Journal of Personnel Psychology

Volume 19 / Number 1 / 2020

Journal of

Personnel Psychology Editor-in-Chief Jonas W. B. Lang Managing Editor Petra Gelléri Associate Editors Tanja Bipp Ilke Inceoglu Anita Keller Cornelia Niessen Deborah Powell Ingo Zettler Xin-An Zhang

New Developments in HEXACO Personality Research Reinout E. De Vries / Michael C. Ashton / Kibeom Lee (Editors)

Advances in HEXACO Personality Research (Series: Zeitschrift für Psychologie - Vol. 227/3) 2019, iv / 70 pp., large format US $49.00 / € 34.95 ISBN 978-0-88937-567-3 The HEXACO (Honesty-Humility, Emotionality, eXtraversion, Agreeableness, Conscientiousness, Openness) six-factor model of personality structure has been in use for over twenty years and offers a convincing alternative to the five-factor model.

how past adjective selection has impacted on personality theory, the volume also presents applications of the model and new approaches to measurement, including an extended twin family study examining genetic and environmental variance and a look at the use of behavior This collection of contributions from cues in a gamified online environaround the world demonstrates that ment. The volume also presents research into the model is very much what is probably the most comprealive. Beginning with a historical hensive meta-analysis of the psyoverview of the early lexical studies chometric properties of the HEXACO of personality structure exploring domain scales.

Contents and topics include • New Developments in HEXACO Personality Research • On the Curious History of the Big Six: Variable Selection and “Moral Exclusion” in the Formation of Fundamental Personality Models • The HEXACO Model in Education and Work • Meta-Analytic Investigations of the HEXACO Personality Inventory (-Revised) • The Nature and Nurture of HEXACO Personality Trait Differences

www.hogrefe.com

• Gamified Personality Assessment: Virtual Behavior Cues of HonestyHumility • Investigating Relative and Absolute Methods of Measuring HEXACO Personality Using Self- and Observer Reports • Effects of HEXACO Traits and Experimental Provocation on Aggression

Journal of

Personnel Psychology Volume 19/Number 1 /2020

Editor-in-Chief

Jonas W. B. Lang, Department of Human Resource Management and Organizational Psychology, Ghent University, Henri Dunantlaan 2, 9000 Ghent, Belgium, Tel. +32 9 264-6452, Fax +32 9 264-6494, E-mail: jonas.lang@ugent.be

Managing Editor

Petra Gelléri, Department of Human Resource Management and Organizational Psychology, Ghent University, Henri Dunantlaan 2, 9000 Ghent, Belgium, E-mail: jpp.editorial.office@gmail.com

Associate Editors

Tanja Bipp, University of Heidelberg, Germany Ilke Inceoglu, University of Exeter, UK Anita Keller, University of Groningen, The Netherlands Cornelia Niessen, University of Erlangen-Nuremberg, Germany Deborah Powell, University of Guelph, Canada Ingo Zettler, University of Copenhagen, Denmark Xin-An Zhang, Shanghai Jiao Tong University, China

Editorial Board

Gerhard Blickle, University of Bonn, Germany Janine Bosak, Dublin City University, Ireland Neil Christiansen, Central Michigan University, USA Brian Connelly, University of Toronto Scarborough, Canada Filip De Fruyt, Ghent University, Belgium Reinout de Vries, VU Amsterdam, The Netherlands Patrick Dunlop, University of Western Australia, Australia Jörg Felfe, Helmut Schmidt University, Germany Zvonimir Galic, University of Zagreb, Croatia Ian Gellatly, University of Alberta, Canada Richard Goffin, University of Western Ontario, Canada Zen Goh, Monash University, Australia Martin Götz, University of Zurich, Switzerland Peter Harms, University of Alabama, USA Alex Haslam, University of Queensland, Australia Verena Haun, University of Mainz, Germany Stefan Höft, University of Applied Labour Studies of the Federal Employment Services (HdBA), Germany Rudolf Kerschreiter, FU Berlin, Germany Martin Kleinmann, University of Zurich, Switzerland Cornelius König, Saarland University, Germany Franciska Krings, University of Lausanne, Switzerland Stefan Krumm, FU Berlin, Germany Kibeom Lee, University of Calgary, Canada Bernd Marcus, University of Rostock, Germany Klaus Melchers, University of Ulm, Germany John P. Meyer, University of Western Ontario, Canada Karin Moser, London South Bank University, UK Klaus Moser, FAU Erlangen-Nuremberg, Germany

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, 361 Newbury Street, 5th Floor, Boston, MA 02115, USA, Phone (857) 880-2002, 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

© 2020 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 2020: Institutions – from US $308.00/€232.00 (print only; pricing for online access can be found in the journals catalog at hgf.io/journalscatalog); Individuals – US $164.00/€118.00 (print & online). 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.

Peter Muck, Federal Employment Agency, Germany Patrick Mussel, FU Berlin, Germany Ioannis Nikolaou, Athens University of Economics and Business, Greece Janneke K. Oostrom, VU Amsterdam, The Netherlands Deirdre O’Shea, University of Limerick, Ireland Carolin Palmer, University of Gießen, Germany Thomas Rigotti, University of Mainz, Germany J. Malte Runge, University of Ghent, Belgium Ann Marie Ryan, Michigan State University, USA Jesus F. Salgado, University of Santiago de Compostela, Spain Niclas Schaper, University of Paderborn, Germany Tabea Scheel, University of Flensburg, Germany Birgit Schyns, NEOMA Business School, Reims, France Roy B. L. Sijbom, University of Amsterdam, The Netherlands Thomas Staufenbiel, University of Osnabrück, Germany H. Canan Sümer, Middle East Technical University, Turkey Robert Tett, University of Tulsa, USA Sjir Uitdewilligen, Maastricht University, The Netherlands Christian Vandenberghe, HEC Montreal, Canada Rolf van Dick, Goethe University of Frankfurt, Germany Tim Vantilborgh, VU Brussels, Belgium Chockalingam Viswesvaran, Florida International University, USA S. Arzu Wasti, Sabanci University, Turkey Serena Wee, University of Western Australia, Australia Oliver Weigelt, University of Rostock, Germany Bettina S. Wiese, RWTH Aachen, Germany Annika Wilhelmy, University of Zurich, Switzerland Hans-Georg Wolff, University of Cologne, Germany

2018 Impact Factor 1.051, 5-year Impact Factor 1.960, Journal Citation Reports (Clarivate Analytics, 2019)

Journal of Personnel Psychology (2020), 19(1)

© 2020 Hogrefe Publishing

Contents Editorial

Timely and to the Point: Expectations for Articles and Reviews at the Journal of Personnel Psychology Jonas W. B. Lang

1

Original Articles

The Influence of Tattoo Content on Perceptions of Employment Suitability Across the Generational Divide Michael J. Tews, Kathryn Stafford, and Ethan P. Kudler

4

Staying Quiet or Speaking Out: Does Peer Reporting Depend on the Type of Counterproductive Work Behavior Witnessed?

Nathan A. Bowling, Brian D. Lyons, and Gary N. Burns

14

The Costs of Working Too Hard: Relationships Between Workaholism, Job Demands, and Prosocial Organizational Citizenship Behavior Guido Alessandri, Evelina De Longis, Enrico Perinelli, Cristian Balducci, and Laura Borgogni

24

Are All Challenges Equal? Goal Orientations and Their Relationship With Private and Public Challenging Job Experiences Roy B. L. Sijbom, Bernd Carette, and Nicoletta G. Dimitrova

33

Research Note

Judging Performance – General Mental Ability and the Convergence of Operational Performance Ratings Andrew B. Speer

44

Erratum

Correction to Bal and Vossaert (2019)

49

News and Announcements

Awards for Outstanding Achievements as Authors and Reviewers 2019

50

© 2020 Hogrefe Publishing

Journal of Personnel Psychology (2020), 19(1)

Editorial

Timely and to the Point Expectations for Articles and Reviews at the Journal of Personnel Psychology Jonas W. B. Lang1,2, Editor-in-Chief Department of Human Resource Management and Organizational Psychology, Ghent University, Ghent, Belgium

1

Business School, University of Exeter, UK

2

The COVID-19 crisis has triggered what is likely the most extensive work reorganization process ever. Organizations have to deal with high levels of uncertainty as well as unprecedented demands on both technical and organizational infrastructure, and employees face numerous issues surrounding job (in)security, work–family issues, and remote working. The topics covered by the Journal of Personnel Psychology thus once again prove extremely relevant to modern working life.

The Journal of Personnel Psychology was originally launched as the German-language Zeitschrift für Personalpsychologie in 2002 and switched over to English in 2010. While the journal is relatively new for an academic journal, it extends a long tradition of publications on personnel selection, personnel psychology, vocational psychology, and applied psychology in central Europe in an international context.

In recent years, the Journal of Personnel Psychology has established itself as a solid international journal in the domain of personnel psychology, organizational psychology, and work psychology. In contrast to most other journals in this field, the Journal of Personnel Psychology focuses on publishing shorter reviews, articles, and reports.

I would like to thank Bernd Marcus for his excellent leadership as Editor-in-Chief of this journal over the past 4 years. He not only assembled a motivated team of young and established scholars but also implemented a set of innovative changes such as registered and hybrid registered reports. In January 2020, I took over the Editor-inChief role from Bernd for new incoming submissions and have since been working with our excellent team including our Associate Editors Tanja Bipp, Ilke Inceoglu, Anita Keller, Cornelia Niessen, Deborah Mary-Jane Powell, XinAn Zhang, and Ingo Zettler, our Managing Editor Petra Gelléri, and our Editorial Board. © 2020 Hogrefe Publishing

In this editorial, I briefly describe the scope and mission of the journal as well as our publishing process, and I discuss a couple of specific challenges for authors and reviewers that result from the somewhat shorter articles the journal publishes.

Scope, Mission, and Publishing Process The journal welcomes excellent empirical and theoretical contributions to basic and applied research in personnel psychology and related methodology. Reviews and theoretical contributions are also welcome. Articles deal with all fields in personnel psychology, including 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.

There are three categories of submission: original articles (with a maximum length of 6,000 words), research notes (with a maximum length of 2,500 words), and review articles (with a maximum length of 8,000 words); all counts include references but exclude tables and figures.

Articles submitted to the journal will initially be screened for general fit with the scope and mission of the journal and for adherence to the publication manual of the American Psychological Association (APA). The initial screening process also includes a check for the questions Journal of Personnel Psychology (2020), 19(1), 1–3 https://doi.org/10.1027/1866-5888/a000259

2

on data transparency. The journal further follows APA’s policies pertaining to duplicate and piecemeal publication of original data. Accordingly, authors must disclose other publications planned or under review on the basis of the same original dataset and should generally be as transparent as possible. The core goal is to enable the reviewing team to adequately evaluate the unique contribution of the submission. Articles that do not pass the initial screening process are generally sent back to the authors without a full review with a brief letter from myself, the managing editor, or one of the associate editors. This letter includes the core reasons why the article has not passed the initial screening process.

The manuscripts that have passed the initial screening process are assigned to an action editor – myself, one of the associate editors, or a guest editor – who will send out the article to two or three reviewers. The reviewers have 30 days to evaluate the article and are asked to provide feedback to the authors and also to the action editor, and a publication recommendation (reject, revise and resubmit, or accept). The action editor makes an informed decision based on the reviews and communicates the decision to the authors.

Expectations for Articles The length restrictions on submissions to the Journal of Personnel Psychology have a number of implications for articles submitted and ultimately published in the journal.

A common expectation in the field is that empirical articles simultaneously make a theoretical and an empirical contribution. While contributions in both areas may increase the visibility of an article and the editorial team may weight both aspects in its decision process, there is no requirement for articles published in the Journal of Personnel Psychology to contribute in both areas. Articles can also simply rigorously test existing theory and expand the field’s knowledge about an important phenomenon or assumption.

We also publish null findings or negative findings as long as the study has been rigorously conducted. In particular, the journal is interested in articles on field interventions and quasiexperimental studies in field settings.

Further, the journal is interested in methodological contributions and scale development articles that are of particular relevance to the field of personnel psychology like, for instance, articles that develop novel methods for correcting for range restriction or articles developing new job performance measures. As a result of the shorter format of the articles in the journal, authors are generally encouraged to provide a more focused and specific Journal of Personnel Psychology (2020), 19(1), 1–3

Editorial

contribution. The shorter format should especially make it easier for young scholars to publish their work.

The most important criterion for empirical publications in the Journal of Personnel Psychology is generally the quality of the research. What is considered high-quality research certainly varies for different research fields.

However, there are three characteristics of most highquality work that I especially want to highlight: The first characteristic is the quality of the research design. The typical challenge in personnel psychology is to balance the rigor of the design with the applied relevance and the degree to which a particular type of design can be implemented in a particular setting. For instance, an online study may allow researchers to easily introduce experimental manipulations but lack applied relevance because of the artificial and non-natural setting. In contrast, a quasiexperimental field study may be highly relevant because of its applied nature but it can be difficult to exclude potential alternative explanations for an observed effect, depending on the exact circumstances in the organization.

In general, the journal prefers quasiexperimental, experimental, and longitudinal research, and multisource over single-source data. We have no policy suggesting that crosssectional studies from a single source should not be considered. The decision depends on the action editor and the reviewers of the specific paper. However, the bar for making a meaningful contribution is naturally higher for papers of this type than for other papers.

A second characteristic of high-quality studies is a sufficient sample size to test a particular theory or model.

We ask authors to refrain from submitting small and underpowered studies. Likewise, we also caution authors to not submit overly complex statistical models that cannot rigorously be described and tested. A general guideline for authors is to think about how likely it would be that their findings could be replicated in an independent second or third study. One tool to avoid overly complex and underpowered studies can be power analyses. However, it is important for authors to be aware that power analyses only help in the planning of a study and not once the data has been collected. The reason is that power analyses are typically conducted by using a priori or typical estimates of model characteristics and effect sizes to simulate a series of hypothetical datasets. Power is simply the percentage of these datasets in which a particular effect of interest is significant. This provides no insights on power when the data are already collected because power is then simply a direct function of the p value of the study. This value thus does not provide any new information beyond the p values of the data (Gelman, 2019; Hoenig & Heisey, 2001; Yuan & Maxwell, 2005) – although this statistic can be a useful metric to illustrate the uncertainty in datasets (Bliese & Wang, 2019). © 2020 Hogrefe Publishing

Editorial

When authors tackle issues pertaining to model complexity and sample size, a useful approach is to imagine a specific dataset as a dataset that is drawn from a large population of potential datasets and to ask questions like: To what degree is it likely that the effects and pattern of results in my data are a specific random pattern in my sample or are a general effect that is likely to emerge in other independent samples?

The third and final element of a high-quality study is the quality of the measurement instruments. There has long been a trend for increasingly short measures. However, there is evidence that shorter measures have less quality because they tend to compromise on either reliability or bandwidth (Smith, McCarthy, & Anderson, 2000). We accordingly encourage authors to carefully weigh the time their participants can devote and the quality of the measurement. As mentioned earlier, the Journal of Personnel Psychology is also interested in improving the measurement quality by publishing innovative articles on scale development.

We encourage authors to provide enough methodological detail so that the editorial team can make an informed decision. In evaluating the amount of methodological detail necessary, it can be useful to consult the APA manual and methodological checklists (Eby et al., 2020).

Expectations for Reviews One goal of the Journal of Personnel Psychology is to provide developmental peer reviews that help authors to improve their work – including in cases where the article reviewed is not accepted for the journal. In line with the brief format of the journal, we ask our peer reviewers to focus on the most crucial elements of the submission that need to be improved by focusing on providing 3–10 core comments that capture the essence of what needs to be improved. Furthermore, peer reviews should not only provide comments on what may be missing in the article but also help authors to cut elements and sharpen the contribution so that the articles fit into the short format of the journal.

© 2020 Hogrefe Publishing

A Word of Thanks I would like to thank again Bernd Marcus for his contribution to the journal and also the current Associate Editors, our Managing Editor Petra Gelléri, and the Editorial Board members and ad hoc reviewers for their enthusiastic work for the journal. Last but not least, I want to thank our authors. The quality of a journal is primarily driven by the quality of the work that is submitted. Please keep submitting your best work to our journal.

References Bliese, P. D., & Wang, M. (2019). Results provide information about cumulative probabilities of finding significance: Let’s report this information. Journal of Management, 014920631988690. https:// doi.org/10.1177/0149206319886909 Eby, L. T., Shockley, K. M., Bauer, T. N., Edwards, B., Homan, A. C., Johnson, R., . . . Oswald, F. L. (2020). Methodological checklists for improving research quality and reporting consistency. Industrial and Organizational Psychology, 13(1), 76–83. https://doi. org/10.1017/iop.2020.14 Gelman, A. (2019). Don’t calculate post-hoc power using observed estimate of effect size. Annals of Surgery, 269(1), e9–e10. https://doi.org/10.1097/SLA.0000000000002908 Hoenig, J. M., & Heisey, D. M. (2001). The abuse of power: The pervasive fallacy of power calculations for data analysis.

American Statistician, 55, 19–24. https://doi.org/10.1198/ 000313001300339897 Smith, G. T., McCarthy, D. M., & Anderson, K. G. (2000). On the sins of short-form development. Psychological Assessment, 12(1), 102–111. https://doi.org/10.1037//1040-3590.12.1.102 Yuan, K.-H., & Maxwell, S. (2005). On the post hoc power in testing mean differences. Journal of Educational and Behavioral Statistics, 30(2), 141–167. https://doi.org/10.3102/ 10769986030002141 Published online July 3, 2020 Jonas W. B. Lang Department of Human Resource Management and Organizational Psychology Ghent University Henri Dunantlaan 2 9000 Ghent Belgium jonas.lang@ugent.be

Journal of Personnel Psychology (2020), 19(1), 1–3

Original Article

The Influence of Tattoo Content on Perceptions of Employment Suitability Across the Generational Divide Michael J. Tews1, Kathryn Stafford2, and Ethan P. Kudler1 School of Hospitality Management, Pennsylvania State University, University Park, PA, USA

1

Department Human Sciences, Ohio State University, Columbus, OH, USA

2

Abstract. The present study extends research on tattoos and employment suitability by examining the extent to which the effects of tattoos on perceived competence and hiring recommendations are contingent upon the generational cohort of hiring managers, tattoo content, and candidate gender. Respondents evaluated hypothetical candidates in a between-subjects design framework. The results demonstrated that candidates with light (more innocent) tattoos were rated lower in perceived competence than candidates with dark (more threatening) tattoos or no tattoos. Regarding hiring recommendations, there were more nuances. Millennial hiring managers viewed candidates with light tattoos more positively than did older managers, and this generational difference was more pronounced for male candidates. Moreover, older hiring managers viewed male candidates with no tattoos more positively than millennials.

Keywords: tattoos, employment suitability, millennials, between-subjects experimental design, hypothetical job candidates

Without question, tattoos have emerged from the taboo closet into the mainstream. In a recent survey of individuals across 18 countries, approximately 38% of the respondents had at least one tattoo (Tennent, 2018). The three most heavily tattooed countries were Italy, Sweden, and the US with 48%, 47%, and 46%, respectively, of the respondents adorned with body art. At the bottom of the list were France, Germany, and Greece with 36%, 36%, and 35%, respectively, of the respondents being tattooed.

Whereas tattoos were once characterized as a deviant art form that was most popular among bikers, prisoners, and military personnel (DeMello, 1995; Larsen, Patterson, & Markham, 2014), the prevalence of tattoos today is much more widespread. While rebellion was once believed to be a primary reason for tattoo adornment, esthetic and uniqueness enhancing motivations are more and more common (Tiggemann & Golder, 2006; Tiggemann & Hopkins, 2011). In increasing numbers, tattoos appear to be an important component of a person’s self-expression.

As tattoos have become more popular, the question arises whether they have been accepted, accommodated, or embraced in the workplace where it is estimated that 45 million individuals in the US workforce have at least one tattoo (Schouten, 2016).

Journal of Personnel Psychology (2020), 19(1), 4–13 https://doi.org/10.1027/1866-5888/a000234

On one hand, there is evidence that tattoos are not desired in the workplace, in line with the contention of Larsen et al. (2014) that tattoos remain a stigmatized and stigmatizing art form. For example, Miller, McGlashan Nicols, and Eure (2009) found that individuals prefer coworkers without tattoos. Timming’s (2015) interviews with recruiters highlighted that tattoos would likely preclude a candidate from getting a job. Furthermore, recent research by Timming, Nickson, Re, and Perrett (2017) found that those with tattoos are perceived as less suitable for employment, and Baumann, Timming, and Gollan (2016) demonstrated that consumers prefer employees without tattoos. This leaning toward nontattooed employees may persist for a number of reasons, including their historical association with violence, aggression, out-group membership, and nonconformity with a company’s brand image.

On the other hand, additional research has shown that tattoos appear to no longer have a detrimental effect on employees. French, Maclean, Robins, Sayed, and Shiferaw (2016) and French, Mortensen, and Timming (2019) found that the earnings of tattooed employees were at least as great as those of nontattooed employees. Furthermore, it was found in both of these studies that tattooed individuals were at least as likely to obtain employment as © 2020 Hogrefe Publishing

M. J. Tews et al., Tattoos and Employment Suitability

nontattooed individuals. Because those with tattoos are less likely to be outliers than they once were, employers may be less apt to consider tattoo status out of necessity rather than preference. In tight labor markets, employers may not have the latitude to take into account one’s tattoo status when it may be challenging to recruit employees who possess the fundamental knowledge, skills, and abilities for a given position. In a related vein, because tattoos have become more normalized, hiring managers could be desensitized to the presence of tattoos on job candidates. Moreover, on a positive side, some hiring managers could embrace tattoos for their esthetic value and the creativity and openness they believe that those adorned with tattoos possess. Tattoos might not be perceived as extreme and deviant, but rather as an innocuous or celebrated form of self-expression.

Notwithstanding the validity of previous research, the central thesis of the present study is that scholars should include characteristics of tattoos, hiring managers, and candidates when examining tattoos and perceptions of employment suitability. The present study will extend previous research by examining several related issues on this front in the context of hiring managers’ perceptions of employment suitability. First, this research will assess whether perceptions of employment suitability are contingent upon tattoo content, distinguishing between dark and light tattoos. We characterized dark tattoos as those of a more threatening, brooding, sullen, and angry nature, and light tattoos as those which are more innocent, light hearted, harmonious, and joyful. Tattoos embody meaning, and dark and light tattoos may not be equivalent in influencing perceptions of employment suitability. In turn, this research will examine whether millennial hiring managers, individuals who were born in the early 1980s through the mid-1990s (Dimock, 2018), have more favorable perceptions of tattoos relative to older hiring managers. The research will also explore whether dark and light tattoos interact with a candidate’s gender to influence perceptions of employment suitability and whether millennial and older hiring managers view dark and light tattoos differently on female and male candidates. Ultimately, the goal of this research is to provide a more nuanced perspective on the weight hiring managers place on tattoos in order to contribute to the larger body of research on selection decision making.

Background Research and Hypotheses Tattoos are not homogeneous, and as such, certain types of tattoos may be perceived less favorably than others. © 2020 Hogrefe Publishing

5

Previous research has often not differentiated tattoo content (see, e.g., Baumann et al., 2016; Miller et al., 2009; Timming, 2017; Timming et al., 2017). For example, the research by Baumann et al. (2016) involved the evaluation of photographs where individuals were adorned only with a tribal tattoo, and the research by Timming et al. (2017) involved the evaluation of photographs of individuals only with a star image. Some tattoos are certainly more extreme than these tattoos, and others are likely more innocuous.

The research by Timming and Perrett (2017) represents a notable study where the effects of different types of tattoos were examined, specifically their relationship with perceived trustworthiness. This research found that tattoos depicting images of violence and nudity resulted in the lowest levels of perceived trustworthiness. Furthermore, tattoos depicting images of Christianity and natural floral settings resulted in the highest ratings of perceived trustworthiness. Timming and Perrett (2016) also found that evaluations varied based on the genre of the tattoos, whereby non-Christian respondents rated Christianthemed tattoos less highly than non-Christian-themed tattoos. The research by Burgess and Clark (2010), another study that included different tattoo content, found that individuals with no tattoo or a “cute” tattoo were deemed as more suitable for employment than those with a tribal tattoo. As Timming et al. (2017) argued, since different tattoos represent genres with different degrees of acceptability, not all body art may be equally stigmatic and a source of prejudice.

To further explore the issue of different content, the present study will examine differences between dark tattoos and light tattoos, figuratively speaking, on perceptions of employment suitability. That is, this research will focus on tattoos that are of a darker or lighter subject matter. As a form of art, tattoos can be characterized in a variety of ways, such as genre, style, size, color, and location on the body. Regarding genre, we contend that one general means to describe tattoos is by whether they are dark or light. Dark tattoos encompass gothic images, symbols reflecting death or violence, and science fiction, among others. Dark tattoos may evoke negative emotions, such as intimidation, disgust, unease, and anxiety.

In turn, light tattoos encompass images such as nature and flowers, symbols of innocence and harmony, and cartoons of a fun and humorous nature. These tattoos may be more apt to evoke positive emotions, such as serenity, loyalty, joy, and inspiration. Given that dark and light tattoos may have different connotations, they could exhibit different relationships with perceptions of employment suitability. While both types may have an adverse impact on perceptions of employment suitability, dark tattoos are thought to be more detrimental than light ones.

Journal of Personnel Psychology (2020), 19(1), 4–13

6

M. J. Tews et al., Tattoos and Employment Suitability

Hypothesis 1: Dark tattoos will lead to more negative perceptions of employment suitability than light ones.

A further issue to be examined in the present study is whether the generational cohort of hiring managers will interact with tattoo type. Namely, it is argued that millennial hiring managers will perceive candidates with tattoos of both types as more suitable for employment than older nonmillennial hiring managers. Millennials were coming of age during the tattoo renaissance of the late 1990s. Tattoos increased in popularity during this decade as a result of tattooists looking to indigenous cultures for inspiration, a growing number of artists seeing tattoos as a legitimate art form, and more celebrities adorning themselves with body art (Larsen et al., 2014). These forces, coupled with millennials’ desire for greater self-expression (Hershatter & Epstein, 2010), can help account for the amount of tattooing among this generational cohort. It is estimated that nearly half of millennials are tattooed (47%), compared to 13% of baby boomers, the generational cohort born in the years following World War II (Harris Poll, 2016). Whereas tattooing was once associated with out-group membership (DeMello, 1995), it appears to be less so among millennials.

Based on similarity-attraction bias (Dean, 2010; Selfhout, Denissen, Branje, & Meeus, 2009), as well as norms aimed toward acceptance of tattoos among millennials, it is argued that millennial hiring managers are more apt to perceive candidates with tattoos as more suitable for employment than older hiring managers.

Since tattoos may be perceived as more controversial among older individuals, older hiring managers could believe that those with tattoos are less suitable for employment. Older hiring managers may feel that those with tattoos fail to adhere to the interview script and fail to conform to the image their organizations attempt to publicly portray. Moreover, older hiring managers could believe that individuals with tattoos possess undesirable attributes. Implicit personality theory asserts that generalized expectations are formed about individuals after some of their central traits are known (Ashmore & Del Boca, 1979). In fact, Dean (2010) found that older individuals have unfavorable attitudes toward those with tattoos, believing that those with tattoos are less intelligent and less honest. As older hiring managers have been surrounded by social prejudice against tattoos to a much greater extent and for a longer period of time than millennials, older hiring managers are expected to be more biased against job candidates with tattoos.

Hypothesis 2: Hiring managers who are millennials will view candidates with tattoos of both types more positively than older hiring managers.

Journal of Personnel Psychology (2020), 19(1), 4–13

Candidate gender may also interact with tattoos in influencing hiring managers’ perceptions of employment suitability. Previous research has demonstrated that individuals perceive females and males with tattoos differently; yet such research has not differentiated tattoo type.

Baumann et al. (2016) found that consumers preferred a female surgeon with a tattoo over a male surgeon with a tattoo. Furthermore, Timming (2017) demonstrated that tattooed males were deemed more suitable for employment in a fine dining setting than tattooed females, but that tattooed females were deemed more suitable than tattooed males for nightclub employment. Drawing on gender stereotypes, dark tattoos may be less detrimental for male candidates and light tattoos may be less detrimental for female candidates. Koch, D’Mello, and Sackett (2015) articulate that gender stereotypes fall into two broad categories: agentic and communal (Eagly & Karau, 2002; Eagly & Steffen, 1984). Agentic attributes, which reflect a propensity to be assertive and controlling, more commonly characterize males. Communal attributes, which reflect being kind and nurturing, more commonly characterize females (Eagly & Karau, 2002). Since dark tattoos more likely reflect agentic qualities, they may be perceived more favorably among males. Since light tattoos more likely reflect communal qualities, they may be perceived more favorably on female candidates. Support for these arguments can be found in previous research on gender discrimination in the workplace, which has found that violations of prescriptive stereotypes often generate negative reactions (Bobbitt-Zeher, 2011; Burgess & Borgida, 1999). Prescriptive stereotypes reflect normatively acceptable characteristics for each gender, which when violated, result in sanctions (Eagly & Karau, 2002).

Thus, when candidates are adorned with tattoos that violate their respective gender norms, they may be perceived less favorably for employment.

Hypothesis 3: Hiring managers will perceive male candidates with dark tattoos more positively relative to females and female candidates with light tattoos more positively relative to male candidates.

The final question to be addressed herein is whether millennial hiring managers view gender nonconformity in tattoo content differently than older hiring managers. In particular, it is argued that millennial hiring managers will perceive gender nonconformity in tattoo content more favorably than their older counterparts. Millennials are thought to be more receptive to diversity and individual differences than older generational cohorts (Rainer & Rainer, 2011), and they appear to be more open to deviation from traditional gender roles. Risman (2018) found that while some millennials do, in fact, hold traditional © 2020 Hogrefe Publishing

M. J. Tews et al., Tattoos and Employment Suitability

gender-role beliefs, others are innovators who defy stereotypes, reject sexual ideologies, and view gender as nonbinary. Furthermore, millennials more frequently identify as lesbian, gay, bisexual, transgender, or queer (LGBTQ ) than older generations and are likely to be supportive of those who are LGBTQ (Harris Poll, 2017). Since millennials tend to hold less rigid gender stereotypes than older generations, they may thus be more accepting of gender nonconforming tattoos on job candidates.

Hypothesis 4: Millennial hiring managers will view candidates with gender nonconforming tattoos more positively than older hiring managers.

Method Sample and Procedure The sample of hiring managers for this research includes 253 individuals recruited from a Qualtrics business panel in the US. A primary screening criterion for inclusion in this study was that the participants were managers whose job responsibilities included recruiting and selecting employees. Through an online survey, the sample of hiring managers evaluated a profile of a hypothetical job candidate. Specifically, the participants read a scenario depicting the interaction between an interviewer and job candidate with a photograph of a tattooed or nontattooed individual.

They then rated the job candidate’s employment suitability.

The average age of the hiring managers was 40.70 years (SD = 12.44), 72% were female, and they were predominantly Caucasian (82%). On average, they had been employed by their company for 9.57 years (SD = 8.30) at the time of the study. Over 70% of the hiring managers completed a form of postsecondary education, where completion of a bachelor’s degree was the most frequent (34%). The hiring managers were employed across a variety of industries, with the majority working in education, health care, hospitality, information technology, manufacturing, or retail.

Candidate Profiles Using a between-subjects design, participants were randomly assigned to evaluate one of six candidate profiles.

The six profiles were created following a 2 × 3 experimental design for a female or male job candidate on whom tattoos were absent, dark, or light. Specifically, the study participants were presented a photograph of a job candidate, ‘Jordan Smith,’ who was either female or male with © 2020 Hogrefe Publishing

7

no tattoo, a dark tattoo, or a light tattoo, along with a description of the candidate that was the same across the six conditions. The profiles were created in the context of hiring and interviewing a new management trainee. The candidate, a soon-to-be college graduate, was described as possessing relevant qualifications, providing good interview answers, and displaying enthusiasm and good interpersonal skills during an onsite job interview.

To create the tattooed conditions, a dark or light tattoo was digitally superimposed on the forearm of the models, who were in their early twenties. The models wore khaki pants and identical short sleeve polo shirts so the tattoo, if present, was visible. Thus, the candidates’ physical attributes other than the tattoos remained constant. The tattoos were all black in color and approximately the same size in all pictures to help minimize the influence of characteristics other than focal content itself. For the dark tattoo condition, respondents were shown a photograph of a model with a tattoo of a horror mask, a serpent, or a skull. For the light tattoo condition, respondents were shown a photograph of a model with a tattoo of a flower, a musical note, or the word “together” in a script font. Multiple tattoos were used for both dark and light tattoo conditions to help overcome any idiosyncrasies associated with one particular design. Before they were used, the tattoos were rated by an independent sample recruited from Amazon Mechanical Turk (n = 251) to validate the tattoos as dark or light. Each of the six tattoos was rated on the extent to which it was dark and light on fivepoint scales, with anchors ranging from 1 “not at all” to 5 “completely.” Supporting the proposed framework, each of the dark tattoos was rated significantly darker than lighter (horror mask: t = 8.79, p < .000; serpent: t = 12.17, p < .000; and skull: t = 2.42, p < .000). Furthermore, each of the light tattoos was rated significantly lighter than darker (flower: t = 15.75, p < .000; music notes; t = 7.24, p < .000; and “together”: t = 2.64, p < .006). An example of a full candidate profile is presented in the Electronic Supplementary Material (ESM 1), along with candidate photographs and the tattoos.

Measures Employment Suitability After reading the profiles, the hiring managers evaluated the candidate’s employment suitability by assessing perceived competence and providing a hiring recommendation.

Perceived competence was assessed with five-items developed by Fiske, Cuddy, Glick, and Xu (2002). Specifically, the hiring managers rated the extent to which the candidate was competent, confident, independent, competitive, and intelligent on a five-point scale with anchors ranging from 1 = not at all to 5 = to a great extent. In turn, Higgins and Judge’s (2004) two-item scale was used to Journal of Personnel Psychology (2020), 19(1), 4–13

8

M. J. Tews et al., Tattoos and Employment Suitability

measure hiring recommendation. These items included I would recommend extending a job offer to this candidate and Overall, I evaluate this candidate positively. These questions were answered on a five-point Likert scale with anchors ranging from (1) strongly disagree to (5) strongly agree. The internal consistency reliability estimates for the perceived competence and hiring recommendation scales were .89 and .85, respectively.

Hiring Manager Generational Cohort In line with the Pew Research Center, millennial hiring managers were operationalized as those born between 1981 and 1996, and non-millennial hiring managers were operationalized as those born before 1981 (Dimock, 2018).

One hundred twenty-five of the hiring managers were millennials, and 128 were non-millennials.

Analytic Strategy An analysis of covariance (ANCOVA) framework was used to assess the impact of the focal variables of interest on the employment suitability outcomes. Four attributes of the hiring managers were included in the analyses to help account for background in their ratings of employment suitability: education, ethnicity, gender, and previous work experience. Education was measured with an eight-point scale ranging from 1 = did not complete high school to 8 = doctoral degree (Krieger, Williams, & Moss, 1997). Previous work experience was operationalized by the number of jobs previously held by the hiring managers. Three main effects of interest were included in the ANCOVA model: generational cohort, candidate gender, and tattoo content.

Three two-way interactions were also included: candidate gender × generational cohort, candidate gender × tattoo content, and generational cohort × tattoo content. Finally, the model included a tattoo content × candidate gender × generational cohort three-way interaction. When there

were statistically significant F ratios, planned comparisons of the relevant adjusted means were examined to ascertain the degree of support for the hypotheses.

Results Table 1 provides the descriptive statistics and correlations among the employment suitability ratings and hiring manager characteristics. Table 2 presents the ANCOVA summaries. For perceived competence, there were two statistically significant explanatory variables, and the R2 was .11. For hiring recommendation, there were three statistically significant explanatory variables, and the R2 was .15. The observed power for the overall models was high for both perceived competence (1 – β = .90) and hiring recommendation (1 – β = .98). At the same time, it should be noted that the observed power for individual variables ranged from .05 to .90 for the perceived competence model and from .06 to .73 for the hiring recommendation model, indicating that the probability of type II errors varied substantially.

Hypothesis 1, which proposed that dark tattoos would lead to more negative perceptions of employment suitability than light ones, was not supported. Regarding hiring recommendation, the tattoo content’s main effect was nonsignificant at the .05 level. For perceived competence, the tattoo content’s main effect explained 3% of the variance.

Table 3 presents the perceived competence marginal means across tattoo content. Counter to expectations, light tattoos resulted in lower perceived competence ratings than dark tattoos (MD = –0.21, t = 2.10, and p = .038) and no tattoos (MD = –0.29, t = 2.10, and p = .041).

Hypothesis 2, which proposed that hiring managers who are millennials would view candidates with tattoos more positively than older hiring managers, was partially supported. The generational cohort × tattoo content

Table 1. Descriptive statistics and correlations among employment suitability ratings and hiring manager characteristics M

SD

1

1. Perceived competence

4.15

0.72

–

2. Hiring recommendation ratings

3.84

0.82

.42**

2

3

4

5

6

7

–

3. Education

5.00

1.62

.03

–.12

–

4. Ethnicity

0.82

0.39

–.04

–.05

–.12

5. Gender

0.28

0.45

–.00

–.02

.02

.05

–

6. Previous work experience

4.22

3.02

–.20**

–.03

–.12

.12

.04

–

–.11

–.15**

–.29**

–.08

–

.31**

.07

–.84**

7. Generational cohort 8. Age

8

0.49

0.50

–.01

.14*

40.70

12.44

–.04

–.21**

.16**

–

.11

–

Note. n = 253. Ethnicity: caucasian = 1, other ethnicities = 0. Gender: male = 1, female = 0. Generational cohort: millennial = 1, non-millennial = 0. Correlations with dichotomous variables are point-biserial. Significance levels reflect two-tailed tests. *p < .05, **p < .01.

Journal of Personnel Psychology (2020), 19(1), 4–13

© 2020 Hogrefe Publishing

M. J. Tews et al., Tattoos and Employment Suitability

9

Table 2. Analysis of covariance summary Perceived competence

Intercept

Hiring recommendation

F

p

Partial η

F

p

Partial η2

1349.92

.000

.85

849.98

.000

.79

2

Hiring manager characteristics Education

0.27

.966

1.03

.408

Ethnicity

0.11

.741

0.38

.538

Hiring manager gender

0.07

.791

0.68

.411

10.45

.001

0.25

.616

0.71

.399

2.60

.108

Candidate gender

2.03

.156

4.00

.047

Tattoo content

3.14

.045

0.94

.391

Previous work experience Generational cohort

.04

Candidate characteristics .03

.02

Interactions Candidate gender × Generational cohort

0.00

.953

1.63

.203

Candidate gender × Tattoo content

0.19

.828

0.10

.905

Generational cohort × Tattoo content

1.43

.242

4.17

.017

.04

Tattoo content × Candidate gender × generational cohort

1.92

.150

3.93

.021

.03

R

.11

2

.15

Note. n = 253. Partial η2 values are presented only for statistically significant F ratios (p < .05).

Table 3. Perceived competence marginal means across tattoo content Mean

SE

Dark tattoo

4.18

0.11

Light tattoo

3.97ab

0.11

No tattoo

4.26

0.15

a

b

Note. n = 253. Superscripts denote means that are significantly different for the purpose of testing Hypothesis 1 (p < .05).

Table 4. Hiring recommendation marginal means across tattoo content for millennial and non-millennial hiring managers Millennial

Non-millennial

Mean

SE

Mean

SE

Dark tattoo

3.91

0.16

3.89

0.14

Light tattoo

4.05a

0.15

3.45a

0.16

No tattoo

3.79

0.21

3.84

0.22

Note. n = 253. Superscripts denote means that are significantly different for the purpose of testing Hypothesis 2 (p < .05).

interaction explained 4% of the variance in hiring recommendation (F = 4.17, p = .017), but was nonsignificant in explaining perceived competence. The significant difference between the millennial and non-millennial hiring managers was for light tattoos (MD = 0.60, t = 2.85, and p = .006). Table 4 presents the hiring recommendation marginal means across tattoo content for the two groups of managers. Figure 1 graphically represents these relationships. The graph illustrates that the ratings were very different for light tattoos, but not appreciably different for © 2020 Hogrefe Publishing

Figure 1. Interaction effect between generational cohort and tattoo content for hiring recommendation.

dark tattoos and no tattoos between millennial and nonmillennial hiring managers.

Hypothesis 3, which proposed that hiring managers would perceive dark tattoos more positively on male candidates relative to females and light tattoos more positively on female candidates relative to male candidates, was not supported. The candidate gender × tattoo content interaction was not significant for either perceived competence or hiring recommendation.

Hypothesis 4, which proposed that millennial hiring managers would view tattoo gender nonconformity more positively than would older hiring managers, was partially supported. The three-way interaction of tattoo content × candidate gender × generational cohort explained 3% of the Journal of Personnel Psychology (2020), 19(1), 4–13

10

M. J. Tews et al., Tattoos and Employment Suitability

Table 5. Hiring recommendation marginal means across tattoo content on female and male candidates for millennial and non-millennial hiring managers Male candidate

Female candidate

Millennial

Nonmillennial

Millennial

Nonmillennial

Mean

SE

Mean

SE

Mean

SE

Mean

SE

Dark tattoo

3.68

0.19

3.82

0.18

4.14

0.21

3.96

0.18

Light tattoo

4.07a

0.17

3.20a

0.20

4.04

0.19

3.69

0.19

No tattoo

3.44

0.26

4.03

0.29

4.15

0.29

3.66

0.30

Note. n = 253. Superscripts denote means that are significantly different for the purpose of testing Hypothesis 4 (p < .05).

hiring managers viewed male candidates with no tattoo less suitable than did non-millennial hiring managers. With respect to female candidates, had there been support for the hypothesis, there would have been a greater distance between the millennial and non-millennial hiring managers for dark tattoos. However, these ratings for dark tattoos were relatively close. Moreover, the non-millennial hiring managers rated females with dark tattoos fairly high.

Post Hoc Analyses Post hoc analyses were performed to determine if the hiring manager’s age would be a better moderator of tattoo content on employment suitability ratings than generational cohort. Age could be a more sensitive moderator as it is an interval variable. To test this proposition, the ANCOVA models were re-estimated substituting age for generational cohort. The R2’s were .10 and .13 for perceived competence and hiring recommendation, respectively. Age explained 6% of the variance in hiring recommendation (F = 11.66, p = .001). However, there was no significant age interaction with tattoo content and candidate gender, as hypothesized.

With respect to perceived competence, the age main effect and interactions were all nonsignificant. In short, the age specification of the models was not superior to the generational cohort specification.

Discussion

Figure 2. Interaction effect of tattoo content, candidate gender, and generational cohort for hiring recommendation.

variance in hiring recommendation (F = 3.93, p = .021).

Millennial hiring managers perceived male candidates with light tattoos more positively than did non-millennial hiring managers (MD = 0.87, t = 3.31, and p = .002). Table 5 presents the hiring recommendation marginal means across tattoo content on female and male candidates for millennial and non-millennial hiring managers. Figure 2 presents the graphical representation of these relationships. In addition to highlighting this difference in perceptions of male candidates with light tattoos, the graph indicates that millennial Journal of Personnel Psychology (2020), 19(1), 4–13

While previous work has demonstrated that an anti-tattoo bias persists (e.g., Baumann et al., 2016; Miller et al., 2009; Timming, 2015; Timming et al., 2017), the present study has found that there may be nuance to whether tattoos are perceived unfavorably or favorably. As tattoos have become increasingly popular, this research has provided insights regarding when and under what conditions tattoos may be perceived negatively. Although significant effects for tattoos were found, the overall variance explained was not necessarily large. Thus, hiring managers appear not to place an inordinate emphasis on tattoos and likely are more attuned to the requisite knowledge, skills, and ability at hand. In this light, it appears that with the mainstreaming of tattoos in society in general, tattoos do not weigh too heavily into employment decisions. It should be noted that tattoo content had a significant main effect on perceived competence, yet there were no significant tattoo content interaction effects. With hiring recommendation, the tattoo content’s main effect was not significant, but there were significant interactions with generational cohort and gender. These findings suggest that ultimately © 2020 Hogrefe Publishing

M. J. Tews et al., Tattoos and Employment Suitability

whether or not tattoos have an effect on hiring may depend on contextual factors.

The fundamental contribution of this research is that negative tattoo effects were largely context dependent.

Namely, tattoo effects on employment suitability were contingent upon tattoo content, the generational cohort of a hiring manager, and the gender of a candidate. With respect to perceived competence, candidates with light tattoos were rated lower in perceived competence than candidates with dark tattoos or no tattoos. Regarding hiring recommendations, there were more nuances. Millennial hiring managers viewed candidates with light tattoos more positively than did older managers, and this generational difference was more pronounced for male candidates. One explanation why light tattoos may have been perceived more negatively than dark tattoos is that light tattoos may have been perceived as juvenile or silly, whereas dark tattoos may have been viewed as more traditional. Research has only begun to differentiate tattoo content in a single investigation (e.g., Timming & Perrett, 2016; Timming & Perrett, 2017), and the present study offers a dark–light tattoo genre distinction that can be employed in future research. The finding that millennial hiring managers were more receptive to tattoos when making hiring recommendations was likely a reflection of the greater prevalence of tattoos on millennials and their greater desire for individuality (Harris Poll, 2016; Hershatter & Epstein, 2010).

The results from this study suggest that there is asymmetry in the hiring recommendations for candidates with gender nonconforming tattoos across millennial and nonmillennial hiring managers. Millennials rated both gender nonconforming groups of candidates highly, whereas non-millennial hiring managers penalized gender nonconforming male candidates (i.e., those with light tattoos).

The high ratings for gender nonconforming candidates by millennial hiring managers may be attributed to more tolerant attitudes toward gender nonconformity in this generational cohort (Risman, 2018). In contrast, the ratings by non-millennial hiring managers that penalized males for gender nonconformity may be due to possible residualized homophobia among older hiring managers and society historically rewarding masculinity more than femininity (Feinman, 1984). This pattern of results parallels previous research that has demonstrated that male nonconformity is usually punished more harshly than female nonconformity (Smetana, 1986).

The post hoc analyses demonstrated that examining age differences in the tattoo-perceptions of employment suitability relationship did not yield better results than using generational cohorts. A greater number of significant effects were found using the generational cohort dichotomization.

Thus, sensitivity was not lost through dichotomization.

Furthermore, modeling age effects as linear may result in © 2020 Hogrefe Publishing

11

the appearance of no effects when, in fact, there were significant opposing effects for millennial and nonmillennial hiring managers. Age may have a curvilinear effect on the influence of tattoo content on employment suitability that is better captured by generational cohorts.

Additional research should determine the optimal number of generational cohorts to capture age differences in tattoo bias beyond the millennial and non-millennial distinction.

The practical implications of this research are twofold.

One, from the employer’s perspective, hiring managers should have an open dialog about the role of tattoos in hiring decisions. They should be aware of their attitudes about tattoos and how such attitudes affect their assessments of candidates. Since tattoos may impact perceptions of employment suitability both unfavorably and favorably, hiring managers need to articulate the potential benefits and drawbacks of considering tattoo status in hiring decisions.

Two, from the job candidate’s perspective, individuals should consider with whom they are interviewing to determine if a tattoo might result in a “penalty” in the employment selection process. Candidates should recognize that tattoos might hurt their employment chances when interacting with older hiring managers relative to younger ones. Until tattoos are more widely accepted and more millennials transition into positions where they have greater hiring decision authority, candidates are probably well advised to conceal any tattoos until they ascertain the culture of organizations from which they are seeking employment.

The results from this study should be interpreted in the context of its limitations. One limitation is that the job candidates in the present study were Caucasians in their early twenties. It is possible that tattoos might be perceived differently on candidates of different ethnicities and ages.

In this light, additional research would be valuable that explores how tattoos interact with different candidate demographic characteristics in influencing perceptions of employment suitability. A second limitation is that this research focused on tattoos in the context of hiring individuals for entry-level management positions in the US. As such, research would be valuable that examines tattoo bias in different cultural contexts. A third limitation is that the hiring managers evaluated hypothetical candidate profiles. While this methodological approach has been often employed in previous research (e.g., Baumann et al., 2016; Timming, 2017; Timming et al., 2017), additional research is needed that focuses on the extent to which tattoos hinder or help the employment prospects of actual job candidates.

In addition to addressing the limitations above, several opportunities for future research are worth pursuing. One opportunity for future research is examining the extent to which tattoo content on hiring managers influences perceptions of employment suitability. Although previous Journal of Personnel Psychology (2020), 19(1), 4–13

12

research has found that tattoos on participants do not significantly impact their ratings of others (e.g., Dean, 2010; Miller et al., 2009; Timming & Perrett, 2016), further research that focuses on specific tattoo content, such as the dark-light distinction examined herein, may yield different results. A second opportunity is examining how tattoos interact with other candidate or employee characteristics in influencing employment suitability, such as human capital, physical attractiveness, or sexual orientation. Moreover, research is needed that examines the influence of tattoos on other meaningful workplace criteria (e.g., workplace deviance, raises, job assignments, and promotions) to help determine the degree to which tattoos influence outcomes for individuals after they enter the workplace. A further recommendation is examining how the gender of the hiring managers interacts with tattoos to influence perception of employment suitability.

In the present study, a high proportion of the hiring managers were female. Although hiring manager gender did not have a significant effect on either perceived competence or hiring recommendation, gender may interact with tattoo genre or generational cohort in influencing perceptions of employment suitability. A final recommendation is examining how employment suitability perceptions are influenced by size, placement, and number. Such tattoo characteristics have largely been overlooked in workplace-tattoo research. One dominant theme in this paper is that not all tattoos are equal, and these additional tattoo characteristics may very well influence how tattooed individuals are perceived.

A central question as more and more individuals adorn themselves with tattoos is whether such body art impacts the outcomes individuals receive in employment contexts. The results from the present study highlight that tattoos may help individuals, hinder their success, or have no influence at all. To varying degrees, what appears to be important in determining how tattoos are perceived is the generational cohort of hiring managers, tattoo content, and the gender of the bearer of the tattoos. By no means is the present study meant to be a definitive test of the impact of tattoos in the workplace.

Rather, this research is intended to add to the extant research base and stimulate future research into this intriguing area of inquiry.

Electronic Supplementary Material The electronic supplementary material is available with the online version of the article at https://doi.org/10.1027/ 1866-5888/a000234

Journal of Personnel Psychology (2020), 19(1), 4–13

M. J. Tews et al., Tattoos and Employment Suitability

ESM 1. Sample candidate profile, candidate photographs, and tattoos

References Ashmore, R. D., & Del Boca, F. K. (1979). Sex stereotypes and implicit personality theory: Toward a cognitive–social psychological conceptualization. Sex Roles, 5, 219–248. https://doi.org/ 10.1007/BF00287932 Baumann, C., Timming, A. R., & Gollan, P. J. (2016). Taboo tattoos? A study of the gendered effects of body art on consumers’ attitudes toward visibly tattooed front line staff. Journal of Retailing and Consumer Services, 29, 31–39. https://doi.org/10.1016/j. jretconser.2015.11.005 Bobbitt-Zeher, D. (2011). Gender discrimination at work: Connecting gender stereotypes, institutional policies, and gender composition of workplace. Gender & Society, 25, 764–786. https://doi. org/10.1177/0891243211424741 Burgess, D., & Borgida, E. (1999). Who women are, who women should be: Descriptive and prescriptive gender stereotyping in sex discrimination. Psychology, Public Policy, and Law, 5, 665–692. https://doi.org/10.1037/1076-8971.5.3.665 Burgess, M., & Clark, L. (2010). Do the “savage origins” of tattoos cast a prejudicial shadow on contemporary tattooed individuals? Journal of Applied Social Psychology, 40, 746–764. https://doi.org/10.1111/j.1559-1816.2010.00596.x Dean, D. H. (2010). Consumer perceptions of visible tattoos on service personnel. Managing Service Quality: An International Journal, 20, 294–308. https://doi.org/10.1108/09604521011041998 DeMello, M. (1995). “Not just for bikers anymore”: Popular representations of American tattooing. The Journal of Popular Culture, 29, 37–52. https://doi.org/10.1111/j.0022-3840.1995.00037.x Dimock, M. (2018). Defining generations: Where millennials end and post-millennials begin. Pew Research Center. Retrieved from http://www.pewresearch.org/fact-tank/2018/03/01/defininggenerations-where-millennials-end-and-post-millennials-begin/ Eagly, A. H., & Karau, S. J. (2002). Role congruity theory of prejudice toward female leaders. Psychological Review, 109, 573–598. https://doi.org/10.1037/0033-295X.109.3.573 Eagly, A. H., & Steffen, V. J. (1984). Gender stereotypes stem from the distribution of women and men into social roles. Journal of Personality and Social Psychology, 46, 735–754. https://doi.org/ 10.1037/0022-3514.46.4.735 Feinman, S. (1984). A status theory of the evaluation of sex-role and age-role behavior. Sex Roles, 10, 445–456. https://doi.org/10.

1007/BF00287561 Fiske, S. T., Cuddy, A. J., Glick, P., & Xu, J. (2002). A model of (often mixed) stereotype content: competence and warmth respectively follow from perceived status and competition.

Journal of Personality and Social Psychology, 82, 878–902. https://doi.org/10.1037/0022-3514.82.6.878 French, M. T., Maclean, J. C., Robins, P. K., Sayed, B., & Shiferaw, L. (2016). Tattoos, employment, and labor market earnings: Is there a link in the ink? Southern Economic Journal, 82, 1212–1246. https://doi.org/10.1002/soej.12132 French, M. T., Mortensen, K., & Timming, A. R. (2019). Are tattoos associated with employment and wage discrimination? Analyzing the relationships between body art and labor market outcomes. Human Relations, 72, 962–987. https://doi.org/10.1177/ 0018726718782597

© 2020 Hogrefe Publishing

M. J. Tews et al., Tattoos and Employment Suitability

Harris Poll. (2016). Tattoo takeover: Three in ten Americans have tattoos, and most don’t stop at just one. Retrieved from https:// theharrispoll.com/tattoos-can-take-any-number-of-formsfrom-animals-to-quotes-to-cryptic-symbols-and-appear-in-allsorts-of-spots-on-our-bodies-some-visible-in-everyday-lifeothers-not-so-much-but-one-thi/ Harris Poll. (2017). Accelerating acceptance 2017. Retrieved from https://www.glaad.org/files/aa/2017_GLAAD_Accelerating_ Acceptance.pdf Hershatter, A., & Epstein, M. (2010). Millennials and the world of work: An organization and management perspective. Journal of Business and Psychology, 25, 211–223. https://doi.org/10.1007/ s10869-010-9160-y Higgins, C. A., & Judge, T. A. (2004). The effect of applicant influence tactics on recruiter perceptions of fit and hiring recommendations: A field study. Journal of Applied Psychology, 89, 622–632. https://doi.org/10.1037/0021-9010.89.4.622 Koch, A. J., D’Mello, S. D., & Sackett, P. R. (2015). A meta-analysis of gender stereotypes and bias in experimental simulations of employment decision making. Journal of Applied Psychology, 100, 128–161. https://doi.org/10.1037/a0036734 Krieger, N., Williams, D. R., & Moss, N. E. (1997). Measuring social class in US public health research: concepts, methodologies, and guidelines. Annual Review of Public Health, 18, 341–378. https://doi.org/10.1146/annurev.publhealth.18.1.341 Larsen, G., Patterson, M., & Markham, L. (2014). A deviant art: tattoo-related stigma in an era of commodification. Psychology & Marketing, 31, 670–681. https://doi.org/10.1002/mar.20727 Miller, B. K., McGlashan Nicols, K., & Eure, J. (2009). Body art in the workplace: Piercing the prejudice? Personnel Review, 38, 621–640. https://doi.org/10.1108/00483480910992247 Rainer, T. S., & Rainer, J. (2011). The millennials: Connecting to America’s largest generation. Nashville, TN: B & H Publishing.

Risman, B. J. (2018). Where the millennials will take us: A new generation wrestles with the gender structure. New York, NY: Oxford University Press.

Schouten, C. (2016). Meet the most “tattoo friendly” companies.

Retrieved from https://www.cbsnews.com/news/meet-themost-tattoo-friendly-companies/ Selfhout, M., Denissen, J., Branje, S., & Meeus, W. (2009). In the eye of the beholder: Perceived, actual, and peer-rated similarity in personality, communication, and friendship intensity during the acquaintanceship process. Journal of Personality and Social Psychology, 96, 1152–1165. https://doi.org/10.1037/a0014468

© 2020 Hogrefe Publishing

13

Smetana, J. G. (1986). Preschool children’s conceptions of sex-role transgressions. Child Development, 57, 862–871. https://doi.org/ 10.2307/1130363 Tennent, J. (2018). Which country has the most people with tattoos?

It’s not the U.S. Newsweek, Retrieved from http://www. newsweek.com/which-country-most-people-tattoos-943104.

Tiggemann, M., & Golder, F. (2006). Tattooing: An expression of uniqueness in the appearance domain. Body Image, 3, 309–315. https://doi.org/10.1016/j.bodyim.2006.09.002 Tiggemann, M., & Hopkins, L. A. (2011). Tattoos and piercings: Bodily expressions of uniqueness? Body Image, 8, 245–250. https:// doi.org/10.1016/j.bodyim.2011.03.007 Timming, A. R. (2015). Visible tattoos in the service sector: A new challenge to recruitment and selection. Work, Employment & Society, 29, 60–78. https://doi.org/10.1177/0950017014528402 Timming, A. R. (2017). Body art as branded labour: At the intersection of employee selection and relationship marketing.

Human Relations, 70, 1041–1063. https://doi.org/10.1177/ 0018726716681654 Timming, A. R., Nickson, D., Re, D., & Perrett, D. (2017). What do you think of my ink? Assessing the effects of body art on employment chances. Human Resource Management, 56, 133–149. https://doi.org/10.1002/hrm.21770 Timming, A. R., & Perrett, D. (2016). Trust and mixed signals: A study of religion, tattoos and cognitive dissonance. Personality and Individual Differences, 97, 234–238. https://doi.org/j.paid.2016.

03.067 Timming, A. R., & Perrett, D. I. (2017). An experimental study of the effects of tattoo genre on perceived trustworthiness: Not all tattoos are created equal. Journal of Trust Research, 7, 115–128. https://doi.org/10.1080/21515581.2017.1289847 History Received August 3, 2018 Revision received February 12, 2019 Accepted February 16, 2019 Published online July 3, 2020 Michael J. Tews School of Hospitality Management Pennsylvania State University University Park, PA 16802 USA mjt17@psu.edu

Journal of Personnel Psychology (2020), 19(1), 4–13

Original Article

Staying Quiet or Speaking Out: Does Peer Reporting Depend on the Type of Counterproductive Work Behavior Witnessed?

Nathan A. Bowling1, Brian D. Lyons2, and Gary N. Burns3 Department of Psychology, Wright State University, Dayton, OH, USA

1

Department of Management, Elon University, Elon, NC, USA

2

3

Department of Psychology, Florida Institute of Technology, Melbourne, FL, USA Abstract. Peer reporting, which occurs when employees report the occurrence of coworkers’ counterproductive work behavior (CWB) to organizational authorities, may help management detect CWBs that would otherwise be overlooked. We examined whether peer reporting depends on two CWB characteristics identified by Robinson and Bennett [(1995) A typology of deviant workplace behaviors: A multidimensional scaling study. Academy of Management Journal, 38, 555–572]: (a) the target of the CWB and (b) the severity of the CWB. Specifically, we hypothesized that witnesses are more likely to report CWBs targeting individuals than CWBs targeting the organization and that they are more likely to report serious CWBs than minor CWBs. Using a diversely employed sample (N participants = 139; N observations = 3451), we found support for the hypothesized effects of CWB severity, but not for the hypothesized effects of CWB target.

Keywords: counterproductive work behavior, workplace deviance, workplace aggression, peer reporting, bystander responses

Considerable research attention has been given to counterproductive work behaviors (CWBs) – harmful employee actions that target other people (e.g., the perpetrator’s coworkers) or target the perpetrator’s organization (Dalal, 2005; Vardi & Weitz, 2004). The CWB construct subsumes a variety of distinct behaviors, such as verbally abusing a coworker, intentionally performing one’s job incorrectly, abusing drugs while at work, and stealing organizational property (see Bennett & Robinson, 2000; Gruys & Sackett, 2003; Spector et al., 2006).

Much of the impetus for studying CWB results from its negative consequences for organizations and their employees. Employee theft, for instance, has been estimated to result in $50 billion in annual losses for US retailers alone (Reilly, 2017). The combined losses resulting from all forms of CWBs are likely much larger (Vardi & Weitz, 2004). Furthermore, some forms of CWBs may negatively affect the well-being of workers. People who are subjected to abusive behavior from supervisors or coworkers, for example, often experience psychological and physical health symptoms (Aquino & Thau, 2009; Bowling & Beehr, 2006).

Journal of Personnel Psychology (2020), 19(1), 14–23 https://doi.org/10.1027/1866-5888/a000238

Unfortunately, efforts to prevent CWBs may often be thwarted by management’s inability to detect CWBs (Carpenter, Rangel, Jeon, & Cottrell, 2017). In most cases, offending workers hide their misbehavior (Berry, Carpenter, & Barratt, 2012); thus, managers may be unaware of who is responsible for a particular instance of CWB, or they may be unaware that a CWB has ever occurred (Carpenter et al., 2017). Peers, however, often witness CWBs committed outside the presence of management (Curphy et al., 1998). Indeed, there are several reasons why peers – in comparison to supervisors – may be especially likely to witness CWBs. CWB perpetrators, for instance, may be more inclined to conceal their misbehavior from supervisors than from peers because supervisors have the authority to impose punishment for engaging in CWB (Bass, Avolio, Jung, & Berson, 2003).

Furthermore, workers might often witness the CWB committed by their peers because people are particularly attentive to their peers’ behavior (Fox, Spector, Goh, & Bruursema, 2007; McArthur & Baron, 1983). Finally, given the interdependence of job tasks, peers often work more closely with each other than with their supervisors (see © 2020 Hogrefe Publishing

N. A. Bowling et al., Peer Reporting of Counterproductive Work Behavior

Comer, 1991). The increased proximity may make it more likely that peers will witness CWBs than supervisors.

An organization’s ability to detect CWBs could thus be enhanced via peer reporting, which occurs when a worker reports the occurrence of a coworker’s CWB to an organizational authority, such as a supervisor or a representative of the organization’s human resources department (Bowling & Lyons, 2015; Lyons & Bowling, 2017; Trevino & Victor, 1992; Victor, Trevino, & Shapiro, 1993). Peer reporting is conceptually distinct from whistleblowing (e.g., the two behaviors differ in who is the perpetrator, who is the victim, and who is the investigating agent; see Bowling & Lyons, 2015; Lyons & Bowling, 2017). In the current study, we examined whether two characteristics of CWBs – CWB target and CWB severity – influence whether witnesses will report their coworkers’ misbehavior.

By examining the effects of the characteristics of individual CWBs, our study makes a meaningful contribution to the peer reporting literature. Indeed, previous research has focused on witness-level (e.g., witnesses’ personality traits and job attitudes; Bowling & Lyons, 2015) and organizational-level (e.g., the presence of a company-level peer-reporting policy; Lyons & Bowling, 2017) variables as predictors of peer reporting, rather than on the characteristics of individual CWBs. As such, the current study contributes to the literature by demonstrating the potential importance of distinguishing among various CWBs. This is noteworthy because both CWB studies, in general (e.g., Bennett & Robinson, 2000; Marcus, Taylor, Hastings, Sturm, & Weigelt, 2016), and peer reporting studies, in particular (e.g., Bowling & Lyons, 2015; Lyons & Bowling, 2017), have often treated conceptually distinct CWBs as though they were interchangeable (for critiques of this practice, see Bragg & Bowling, 2018; Carpenter et al., 2017; Spector et al., 2006).

Characteristics of CWBs as Predictors of Peer Reporting

15

reporting of various types of CWBs (e.g., Bowling & Lyons, 2015; Lyons & Bowling, 2017). These studies, in other words, treat peer reporting of one type of CWB (e.g., theft) as being interchangeable with peer reporting of other types of CWBs (e.g., sexual harassment). Because this approach produces a single composite peer reporting score, these studies do not examine the possibility that the likelihood a worker will engage in peer reporting is influenced by characteristics of the CWBs that they have witnessed. This omission is critical because individual CWBs may have unique qualities that make them more or less likely to be reported (Carpenter et al., 2017). Consider, for example, potential differences between witnessing the theft of office supplies versus witnessing the theft of money. Although the two behaviors would be treated as being interchangeable by most CWB researchers (i.e., because both involve theft; see Gruys & Sackett, 2003; Spector et al., 2006), they may produce different responses from witnesses. Because of the particularly strong societal norm against stealing money (see Ariely & Jones, 2012), we would expect that witnessing someone stealing money is more likely to evoke a sense of duty to report than witnessing someone pilfering from the office supply cabinet.

In the current study, we conducted analyses at the CWB item level to examine whether witnesses are more likely to report some types of CWBs than they are to report other types of CWBs. Studying the effects of CWB type is important because knowledge about which CWBs employees will not naturally report could help guide the content of organizational policies designed to encourage peer reporting. Organizational policies, in other words, could be designed to target the particular CWBs that would otherwise go unreported (see Lyons & Bowling, 2017). As we discuss below, we predict that two characteristics of CWBs influence one’s likelihood of engaging in peer reporting: (a) the target of the CWB and (b) the severity of the CWB. We focused on these two characteristics because seminal work by Robinson and Bennett (1995) identified them as two important dimensions of CWB.

Target of the CWB Research has given inadequate attention to the possibility that CWB characteristics influence a witness’s likelihood of peer reporting. In some studies, researchers were unable to examine differences across types of CWBs because they measured peer reporting of only one type of CWB. Victor et al. (1993) and Schmidtke (2007), for example, examined peer reporting of employee theft, whereas Gruys, Stewart, and Bowling (2010, Study 2) examined peer reporting of coworkers’ drug and alcohol abuse.

Other studies have used composite peer reporting measures formed by summing items that assess peer © 2020 Hogrefe Publishing

Some CWBs target individual people (CWB-Is), whereas other CWBs target the organization (CWB-Os; Bennett & Robinson, 2000; Dalal, 2005; Spector et al., 2006).

Verbally abusing a subordinate and stealing property belonging to a coworker are examples of CWB-Is, and intentionally doing one’s job tasks incorrectly and stealing property belonging to one’s employer are examples of CWB-Os. Because witnesses share more similarities with a human CWB target (e.g., a coworker) than with a nonhuman CWB target (e.g., an organization), we expect them Journal of Personnel Psychology (2020), 19(1), 14–23

16

N. A. Bowling et al., Peer Reporting of Counterproductive Work Behavior

to more readily empathize with the target of CWB-I than with the target of CWB-O (see Batson, Turk, Shaw, & Klein, 1995; Preston & de Waal, 2002). We expect that empathy, in turn, will make witnesses to come to the aid of a CWB target (see Cialdini, Brown, Lewis, Luce, & Neuberg, 1997; de Waal, 2008) – perhaps by reporting CWB directed at that target. Together, these mechanisms suggest that observing CWB is more likely to result in the reporting of CWB-Is than the reporting of CWB-Os. Hypothesis 1 (H1): Witnesses are more likely to report CWB-Is than they are to report CWB-Os.

likely visible than are CWB-Os (Berry et al., 2012), and serious CWBs are more likely visible than are minor CWBs. Furthermore, we examine the effects of both CWB target and CWB severity on peer reporting. Bowling and Lyons (2015), in contrast, examined only CWB severity.

Unlike previous studies that focused on either employeelevel (Bowling & Lyons, 2015) or organizational-level predictors of peer reporting (Lyons & Bowling, 2017), we focused on effects that occur at the CWB item level.

Method Sample and Procedure

Severity of the CWB Researchers have distinguished between minor CWBs (e.g., gossiping about a coworker, taking excessive work breaks) and serious CWBs (e.g., sexually harassing a coworker, embezzling from one’s employer; Robinson & Bennett, 1995). Drawing from the reasoning of Bowling and Lyons (2015), we predict that witnesses are more likely to report serious CWBs than they are to report minor CWBs. It is generally clear to witnesses of serious CWBs that they should report the behavior that they have observed and that failing to report could pose significant consequences for the CWB victim, the organization, and the witness. If a worker fails to report a physical assault between their peers, for example, then an upward-spiraling effect would occur to the organization – potentially culminating into even more serious CWB (Andersson & Pearson, 1999).

This clarity may counteract a general hesitancy to peer report. When a worker witnesses a minor CWB, however, it is generally unclear to them if they should report that behavior. Furthermore, the consequences of failing to report a minor CWB are less obvious. As a result, witnesses of minor CWBs may yield to a general hesitancy to peer report.

Hypothesis 2 (H2): Witnesses are more likely to report serious CWBs than they are to report minor CWBs.

The Current Study The current study contributes to the peer reporting literature in several ways. First, we controlled for the effects of CWB visibility when testing both our hypotheses. This is important because CWB visibility – the extent to which a given CWB can be easily observed by witnesses – may be confounded with CWB target and CWB severity (see Carpenter et al., 2017). Specifically, CWB-Is are more Journal of Personnel Psychology (2020), 19(1), 14–23

We initially sampled 266 employed participants using Amazon’s Mechanical Turk (MTurk; https://requester. mturk.com/). We used MTurk because several studies suggest that this and other crowdsourcing sampling methods generally yield quality data (see Casler, Bickel, & Hackett, 2013; Landers & Behrend, 2015; Mason & Suri, 2012). Crowdsourcing methods are particularly suited for peer reporting research because a high level of anonymity is afforded to participants (i.e., the study is not sponsored by the participants’ employers and supervisors have no means of accessing participants’ responses). Due to the given anonymity, any tendency of participants to engage in social desirability, which may produce inflated self-reports of peer reporting, should be minimized.

We provided participants with a monetary incentive (US$1.00) in exchange for completing an anonymous online survey. Given that the objective of this study was to examine factors influencing the degree to which witnesses reported the CWBs that they have observed, we removed 127 respondents who did not observe any CWBs. After applying these inclusion criteria, the final sample consisted of 139 employed participants (i.e., 52.3% of the initial sample).

The mean age of participants within the final sample was 31.87 years, and the majority of participants were male (63.3%), white (65.5%), and college-educated (82% had earned at least a bachelor’s degree). All participants were employed and worked in their organization for at least one year (89.2%), were experienced in their respective field (mean years = 7.72), worked full-time (mean hours worked per week = 38.43), and held a nonmanagerial position (64%). The majority of participants worked in retail (20.7%), education (12.7%), healthcare and social services (12.2%), professional services (12.2%), or finance and insurance (10.8%).

© 2020 Hogrefe Publishing

N. A. Bowling et al., Peer Reporting of Counterproductive Work Behavior

17

Table 1. CWB item coding by CWB target, severity, and visibility Gruys and Sackett’s (2003) CWB scale item

CWB target

Mean severity rating (SD)

Mean visibility rating (SD)

*A co-worker helped another person or advised them how to take company property or merchandise.

CWB-O

4.50 (0.58)

2.25 (0.50)

*A co-worker took cash or property belonging to the company.

CWB-O

5.00 (0.00)

2.25 (0.50)

*A co-worker took cash or property belonging to another co-worker.

CWB-I

5.00 (0.00)

2.50 (0.58)

*A co-worker took office supplies from the company.

CWB-O

4.00 (0.00)

1.75 (0.50)

*A co-worker took petty cash from the company.

CWB-O

4.50 (0.58)

1.50 (0.58)

*A co-worker gave away goods or services for free.

CWB-O

4.50 (0.58)

1.75 (0.50)

*A co-worker provided goods or services at less than the price established by the company.

CWB-O

3.75 (0.50)

1.75 (0.50)

CWB-I

5.00 (0.00)

3.75 (0.96)

*A co-worker defaced, damaged, or destroyed property, equipment, or product belonging to the company.

CWB-O

5.00 (0.00)

3.50 (0.58)

*A co-worker deliberately sabotaged the production of product in the company.

CWB-O

4.75 (0.50)

2.50 (0.58)

*A co-worker intentionally failed to give a supervisor or another coworker necessary information.

CWB-I

5.00 (0.00)

2.00 (0.82)

*A co-worker provided the organization with false information to obtain a job (i.e., regarding education or experience).

CWB-O

4.50 (0.58)

2.25 (0.96)

*A co-worker lied to a supervisor to cover up a mistake.

CWB-I

3.50 (0.58)

2.25 (0.50)

*A co-worker conducted personal business during work time.

CWB-O

2.00 (0.00)

2.50 (0.58)

*A co-worker spent time on the internet for reasons not related to work.

CWB-O

1.50 (0.58)

2.00 (0.82)

*A co-worker took a long lunch or coffee break without approval.

CWB-O

1.50 (0.58)

2.25 (1.26)

*A co-worker wasted time on the job.

CWB-O

2.00 (0.82)

1.75 (0.50)

*A co-worker wasted company resources.

CWB-O

2.25 (0.50)

2.00 (0.00)

*A co-worker used company resources they weren’t authorized to use.

CWB-O

3.00 (0.82)

2.00 (0.00)

*A co-worker made personal long distance calls at work.

CWB-O

1.75 (0.50)

2.00 (0.82)

*A co-worker mailed personal packages at work.

CWB-O

1.75 (0.50)

2.75 (1.50)

*A co-worker endangered themselves by not following safety procedures.

CWB-I

4.75 (0.50)

3.25 (0.96)

*A co-worker endangered other co-workers by not following safety procedures.

CWB-I

4.75 (0.50)

3.25 (0.96)

A co-worker misused a business expense account.

A co-worker took cash or property belonging to a customer.

A co-worker misused employee discount privileges. *A co-worker defaced, damaged, or destroyed property belonging to another co-worker.

A co-worker defaced, damaged, or destroyed property, belonging to a customer.

A co-worker destroyed or falsified company records or documents.

A co-worker discussed confidential matters with unauthorized personnel within or outside the organization.

A co-worker made personal photocopies at work.

A co-worker used email for personal purposes.

A co-worker played computer games during work time.

A co-worker altered a time card to get paid for more hours than they worked.

A co-worker worked unnecessary overtime.

A co-worker endangered customers by not following safety procedures.

(Continued on next page)

© 2020 Hogrefe Publishing

Journal of Personnel Psychology (2020), 19(1), 14–23

18

N. A. Bowling et al., Peer Reporting of Counterproductive Work Behavior

Table 1. (Continued) Gruys and Sackett’s (2003) CWB scale item

CWB target

Mean severity rating (SD)

Mean visibility rating (SD)

*A co-worker was absent from work without a legitimate excuse.

CWB-O

2.75 (0.96)

2.75 (0.96)

*A co-worker intentionally came to work late.

CWB-O

2.50 (1.00)

3.25 (0.96)

A co-worker failed to read the manual outlining safety procedures.

A co-worker used sick leave when they weren’t really sick. *A co-worker left work early without permission.

CWB-O

2.00 (0.82)

3.50 (1.29)

*A co-worker missed work without calling in.

CWB-O

3.00 (0.82)

4.00 (1.15)

*A co-worker intentionally performed his/her job below acceptable standards.

CWB-O

2.50 (1.00)

2.75 (0.96)

*A co-worker intentionally did work badly or incorrectly.

CWB-O

2.75 (0.50)

2.75 (0.96)

*A co-worker intentionally did slow or sloppy work.

CWB-O

2.50 (1.00)

3.00 (0.82)

*A co-worker came to work under the influence of alcohol.

CWB-O

5.00 (0.00)

4.50 (0.58)

*A co-worker engaged in alcohol consumption on the job.

CWB-O

5.00 (0.00)

3.75 (0.50)

*A co-worker had his/her performance affected due to a hangover from alcohol.

CWB-O

4.25 (0.50)

3.25 (0.50)

*A co-worker engaged in drug use on the job.

CWB-O

5.00 (0.00)

4.00 (0.82)

*A co-worker came to work under the influence of drugs.

CWB-O

5.00 (0.00)

4.25 (0.50)

*A co-worker possessed or sold drugs on company property.

CWB-O

5.00 (0.00)

3.00 (0.82)

*A co-worker had his/her performance affected due to a hangover from drugs.

CWB-O

4.50 (0.58)

3.25 (0.50)

CWB-I

3.50 (0.58)

5.00 (0.00)

*A co-worker verbally abused another co-worker.

CWB-I

4.50 (0.58)

4.75 (0.50)

*A co-worker verbally abused a supervisor.

CWB-I

4.50 (0.58)

4.75 (0.50)

*A co-worker used sexually explicit language in the workplace.

CWB-I

4.50 (0.58)

4.50 (0.58)

CWB-I

5.00 (0.00)

5.00 (0.00)

*A co-worker physically attacked (e.g., pushing, shoving, hitting) a supervisor.

CWB-I

5.00 (0.00)

5.00 (0.00)

*A co-worker made unwanted sexual advances toward another coworker.

CWB-I

5.00 (0.00)

4.00 (1.15)

*A co-worker made unwanted sexual advances toward a supervisor.

CWB-I

5.00 (0.00)

3.25 (1.26)

CWB-I

5.00 (0.00)

3.25 (1.26)

A co-worker argued or fought with a co-worker. *A co-worker yelled or shouted on the job.

A co-worker verbally abused a customer.

A co-worker argued or fought with a supervisor.

A co-worker argued or fought with a customer. *A co-worker physically attacked (e.g., pushing, shoving, hitting) another co-worker.

A co-worker physically attacked (e.g., pushing, shoving, hitting) a customer.

A co-worker made unwanted sexual advances toward a customer. *A co-worker made unwanted sexual advances toward a subordinate.

Note. CWB = counterproductive work behavior. CWB-I = counterproductive work behavior toward individuals; CWB-O = counterproductive work behavior toward the organization. Severity and visibility were rated on a 1 (very low) to 5 (very high) scale. Items marked with an asterisk were retained.

Measures Peer Reporting To measure the frequency of peer reporting of various CWBs, we adapted the 66-item CWB scale proposed by Gruys and Sackett (2003). Following Bowling and Lyons (2015), we first removed 20 items that lacked relevance to all positions. The majority of these items involved the use of Journal of Personnel Psychology (2020), 19(1), 14–23

equipment (e.g., personal photocopies, playing computer games), access to higher-level documents (e.g., confidential documents, falsifying company records), or direct interactions with customers (e.g., physically attacking a customer).

Table 1 provides a list of retained items.

For each of the 46 items, we changed the frame of reference from “I” to “A coworker” and created three response options: (a) did not witness the behavior; (b) witnessed the © 2020 Hogrefe Publishing

N. A. Bowling et al., Peer Reporting of Counterproductive Work Behavior

behavior, but did not report it; or (c) witnessed the behavior and did report it. All the above-mentioned items about behaviors were witnessed during the past year. We created two variables for each peer reporting item. The first variable reflected whether participants had observed (1) the given CWB or not (0). The second variable, which represented whether participants had reported (1) the CWB or not (0), was only created for a given participant if that CWB had been observed.

CWB Target We used a two-step process to code for CWB target. First, we coded each CWB item as CWB-I (1) or CWB-O (0) by using the x-axis of Figure 1 in Gruys and Sackett (2003, p. 39). This yielded 21 CWB-I items and 25 CWB-O items.

Second, we revisited the individual items to examine whether the outcome of the CWB was directed to individuals or to the organization. With full agreement across four coders – an industrial and organizational psychology professor, a management professor, and two industrial and organizational psychology PhD students – we changed the target for 12 items, mostly originating from the study of Gruys and Sackett on alcohol and drug dimensions. This change resulted in 15 CWB-I items and 31 CWB-O items.

CWB Severity We measured CWB severity by having the four coders that we used to assess CWB target rate for each of the 46 CWB items (Gruys and Sackett, 2003) on a severity scale from 1 (very low) to 5 (very high). The ICC(2) for these ratings was 0.95. The mean severity ratings of each item are shown in Table 1. CWB severity was not significantly correlated with ratings of CWB target (r = 0.24, p = .11).

CWB Visibility We measured CWB visibility by having four coders rate each of the 46 CWB items (Gruys and Sackett, 2003) on a visibility scale from 1 (very low) to 5 (very high). The ICC(2) for these ratings was 0.86. CWB visibility was not significantly correlated with ratings of CWB target (r = 0.23, p = .12), but was correlated with CWB severity (r = 0.51, p < .01), indicating that more severe CWBs were typically more visible.

Controls We controlled for two demographic variables in our analyses – job level and organizational tenure. Consistent with prior peer reporting research (Bowling & Lyons, 2015; Gruys et al., 2010), we expect that managers and those who have been employed with the organization for a longer time would be more likely to report the CWBs they had witnessed than would nonmanagers and newer employees.

We measured job level dichotomously (0 = nonmanager; 1 = manager) and measured organizational tenure via a

© 2020 Hogrefe Publishing

19

5-point scale (1 = less than a year, 2 = 1–3 years, 3 = 4–6 years, 4 = 7–9 years, and 5 = >10 years).

Results Data Screening for Insufficient Effort Responding Researchers have given increased attention to data quality problems that occur when participants engage in insufficient effort responding (IER; see Huang, Liu, & Bowling, 2015; Meade & Craig, 2012). We examined the effects of IER on the current findings by using the Mahalanobis distance (d) index to identify a subset of participants suspected of engaging in IER. Mahalanobis d has two particularly desirable features: (a) it converges well with other IER indices (Bowling et al., 2016; Meade & Craig, 2012) and (b) it produces clearly defined cut scores (Aguinis, Gottfredson, & Joo, 2013). This procedure identified one participant as engaging in careless responding.

We tested the hypotheses twice – with this participant included and with this participant excluded. The pattern of the results did not change across analyses; we thus report only the analyses with the flagged participant included.

Mixed-Effects Logistic Regression We conducted analyses at the item level using linear mixedeffects logistic regression with glmer using the lme4 package (version 1.1-18-1) in R (version 3.5.1; Bates, Maechler, Bolker, & Walker, 2013). Mixed-effects logistic regression is similar to logistic regression (i.e., the criterion variable is binary), but it allows for clustered data. In this case, CWB items are clustered within employees. We created logistic models for both observing and reporting CWBs, although our hypotheses focused only on reporting CWBs. We started all analyses with a null model that included participants as a random factor to acknowledge that items were nested within participants; we added the predictor variables to this model sequentially – first, the control variables; second, the CWB item characteristics (i.e., target, severity, and visibility); and finally, the interaction between target and severity – to examine improvements in model fit. All predictors were treated as fixed effects using a maximum likelihood estimation with an adaptive Gauss– Hermite quadrature of 10. Regression coefficients from the final model are presented in Table 2.

Ancillary Analyses: Relationships for Observing CWBs For observations of CWBs (N participants = 139; N observations = 6394), adding job status and tenure did not Journal of Personnel Psychology (2020), 19(1), 14–23

20

N. A. Bowling et al., Peer Reporting of Counterproductive Work Behavior

Table 2. Mixed-effects logistic regression coefficients for peer CWB observation and reporting CWB observed

CWB reported 95% CI OR

Job level (1 = manager) Tenure CWB visibility CWB target CWB severity

95% CI OR

B

SEB

OR

Lower

Upper

B

SEB

OR

0.36

0.25

1.43

0.87

2.34

0.87*

0.32

2.39

–0.11

Lower

Upper

1.28

4.48

0.10

0.90

0.74

1.08

–0.03

0.13

0.97

0.76

1.25

0.21*

0.03

1.23

1.15

1.32

0.03

0.05

1.03

0.93

1.14

0.03

0.07

1.03

0.88

1.19

–0.27*

0.12

0.76

0.61

0.96

–0.72*

0.03

0.48

0.46

0.51

0.26*

0.04

1.30

1.20

1.41

Note. CI = confidence interval; CWB = counterproductive work behavior; OR = odds ratio. CWB target: 0 = organizational, 1 = individual. Intraclass correlation coefficients were 0.18 for CWB observed and 0.25 for CWB reported. Intercepts were 2.36 for CWB observed and –2.96 for CWB reported. *p < .05.

OR = 1.16, 95% CI OR = 1.04, 1.31; Bseverity = –0.68, SEB = 0.05, OR = 0.51, 95% CI OR = 0.46, 0.56).

Figure 1. Interaction between target and severity in observing CWBs.

significantly improve model fit, χ2(2) = 1.49, p = .47; adding CWB target, severity, and visibility significantly improved the model fit beyond the previous step, χ2(3) = 764.80, p < .01; finally, the interaction between CWB target and severity significantly improved the model fit beyond the previous step, χ2(1) = 129.99, p < .01. The interaction between target and severity was significant (B = –1.31, SEB = 0.13, OR = 0.27, 95% CI OR = 0.21, 0.33) but did not change the interpretation of the main effects. The interaction shown in Figure 1 was created by centering all control variables and plotting severity one standard deviation above and below the mean. As shown in Figure 1, the probability of witnessing CWB-Is was higher than witnessing CWB-Os when severity was low, and the probability of witnessing a CWB decreased with an increase in severity. The interaction in Figure 1 shows that the negative trend associated with severity is stronger for CWB-Is than for CWB-Os. As suggested by an anonymous reviewer, we also conducted separate analyses for managers and nonmanagers (previously controlled for as the job level variable). For observing CWBs, the pattern of significance was the same for both groups, but the effects of both visibility and severity were slightly stronger for nonmanagers (Bvisibility = 0.23, SEB = 0.04, OR = 1.26, 95% CI OR = 1.16, 1.38; Bseverity = –0.75, SEB = 0.04, OR = 0.47, 95% CI OR = 0.44, 0.51) than for managers (Bvisibility = 0.15, SEB = 0.06,

Journal of Personnel Psychology (2020), 19(1), 14–23

Hypotheses Testing: Relationships for Reporting CWBs We expected witnesses to be more likely to report CWB-Is than CWB-Os (H1) and to be more likely to report serious CWBs than minor CWBs (H2). To test these hypotheses, we used responses from only those participants who had indicated that they had observed the given CWB (N participants = 139; N observations = 3451). Adding the control variables, job level and organizational tenure, significantly improved the model fit over the null model, χ2(2) = 7.03, p < .05; adding CWB characteristics significantly improved the model fit beyond the previous step, χ2(3) = 47.59, p < .01; finally, the interaction between CWB target and severity did not improve the model fit, χ2(1) = 1.03, p = .31. The odds of CWBs being reported by participants increased when the observer was a manager, when the CWBs targeted the organization, and when the CWBs were rated as more severe. We therefore found support for H2, but not for H1.

Based on the recommendations of an anonymous reviewer, we conducted analyses for both managers and nonmanagers. For reporting CWBs, the pattern of significance diverged: CWB severity was a significant predictor for both groups, but it was more important for nonmanagers (B = 0.31, SEB = 0.06, OR = 1.36, 95% CI OR = 1.22, 1.51) than for managers (B = 0.22, SEB = 0.06, OR = 1.24, 95% CI OR = 1.10, 1.40). Furthermore, CWB target was a significant predictor of reporting CWBs for nonmanagers (B = –0.37, SEB = 0.16, OR = 0.69, 95% CI OR = 0.50, 0.94), but not for managers (B = –0.15, SEB = 0.17, OR = 0.86, 95% CI OR = 0.61, 1.22).

Discussion Peer reporting, which occurs when witnesses report their coworkers’ CWBs to organizational authorities, has been

© 2020 Hogrefe Publishing

N. A. Bowling et al., Peer Reporting of Counterproductive Work Behavior

the focus of several studies (e.g., Bowling & Lyons, 2015; Lyons & Bowling, 2017; Trevino & Victor, 1992; Victor et al., 1993). Much of the motivation for studying peer reporting is tied to the fact that it can help an organization detect CWBs that would otherwise be overlooked by management. Indeed, there are several reasons why CWBs that are overlooked by the management may often be witnessed by peers: (a) most perpetrators take pains to hide their misbehavior from their supervisors (Berry et al., 2012; Carpenter et al., 2017), (b) peers generally work more closely with each other than with their supervisors (Comer, 1991), and (c) peers may be especially attentive to each other’s behavior (Fox et al., 2007; McArthur & Baron, 1983).

Prior research, unfortunately, has generally overlooked the possibility that witnesses are more likely to report some types of CWBs than they are to report other types of CWBs. Instead, research has generally treated peer reporting of distinct types of CWBs as being interchangeable with each other (e.g., Bowling & Lyons, 2015) or has focused on the peer reporting of a single type of CWB (e.g., Victor et al., 1993, focused on peer reporting of employee theft). The current study contributes to the literature by examining two characteristics of CWBs that we hypothesized would influence peer reporting behavior: (a) CWB target and (b) CWB severity. We discuss our findings regarding both of these CWB characteristics below.

Target and Severity of the CWB We predicted that peer reporting would more likely occur among witnesses of CWB-Is than among witnesses of CWB-Os. The degree of empathy a witness feels for a CWB target – which is presumably high when the target is another person – provided the basis for this prediction.

Specifically, we expect witnesses to more readily empathize with a target to the extent that the witness and target are similar to each other (see Batson et al., 1995; Preston & de Waal, 2002). Experiencing empathy, in turn, may spur the witness to help the target (see Cialdini et al., 1997; de Waal, 2008). Our results, however, did not support this prediction: although the odds of a given CWB being observed were similar for CWB-Is and CWB-Os, the odds of an observed CWB being reported was lower for CWB-Is than CWB-Os. One possible explanation for these findings is that witnesses may often believe it is unnecessary to report CWB-Is because the victims – who are people – are capable of reporting that they have been targeted. Witnesses, on the other hand, may believe it is necessary to report CWB-Os because the organization, as an inanimate object, depends on witnesses to peer report.

© 2020 Hogrefe Publishing

21

Moreover, we predicted that peer reporting would more likely occur among witnesses of serious CWBs than among witnesses of minor CWBs. It is generally clear that one has a duty to report serious CWBs, whereas it is less clear whether one has a duty to report minor CWBs (see Bowling & Lyons, 2015). Our results support this prediction. This suggests that the most commonly observed types of misbehaviors – minor CWBs – are often underreported.

Future Research Additional research is needed to fully examine the processes that precede peer reporting behavior. Drawing from the bystander response literature (see Ferguson & Barry, 2011; Fischer et al., 2011; Latané & Darley, 1970), future studies should examine whether a CWB that has occurred was (a) noticed by a would-be witness, (b) was deemed by the witness as worthy of being reported, and (c) was actually reported. Several factors are likely to influence each of these processes. Witnesses, for instance, may be more likely to notice CWB-Is than CWB-Os because the former are more visible than are the latter (Berry et al., 2012).

Once witnesses notice a given CWB, they may be more likely to judge that it warrants being reported if that behavior is indeed atypical. Witnesses, in other words, may regard a behavior as truly “deviant” – and hence worthy of reporting – only if it violates organizational norms within their workplace (Götz, Bollmann, & O’Boyle, 2019; Palmer, 2012; Warren, 2003) or is regarded as deviant by societal standards (Andersson & Pearson, 1999). Finally, once witnesses deem a behavior as worthy of reporting, they may or may not actually report it.

However, what individual and contextual factors determine if a behavior that is deemed worthy of being reported is in fact reported? Some possible individual factors include the job attitudes, moral awareness, and personalities of the witnesses (Bowling & Lyons, 2015; Gruys et al., 2010; Reynolds, 2006). As noted in the Introduction, witness empathy could also prompt a reporting behavior, especially if combined with contextual factors (see Trevino, 1986). A favorable personal relationship between the witness and CWB-I victim (see Porath & Erez, 2009), for example, could make the witness experience empathy for the victim. Empathy, in turn, may increase the likelihood that the witness will engage in peer reporting behavior.

Other contextual factors may include the presence of an organizational policy requiring witnesses to report CWBs (Lyons & Bowling, 2017), witness–perpetrator relationships, the number of other witnesses present (Fischer et al., 2011), and the effect of the CWB on the witnesses’ work group (Curphy et al., 1998; Ferguson & Barry, 2011; Journal of Personnel Psychology (2020), 19(1), 14–23

22

N. A. Bowling et al., Peer Reporting of Counterproductive Work Behavior

Trevino & Victor, 1992; Victor et al., 1993). Future research should examine the potential interactions between individual characteristics and such contextual factors in predicting peer reporting behavior.

Limitations We should acknowledge two limitations of the current research.First, we used a cross-sectional research design, which precluded us from testing causal relationships. This is a minor limitation, however, because witnessing CWB necessarily precedes the reporting of that CWB. Similarly, the CWB characteristics that we examined are preexisting qualities that precede both the observing and the reporting of CWBs. Second, we measured both observing CWBs and reporting CWBs using participant self-reports, which potentially leaves the current study vulnerable to the effects of common-method variance (CMV; see Spector, 2006).

We should note, however, that we used ratings from independent judges to assess CWB characteristics, and thus, we did not rely exclusively on participant self-reports. As a result, CMV is only a minor concern.

Implications and Conclusion In sum, we found that peer reporting base rates varied across different types of CWBs. These findings have important practical implications. Although witnesses generally fail to report most forms of CWB (Bowling & Lyons, 2015), they are particularly unlikely to report CWB-Is and minor CWBs. Organizations may thus wish to focus their efforts toward encouraging the peer reporting of these types of CWBs, perhaps by instituting policies that require witnesses to report particular CWBs. To the extent that such policies specify which CWB must be reported, they could be described as creating a clear peer reporting situation (see Lyons & Bowling, 2017). Policies may thus be used to impose a clear peer reporting situation in instances where the nature of the CWB one has witnessed would otherwise create an ambiguous peer reporting situation.

References Andersson, L. M., & Pearson, C. M. (1999). Tit for tat? The spiraling effect of incivility in the workplace. Academy of Management Review, 24, 452–471. https://doi.org/10.5465/amr.1999.2202131 Aguinis, H., Gottfredson, R. K., & Joo, H. (2013). Best-practice recommendations for defining, identifying, and handling outliers. Organizational Research Methods, 16, 270–301. https://doi. org/10.1177/1094428112470848

Journal of Personnel Psychology (2020), 19(1), 14–23

Aquino, K., & Thau, S. (2009). Workplace victimization: Aggression from the target’s perspective. Annual Review of Psychology, 60, 717–741. https://doi.org/10.1146/annurev.psych.60.110707.163703 Ariely, D., & Jones, S. (2012). The (honest) truth about dishonesty: How we lie to everyone – especially ourselves (Vol. 336). New York, NY: HarperCollins.

Bass, B. M., Avolio, B. J., Jung, D. I., & Berson, Y. (2003). Predicting unit performance by assessing transformational and transactional leadership. Journal of Applied Psychology, 88, 207–218. https://doi.org/10.1037/0021-9010.88.2.207 Bates, D., Maechler, M., Bolker, B., & Walker, S. (2013). lme4: Linear mixed-effects models using Eigen and S4 (R package version 1.0-5). Retrieved from https://CRAN.R-project.org/package=lme4 Batson, C. D., Turk, C. L., Shaw, L. L., & Klein, T. R. (1995). Information function of empathic emotion: Learning that we value the other’s welfare. Journal of Personality and Social Psychology, 68, 300–313. https://doi.org/10.1037/0022-3514.68.2.300 Bennett, R. J., & Robinson, S. L. (2000). Development of a measure of workplace deviance. Journal of Applied Psychology, 85, 349–360. https://doi.org/10.1037/0021-9010.85.3.349 Berry, C. M., Carpenter, N. C., & Barratt, C. L. (2012). Do otherreports of counterproductive work behavior provide an incremental contribution over self-reports? A meta-analytic comparison. Journal of Applied Psychology, 97, 613–636. https://doi. org/10.1037/a0026739 Bowling, N. A., & Beehr, T. A. (2006). Workplace harassment from the victim’s perspective: A theoretical model and meta-analysis.

Journal of Applied Psychology, 91, 998–1012. https://doi.org/10.

1037/0021-9010.91.5.998 Bowling, N. A., Huang, J. L., Bragg, C. B., Khazon, S., Liu, M., & Blackmore, C. E. (2016). Who cares and who is careless? Insufficient effort responding as a reflection of respondent personality. Journal of Personality and Social Psychology, 111, 218–229. https://doi.org/10.1037/pspp0000085 Bowling, N. A., & Lyons, B. D. (2015). Not on my watch: Facilitating peer reporting through employee job attitudes and personality traits. International Journal of Selection and Assessment, 23, 80–91. https://doi.org/10.1111/ijsa.12097 Bragg, C. B., & Bowling, N. A. (2018). Not all forms of misbehavior are created equal: Differential personality facet-counterproductive work behavior relations. International Journal of Selection and Assessment, 26, 27–35. https://doi.org/10.1111/ijsa.12200 Carpenter, N. C., Rangel, B., Jeon, G., & Cottrell, J. (2017). Are supervisors and coworkers likely to witness employee counterproductive work behavior? An investigation of observability and self-observer convergence. Personnel Psychology, 70, 843–889. https://doi.org/10.1111/peps.12210 Casler, K., Bickel, L., & Hackett, E. (2013). Separate but equal? A comparison of participants and data gathered via Amazon’s MTurk, social media, and face-to-face behavioral testing.

Computers in Human Behavior, 29, 2156–2160. https://doi.org/ 10.1016/j.chb.2013.05.009 Cialdini, R. B., Brown, S. L., Lewis, B. P., Luce, C., & Neuberg, S. L. (1997). Reinterpreting the empathy-altruism relationship: When one into one equals oneness. Journal of Personality and Social Psychology, 73, 481–494. https://doi.org/10.1037/0022-3514.73.

3.481 Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analyses for the behavioral sciences (3rd ed.), Mahwah, NJ: Lawrence Erlbaum Associates.

Comer, D. R. (1991). Organizational newcomers’ acquisition of information from peers. Management Communication Quarterly, 5, 64–89. https://doi.org/10.1177/0893318991005001004 Curphy, G. J., Gibson, F. W., Macomber, G., Calhoun, C. J., Wilbanks, L. A., & Burger, M. J. (1998). Situational factors affecting peer reporting intentions at the U.S. Air Force Academy: A scenario-

© 2020 Hogrefe Publishing

N. A. Bowling et al., Peer Reporting of Counterproductive Work Behavior

based investigation. Military Psychology, 10, 27–43. https://doi. org/10.1207/s15327876mp1001_3 Dalal, R. S. (2005). A meta-analysis of the relationship between organizational citizenship behavior and counterproductive work behavior. Journal of Applied Psychology, 90, 1241–1255. https:// doi.org/10.1037/0021-9010.90.6.1241 de Waal, F. B. M. (2008). Putting the altruism back into altruism: The evolution of empathy. Annual Review of Psychology, 59, 279–300. https://doi.org/10.1146/annurev.psych.59.103006.093625 Ferguson, M., & Barry, B. (2011). I know what you did: The effects of interpersonal deviance on bystanders. Journal of Occupational Health Psychology, 16, 80–94. https://doi.org/10.1037/a0021708 Fischer, P., Krueger, J. I., Greitemeyer, T., Vogrincic, C., Kastenmüller, A., Frey, D., … Kainbacher, M. (2011). The bystander-effect: A meta-analytic review on bystander intervention in dangerous and non-dangerous emergencies. Psychological Bulletin, 137, 517–537. https://doi.org/10.1037/a0023304 Fox, S., Spector, P. E., Goh, A., & Bruursema, K. (2007). Does your coworker know what you’re doing? Convergence of self-and peer-reports of counterproductive work behavior. International Journal of Stress Management, 14, 41–60. https://doi.org/doi 10.1037/1072-5245.14.1.41 Götz, M., Bollmann, G., & O’Boyle, E. H. (2019). Contextual undertow of workplace deviance by and within units: A systematic review.

Small Group Research, 50, 39–80. https://doi.org/10.1177/ 1046496418790044 Gruys, M. L., & Sackett, P. R. (2003). Investigating the dimensionality of counterproductive work behavior. International Journal of Selection and Assessment, 11, 30–42. https://doi.org/ 10.1111/1468-2389.00224 Gruys, M. L., Stewart, S. M., & Bowling, N. A. (2010). Choosing to report: Characteristics of employees who report the counterproductive work behavior of others. International Journal of Selection and Assessment, 18, 439–446. https://doi.org/10.1111/j.

1468-2389.2010.00526.x Huang, J. L., Liu, M., & Bowling, N. A. (2015). Insufficient effort responding: Examining an insidious confound in survey data.

Journal of Applied Psychology, 100, 828–845. https://doi.org/10.

1037/a0038510 Landers, R. N., & Behrend, T. S. (2015). An inconvenient trust: Arbitrary distinctions between organizational, Mechanical Turk, and other convenience samples. Industrial and Organizational Psychology: Perspectives on Science and Practice, 8, 142–164. https://doi.org/10.1017/iop.2015.13 Latané, B., & Darley, J. M. (1970). The unresponsive bystander: Why doesn’t he help? New York, NY: Appleton-Century-Croft.

Lyons, B. D., & Bowling, N. A. (2017). On the effectiveness of peer reporting policies. Journal of Managerial Psychology, 32, 547–560. https://doi.org/10.1108/JMP-04-2017-0147 Marcus, B., Taylor, O. A., Hastings, S. E., Sturm, A., & Weigelt, O. (2016). The structure of counterproductive work behavior: A review, a structural meta-analysis, and a primary study. Journal of Management, 42, 203–233. https://doi.org/10.1177/ 0149206313503019 Mason, W., & Suri, S. (2012). Conducting behavioral research on Amazon’s Mechanical Turk. Behavior Research Methods, 43, 1–23. https://doi.org/10.3758/s13428-011-0124-6 McArthur, L. Z., & Baron, R. M. (1983). Toward an ecological theory of social perception. Psychological Review, 90, 215–238. https:// doi.org/10.1037/0033-295X.90.3.215 Meade, A. W., & Craig, S. B. (2012). Identifying careless responses in survey data. Psychological Methods, 17, 437–455. https://doi. org/10.1037/a0028085 Palmer, D. A. (2012). Normal organizational wrongdoing: A critical analysis of theories of misconduct in and by organizations.

Oxford, UK: Oxford University Press.

© 2020 Hogrefe Publishing

23

Porath, C. L., & Erez, A. (2009). Overlooked but not untouched: How rudeness reduces onlookers’ performance on routine and creative tasks. Organizational Behavior and Human Decision Processes, 109, 29–44. https://doi.org/10.1016/j.obhdp.2009.01.

003 Preston, S. D., & de Waal, F. B. M. (2002). Empathy: Its ultimate and proximate bases. Behavioral and Brain Sciences, 25, 1–20. https://doi.org/10.1017/S0140525X02000018 Reilly, K. (2017). Shoplifting and other fraud cost retailers nearly $50 billion last year. Retrieved from http://money.com/money/ 4829684/shoplifting-fraud-retail-survey/ Reynolds, S. J. (2006). Moral awareness and ethical predispositions: Investigating the role of individual differences in the recognition of moral issues. Journal of Applied Psychology, 91, 233–243. https://doi.org/10.1037/0021-9010.91.1.

233 Robinson, S. L., & Bennett, R. J. (1995). A typology of deviant workplace behaviors: A multidimensional scaling study. Academy of Management Journal, 38, 555–572. https://doi.org/10.

5465/256693 Schmidtke, J. M. (2007). The relationship between social norm consensus, perceived similarity, and observer reactions to coworker theft. Human Resource Management, 46, 561–582. https://doi.org/10.1002/hrm.20182 Spector, P. E. (2006). Method variance in organizational research: Truth or urban legend? Organizational Research Methods, 9, 221–232. https://doi.org/10.1177/1094428105284955 Spector, P. E., Fox, S., Penney, L. M., Bruursema, K., Goh, A., & Kessler, S. (2006). The dimensionality of counterproductivity: Are all counterproductive behaviors created equal? Journal of Vocational Behavior, 68, 446–460. https://doi.org/10.1016/j.jvb.

2005.10.005 Trevino, L. K. (1986). Ethical decision making in organizations: A person-situation interactionist model. Academy of Management Review, 11, 601–617. https://doi.org/10.5465/amr.1986.

4306235 Trevino, L., & Victor, B. (1992). Peer reporting of unethical behavior: A social context perspective. Academy of Management Journal, 35, 38–64. https://doi.org/10.5465/256472 Vardi, Y., & Weitz, E. (2004). Misbehavior in organizations. Mahwah, NJ: Lawrence Erlbaum.

Victor, B., Trevino, L. K., & Shapiro, D. L. (1993). Peer reporting of unethical behavior: The influence of justice evaluations and social context factors. Journal of Business Ethics, 12, 253–263. https://doi.org/10.1007/BF01666528 Warren, D. E. (2003). Constructive and destructive deviance in organizations. Academy of Management Review, 28, 622–632. https://doi.org/10.5465/amr.2003.10899440 History Received June 11, 2018 Revision received April 2, 2019 Accepted May 11, 2019 Published online July 3, 2020 ORCID Nathan A. Bowling  https://orcid.org/0000-0003-3768-4939 Nathan A. Bowling Wright State University 303C Fawcett Hall 3640 Colonel Glenn Highway Dayton, OH 45435-0001 USA nathan.bowling@wright.edu

Journal of Personnel Psychology (2020), 19(1), 14–23

Original Article

The Costs of Working Too Hard Relationships Between Workaholism, Job Demands, and Prosocial Organizational Citizenship Behavior Guido Alessandri1, Evelina De Longis1, Enrico Perinelli2, Cristian Balducci3, and Laura Borgogni1 Department of Psychology, Sapienza University of Rome, Italy Department of Psychology and Cognitive Science, University of Trento, Italy

1

2

3

Department of Psychology, University of Bologna, Italy Abstract. Despite the relatively intuitive link between working hard and achievements at work, results from empirical studies tend to characterize workaholics more often as hard workers rather than smart workers. Indeed, the link between workaholism and job performance is not obvious. In this paper, we investigated the link between workaholism and a core component of contextual performance, namely, prosocial organizational citizenship behavior (P-OCB). More in detail, we posited a mediational model in which workaholic tendencies negatively predicted P-OCB indirectly through an increased perception of job demands. This model was tested using longitudinal data from a sample of 85 police officers assessed once every two weeks for three months. Results from multilevel structural equation analyses demonstrated the model’s good fit and corroborated the mediated effect. All in all, our results point to an organizational cost of workaholism, represented by its aversive impact on P-OCB. Keywords: job demands, multilevel structural equation modeling, organizational citizenship behavior, police officers, workaholism

Work addiction, or workaholism, is generally seen as a dispositional type of heavy work investment, in which individuals feel compelled to engage in work-related activities because of internal contingencies that control their behavior (Oates, 1971; Scott, Moore, & Miceli, 1997).

Workaholics have a tendency to work very hard beyond what is reasonably expected or requested of them (Schaufeli, Taris, & van Rhenen, 2008b; Snir & Zohar, 2008) and display a compulsive and obsessive preoccupation toward work (Ng, Sorensen, & Feldman, 2007).

Despite the relatively intuitive link between working hard and achievements at work (Ng, Eby, Sorensen, & Feldman, 2005), results from empirical studies tend to characterize workaholics as workers who are able to do a lot of work (i.e., “hard workers”), but not generally good work (i.e., “smart workers”; e.g., Spence & Robbins, 1992). Thus, despite some suggestions that workaholism may have positive organizational consequences(seeBaruch,2011;Ng etal.,2007), the link between workaholism and job performance is not obvious (see Clark, Michel, Zhdanova, Pui, & Baltes, 2016).

Also, less investigated is the link between workaholism and other components of job performance, such as organizational citizenship behavior (OCB). According to Organ’s (1988) definition, OCB represents an “individual behavior that is discretionary, not directly or explicitly recognized by the formal reward system, and in the Journal of Personnel Psychology (2020), 19(1), 24–32 https://doi.org/10.1027/1866-5888/a000240

aggregate, promotes the efficient and effective functioning of the organization” (p. 4). Since the seminal contribution of Bateman and Organ (1983), the practical importance of OCB has been largely demonstrated with respect to several organizational outcomes, such as managerial evaluations of performance and judgments regarding pay raises, promotions, and organizational performance and success (Organ, 2018; Podsakoff, Whiting, Podsakoff, & Blume, 2009).

In this study, drawing on the conservation of resources (COR) theory (Hobfoll, 1989), we focused on the relationships between workaholism and a specific class of OCB, namely, prosocial organizational citizenship behavior (P-OCB). P-OCB is characterized by positive behaviors toward colleagues (such as helping others who have been absent or taking a personal interest in other employees) that Williams and Anderson (1991) have described as immediately benefiting specific workers and indirectly impacting their organization. Indeed, P-OCB provides several benefits to the organization, including increased productivity, a broader circulation of resources within the organization and higher organizational flexibility and performance stability (Organ, 2018).

As other classes of prosocial interpersonal behaviors, P-OCB rests on worker’s self-regulation abilities. Indeed, © 2020 Hogrefe Publishing

G. Alessandri et al., The Costs of Workaholism

the ability to master one’s own emotions and behaviors tends to be related to the ability to empathize with other people (Alessandri, Caprara, Eisenberg, & Steca, 2009). In this regard, studies conducted in the general population have revealed close links between a broad set of prosocial behaviors and higher resistance to interpersonal distress, namely, a self-focused, aversive response to the apprehension of another’s need or distress (Batson, 1998; Davis, 1994; Eisenberg et al., 1994), and stronger abilities to regulate emotions such as anger and despondency (Alessandri et al., 2009; Eisenberg & Okun, 1996; Okun, Shepard, & Eisenberg, 2000). As such, P-OCB heavily weights on workers’ ability to use personal resources for self-regulating. Yet, personal resources are not unlimited and individuals have to carefully choose where to dynamically allocate their resources in accordance with their valued personal goals (Hobfoll, 2001). The more resources individuals invest in the pursuit of ones’ specific selfrelevant goal, the less they spare to use in the achievement of different goals (Hobfoll, 1989).

Drawing on the above reasoning, in this paper, we tested a mediational model linking workaholism to (less) P-OCB through the mediation of perceived job demands. We use the COR (Hobfoll, 1989, 2001) theory as the overarching framework to develop our hypothesis. The basic idea in our model is that workaholism represents a demanding and resource-depleting stable individual disposition that leads individuals to overinvest their personal resources in taskrelated activities, thus reducing other investment at work.

For this reason, we focus on dispositional workaholism, namely, the tendency to work compulsively, obsessively, and hard (Clark et al., 2016).

We believe that our emphasis on the interpersonal cost of workaholism, in terms of reduced P-OCB, has the potential to contribute to the literature regarding its complex relationships with workers’ organizational behaviors. On the one hand, we aim to clarify the mechanism leading workaholics to progressively disinvest from interpersonal relationships, as attested by reduced P-OCB. The idea is that giving the cost associated with P-OCB, to save personal resources, workaholics may simply decide to withdraw from this area. On the other hand, we aim to point out a possible mechanism impairing the overall contribution of workaholics to organizational performance through their lack of contribution to contextual performance (Borman & Motowidlo, 1997).

Moreover, we use dynamic data that allow us to test our hypotheses at the appropriate level of analysis. We indeed conceptualize workaholism as a trait (i.e., a stable individual disposition) and job demands and P-OCB as partly stable and partly fluctuating “state-like” variables that may change across time and thus across varying dispositional circumstances. Our aim is to investigate if there © 2020 Hogrefe Publishing

25

are direct (workaholism → job demands and job demands → P-OCB) and indirect (workaholism → P-OCB through job demands) relationships among the stable components of those variables. Note that, whereas we expect to find a dynamic relationship between state job demands and state P-OCB, this was not the focal interest of this paper. In sum, distinguishing the between and the within level of analysis and testing our hypotheses at the appropriate (betweenworkers) level of analysis is particularly critical in this paper, given our interest on dispositional workaholism and on its effect on workers’ dispositional tendency to enact P-OCB. Below, we present our theoretical framework in detail and develop the specific hypotheses corroborating our model.

Workaholism and Job Demands Work addiction or workaholism has been generally described as a dispositional type of heavy work investment, where individuals feel compelled to engage in workrelated activities because of internal contingencies that control their behavior (Lowman, 1993; Oates, 1971; Scott et al., 1997). Two prototypical dimensions characterize workaholic individuals (Clark et al., 2016): (1) a pervasive preoccupation and compulsion regarding one’s work, leading individuals to appear constantly obsessed with work, continuously thinking about work-related activities (even when they are not at work), and being unable to detach from it (Ng et al., 2007; Porter, 1996; Robinson, 1999; Schaufeli, Taris, & Bakker, 2008a; Scott et al., 1997; Spence & Robbins, 1992); and (2) a tendency to work very hard, by far in excess when compared to colleagues and collaborators and well beyond what is reasonably expected by the requirements of the job, even in the face of potential negative consequences (Ng et al., 2007; Schaufeli et al., 2008a; Snir & Zohar, 2008).

Described in these terms, it is clear that one distinctive feature of workaholism is a heavy resource investment in ones’ own work activity (Balducci, Avanzi, & Fraccaroli, 2018). Given their inner dispositional drive to work hard, workaholics perceive a high level of job demands, in terms of workload and time pressure, which they actively contribute to creating (see Clark et al., 2016). These job demands should not necessarily reflect higher work assignment (workload) or higher pressure on the worker.

Instead, they may simply be a consequence of the distinctive personality profile of workaholic individuals.

For example, in the study conducted by Schaufeli et al.

(2008b), workaholics resulted as rigid, not able to delegate, and with a strong tendency to perfectionism that Journal of Personnel Psychology (2020), 19(1), 24–32

26

G. Alessandri et al., The Costs of Workaholism

lead them to constantly seek out more job-related tasks and all aspects that may fuel high levels of job demands.

In sum, there is a large body of empirical evidence (see Clark et al., 2016) supporting the view of workaholism as a dispositional tendency associated with the perception, if not with the active search, of a high level of job demands.

H1: Workaholism is positively related to job demands at the between (i.e., trait) level of analysis.

Job Demands and P-OCB According to COR theory (Hobfoll, 1989), investing more personal resources on a goal means to remain with fewer resources to invest in other goals. Given the primacy of resource loss over resource gain (Hobfoll, 2001), workaholics are expected to refrain from investing their personal resources in any other “resource demanding activity” perceived as not belonging to their main area of concentration, namely, their work task. This way, they strive to preserve their personal resources in order to deal with their demanding work activity. Unfortunately, P-OCB represents a resource-depleting behavior. As reiterated by many theorists and corroborated by several empirical studies, there is a cost in helping others in terms of emotional resources investment to cope with both others’ negative emotions and one’s own emotional distress (Batson, 1998).

As stated above, P-OCB is a discretionary behavior carrying a cost for the individual in terms of personal resource investment (Koopman, Lanaj, & Scott, 2016).

Thus, in line with COR theory (Hobfoll, 1989), enacting P-OCB becomes less likely when personal resources are perceived as already low or almost all invested in another important endeavor (Hobfoll, 2001). Therefore, it is likely that the more workers seek out a heavy workload or perceive a higher temporal pressure to complete their taskrelated activities, the lower the level of resources (e.g., physical energy, time) they have to invest in P-OCB. Moreover, there is a large body of literature connecting lower levels of P-OCB with stress and negative emotions (Cropanzano, Rupp, & Byrne, 2003; Ziegler, Schlett, Casel, & Diehl, 2012), two well-documented outcomes of workaholism (Schaufeli, Bakker, van der Heijden, & Prins, 2009a). This reasoning leads us to formulate our second hypothesis.

H2: Job demands predict a lower frequency of P-OCB at both the within (or state) and between (or trait) level of analyses.

Journal of Personnel Psychology (2020), 19(1), 24–32

Combining H1 and H2 leads us to hypothesize an indirect relationship between workaholism and P-OCB. As explained by Kaplan, Bradley, Luchman, and Haynes (2009), the stress associated with unusual high job demands may itself represent the reason why workaholics are less likely to engage in the various forms of OCB than other workers. Furthermore, we cannot exclude the fact that when faced with the need for keeping up with selfimposed job demands, workaholics may consider P-OCB as a distraction that keeps them from meeting workrelated goals. From their point of view, they may perceive P-OCB as “nonessential” discretionary acts and thus akin to a waste of time and energy.

H3: Job demands mediate the relationship between workaholism and P-OCB. To strengthen the robustness of the model, we controlled for emotional stability, agreeableness, and conscientiousness, three personality traits that have been repeatedly found to be associated with workaholism (see Clark et al., 2016), as well as representing powerful predictors of P-OCB (Chiaburu, Oh, Berry, Li, & Gardner, 2011).

Nature of the Research Context We tested this model by following a sample of police officers for three consecutive months. We selected police officers given the specific nature of this profession. Indeed, policing is usually identified as a stressful occupation (e.g., Hall, Dollard, Tuckey, Winefield, & Thompson, 2010). In particular, police officers are routinely exposed to acute and chronic occupational stressors (see Webster, 2013, for a review) and are at higher risk for developing stressrelated pathologies such as post-traumatic stress disorder, burnout, and suicide (Burke, 1993; Liberman, Best, Metzler, Fagan, Weiss, & Marmar, 2002; Violanti, 1997). Moreover, police officers are often called to work shifts due to policing being a 24-hour seven-day a week job. This leads police officers to face the cost of forced overtime but also allows them to volunteer for overtime (e.g., receiving extra payment). The amount of overtime worked and overtime practices differ widely from department to department and among police officers within the same department. Unfortunately, there are limited public data available regarding this phenomenon (Vila, 2006). Moreover, the existing literature documents that police officers have different thoughts when it comes to overtime. Some officers like to work overtime and volunteer for as much overtime as they can get, while others despise it and do everything they can to get out of it (see © 2020 Hogrefe Publishing

G. Alessandri et al., The Costs of Workaholism

Vila, 2006). This has led police departments to regulate the maximal amount of overtime allowed. In sum, the police organizations naturally provide a heavy workload on police officers. Thus, the stressful nature of the job along with openly incentivizing working hard makes policing a highly favorable environment for the development and expression of workaholism symptoms. Previous works suggest that police officers are not exempt from workaholism tendencies, given that working hard and assigning centrality to work are considered normative and descriptive of the profession (Taris, van Beek, & Schaufeli, 2012). In light of the above considerations, we considered a police department a potentially interesting setting for testing our theoretical model.

27

and could be filled out at work or at home. Participants had 12 hours to fill out all questionnaires (questionnaires were time stamped from 8:00 a.m. to 8:00 p.m.). Participants were given the opportunity to participate in a lottery where 10 of them had the opportunity to win a token of approximately 50 euros.

Measures

Approximately 100 Italian state police officers working in a large police station were contacted and invited to take part in this study. Among them, 95 agreed to participate, but only 85 (53% were males) offered data that could be used for the aims of the present study (we excluded participants who responded at less than four time points; all remaining participants provided complete data). Mean age was 43.33 (SD = 4.58) years, and mean job tenure was 21.01 (SD = 4.78) years.

Most of the participants worked as members of patrols with assigned areas, and their main roles included the following: enforce laws and ordinances, regulate traffic, control crowds, prevent crime, and arrest violators. According to the police station records, the regular working time amounted to about seven hours per day with a mean overtime (voluntary and/or requested) of about three hours per day.

Workaholism (α = 0.88). Workaholism was measured by using the 10-item version of the Dutch work addiction scale (DUWAS; Schaufeli, Shimazu, & Taris, 2009b).

Example items included the following: “I feel that there’s something inside me that drives me to work hard” and “I stay busy and keep many irons in the fire,” which were rated from 1 (never) to 4 (always).

Job demands (αs ranged from .79 to .81). Every two weeks, job demands were measured by adapting three items from the Job Content Questionnaire (Karasek, Brisson, Kawakami, Houtman, Bongers, & Amick, 1998; for example, “During the last two weeks, I had much to do at work”) rated from one (strongly disagree) to five (strongly agree).

P-OCB (αs ranged from .81 to .85). Every two weeks, P-OCB was measured by adapting four items from Williams and Anderson’s (1991) scale (e.g., “During the last two weeks, I helped others who had been absent”) rated from 1 (never) to 5 (very often).

Personality Traits. Agreeableness (α = .78), emotional stability (α = .84), and conscientiousness (α = .81) were measured using a reduced version of the Big Five questionnaire-2 (BFQ-2; Caprara, Barbaranelli, Borgogni, & Vecchione, 2007). Each trait was assessed by 8 items, thus comprising 24 items in total. Respondents indicated agreement with the extent to which each item described them on a 5-point scale (1 = very false for me; 5 = very true for me).

Procedure

Data Analysis

One month before the start of the study (January 2015), participants completed a questionnaire aimed at collecting general sociodemographic data, their personality profile (in terms of the Big Five), and a measure of workaholism.

Then, participants completed questionnaires over three consecutive months, once every two weeks on Friday, assessing experienced job demands and P-OCB (for a total of 510 two-week spaced measurements). The spacing of the survey was decided in accordance with internal shift cycles (a complete shift lasted two weeks). Questionnaires were matched using anonymous codes that respondents created at the beginning of the survey from personal information. All questionnaires were administered online

The data gathered in this study had a multilevel (or hierarchical) structure with measurements nested within individuals. Thus, in order to estimate our hypotheses, we implemented a multilevel 2–1–1 mediational model. In this model, workaholism and covariates (personality traits) represent individual difference variables that vary between individuals (i.e., level 2 variables), whereas job demands and P-OCB represent variables with both withinindividual (level 1; i.e., variability across different weeks for the same person), and between-individual (level 2; i.e., variability across different individuals) variations.

Hypotheses were investigated within the framework of multilevel SEM (ML-SEM; Preacher, Zyphur, & Zhang,

Method Participants

© 2020 Hogrefe Publishing

Journal of Personnel Psychology (2020), 19(1), 24–32

28

G. Alessandri et al., The Costs of Workaholism

2010) using Mplus 8 (Muthén & Muthén, 1998–2017). In the case of a multilevel mediational model, ML-SEM allows disentangling between and within components of variance, thus reducing bias in the estimation of mediation effects in clustered data (Preacher et al., 2010). Model fit was assessed according to the following criteria: Yuan–Bentler (YB) χ2 likelihood ratio statistic, comparative fit index (CFI), root mean square error of approximation (RMSEA), and standardized root mean square residual for level 1 (SRMR_L1) and for level 2 (SRMR_L2). The model fit the data well according to the following criteria: nonsignificant YBχ2, CFI > 0.90, and RMSEA and SRMR < .08.

The critical values for the upper and lower confidence limits for indirect effects were tested by using the Monte Carlo method for assessing mediation CI (Hayes & Scharkow, 2013) with 20,000 replications. To compare the fit of the nested models, we used the Satorra–Bentler likelihood ratio test (ΔSBχ2).

that our study has (a) a between-level sample size higher than 80, (b) a low complexity of the between-level model (number of free parameters < 24), and (c) high ICCs (> .50), we deemed our design trustworthy for investigating the hypothesized model.

Results As reported in Table 1, job demands and P-OCB correlated significantly (p < .01) and negatively at both levels of analysis (r = .35 at level 1; r = .33 at level 2). At level 2, workaholism was significantly and moderately correlated with job demands (r = .28, p < .01) and P-OCB (r = .21, p < .05). Table 1 also shows the ICC, which assesses the size of level 2 variance compared to total variance (i.e., the sum of level 1 variance and level 2 variance): The results suggested that a substantial (ICC > .10) proportion of variance in job demands and P-OCB lies at level 2.

Power Consideration In multilevel analyses, the number of clusters (in crosssectional studies) or subjects (in dynamic designs, as our case) at the between-level plays the more important role in ensuring the asymptotic consistency of parameter estimations, impacting also their statistical significance (Meuleman & Billiet, 2009). A simulation study by Meuleman and Billiet (2009) found that, along with the between-level sample size, the complexity of the between-level model and the size of the intra-class correlations (ICCs) need to be considered. For example, they found that with a low complexity of the between-level model (i.e., fewer than 24 parameters to be estimated; see Meuleman & Billiet, 2009, Table 8) and high ICCs (i.e., > .50; see Meuleman & Billiet, 2009, Table 7) a between-level sample size of 80 led to a parameter bias that did not exceed 5% and a standard error bias that did not exceed 10%, as recommended by the literature on power analysis (e.g., Boomsma, 2013; Hoogland & Boomsma, 1998; L. K. Muthén & Muthén, 2002). Accordingly, given

Results from ML-SEM Analysis The results from ML-SEM analysis revealed that the hypothesized model fit the data very well, according to a nonsignificant χ2 [YBχ2(1) = 2.11, p = .15], and values of all other indices in agreement with the more stringent standards: CFI = .99; RMSEA = .046; SRMR_L1 = .001; SRMR_L2 = .024. At the “between-workers” level (level 2), after fixing the nonsignificant paths to zero (a) from emotional stability and conscientiousness to job demands and P-OCB, and (b) from agreeableness to job demands, the fit of the model did not significantly worsen [ΔSBχ2(5) = 7.25, p = .21]. Likewise, including a direct path from workaholism to P-OCB did not significantly improve the fit of the model [ΔSBχ2(1) = 2.60, p = .11]. All in all, the results (see Figure 1) supported the above presented theoretical model. Indeed, workaholism was significantly and strongly linked to job demands (H1), and the latter resulted as a

Table 1. Means, standard deviations, ICC, and zero-order correlations for variables at levels 1 and 2 1

2

3

4

1. Job demands

1

–

–.35

–

–

–

2. Workaholism

.28**

1

–

–

–

–

–

– –

1

–

.26**

1

**

3. P-OCB

–.33

1

–

4. Agreeableness

–.13n.s.

.56**

.22*

1

5. Conscientiousness

–.09

.28

.16

6. Emotional stability

–.11n.s.

**

n.s.

–.21* **

.30**

n.s.

–.14n.s.

.52

**

.20n.s.

5

6

Means

SD

ICC

1.71

1.23

.54

1.87

0.44

–

3.41

0.93

.61

4.01

0.39

–

3.91

0.41

–

3.61

0.64

–

Note. ICC = intraclass correlation coefficient; OCB = organizational citizenship behavior; P-OCB = prosocial organizational citizenship behavior. The correlations for job demands and P-OCB at the “within-individual” level (level 1) are reported above the diagonal. Correlations for the “between-individual” level (level 2) are reported below the diagonal. n.s.p > .05; *p < .05; **p < .01.

Journal of Personnel Psychology (2020), 19(1), 24–32

© 2020 Hogrefe Publishing

G. Alessandri et al., The Costs of Workaholism

29

Figure 1. The multilevel 2–1–1 mediation model with standardized estimates. Note. A = agreeableness; C = conscientiousness; E = emotional stability; JDM = job demands; P-OCB = prosocial organizational citizenship behavior; WHO = workaholism. Solid lines represent significant paths. Dotted lines represent nonsignificant paths. Estimation method was robust maximum likelihood (MLR in Mplus). **p < .01.

significant predictor of P-OCB (H2; R2 = .37). The indirect ( .07; 95% CI = .10, .001) effect linking workaholism to P-OCB was also significant (H3). At the within level of analysis (i.e., level 1), there was a significant prediction of P-OCB from job demands.

Discussion The present results supported the hypothesis that perceived and, perhaps, actively sought out job demands decreased workaholics’ P-OCB, which represents the core component of contextual performance, also after controlling for conscientiousness, emotional stability, and agreeableness. Thus, our results point to an organizational cost of workaholism, represented by its aversive impact on P-OCB. Our results call into question the notion that the tendency to work hard naturally makes a workaholic a good performer and align with previous research showing the costs of workaholism (e.g., Balducci et al., 2018). Yet, © 2020 Hogrefe Publishing

the indirect and negative link between workaholism and P-OCB suggests a further indirect link between workaholism and overall job performance that deserves attention in future research, as its direction (negative or positive) is not obvious. Indeed, on the one hand, it is likely that workaholic tendencies lead to working hard and thus to producing more. On the other hand, there is a risk that workaholics’ excessive in-role job performance may be canceled out by their lower contextual job performance.

At this point, a question arises, “Are workaholics ever a good investment for the organization?” Whereas our data did not allow us to offer an adequate answer to this question, we nonetheless surmise that a potential response is, “It depends on the kind of job.” Likely, jobs characterized by high job complexity, the need to express high competences, and jobs where performance depends less on the interdependence between workers may represent an optimal niche for workaholics. The gain may be much less, if not negative, in jobs characterized by a high degree of interdependence among workers. Given that helping coworkers requires individuals to expend both Journal of Personnel Psychology (2020), 19(1), 24–32

30

their time and effort (i.e., costs), it is not surprising that increased job demands is the key mechanism leading workaholics not to invest in P-OCB. Likely, in their heroic attempt to catch up with their work, workaholics do not perceive the possible rewards associated with P-OCB that often comes in the form of additional resources, emotional and instrumental support, and a sense of belonging. As postulated by the social exchange theory (Blau, 1964), it is likely that workaholics are not motivated to enact P-OCB probably because, from their perspective, the rewards may not outweigh the costs. At the same time, cooperativeness (i.e., agreeableness) is a tendency that is usually unrelated to workaholism (e.g., Clark et al., 2016).

Limitations This study has several limitations, including a limited level 2 sample size, the reliance on self-report questionnaires, and a research design that precludes any strict conclusion about causality. Furthermore, since the sample size consists of police officers only, findings of this study need to be replicated in samples of workers from different occupations. In this regard, it seems necessary to clarify to what extent the results we obtained were determined by the specific context or the selected sample. For example, in different settings and populations, other variables such as organizational culture, job role/level, or characteristics of the task may affect the indirect relationship between workaholism and P-OCB. Hence, these findings need to be replicated on different and larger samples, including, whenever possible, other-rated measures (e.g., coworkers, supervisors) of OCB. Furthermore, other aspects of contextual performance may be explored, as there may be differences in workaholics’ tendency to enact OCB directed toward individuals and workaholics’ tendency to enact OCB directed toward the organization.

Implications and Conclusion Our results have both practical and theoretical implications. From a practical standpoint, they may encourage practitioners to develop interventions that aim to make workers aware (a) that individuals with workaholic tendencies tend to perceive (and maybe contribute to create) high levels of job demands and that (b) this tendency may prevent them from performing OCB, an important component of contextual performance. Specifically, interventions aimed at preventing workaholism should target both the Journal of Personnel Psychology (2020), 19(1), 24–32

G. Alessandri et al., The Costs of Workaholism

environment and the workaholic (van Wijhe, Schaufeli, & Peeters, 2010). Programs should target rewarding appropriate behaviors (not excessive work) and supporting a healthy work–life balance. Training programs aiming at improving time management, stress management, assertiveness, and personal effectiveness skills may also be useful (Schabracq, 2005; van Wijhe et al., 2010). Finally, targeting workaholics’ social skills may promote positive interactions and social support at work, increasing the probability that the workaholics may invest resources in cooperative and P-OCB at work (Fligstein, 2001; van Wijhe et al., 2010).

From a theoretical point of view, our results are in line with the COR framework and contribute to our understanding of the correlates of workaholism, as they shed light on its association with P-OCB as an indicator of contextual performance. In particular, our study points to two undesirable organizational consequences of workaholism. The first is associated with the tendency of workaholics to save resources when it comes to invest in interpersonal relationships and they perceive to be versing in a stressful work condition. The second is the existence of a possible negative pathway linking workaholism to job performance through the mediation of perceived stress and the consequent disinvestment in a key component of contextual performance, namely, P-OCB. Clearly, given the lack in our study of a direct measure of job performance, the existence of this indirect pathway should be more directly tested in future studies. However, given the significant relationship between P-OCB and job performance attested in previous studies (Podsakoff et al., 2009), this seems a likely possibility.

Whereas most studies have investigated the association between workaholism and task performance, the present study focused on extra-role behaviors, for which less evidence is available, thus contributing to gain a more complete picture of the relationship between workaholism and job performance.

Of course, our study also raises some important questions.

For example, one may wonder about the mechanisms that may moderate the relationship between workaholic tendencies and job demands. Or, more in general, one may wonder about the optimal levels of job demands: The level maximizing workers’ performance on specific tasks while also leaving them additional resources to invest in extra-role behaviors, such as OCB, should be addressed in future studies.

In conclusion, our study sheds light on an important organizational cost of workaholism (in terms of an impaired contextual performance), and we hope that it contributes to stimulate future research that aims at helping workers in managing their approach to workload. © 2020 Hogrefe Publishing

G. Alessandri et al., The Costs of Workaholism

References Alessandri, G., Caprara, G. V., Eisenberg, N., & Steca, P. (2009).

Reciprocal relations among self-efficacy beliefs and prosociality across time. Journal of Personality, 77, 1229–1259. https://doi. org/10.1111/j.1467-6494.2009.00580.x Balducci, C., Avanzi, L., & Fraccaroli, F. (2018). The individual “costs” of workaholism: An analysis based on multisource and prospective data. Journal of Management, 44, 2961–2986. https:// doi.org/10.1177/0149206316658348 Baruch, Y. (2011). The positive well-being aspects of workaholism in cross cultural perspective. Career Development International, 16, 572–591. https://doi.org/10.1108/13620431111178335 Bateman, T. S., & Organ, D. (1983). Job satisfaction and the good soldier: The relationship between affect and employee “citizenship”. Academy of Management Journal, 26, 587–595. https://doi.org/10.2307/255908 Batson, C. D. (1998). Altruism and prosocial behavior. In D. T. Gilbert, S. T. Fiske, & G. Lindzey (Eds.), Handbook of social psychology (Vol. 2, pp. 282–316). Boston, MA: McGraw-Hill.

Blau, P. M. (1964). Exchange and power in social life. New York, NY: Wiley.

Boomsma, A. (2013). Reporting Monte Carlo studies in structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal, 20, 518–540. https://doi.org/10.1080/10705511.

2013.797839 Borman, W. C., & Motowidlo, S. J. (1997). Task performance and contextual performance: The meaning for personnel selection research. Human Performance, 10, 99–109. https://doi.org/10.

1207/s15327043hup1002_3 Burke, R. J. (1993). Workfamily stress, conflict, coping, and burnout among police officers. Stress Medicine, 9, 171–180. https://doi. org/10.1002/smi.2460090308 Caprara, G. V., Barbaranelli, C., Borgogni, L., & Vecchione, M. (2007).

Big Five questionnaire-2: manuale. Florence, Italy: Organizzazioni Speciali.

Chiaburu, D. S., Oh, I. S., Berry, C. M., Li, N., & Gardner, R. G. (2011). The five-factor model of personality traits and organizational citizenship behaviors: A meta-analysis. Journal of Applied Psychology, 96, 1140–1166. https://doi.org/10.1037/ a0024004.

Clark, M. A., Michel, J. S., Zhdanova, L., Pui, S. Y., & Baltes, B. B. (2016). All work and no play? A meta-analytic examination of the correlates and outcomes of workaholism. Journal of Management, 42, 1836–1873. https://doi.org/10.1177/0149206314522301 Cropanzano, R., Rupp, D. E., & Byrne, Z. S. (2003). The relationship of emotional exhaustion to work attitudes, job performance, and organizational citizenship behaviors. Journal of Applied Psychology, 88, 160–169. https://doi.org/10.1037/0021-9010.88.1.160 Davis, M. H. (1994). Empathy: A social psychological approach.

Madison, WI: Brown & Benchmark.

Eisenberg, N., Fabes, R. A., Murphy, B., Karbon, M., Maszk, P., Smith, M., … Suh, K. (1994). The relations of emotionality and regulation to dispositional and situational empathy-related responding. Journal of Personality and Social Psychology, 66, 776–797. https://doi.org/10.1037/0022-3514.66.4.776 Eisenberg, N., & Okun, M. A. (1996). The relations of dispositional regulation and emotionality to elders’ empathy-related responding and affect while volunteering. Journal of Personality, 64, 157–183. https://doi.org/10.1111/j.1467-6494.1996.tb00818.x Fligstein, N. (2001). Social skill and the theory of fields. Sociological Theory, 19, 105–125. https://doi.org/10.1111/0735-2751.00132 Hall, G. B., Dollard, M. F., Tuckey, M. R., Winefield, A. H., & Thompson, B. M. (2010). Job demands, workfamily conflict, and emotional exhaustion in police officers. Journal of Occupational

© 2020 Hogrefe Publishing

31

and Organizational Psychology, 83, 237–250. https://doi.org/10.

1348/096317908X401723 Hayes, A. F., & Scharkow, M. (2013). The relative trustworthiness of inferential tests of indirect effects in statistical mediation analysis: Does method really matter? Psychological Science, 24, 1918–1927. https://doi.org/10.1177/0956797613480187 Hobfoll, S. E. (1989). Conservation of resources: A new attempt at conceptualizing stress. American Psychologist, 44, 513–524. https://doi.org/10.1037/0003-066X.44.3.513 Hobfoll, S. E. (2001). The influence of culture, community, and the nested-self in the stress process: Advancing conservation of resources theory. Applied Psychology: An International Review, 50, 337–421. https://doi.org/10.1111/ 1464-0597.00062 Hoogland, J. J., & Boomsma, A. (1998). Robustness studies in covariance structure modeling: An overview and a metaanalysis. Sociological Methods & Research, 26, 329–367. https:// doi.org/10.1177/0049124198026003003 Kaplan, S., Bradley, J. C., Luchman, J. N., & Haynes, D. (2009). On the role of positive and negative affectivity in job performance: A meta-analytic investigation. Journal of Applied Psychology, 94, 162–176. https://doi.org/10.1037/a0013115 Karasek, R., Brisson, C., Kawakami, N., Houtman, I., Bongers, P., & Amick, B. (1998). The job content questionnaire (JCQ): An instrument for internationally comparative assessments of psychosocial job characteristics. Journal of Occupational Health Psychology, 3, 322–355. https://doi.org/10.1037/1076-8998.3.4.322 Koopman, J., Lanaj, K., & Scott, B. A. (2016). Integrating the bright and dark sides of OCB: A daily investigation of the benefits and costs of helping others. Academy of Management Journal, 59, 414–435. https://doi.org/10.5465/amj.2014.0262 Liberman, A. M., Best, S. R., Metzler, T. J., Fagan, J. A., Weiss, D. S., & Marmar, C. R. (2002). Routine occupational stress and psychological distress in police. Policing: An International Journal of Police Strategies & Management, 25, 421–441. https://doi.org/10.

1108/13639510210429446 Lowman, R. L. (1993). Counseling and psychotherapy of work dysfunctions. Washington, DC: American Psychological Association.

Meuleman, B., & Billiet, J. (2009). A Monte Carlo sample size study: How many countries are needed for accurate multilevel SEM? Survey Research Methods, 3, 45–58. https://doi.org/10.18148/ srm/2009.v3i1.666 Muthén, L. K., & Muthén, B. O. (2002). How to use a Monte Carlo study to decide on sample size and determine power. Structural Equation Modeling: A Multidisciplinary Journal, 9, 599–620. https://doi.org/10.1207/S15328007SEM0904_8 Muthén, L. K., & Muthén, B. O. (1998–2017). Mplus user’s guide (8th ed.). Los Angeles, CA: Muthén & Muthén.

Ng, T. W. H., Eby, L. T., Sorensen, K. L., & Feldman, D. C. (2005).

Predictors of objective and subjective career success: A metaanalysis. Personnel Psychology, 58, 367–408. https://doi.org/10.

1111/j.1744-6570.2005.00515.x Ng, T. W. H., Sorensen, K. L., & Feldman, D. C. (2007). Dimensions, antecedents, and consequences of workaholism: A conceptual integration and extension. Journal of Organizational Behavior, 28, 111–136. https://doi.org/10.1002/job.424 Oates, W. (1971). Confessions of a workaholic: The facts about work addiction. New York, NY: World.

Okun, M. A., Shepard, S. A., & Eisenberg, N. (2000). The relations of emotionality and regulation to dispositional empathy-related responding among volunteers-in-training. Personality and Individual Differences, 28, 367–382. https://doi.org/10.1016/S01918869(99)00107-5 Organ, D. W. (2018). Organizational citizenship behavior: Recent trends and developments. Annual Review of Organizational

Journal of Personnel Psychology (2020), 19(1), 24–32

32

Psychology and Organizational Behavior, 5, 295–306. https://doi. org/10.1146/annurev-orgpsych-032117-104536 Organ, D. W. (1988). Organizational citizenship behavior: The good soldier syndrome. Lexington, MA: Lexington Books.

Podsakoff, N. P., Whiting, S. W., Podsakoff, P. M., & Blume, B. D. (2009). Individual- and organizational-level consequences of organizational citizenship behaviors: A meta-analysis. Journal of Applied Psychology, 94, 122–141. https://doi.org/10.1037/ a0013079 Porter, G. (1996). Organizational impact of workaholism: Suggestions for researching the negative outcomes of excessive work.

Journal of Occupational Health Psychology, 1, 70–84. https://doi. org/10.1037/1076-8998.1.1.70 Preacher, K. J., Zyphur, M. J., & Zhang, Z. (2010). A general multilevel SEM framework for assessing multilevel mediation. Psychological Methods, 15, 209–233. https://doi.org/10.1037/a0020141 Robinson, B. E. (1999). The work addiction risk test: Development of a tentative measure of workaholism. Perceptual and Motor Skills, 88, 199–210. https://doi.org/10.2466/pms.1999.88.1.199 Schabracq, M. J. (2005). Well-being and health. What HRM can do about it. In R. J. Burke & C. L. Cooper (Eds.), Reinventing HRM: Challenges and new directions (pp. 187–206). London, UK: Routledge.

Schaufeli, W. B., Bakker, A. B., van der Heijden, F. M. M. A., & Prins, J. T. (2009a). Workaholism, burnout, and well-being among junior doctors: The mediating role of role conflict. Work & Stress, 23, 155–172. https://doi.org/10.1080/02678370902834021 Schaufeli, W. B., Shimazu, A., & Taris, T. W. (2009b). Being driven to work excessively hard: The evaluation of a two-factor measure of workaholism in The Netherlands and Japan. Cross-Cultural Research, 43, 320–348. https://doi.org/10.1177/1069397109337239 Schaufeli, W. B., Taris, T. W., & Bakker, A. B. (2008a). It takes two to tango: Workaholism is working excessively and working compulsively. In R. J. Burke & C. L. Cooper (Eds.), The long work hours culture: Causes, consequences and choices (pp. 203–225).

Bingley, UK: Emerald.

Schaufeli, W. B., Taris, T. W., & van Rhenen, W. (2008b). Workaholism, burnout, and work engagement: Three of a kind or three different kinds of employee well-being? Applied Psychology: An International Review, 57, 173–203. https://doi.org/10.1111/j.14640597.2007.00285.x Scott, K. S., Moore, K. S., & Miceli, M. P. (1997). An exploration of the meaning and consequences of workaholism. Human Relations, 50, 287–314. https://doi.org/10.1177/001872679705000304 Snir, R., & Zohar, D. (2008). Workaholism as discretionary time investment at work: An experience-sampling study. Applied Psychology: An International Review, 57, 109–127. https://doi. org/10.1111/j.1464-0597.2006.00270.x Spence, J. T., & Robbins, A. S. (1992). Workaholics: Definition, measurement, and preliminary results. Journal of Personality Assessment, 58, 160–178. https://doi.org/10.1207/s15327752jpa5801_15 Taris, T. W., van Beek, I., & Schaufeli, W. B. (2012). Demographic and occupational correlates of workaholism. Psychological Reports,

Journal of Personnel Psychology (2020), 19(1), 24–32

G. Alessandri et al., The Costs of Workaholism

110, 547–554. https://doi.org/10.2466/03.09.17.PR0.110.2.547554 van Wijhe, C., Schaufeli, W. B., & Peeters, M. C. (2010). Understanding and treating workaholism: Setting the stage for successful interventions. In C. L. Cooper & R. J. Burke (Eds.), Psychological and behavioural risks at work (pp. 107–134). Chichester, UK: Wiley.

Vila, B. (2006). Impact of long work hours on police officers and the communities they serve. American Journal of Industrial Medicine, 49, 972–980. https://doi.org/10.1002/ajim.20333 Violanti, J. M. (1997). Suicide and the police role: A psychosocial model. Policing: An International Journal of Police Strategies & Management, 20, 698–715. https://doi.org/10.1108/ 13639519710368107 Webster, J. H. (2013). Police officer perceptions of occupational stress: The state of the art. Policing: An International Journal of Police Strategies & Management, 36, 636–652. https://doi.org/ 10.1108/PIJPSM-03-2013-0021 Williams, L. J., & Anderson, S. E. (1991). Job satisfaction and organizational commitment as predictors of organizational citizenship and in-role behaviors. Journal of Management, 17, 601–617. https://doi.org/10.1177/014920639101700305 Ziegler, R., Schlett, C., Casel, K., & Diehl, M. (2012). The role of job satisfaction, job ambivalence, and emotions at work in predicting organizational citizenship behavior. Journal of Personnel Psychology, 11, 176–1s90. https://doi.org/10.1027/1866-5888/ a000071 History Received November 11, 2018 Revision received July 2, 2019 Accepted July 4, 2019 Published online July 3, 2020 Funding Guido Alessandri was supported by a research grant (named “Progetto di Ateneo,” no. RM11715C809391B1) awarded by the Sapienza University of Rome. Enrico Perinelli was supported by a research fellowship (research title: “WeBeWo LAB: Quality of Social Relationships in Workplace,” number: 40103205) granted by the Autonomous Province of Trento and the Department of Psychology and Cognitive Science (University of Trento).

ORCID Guido Alessandri  https://orcid.org/0000-0003-4731-5248 Guido Alessandri Department of Psychology Sapienza University of Rome Via dei Marsi 78 00185 Rome Italy guido.alessandri@uniroma1.it

© 2020 Hogrefe Publishing

Original Article

Are All Challenges Equal?

Goal Orientations and Their Relationship With Private and Public Challenging Job Experiences Roy B. L. Sijbom1, Bernd Carette2,3, and Nicoletta G. Dimitrova2,4 Department of Work and Organizational Psychology, University of Amsterdam, The Netherlands

1

Department of Personnel Management, Work and Organizational Psychology, Ghent University, Ghent, Belgium

2

Deloitte, Belgium

3

Department of Human Resources and Organisational Behaviour, University of Greenwich Business School, London, UK

4

Abstract. This study seeks to advance theory on the motivational underpinnings of striving for challenge. We propose and empirically demonstrate that challenging job experiences can be meaningfully subdivided into private challenging job experiences (private challenges) and public challenging job experiences (public challenges). Drawing on achievement goal theory, in a two-wave field study among 226 employees (Study 1) and a multi-source field study among 326 employees (Study 2), we found initial evidence regarding differential effects of employees’ mastery-approach goals and performance-approach goals in relation to private challenges and public challenges. Furthermore, Study 2 showed a negative relationship between performance-approach goals and supervisor-rated in-role job performance when public challenges were low.

Theoretical and practical implications of these findings are discussed.

Keywords: job challenge, employee development, challenging experiences, mastery goal orientation, performance goal orientation

Challenging job experiences have been considered to be one of the most important determinants of employee development (DeRue & Wellman, 2009; Dong, Seo, & Bartol, 2014).

Notwithstanding the developmental possibilities of challenging job experiences, people may differ in the extent to which they are motivated, and thus willing, to perform challenging tasks. People’s motivation is a fundamental driving force of performing specific tasks, yet surprisingly little research examined motivational factors that may cause employees to perform challenging tasks in their jobs (for an exception, see Preenen, Van Vianen, & De Pater, 2014).

Drawing on achievement goal theory (Dweck & Leggett, 1988; Elliot & Church, 1997), we investigate employees’ goal orientation as a motivational construct that may affect how individuals approach, interpret, and perform challenging tasks. Goal orientation represents competencerelevant aims that individuals adopt and pursue in achievement situations (DeShon & Gillespie, 2005). Our core argument is that individuals’ desire to enhance competence (i.e., mastery goals) or to demonstrate competence (i.e., performance goals) may determine their preference for particular challenging job experiences.

Individuals pursuing mastery goals are primarily focused on learning and development (Dweck, 1986), which makes challenging tasks that hold developmental potential © 2020 Hogrefe Publishing

interesting for them. In contrast, individuals pursuing performance goals may only be interested in challenging tasks in which competence can be demonstrated to others or favorable judgments can be gained (e.g., recognition and external rewards) (Dweck, 1986; Farr, Hofmann, & Ringenbach, 1993). Based on characteristics of challenging job experiences, we argue that a fruitful distinction can be made between, what we label, private challenging job experiences (private challenges) and public challenging job experiences (public challenges). Accordingly, we examine differential effects of individuals’ goal orientation in relation to these challenging job experiences.

Although employees may have a preference for particular challenging tasks, oftentimes challenging tasks are a relatively fixed part of the working environment. Therefore, drawing on insights from the person–environment (P–E) fit literature (Edwards, Caplan, & van Harrison, 1998), we also examine the impact that alignment between employees’ goal orientation and challenging job experiences might have on one’s in-role job performance. Specifically, we expect individuals pursuing performance-approach (PAp) goals to be sensitive to (mis)alignment of challenging job experiences because of their motivation to demonstrate competence relative to others. Together, our research advances theory and practice on challenging tasks through the implication that challenging job experiences differ, and that employees Journal of Personnel Psychology (2020), 19(1), 33–43 https://doi.org/10.1027/1866-5888/a000241

34

R. B. L. Sijbom et al., Goal Orientations and Challenging Job Experiences

might prefer different challenging job experiences depending on their motivational goal strivings.

study, we focus on the effects of stable employees’ goal orientations specific to the work domain.

Conceptualization of Goal Orientation

Challenging Job Experiences

Goal orientations are perceptual–cognitive frameworks that describe how individuals define, interpret, and respond to competence-relevant achievement situations, including the workplace (DeShon & Gillespie, 2005; Dweck & Leggett, 1988). Two main types of goal orientations that individuals adopt in achievement situations are mastery goals (also termed learning goals) and performance goals (Dweck, 1986; Farr et al., 1993). Individuals who pursue mastery goals are motivated to develop competence by acquiring new skills and mastering new situations. Individuals who pursue performance goals are motivated to demonstrate and validate one’s competence by seeking favorable judgments and by outperforming others (Elliot & Church, 1997; Dweck, 1986).

Researchers further bifurcated mastery goals and performance goals in approach and avoidance versions (Elliot, 1999; Elliot & McGregor, 2001). Approach goals are directed toward positive or desirable events, whereas avoidance goals are directed toward avoiding negative or undesirable outcomes (Elliot & McGregor, 2001). This resulted in a 2 × 2 framework, or four-factor model, of goal orientations (Baranik, Barron, & Finney, 2007; Elliot & McGregor, 2001), in which four different types of goal orientations people can pursue are distinguished. Masteryapproach (MAp) goals reflect a desire to perform better than one has done before; mastery-avoidance (MAv) goals reflect a desire to avoid performing worse than one has done before; PAp goals reflect a desire to demonstrate competence relative to others and to gain favorable judgment about it; and performance-avoidance (PAv) goals reflect a desire to avoid demonstrating incompetence relative to others and to avoid negative judgments about it (Baranik et al., 2007; Elliot & Church, 1997; Elliot & Moller, 2003). Our conceptualization of PAp goals and PAv goals consists of a competence demonstration aspect and a normative evaluation aspect (cf. Elliot & Church, 1997).

Although different conceptualizations of goal orientations are used in the literature (see DeShon & Gillespie, 2005), we conceptualize and operationalize goal orientation as an individual trait-like variable that is relatively stable over time in a specific achievement domain (i.e., work domain) (Payne, Youngcourt, & Beaubien, 2007; VandeWalle & Cummings, 1997). That is, in our Journal of Personnel Psychology (2020), 19(1), 33–43

Challenging job experiences fulfill a pivotal role in the process of individual skill development (e.g., McCauley, Ruderman, Ohlott, & Morrow, 1994). This is because challenging job experiences put employees in dynamic situations for which existing tactics and routines are inadequate and that require new ways of dealing with work situations. Oftentimes, these tasks are complex and decisions need to be made under conditions of uncertainty and risk. Although execution of challenging tasks may be stressful, it may result in positive feelings (Cavanaugh, Boswell, Roehling, & Boudreau, 2000). That is, if employees successfully handle challenging job experiences, they can feel a sense of achievement or they might receive material gains such as a better chance for promotion and pay raises.

The extent to which a job is challenging depends on the presence of a number of job features relating to the roles, responsibilities, tasks, and context in which one is operating (DeRue & Wellman, 2009; McCauley et al., 1994). In line with prior research, we conceive challenging job experiences as “job characteristics that provide individuals with the opportunity and motivation to learn and that may result in the development of a wide range of skills, abilities, insights, knowledge, and values” (De Pater, Van Vianen, Bechtoldt, & Klehe, 2009, p. 299). Employees will thus experience challenge when there are unusual problems to solve, risky decisions to be made, and/or difficult obstacles have to be overcome (De Pater, Van Vianen, Fischer, & Van Ginkel, 2009).

Distinguishing Between Private and Public Challenges Although all challenging job experiences share the notion of complexity and the holding of a developmental potential (e.g., DeRue & Wellman, 2009), we argue that challenging job experiences may also differ on other relevant aspects.

First, challenging job experiences may differ in the extent to which the content of work tasks is clearly defined.

Challenging job experiences may consist of clear expectations of what has to be done (e.g., give a presentation), but they may also be more ambiguous (e.g., deal with tasks that are relatively new for you). Second, tasks can be executed in sight (high visibility) or out of sight of others (low visibility), meaning that the extent to which progress © 2020 Hogrefe Publishing

R. B. L. Sijbom et al., Goal Orientations and Challenging Job Experiences

and outcomes are visible to others may differ. Taking these distinguishing features into account may help to improve our understanding of why individuals are motivated, and thus willing, to execute certain types of challenging job experiences. Therefore, we propose to make a distinction between private and public challenges.

We conceptualize private challenges as work activities that are challenging, are relatively ambiguous regarding task content (i.e., unclear which activities are involved), and for which progress and/or outcomes are not necessarily visible to others. Although these challenging experiences can entail some level of visibility, this is not characteristic of these experiences. In contrast, we conceptualize public challenges as work activities that are challenging, are clearly defined, and for which progress and outcomes are inextricably linked with visibility to others (e.g., tasks carried out in sight of others). This conceptualization is in line with the notion that some challenges can be seen as opportunities to demonstrate competence visible to others (Dragoni, Tesluk, Russell, & Oh, 2009). The visibility of outcomes and progress to others makes public challenges excellent opportunities for gaining status, rewards, and acknowledgment within a team and/or organization.

Mastery-Approach Goals and Private and Public Challenges Individuals pursuing MAp goals are focused on developing and gaining competence by acquiring new skills and mastering new situations (Elliot & McGregor, 2001). Their focus on skill development implies an intrinsic interest in understanding and mastering challenging tasks. Given that both private and public challenges contain opportunities for task mastery, it turns them into excellent learning experiences to fulfill their developmental goals. Research evidence indeed shows that MAp goals are positively related to performing challenging tasks (Preenen et al., 2014). Furthermore, MAp goals are associated with adaptive responses in handling challenging situations, such as enhanced explorative interest and learning opportunity appraisals in response to voiced ideas (Sijbom, Janssen, & Van Yperen, 2015a, 2015b). In line with previous findings, we expect that employees’ MAp goals will be positively related to private and public challenges because these experiences foster an intrinsic interest in the task itself, like learning new skills and mastering new situations. Accordingly, we hypothesize the following: © 2020 Hogrefe Publishing

35

Hypothesis 1 (H1): Employees’ MAp goals are positively related to private (H1a) and public (H1b) challenges.

Mastery-Avoidance Goals and Private and Public Challenges Individuals pursuing MAv goals focus on the preservation of existing competencies and skills (Elliot & McGregor, 2001). Consequently, they may primarily focus on tasks that are familiar, well-understood, and allow for evaluation of existing skills. Indeed, they prefer nonchallenging tasks over challenging tasks because the latter may make stagnation of development salient (Elliot & McGregor, 2001). Given that private and public challenges allow for learning new skills, employees pursuing MAv goals may be actively seeking for easier tasks rather than more challenging tasks. Although research on MAv goals is scarce, the available research provides some evidence for our argumentation. For example, MAv goals have been shown to be deleterious for performance improvement (Van Yperen, Elliot, & Anseel, 2009). Also, having an avoidance orientation is negatively linked to seeking challenging job experiences (Elliot, 1999). However, research by Preenen et al. (2014) found a null relationship between MAv goals and performance of challenging tasks.

Based on our argumentation and previous findings, we hypothesize the following: Hypothesis 2 (H2): Employees’ MAv goals are negatively related to private (H2a) and public (H2b) challenges.

Performance-Approach Goals and Public Challenges Employees pursuing PAp goals are focused on demonstration of competence and outperforming others (Dweck, 1986; Elliot & Moller, 2003). Consequently, they may primarily focus on challenging job experiences that are visible to others because this is instrumental in appearing competent and for gaining favorable judgments. That is, by executing public challenges, others (i.e., leaders, colleagues) may notice how well one is executing challenging work tasks. Likewise, excelling on tasks that are more complicated than those of one’s coworkers might serve the purpose of showing that one performs better than others.

Journal of Personnel Psychology (2020), 19(1), 33–43

36

R. B. L. Sijbom et al., Goal Orientations and Challenging Job Experiences

Additionally, performing well on visible challenging tasks may results in external rewards, such as acknowledgment or attainment of favorable judgments (VandeWalle & Cummings, 1997). These external rewards may be perceived as an affirmation of superior ability and are likely to be valued by individuals pursuing PAp goals.

Given that individuals pursuing PAp goals want to secure favorable evaluations (VandeWalle & Cummings, 1997), they are likely to use rehearsal and preparation of activities as learning strategies (Elliot, McGregor, & Gable, 1999; Steele-Johnson, Beauregard, Hoover, & Schmidt, 2000). That is, by rehearsing and preparing the activities that need to be executed, they are able to perform well on these tasks, especially tasks for which the content is (relatively) clear do allow for (a certain degree of) preparation and rehearsal. Accordingly, PAp goals can be expected to be positively related to public challenges because these tasks provide clarity about which activities are involved and may thus allow for such rehearsal. We do not expect PAp goals to be related to private challenges because execution of these tasks is associated with less visibility. Also, there is more ambiguity on which activities are involved, making these tasks less suitable for rehearsal.

Taken together, we hypothesize the following: Hypothesis 3 (H3): Employees’ PAp goals are positively related to public challenges.

Performance-Avoidance Goals and Public Challenges Individuals motivated by PAv goals are striving to avoid incompetence relative to others (Elliot & Church, 1997).

Challenging achievement situations in which their performance is directly visible to others (i.e., public challenges) may therefore be perceived as threatening. That is, challenging job tasks entail the risk of failure and thereby demonstration of inability or poor performance relative to others. Given this perceived risk and the motivation to avoid negative evaluative judgments, individuals motivated by PAv goals may prefer to perform nonchallenging tasks by which demonstration of incompetence can be avoided. As such, they will actively avoid seeking and executing public challenging job tasks.

In line with this argumentation, meta-analytic results showed that PAv goals were negatively linked to the difficulty of self-set goals (Payne et al., 2007), meaning that PAv goals are negatively related to challenge seeking.

Furthermore, research consistently showed that PAv goals are linked to maladaptive outcomes, such as reduced Journal of Personnel Psychology (2020), 19(1), 33–43

interest in the task at hand, self-handicapping, and anxiety (e.g., Elliot & Church, 1997; Elliot & McGregor, 2001).

Accordingly, we hypothesize the following: Hypothesis 4 (H4): Employees’ PAv goals are negatively related to public challenges.

The Effects of Goal Orientation and Challenging Job Experiences on In-role Job Performance Although employees may prefer certain challenging job experiences, oftentimes these experiences can be regarded as a relatively fixed characteristic of tasks that need to be executed. As such, these tasks may be more privately or publicly challenging in nature. We expect that a (mis)fit between employees’ goal strivings and the nature of challenging tasks might impact in-role job performance.

Here, we particularly focus on the effects of PAp goals for two reasons. First, meta-analytic findings show that the relationship between PAp goals and performance is inconsistent (Payne et al., 2007), which suggests the likely presence of moderator variables. Second, for employees pursuing PAp goals, in-role job performance may serve as information for social comparison and competence demonstration (Elliot, 1999). Accordingly, the association between individuals’ PAp goals and in-role job performance can best be understood by taking the public challenging characteristics of job experiences into account.

We expect that the relative presence/absence of public challenges may affect the motivation of individuals with PAp goals to perform well on these tasks. When challenging job experiences are highly present in one’s tasks, this means the performance is visible to others. Under these conditions, individuals pursuing PAp goals may be motivated to perform well because their performance directly serves their goal of competence demonstration. That is, performing well allows them to secure external approval and positive external evaluations. When job tasks are characterized by relatively low levels of public challenges, performance is less visible to other members in the organization. Under these conditions, individuals pursuing PAp goals may be less motivated to perform well because it is not instrumental to achieving their goal of demonstrating competence relative to others. Accordingly, a negative relationship can be expected under these conditions. Therefore, we hypothesize the following: Hypothesis 5 (H5): The relationship between employees’ PAp goals and in-role job performance is © 2020 Hogrefe Publishing

R. B. L. Sijbom et al., Goal Orientations and Challenging Job Experiences

moderated by public challenges, such that this relationship is positive (negative) when public challenges are high (low).

37

38.40 years (SD = 11.27), and the average tenure was 14.87 years (SD = 11.47).

Measures

Study 1 Method Participants and Procedure We conducted a temporally lagged survey design with a four-month time lag. We used a convenience sample of Belgian employees who were invited personally or by email via professional network contacts (e.g., LinkedIn) to participate in the study. Participants received either a digital questionnaire or a hardcopy. At Time 1, 650 questionnaires were distributed. We received 555 questionnaires of which 452 could be used (T1 response rate = 69.5%). At Time 2, we were able to contact 360 participants to fill out the questionnaire. We received 256 questionnaires of which 226 could be used for further analyses (T2 response rate = 62.8%). Our final sample, therefore, consisted of 226 participants who completed all relevant study variables at T1 and T2 (overall response rate = 34.8%; 52.2% were female; and 70.4% were employed in private sector organizations). The mean age was

Goal Orientation (T1) Employees’ goal orientations were assessed using the 18item goal orientation in a work domain measure (Baranik et al., 2007). Scale items were translated into Dutch using a translation back-translation procedure. The items were rated on a scale ranging from 1 (totally disagree) to 5 (totally agree). An example item for PAp goals (four items) is “I like to show that I can perform better than my coworkers”; for MAp goals (four items), “I often look for opportunities to develop new skills and knowledge”; for PAv goals (four items), “I would avoid taking on a new task if there was a chance that I would appear rather incompetent to others”; and for MAv goals (six items), “At work, I focus on not doing worse than I have personally done in the past on my job.”

Private and Public Challenges (T2) Private challenges were measured using four items, from the 10-item job challenge measure of De Pater et al.

(2010), which were conceptually aligned with our construct. An example item is “In my job I have to deal with

Table 1. Rotated factor loadings of a two-dimensional job challenge EFA model Job challenge feature

Designated challenge dimension

Factor 1

1. In my job I have to deal with tasks that are relatively new to me and that, strictly speaking, are not directly linked to my education and experience.

Private

0.907

Factor 2

2. It is my responsibility to start up or try out something new or to initiate strategic changes in my division.

Private

0.608

3. I am responsible for a diverse range of job responsibilities. For instance, I am responsible for several projects, services, workgroups, technologies, etc.

Private

0.669

4. It is my responsibility to manage relationships with important external contacts and organizations, such as clients, commissioners, and specific occupational groups.

Public

5. For others, mainly the management, I personify a specific project within my organization.

Public

6. It is my responsibility to co-operate with individuals originating from diverse cultures or organizations or with organizations in other countries.

Private

7. It is a part of my job to regularly make my appearance in public, for instance, to present my work at conferences or represent my organization.

Public

0.787

8. It is my responsibility to perform activities that are highly visible for others in my organization, for instance for (top) management. As a consequence, my successes and failures are easily observable to others.

Public

0.834

9. To function effectively, I have to use my influence with others, who formally are not subjected to my authority, such as (top) management and important individuals working for other divisions.

Public

0.808

10. It is my responsibility to carry out tasks that my colleagues consider risky.

Public

0.617

0.511

Note. Italicized items were excluded from further analyses. EFA = exploratory factor analysis.

© 2020 Hogrefe Publishing

Journal of Personnel Psychology (2020), 19(1), 33–43

38

R. B. L. Sijbom et al., Goal Orientations and Challenging Job Experiences

tasks that are relatively new to me and that, strictly speaking, are not directly linked to my education and experience.” Public challenges were measured using six items from the measure of De Pater et al. (2010) that were conceptually aligned with our construct. An example item is “It is a part of my job to regularly make my appearance in public, for instance, to present my work at conferences or represent my organization.” In Table 1, all items for the scales are presented. For both scales, respondents indicated, on a scale ranging from 1 (does not apply to me at all) to 5 (very much applies to me), the extent to which challenging job aspects were applicable to their current job situation. In the next section, we provide further evidence for the validity of these two dimensions.

Control Variables (T1) We measured gender (0 = male; 1 = female) as a potential control variable because previous research showed that women are given fewer challenging assignments than their male colleagues (De Pater et al., 2010).

Data Considerations and Preliminary Analyses Our data included missing values (0.14% of all values were missing). As Little’s missing completely at random (MCAR) test (χ2[173, N = 226] = 172.51, p = .50) was not statistically significant (i.e., missing values are completely random), the expectation maximization (EM) estimation in SPSS 24.0 was used to impute the missing values (Collins, Schafer, & Kam, 2001). Because some of the predictors were correlated (see Table 2), variance inflation factors (VIF) were examined. The VIF values (< 1.43) indicated that multicollinearity was not a problem in these data.

To examine the viability of our two-dimensional job challenge model, we examined the scales’ internal

reliability and conducted an exploratory factor analysis (EFA) using Oblimin Rotation on the 10 items. The reliability of the four-item private challenges scale was relatively low (α = .68). Removing item 6 (see Table 1) would improve the reliability of the scale (α = .73). From our EFA, two factors emerged. However, item 5 (see Table 1 for exact item) loaded high on both factors. Based on these considerations, we excluded both item 5 and item 6 and re-ran the EFA. The factor loadings of this final analysis are presented in Table 1 and provide initial support for our two-dimensional job challenge model. Accordingly, we used three items to measure private challenges (α = .73) and five items to measure public challenges (α = .80).

To further validate the conceptual distinction between private and public challenges, we examined whether both scales differed on clarity of work task and visibility of task execution. For each challenging job experience, participants answered questions related to clarity of work task (e.g., “This work task is clearly defined”; four items with α in the range of .84–.93) and visibility of task execution (e.g., “The execution of this work task is visible to others”; four items with α in the range of .84–.91) using a scale ranging from 1 (totally disagree) to 5 (totally agree). Results of this study (N = 153 using MTurk; Mage = 37.11 years, 39.5% women, Mtenure = 15.87 years) showed that public challenges were more clearly defined (M = 3.40, SD = 0.69) than private challenges (M = 3.10, SD = 0.91), t(152) = 5.21, p < .001. Also, the visibility of task execution was higher for public challenges (M = 3.86, SD = 0.60) than for private challenges (M = 3.43, SD = 0.65), t(152) = 7.86, p < .001.

These results provide additional evidence for our conceptual distinction.

Finally, we conducted confirmatory factor analyses (CFAs) using AMOS 25.0 with maximum likelihood estimations. Results showed that our two-dimensional job challenge model provided an acceptable fit to the data: χ2(19) = 35.087, p = .014; comparative fit index (CFI) = .973;

Table 2. Descriptive statistics, correlations, and reliability estimates of Study 1 variables Variable

M

SD

1.

2.

3.88

0.63

.04

(.75)

3.01

0.96

.06

.21**

(.88)

MAv goals (T1)

3.80

0.66

.11

.16*

.23**

(.74)

PAv goals (T1)

2.55

0.88

.00

.29**

.34**

.25**

1.

Gender (T1)

0.52

2.

MAp goals (T1)

3.

PAp goals (T1)

4.

5.

3.

4.

5.

6.

7.

(.86)

6.

Private challenges (T2)

2.90

1.00

.18**

.29**

.12

.09

.12

(.73)

7.

Public challenges (T2)

2.75

0.97

.22**

.29**

.19**

.09

.03

.63**

(.80)

Note. N = 226; *p < .05; **p < .01; MAp = mastery-approach; MAv = mastery-avoidance; PAp = performance-approach; PAv = performance-avoidance; Private challenges = private challenging job experiences; Public challenges = public challenging job experiences. For the dichotomous variable gender, the mean denotes the percentage of females. Reliability estimates (Cronbach’s α) are presented on the diagonal.

Journal of Personnel Psychology (2020), 19(1), 33–43

© 2020 Hogrefe Publishing

R. B. L. Sijbom et al., Goal Orientations and Challenging Job Experiences

39

Table 3. Results of path analysis for both Study 1 (N = 226) and Study 2 (N = 326) Study 1 (gender included as a control variable)

Study 1 Hypothesis

Path

Estimate

SE

β

p

Estimate

SE

β

Study 2 p

Estimate

SE

β

p

H1a

MAp goals → Public

.47

.11

.31

<.001

.46

.11

.30

<.001

.38

.08

.26

<.001

H1b

MAp goals → Private

.43

.11

.27

<.001

.42

.11

.27

<.001

.33

.08

.25

<.001

H2a

MAv goals → Public

.27

.10

.19

.005

.24

.10

.16

.013

.12

.09

.09

.169

H2b

MAv goals → Private

.23

.10

.15

.025

.20

.10

.13

.050

.07

.09

.05

.436

PAp goals → Public

.16

.07

.15

.029

.14

.07

.14

.040

.27

.07

.24

<.001

PAp goals → Private

.11

.07

.11

.126

.10

.07

.10

.160

.00

.07

.00

.982

H3 H4

PAv goals → Public

.06

.08

.05

.463

.06

.08

.05

.497

.07

.07

.06

.352

PAv goals → Private

.05

.09

.04

.578

.05

.08

.05

.535

.04

.07

.04

.592

Note. MAp = mastery-approach; MAv = mastery-avoidance; PAp = performance-approach; PAv = performance-avoidance; Private = private challenging job experiences; Public = public challenging job experiences.

Tucker-Lewis index (TLI) = .948; and root mean square error of approximation (RMSEA) = .061. The fit was significantly better than the fit of a unidimensional model, Δχ2(1) = 25.640, p < .001; CFI = .931; TLI = .875; and RMSEA = .095.

remain similar, except that the relationship between MAv goals and private challenges became marginally statistically significant.

Study 2 Results Table 3 presents descriptive statistics, correlations, and reliability estimates. We conducted a path analysis using AMOS 25.0 to test H1–H4. We covaried the four goal orientations with each other. Also, given the substantial correlation between the two dependent variables (r = .63), we correlated the error distributions of the two dependent variables with each other to model the unexplained correlation between them. Tests of model fit were not relevant because the tested model was fully saturated (Hoyle, 2012).

The results (see Table 3) showed that MAp goals were positively related to both public (b = .47, SE = 0.11, β = .31, p < .001) and private challenges (b = .43, SE = 0.11, β = .27, p < .001), thereby supporting H1a and H1b. MAv goals were negatively related to both public (b = .27, SE = 0.10, β = .19, p = .005) and private challenges (b = .23, SE = 0.10, β = .15, p = .025), thereby supporting H2a and H2b.

In support of H3, PAp goals were statistically significantly related to public challenges, b = .16, SE = 0.07, β = .15, p = .029. PAv goals were not statistically significantly related to public challenges (b = .05, SE = 0.06, β = .05, p = .463).

Thus, H4 was not supported. For completeness, neither PAp goals nor PAv goals were statistically significantly related to private challenges. Given that gender was significantly correlated with both private and public challenges (see Table 2), we also tested a model in which we controlled for the relationship between gender and both challenging job experiences (see Table 3). The results © 2020 Hogrefe Publishing

The purpose of Study 2 is twofold. First, we aim to replicate H1–H4 using a different sample. Second, we examine public challenges as a moderator on the relationship between employees’ PAp goals and in-role job performance to test H5.

Method Sample and Procedure We used a sample of work groups from several industries in Belgium. Trained students collected data as part of a work psychology course. Students contacted organizations regarding their groups’ interest in participating. A survey package – containing the supervisor survey, employee surveys, and envelopes – was given to the supervisor. A cover letter explained the nature of the research and assured anonymity and confidentiality to participants. The supervisor of each work group was asked to inquire about subordinates’ interest in the survey to ensure voluntary participation and then to randomly distribute surveys to five employees within their work group. The supervisor rated the individual performance of the five selected employees. On completion, respondents sealed their survey in an envelope and returned it to their supervisor, from which they were collected by the student.

A sample of 380 employees and their 76 supervisors received questionnaires. Because of incomplete data, 57 employees were excluded yielding an effective response rate of Journal of Personnel Psychology (2020), 19(1), 33–43

40

R. B. L. Sijbom et al., Goal Orientations and Challenging Job Experiences

“This employee increases the pace of work if necessary to meet a deadline.” The response scale ranged from 1 (not at all) to 7 (very much).

85.0%. The final sample consisted of 326 employees nested in 69 groups. Group sizes ranged from 3 to 5 (M = 4.72; SD = 0.57). Of the employees responding, 37.4% were men, and 58.6% had a college degree or higher. Their ages ranged from 17 to 64 years (M = 38.27; SD = 12.06), 70.6% of the employees had a full-time position, and mean organizational tenure was 10.82 years (SD = 9.96). On average, employees worked 5.31 years (SD = 5.54) with their current supervisor.

The main sectors represented in the sample included healthcare (16.4 %), retail (15.2 %), public sector (12.1 %), financial services (11.8%), and manufacturing (7.7%).

Control Variable Similar to Study 1, gender (0 = male; 1 = female) was measured as a potential control variable.

Data Considerations and Preliminary Analyses Our data included missing values. Little’s MCAR test was statistically significant (χ2[315, N = 326] = 448.00, p < .001), meaning that the data were not missing completely at random. However, given that no systematic pattern of missing values was observed and the number of missing values was small (0.16% of all values were missing), we did use the EM estimation in SPSS 24.0 to impute the missing values (Arbuckle, 1996). VIF values (≤1.65) indicated that multicollinearity was not a problem in these data.

Measures Goal Orientation Employees’ goal orientations were assessed with the same scales as in Study 1. Items were rated on a scale ranging from 1 (totally disagree) to 7 (totally agree).

Private and Public Challenges Private and public challenges were measured using the same 3-item and 5-item scales as in Study 1. The response scale ranged from 1 (does not apply to me at all) to 7 (very much applies to me). The two-dimensional job challenge model revealed an acceptable fit to the data (χ2(19) = 57.485, p < .001; CFI = 0.968; TLI = 0.953; RMSEA = 0.079) and was significantly better than the fit of a unidimensional model, Δχ2(1) = 49.342, p < .01; CFI = 0.928; TLI = 0.900; RMSEA = 0.116.

Results and Discussion Table 4 presents descriptive statistics, correlations, and reliability estimates. We conducted the same analytical procedure as in Study 1 to test H1–H4. The results are presented in Table 3. H1a, H1b, and H3 were supported and thus replicated in Study 2. H2a and H2b were not supported and therefore not replicated in Study 2. Like Study 1, we did not find support for H4 in Study 2.

For H5, supervisor-rated in-role job performance was the dependent variable. Because multiple employees were rated by the same supervisor, the data may not be completely independent. The intraclass correlation coefficient (ICC1) was statistically significant (ICC1 = 0.12, p = .033).

Consequently, we accounted for this nested multilevel

In-role Job Performance To measure in-role job performance, respondents’ immediate supervisors were asked to rate the in-role job performance of each employee using the following four items (cf. Williams & Anderson, 1991): (1) “This employee adequately completes assigned duties.” (2) “This employee meets formal requirements of the job.” (3) “This employee maintains high quality standards at work.” (4)

Table 4. Descriptive statistics and reliability estimates of Study 2 variables and correlations among them Variable

M

SD

1. .11*

2.

3.

4.

5.

6.

1.

Gender

0.63

2.

MAp goals

5.00

1.07

3.

PAp goals

3.79

1.40

.13*

.30**

(.85)

4.

MAv goals

4.79

1.10

.03

.14*

.30**

5.

PAv goals

3.50

1.37

.07

.07

.40**

.53**

(.88)

6.

Private challenges

4.73

1.46

.12*

.26**

.07

.07

.03

(.72)

7.

8.

(.84) (.82)

7.

Public challenges

3.81

1.56

.21**

.33**

.27**

.01

.03

.67**

(.87)

8.

In-role job performance

5.54

0.98

.10

.16*

.07

.08

.01

.03

.03

(.85)

Note. N = 326; *p < .05; **p < .01; MAp = mastery-approach; MAv = mastery-avoidance; PAp = performance-approach; PAv = performance-avoidance. For the dichotomous variable gender, the mean denotes the percentage of females. Reliability estimates (Cronbach’s α) are presented on the diagonal.

Journal of Personnel Psychology (2020), 19(1), 33–43

© 2020 Hogrefe Publishing

R. B. L. Sijbom et al., Goal Orientations and Challenging Job Experiences

Table 5. Results of hierarchical linear modeling regression for supervisor-rated in-role job performance (Study 2) Model 1 Variable

Coefficient

Intercept γ00

5.53**

PAp goals γ10 PAv goals γ20 MAp goals γ30

Model 2 SE

Coefficient

SE

0.06

5.52**

0.07

0.18**

0.07

0.17*

0.07

0.07

0.07

0.06

0.07

0.20**

0.06

0.19**

0.06

MAv goals γ40

0.05

0.07

0.05

0.07

Private γ50

0.03

0.07

0.04

0.07

Public γ60

0.03

0.08

0.05

0.08

PAp goals × Public γ70

0.13*

0.06

PAv goals × Public γ80

0.04

0.06

MAp goals × Public γ90

0.07

0.06

0.01

0.06

MAv goals × Public γ100 2 Log-likelihood

914.39

924.54

Note. N = 326; **p < .01; *p < .05; MAp = mastery-approach; MAv = mastery-avoidance; PAp = performance-approach; PAv = performanceavoidance; Private = private challenging job experiences; Public = public challenging job experiences.

structure by allowing a random intercept to control for supervisor effects on job performance ratings. We used linear mixed models in SPSS 24.0 with restricted maximum likelihood estimation method to test our hypothesis.

All continuous variables were standardized (Aiken & West, 1991).

The results are presented in Table 5. As shown in Model 1, PAp goals were negatively related to in-role job performance (γ10 = 0.18, SE = 0.07, t(309.51) = 2.70, p = .007), whereas MAp goals were positively related to in-role job performance (γ30 = 0.20, SE = 0.06, t(306.10) = 3.21, p = .001). The results of Model 2 showed that the interaction between PAp goals and public challenges was significant (γ70 = 0.13, SE = 0.06, t(304.45) = 2.27, p = .024) and is plotted in Figure 1. Simple

41

slope analyses (Aiken & West, 1991) showed a negative relation between PAp goals and in-role job performance under conditions of low ( 1 SD) public challenges, γ = 0.30, SE = 0.08, t(294.51) = 3.59, p < .001, and no statistically significant relation under conditions of high (+1 SD) public challenges, γ = 0.04, SE = 0.09, t(311.12) = 0.38, p = .701. Therefore, H5 was partially supported. No other interactions were statistically significant. For the sake of completeness, in an additional analysis we investigated the interactions between goal orientation and private challenges. No significant interactions were found.

General Discussion In two studies, we showed that challenging job experiences can be meaningfully distinguished into two subcomponents, namely, private and public challenges. Applying this more fine-grained conceptualization enabled us to show that PAp goals were only positively related to public challenges, whereas employees’ MAp goals were positively related to both private and public challenges. Furthermore, in Study 2, we showed that when a work environment was characterized by relatively low levels of public challenges, the relationship between employees’ PAp goals and in-role job performance was negative. Relatively high levels of public challenges buffered this negative relationship.

Together, these two studies provide initial evidence that making a distinction based on the nature of challenging job experiences may help to advance our understanding of the motivational underpinnings of performing challenging job experiences.

In Study 2, partial support was found for our interaction hypothesis. A possible explanation might relate to the negative main effect between PAp goals and in-role job performance that, although not anticipated, was found (cf.

Janssen & Van Yperen, 2004). Rather than leading to an increase in in-role job performance, the negative relationship between PAp goals and in-role job performance was buffered under conditions of high public challenges.

Hence, high public challenges may, in fact, be motivating for employees pursuing PAp goals, but they do not translate into enhanced in-role job performance.

Theoretical Implications

Figure 1. The interaction effect of performance-approach goals and public challenging job experiences on supervisor-rated in-role job performance (Study 2).

© 2020 Hogrefe Publishing

Job challenge received notable research attention because it is considered to be one of the most important determinants of employees’ development (DeRue & Wellman, 2009; Dong et al., 2014). Our findings contribute to this emerging body of research in several ways. First, we Journal of Personnel Psychology (2020), 19(1), 33–43

42

R. B. L. Sijbom et al., Goal Orientations and Challenging Job Experiences

redirect prior theory by providing empirical evidence in support of a two-dimensional job challenge model. In particular, we suggest that challenging job experiences can be subdivided into private and public challenges, based on characteristics like clarity of work tasks and visibility of progress and outcomes. Second, we contribute to the job challenge literature by empirically demonstrating that individuals’ PAp goals are related to their willingness to perform public challenges only. This finding is in line with the idea that pursuit of PAp goals is associated with a desire for status (Levy, Kaplan, & Patrick, 2004), and the importance of external evaluations to define task success (Darnon, Dompnier, Gilliéron, & Butera, 2010). In this respect, we provide a more-fine grained understanding regarding motivational underpinnings of challenging job experiences. Finally, in line with P–E fit theory, we show that challengingaspectsoftheworkenvironment areimportantto take into account, particularly for individuals pursuing PAp goals, as a misalignment with motivational preferences may hamper in-role job performance.

through a longitudinal or experimental design. Second, we focused on employees’ goal orientation as an important motivational antecedent. Future research should investigate a broader range of antecedents of private and public challenges. Third, the results regarding MAv goals were inconclusive, meaning that future research may further examine this relationship by taking into account possible moderating variables, such as trait self-efficacy. Finally, the mechanism linking goal orientation to challenging work tasks remains unclear. Some potential mechanisms include job crafting, selection, placement, or promotion in roles requiring public challenge (e.g., a person with high PAp goals being selected by their supervisor for publically challenging tasks due to their good prior performance) (e.g., Schneider, 1987; Wrzesniewski & Dutton, 2001). Future research should further investigate those mechanisms. In conclusion, this study challenges scholars and practitioners to no longer think of job challenge as a monolithic construct, but instead consider it in a more nuanced way.

Practical Implications

References

Our findings have several noteworthy implications for managerial practice. Given the developmental potential inherent to challenging job experiences, it is important to give people challenging job experiences in order to keep them on board (Heavey, Holwerda, & Hausknecht, 2013).

Individuals pursuing MAp goals and PAp goals may be motivated by challenging job experiences, yet they differ in the nature of challenging tasks that motivates them. Organizations may serve the aims of MAp goals individuals by stimulating them to execute both private and public challenges, whereas for individuals with PAp goals solely public challenges are stimulating. In short, it is important to adjust the nature of challenging job experiences to employees’ motivational strivings in order to retain a highly performing workforce.

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

Arbuckle, J. L. (1996). Full information estimation in the presence of incomplete data. In G. A. Marcoulides & R. E. Schumacker (Eds.), Advanced structural equation modeling: Issues and techniques (pp. 243–277). Mahwah, NJ: Lawrence Erlbaum Associates.

Baranik, L. E., Barron, K. E., & Finney, S. J. (2007). Measuring goal orientation in a work domain: Construct validity evidence for the 2 × 2 framework. Educational and Psychological Measurement, 67, 697–718. https://doi.org/10.1177/0013164406292090 Cavanaugh, M. A., Boswell, W. R., Roehling, M. V., & Boudreau, J. W. (2000). An empirical examination of self-reported work stress among U.S. managers. Journal of Applied Psychology, 85, 65–74. https://doi.org/10.1037/0021-9010.85.1.65 Collins, L. M., Schafer, J. L., & Kam, C.-M. (2001). A comparison of inclusive and restrictive strategies in modern missing data procedures. Psychological Methods, 6, 330–351. https://doi.org/ 10.1037/1082-989x.6.4.330 Darnon, C., Dompnier, B., Gilliéron, O., & Butera, F. (2010). The interplay of mastery and performance goals in social comparison: A multiple-goal perspective. Journal of Educational Psychology, 102, 212–222. https://doi.org/10.1037/a0018161 De Pater, I. E., Van Vianen, A. E. M., & Bechtoldt, M. N. (2010).

Gender differences in job challenge: A matter of task allocation.

Gender, Work & Organization, 17, 433–453. https://doi.org/10.

1111/j.1468-0432.2009.00477.x De Pater, I. E., Van Vianen, A. E. M., Bechtoldt, M. N., & Klehe, U.-C. (2009). Employees’ challenging job experiences and supervisors’ evaluations of promotability. Personnel Psychology, 62, 297–325. https://doi.org/10.1111/j.1744-6570.2009.01139.x De Pater, I. E., Van Vianen, A. E. M., Fischer, A. H., & Van Ginkel, W. P. (2009). Challenging experiences: Gender differences in task choice. Journal of Managerial Psychology, 24, 4–28. https://doi. org/10.1108/02683940910922519 DeRue, D. S., & Wellman, N. (2009). Developing leaders via experience: The role of developmental challenge, learning

Limitations and Future Research Our study is not without limitations. First, our two-wave study design used in Study 1 does not allow to draw causal conclusions about the relationship between employees’ goal orientation and challenging job experiences. Yet, we assume that reversed causality is less plausible because goal orientations are considered to be rather stable traitlike individual characteristics (DeShon & Gillespie, 2005; Dweck & Leggett, 1988). Nevertheless, it would be useful for future research to directly test the causal relationship between goal orientation and private/public challenges Journal of Personnel Psychology (2020), 19(1), 33–43

© 2020 Hogrefe Publishing

R. B. L. Sijbom et al., Goal Orientations and Challenging Job Experiences

orientation, and feedback availability. Journal of Applied Psychology, 94, 859–875. https://doi.org/10.1037/a0015317 DeShon, R. P., & Gillespie, J. Z. (2005). A motivated action theory account of goal orientation. Journal of Applied Psychology, 90, 1096–1127. https://doi.org/10.1037/0021-9010.90.6.1096 Dong, Y., Seo, M.-G., & Bartol, K. M. (2014). No pain, no gain: An affectbased model of developmental job experience and the buffering effects of Emotional Intelligence. Academy of Management Journal, 57, 1056–1077. https://doi.org/10.5465/amj.2011.0687 Dragoni, L., Tesluk, P. E., Russell, J. E. A., & Oh, I.-S. (2009). Understanding managerial development: Integrating developmental assignments, learning orientation, and access to developmental opportunities in predicting managerial competencies. Academy of Management Journal, 52, 731–743. https:// doi.org/10.5465/amj.2009.43669936 Dweck, C. S. (1986). Motivational processes affecting learning.

American Psychologist, 41, 1040–1048. https://doi.org/10.1037/ 0003-066x.41.10.1040 Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95, 256–273. https://doi.org/10.1037/0033-295x.95.2.256 Edwards, J. R., Caplan, R. D., & van Harrison, R. (1998). Person– environment fit theory: Conceptual foundations, empirical evidence and direction for future research. In C. L. Cooper (Ed.), Theories of organisational stress (pp. 28–67). Oxford, UK: Oxford University Press.

Elliot, A. J. (1999). Approach and avoidance motivation and achievement goals. Educational Psychologist, 34, 169–189. https://doi.org/10.1207/s15326985ep3403_3 Elliot, A. J., & Church, M. A. (1997). A hierarchical model of approach and avoidance achievement motivation. Journal of Personality and Social Psychology, 72, 218–232. https://doi.org/10.1037// 0022-3514.72.1.218 Elliot, A. J., & McGregor, H. A. (2001). A 2 × 2 achievement goal framework. Journal of Personality and Social Psychology, 80, 501–519. https://doi.org/10.1037//0022-3514.80.3.501 Elliot, A. J., McGregor, H. A., & Gable, S. (1999). Achievement goals, study strategies, and exam performance: A mediational analysis. Journal of Educational Psychology, 91, 549–563.

Elliot, A. J., & Moller, A. C. (2003). Performance-approach goals: good or bad forms of regulation? International Journal of Educational Research, 39, 339–356. https://doi.org/10.1016/j. ijer.2004.06.003 Farr, J. L., Hofmann, D. A., & Ringenbach, K. L. (1993). Goal orientation and action control theory: Implications for industrial and organizational psychology. In C. L. Cooper & I. T. Robertson (Eds.), International review of industrial and organizational psychology (pp. 193–232). New York: Wiley.

Heavey, A. L., Holwerda, J. A., & Hausknecht, J. P. (2013). Causes and consequences of collective turnover: A meta-analytic review. Journal of Applied Psychology, 98, 412–453. https://doi. org/10.1037/a0032380 Hoyle, R. H. (2012). Handbook of structural equation modeling. New York: Guilford Press.

Janssen, O., & Van Yperen, N. W. (2004). Employees’ goal orientations, the quality of leader-member exchange, and the outcomes of job performance and job satisfaction. Academy of Management Journal, 47, 368–384. https://doi.org/10.2307/20159587 Levy, I., Kaplan, A., & Patrick, H. (2004). Early adolescents’ achievement goals, social status, and attitudes towards cooperation with peers. Social Psychology of Education, 7, 127–159. https://doi.org/10.1023/B:SPOE.0000018547.08294.b6 McCauley, C. D., Ruderman, M. N., Ohlott, P. J., & Morrow, J. E. (1994). Assessing the developmental components of managerial jobs. Journal of Applied Psychology, 79, 544–560. https://doi. org/10.1037/0021-9010.79.4.544

© 2020 Hogrefe Publishing

43

Payne, S. C., Youngcourt, S. S., & Beaubien, J. M. (2007). A metaanalytic examination of the goal orientation nomological net.

Journal of Applied Psychology, 92, 128–150. https://doi.org/10.

1037/0021-9010.92.1.128 Preenen, P., Van Vianen, A., & De Pater, I. (2014). Challenging tasks: The role of employees’ and supervisors’ goal orientations. European Journal of Work and Organizational Psychology, 23, 48–61. https://doi.org/10.1080/1359432x.2012.702420 Schneider, B. (1987). The people make the place. Personnel Psychology, 40, 437–453. https://doi.org/10.1097/00006247199305000-00001 Sijbom, R. B. L., Janssen, O., & Van Yperen, N. W. (2015a). How to get radical creative ideas into a leader’s mind? Leader’s achievement goals and subordinates’ voice of creative ideas. European Journal of Work and Organizational Psychology, 24, 279–296. https://doi.org/10.1080/1359432X.2014.892480 Sijbom, R. B. L., Janssen, O., & Van Yperen, N. W. (2015b). Leaders’ receptivity to subordinates’ creative input: The role of achievement goals and composition of creative input. European Journal of Work and Organizational Psychology, 24, 462–478. https://doi.org/10.1080/1359432x.2014.964215 Steele-Johnson, D., Beauregard, R. S., Hoover, P. B., & Schmidt, A. M. (2000). Goal orientation and task demand effects on motivation, affect, and performance. Journal of Applied Psychology, 85, 724–738. https://doi.org/10.1037//0021-9010.85.5.

724 Van Yperen, N. W., Elliot, A. J., & Anseel, F. (2009). The influence of mastery-avoidance goals on performance improvement. European Journal of Social Psychology, 39, 932–943. https://doi.org/10.1002/ ejsp.590 VandeWalle, D., & Cummings, L. L. (1997). A test of the influence of goal orientation on the feedback-seeking process. Journal of Applied Psychology, 82, 390–400. https://doi.org/10.1037/00219010.82.3.390 Williams, L. J., & Anderson, S. E. (1991). Job satisfaction and organizational commitment as predictors of organizational citizenship and in-role behaviors. Journal of Management, 17, 601–617. https://doi.org/10.1177/014920639101700305 Wrzesniewski, A., & Dutton, J. E. (2001). Crafting a job: Revisioning employees as active crafters of their work. Academy of Management Review, 26, 179–201. https://doi.org/10.5465/amr.2001.

4378011. Retrieved from http://amr.aom.org/content/26/2/179. short History Received May 24, 2018 Revision received July 11, 2019 Accepted July 11, 2019 Published online July 3, 2020 Acknowledgments An earlier version of this article was presented at the 78th Annual Meeting of the Academy of Management in Chicago, IL, USA, August 10–14, 2018.

ORCID Roy B. L. Sijbom  https://orcid.org/0000-0001-8473-3903 Roy B. L. Sijbom Department of Work and Organizational Psychology University of Amsterdam PO Box 15919 1001 NK Amsterdam The Netherlands r.b.l.sijbom@uva.nl

Journal of Personnel Psychology (2020), 19(1), 33–43

Research Note

Judging Performance – General Mental Ability and the Convergence of Operational Performance Ratings Andrew B. Speer Department of Psychology, Wayne State University, Detroit, MI, USA Abstract. This research examined whether general mental ability (GMA) predicts rater convergence with other performance measures in operational performance appraisals (PAs). GMA is consistently related to accurate judgments of others. However, contexts in which these effects have been examined differ from real PA environments. In this study, ratings from managers who also took a GMA test were compared to ratings from other knowledgeable sources (peers, subordinates, self). Ratings from managers with higher GMA converged more with others’ evaluations of ratee job performance, with correlations ranging from .15 (peers) to .28 (self), and .30 with a composite across the three sources.

These findings establish external validity in support of past research examining the relationship between GMA and PA rating convergence.

Keywords: job performance ratings, performance appraisal, convergence, general mental ability

Performance appraisals (PAs) involve employee judgments that are particularly impactful within organizations, as PAs help determine pay changes and employment decisions (e.g., terminations, promotions, lateral transfers) and facilitate coaching and development. Given the criticality of PAs, it is important to determine ways to increase the accuracy or quality of PA ratings, which themselves have been criticized for reasons ranging from low reliability to negative user reactions (Murphy, Cleveland, & Hanscom, 2018). The current paper researches individual differences in rating convergence with other performance measures during PAs. Recently, De Kock, Lievens, and Born (2018) summarized research regarding individual differences in the ability to accurately judge the qualities of others. Their review spanned various settings and types of human resources judgments (e.g., interviews, assessment centers, performance evaluations) and revealed that dispositional intelligence (e.g., Christiansen, Wolcott-Burnam, Janovics, Burns, & Quirk, 2005) and general mental ability (GMA, i.e., intelligence) are consistently related to judgment accuracy. This review, along with the current body of literature on human judgment, is informative for understanding which individual differences make people good judges of others. However, there are limits to the external validity of that research when applied to PA contexts, as no known study has examined well-known trait predictors of judgment quality in real organizational PA settings.

Journal of Personnel Psychology (2020), 19(1), 44–48 https://doi.org/10.1027/1866-5888/a000244

Past studies have shown that certain traits relate to judgment quality when assessing ratees performing workrelated tasks, with consistent support for GMA (e.g., Borman, 1979; Hauenstein & Alexander, 1991). However, this research has generally been in laboratory settings and has involved judgments based on short observational periods. Such settings are in contrast to real PA contexts where raters have conflicting motives beyond accuracy (e.g., Spence & Keeping, 2011), where judgments are made following what is usually a year’s worth of behavioral observation, and where the people making ratings have myriad of other responsibilities beyond simply evaluating others’ behavioral effectiveness. As such, the current research builds upon the current judgment literature by investigating the relationships between GMA and rating convergence with other performance measures within a real PA context.

Judgment Quality and GMA An accurate judgment represents how closely a rater’s evaluations align with target true scores, or as Funder (1999) stated, “the relation between what is perceived and what is” (p. 3). Contemporary investigations of judgment quality are often framed within Funder’s realistic accuracy model (RAM) in describing the requirements © 2020 Hogrefe Publishing

A. B. Speer, Differences in Performance Rating Convergence

to form high-quality judgments. These requirements include expression of relevant and available information from the target being rated and then the detection and utilization of that information by raters to form a judgment.

While eliciting trait-relevant information involved in steps 1 and 2 of RAM is important, most individual differences research has examined traits that facilitate information detection and utilization. GMA is thought to be one of these individual difference variables and is consistently one of the strongest predictors of judgment quality across settings (De Kock et al., 2018). It is defined as the ability to manipulate, store, retrieve, evaluate, and process information (Murphy & Davidshofer, 2005), and individuals higher in GMA are able to more seamlessly detect and process information, retrieve and remember that information, and then integrate that information to form accurate judgments of others.

GMA and Performance Appraisal Judgments There are several reasons why the GMA–judgment accuracy relationship might differ within PA field settings. First, because most PAs are conducted on an annual or biannual cadence, observation, encoding, and storage (DeNisi, Cafferty, & Meglino, 1984) occur over a longer duration than most contexts in judgment research. Longer observation periods increase the relevance and availability of information to raters. At the same time, it also allows for a lot of information processing to go wrong. Information may fail to be observed, might be poorly encoded due to biases, and might not be processed thoroughly enough for longterm memory storage. Having higher GMA should facilitate the detection, initial coding, and storage of information.

Second, over the course of the PA rating cycle and closer to the ratings themselves, ratee information is retrieved, reconsidered, and integrated with new information (DeNisi et al., 1984). Limitations in memory will reduce usable information and hinder evaluations at these phases; the sheer amount of information being considered (usually a year’s worth of behaviors) will require both elaborately developed schemas and extensive mental processing.

Lippa and Dietz (2000) proposed that intelligence will be more strongly related to judgment quality as the complexity of the judgment task is increased, and given the aforementioned contextual features, the PA context is quite complex.

Finally, all this ratee information must eventually be translated into ratings. The past several decades of PA © 2020 Hogrefe Publishing

45

research have unequivocally highlighted the importance of the social context in PA ratings; ratings do not occur in a vacuum and raters are not always motivated to be accurate (e.g., Spence & Keeping, 2011). Thus, even though we know that individual differences are related to judgment quality, we know less about whether these traits still exert effects in contexts in which motivations of the raters are more complex, once again highlighting the need to better understand the GMA–judgment quality relationship in actual PA contexts. The current study fills in this research gap by examining how rater GMA impacts rating quality in an operational PA context. Rating quality is conceptualized as ratings that exhibit higher convergence with other measures of ratee job performance. In other words, it is reflected by ratings that exhibit higher convergent validity.

When raters are not entirely motivated to rate accurately, the ability to judge others should become less important to establishing accurate ratings, as other motivations (e.g., conflict avoidance; Spence & Keeping, 2011) will affect how judgments are made. Whether or not this is counterbalanced by the increased complexity of the operational PA judgment task in determining the relationship between GMA and rating quality is unclear. Notwithstanding, there is a strong theoretical justification for GMA as a predictor of judgment quality, as reflected here by rating convergence with other performance measures.

Hypothesis 1 (H1). GMA is positively related to rating convergence within real PAs.

Method Participants and Procedure Seventy-one senior managers (i.e., supervisors of other managers) from a large US organization (a) completed a GMA test as part of a concurrent validation study and (b) also rated their direct reports as part of a 360° feedback program. The concurrent validation study was part of an effort to create a prehire assessment for senior leaders. As part of a separate endeavor, the same 71 leaders who participated in the concurrent validation study also made developmental ratings of their direct reports, who were first-level managers (i.e., supervisors of nonmanagers).

These ratings were part of a larger 360° feedback program meant to develop the leadership skills of those being rated.

All senior managers rated at least two direct reports, with a total of 270 ratings being made overall ( k per manager = 3.80). Senior managers (i.e., raters) had been in their positions for an average of 3.53 years (SD = 3.16). The rated Journal of Personnel Psychology (2020), 19(1), 44–48

46

targets (i.e., direct reports) had been in their positions for an average of 4.99 years (SD = 5.64). Demographic information for the sample was not available. However, the population of managers within the company was approximately 60% male and 80% white.

Measures General Mental Ability The Learning Index (Profiles International, 2014) was used to measure GMA of senior leaders in the sample. The test measures the domains of numerical and verbal reasoning using a total of 68 static multiple-choice questions.

Items were developed to assess these domains of general learning. The test was administered online in an unproctored setting without any time limit. Test reliability is acceptable (α = .92), and scores have exhibited evidence of construct validity, correlating .53 with scholastic achievement test scores in a separate sample (Profiles International, 2014).

360° Performance Ratings The senior managers supervised employees who partook in a 360° feedback program. These ratees were evaluated by their direct supervisors (i.e., the primary study sample), their peers (i.e., coworkers), their subordinates (i.e., direct reports), and themselves (i.e., self) according to a set of 14 company-specific competencies: • Achieves results • Business savvy • Coaching • Communicates effectively • Courage • Customer focus • Decision quality • Dependability • Encourages diversity • Flexibility • Innovation • Interpersonal effectiveness

1

A. B. Speer, Differences in Performance Rating Convergence

• Leads strategically • Teamwork All ratees were rated by at least two peers (M = 3.84) and two subordinates (M = 4.12), and ratings were averaged within target by source such that each target had a single set of ratings by source (supervisor, peer, subordinates, self). The 14 competencies were developed by an internal human resources team to reflect general leader qualities of success in the organization. Each rating source assessed the ratees on these 14 competencies using five-point continuous scales, with 3–4 performance items pertaining to each competency, and scores were then aggregated to the competency level. Of the source ratings, the manager ratings are of focal concern for this study, as these ratings came directly from the primary sample (N = 71) who had GMA scores. Ratings from other sources (subordinates, coworkers, self) were used as convergent performance measures.

Convergence Scores The focal set of ratings came from the 71 senior managers, and those ratings were compared to performance ratings from the targets’ subordinates and peers, and the targets’ own self-ratings. Convergence scores were calculated separately for each source. Because ratings from the managers and from other sources are influenced by the same latent construct (i.e., ratee job performance), higher quality ratings (i.e., those that better assess the latent domain) should therefore exhibit stronger convergence with these comparison ratings.

To calculate indices of convergence, profile correlations (Funder, 1999) were computed between the senior manager ratings and other source ratings. A profile correlation measures whether an entire set of ratings (i.e., all the competency ratings) converges with the same ratings from another source. Whereas Cronbach’s (1955) accuracy metrics are often applied when targets possess definitive true scores, the “other” ratings used in the study are best aligned within a convergent validity framework and represented more parsimoniously by profile correlations.1

There are several additional reasons why Cronbach’s accuracy metrics were not utilized in this study. For one, because some managers only rated two employees, estimates of Cronbach’s metrics such as differential elevation are likely to become unreliable with only two aggregate values being deviated from each source’s mean. Second, although Cronbach’s metrics break down the alignment of ratings into various types of convergent information, none provide measures of absolute agreement at the target level, which some believe to be the defining feature of accuracy. Besides elevation, which calculates overall agreement across targets and is therefore uninformative in distinguishing judgments made between targets, all other Cronbach’s indices are based on deviations from their own vector means. Thus, Cronbach’s metrics are not advantageous beyond profile correlations in this sense. Finally, it is not challenging to construct rater and true score vectors that exhibit zero agreement and a different rank order of target scores and yet produce perfect differential accuracy. For example, if a rater’s judgments for two targets assessed on three traits were target A = 2, 2, and 2 and target B = 4, 4, and 4, and the corresponding true score estimates were target A = 4, 4, and 4, and target B = 2, 2, and 2, differential accuracy and elevation are perfect despite these ratings being clearly misaligned. On the other hand, a profile correlation more appropriately depicts this strong degree of misalignment.

Journal of Personnel Psychology (2020), 19(1), 44–48

© 2020 Hogrefe Publishing

A. B. Speer, Differences in Performance Rating Convergence

47

These were calculated for each senior manager by creating a vector of all ratings made by that manager for all ratees (as each senior manager rated at least two employees according to 14 competencies, the minimum number of values in that vector was 28 ratings) and correlating that vector with matched ratings from other sources. This resulted in three convergence scores labeled “profile convergence – subordinates,” “profile convergence – peers,” and “profile convergence – self.” Finally, these three scores were equally weighted into a composite to reflect overall convergence, which is labeled “overall profile convergence.” This score reflects perspectives from all sources and thus should more precisely triangulate performance true scores. A higher profile correlation indicates that the relative ordering of ratings for senior managers closely matches the relative ordering of ratings from other sources.

Results and Discussion Table 1 displays descriptive statistics and correlations for the 360° ratings, separated by source. Table 2 displays correlations between all rater variables. As shown in Table 1, higher ratings were given by subordinates, and the lowest ratings were given by senior managers. Ratings from different sources demonstrated moderate convergence ð r ¼ :28Þ.

To test H1, GMA scores were correlated with profile convergence scores (Table 2). Consistent with the past research examining the correlation between GMA and ratings, GMA was positively and significantly related to overall profile convergence (r = .30, p < .01). Thus, Table 1. Rater descriptive statistics and correlations among sources M

SD

1. Manager ratings

3.66

0.60

1.

2.

3.

2. Subordinate ratings

3.94

0.46

.09

3. Peer ratings

3.68

0.41

.28**

.45**

4. Self-ratings

3.78

0.50

.13*

.39**

4.

.32**

Note. Correlations were computed at the ratee level (N = 270). *p < .05, **p < .01 (two-tailed). M = mean, SD = standard deviation.

Table 2. Correlations between GMA and rating convergence 1.

2.

3.

4.

5.

1. Rater GMA 2. Profile convergence – subordinates .20* 3. Profile convergence – peers

.15

4. Profile convergence – self

.28** .04

.16

5. Overall profile convergence

.30** .65** .71** .59**

.14

Note. N = 71. *p < .05, **p < .01 (one-tailed). GMA = general mental ability.

© 2020 Hogrefe Publishing

performance ratings from managers with higher GMA converged more with other performance data than did ratings from managers with lower GMA. H1 was supported. Considering profile correlations for specific sources, GMA relationships ranged from .15 for peer convergence (p = .11) to .28 for self-convergence (p < .01).

These findings establish external validity and extend the past research regarding the relationship between GMA and PA rating quality. Operational PA environments involve longer observation periods and consist of an amalgamation of rater motives. This makes operational PA judgments more complex, which should enhance the importance of GMA in affecting rating quality. At the same time, because managers are motivated by social and environmental factors when making ratings, accuracy becomes partially volitional, therefore potentially lessening the importance of GMA. Despite these conflicting assumptions, the effect size found here is slightly higher than typical GMA-rating quality effects (e.g., De Kock et al., 2018). Because of the increased complexity of the judgment task in real PA settings, individual differences related to information processing may become more vital to highquality judgments than when judgments are performed in less complex environments (e.g., shorter duration periods).

From a practical standpoint, it may be challenging to hire managers solely for their ability to rate others, and GMA is not malleable via training. That said, it is well established that GMA is related to job performance, and therefore, current selection procedures that focus on GMA as predictors of job performance will simultaneously help hire managers who are more capable of rating others; thus, this study further highlights the importance of GMA in work contexts. For raters lower in GMA, implementing procedures to limit cognitive load and to facilitate information recall (e.g., diaries) should help offset mental limitations.

Despite these findings, there are limitations to this research. First, this was a small sample with low power.

Although many correlations were moderately positive in the expected directions, replication is needed with larger samples. Second, the rating context was developmental, and thus, the results may not generalize to administrative PA contexts where the influence of social factors will be more prominent. It is well known that ratings are inflated when completed in administrative contexts and are tied to pay (Jawahar & Williams, 1997). In such cases, accurate judgments will require not only the ability to accurately rate others but also the motivation to do so (Murphy et al., 2018). When raters are not motivated to be accurate, the correlation between rater ability and rating accuracy should weaken, as other motives will more strongly exert their influences on ratings. Although this study did not examine rater motivation, the fact that ratings were completed in a developmental 360° context may have Journal of Personnel Psychology (2020), 19(1), 44–48

48

resulted in higher GMA–rating convergence correlations.

Furthermore, and as pointed out during the review of this paper, GMA might affect rating strategies in ways that are unique to administrative settings. For example, some might argue that there are benefits to making ratings that do not perfectly align to actual employee evaluations, if perhaps raters want to motivate ratee behavior in certain ways. It is possible that GMA is related to raters making smarter instrumental use of their judgments in administrative settings. Thus, future research should explore the interaction between rater ability and motivation and how these factors influence rating convergence and rater tendencies under various PA scenarios.

Third, in establishing convergent measures, having an abundance of criteria is preferred. Although this study included ratings from three other sources, additional measures such as behavioral or objective performance data would be helpful to triangulate the best estimate of “true performance” to evaluate against the managers’ ratings. Finally, this study used only a single measure of GMA, and this measure was unproctored and administered online. Because the measure was unproctored, it is possible that highly motivated managers used aids to boost test performance (e.g., search for answers online, ask friends or family members for answers); this would detract from the validity of the GMA measure. It would therefore be beneficial to replicate results with other proctored GMA measures (e.g., Wonderlic) and also possibly with more specific cognitive abilities (e.g., social intelligence).

In conclusion, the current study extended past rating judgment research by establishing external validity for the relationship between GMA and rating convergence in PAs. Future research and practice should consider GMA for understanding how raters form PA judgment in operational PAs.

A. B. Speer, Differences in Performance Rating Convergence

Human Performance, 18, 123–149. https://doi.org/10.1207/ s15327043hup1802_2.

Cronbach, L. J., & Keeping, L. (1955). Processes affecting scores on “understanding of others” and “assumed similarity.” Psychological Bulletin, 52, 177–193.

De Kock, F. S., Lievens, F., Born, M. P. (2018). The profile of the ‘Good Judge’ in HRM: A systematic review, systematic review and agenda for future research. Human Resources Management Review, Advance online publication. https://doi.org/10.1016/j. hrmr.2018.09.003.

DeNisi, A. S., Cafferty, T. P., & Meglino, B. M. (1984). A cognitive view of the performance appraisal process: A model and research propositions. Organizational Behavior & Human Performance, 33, 360–396. https://doi.org/10.1016/00305073(84)90029-1.

Funder, D. C. (1999). Personality judgment: A realistic approach to person perception. San Diego, CA: Academic Press.

Hauenstein, N. M., & Alexander, R. A. (1991). Rating ability in performance judgments: The joint influence of implicit theories and intelligence.Organizational Behavior andHuman Decision Processes, 50, 300–323. https://doi.org/10.1016/0749-5978(91)90024-N. Jawahar, I. M., & Williams, C. R. (1997). Where all the children are above average: The performance appraisal purpose effect.

Personnel Psychology, 50, 905–925. https://doi.org/10.1111/j.

1744-6570.1997.tb01487.x.

Lippa, R. A., Dietz, J. K. (2000). The relation of gender, personality, and intelligence to judges’ accuracy in judging strangers’ personality from brief video segments. Journal of Nonverbal Behavior 24, 25–43. https://doi.org/10.1023/A:1006610805385.

Murphy, K. R., Cleveland, J. N., & Hanscom, M. E. (2018). Performance Appraisal and Management. SAGE. Murphy, K., & Davidshofer, C. (2005). Psychological testing: Principles and applications (6th ed.). Upper Sadddle River, NJ: Prentice Hall.

Profiles International. (2014). ProfileXT technical manual (8th ed.).

Waco, TX. Spence, J. R., & Keeping, L. (2011). Conscious rating distortion in performance appraisal: A review, commentary, and proposed framework for research. Human Resource Management Review, 21, 85–95. https://doi.org/10.1016/j.hrmr.2010.09.013.

History Received January 16, 2019 Revision received July 13, 2019 Accepted August 6, 2019 Published online July 3, 2020

References

ORCID Andrew B. Speer  https://orcid.org/0000-0002-3376-2103

Borman, W. C. (1979). Individual differences correlates of accuracy in evaluating others’ performance effectiveness. Applied Psychological Measurement, 3, 103–115. https://doi.org/10.1177/ 014662167900300111.

Christiansen, N. D., Wolcott-Burnam, S., Janovics, J. E., Burns, G. N., & Quirk, S. W. (2005). The good judge revisited: Individual differences in the accuracy of personality judgments.

Andrew B. Speer Department of Psychology Wayne State University 5057 Woodward Ave Detroit, MI 48202 USA speerworking@gmail.com

Journal of Personnel Psychology (2020), 19(1), 44–48

© 2020 Hogrefe Publishing

Erratum Correction to Bal and Vossaert (2019) In the article entitled “Development of an I-deals motivation and management measure” by P. Matthijs Bal and Lien Vossaert (Journal of Personnel Psychology, 18, 201–215, https://doi.org/10.1027/1866-5888/a000236), the authors’ affiliations were given incorrectly on the first page.

The correct affiliations read as follows: P. Matthijs Bal1,2 and Lien Vossaert3 1

Department of People and Organisation, Lincoln International Business School, University of Lincoln, UK 2 Department of Industrial Psychology and People Management, University of Johannesburg, South Africa

© 2020 Hogrefe Publishing

3

Department of Personnel Management, Work and Organizational Psychology, Ghent University, Belgium The authors and the publisher regret any inconvenience or confusion this error might have caused.

Reference Bal, P. M., & Vossaert, L. (2019). Development of an I-deals motivation and management measure. Journal of Personnel Psychology, 18, 201–215. https://doi.org/10.1027/1866-5888/a000236 Published online July 3, 2020

Journal of Personnel Psychology (2020), 19(1), 49 https://doi.org/10.1027/1866-5888/a000251

News and Announcements Awards for Outstanding Achievements as Authors and Reviewers 2019 The Journal of Personnel Psychology is delighted to announce the winners of the Best Paper Award and the Best Reviewers Award for 2019, chosen by a committee composed of members of the editorial team.

Best Paper Award 2019 The 2019 Best Paper Award goes to: Gillet, N., Morin, A. J. S., Choisay, F., & Fouquereau, E. (2019). A person-centered representation of basic need satisfaction balance at work. Journal of Personnel Psychology, 18, 113–128. doi:10.1027/1866-5888/a000228

Journal of Personnel Psychology (2020), 19(1), 50 https://doi.org/10.1027/1866-5888/a000250

Best Reviewer Awards The truly unsung heroes in the process of publishing research are the anonymous external reviewers, who often contribute substantially to the quality of the final product without being recognized at all. In an attempt to change this at least in a few of the most deserved cases, the Journal of Personnel Psychology distinguishes outstandingly helpful reviewers with its annual Best Reviewer Award.

For 2019, these awards go to Christian Vandenberghe (HEC Montréal, Canada) and Oliver Weigelt (University of Rostock, Germany).

Congratulations to the award winners!

© 2020 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 https://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 themselves and any coauthors that the manuscript has not been submitted or published elsewhere, and that they hold 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 machine readable 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 January 2020

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 (Eds.)

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

www.hogrefe.com

sec-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.

Set of cards covering VIA’s 24 character strengths, 6 virtues – and practical interventions to help your clients!

“The cards are insightful, user-friendly, and ready-for-impact – a tangible resource to help clients build character strengths fluency, catalyze exploration, and set clients on a trajectory of strengths application for building well-being, enhancing relationships, and managing stress.”

Ryan M. Niemiec, PsyD, Education Director, VIA Institute on Character, Cincinnati, OH

Matthijs Steeneveld / Anouk van den Berg

Character Strengths Intervention Cards 50 Cards With Instruction Booklet 2020, 50 cards + 16-page booklet US $34.80 / € 27.95 ISBN 978-0-88937-566-6 Also available as eBook The VIA character strengths look at what positive character traits help us lead fulfilling and happy lives, rather than looking at what is wrong with us. Research has shown that knowing your strengths and using them more often leads to greater well-being, better performance, and more resilience. With these cards, you can help clients learn about their character strengths.

This full-color 50-card set provides cards for each of the 24 VIA character strengths and 6 virtues as well

www.hogrefe.com

as information cards to hand out in groups and individual sessions. On top of that, 16 ready-to-use, evidence-based intervention cards help clients discover and explore their strengths and practice applying them more often. The cards are a valuable addition to the toolboxes of coaches, trainers, and therapists from any background. The card set is an excellent resource to use with the book Character Strengths Interventions: A Field Guide for Practitioners by Ryan M. Niemiec (ISBN 978-0-88937-492-8).

First papers now published!

Be part of this exciting journey and submit your paper now!

https://www.editorialmanager.com/ptad

OA New al Journ

“PTAD is a unique academic journal, filling the burgeoning gap in the field of test adaptations and development – I’m very excited to announce the release of our first papers and look forward to even more submissions!”

Matthias Ziegler, Editor-in-chief

Psychological Test Adaptation and Development (PTAD) is the first open access, peer-reviewed journal publishing papers on adaptations of tests to specific (e.g., cultural) needs, test translations, or the development of existing measures.

For more information, visit https://eu.hogrefe.com/products/journals/ptad Why you should publish in PTAD: • A unique outlet for research papers portraying adaptations (e.g., translations) and developments (e.g., state to trait) of individual tests – the backbone of assessment • Official open-access journal of the European Association of Psychological Assessment (EAPA) • With an expert editor-in-chief, supported by a stellar cast of internationally renowned associate editors • Fully embraces open science – including registered reports

Benefits for authors: • Clear guidance on the structure of papers • Fast peer-review • With the optional registered report format you can get expert advice from seasoned reviewers to help improve your research • Open access publication, with a choice of Creative Commons licenses • Widest possible dissemination of your paper – and thus of qualified information about your test and your research • Generous APC waiver program

Introductory Editorials: Matthias Ziegler, Psychological Test Adaptation and Development – A New Beginning https://doi.org/10.1027/2698-1866/a000001

Original Article: Ziwen Teuber, Qichen Wang, Yanjie Su, Arnold Lohaus, & Fridtjof W. Nussbeck, Human Resources in Chinese Youngsters – A Chinese Adaptation of the QARCA https://doi.org/10.1027/2698-1866/a000003

Matthias Ziegler, Psychological Test Adaptation and Development – How Papers Are Structured and Why https://doi.org/10.1027/2698-1866/a000002

www.hogrefe.com