a basic demographic control variable that could potentially affect voice (LePine & Van Dyne, 1998), so we controlled employees’ gender. Drawing on the work of Morrison et al. (2011), employees with longer dyadic tenure may feel more comfortable speaking up than newcomers. Therefore, we also chose dyadic tenure as a control variable.

Analytical Strategy We firstly adopted confirmatory factor analysis (CFA) to test the distinctiveness of the three employee self-reported 1

37

variables (i.e., critical thinking, inspirational motivation, and voice efficacy). LISREL 8.70 (Scientific Software International, Inc., Skokie, IL) was used, and three indices were chosen to represent the goodness of fit: the root mean square error of approximation (RMSEA), the comparative fit index (CFI), and the standardized root mean square residual (SRMR). Secondly, we conducted regression analysis to examine the effect of critical thinking and inspirational motivation on employee voice, and we followed Baron and Kenny’s (1986) procedure to test the mediating effect of voice efficacy. To further estimate the indirect effects of our antecedents on voice behavior, we employed the bootstrapping approach with the aid of an SPSS macro developed by Preacher and Hayes (2008).

Results Table 1 displays means, standard deviations, correlations, and reliabilities for all variables. The results showed that both critical thinking and inspirational motivation were significantly correlated with voice efficacy (r = .40, p < .01; r = .30, p < .01, respectively) and voice behavior (r = .26, p < .01; r = .24, p < .01, respectively). Voice efficacy was also significantly correlated with voice behavior (r = .37, p < .01). Therefore, Hypotheses 1–4 were preliminarily supported (see Table 1). The Cronbach’s α for our measures ranged from .64 to .87, indicating that the reliability of items was within an acceptable range (see Table 1).

To examine the measurement model fit and verify the discriminant validity of the three variables, we conducted a series of CFAs. Table 2 summarizes these model fit results. The hypothesized three-factor model (model 1 in Table 2) was compared with all alternative models. In models 2 through 4, items for any two variables loaded on a common factor, and others loaded on their own factor.

In model 5, all items loaded on one single factor. As shown in Table 2, the hypothesized three-factor model was an adequate fitting model: w2(186) = 413.31; w2/df = 2.22; RMSEA = .07; CFI = .90; SRMR = .07 (Kelloway, 1996; Hoyle, 2012). It fit better than any alternative model.

In the three-factor model, all loadings were statistically significant except for critical thinking. Facione (1990) defines critical thinking as a set of thinking skills that include interpretation, analysis, evaluation, inference, explanation, and self-regulation. These subskills might be highly correlated with each other, but these items might not converge at a certain factor as reflective indicators did.

In the pilot study, we chose employees from a large-scale food company. Four hundred questionnaires were distributed, and 302 copies were collected, yielding a final response rate of 75.5%. Among the samples, 73.2% were male, 79.6% held at least a Bachelor’s degree, and their average age was 29.85 years.

Ó 2018 Hogrefe Publishing

Journal of Personnel Psychology (2018), 17(1), 33–41

38

J. Jiang et al., Employees’ Critical Thinking and Voice Behavior

Table 1. Descriptive statistics, correlations, and reliabilities Mean

SD

1

2

3

4

5

1. Gender

0.21

0.41

–

2. Dyadic tenure

2.20

2.49

.02

–

3. Critical thinking

3.93

0.38

.03

.01

4. Voice efficacy

3.98

0.61

.12

.01

.40**

5. Inspiration motivation

4.00

0.54

.12

.03

.40**

.30**

(.87)

6. Employees’ voice

3.61

0.50

.26**

.16*

.26**

.37**

.24**

6

(.64) (.85) (.85)

Notes. N = 217–273. Cronbach’s α in parentheses on the diagonal. *p < .05; **p < .01 (two-tailed).

Table 2. Summary of model fit indices Model

w2

Δw2

df

SRMR

CFI

3-Factor: CT; IM; VE

413.31

–

186

0.07

0.90

RMSEA 0.07

2-Factor: CT + IM; VE

870.25

456.94

188

0.10

0.76

0.12

2-Factor: CT + VE; IM

936.46

523.15

188

0.11

0.75

0.12

2-Factor: CT; IM + VE

1,279.51

866.20

188

0.12

0.64

0.15

Single-factor

1,792.32

1,379.01

189

0.13

0.51

0.18

Notes. N = 262. CT = critical thinking; VE = voice efficacy; IM = inspirational motivation.

Table 3. The effect of critical thinking and inspirational motivation on employee voice via voice efficacy Voice efficacy Variables

Model 1

Employee voice Model 2

Model 3

Model 4

Model 5

Gender

.12

.07

.25**

.22**

Dyadic tenure

.01

.02

.18*

.17**

.21** .17**

Critical thinking

.30**

.17*

.09

Inspirational motivation

.27**

.18**

.07

Voice efficacy R2

.33** .01

ΔR2

.24**

.09**

.23**

.18**

.26**

.09**

.08**

Bootstrap results for indirect effect ab

SE

Boot 95% CI

Critical thinking

.17

.05

[.08, .28]

Inspirational motivation

.14

.04

[.07, .25]

Notes. N = 212–215. Unstandardized regression coefficients are reported. *p < .05; **p < .01 (two-tailed).

Table 3 shows the results for tests of the effects of critical thinking and inspirational motivation on employee voice via voice efficacy. To examine Hypotheses 1 and 3, we regressed employees’ voice on the control variables, critical thinking, and inspirational motivation (see model 4 in Table 3). The results indicate that employees’ critical thinking and their supervisors’ inspirational motivational behavior were both significantly related to voice behavior (β = .17, p < .05; β = .18, p < .01) and accounted for significant extra variance in voice behavior (ΔR2 = .09, p < .01). Thus, Hypotheses 1 and 3 are supported.

Journal of Personnel Psychology (2018), 17(1), 33–41

Next, we tested Hypotheses 2 and 4, both of which posited a mediating role of voice efficacy. In model 2, we regressed voice efficacy on the control variables, critical thinking, and inspirational motivation. In model 5, we regressed employee voice on the control variables, critical thinking, inspirational motivation, and voice efficacy.

As illustrated in Table 3, we found that both critical thinking and inspirational motivation had significant positive effects on voice efficacy (β = .30, p < .01; β = .27, p < .01, respectively). When employee voice efficacy was added to the equation in model 5, neither of them remained significant Ó 2018 Hogrefe Publishing

J. Jiang et al., Employees’ Critical Thinking and Voice Behavior

at the conventional level, but employee voice efficacy became significant (β = .33, p < .01). These results were consistent with Hypotheses 2 and 4.

To further estimate the indirect effect, we used the bootstrapping approach with the aid of a PROCESS macro developed by Preacher and Hayes (2008). We ran the macro by entering either critical thinking or inspirational motivation as the independent variable, voice behavior as the dependent variable, gender and dyadic tenure as covariates, and voice efficacy as the mediator. As shown in Table 3, the indirect effect of critical thinking on voice behavior through voice efficacy was .17 (SE = .05, 95% CI [.08, .29]), and the indirect effect of inspirational motivation on voice behavior was .14 (SE = .04, 95% CI [.07, .26]). Therefore, our results support Hypotheses 2 and 4.

Overall, our hypotheses were all supported.

Discussion This study aimed to shed light on the underlying mechanism explaining how the personal factor of critical thinking and the situational factor of leaders’ inspirational motivation influence employees’ voice behavior via voice efficacy.

The results of this study have both theoretical and practical implications.

Theoretical Implications This study answered the call for a more comprehensive understanding of the role of voice efficacy in fear situations (Kish-Gephart et al., 2009). To date, a great deal of research has tried to explore the underlying motivations of employees speaking up (e.g., Lam & Mayer, 2013; Liang et al., 2012; Van Dyne, Ang, & Botero, 2003). Prosocial motivations, such as a sense of obligation (Liang et al., 2012), conscientiousness (Nikolaou, Vakola, & Bourantas, 2008), and customer orientation (Lam & Mayer, 2013), are the core premises found throughout the voice literature (Morrison, 2014).

However, voice behavior is inherently challenging and risky (e.g., Detert & Edmondson, 2011; Morrison, 2014).

Employees’ speaking up not only depends on an internalized desire to commit to improvement or helping others but is also motivated by a sense of sufficient confidence to cope with fear situations. In light of the potential negative consequences related to voice, this study has found employees to be more likely to speak up when they have a strong sense of voice efficacy, and the empirical results support this hypothesis. These findings can enrich the voice literature from a motivational perspective.

Based on the implicit voice theory, we explained how critical thinking, a personal variable, affects employees’ Ó 2018 Hogrefe Publishing

39

voice efficacy, which inspires employees to speak up.

Relying on the implicit voice theory can trigger the specific belief that it is unwise to speak up without solid data, airtight reasoning, or clear solutions (Detert & Edmondson, 2011).

From this perspective, the ability to back up suggestions plays an important role in predicting employees’ voice efficacy and further determines whether or not employees speak up. Critical thinking is a kind of method-centered thinking (Harrigan & Vincenti, 2004; Yanchar et al., 2008), and critical thinkers can use their cognitive skills to clarify issues, express the significance of their suggestions, and even offer solutions to their leaders (Facione, 1990, 2011; Facione et al., 1997). Once employees recognize their ability to manage and successfully handle issues in their work, they will be more likely to express new ideas and concerns about work practices (Kish-Gephart et al., 2009; Morrison et al., 2011). Therefore, the study concludes that employees’ critical thinking can lead to a strong sense of voice efficacy and further influence employees’ voice behavior. This finding highlights the importance of cognitive skills in creating psychological efficacy for voice research.

We investigated leaders’ inspirational motivation as the situational factor that impacts employees’ voice efficacy and further indirectly exerts influence on employees’ voice.

Although scholars have investigated the mediators that link transformational leadership and employees’ voice, such as social and personal identity (Liu et al., 2010) and value congruence (Wang et al., 2012), none of the literature focuses on the psychological process that is motivated by the capability to cope with fear in voice situations. Leaders who utilize inspirational motivational behavior tend to emphasize their influence on their followers as a whole (Wang et al., 2012). When leaders show a high level of inspirational motivation, employees see themselves collectively and feel an obligation to put a great deal of effort into their work (Liu et al., 2010). A thorough understanding of work-related issues strengthens employees’ confidence in their own capability to voice their views, which encourages them to express their concerns. This finding, to some extent, enriches the literature on employees’ voice and transformational leadership.

Practical Implications This study has important practical significance. Our study indicates that voice efficacy plays a mediating role in the relationship between critical thinking and employees’ voice.

Enterprises should pay more attention to employees’ critical thinking training because the more in-depth information processing employees engage in, the more confident they will be to present their ideas. Meanwhile, in order to encourage employees to express concerns regarding existing or potential issues of dysfunction, managers should Journal of Personnel Psychology (2018), 17(1), 33–41

40

exhibit more inspirational motivational behaviors. When leaders emphasize a shared vision, followers are more likely to define themselves as members of an organization or group; as a result, employees are more likely to strengthen their own self-perceptions of voice efficacy, which can inspire them to bring about constructive change for their organizations.

Limitations and Future Research Directions Although this study has produced meaningful results, it is not without limitations that must be addressed in future research. We investigated antecedent and mediating variables from the same source at the same time. To avoid common method bias, future empirical studies can collect data of antecedents and mediators at separate times. The causal relationships in our test model might be reversed by cross-sectional research, and future studies could employ experimental and longitudinal designs to evaluate the causality implied in our model. We also drew upon the implicit voice theory alone to guide our framework.

Future work could also explore the relationship between the implicit voice theory and employees’ voice or silence behaviors. We emphasized that critical thinking acts as personal ability to offer high-quality suggestions (Facione, 2011; Facione et al., 1997); however, the measure of employees’ voice behavior developed by Liang et al.

(2012) includes two dimensions: promotive voice and prohibitive voice. To some extent, Liang et al.’s (2012) voice measurement reflects voice content rather than the quality of suggestions. Future research should investigate the role of critical thinking in predicting specific voice qualityrelated variables. Finally, this study only assessed one aspect of transformational leadership. To have a comprehensive understanding of the role of leaders in employees’ voice behavior, future studies can test other dimensions of transformational leadership or related concepts, such as supportive supervision. Furthermore, the sample in this study was drawn exclusively from mainland China.

We should thus be cautious when generalizing these findings to other cultures as the overall model must be tested in other cultural contexts.

Conclusion This study used the implicit voice theory to examine the personal factor of critical thinking and the situational factor of leaders’ inspirational behavior in exerting influence on employees’ voice via voice efficacy. The results show that critical thinking and leaders’ inspirational motivational behavior are significantly associated with employees’ voice.

Journal of Personnel Psychology (2018), 17(1), 33–41

J. Jiang et al., Employees’ Critical Thinking and Voice Behavior

Voice efficacy plays a mediating role in the relationships among critical thinking, leaders’ inspirational motivational behavior, and employees’ voice.

Acknowledgments This work was supported by grants from the Ministry of Education Fund of China (15YJC630043) and the National Natural Science Foundation of China (71502013, 71232002).

References Antonakis, J., & House, R. J. (2002). The full-range leadership theory: The way forward. In B. J. Avolio & F. J. Yammarino (Eds.), Transformational and charismatic leadership: The road ahead (pp. 3–33). Amsterdam, The Netherlands: JAI Press.

Ashford, S. J., Rothbard, N. P., Piderit, S. K., & Dutton, J. E. (1998).

Out on a limb: The role of context and impression management in selling gender-equality issues. Administrative Science Quarterly, 43, 23–57. https://doi.org/10.2307/2393590 Bandura, A. (1986). Social foundations of thought and action.

Englewood Cliffs, NJ: Prentice Hall.

Bandura, A., & Schunk, D. H. (1981). Cultivating competence, self-efficacy, and intrinsic interest through proximal selfmotivation. Journal of Personality and Social Psychology, 41, 586–598. https://doi.org/10.1037/0022-3514.41.3.586 Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic and statistical considerations. Journal of Personality and Social Psychology, 51, 1173–1182. https://doi. org/10.1037/0022-3514.51.6.1173 Bass, B. M., & Avolio, B. J. (1995). Multifactor leadership questionnaire. Binghamton, NY: Center for Leadership Studies.

Detert, J., & Burris, E. (2007). Leadership behavior and employee voice: Is the door really open? Academy of Management Journal, 50, 869–884. https://doi.org/10.5465/AMJ.2007.26279183 Detert, J., & Edmondson, A. (2011). Implicit voice theories: Takenfor-granted rules of self-censorship at work. Academy of Management Journal, 54, 461–488. https://doi.org/10.5465/ AMJ.2011.61967925 Dvir, T. E., Eden, D., Avolio, B. J., & Shamir, B. (2002). Impact of transformational leadership on follower development and performance: A field experiment. Academy of Management Journal, 45, 735–744. https://doi.org/10.2307/3069307 Facione, P. A. (1990). The Delphi report. Critical thinking: A statement of expert consensus for purposes of educational assessment and instruction. Millbrae, CA: California Academic Press.

Facione, P. A. (2011). Critical thinking: What it is and why it counts.

Millbrae, CA: Measured Reasons.

Facione, P. A., Facione, N. C., & Giancarlo, C. A. (1997). Professional judgement and the disposition toward critical thinking.

Millbrae, CA: California Academic Press.

Harrigan, A., & Vincenti, V. (2004). Developing higher-order thinking through an intercultural assignment: A scholarship of teaching inquiry project. College Teaching, 52, 113–120.

Hoyle, R. H. (2012). Handbook of structural equation modeling: Foundations and extensions. New York, NY: Guilford.

Jiang, J., & Yang, B. (2015). Roles of creative process engagement and leader-member exchange in critical thinking and employee creativity. Social Behavior and Personality, 43, 1217–1232. https://doi.org/10.2224/sbp.2015.43.7.1217 Ó 2018 Hogrefe Publishing

J. Jiang et al., Employees’ Critical Thinking and Voice Behavior

Jung, D. I. (2000). Transformational and transactional leadership and their effects on creativity in groups. Creativity Research Journal, 13, 185–195. https://doi.org/10.1207/ S15326934CRJ1302_6 Kelloway, E. K. (1996). Common practices in structural equation modeling. In C. L. Cooper & I. T. Robertson (Eds.), International review of industrial and organizational psychology (pp.

141–180). Chichester, UK: Wiley.

King, P. M., & Kitchener, K. S. (2004). Reflective judgment: Theory and research on the development of epistemic assumptions through adulthood. Educational Psychologist, 39, 5–18. https://doi.org/10.1207/s15326985ep3901_2 King, P. M., Kitchener, K. S., & Wood, P. K. (1994). Developing reflective judgment: Understanding and promoting intellectual growth and critical thinking in adolescents and adults. San Francisco, CA: Jossey-Bass.

Kish-Gephart, J. J., Detert, J. R., Treviño, L. K., & Edmondson, A. C. (2009). Silenced by fear: The nature, sources, and consequences of fear at work. Research in Organizational Behavior, 29, 163–193. https://doi.org/10.1016/j.riob.2009.07.002 Lam, C. F., & Mayer, D. M. (2013). When do employees speak up for their customers? A model of voice in a customer service context. Personnel Psychology, 3, 637–666. https://doi.org/ 10.1111/peps.12050 LePine, J. A., & Van Dyne, L. (1998). Predicting voice behavior in work groups. Journal of Applied Psychology, 83, 853–868. https://doi.org/10.1037/0021-9010.83.6.853 LePine, J. A., & Van Dyne, L. (2001). Voice and cooperative behavior as contrasting forms of contextual performance: Evidence of differential relationships with Big Five personality characteristics and cognitive ability. Journal of Applied Psychology, 86, 326–336. https://doi.org/10.1037/0021-9010.

86.2.326 Liang, J., Farh, C. C., & Farh, J. L. (2012). Psychological antecedents of promotive and prohibitive voice: A two-wave examination. Academy of Management Journal, 55, 71–92. https://doi.org/10.5465/amj.2010.0176 Liu, W., Zhu, R. H., & Yang, Y. K. (2010). I warn you because I like you: Voice behavior, employee identifications, and transformational leadership. The Leadership Quarterly, 21, 189–202. https://doi.org/10.1016/j.leaqua.2009.10.014 Morrison, E. W. (2014). Employee voice and silence. Annual Review of Organizational Psychology and Organizational Behavior, 1, 173–197. http://doi.org/10.1146/annurev-orgpsych-031413091328 Morrison, E. W., Wheeler-Smith, S. L., & Kamdar, D. (2011).

Speaking up in groups: A cross-level study of group voice climate and voice. Journal of Applied Psychology, 96, 183–191. https://doi.org/10.1037/a0020744 Nikolaou, I., Vakola, M., & Bourantas, D. (2008). Who speaks up at work? Dispositional influences on employees’ voice behavior.

Personnel Review, 37, 666–679.

Ó 2018 Hogrefe Publishing

41

Paul, R., & Elder, L. (2002). Critical thinking. Tools for taking charge of your learning and your life. Upper Saddle River, NJ: Prentice Hall.

Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40, 879–891. https://doi.org/10.3758/BRM.40.3.879 Ross, M. (1989). Relation of implicit theories to the construction of personal histories. Psychological Review, 96, 341–357. https://doi.org/10.1037/0033-295X.96.2.341 Seibert, S., Kraimer, M. L., & Crant, J. M. (2001). What do proactive people do? A longitudinal model linking proactive personality and career success. Personnel Psychology, 54, 845–874. https://doi.org/10.1111/j.1744-6570.2001.tb00234.x Van Dyne, L. V., Ang, S., & Botero, I. C. (2003). Conceptualizing employee silence and employee voice as multidimensional constructs. Journal of Management Studies, 40, 1359–1392. https://doi.org/10.1111/1467-6486.00384 Wang, A., Hsieh, H., Tsai, C., & Cheng, B. (2012). Does value congruence lead to voice? Cooperative voice and cooperative silence under team and differentiated transformational leadership. Management and Organization Review, 8, 341–370. https://doi.org/10.1111/j.1740-8784.2011.00255.x Wei, X., Zhang, Z. X., & Chen, X. P. (2015). I will speak up if my voice is socially desirable: A moderated mediating process of promotive versus prohibitive voice. Journal of Applied Psychology, 5, 1641–1652. https://doi.org/10.1037/ a0039046 Wu, J. B., Tsui, A. S., & Kinicki, A. J. (2010). Consequences of differentiated leadership in groups. Academy of Management Journal, 53, 90–106. https://doi.org/10.5465/AMJ.2010.

48037079 Yanchar, S. C., Slife, B. D., & Warne, R. (2008). Critical thinking in disciplinary practice. Review of General Psychology, 12, 265–281. https://doi.org/10.1037/1089-2680.12.3.265 Received July 12, 2015 Revision received June 17, 2017 Accepted June 21, 2017 Published online January 3, 2018

Ang Gao School of Management and Economics Beijing Institute of Technology Main Building 219 South Zhongguancun Street No 5 Beijing 100081 China gaoang@bit.edu.cn

Journal of Personnel Psychology (2018), 17(1), 33–41

Original Article

Is Emotional Engagement Possible in Emotionally Demanding Jobs?

The Role of Leader-Member Exchange (LMX) Long W. Lam,1 Angela J. Xu,2 and Raymond Loi1 1

Department of Management and Marketing, University of Macau, PR China

2

School of Management, Jinan University, Guangzhou, PR China

Abstract: Guided by work engagement theory and self-control theory, this study hypothesizes that among high leader-member exchange (LMX) employees, emotional job demands are positively related to emotional engagement and negatively related to subsequent intention to quit, whereas among low-LMX employees, emotional job demands are negatively related to emotional engagement and positively related to subsequent intention to quit. Using data collected from 182 resort and casino staff at two waves, we revealed that through emotional engagement, emotional job demands have a positive indirect effect on intention to quit for low-LMX employees but a negative indirect effect for high-LMX employees. The findings carry important implications for resource-based interventions aimed at increasing emotional engagement and decreasing intention to quit among employees confronting emotional job demands.

Keywords: emotional job demands, emotional engagement, leader-member exchange (LMX), intention to quit

In the new preface of her seminal book, Hochschild (2012, p. 5) gave the following description of emotionally demanding jobs.

“Then there are the ‘toxin handlers’ – complaints clerks, bankruptcy court personnel, bank officials dealing with home foreclosures, divorce lawyers, parking meter attendants, and those who specialize in firing workers. . . Their job is to deliver bad news and, often, to receive the brunt of customer frustration, despair, and rage. And finally there are those who don’t so much handle the bad news of others as face a real chance of experiencing pain or loss of their own: soldiers, firefighters. . .”

As this narrative vividly illustrates, emotionally demanding jobs require employees to handle emotionally charged situations (De Jonge, Le Blanc, Peeters, & Noordam, 2008), such as interacting with angry and aggressive customers (Grandey, Dickter, & Sin, 2004; Van Woerkom, Bakker, & Nishii, 2016). Emotional demands resulting from interaction with customers, as Zapf, Seifert, Schmutte, Mertini, and Holz (2001) suggested, represent a crucial aspect of emotion work. Studies have revealed that people become exhausted under repeated exposure to emotional job demands (e.g., Bakker & Demerouti, 2007; Bakker, Journal of Personnel Psychology (2018), 17(1), 42–52 https://doi.org/10.1027/1866-5888/a000194

Demerouti, & Euwema, 2005), and come to view quitting their jobs as the natural way out (e.g., Siong, Mellor, Moore, & Firth, 2006). For instance, hospitality sectors, in which employees are required to display positive emotions, studies have shown turnover to be particularly common for organizations (Robinson, Kralj, Solnet, Goh, & Callan, 2014).

Organizations generally expect employees to be emotionally engaged in handling emotionally demanding jobs, which require employees to be empathetic toward others’ feelings and to devote their affective energy to modifying their inner feelings to meet job requirements and provide good quality of service (Grandey, 2003). According to Kahn (1990), emotionally engaged individuals harness themselves to fulfill their role requirements, whereas emotionally disengaged individuals perform their work superficially by withdrawing from their work roles. Unlike physical and cognitive engagement, which involves investing “hand” and “head” in fulfilling job demands (Rich, LePine, & Crawford, 2010), emotional engagement refers to whether individuals are emotionally connected to their work and to others (such as clients) during their work performance.

When employees are emotionally engaged, they put their “hearts” into their work, which is the most desirable condition for emotional work (Ashforth & Humphrey, 1993).

However, whether this desirable condition can be met is unclear because not all employees are willing to completely Ó 2018 Hogrefe Publishing

L. W. Lam et al., LMX and Emotional Engagement

43

Figure 1. Conceptual model.

Leader-member exchange (LMX)

Emotional job demands

(+ under high-LMX) (- under low-LMX)

Emotional engagement

(-)

devote themselves to their work. Thus, it is of theoretical and practical significance to examine the boundary conditions that enable employees’ emotional engagement at work and subsequently prevent them from quitting in the face of emotional job demands. This study aims to contribute to this stream of research by studying emotional job demands of casino employees. Similar to most service works, casino employees are expected to maintain positive emotions in serving customers. Yet, in the casino context, employees are also confronted with emotionally charged situations involving angry and hostile gamblers who blame casinos for their misfortune. The demands to manage emotions and to deliver proper expressions are thus particularly salient among this group of workers (Brotheridge & Grandey, 2002; Zapf, 2002). As such, employees of casinos provide an ideal context to examine the relation between emotional job demands and emotional engagement.

Guided by work engagement and self-control theories (Kahn, 1990; Muraven & Baumeister, 2000), this study posits that leader-member exchange (LMX), which refers to the quality of emotion- and resource-based exchange relationships between supervisors and subordinates (Sparrowe & Liden, 1997), is an important job resource that enables employees to be emotionally engaged at emotionally demanding situations. LMX characterizes a supervisor-subordinate dyadic relationship as both long-term and stable. In addition to general social support that comes from peers to fulfill the need to belong (Schaufeli & Bakker, 2004), high-LMX subordinates can obtain a steady supply of resources such as information, consideration, and encouragement from supervisors (Liden, Sparrowe, & Wayne, 1997). In so doing, this study may shed new light on the boundary conditions under which the positive job demands-engagement relationship can be upheld (Crawford, LePine, & Rich, 2010; De Jonge et al., 2008) and enrich the current job demands-resources model (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001).

Second, performing emotion work requires employees to invest emotional energy in such a way that emotional engagement becomes the most important and relevant form of work engagement. As such, the relationship Ó 2018 Hogrefe Publishing

Intention to quit

between emotional job demands and emotional engagement is important for both theory and practice of emotion work (Crawford et al., 2010). This study highlights LMX as a potentially important job resource that could help organizations build an emotionally engaged workforce.

Third, prior research has provided evidence that employees are more likely to quit emotionally demanding jobs (Brotheridge & Grandey, 2002; Halbesleben & Buckley, 2004), which leads to higher replacement costs and lower service quality (Hausknecht, Trevor, & Howard, 2009).

By analyzing the interactive effects of emotional job demands and LMX on emotional engagement and turnover intention, our study carries the potential for resolving the puzzle of why some employees quit emotionally demanding jobs while others stay engaged. Figure 1 summarizes our hypothesized relationships.

Theoretical Background and Development of Hypotheses Work Engagement and Self-Control Theories The work engagement literature contends that individuals can enter a persuasive and persistent affective-cognitive state in which they are focused and attentive to their work and absorbed by the work roles they are asked to perform (Saks, 2006). To illustrate the connection between one’s self and role during such an affective-cognitive state, Kahn (1990, p. 700) referred to work engagement as “the simultaneous employment and expression of a person’s ‘preferred self’ in task behaviors that promote connections to work and to others.” Kahn (1990, p. 701) further stated that the opposite would happen for disengaged individuals: “personally disengaging means uncoupling self from role,” and that people hide their preferred selves and stop devoting energy to their tasks to become “impersonal or emotionally unexpressive.” Unlike engaged individuals who are psychologically present at work (Rothbard, 2001), disengaged employees are usually more detached Journal of Personnel Psychology (2018), 17(1), 42–52

44

and robotic (Hochschild, 1983). In addition to effective task performance, researchers have considered engagement a particularly salient factor in fulfilling a demanding job (Schaufeli & Bakker, 2004) and successfully comprehending a complex work role (Rothbard, 2001).

To understand when individuals can become engaged, we draw on self-control theory in order to highlight the role of resources such as LMX in handling emotionally demanding jobs (Muraven & Baumeister, 2000). Self-control theorists argue that considerable efforts are needed for almost any kind of activity. Self-control in this case operates much like a muscle so that exercise of self-control is likely to reduce the strength available for subsequent self-control.

Self-control and work engagement are closely related because individuals need to harness their self in their work roles in order to stay engaged, and it will be difficult for them to do so under low self-control. Thus, self-control theorists argue that the continuous efforts to exercise selfcontrol in order to be vigilant or engaged will dissipate over time unless individuals are furnished with a regular supply of resources. In this study, we posit the depletion of resources for self-control to be particularly fast if individuals are required to meet different demands simultaneously or successively, such as controlling emotions and delivering proper expressions in front of customers (Diestel & Schmidt, 2011). We thus expect that depending on the level of resources such as LMX, emotional job demands will be either positively or negatively related to emotional engagement.

The Moderating Role of LMX in Response to Emotional Job Demands According to LMX literature, a leader develops individualized relationships with each follower rather than establishing one universal relationship with every direct report (Sparrowe & Liden, 1997). Some followers are chosen by the leader to maintain high-LMX relationships because they are competent to fulfill leaders’ role expectations, and others are considered low-LMX members (Graen & Uhl-Bien, 1995). Leaders regard high-LMX members as “trusted assistants” and assign them more important and meaningful work. At the same time, leaders offer more valuable information (e.g., guidance), promotion opportunities, social support, and encouragement to this group of of followers (Xu, Loi, & Lam, 2015). By receiving these valuable resources, high-LMX members feel obliged to dedicate more efforts to their jobs and take on challenging assignments (Liao, Liu, & Loi, 2010). LMX scholars have often used social exchange to describe supervisor-subordinate relationships that are characterized by high levels of mutual trust, respect, and obligation (Loi, Mao, & Ngo, 2009).

Journal of Personnel Psychology (2018), 17(1), 42–52

L. W. Lam et al., LMX and Emotional Engagement

Within social exchange relationships, high-LMX members perceive a long-term and mature partnership with their leaders.

Confronted with high emotional job demands (i.e., angry and aggressive customers), employees are likely to feel or to act negatively. As Muraven and Baumeister (2000) suggested, dealing with aversive emotions such as anger requires individuals to exercise considerable self-control in order for them to change the way they will otherwise think or behave (i.e., being angry in front of angry customers). In doing so continuously, however, individuals demand a steady supply of resources. Otherwise, the strength to exercise self-control will be depleted and individuals will be less able to control their behaviors afterwards. As such, we argue that high LMX accompanied with a steady flow of guidance, consideration, and encouragement from supervisors (Liden et al., 1997) may allow employees to exercise more self-control in handling emotional job demands (i.e., high emotional engagement).

With high LMX, employees can presume to receive leaders’ continuous support in recovering their regulatory resource under high emotional demands. In turn, these employees will be less likely to conserve their regulatory resource necessary for self-control, so that we can expect them to be emotionally engaged in dealing with emotionally demanding customers (Hobfoll, 1989). On the other hand, when resources are not ensured, it can be difficult for employees to sustain long interactions with difficult customers in desirable emotions as the resource needed for self-control will be depleted quickly. As a result, lowLMX employees are likely to feel “tired” and emotionally disengaged in resolving emotional job demands repetitively and also feel difficult to be empathetic toward the feelings of others. Since low-LMX employees do not expect to receive ample support from their supervisors under high emotional demands, they may also conserve their limited regulatory resource by refraining from emotional engagement.

The above theoretical arguments can be further integrated with Kahn’s (1990) work engagement theory.

When compared with low-LMX members, high-LMX members are more likely to possess psychological availability, referring to an individual’s readiness to devote his or her energy (e.g., emotional energy) to performing a required role (Kahn, 1990). High-LMX employees receive more resources and emotional support from supervisors, and their supervisors also encourage them to adopt a cando attitude (Liao et al., 2010). Availability of resources increases their motivation to exert self-control during interactions with emotionally demanding customers without the worry of resource depletion. Thus, they are able to take on emotionally demanding jobs and manage their inner emotions in handling the emotionally charged situations Ó 2018 Hogrefe Publishing

L. W. Lam et al., LMX and Emotional Engagement

(i.e., less emotional dissonance; see Brotheridge & Grandey, 2002).

In addition, high-LMX employees tend to feel psychologically safe, referring to “feeling able to show and employ one’s self without fear of negative consequences to selfimage, status, or career” (Kahn, 1990, p. 708). Emotionally demanding jobs require employees to deal with adverse reactions associated with handling emotionally charged elements such as customer anger and distress. Feelings of psychological safety as a result of positive interactions with the supervisor necessitate the exertion of self-control as they may feel less threatened by such jobs. With long-term relationships with their supervisors that are fueled with mutual trust and respect (Liden et al., 1997), high-LMX members are more likely to take their work environment as controllable. They would view the emotionally demanding jobs as challenging task assignments and feel worthwhile and valuable when performing them, thus experiencing psychological meaningfulness (Kahn, 1990, p. 704).

For the abovementioned reasons, high-LMX members are more likely to appraise emotionally demanding jobs as positive and challenging opportunities to realize their work roles (Crawford et al., 2010). Therefore, we argue that emotional engagement of high-LMX members grows as emotional job demands increase. Consistent with these expectations, studies have shown that employees are more intrinsically motivated to perform jobs in which they have more control and support (Van Yperen & Hagedoorn, 2003; Van Yperen & Janssen, 2002). De Jonge et al.

(2008), for instance, revealed that when health care workers receive considerable emotional support from supervisors, they become more motivated when performing emotionally demanding jobs. However, unlike high-LMX members, leaders treat low-LMX members as “hired hands” who perform rudimentary and mundane tasks. Such tasks predispose low-LMX members to perform their jobs in compliance with contractual requirements and obligatory duties only (Loi, Ngo, Zhang, & Lau, 2011). They are likely to have a very different view of emotional job demands from high-LMX members.

First, leaders provide low-LMX employees only with what they need to perform their prescribed jobs (Graen & Uhl-Bien, 1995). Low-LMX members thus face daily work contexts that are characterized by less resource-based support and information flow from their direct supervisors (Loi, Chan, & Lam, 2014). Subordinates in these relationships do not anticipate instant emotional support from their supervisors and make no substantial emotional investment in such relationships. Thus, low-LMX employees may exhibit low readiness to dedicate their personal energy to emotionally demanding jobs (i.e., a lack of psychological availability). Without sufficient support from supervisors, they may also lack motivation in exercising self-control Ó 2018 Hogrefe Publishing

45

and may even tend to withdraw from emotionally charged encounters. Second, because low levels of trust and respect characterize a low-quality LMX relationship, subordinates may become more sensitive to the potentially negative repercussions of emotional job demands (i.e., a lack of psychological safety) and may refrain from investing their preferred selves in emotionally demanding jobs. Low psychological safety together with adverse interactions with customers may further prohibit low-LMX employees to exert self-control during emotionally demanding situations.

Because low-LMX employees lack psychological availability and safety, they may also find increasing emotional job demands unwarranted. They may even feel that little is expected of their selves and experience lack of meaningfulness from their jobs. Therefore, their motivation to deal with such demands diminishes, and they resort to disengaging (i.e., becoming passive and apathetic) rather than engaging.

Owing to the above reasons, we propose: Hypothesis 1: LMX moderates the relationship between emotional job demands and emotional engagement such that the relationship is positive among high-LMX employees and negative among low-LMX employees.

Emotional Job Demands and Intention to Quit Although some studies have shown that employees’ intention to quit intensifies when they face emotionally demanding jobs (Robinson et al., 2014), others have argued that job resources and work engagement suppress this intention (Bakker & Demerouti, 2007; Schaufeli & Bakker, 2004).

The following sections explain why different relations are expected between emotional job demands and intention to quit due to emotional engagement for high- and lowLMX employees.

As suggested previously, under high emotional job demands, we expect high-LMX employees to be more emotionally engaged. According to Kahn’s (1990) theory, work engagement is an affective-cognitive state in which a strong connection between one’s self and roles takes place, and engaged individuals feel more personally connected to others. Furthermore, after employees have invested considerable emotional energy in dealing with emotionally demanding jobs (Rich et al., 2010), they may develop stronger attachment to organizations (Allen & Meyer, 1990). Therefore, lower levels of quit intention are expected among these emotionally engaged labors.

For example, empirical studies have shown that psychological investment promotes intentions to remain in an organization (Arkes & Blumer, 1985). We expect that under high Journal of Personnel Psychology (2018), 17(1), 42–52

46

LMX, the positive influence of emotional job demands on emotional engagement will further manifest into lower turnover intention.

However, the opposite is predicted among low-LMX employees, as emotional job demands are expected to be negatively related to emotional engagement which is hypothesized to be negatively related to intention to quit.

The detachment of individual self from work role implies less connection to others and organizations so that increased intention to quit can be expected among this group of employees. In addition to the state of emotional disengagement, without supervisory resources, low-LMX employees are likely to experience reduced ability and motivation in handling emotional job demands (Brotheridge & Grandey, 2002). Such negative work attitudes have been linked consistently to increased intention to leave (Halbesleben & Buckley, 2004; Schaufeli & Bakker, 2004). Finally, because the role expectations of low-LMX employees differ drastically from those of highLMX members, the former may not welcome jobs with a high emotional demand because they lack supervisor support, encouragement, and appreciation (i.e., a low level of job resources). According to self-control theory (Muraven & Baumeister, 2000), individuals have a tendency to conserve self-control strength under low resources.

We can expect disengaged individuals to further withdraw their emotional energies from their work, and intention to quit subsequently increases (Lee & Ashforth, 1996). Consistent with our speculation, Schaufeli and Bakker (2004) found the reduction of job resources to be a contributing factor to high turnover intention among service workers, and found work engagement to play a significant role in accounting for such relationship. Hence, we propose: Hypothesis 2a: Among high-LMX employees, emotional job demands are negatively related to intention to quit through increased emotional engagement.

Hypothesis 2b: Among low-LMX employees, emotional job demands are positively related to intention to quit through decreased emotional engagement.

Method Participants and Procedure A two-wave questionnaire survey was administered to employees working in integrated resorts and casinos in Macau. As in most service industries, these employees were tasked with handling emotionally charged situations (e.g., angry gamblers) and maintaining positive emotions in front

Journal of Personnel Psychology (2018), 17(1), 42–52

L. W. Lam et al., LMX and Emotional Engagement

of customers (Taormina & Kuok, 2009). Majority of our respondents worked in casinos as dealers and slot operators so that they had frequent interactions with gamblers.

In Macau, where our data were collected, gamblers were said to release their negative emotions by cursing and confronting the dealers and other casino employees (e.g., Macau Daily, 2016; Wong & Lam, 2013). At Time 1, 200 employees participated in the study through a training course offered by a local university. The participants were informed that taking the questionnaire was voluntary and all of their responses would be kept strictly confidential.

The participants were asked to rate the measures of emotional job demands and LMX. Two weeks later (Time 2), the second questionnaires were administered to those who completed the first round. They rated their emotional engagement and intention to quit. One hundred eighty-two valid questionnaires were obtained, indicating an overall response rate of 91%.

Among the participants, 53.8% were male and 29.3% had a university degree or higher. The majority (57.2%) of our participants were 23–32 years old, and most of them (58.5%) had worked for their current companies for more than 3 years.

Measures Established scales with sufficient reliability were adopted to measure the study constructs. As all of the participants were Chinese, appropriate back-translation procedures (Brislin, 1970) were followed to develop the Chinese version of the questionnaires. Except for the measure of emotional job demands, all items were rated on a 6-point Likert-type scale anchored with endpoints (1 = strongly disagree; 6 = strongly agree).

Emotional Job Demands (Time 1) Four items originally developed by Van Veldhoven and Meijman (1994) and used in Bakker et al. (2005) study were used to assess how often our participants engaged in emotionally demanding tasks on a 6-point scale from 1 (= never) to 6 (= always). Sample items included “in your work do you deal with clients who incessantly complain, although you always do everything to help them?” and “do you have to deal with clients who do not treat you with the appropriate respect and politeness?” The α coefficient for this scale was .86.

Leader-Member Exchange (LMX; Time 1) The 7-item scale used by Graen and Scandura (1987) was adopted. One sample item read “my supervisor understands my job’s problems and needs.” The Cronbach’s α for this scale was .89.

Ó 2018 Hogrefe Publishing

L. W. Lam et al., LMX and Emotional Engagement

Emotional Engagement (Time 2) Employees’ emotional engagement was assessed on the 6-item scale used by Rich et al. (2010). Sample items included “I am enthusiastic in my job” and “I am excited about my job.” The scale’s reliability was .94.

Intention to Quit (Time 2) Rosin and Korabik’s (1991) 4-item scale was used to measure employees’ intention to quit. One sample item was “I am planning to leave my job within the next six months.” The Cronbach’s α was .85.

Control Variables Consistent with previous studies (e.g., De Jonge et al., 2008; Tzeng, 2002), organizational tenure and education were assessed as control variables.

Analytical Strategy First, a series of moderated regression analyses were conducted for emotional engagement to test our first hypothesis. The Johnson-Neyman technique was implemented to probe the upper and lower bounds of LMX for which the interaction effect (Emotional Job Demands LMX) would be statistically significant (Aiken & West, 1991; Nandkeolyar, Shaffer, Li, Ekkirala, & Bagger, 2014). Different from the traditional pick-a-point approach, in which the critical values of the moderator (usually ±1 SD) have been criticized as arbitrary, the Johnson-Neyman technique determines the critical values of the moderator (i.e., regions of significance), in which the focal predictor has a statistically significant effect on the dependent variable (Bauer & Curran, 2005; Hayes & Matthes, 2009; Preacher, Curran, & Bauer, 2006).

Second, Edwards and Lambert’s (2007) first-stage moderation model was used to examine whether emotional job demands were negatively associated with intention to quit via increased emotional engagement for high-LMX employees (i.e., Hypothesis 2a), and whether emotional job demands were positively related to intention to quit via decreased emotional engagement for lowLMX employees (i.e., Hypothesis 2b). Accordingly, two regression coefficients were obtained to calculate the moderated mediating effects. One was the moderated coefficient of emotional job demands on emotional engagement conditional on LMX. The other coefficient was obtained from regressing intention to quit on emotional engagement while controlling for emotional job demands. Finally, the significance of the conditional indirect effects was examined through bootstrapping to construct the Monte Carlo confidence intervals (Preacher & Selig, 2012).

Ó 2018 Hogrefe Publishing

47

Results Confirmatory Factor Analyses (CFA) Results CFAs were conducted to examine whether the respondents can clearly distinguish the study constructs, that is, emotional job demands, LMX, emotional engagement, and intention to quit. The results demonstrated that the fourfactor model fit the data well (w2 = 519.73, df = 183, p < .001; CFI = 0.94, IFI = 0.94, SRMR = 0.07), whereas the three-factor (combining emotional job demands and emotional engagement on one factor; w2 = 956.45, df = 186, p < .001; CFI = 0.86, IFI = 0.86, SRMR = 0.12) and the one-factor (consisting of these four variables; w2 = 1,975.15, df = 189, p < .001; CFI = 0.74, IFI = 0.75, SRMR = 0.17) models show poorer measurement fitness.

These results demonstrate the discriminant validity of our study constructs.

Hypotheses Testing Table 1 displays the descriptive statistics and correlations among our variables. The moderating regression test results are reported in Table 2. The first hypothesis proposes the moderating role of LMX on the relationship between emotional job demands and emotional engagement.

Emotional job demands and LMX were mean-centered before calculating their interaction term to avoid potential multicollinearity (Aiken & West, 1991). A moderating effect was evident if the beta coefficient of the interaction term was significant. Model 4 shows the interaction between emotional job demands and LMX was significant (β = 0.21, p < .01) and explained an additional 4% of the variance in emotional engagement.

The Johnson-Neyman technique was used to detect the regions of significance, wherein the direction and significance of the simple slopes were evaluated. As shown in Table 3, the regions of significance on LMX ranged from 1 to 3.13 (i.e., low LMX) and 5.05 to 6 (i.e., high LMX) so that simple slopes within these two regions are statistically significant. The pattern of the significant interaction effects at high and low values of LMX is plotted in Figure 2.

As shown, the relationship between emotional job demands and emotional engagement is positive (β = 0.28, p < .05) for high-LMX employees (i.e., 5.05) and negative (β = 0.14, p < .05) for low-LMX employees (i.e., 3.13). Thus, Hypothesis 1 is supported.

Hypotheses 2a and 2b were evaluated based on the conditional indirect effect of emotional job demands on intention to quit through emotional engagement for both

Journal of Personnel Psychology (2018), 17(1), 42–52

48

L. W. Lam et al., LMX and Emotional Engagement

Table 1. Means, standard deviations, and correlations among the variables

1. Education

Mean

SD

3.56

1.12

1

2

3

4

2. Organizational tenure

4.14

1.22

0.03

3. Emotional job demands

4.37

1.08

0.23**

0.00

(0.86)

4. LMX

3.46

0.90

0.02

0.02

0.26**

5

6

(0.89)

5. Emotional engagement

3.90

1.02

0.05

0.08

0.22**

0.46***

(0.85)

6. Intention to quit

3.03

1.30

0.02

0.18*

0.15+

0.44***

0.47**

(0.94)

Notes. n = 169 (missing data was handled with listwise deletion). Reliability coefficients in parentheses on the diagonal. Organizational tenure was measured in months according to five categories (1 = “6 or below,” 2 = “7–12,” 3 = “13–24,” 4 = “25–36,” and 5 = “37 or above”). Education was measured according to five levels (1 = “primary school,” 2 = “junior school,” 3 = “high school,” 4 = “junior college,” and 5 = “university or above”). +p < .10, *p < .05, **p < .01, ***p < .001 (two-tailed test).

Table 2. Multiple regressions: moderating effects Emotional engagement Model 3

Intention to quit

Model 1

Model 2

Model 4

Model 5

Model 6

Education

0.05

0.00

0.01

0.01

0.07

0.07

Organizational tenure

0.07

0.08

0.08

0.10

0.18*

0.15*

0.22**

0.10

0.06

0.17*

0.07

Control variables

Independent variables Emotional job demands Mediator Emotional engagement

0.45***

Moderator LMX

0.43***

0.42***

Interaction Emotional Job Demands LMX

0.21**

R2

0.01

0.05

0.22

0.27

0.06

0.25

Adjusted R2

0.00

0.04

0.21

0.25

0.04

0.23

F-statistic

0.66

3.05*

R2 change

0.04

F-statistic change

7.78**

11.86*** 0.17 36.35***

11.88*** 0.04 9.49**

3.50

13.73*** 0.19 41.82***

Notes. n = 169. LMX = leader-member exchange. Organizational tenure was measured in months according to five categories (1 = “6 or below,” 2 = “7–12,” 3 = “13–24,” 4 = “25–36,” and 5 = “37 or above”). Education was measured according to five levels (1 = “primary school,” 2 = “junior school,” 3 = “high school,” 4 = “junior college,” and 5 = “university or above”). Standardized coefficients are reported. *p < .05; **p < .01; ***p < .001 (two-tailed test).

high- and low-LMX employees. In Model 6 of Table 2, emotional engagement and intention to quit are shown to be negatively and significantly related (β = 0.45, p < .001). Together with the simple slope coefficients mentioned above, the 95% Monte Carlo confidence intervals were bootstrapped and plotted against LMX. Indirect effects are considered to be significant if the confidence intervals do not contain zero. As Figure 3 illustrates, the indirect effects are significant for any value of LMX below 3.13 (i.e., low LMX) and above 5.05 (i.e., high LMX). At high LMX values, the indirect effect of emotional job demands on intention to quit is negative and significant (indirect effect = 0.28 0.58 = 0.16, with a 95% CI of [ 0.3447, 0.0012]). However, the indirect effect is positive and

Journal of Personnel Psychology (2018), 17(1), 42–52

significant at low-LMX values (indirect effect = 0.13 0.58 = 0.08, with a 95% CI of [0.0003, 0.1692]).

Therefore, Hypotheses 2a and 2b are supported.

Discussion Consistent with Kahn’s (1990) work engagement and Muraven and Baumeister’s (2000) self-control theories, we found evidence supporting our hypotheses that emotional job demands and emotional engagement can be either positively or negatively related depending on the levels of LMX. Furthermore, we also found significant Ó 2018 Hogrefe Publishing

L. W. Lam et al., LMX and Emotional Engagement

Table 3. Conditional effect of emotional job demands on emotional engagement for a range of LMX values LMX

Simple slope

SE

t

p

1.00

0.60

0.18

3.39

.001

1.25

0.54

0.16

3.39

.001

1.50

0.49

0.14

3.38

.001

1.75

0.44

0.13

3.37

.001

2.00

0.38

0.12

3.33

.001

2.25

0.33

0.10

3.24

.001

2.50

0.27

0.09

3.09

.002

Emotional Engagement (Time 2)

49

5.5

5 LMX (Time 1)

4.5 4

Low

High

(3.13)

(5.05)

3.5

3 Low

High

Emotional Job Demands (Time 1)

2.75

0.22

0.08

2.81

.006

3.00

0.17

0.07

2.34

.020

3.13

0.14

0.07

1.96

.050

3.25

0.11

0.07

1.67

.097

3.50

0.06

0.07

0.86

.393

3.75

0.00

0.07

0.06

.953

0.8

4.00

0.05

0.08

0.61

.545

0.6

4.25

0.10

0.09

1.11

.267

4.50

0.16

0.11

1.49

.139

4.75

0.21

0.12

1.76

.080

5.05

0.28

0.14

1.96

.050

5.25

0.32

0.15

2.13

.035

5.50

0.37

0.17

2.25

.026

5.75

0.43

0.18

2.34

.020

6.00

0.48

0.20

2.42

.017

Conditional Indirect Effect

Figure 2. Leader-member exchange (LMX; Time 1) as a moderator of emotional job demands (Time 1) and emotional engagement (Time 2).

0.4 Point Estimate

0.2 0

Bootstrap 95% CI Upper Limit

-0.2

Bootstrap 95% CI Lower Limit

-0.4 -0.6 1.0 1.5 2.0 2.5 3.0 3.3 3.8 4.3 4.8 5.0 5.5 6.0

Note. The values making the relationship between emotional job demands and emotional engagement just positive and negative are given in bold.

conditional indirect effect of emotional job demands on intention to quit through emotional engagement. Specifically, emotional demands were positively and significantly related to intention to quit through emotional engagement for low-LMX employees. However, the opposite was found to hold for high-LMX employees, whose intentions to quit were actually less due to their heightened emotional engagement in performing emotionally demanding jobs.

These findings underscore the importance of LMX and emotional engagement in understanding emotional job demands, and carry important implications for the literature and practice regarding job demands and resources.

Implications for Theory and Future Research First, our results indicate why it is important to examine LMX as a valuable job resource for emotionally demanding jobs. Our findings suggest that without such important job resource, employees may negatively appraise emotional job demands. Such employees become less inclined to devote their affective energy to their jobs (i.e., emotionally disengaged), and their intention to quit subsequently intensifies. In contrast, since high-LMX subordinates receive Ă&#x201C; 2018 Hogrefe Publishing

LMX

Figure 3. Conditional indirect effect of emotional job demands on intention to quit through emotional engagement for a range of LMX values.

constant amount of reliable supervisory resources (e.g., supervisory guidance and experience sharing), they are more likely to handle emotional job demands positively with more emotional engagement and less intention to quit.

Second, these findings also help clarify the job demandsengagement relationship. Previous findings regarding the direct effect of job demands on work engagement have been mixed. Although most studies have found the relationship to be nonexistent or negative (Schaufeli & Bakker, 2004; Schaufeli, Taris, & Van Rhenen, 2008), others have reported positive relationships (Albrecht, 2015; Xanthopoulou, Bakker, Demerouti, & Schaufeli, 2007).

Based on the results of their meta-analyses, Crawford and his colleagues (2010) elucidated the importance of further examining the direct impact of job demands on work engagement and their indirect impact on distal outcomes that are relevant for organizational effectiveness. They further suggested that researchers look into the nature of job demands. By integrating the theoretical underpinnings of work engagement theory and self-control theory, this study is among the first to examine emotional job demands Journal of Personnel Psychology (2018), 17(1), 42â&#x20AC;&#x201C;52

50

and the moderating role of LMX. The results provide empirical support to answer the call of Crawford et al.

(2010) to disentangle the relationship among job demands, work engagement, and turnover intention (see also Xanthopoulou, Bakker, & Fischbach, 2013).

Third, although high turnover intention has long been a major issue in emotionally demanding jobs such as those in the hospitality sector (e.g., Robinson et al., 2014), this study revealed that not all employees facing emotionally demanding jobs exhibit an intention to quit. If employees are provided with steady amount of job resources embedded in high-LMX, they are more likely to have the “strength” to handle emotionally charged situations (Muraven & Baumeister, 2000), and to stay in the jobs to realize their potential. This study suggests that emotional engagement may play a key role in preventing employees’ intention to leave emotionally demanding jobs.

Study Limitations and Future Research The limitations of this study should be noted for future research. First, this study focused only on resorts and casinos in capturing emotionally demanding jobs. Future studies should consider emotionally demanding jobs outside the hospitality sector (e.g., nursing and firefighting) to enhance the robustness of this study’s findings.

Second, although the data collection procedure was divided into two periods, the potential threat of common method bias could not be completely ruled out because all of the study measures were rated by employees (Podsakoff, MacKenzie, & Podsakoff, 2012). Future research could consider collecting objective data such as actual turnover rather than intention to quit. Third, we have argued that LMX is a steady source of supervisory resources enhancing employees’ psychological availability and safety. Future research may consider directly measuring such mechanisms through which LMX is expected to moderate the relationship between emotional job demands and emotional engagement.

Finally, according to Kahn (1990) and May, Gilson, and Harter (2004), work engagement serves a purpose for employees beyond effective role performance, that is, greater fulfillment of the human spirit. Indeed, some individuals may find it fulfilling by introducing positive emotions into otherwise emotionally charged situations (e.g., marriage counseling). Adelmann (1995) argued that emotionally demanding jobs allow people to take advantage of their emotional intelligence by fostering positive interactive experiences with customers. It would therefore be worthy for future studies to examine whether emotional job demands, work meaningfulness, and accomplishment are connected through work engagement.

Journal of Personnel Psychology (2018), 17(1), 42–52

L. W. Lam et al., LMX and Emotional Engagement

Practical Implications First, managers and organizations should be aware that emotionally demanding jobs can be resource draining and tiring for employees. While we did not measure rest in our study, it is conceivable that periods of relief through proper work schedules are useful for employees to recoup from emotional job demands (Muraven & Baumeister, 2000). Extended periods of relief such as vacations are also useful means for employees to be away from emotionally draining jobs and to gain resources (Hobfoll & Shirom, 2001). Second, given the important role of LMX in cultivating emotional engagement and reducing turnover, organizations in the service sector should encourage, train, and provide necessary support for managers to develop high-quality relationships with their subordinates.

Third, managers should be aware of their important roles in affecting the way their followers appraise emotional job demands. For example, leaders should encourage their followers to take on emotional jobs and offer them sufficient support. In particular, leaders could give them clear guidance and share their experience in terms of how to handle demanding customers. Leaders can also recast emotional jobs in a more positive light (e.g., helping the customers) and cultivate a safe climate for their followers to handle emotional customers in a creative manner.

References Adelmann, P. K. (1995). Emotional labour as a potential source of job stress. In S. L. Sauter & L. R. Murphey (Eds.), Organizational risk factors for job stress (pp. 371–381). Washington, DC: American Psychological Association.

Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Thousand Oaks, CA: Sage.

Albrecht, S. L. (2015). Challenge demands, hindrance demands, and psychological need satisfaction. Journal of Personnel Psychology, 14, 70–79. https://doi.org/10.1027/1866-5888/ a000122 Allen, N. J., & Meyer, J. P. (1990). The measurement and antecedents of affective, continuance, and normative commitment to the organization. Journal of Occupational and Organizational Psychology, 63, 1–8. https://doi.org/10.1111/ j.2044-8325.1990.tb00506.x Arkes, H. R., & Blumer, C. (1985). The psychology of sunk cost.

Organizational Behavior and Human Decision Processes, 35, 124–140. https://doi.org/10.1016/0749-5978(85)90049-4 Ashforth, B. E., & Humphrey, R. H. (1993). Emotional labor in service roles: The influence of identity. Academy of Management Review, 18, 88–115. https://doi.org/10.5465/AMR.1993.

3997508 Bakker, A. B., & Demerouti, E. (2007). The job demands-resources model: State of the art. Journal of Managerial Psychology, 22, 309–328. https://doi.org/10.1108/02683940710733115 Bakker, A. B., Demerouti, E., & Euwema, M. C. (2005). Job resources buffer the impact of job demands on burnout.

Ó 2018 Hogrefe Publishing

L. W. Lam et al., LMX and Emotional Engagement

Journal of Occupational Health Psychology, 10, 170–180. https://doi.org/10.1037/1076-8998.10.2.170 Bauer, D. J., & Curran, P. J. (2005). Probing interactions in fixed and multilevel regression: Inferential and graphical techniques.

Multivariate Behavioral Research, 40, 373–400. https://doi.org/ 10.1207/s15327906mbr4003_5 Brislin, R. W. (1970). Back-translation for cross-cultural research.

Journal of Cross-Cultural Psychology, 1, 185–216. https://doi. org/10.1177/135910457000100301 Brotheridge, C. M., & Grandey, A. A. (2002). Emotional labor and burnout: Comparing two perspectives of “people work”. Journal of Vocational Behavior, 60, 17–39. https://doi.org/10.1006/ jvbe.2001.1815 Crawford, E. R., LePine, J. A., & Rich, B. L. (2010). Linking job demands and resources to employee engagement and burnout: A theoretical extension and meta-analytic test. Journal of Applied Psychology, 95, 834–848. https://doi.org/10.1037/ a0019364 De Jonge, J., Le Blanc, P. M., Peeters, M. C., & Noordam, H. (2008).

Emotional job demands and the role of matching job resources: A cross-sectional survey study among health care workers. International Journal of Nursing Studies, 45, 1460–1469. https://doi.org/10.1016/j.ijnurstu.2007.11.002 Demerouti, E., Bakker, A. B., Nachreiner, F., & Schaufeli, W. B. (2001). The job demands-resources model of burnout. Journal of Applied Psychology, 86, 499–512. https://doi.org/10.1037/ 0021-9010.86.3.499 Diestel, S., & Schmidt, K. H. (2011). Costs of simultaneous coping with emotional dissonance and self-control demands at work: Results from two German samples. Journal of Applied Psychology, 96, 643–653. https://doi.org/10.1037/a0022134 Edwards, J. R., & Lambert, L. S. (2007). Methods for integrating moderation and mediation: A general analytical framework using moderated path analysis. Psychological Methods, 12, 1–22. https://doi.org/10.1037/1082-989X.12.1.1 Graen, G. B., & Scandura, T. A. (1987). Toward a psychology of dyadic organizing. Research in Organizational Behavior, 9, 175–208.

Graen, G. B., & Uhl-Bien, M. (1995). Relationship-based approach to leadership: Development of leader-member exchange (LMX) theory of leadership over 25 years: Applying a multi-level multidomain perspective. The Leadership Quarterly, 6, 219–247. https://doi.org/10.1016/1048-9843(95)90036-5 Grandey, A. A. (2003). When “the show must go on”: Surface and deep acting as predictors of emotional exhaustion and service delivery. Academy of Management Journal, 46, 86–96. https:// doi.org/10.2307/30040678 Grandey, A. A., Dickter, D. N., & Sin, H. P. (2004). The customer is not always right: Customer aggression and emotion regulation of service employees. Journal of Organizational Behavior, 25, 397–418. https://doi.org/10.1002/job.252 Halbesleben, J. R., & Buckley, M. R. (2004). Burnout in organizational life. Journal of Management, 30, 859–879. https://doi. org/10.1016/j.jm.2004.06.004 Hausknecht, J. P., Trevor, C. O., & Howard, M. J. (2009). Unit-level voluntary turnover rates and customer service quality: Implications of group cohesiveness, newcomer concentration, and size. Journal of Applied Psychology, 94, 1068–1075. https://doi.org/10.1037/a0015898 Hayes, A. F., & Matthes, J. (2009). Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations. Behavior Research Methods, 41, 924–936. https://doi.org/10.3758/BRM.41.3.924 Hobfoll, S. E. (1989). Conservation of resources: A new attempt at conceptualizing stress. The American Psychologist, 44, 513–524. https://doi.org/10.1037/0003-066X.44.3.513

Ó 2018 Hogrefe Publishing

51

Hobfoll, S. E., & Shirom, A. (2001). Conservation of resources theory: Applications to stress and management in the workplace. In R. T. Golembiewski (Ed.), Handbook of organizational behavior (pp. 57–80). New York, NY: Marcel Dekker.

Hochschild, A. (1983). The managed heart: Communication of human feeling. Berkeley, CA: University of California Press.

Hochschild, A. (2012). The managed heart: Commercialization of human feeling (3rd ed.). Berkeley, CA: University of California Press.

Kahn, W. A. (1990). Psychological conditions of personal engagement and disengagement at work. Academy of Management Journal, 33, 692–724. https://doi.org/10.2307/256287 Lee, R. T., & Ashforth, B. E. (1996). A meta-analytic examination of the correlates of the three dimensions of job burnout. Journal of Applied Psychology, 81, 123–133. https://doi.org/10.1037/ 0021-9010.81.2.123 Liao, H., Liu, D., & Loi, R. (2010). Looking at both sides of the social exchange coin: A social cognitive perspective on the joint effects of relationship quality and differentiation on creativity.

Academy of Management Journal, 53, 1090–1109. https://doi. org/10.5465/AMJ.2010.54533207 Liden, R. C., Sparrowe, R. T., & Wayne, S. J. (1997). Leadermember exchange theory: The past and potential for the future.

In G. R. Ferris (Ed.), Research in personnel and human resources management (Vol. 15, pp. 47–119). Greenwich, CT: JAI. Loi, R., Chan, K. W., & Lam, L. W. (2014). Leader-member exchange, organizational identification, and job satisfaction: A social identity perspective. Journal of Occupational and Organizational Psychology, 87, 42–61. https://doi.org/10.1111/ joop.12028 Loi, R., Mao, Y., & Ngo, H. Y. (2009). Linking leader-member exchange and employee work outcomes: The mediating role of organizational social and economic exchange. Management and Organization Review, 5, 401–422. https://doi.org/10.1111/ j.1740-8784.2009.00149.x Loi, R., Ngo, H. Y., Zhang, L., & Lau, V. P. (2011). The interaction between leader-member exchange and perceived job security in predicting employee altruism and work performance. Journal of Occupational and Organizational Psychology, 84, 669–685. https://doi.org/10.1348/096317910X510468 Macau Daily. (2016, July 31) [A legislator’s comment on recent casino responses to gamblers’ attack on dealers] (original in Chinese). Retrieved from: http://www.macaodaily.com/html/ 2016-07/31/content_1110334.htm May, D. R., Gilson, R. L., & Harter, L. M. (2004). The psychological conditions of meaningfulness, safety and availability and the engagement of the human spirit at work. Journal of Occupational and Organizational Psychology, 77, 11–37. https://doi.org/10.1348/096317904322915892 Muraven, M., & Baumeister, R. F. (2000). Self-regulation and depletion of limited resources: Does self-control resemble a muscle? Psychological Bulletin, 126, 247–259. https://doi.org/ 10.1037/0033-2909.126.2.247 Nandkeolyar, A. K., Shaffer, J. A., Li, A., Ekkirala, S., & Bagger, J. (2014). Surviving an abusive supervisor: The joint roles of conscientiousness and coping strategies. Journal of Applied Psychology, 99, 138–150. https://doi.org/10.1037/a0034262 Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012).

Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 65, 539–569. https://doi.org/10.1146/annurevpsych-120710-100452 Preacher, K. J., Curran, P. J., & Bauer, D. J. (2006). Computational tools for probing interactions in multiple linear regression, multilevel modeling, and latent curve analysis. Journal of

Journal of Personnel Psychology (2018), 17(1), 42–52

52

Educational and Behavioral Statistics, 31, 437–448. https://doi. org/10.3102/10769986031004437 Preacher, K. J., & Selig, J. P. (2012). Advantages of Monte Carlo confidence intervals for indirect effects. Communication Methods and Measures, 6, 77–98. https://doi.org/10.1080/ 19312458.2012.679848 Rich, B. L., LePine, J. A., & Crawford, E. A. (2010). Job engagement: Antecedents and effects on job performance. Academy of Management Journal, 53, 617–635. https://doi.org/10.1080/ 19312458.2012.679848 Robinson, R. N., Kralj, A., Solnet, D. J., Goh, E., & Callan, V. (2014).

Thinking job embeddedness not turnover: Towards a better understanding of frontline hotel worker retention. International Journal of Hospitality Management, 36, 101–109. https://doi. org/10.1016/j.ijhm.2013.08.008 Rosin, H. M., & Korabik, K. (1991). Workplace variables, affective responses, and intention to leave among women managers.

Journal of Occupational Psychology, 64, 317–330. https://doi. org/10.1111/j.2044-8325.1991.tb00563.x Rothbard, N. P. (2001). Enriching or depleting? The dynamics of engagement in work and family roles. Administrative Science Quarterly, 46, 655–684. https://doi.org/10.2307/3094827 Saks, A. M. (2006). Antecedents and consequences of employee engagement. Journal of Managerial Psychology, 21, 600–619. https://doi.org/1108/02683940610690169 Schaufeli, W. B., & Bakker, A. B. (2004). Job demands, job resources, and their relationship with burnout and engagement: A multi-sample study. Journal of Organizational Behavior, 25, 293–315. https://doi.org/10.1002/job.248 Schaufeli, W. B., Taris, T. W., & Van Rhenen, W. (2008).

Workaholism, burnout, and work engagement: Three of a kind or three different kinds of employee well-being? Applied Psychology, 57, 173–203. https://doi.org/10.1111/j.1464-0597.

2007.00285.x Siong, Z. M. B., Mellor, D., Moore, K. A., & Firth, L. (2006).

Predicting intention to quit in the call centre industry: Does the retail model fit? Journal of Managerial Psychology, 21, 231–243. https://doi.org/10.1108/02683940610659579 Sparrowe, R. T., & Liden, R. C. (1997). Process and structure in leader-member exchange. Academy of Management Review, 22, 522–552. https://doi.org/10.5465/AMR.1997.9707154068 Taormina, R. J., & Kuok, A. C. H. (2009). Factors related to casino dealer burnout and turnover intention in Macau: Implications for casino management. International Gambling Studies, 9, 275–294. https://doi.org/10.1080/14459790903359886 Tzeng, H. M. (2002). The influence of nurses’ working motivation and job satisfaction on intention to quit: An empirical investigation in Taiwan. International Journal of Nursing Studies, 39, 867–878. https://doi.org/10.1016/S0020-7489(02)00027-5 Van Veldhoven, M., & Meijman, T. F. (1994). Het meten van psychosociale arbeidsbelasting met een vragenlijst: De vragenlijst beleving en beoordeling van de arbeid [The measurement of psychosocial strain at work: The experience and evaluation of work questionnaire]. Amsterdam, The Netherlands: NIA.

Journal of Personnel Psychology (2018), 17(1), 42–52

L. W. Lam et al., LMX and Emotional Engagement

Van Woerkom, M., Bakker, A. B., & Nishii, L. H. (2016). Accumulative job demands and support for strength use: Fine-tuning the job demands-resources model using conservation of resources theory. Journal of Applied Psychology, 101, 141–150. https://doi.org/10.1037/apl0000033 Van Yperen, N. W., & Hagedoorn, M. (2003). Do high job demands increase intrinsic motivation or fatigue or both? The role of job control and job social support. Academy of Management Journal, 46, 339–348. https://doi.org/10.2307/30040627 Van Yperen, N. W., & Janssen, O. (2002). Fatigued and dissatisfied or fatigued but satisfied? Goal orientations and responses to high job demands. Academy of Management Journal, 45, 1161–1171. https://doi.org/10.2307/3069431 Wong, I. L. K., & Lam, P. S. (2013). Work stress and problem gambling among Chinese casino employees in Macau. Asian Journal of Gambling Issues and Public Health, 3, 1–7. https:// doi.org/10.1186/2195-3007-3-7 Xanthopoulou, D., Bakker, A. B., Demerouti, E., & Schaufeli, W. B. (2007). The role of personal resources in the job demandsresources model. International Journal of Stress Management, 14, 121–141. https://doi.org/10.1037/1072-5245.14.2.121 Xanthopoulou, D., Bakker, A. B., & Fischbach, A. (2013). Work engagement among employees facing emotional demands: The role of personal resources. Journal of Personnel Psychology, 12, 74–84. https://doi.org/10.1027/1866-5888/a000085 Xu, A. J., Loi, R., & Lam, L. W. (2015). The bad boss takes it all: How abusive supervision and leader–member exchange interact to influence employee silence. The Leadership Quarterly, 26, 763–774. https://doi.org/10.1016/j.leaqua.2015.03.002 Zapf, D. (2002). Emotion work and psychological well-being: A review of the literature and some conceptual considerations.

Human Resource Management Review, 12, 237–268. https:// doi.org/10.1016/S1053-4822(02)00048-7 Zapf, D., Seifert, C., Schmutte, B., Mertini, H., & Holz, M. (2001).

Emotion work and job stressors and their effects on burnout.

Psychology & Health, 16, 527–545. https://doi.org/10.1080/ 08870440108405525

Received September 20, 2016 Revision received July 11, 2017 Accepted July 13, 2017 Published online January 3, 2018

Angela J. Xu School of Management Jinan University No. 601, Huangpu Avenue West Tianhe District Guangzhou PR China xujieangela@163.com

Ó 2018 Hogrefe Publishing

Practical applications for psychological measurement Contents and topics include

• Measuring Individual Differences in Implicit Learning With Artificial Grammar Learning Tasks: Conceptual and Methodological Conundrums

• Measuring Age-Related Differences in Using a Simple Decision Strategy: The Case of the Recognition Heuristic • Measuring the Zero-Risk Bias: Methodological Artefact or Decision Making Strategy?

• Assessing Suffering in Experimental Pain Models: Psychological and Psychophysiological Correlates • Is thhe Implicit Association Test for Aggressive Attitudes a Measure for Attraction to Violence or Traumatization?

• Measuring a Mastery Goal Structure Using the TARGET Framework: Development and Validation of a Classroom Goal Structure Questionnaire

• Parents’ and Teachers’ Opinions on Bullying and Cyberbullying Prevention: The Relevance of Their own Children’s or Students’ Involvement

• Intercultural Competence Development Among University Students From a Self-Regulated Learning Perspective: Theoretical Model and Measurement

Bernd Leplow (Editor)

Applied Psychological Measurement Zeitschrift für Psychologie, Vol. 225/1 2017, iv + 98 pp., large format US $49.00 / € 34.95 ISBN 978-0-88937-498-0 In behavioral science, measurement methods and theory are often discussed in isolation, separate from specific substantive research questions. This frequently leads to the development of tools that do not fit substantive research questions of current interest closely enough to provide convincing scientific answers. As a consequence, there is a need for the development of more specific theory-guided measurement devices, instruments, and as-

www.hogrefe.com

sociated statistical methods that are tailored to the research questions of interest.

This volume presents examples of this type of research-question-driven applied psychological measurement in three areas: individual differences in cognition, applied fields such as neuropsychology and trauma research, and educational psychology and competence research.

How to meet people’s increasing need to develop and manage their own lives and careers “A must read for all career development professionals and students alike. The Handbook of the Life Design is a new and essential resource for those working to improve career services in line with today’s challenges and conditions.”

Sara Santilli, PhD, writing in Career Convergence, February 2015

Laura Nota / Jérôme Rossier (Editors)

Handbook of Life Design

From Practice to Theory and from Theory to Practice 2015, vi + 298 pp., hardcover US $54.00 / € 38.95 ISBN 978-0-88937-447-8 Also available as eBook Our lives and careers are becoming ever more unpredictable. The “lifedesign paradigm” described in detail in this ground-breaking handbook helps counselors and others meet people’s increasing need to develop and manage their own lives and careers.

Life-design interventions, suited to a wide variety of cultural settings, help

www.hogrefe.com

individuals become actors in their own lives and careers by activating, stimulating, and developing their personal resources. This handbook first addresses life-design theory, then shows how to apply life designing to different age groups and with more at-risk people, and looks at how to train life-design counselors.

News and Announcements Awards for Outstanding Achievements as Authors and Reviewers 2017

The Journal of Personnel Psychology is delighted to announce the winners of the Best Paper Award and the Best Reviewers Award for 2017, as based on nominations by all action editors and subsequent review by a committee composed of members of the editorial team. Both awards are in principle “immaterial.” However, as a token of recognition the corresponding author of the best paper and the best reviewers will each receive a book or 1-year journal subscription of their choice from the Hogrefe program.

Best Paper Award 2017 The 2017 Best Paper Award goes to: Gläser, D., van Gils, & Van Quaquebeke, N. (2017). Pay-forperformance and interpersonal deviance: Competitiveness as the match that lights the fire. Journal of Personnel Psychology, 16, 77–90. https://doi.org/10.1027/1866-5888/ a000181

Ó 2018 Hogrefe Publishing

Best Reviewer Awards Our special thanks go out to all anonymous external reviewers, without whom publication of scientific research would not be possible. In an attempt to acknowledge at least a few outstanding achievements in this category, the Journal of Personnel Psychology distinguishes outstandingly helpful reviewers with its annual Best Reviewer Award.

For 2017, these awards go to Roy B. L. Sijbom (University of Amsterdam, The Netherlands), Despoina Xanthopoulou (Aristotle University of Thessaloniki, Greece), and Ingo Zettler (University of Copenhagen, Denmark).

Congratulations to the award winners!

Journal of Personnel Psychology (2018), 17(1), 53 https://doi.org/10.1027/1866-5888/a000200

News and Announcements Call for Proposals 2020 and 2021 Special Issues of the Journal of Personnel Psychology

The Journal of Personnel Psychology is seeking proposals from prospective guest editors for special issues to be published in the 2020 and 2021 volumes. Proposals will be evaluated by the team of associate editors, and the guest editor(s) will be responsible for overseeing the review process and selecting the content of the issue.

Successful proposals must have an overarching theme that fits the mission and scope of the Journal of Personnel Psychology. To give a few examples, the journal has in recent years published special issues on â&#x20AC;&#x153;Reward Managementâ&#x20AC;? (2017, guest edited by Conni H. Antoni, Xavier Baeten, Stephen J. Perkins, Jason D. Shaw, and Matti Vartiainen). â&#x20AC;&#x153;Gender Influences on Career Developmentâ&#x20AC;? (2015, guest edited by Annett HĂźttges and Doris Fay). â&#x20AC;&#x153;New Approaches to Job Demandsâ&#x20AC;? (2015, guest edited by Christian Korunka and Bettina Kubicek). â&#x20AC;&#x153;Insights Beyond g: Specific Cognitive Abilities at Workâ&#x20AC;? (2014, guest edited by Stefan Krumm, Lothar Schmidt-Atzert, and Anastasiya A. Lipnevich). â&#x20AC;&#x153;The Role of Norms in Virtual Workâ&#x20AC;? (2013, guest edited by Karin S. Moser and Carolyn M. Axtell). â&#x20AC;&#x153;Leading with integrityâ&#x20AC;? (2012, guest edited by Jeroen Stouten, Marius van Dijke und David De Cremer).

Journal of Personnel Psychology (2018), 17(1), 54 https://doi.org/10.1027/1866-5888/a000201

â&#x20AC;&#x153;Shared Leadershipâ&#x20AC;? (2010, guest edited by Craig Pierce, JĂźrgen Wegge, Julia Hoch, and Hans Jeppe Jeppesen).

In 2018, the journal will publish a special issue on â&#x20AC;&#x153;Applicant Behaviorâ&#x20AC;? (guest edited by Marise Ph. Born, Annemarie M. F. Hiemstra, and Janneke K. Oostrom).

Proposals should include the following information: Name(s) and contact details of guest editor(s).

Title of special issue.

Need and rationale for this special issue (max. 300 words).

Possible topics of inquiry (max. 300 words).

Time line (including preferred year of publication 2020 or 2021).

Editorial experience of the guest editor(s).

All proposals should be e-mailed to the Managing Editor, Petra GellĂŠri (jpp.editorial.office@gmail.com) no later than July 1, 2018.

Further information about the journal and free online sample issues are available here: www.hogrefe.com/j/jpp

Ă&#x201C; 2018 Hogrefe Publishing

Instructions to Authors Aims and Scope of Journal of Personnel Psychology: The journal welcomes excellent empirical and theoretical contributions to basic and applied research in personnel psychology and related methodology. Reviews are also welcome, as are replications of previous research. Articles deal with all fields in personnel psychology, such as personnel selection, performance measurement, motivation, leadership, organizational commitment, personnel development and training, new test developments, and job analysis. As many topics in personnel psychology are closely related to issues in other branches of psychology or, more generally, the social sciences and human resource management, the journal is open to contributions of an interdisciplinary nature.

Journal of Personnel Psychology publishes the following types of articles: Original Articles, Review Articles, Research Notes, Registered Reports, and Hybrid Registered Reports.

Manuscript submisson: All manuscripts should be submitted electronically at http://www.editorialmanager.com/jppsy Detailed instructions to authors are provided at http://www. hogrefe.com/j/jpp Copyright Agreement: By submitting an article, the author confirms and guarantees on behalf of him-/herself and any coauthors that the manuscript has not been submitted or published elsewhere, and that he or she holds all copyright in and titles to the submitted contribution, including any figures, photographs, line drawings, plans, maps, sketches, and tables, and that the article and its contents do not infringe in any way on the rights of third parties. The author indemnifies and holds harmless the publisher from any third-party claims.

The author agrees, upon acceptance of the article for publication, to transfer to the publisher the exclusive right to reproduce and distribute the article and its contents, both physically and in nonphysical, electronic, or other form, in the journal to which it has been submitted and in other independent publications, with no limitations on the number of copies or on the form or the extent of distribution. These rights are transferred for the duration of

copyright as defined by international law. Furthermore, the author transfers to the publisher the following exclusive rights to the article and its contents: 1. The rights to produce advance copies, reprints, or offprints of the article, in full or in part, to undertake or allow translations into other languages, to distribute other forms or modified versions of the article, and to produce and distribute summaries or abstracts.

2. The rights to microfilm and microfiche editions or similar, to the use of the article and its contents in videotext, teletext, and similar systems, to recordings or reproduction using other media, digital or analog, including electronic, magnetic, and optical media, and in multimedia form, as well as for public broadcasting in radio, television, or other forms of broadcast.

3. The rights to store the article and its content in machinereadable or electronic form on all media (such as computer disks, compact disks, magnetic tape), to store the article and its contents in online databases belonging to the publisher or third parties for viewing or downloading by third parties, and to present or reproduce the article or its contents on visual display screens, monitors, and similar devices, either directly or via data transmission.

4. The rights to reproduce and distribute the article and its contents by all other means, including photomechanical and similar processes (such as photocopying or facsimile), and as part of so-called document delivery services.

5. The right to transfer any or all rights mentioned in this agreement, as well as rights retained by the relevant copyright clearing centers, including royalty rights to third parties.

Online Rights for Journal Articles: Guidelines on authors’ rights to archive electronic versions of their manuscripts online are given in the document ‘‘Guidelines on sharing and use of articles in Hogrefe journals’’ on the journal’s web page at www.hogrefe.com/ j/jpp

September 2016

Cultural diversity – challenge and opportunity “It’s a book that we were all waiting for, and will be useful not only to psychologist practitioners and students, but also to stakeholders and policy makers in education.”

Bruna Zani, Professor of Social and Community Psychology, Department of Psychology, Alma Mater Studiorum-University of Bologna, Bologna, Italy; EFPA Executive Council Member

Alexander Thomas (Editor)

Cultural and Ethnic Diversity How European Psychologists Can Meet the Challenges 2018, x + 222 pp.

US $56.00 / € 44.95 ISBN 978-0-88937-490-4 Also available as eBook Culture and diversity are both challenge and opportunity. This volume looks at what psychologists are and can be doing to help society meet the challenges and grasp the opportunities in education, at work, and in clinical practice. The increasingly international and globalized nature of modern societies means that psychologists in particular face new challenges and have new opportunities in all areas of practice and research.

The contributions from leading European experts cover relevant intercultural issues and topics in areas as di-

www.hogrefe.com

verse as personality, education and training, work and organizational psychology, clinical and counselling psychlogy, migration and international youth exchanges.

As well as looking at the new challenges and opportunities that psychologists face in dealing with people from increasingly varied cultural backgrounds, perhaps more importantly they also explain and discuss how psychologists can deepen and acquire the intercultural competencies that are now needed in our professional lives.

The first structured resource for psychologists that combines mindfulness with character strenghts Ryan M. Niemiec

Mindfulness and Character Strengths A Practical Guide to Flourishing

2014, xx + 274 pp. + CD with meditation exercises US $39.80 / € 27.95 ISBN 978-0-88937-376-1 Also available as eBook At the core of this hands-on resource for psychologists and other practitioners, including educators, coaches, and consultants, is MindfulnessBased Strengths Practice (MBSP), the first structured program to combine mindfulness with the character strengths laid out in the VIA Institute’s classification developed by Drs. Martin E. P. Seligman and Christopher Peterson. This 8-session program systematically boosts awareness and application of character strengths – and so helps people flourish and lead more fulfilling lives.

The author’s vast experience working with both mindfulness and character strengths is revealed in his sensitive and clear presentation of the conceptual, practical, and scientific elements of this unique combined approach. It is not only those who are new to mindfulness or to character strengths who will appreciate the detailed primers on these topics in the first

www.hogrefe.com

section of the book. And the deep discussions about the integration of mindfulness and character strengths in the second section will benefit not just intermediate and advanced practitioners. The third section then leads readers step-by-step through each of the 8 MBSP sessions, including details of session structure and content, suggested homework, 30 practical handouts, as well as inspiring quotes and stories and useful practitioner tips. An additional chapter discusses the adaption of MBSP to different settings and populations (e.g., business, education, individuals, couples). The mindfulness and character strengths meditations on the accompanying CD support growth and development.

This highly accessible book, while primarily conceived for psychologists, educators, coaches, and consultants, is suitable for anyone who is interested in living a flourishing life.

How to be more persuasive and successful in negotiations “Presented in a concise and even entertaining style, this book succeeds in demonstrating how to negotiate successfully and fairly at the same time. A clear recommendation.”

Heinz Schuler, PhD, Hohenheim University, Stuttgart, Germany

Marco Behrmann

Negotiation and Persuasion

The Science and Art of Winning Cooperative Partners 2016, viii + 128 pp.

US $34.80 / € 24.95 ISBN 978-0-88937-467-6 Also available as eBook Scientific research shows that the most successful negotiators analyze the situation thoroughly, self-monitor wisely, are keenly aware of interpersonal processes during the negotiation – and, crucially, enter negotiations with a fair and cooperative attitude. This book is a clear and compact guide on how to succeed by means of such goal-oriented negotiation and cooperative persuasion. Readers learn models to understand and describe what takes place during negotiations, while numerous figures, charts, and checklists clearly summarize effective

www.hogrefe.com

strategies for analyzing context, processes, competencies, and the impact of our own behavior. Real-life case examples vividly illustrate the specific measures individuals and teams can take to systematically improve their powers of persuasion and bargaining strength. The book also describes a modern approach to raising negotiation competencies as part of personnel development, making it suitable for use in training courses as well as for anyone who wants to be a more persuasive and successful negotiator.