The Asian Journal of Business Research Vol 1 No. 2

2 2011

2 2011

Asian Journal of Business Research Volume 1

Number 2

2011

Editorial Kim-Shyan Fam, Zhilin Yang and Ernest Cyril de Run

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Country Image and Brand Equity Effects of Chinese Firms and their Products on Developed-Market Consumer Perceptions Francis M. Ulgado, Na (Amy) Wen, and Moonkyu Lee

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Standardization or Adaptation in International Advertising Strategies: The Roles of Brand Personality and Country-Of-Origin Image Xuehua Wang and Zhilin Yang

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Impact of Quantity and Timeliness of E-WOM Information on Consumer’s Online Purchase Intention Under C2c Environment Zhang Bin, Fu Xiao-rong, Xie Qing-hong, Xiao Liu-li, and Che Yu

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Determinants of Internet Buying Behavior in India Ruchi Nayyar and S. L Gupta

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Online Shopper Behavior: Influences of Online Shopping Decision Chayapa Katawetawaraks and Cheng Lu Wang

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Assessing Customer Satisfaction with Non-Profit Organizations: Evidence from Higher Education Lily Huang, Zhilin Yang, and Gerald Hampton

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AJBR ISSN 1178-8933 Volume 1 Number 2 2011

Asian

Journal of Business Research

Copyright Š 2011 Asia Business Research Corporation Limited

All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording or any information storage and retrieval system, without permission in writing from the publisher.

The work published is the sole responsibility of the author/s.

Founding Editor

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Editor

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Managing Editor

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Professor Kim-Shyan Fam, Victoria University of Wellington, New Zealand

Associate Professor Zhilin Yang, City University of Hong Kong, Hong Kong

Associate Professor Dr Ernest Cyril de Run, Universiti Malaysia Sarawak, Malaysia

Published by Asia Business Research Corporation (ABRC) Limited PO Box 5257, Lambton Quay, Wellington 6145, New Zealand

Volume 1 Number 2, 2011 ISSN 1178-8933

First published in 2011 Printed in Malaysia

Editorial Board

Founding Editor Professor Kim-Shyan Fam Victoria University of Wellington, New Zealand Editor Associate Professor Zhilin Yang City University of Hong Kong, Hong Kong Managing Editor Associate Professor Ernest Cyril de Run University Malaysia Sarawak, Malaysia

Editorial Advisory Board Professor Russell Belk York University, Canada

Professor Susan Hart University of Strathclyde, UK

Professor John Dawson University of Stirling, UK

Professor Leslie de Chernatony University of Birmingham, UK

Professor Michael Hyman New Mexico State University, USA

Professor Phil Harris University of Chester, UK

Professor Lรกszlรณ Jรณzsa Szechenyi Istvan University, Hungary

Professor Zuohao Hu Tsinghua University, China

Professor Jรณzsef Berรกcs Corvinus University of Budapest, Hungary

Professor Kara Chan Hong Kong Baptist University, Hong Kong

Professor Samsinar Md. Sidin Universiti Putra Malaysia, Malaysia

Professor Datuk Md Zabid Abdul Rashid Universiti Tun Abdul Razak, Malaysia

Editorial Review Board Professor Ashish Sinha University of New South Wales, Australia

Professor Michael Basil University of Lethbridge, Canada

Assistant Professor Amy Na Wen City University of Hong Kong, Hong Kong

Dr Mark Davies Herriot-Watt University, Scotland

Dr David Waller University of Technology Sydney, Australia

Associate Professor Fang Wan University of Manitoba, Canada

Professor Nelson Ndubisi Nottingham University Malaysia, Malaysia

Professor David Ackerman California State University, Northbridge, USA

Dr Song Yang University of South Australia, Australia

Professor Sanjay K. Jain University of Delhi, India

Dr Fang Liu University of Western Australia, Australia

Associate Professor Palanisamy Ganesan VIT University, India

Professor Kenneth Alan Grossberg Waseda University, Japan

Dr Shankar Lal Gupta Birla Institute of Technology, India

Professor Yong Ki Lee Sejong University, Korea

Professor Badar Iqbal Aligarh Muslim University, India

Dr Pedro Brito Universidade do Porto, Portugal

Associate Professor Ernest Cyril de Run Universiti Malaysia Sarawak, Malaysia

Professor José Luis Vázquez-Burguete Universidad de León, Spain

Professor HS Cheema CEO & Dean, IFEEL, India

Assistant Professor Andreas Petrou Cyprus International Institute of Management, Cyprus

Dr Anizah Hj Zainuddin Universiti Teknologi MARA Malaysia, Malaysia

Associate Professor Tho Nguyen University of Economics, HCM City, Vietnam

Dr Boo Ho Voon Universiti Teknologi MARA Sarawak, Malaysia

Professor Syed Anwar Hamdan Bin Mohammed University, UAE

Associate Professor Margaret Craig-Lees AUT University, New Zealand

Dr Paurav Shukla University of Brighton, UK

Dr Henry Chung Massey University, New Zealand

Assistant Professor Fiona Sussan George Mason University, USA

Dr Mathew Parackal University of Otago, New Zealand

Assistant Professor Kawpong Polyorat Khonkaen University, Thailand

Associate Professor Michele Akoorie University of Waikato, New Zealand

Professor Yang Xue North China University of Water Conservancy and Electric Power, China

Associate Professor Joanna Scott-Kennel Waikato University, New Zealand

Professor Zoltan Veres Budapest Business School, Hungary

Professor Wang Yangron North China University of Water Conservancy and Electric Power, China

Editorial

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Asia’s big two: China and India.

It is indeed an honor to be the latest Managing Editor of the Asian Journal of Business Research and to see the progress of the journal. The journal is the concentrated effort of the Marketing in Asia Group whose desire is to promote academic discussion in the context of business in Asia, yet with a global perspective. The Marketing in Asia Group seeks to disseminate knowledge of Asian business based on rigorous yet pragmatic research and this has seen the publications of books as well as this journal and a conference specific to the issue of business in Asia.

In the spirit of sharing knowledge of Asia, this edition has a mixture of authors from different nations discussing about issues in China and India. Both nations are growing economies with large populations. China is the world’s second largest economy. India is fast becoming an economic powerhouse, with good economic growth and business friendly policies. The capabilities and potential of both nations make them an intriguing and rich research area to be looked into by researchers.

The first paper discusses the impact of country image and brand equity of companies from China but from the perspective of Americans. This is in line with the aspirations of the journal and further articles that look at the various issues in Asia but from the viewpoint of other nations or cultures is most welcomed. This will help in the development of an understanding of business in Asia from a variety of perspectives. The second article looked at brand personality and country of origin effect and again the study contrasted China versus United States but from the perspective of Macau respondents. The study looked at two TV editions of four brands in four product categories. From FMCG, the next article looks at e-commerce. Respondents were University students in China who responded to issues on e-wom, trust and purchase intention.

From China we then traverse to India to look at an article that discusses the determinants of buying behavior over the Internet. The article suggests that perceived ease of use and perceived usefulness are antecedents of intention to purchase online in India. The following article describes online shopping behavior and suggests a framework for online consumer decision.

The final article is on consumer satisfaction with non-profit organizations. This paper deals with how Westerners (respondents from USA and The Netherlands) view such organizations.

This is of interest to the journal as we hope that such papers can be replicated in the Asian context, perhaps with a different approach such as looking at the various Asian lifestyle and philosophy towards philanthropy.

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We do hope that you will enjoy reading the journal and benefit from the knowledge shared.

Our gratitude and thanks to all our contributors and reviewers without whom this journal will never be possible. The editorial team at the Asian Journal of Business Research encourages academic and industry-based researchers to contribute research papers and case studies for its peer-reviewed publication.

Kim-Shyan Fam Zhilin Yang Ernest Cyril de Run

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Asian Journal of Business Research

Volume 1

Number 2

2011

Country Image and Brand Equity Effects of Chinese Firms and Their Products on Developed-Market Consumer Perceptions Francis M. Ulgado, Georgia Institute of Technology Na (Amy) Wen, City University of Hong Kong Moonkyu Lee, Yonsei University

Abstract As China’s rapid economic growth continues to be a significant dimension of the world economy and international business, more Chinese multinational firms have been emerging with increasing efforts towards internationalization. While manufacturing, labor efficiency and costs have been a source of their competitive advantage, one area of relative weakness has been their lack of corporate/product brand equity and recognition. Coupled with potential negative country image effects, this deficiency has hindered a more positive perception and acceptance of brands and products from China, particularly in the more developed markets, such as the United States (U.S.). This empirical study examines the nature of such a challenge faced by Chinese firms and their need to develop an effective branding strategy for success in the U.S. market.

Keywords: Country image, COO, country of origin effects, customer perceptions, brand strategy, Chinese brands, emerging market brands, marketing to developed market customers

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Introduction The Country-of-Origin or COO effect refers to “the picture, the reputation, the stereotype that business people and consumers attach to products and services associated with a specific country” (Lin and Kao, 2004; p.38). Such an image may emerge from representative products, national characteristics, economic and political background, history and traditions (Nagashima, 1970). This paper furthers the notion that the nationality associated with consumer products and services, or their COO, is continues to remain a significant factor in consumer perception and purchasing behavior (Peterson and Jolibert, 1995; Al-Sulaiti and Baker, 1998; Verlegh and Steenkamp, 1999; De Wet, Pothas and De Wet, 2001; Sharma 2010). COO studies have argued that consumers have diverse perceptions about products or services made in or associated with foreign countries, and that these perceptions affect their behavior based on stereotyped national images of the country of association. Extensive empirical research has been completed in this area throughout the past fifty years, concluding that COO effects do exist and they have considerable impact on product quality evaluations and purchase intentions (e.g., Bilkey and Nes, 1982; Cordell, 1992; Tse and Gorn, 1993; Papadopoulos and Heslop, 2002; Usunier and Cestre 2008). In fact, the COO effect on consumers is one extrinsic cue that has grown increasingly significant as the trend towards globalization of production and multinational enterprise (MNE) strategy has intensified, particularly for those from emerging markets such as Taiwan, China and India.

While studies have concluded that under specific conditions, consumers may exhibit a preference for domestically made alternatives, or “ethnocentrism” (Han, 1988; Hong and Wyer, 1989; Papadopoulos, Heslop and Beracs, 1990), or those from more developed countries (Shimp and Sharma, 1987; Han, 1988; Granzin and Olsen, 1998; Douglas and Nijssen, 2004; Josiassen and Harzing 2008). Other research has also revealed that the economic development of associated countries indeed plays a role, as products made in less-developed countries were not perceived as quality products (Reierson, 1966; Schooler, 1971; Gaedeke, 1973; Pappu, Quester and Cooksey 2007).

It is based on this stream of research that we apply the concept of COO to the case of brands and products associated with a major developing and emerging market, China. While Chinese MNEs have traditionally focused on other emerging developing markets located in neighboring Asian countries to export to and invest in, and have more recently established a dominant product and investment presence in other emerging markets in Africa, the Middle East and Latin America Gao, Woetzel and Wu, 2003; Wu, 2005), Chinese firms now compete in the developed markets of Europe and North America (Gumbel and Jakes, 2005). Chinese brands such as Lenovo (personal computers) and Haier (home appliances) have entered the U.S. market with others, such as Geely and Chery automobiles planning to follow suit. As Chinese firms expand into more developed economies, like the U.S., the literature has investigated the various challenges and issues that they face when competing in such markets. A major challenge for the internationalization of Chinese multinationals is the globalization of Chinese brands. While China has become a dominant manufacturer to the world, it has been noted that a single Chinese brand has yet to be significantly recognized globally (Fan, 2006). In addition, Chinese firms have had uncertain success with Chinese brands in more competitive, complex and sophisticated developed markets (Gao, Woetzel and Wu, 2003; Grosse, 2003 ).

Chinese branding difficulty has been attributed to various weaknesses, affecting Chinese brand 2

strategy success. For example, relative branding inexperience (Thomas Group, 2006), lack of distribution capabilities, advertising/promotion savvy (Gao, Woetzel and Wu 2003) and a negative COO effect (Brouthers, Story and Hadjimarcou 2005) have contributed to weak brand awareness and perceptions in developed markets. As a result, studies have indicated that less than positive general perceptions and attitudes exist towards products from China from among developed market consumers, such as the U.S. buyer. For instance, in a 2002 study, only 17 percent of U.S. residents surveyed expressed a high degree of interest in purchasing products imported from China (The Futurist, 2006). In the same survey, the major reason for the lack of interest is the inferior quality associated with Chinese brands. Meanwhile, another survey found that a “Made in China� label hurt Chinese brands (Interbrand, 2005).

While the increased globalization of firms from emerging markets have motivated recent studies to focus on COO effects involving emerging markets as both producing countries and consuming countries (Demirbag Sahadev and Mellahi, 2010; Sharma, 2010), few studies have started to examine the COO phenomenon specific to China. Brouthers, Story and Hadjimarcou (2008) used signaling theory in their study of low value products associated with China (wallet, wine glass, and umbrella). They suggest that multiple COO labeling and the use of secondary country associations, as well as the use of familiar brands, or a combination of both, as ways to overcome any negative COO effects. Fetscherin and Toncar (2009) focused the country of origin effects on the brand personality perception of US consumers by focusing on a comparison of American, Indian and Chinese automobiles. Their findings indicate that the country of manufacture has a significant impact on perceived brand personality.

Therefore, given the paucity of extant studies on the topic, t he purpose of this paper is to further examine the nature of negative COO effects in developed markets for products associated with China as an emerging market, and the significance of other extrinsic cues as moderating factors.

Specifically, the paper seeks to: 1) further confirm that although U.S. consumers are exposed to numerous products manufactured in China, they maintain a low awareness and understanding of Chinese brands in general, and that brands and products, an association with China exerts a negative influence on the perceptions and attitudes of the U.S. consumer; 2) to broaden the work of Brouthers,Story and Hadjimarcou (2008) by investigating more high-value products (white goods, laptops and autos) and related brands given the actual U.S. market experience of Chinese brands Haier and Lenovo, and the potential experience of Geely; 3) to consider the option of developed-country manufacturing as an alternative to multiple COO labeling (Brouthers,Story and Hadjimarcou 2008); 4) to explore the option of developing Chinese brands as an alternative to utilizing established developed country brands ; 5) to explore the moderating effects of other extrinsic cues such as country-of-brand, country-of-manufacture, product category, and brand familiarity considerations, and their impact on overall COO on product quality perceptions and willingness to buy.

In pursuit of this direction, the paper continues with a conceptual development and framework based on existing research. From this section and additional studies, hypotheses are next derived.

Through a survey approach, these hypotheses are then tested and the results discussed. Overall findings indicate that while the moderating variables vary in their impact, brand strength and the country of brand dominate other considerations, contrary to findings of previous research.

In the remaining sections, managerial implications are offered while limitations and future research opportunities are identified.

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Conceptual Development and Framework Components of the Country-of-Origin Effect In the early stages of COO as a research field, country of origin effects were considered a single cue “made-in” concept in which products were typically headquartered, branded and manufactured in the same country (Dichter, 1962). However, this approach eventually became a cited limitation as the need to further decompose COO was realized (Johansson, Douglas and Nonaka., 1985; Ozsomer and Cavusgil, 1991; Ettenson, 1993). With the growth of international value chains and multi-country production locations, the notion of COO has evolved into a more complex multi-component construct. Given the increased occurrence of “bi-national” products carrying a brand associated with one country, but manufactured in another country, the overall COO effect has been more commonly characterized as consisting of two sub-types of country association: Country-of-Brand (COB), the country that the brand is originally from and usually where the headquarters is located, and Country-of-Manufacture (COM), the country where the product is primarily produced and assembled (Ulgado and Lee, 1993; Lim and O’Cass, 2001; Fetscherin and Toncar 2010). Moreover, the COM effect has been further dissected into Country-of-Parts (COP), Country-of-Design (COD), and Countryof-Assembly (COA) (Chao, 1993; Insch and McBride, 1998). This prevalence of bi-national and multi-national products may result in potential dissonance for consumers as they try to reconcile conflicting perceptions about the country association of different components of the product (Phau and Prendergast, 2000).

Research has shown that manufacturing location and the perceived country of manufacture can affect consumer perceptions of product quality (Lee and Schaniger 1996). When an MNE elects to change the manufacturing location of a particular product from a country with a favorable consumer association to one with less favorable perceptions, the overall COO effect could be affected despite maintaining a positive COB influence. Han and Terpstra (1988) for example found that Japanese autos experienced brand deterioration when production was located in developing countries. In other instances, the impact of the COB affected consumer product quality perceptions greater than the COM effect. Ulgado and Lee (1993) discovered that a strong well-developed brand can overcome any negative COM influence, as consumers are convinced that the same level of quality is maintained in all its manufacturing operations. The decomposition of the overall COO effect into its COB and COM components can be potentially significant to international operations and marketing managers and their international brand and manufacturing location strategies.

Cognitive and Affective COO Effects Prior research on COO effects has essentially used either a cognitive or affective theoretical perspective. Under the cognitive approach, consumer information processing research argues that in addition to a product’s intrinsic physical attributes (such as performance, design, taste) , consumers also rely on extrinsic product-related features (such as brand, price, COO) in their product evaluation (Schellinck, 1983; Peter and Olson, 1987). Research in marketing has provided evidence that consumers often use extrinsic cues as the basis for their evaluation of product quality (Rao and Monroe, 1989; Dodds Monroe and Grewal, 1991 for price and brand effects). Specifically, a substantial amount of research has supported the significance of COO as an extrinsic cue affecting consumer product evaluations (see Bilkey and Ness, 1982; Johansson, Douglas, and Nonaka 1985; and Ozsomer and Cavusgil, 1991 for a more detailed review).

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In this regard, studies have suggested that consumers prefer products from some countries over others (Tongberg 1972; Yaprak, 1978). Such preference bias for products generally exists across levels of economic development of countries, indicating their hierarchical nature (Schooler, 1971; Wang and Lamb, 1983). In particular, research has indicated that country identification generally has a positive effect on product evaluations for some, relatively more developed countries (Han and Terpstra, 1988; Papadopoulos, Heslop and Beracs, 1990), while it has a negative impact for other, less developed countries (Krishnakumar, 1974; Khanna, 1986). As a result, COO effects can act as a cognitive cue from which consumers can infer beliefs about a specific product based on their perceptions about the country from which the product originates (Verlegh and Steenkamp, 1999), indicating that consumers’ product perceptions can be derived from stereotypical beliefs about the originating country (Erickson et al., 1984) Overall product evaluation is influenced by country stereotyping impacting consumer evaluation of products from that country (Bilkey and Nes, 1982; Maheswaran, 1994). For example, certain countries are regarded as offering superior performance for certain categories of goods - French wines, German engineering, Swiss watches. Conversely, negative associations may exist for some countries, e.g. high technology products like cars produced in less developed countries such as China or India.

In addition to the cognitive aspects of COO, other studies have focused on the affective effects of COO on consumer perception, examining its emotional or symbolic impact on product evaluation (Hong and Wyer, 1989, 1990). For example, COO may associate a product with patriotism, national identity, pride, status, authenticity, exoticness, or other attributes of selfexpression or image (Botschen and Hemettsberger, 1998; Verlegh and Steenkamp, 1999).

Consumer perceptions of a brand from a particular country can create intangible assets or liabilities in the minds of the consumers that do not necessarily have a direct link to product performance (Kim and Chung 1997). Other affective associations can also be related to consumer attitudes towards the policies, practices or actions of a particular country (Leonidou, Palihawadana and Talias, 2007). As a result consumers penalize some countries by boycotting their products, and support others by buying their products (Smith, 1993). Other types of noncognitive biases based on subjective judgments or normative criteria have additionally been identified as COO-related factors, such as consumer racism (Ouellet, 2007) and home-country bias stemming from consumer nationalism or ethnocentrism (Shimp and Sharma, 1987; Klein, Ettenson and Krishnan, 2006; Verlegh, 2007).

Moderating Factors Affecting COO Since other cues, in addition to country information, are available to consumers in reality, the research paradigm should be extended to investigate potential interactions between the country label and these cues, as a number of studies have indeed found variables that moderate the COO effect. Therefore it is important to specify conditions under which consumers show different COO effects rather than documenting the general effect.

Such variables can be macro or micro-related factors, external to the consumer. For example, studies have found the COO effect to be consuming country-specific (Nagashima, 1970; Cattin, Jolibert and Lohnes, 1982; Wong, Polonsky and Garma, 2008; Sharma, 2010), product/ product-category specific (Bannister and Saunders 1978; Lumpkin, Crawford and Kim, 1985; Roth and Romeo, 1992; Hamin, 2006). Pappu et al (2007) further showed that consumers hold different sets of beliefs across product categories and that their perceptions of products 5

from a specific country vary by product category. While a number of studies have involved the automobile product-category, most of them have looked at the comparison across product categories. Comparisons have been between autos, appliances, clothing, perfume, and toiletries (Darling and Kraft, 1977); cameras and calculators (Yaprak, 1978); pharmaceutical products (Mffenegger et al. 1980), fresh fruit and vegetables (Hooley et al. 1988); beer, shoes, crystal, bicycles, and watches (Roth and Romeo, 1992), and athletic shoes and television sets (Ulgado and Lee, 1993). Moreover, these effects are generally less significant for low-value products with simple manufacturing processes (such as shoes, clothing) than for high-value products with complex manufacturing (such as computers, automobiles) (Ahmed et al., 2002).

Other moderating variables are more internal to the consumer and deal with demographic and psychographic consumer-specific variables (Anderson and Cunningham, 1972; Eroglu and Machleit 1988; Wall, Heslop and Hofstra 1988). More recent studies have investigated the moderating effects of consumer materialism (Demirbag, Sahadev and Mellahi, 2010; Sharma 2010) and value consciousness (Kinra, 2006; Sharma, 2010). For example, Demirbag, Sahadev and Mellahi (2010) found that the moderating role of materialism depends on the type of product. Namely, materialism is a significant negative moderator for high value products from emerging countries, and is less significant for low value products from emerging markets.

Meanwhile, Sharma (2010) showed significant differences in the moderating influences of consumer ethnocentrism, materialism and value consciousness on COO effects across four different developed and emerging markets.

HYPOTHESES We start with the findings of earlier studies which have shown that while more developed countries generally exhibit a positive COO effect on product evaluations and consumer perceptions of product quality (e.g. Gaedeke, 1973; Wall and Heslop, 1986; Papadopoulos, Heslop and Beracs, 1990), it has a negative impact for less developed countries (Krishnakumar, 1974; Khanna, 1986; Pappu, Quester and Cooksey 2007). More recent research has found this to be true in the case of U.S. consumers and their attitudes towards Chinese products and brands in general (The Futurist, 2006; Interbrand, 2005): H1a: U.S. consumers have a generally low quality perception of Chinese products.

H1b: U.S. consumers have a generally unfavorable perception of Chinese brands.

Specific to brand, we also propose that Chinese brands have very weak brand equity in the U.S. market, indicated by low recognition and awareness of brands from China (Fan, 2006; Gao, Woetzel and Yu, 2003). Therefore: H2: U.S. consumers have a generally low level of awareness of Chinese brands.

If hypotheses 1 and 2 hold, then previous cited findings can be confirmed and it can be established that, in general, a negative COO effect influences the perception of U.S. consumers when it comes to products and brands associated with China. The level of a country’s economic development can be seen as representative of a country’s overall ability to manufacture 6

products that require a particular level of skill and technology (Verlegh and Steenkamp, 1999).

Therefore, a country’s ability to produce globally competitive products or services, embodied in its economic capacity, is an information cue that influences customers’ perceptions and images of COO (Lin and Sternquist, 1994). Similarly, Wall, Leifeld and Heslop (1991) found that unknown brands are only favored when they are made in more developed, high reputation countries. In the case of Chinese brands, we introduce the notion that consumer perception and evaluation of a product with a brand associated with China can be significantly affected by the level of economic development of the country-of-manufacture (COM), other than China.

Specifically, the overall Chinese COO effect can be moderated by a developed country COM. Therefore, we propose: H3: For Chinese brands, the overall COO effect on the perception of U.S. consumers is significantly positively influenced by the COM (country-of-manufacture) associated with a favorable image.

In addition to COO, research has considered other extrinsic cues in a multi-cue approach to determining their effects on consumer perception (e.g., Srinivasan, Jain and Sikand, 2003; Miyazaki, Grewal and Goodstein, 2005). Studies have found that when additional cues are present, the relative importance of COO on product evaluation decreases (Johansson, Douglas and Nonaka, 1985; Johansson and Nebenzhal, 1986; Hastak and Hong, 1991). One extrinsic cue that has received attention is brand and related COB effects. The rationale is that customers who lack information about the product may rely on the brand name to infer its quality (Sybillo and Jacoby, 1974). In today’s global environment, it is common to find products manufactured in one country and branded in another. Studies have shown that a strong brand and/or COB effect can outweigh negative COM effects (Cordell, 1993; Tse and Gorn, 1993; Ulgado and Lee, 1993; Jo, Nakamoto and Nelson, 2003; Ahmed et al., 2004, Chao, Wuhrer and Werani, 2005). In the case of Chinese products, the strength of a non-Chinese brand (NCB) may have a moderating influence on possible negative COM effects associated with products made in China. Hence, we propose: H4a: For products manufactured in China, the overall COO effect on the perception of U.S. consumers is significantly positively influenced by the association with a non-Chinese brand with strong brand equity.

H4b: For products associated with China, the COB (country-of-brand) effects are stronger than COM (country-of-manufacture) effects on the perception of U.S. consumers.

While it has been proposed that Chinese brands have a low level of awareness and recognition and, therefore, brand strength in the U.S. market, it is argued that some Chinese brands are more developed than others. Brands like Lenovo and Haier have already been introduced to the U.S. market, while others such as Geely and Chery have not. Therefore, it is proposed that the U.S. consumer is more familiar with the introduced brands and their products. In this regard, Schaefer (1997) concluded that brand familiarity and objective product knowledge has a significant impact on COO effects in product evaluations. Lee and Ganesh (1999) found that with product and brand familiarity, moderate familiarity consumers are less influenced by COO than low or high familiarity consumers. Therefore: H5: The more developed (in terms of consumer familiarity) the Chinese brand in the U.S. 7

market, the more positive the COO effect on the perception of U.S. consumers.

There are indications that COO effects vary across product or service categories (Kaynak and Cavusgil, 1983; Ulgado and Lee, 1993; Jaffe and Nebenzhal, 2001; Javalgi, Cutler and Winans, 2001). Most studies of COO effects have focused on high-value products, such as automobiles and electronics (e.g., Han and Terpstra, 1988; Chao, 1989, 1993; Han, 1988; Tse and Lee, 1993; Maheswaran, 1994). Others have looked at the impact of customers’ COO perceptions on low-value products such as clothing or coffee (Wall, Leifeld and Heslop, 1991; Ulgado and Lee, 1993; Ahmed et al., 2004). Li and Wyer (1994) concluded that COO effects on product evaluation are more significant in the purchase for high value products, such as automobiles, electronics and white goods. Conversely, for low-value basic products such as food and apparel, the purchase decision is less significant. Thus, the influence of COO in product evaluation is expected to be weak, partly due to the product’s lower monetary risk (Ahmed et al., 2004).

Similarly, for low-value products where the value for money matters more than image and quality, price can be seen as more influential than COO effects in customers’ purchase decisions (Wall, Leifeld and Heslop, 1991). Hence: H6a: For products associated with China, the overall COO effect on the perception of U.S. consumers is significantly higher for high value products.

H6b: For products associated with China, the overall COO effect on the perception of U.S. consumers is significantly lower for low value products.

METHODOLOGY Pilot Study A paper and pencil pilot study was conducted with eighty-six adult respondents in a major metropolitan area in southeastern United States to determine their perceptions of different product categories and their value levels, related varying conditions regarding corresponding brands associated with developed countries such as the U.S. and Japan, and a less-developed country such as China. The respondents were also asked about their familiarity with specific Chinese brands in selected product categories. The study results indicated that product categories such as apparel (clothing and shoes), toys, kitchenware and cosmetics are considered low-value, while electronic products such as kitchen small appliances (toaster ovens and compact refrigerators), stereo equipment, television sets and laptop computers, as well as other ‘powered’ equipment (automobiles, powerboats, and motorcycles) are considered high-value.

Among the high-value products, their respective values compact refrigerators (low), laptop computers (middle), and autos (high) were further identified accordingly.

With regard to specific brands in each product category, the respondents considered Ford Focus, Toyota Corolla, Honda Civic Ford Fiesta, and Honda Accord as the top five compact car brands (Dell, Toshiba, HP, Apple and Sony for laptops; GE, Sanyo, Kenmore, Frigidaire and Hitachi for compact refrigerators) associated with the U.S. and Japan, in terms of overall quality and willingness to purchase. When asked about specific Chinese auto brands, the two respondents that were able to respond correctly, mentioned Geely with no respondent able to 8

identify a specific model (Lenovo and Haier were the only Chinese brands mentioned for laptop computers and compact refrigerators respectively), which they rated lower than the American and Japanese counterparts. When asked about specific Chinese brands, the respondents were most familiar with Lenovo, followed by Haier, and least familiar with Geely.

Main Study To empirically test the hypotheses, a paper and pencil survey approach was used. We incorporated exploratory questions in the first two part of the questionnaire. In this section the respondents were asked about their awareness of Chinese brands by “listing as many Chinese brands they are aware of” (unaided recall), their reasons behind their willingness-to-purchase (or not to buy) a product “Made in China” (open-ended; list top three reasons), and their general feelings about Chinese products and brands by rating (7-point Likert scale) their overall level of quality and level of favorability. The second section of the survey asked respondents to rate both their quality perceptions and their willingness-to-purchase products “Made in China” for seven product categories ranging in product value.

In the following main section, respondents were asked to provide ratings on a 7-point scale for five quality measures (design/style, reliability, durability, service support, and performance satisfaction) that made up the overall “Quality” dependent variable. Reliability of the five dimensions was deemed acceptable with a Cronbach’s Alpha of 0.91 bivariate correlations across the five measures ranged from 0.72 to 0.87. A single factor was derived, accounting for 76 percent of the variance. As a result, the five dimensions were averaged and regarded as a single main dependent variable. To further support respondent quality perceptions, respondents were asked to rate a second variable ‘Willingness to buy”. Consequently, respondents evaluated 12 specific product scenarios for both quality and willingness-to-purchase. The information for each product option included the brand and product category, an intrinsic product attribute, the country-of-manufacture/assembly, retailer where available, and the price. Products were selected from previously identified product categories (automobile, laptop computer, and compact refrigerator), and brands were selected for each category (Toyota Corolla, Geely Haoqing, Dell, Lenovo, G.E., and Haier) with different associations of county-of-manufacture/ assembly (U.S., Canada, and China).

The final section of the survey included questions asking the respondents to identify Chinese brands from a list of 16 brand names (aided recall). The rest of this section asked for classification information about the respondent. Responses from a convenience sample of 247 adult consumers in a Southeastern U.S. metropolitan area were used for this study.

RESULTS Sample Characteristics The survey responses of 247 adults were used for the study, of whom, 50.4 percent were female while 49.6 percent were male. The age range varied from 18-24 year-olds (22.7 percent), 25-29 (15.3 percent), 30-39 (16.5 percent), 40-49 (21.9 percent), 50-59 (17.8 percent) 6069 (4.1 percent) and 70+ (1.7 percent). The significant majority of respondents were welleducated (78.2 percent), having attended a 4-year college (55.1 percent) or graduate school (23.1 percent). The number of individuals (adults and children) living in the respondent’s 9

household ranged as follows: 1-2 (41.9 percent), 3-4 (47.3 percent), and 5 or more (11 percent).

Household income was somewhat skewed towards the upper income levels (11.7 percent in the below $40K bracket, 29.6 percent in the $40-79K range, 16.4 percent in the $80-99K level, and 42.6 percent in the $100K+ segment).

Test of Hypotheses Hypothesis 1a posits that U.S. consumers generally have a low quality perception of Chinese products, while Hypothesis 1b argued that U.S. consumers generally had an unfavorable perception when it comes to Chinese brands. Respondents were asked how they felt about Chinese products in general. They were also asked how they felt about Chinese brands. Table I exhibits the means and standard deviations of the ratings.

Table I: Hypothesis 1a AND 1b- Perceptions of Chinese Products and Brands

Mean

Std. Deviation

Chinese Products*

3.7796

1.21145

Chinese Brands**

3.8481

1.05069

*1=Low Quality, 7=High Quality **1=Very Unfavorable, 7=Very Favorable

As shown in the table, the respondents considered Chinese products as low in quality (M=3.78) and have an unfavorable attitude towards Chinese brands (M=3.85). Thus, Hypotheses 1a and 1b are supported and the previous surveys are validated. In general, it is further confirmed that U.S. consumers surveyed do not have a positive view of Chinese products and brands.

Hypothesis 2 stated that U.S. consumers generally had low brand awareness for Chinese brands.

Respondents were asked to list as many Chinese brands as they were aware of (unaided recall).

The results revealed that 84.2 percent of the respondents could not think of any, while only 11.3 percent could correctly recall only one Chinese brand. Only 4.4 percent could correctly recall 2 or more Chinese brands. Therefore Hypothesis 1 and the findings of previous research are supported in the notion that U.S. consumers have a very low, if not non-existent, awareness of Chinese brands.

Hypothesis 3 claims that the overall COO effect on the perception of U.S. consumers was significantly positively influenced by the COM associated with a favorable image. In particular, for the same brands, the more positive the COM effect, the more positive the overall COO. The respondents were asked to rate (in terms of quality and willingness-to-purchase) three products (automobiles, computers, and refrigerators) with Chinese brands, namely, Geely Haoqing, Lenovo and Haier, all made in China. They were also asked to rate three other products (automobiles, computers, and refrigerators) with the same three Chinese brands, only 10

this time made in the U.S. or Canada. One-way MANOVA and GLM multivariate analysis was used, producing an overall significant result (p<.05) with the contrast result significant between “Made in China” and “Made in U.S. or Canada”. This is shown in Table II. Table II: Hypothesis 3- Country-Of-Manufacture (COM) Effects Multivariate Tests Effect F Hypothesis df Error df Sig. Intercept 3887.823 2.000 1357.000 .000 COM 3.173 2.000 1357.000 .042 Pairwise Comparisons Dependent Variable Quality

(I) COM China Made

Willingness to China buy Made

(J) COM NonChina Made NonChina Made

(I) Mean

(J) Mean

3.682

3.880

3.147

3.380

Mean Difference (I-J)

Std. Error

Sig.

-.198(*)

.086

.022

-.233(*)

.096

.016

Based on estimated marginal means * The mean difference is significant at the .05 level.

Therefore, these results support Hypothesis 3. U.S. customers have a more positive quality perception and greater willingness-to-purchase Chinese brands if they are made in a more developed and more reputable country, such as the U.S. or Canada, than if they were made in China.

While the preceding hypothesis involves the COM effect, Hypotheses 4a and 4b considers the COB effect. While the results have shown that a “Made in China” COM does adversely affect consumer perception and willingness-to-purchase, Hypothesis 4a posits that this negative effect can be influenced by a positive COB effect, resulting in a more positive overall COO effect and consumer reaction. The respondents were asked to rate (along quality and willingnessto-purchase) three products made in China with Chinese brands (Geely Haoqing, Lenovo and Haier). They were then asked to rate three more products; Toyota Corolla, Dell and G.E., made in China, with non-Chinese brands with relatively greater brand strength and recognition. A one-way MANOVA and GLM multivariate analysis was used, producing an overall significant result (p<.05) with the contrast result significant between the weaker Chinese brands and the stronger non-Chinese brands. This is indicated in Table III.

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Table III: Hypothesis 4a- Country-of-Brand (COB) Effects Effect F Hypothesis df Error df Sig. Intercept 5764.796 2.000 1393.000 .000 COB 149.327 2.000 1393.000 .000

Pairwise Comparisons Dependent Variable Quality Willingness to buy

(I) COB Weak Brand Weak Brand

(J) COB Strong Brand Strong Brand

(I) Mean 3.730

(J) Mean Mean Difference (I-J) 5.121 -1.391(*)

3.170

4.517

Std. Error

Sig.

.082

.000

.095

.000

-1.347(*)

Based on estimated marginal means * The mean difference is significant at the .05 level.

Therefore, the results support Hypothesis 4a. U.S. customers have a more positive quality perception and greater willingness-to-purchase Chinese-made products if they are branded with stronger, more recognizable brands with superior brand equity. Since the results show support for both Hypothesis 3 (COM effects) and Hypothesis 4a (COB effects), the question as to which effect was stronger emerges. Hypothesis 4b seeks to provide the answer. To this effect, the respondents were asked to rate three products made in China, but with non-Chinese brand names (Toyota Corolla, Dell and G.E.), respectively. In addition, they were asked to rate three products that were made in the U.S. or Canada, however, with Chinese brand names (Geely Haoqing, Lenovo and Haier). One-way MANOVA and GLM multivariate analysis was used, producing an overall significant result (p<.05) with the contrast result significant between Chinese brands made outside of China, and non-Chinese brands made in China. See Table IV below.

Table IV: Hypothesis 4b- COB Versus COM Effects Multivariate Tests Effect F Hypothesis df Error df Sig. Intercept 6358.730(a) 2.000 1395.000 .000 COB vs. COM 112.871(a) 2.000 1395.000 .000

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Pairwise Comparisons Dependent Variable Quality

(I) COB vs.

COM Chinese brand made in outside of China

Willingness Chinese to buy brand made in outside of China

(I) (J) (J) COB Mean Mean vs. COM Non3.891 5.085 Chinabrand made in China Non3.389 4.503 Chinabrand made in China

Mean Difference (I-J)

Std. Error Sig.(a)

-1.194(*)

.080

.000

-1.114(*)

.096

.000

Based on estimated marginal means * The mean difference is significant at the .05 level.

Support for Hypothesis 4b was also given by the results. For the U.S. consumers surveyed, the COB effect was stronger than the COM effect on their quality perception and willingnessto-purchase. While COB seems to be the more dominant component of the overall COO effect on the U.S. consumer, and a stronger COB effect implies a more positive consumer response, a more detailed examination of the characteristics of Chinese brands with regard to their COB influence on the respondents is required. Hypothesis 5 suggests that while Chinese brands are relatively weak in general, some Chinese brands are comparatively stronger and more developed than others from the perspective of the U.S. market.

Since Geely Haoqing has not yet been introduced in the U.S., it is expected to be the least developed and the weakest brand. Meanwhile, Lenovo would be the most developed with the strongest equity (e.g. the widely publicized connection with IBM), while Haier would be somewhere in the middle. The quality and willingness-to-purchase ratings given in the survey, specific to the three Chinese brands (Geely Haoqing, Lenovo and Haier), were analyzed using one-way MANOVA and GLM multivariate analysis. The overall result was significant (p<0.5). However, while the contrast result was significant between the least developed brand and the middle and high counterparts, the result was insignificant between the middle and highly developed brands (Table V).

Table V: Hypothesis 5- Brand Development Multivariate Tests Effect F Hypothesis df Error df Sig. Intercept 3981.110(a) 2.000 1356.000 .000 Brand Development 26.572 4.000 2714.000 .000

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Pairwise Comparisons (K) Brand (I) (J) (K) Mean Development Mean Mean Mean Difference (I-J); Dependent (I) Brand (J) Brand (I-K); Std. Variable Development Development (J-K) Error Sig. Quality

Willingness to buy

Low Developed

Low Developed

Middle Developed

Middle Developed

High Developed

High Developed

3.420 3.864 4.048

2.589 3.502 3.670

-.444(*)

.104 .000

-.628(*)

.104 .000

-.184

.104 .077

-.913(*)

.114 .000

-1.081(*) .115 .000 -.168

Based on estimated marginal means * The mean difference is significant at the .05 level

.114 .139

In general, the results support Hypothesis 5, specifically between the brand not yet available in the U.S. market and its already introduced counterparts. In this sense, Lenovo and Haier are stronger, more developed brands in the U.S. than Geely Haoqing. And therefore, have a relatively more positive COO effect.

Lastly, Hypotheses 6a and 6b proposed that for high value products, the COO effects are greater than for products with lower value. Specifically, the COO effects are more significant when it comes to automobiles, than when a laptop computer is involved, and even lower for a compact refrigerator. In the study, the respondents were asked to rate three product types (automobiles, computers, and refrigerators) made in China (with the Chinese brands: Geely Haoqing, Lenovo and Haier), in terms of product quality and willingness-to-purchase. The data was analyzed (one-way MANOVA and GLM multivariate analysis) and the overall result was significant (p<0.5). The contrast result was also significant between the high value product (automobile) and its low and medium value counterparts. However, the comparison between the low value (compact refrigerator) and medium value (laptop computer) products was (p=.098). This was evident in the following Table VI.

Table VI: Hypothesis 6a and 6b: Product Value Multivariate Tests Effect F Hypothesis df Error df Sig. Intercept 6936.674(a) 2.000 2073.000 .000 Value 32.702 4.000 4148.000 .000

14

Pairwise Comparisons

Dependent (I) (J) Variable Value Value Quality Low Middle Value Value

Willingness Low Middle to buy Value Value

(K) Brand (I) (J) (K) Mean Development Mean Mean Mean Difference (I-J); (IK); (J-K) Sig. High Value 4.301 4.480 3.932 -.179 .098

High Value

.369(*) .548(*) 3.962 4.063 3.080 -.101

.000 .000

.882(*) .983(*)

.000 .000

Based on estimated marginal means * The mean difference is significant at the .05 level.

.212

The results partially support Hypotheses 6a and 6b in the sense that the high value product exhibited the relatively greatest COO effect for Chinese products. When it comes to Geely Haoqing automobiles, a more negative COO effect resulted in a lower quality perception and willingness-to-purchase for U.S. consumers relative to the other products with lower value.

In contrast, the lower value Haier compact refrigerator was regarded more positively. What was interesting and unexpected was that the product with a level of value in-between (Lenovo laptop computers) the other two received the most positive customer reception. It was possible that the relatively stronger brand equity outweighed the product value effect on COO.

MANAGERIAL IMPLICATIONS AND CONCLUSIONS The results of the study do confirm that for brands and products associated with China, COO effects do adversely influence the U.S. consumer and their quality perceptions and willingnessto-purchase. Our findings support the notion that in a more developed environment, such as the U.S., the market generally tends to have a low quality perception of brands and products from a less developed source such as China. Moreover, there is significantly little to no brand awareness for Chinese brands among U.S. consumers. Therefore, as Chinese firms globalize and expand into more developed markets, dealing with the COO effect and building brand strength are critical to their strategic success.

The negative COM effect that a “made in China” association has on developed-market consumers needs to be ideally reversed into a positive effect, or in the least, neutralized. Under similar situations, such has been achieved through substantial communication with countryimage marketing through advertising and promotion. Taiwan, for example, has invested in a “very well made in Taiwan” marketing campaign and even developed the “innovalue” tag line to capture the innovation and value that Taiwan-made products can offer. In another example, Colombian coffee growers de-commoditized the status of their coffee and created a positive COO effect in a specific product category. In addition, they built a personality around the product personified in the brand character, “Juan Valdez”. Other developing countries, such 15

as South Korea, Indonesia, and Chile have utilized marketing and advertising to developed markets like the U.S. to deal with COO issues and create brand/product awareness and a positive COM effect. Another option would be to change the COM by establishing operations in more developed and reputable environments, such as the developed market itself. This can be done through either greenfield or merger/acquisition activity. In fact, we have seen a number of firms from less developed countries initiating overseas manufacturing in this manner.

These implications support the classic precept that international marketing managers, armed with market knowledge should first develop a quality product with effective and strong attributes to successfully meet customer needs. The next task would be to then build, establish and maintain strong brand equity to complement the product. The competitive edge derived from product characteristics and brand should be introduced and reinforced through sufficient and appropriate marketing communication. This marketing emphasis on brand and product attributes can effectively outweigh any negative COM effects. Previous studies (Chao, 1989: Tse and Gorn, 1993) have suggested ways that firms with traditionally unfavorable COO effects (e.g. those from less developed or emerging markets) can become more competitive. They could shift from exporting domestically manufactured products to foreign manufacturing in a favorable country image location such as a more developed economy like the United States.

The underlying assumption is that foreign direct investment (FDI) in manufacturing would realize a positive effect of COM. For example, by assembling its autos in the U.S., Geely could overcome any negative association with a “made-in-China” label. This follows the FDI strategy of Korean auto manufacturers Kia and Hyundai who have indeed located assembly plants in the southeastern United States.

The findings of the study further suggest that a weak brand, or negative COB effect, also needs to be addressed. In fact, the results indicate that it may even be more important to focus on COB, rather than COM. As past research has shown, a strong brand can dominate over negative COM effects (Ulgado & Lee, 1993). The findings are encouraging for international firms from less developed or emerging economies which seek to enter more developed markets as part of their globalization strategy. The results imply that the marketing emphasis of these companies should be first on creating a known and favorable brand image, which is expected to reduce a negative COM effect. For instance, Korean firms Daewoo (“Daewoo, That’s Who” campaign) and LG, as well as Taiwanese companies Acer and HTC have placed their advertising emphasis on company brand awareness and image building. Nevertheless, it should be maintained that a brand name will never by established without actual and significant intrinsic product attribute strength, and a marketing focus on them. Korean automaker Hyundai appears to put this idea into practice as its advertising emphasizes product features, price and performance.

Rather than FDI alternatives, Geely and other similar unknown or weaker Chinese brands could be better off by first developing a recognized brand image and building strong brand equity.

Instead of overseas transplant manufacturing to achieve positive COM effects, maintained domestic manufacturing with exporting, licensing, and private labeling through established retail distributors (such as Samsung did when it first entered the U.S.), could provide more profitable advantages in the long run. Another alternative would be the acquisition of a company with established brands, or a merger, joint venture, or strategic alliance with such a firm. This would not offer not only known-brand advantages but marketing, distribution and servicing experience and resources. Once product performance and other intrinsic attribute reputation 16

is established, along with a build-up of brand recognition, any negative COM effect would diminish as the brand name effect would dominate. The now-prestigious Japanese brands such as Nikon, Sony, and Honda (which once had a negative COM effect), and the more recent Korean brands like Hyundai, LG and Samsung have relied on exporting and building brand equity through intrinsic product attribute quality and other positive extrinsic features such as warranties, servicing, retailer reputation and price.

The findings of the current study also imply that for strong and favorable brands, country sourcing considerations become less significant as global brand strength and reputation overshadow COM effects. In the long run, a more global environment, with increased multi-country sourcing and/or assembly, and the proliferation of quality global brands, would eventually diminish the significance of COM relative to brand name and intrinsic product attributes. While the “madein” concept and COM could eventually mean several different countries, the brand and the country associated with it, COB, would remain consistent. Therefore, the implications suggest that COM considerations should not dominate manufacturing and sourcing strategies. Adequate research should be performed to confirm the existence and significance of any beneficial COM effects on consumer perception. The potential benefits from expected positive COM influence to be gained by FDI should be carefully weighed against the resulting costs. Other alternatives to achieving these benefits should be evaluated. Moreover, the advantages of product attribute and brand equity development alternatives and their effect over any negative COM effects should be considered. Other factors such as trade barriers, labor, transportation or distribution costs, and technology transfer may prove to be more viable reasons behind manufacturing and sourcing location.

Chinese companies can create higher brand awareness and build brand strength either through marketing and advertising of an existing Chinese brand, such as the case of Haier, or through acquisition and/or association with an already existing strong brand, such as the case of Lenovo and IBM. With Haier, the critical marketing component for its growing brand recognition is its accessibility to the U.S. consumer through distribution and product availability. For Lenovo, the focus has been more on acquisition, advertising and publicity. In both these cases, the other critical factor to its continued brand building is a good, quality product. These are some of the lessons that Chinese automobile manufacturers, can derive from those already in the developed markets. Most recently, Geely has in fact resorted to the strategy of acquisition of a strong brand through its purchase of Volvo. This approach has also been popular with India-based Tata Motors and its acquisition of established luxury auto brands Jaguar and Land Rover. In addition, Geely has also decided to dissolve the “Geely” brand by 2012 (Glucker, 2010) and build its other sub-brands (such as Gleagle, Emgrand, Englon and now Volvo). As Geely or Chery gear up towards a U.S. market entry, they first need to realize their brand weakness and focus on efforts to deal with the disadvantage. At the same time, they also need to ensure that their product quality is built and maintained. The study also suggests that dealing with negative COO effects, including both COM and COB, is even more critical given the high-value product category that these Chinese automakers are in.

While this paper provides further insight into the COO effects, with respect to China, from the perspective of the U.S. consumer, additional research is needed. The study was limited in terms of geography and respondent characteristics. A broader, nationwide or multi-country study with a more extensive sample would include additional COO effects related to other 17

developed and less-developed markets besides China and the U.S. This would improve the generalizability of the results and could clarify the COO effects (e.g. ‘foreign’ vs. ‘Chinese’).

The product categories were also limited to three moderate to high-priced, high-value items.

Comparisons with other types of products and product categories need to be considered.

Auxiliary investigation into the moderating effects of familiarity and other variables can also supplement our understanding of COO. Nevertheless, the study offers additional evidence of what Chinese firms are faced with, and what they can do in response as they venture farther in their globalization efforts.

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Asian Journal of Business Research

Volume 1

Number 2

2011

Standardization or Adaptation in International Advertising Strategies: The Roles of Brand Personality and Country-OfOrigin Image Xuehua Wang Shanghai University of Finance and Economics Zhilin Yang Victoria University of Wellington

Abstract This study investigates the issue of standardization and adaptation in international advertising from a consumer perspective by focusing on two variables, i.e., brand personality and countryof-origin (hereafter COO). Results reveal that brand personality is positively related to a more adaptive approach by firms; whereas COO image is found to exert a positive influence on a more standardized approach by firms. Implications for research as well as for practice are discussed.

Keywords: Brand personality, Country-of-Origin, Standardization, Adaptation, International Advertising.

Introduction The issue of international advertising standardization and adaptation has remained unresolved during the last several decades (Agrawal, 1995; Papavassiliou and Stathakopoulos, 1997).

International advertising standardization refers to utilizing the same or similar advertising messages across different countries or areas; international advertising adaptation is defined as using different advertising messages in separate markets (Kotler, 2008). However, there are no absolute international adaptation practices or advertising standardization across boundaries.

Academics have gradually recognized the importance of a contingency approach, which argues that the best advertising strategy needs to be carefully determined depending on an analysis of factors inherent in the particular situation or environment at hand (Buzzell, 1968; Miracle, 1968; Ryans, 1969). By answering this call, Papavassiliou and Stathakopoulos (1997) have conceptually developed a framework to summarize the relevant factors that impact the choice of the appropriate international advertising strategies; these factors include local environmental determinants, firm environmental determinants, and intrinsic determinants. However, few studies focus on the influence of specific determinants pertaining to the extent of standardization or adaptation of international advertising strategies.

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To address this gap, this study aims to investigate the issue of international advertising standardization and adaptation from a specific consumer profile perspective, specifically focusing on two factors, i.e., brand personality and COO effect, which are found to be significant in influencing consumer decision making (Wang and Yang, 2008).

Consumers purchase branded products not only for their functional benefits, but more importantly for the symbolic meanings embedded in products (Veryzer, 1995). Symbolic brand benefits refer to the signaling effects shown to others when consuming the brand (Keller, 1993).

In addressing the symbolic meanings contained in products/brands, several important research areas emerge; among them are brand personality and COO image.

Brand personality denotes the phenomenon that a brand is frequently related to various human personality characteristics, such as fashion-consciousness, prestige, and being down-to-earth (Aaker, 1997). Brand personality has been found to be positively associated with consumer preferences, such as usage, loyalty, trust, feelings of comfort, and confidence in consumers’ minds (Biel, 1993; Fournier, 1998; Sirgy, 1982). Therefore, brand personality is an important factor to consider when firms enter markets in different countries. However, it remains a question as to whether, or to what extent, a firm should standardize or adapt its international advertising strategy when its brand personality is strongly/weakly perceived by local consumers (Barich and Philip, 1991; Wang, Yang, and Liu, 2009). Empirical evidence is also lacking as to how brand personality affects a firm’s international advertising standardization and adaptation strategies. In addition, it is found that the advertisements of each country ideally display a certain degree of sensitivity to the brand personality characteristics of the specific local market (Mueller, 1987). It may be expected that the stronger the local brand personality characteristics, the more adaptive to local culture the international advertising strategy tends to be. Therefore, the first objective of this study is to investigate the impact of brand personality on international advertising strategies.

Country-of-origin refers to the country with which a manufacturer’s product is associated (Saeed, 1994). COO image describes the stereotypic perception that consumers hold toward the country’s representative products or brands (Nagashima, 1970; Roth and Romeo, 1992).

Prior relevant literature finds that consumers vary in their evaluation of products/brands from different countries; hence, these variations influence their attitudes and purchase intention toward the products/brands (Roth and Romeo, 1992; Schooler, 1965; Yasin et al., 2007). This COO concept can help international advertising managers to understand, in considerable detail, the target market so as to develop more effective advertising messages (Papavassiliou and Stathakopoulos, 1997). In addition, it is difficult for consumers to change this stereotypic COO image perception regarding a specific product/brand from a particular country; thus, firms ought to make full use of these COO image stereotypes, instead of trying to change them dramatically (Roth and Romeo, 1992; Wang and Yang, 2008). Therefore, it may be suggested that COO image could exert a positive influence on international advertising standardization.

However, it lacks empirical evidence as to how COO image influences the extent of international advertising standardization and adaptation; thus, the second objective of this study is to examine the relationship between COO image and the extent of international advertising standardization and adaptation.

Given the foregoing, the objectives of this study are to examine the influences of brand 26

personality and COO image on the extent of standardization and adaptation in international advertising strategies, respectively. Subsequently, we will review and elaborate on relevant conceptual background, and then, further develop research hypotheses.

Conceptual Background and Hypotheses Development Standardization and Adaptation of International Advertising When going international, firms must consider different degrees of two types of advertising strategies, i.e., standardization and adaptation. This topic has attracted enormous attention during the last several decades (e.g., Buzell, 1968; Ghoshal, 1987; Levitt, 1983; Papavassiliou and Stathakopoulos, 1997; Solberg, 2001). Standardization of international advertising strategy is defined as utilizing the same, or common, advertising messages on an international basis, since the worldwide marketplace has become increasingly homogeneous, to the extent that international firms can market standardized products/services all over the world through identical advertising strategies, principally due to such influences as TV, movies, and the Internet (Jain, 1989). The rationale behind this position is that consumers in different countries or areas share the same, or very similar, wants and needs; therefore, they can be persuaded by universal advertising appeals (Buzell, 1968; Fatt, 1967; Killough, 1978; Levitt, 1983). Such an international advertising strategy can result in substantial media and production cost savings, because the multinational company needs only to develop a common advertising campaign across world markets.

By contrast, adaptation of an international advertising strategy suggests that each market must be considered, for the most part, as a distinctly separate unit and adaptations must be made accordingly (Pratt, 1956, p.172) due to differences in culture, economic status, legal conditions, and foreign market media. In the 1960s, academicians gradually shifted towards the contingency approach when using international advertising, indicating that whether to standardize or not is not a dichotomous decision, and that there are various degrees of international advertising standardization and adaptation, depending on analysis of the factors relating to the particular situation or environment at hand (Buzzell, 1968; Miracle, 1968; Ryans, 1969).

Papavassiliou and Stathakopoulos (1997) develop a conceptual framework to capture the related factors that impact the degrees of adaptation or standardization in international advertising. One of the most important determinants is consumer profile, which encompasses the demographic, psychographic, and behavioral characteristics of consumers in the host country (Papavassiliou and Stathakopoulos, 1997). However, relatively few articles deal with the influence of consumer-related characteristics on the degree of standardization or adaptation in international advertising strategy; thus, this study intends to contribute new insights in this area by addressing two related influential factors in consumer decision making, i.e., brand personality and COO image.

Brand Personality Aaker (1997) defines brand personality as the human traits associated with a specific brand; Sweeney and Brandon (2006) further consider this concept from the perspective of interpersonal relationship with the brand and regard brand personality as those human characteristics corresponding to the interpersonal relationship that are relevant to depicting the brand as a relationship partner. Consumers imbue different brands with different brand personalities. For 27

instance, consumers may portray the brand of Leviâ&#x20AC;&#x2122;s as a brave, modern, and swaggering young man; while the brand of Coca-Cola may be personalized as a more traditional, family-oriented, and conservative man. Brand personality relates to the symbolic values possessed by a brand (Keller, 2003). Through association of brands with human personality characteristics and by consuming the brands, consumers can enhance their self-concept (Belk et al., 1982).

Consumers in different cultures tend to prefer different brand personality characteristics. For instance, in Eastern countries, the traditional brand traits such as family, down-to-earth, and friends are more generally preferred; whereas in Western countries, consumers may attach more value to such brand personality characteristics such as individualism, creativity, and risk-taking.

At the same time, as globalization intensifies, more and more people in different cultures share certain similar or common brand traits, such as prestige and social status. Thus, an important task for international advertising managers is to decide the degree of standardization and adaptation of international advertising when extending their campaigns to different cultures. In practice, the advertisements of each country ideally display a certain degree of sensitivity to the cultural uniqueness and to the brand personality characteristics of the specific local market (Mueller, 1987). Thus, the stronger the local brand personality characteristics, the more adaptive to local culture the international advertising strategy tends to be. Hence, we hypothesize that: H1: Local brand personality strength tends to be positively related to the degree of adaptation of international advertising strategies.

COO Image COO image is important in affecting consumersâ&#x20AC;&#x2122; perceptions toward products/brands from a given country (Johansson, Douglas, and Nonaka, 1982; Saeed, 1994; Ahmed, Johnson, and Boon, 2004), and can further influence purchase intention (Roth and Romeo, 1992; Papadopoulos and Heslop, 1993). Hong and Wyer (1989) find that COO image is positively related to consumersâ&#x20AC;&#x2122; product quality evaluations. Thus, if a country possesses a positive image on particular product category dimensions important for product classification and evaluation, then consumers would hold favorable attitudes toward products of this category from that country (Roth and Romeo, 1992). For instance, when talking about fashionable clothing, people would think favorably of brands originating in Italy.

The COO image concept can help international advertising managers to understand more thoroughly their target market and thus develop a more suitable advertising program for the local market. For instance, Germany is famous for making cars and also enjoys a good reputation throughout the world. Thus, a joint venture company in China, collaborating with its German partner, can make good use of the particular and positive COO image of Germany, and thus develop advertising messages specifically emphasizing such a COO image. An important characteristic of COO image is that it represents a stereotypic perception toward a specific kind of product or brand manufactured in, or originating from, a particular country (Lin and Chen, 2006). It is not easy for consumers to change this stereotypic COO image perception in the short term; thus, companies should utilize these image stereotypes, instead of trying to change them dramatically (Roth and Romeo, 1992). Hence, the stronger the COO image is, the more standardized the international advertising strategy tends to be when using COO-related ad messages. Therefore, we hypothesize that:

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H2: COO image tends to be positively related to the extent of standardization of international advertising strategy.

Research Methodology Questionnaire and Measures The questionnaire included two sections. The first section measured three factors (Brand personality, COO image, the perceived extent of standardization in international advertising); the second part recorded respondent demographic information. The questionnaire was originally in English; then it was translated and back-translated into Chinese until acceptable translation accuracy was achieved.

Brand personality was measured by adapting Aaker (1997)’s five-dimensional scale, including sincerity (inclusive of down-to-earth, honest, wholesome, and cheerful), excitement (daring, spirited, imaginative, and up-to-date), competence (reliable, intelligent, and successful), sophistication (upper class and charming) and ruggedness (outdoorsy and tough) on a 7-point scale with a Cronbach’s alpha reliability coefficient of .92. Based upon Table I, the correlation coefficients for the four components of brand personality (i.e., sincerity, excitement, competence, and sophistication) were in the range of 0.69 to 0.74, which were all significant at the p < .01 level. In addition, each of the four components was highly correlated with the overall scale of brand personality (.80 or above).

Table I: Correlations among the Four Components of Brand Personality Sincerity Excitement Competence Sophistication Sincerity Excitement Competence Sophistication Brand personality

1.000 .69* .72* .74*

1.000 .70* .71*

1.000 .72*

1.000

.89*

.87*

.85*

.80*

Brand personality

1.000

Note: *Statistically significant at p < .01 level.

Roth and Romeo (1992)’s scale was adapted to measure COO image. It includes four dimensions: innovativeness (using new technology and engineering development level), design (appearance and style), prestige (status and reputation), and workmanship (reliability, durability, craftsmanship, and quality). Nine items with anchors ranging from 1 “absolutely disagree” to 7 “absolutely agree”, with a Cronbach’s alpha reliability coefficient of .91, were used for measurement. Results presented in Table II showed that correlations among the four components of COO image ranged from 0.51 to 0.63 and all were statistically significant at the p < .01 level. Each component was highly correlated with the overall measure of COO image (.77 or above).

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Table II: Correlations among the Four Components of COO Image Innovativeness Design Innovativeness Design Prestige Workmanship COO image

1.000 .51* .52* .61* .78*

1.000 .59* .63* .81*

Prestige

Workmanship

COO image

1.000 .57* .77*

1.000 .89*

1.000

Note: *Statistically significant at p < .01 level.

We used a subjective measure for the perceived extent of standardization and adaptation of international advertising, such as the communication platform, creative idea, or concept (Solberg, 2002; van Raaij, 1997). The concept was captured by using five items including “To what extent do you consider that the advertising of the brand is standardized in terms of (1) its selling argument; (2) its main idea; (3) its text; (4) its endorsers; and (5) its product associations” with a Cronbach’s coefficient alpha of 0.88. The final pool of measurement items was determined by soliciting suggestions from experts in this field.

Finally, all measures were subjected to a confirmatory factor analysis (CFA) to check validity issues. The CFA allows for a validity evaluation of the measures used. The fit indices (χ²/df = 1.92, p = .000, goodness-of-fit index [GFI] = .91, adjusted goodness-of-fit index [AGFI] = .90, confirmatory fit index [CFI] = .95, normed fit index [NFI] = .93, root mean squared error of approximation [RMSEA] = .04) suggest a good fit of the measurement model. All items loaded significantly (critical ratio [CR] > 1.96) on their corresponding constructs. Therefore, evidence of trait validity is provided for the dependent measures (Anderson and Gerbing, 1988).

Sample and Data College students in Macau were recruited as our sample respondents. First they were required to watch two TV editions of four brands in four product categories (i.e., beer, cola, razors, and clothes); these brands were Budweiser for beer, Coca-Cola for cola, Gillette for razors, and Levi’s for clothes, which were all familiar to youngsters in China. The two TV editions for each brand were from the U.S. and mainland China, respectively. There were two reasons that we use students in Macau to watch ads from U.S. and mainland China. First, Macau is adjacent to Mainland China and has been greatly influenced by Mainland China’s consumption culture, since it is a tiny place with limited resources. Thus, the cultural difference between Macau and mainland China is relatively small. Second, most of the university students that we sampled were from the Chinese mainland (72.9%). Subsequently, each student in the sample was asked to complete the questionnaire based upon his/her understanding of these different ads. Three hundred and fifty six questionnaires were distributed. Two hundred and sixty one usable questionnaires were finally collected with a response rate of 73.3%. There were 145 female (55.6%) and 116 male respondents (44.4%). Ages of respondents were primarily between 20 and 23 years old (92.7).

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Results Regression analysis was used to test the two hypotheses, after controlling for gender and age. Gender was dummied in the regression analysis. It was hypothesized by H1 that brand personality would be positively related to the extent of adaptation of international advertising strategy. According to Table III, regression results indicated that brand personality produced a significant and positive standardized coefficient (.21) on the extent of adaptation of international advertising strategy, thus supporting H1.

Table III: Hierarchical Regression Analysis Results (DV: The Extent of Ad Adaptation) Explanatory Variables Gender Age Brand personality COO image Constant F R2 Overall model p value

Note: * p < .01.

Beer .11* .05 .12* -.10* 3.22 11.43 (p < .001) .21 .000

Cola .03 .04 .07* -.09* 2.71 9.05 (p < .001) .14 .000

Razors .09* .02 .25* -.29* 2.94 17.82 (p < .001) .30 .000

Clothes .08* .03 .15* -.11* 3.76 14.13 (p < .001) .23 .000

H2 predicted that COO image would exert a negative influence on the extent of adaptation of international advertising strategy. Based on models 2 and 3 in Table III, regression results revealed that COO image was negatively and significantly related to the extent of adaption in international advertising with a standardized coefficient of -0.27. Therefore, H2 was supported.

We also split the database based on the four product categories (see Table IV). We found that the cola product category produced less significant results than other three categories. Specifically, for the cola sample, the standardized regression coefficients for brand personality and COO image were 0.07 and -0.09, respectively. In contrast, the razor product category generated stronger significant results than other three product categories. Specifically, the standardized regression coefficients for brand personality and COO image were 0.25 and -0.29, respectively for the razor sample. This finding indicated that the effectiveness or impact of brand personality and COO image on the extent of adaptation of international advertising may depend on product categories.

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Table IV: Standardized Regression Coefficients across Different Product Categories (DV: The Extent of Ad Adaptation) Explanatory Variables Model 1 Model 2 Model 3 Gender √ √ √ Age √ √ √ √; (.21)1 ; √; (.20)1; (.25)2 Brand personality (.27)2 √; (-.27) 1 ; COO image (-.29)2 Constant 2.19 2.98 3.86 7.81 12.79 14.95 F (p < .001) (p < .001) (p < .001) 2 .12 .25 .29 R 2 .12 .13 .04 R change Adj- R2 .10 .23 .27 .000 .000 .000 Overall model p value Notes: 1 is the standardized regression coefficient; 2 is the unstandardized regression coefficient.

Discussion This study investigates the relationship between brand personality, COO image and the extent of standardization vs. adaptation in international advertising strategy, which no prior studies have explored empirically. Results reveal that the stronger the brand personality, the more adaptive the international advertising is to local consumer needs and wants; COO image is found to be negatively related to the extent of adaptation of international advertising due to its stereotypic characteristic. Implications for research as well as for practice will be discussed.

The stronger the brand personality, the stronger the extent of adaptation of international advertising tends to be. Different consumer segments across the world attach different personality characteristics to the same object. For instance, the color of red is associated with active, hot or enthusiastic in Asian countries; in contrast, red is poorly received in African countries. Thus, in line with this prior relevant research, this study finds that advertising messages have to be adapted to local brand personality perceptions to achieve higher acceptance rate (Melewar and Vemmervik, 2004).

COO image is found to be negatively related to the extent of adaptation in international advertising. COO image represents the stereotypic perception that consumers hold toward the country’s typical products/brands (Roth and Romeo, 1992; Bluemelhuber et al., 2007). One important role played by COO image is called the halo effect (Han, 1989). That is, when consumers are not familiar with a product/ brand, they rely primarily on the halo effect to infer product/brand attributes, thus affecting their product/brand attitudes. Moreover, it is not easy to change COO image of a particular country toward its representative products/brands in the short term; thus, because of this COO image characteristic, multinational companies need to use a high extent of standardization in their international advertising strategy to optimize COO advertising appeal.

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Another finding is that the cola sample generated less significant results than the other three product categories for brand personality and COO image. This may be due to the fact that Coca Cola has enjoyed a unified brand image and comparatively similar brand personality characteristics across the world. Thus, the effect of brand personality and COO image for cola was not so evident as for the other three product categories. In addition, we also found that the razor sample generated more significant standardized regression coefficients than the other three product categories. The razor advertisement of the US version featured male-female intimacy and the endorsers were foreigners; whereas the China version was related to friends and work scenarios and the endorsers were Chinese. After students watched the two ads, they were required to imagine that the two endorsers in the US version were replaced by Chinese; some students responded that such an intimate advertising scenario would make them feel uneasy, which may be due to the cultural differences between Eastern and Western values.

Our findings also tell us that the effect of consumer profile variables may be dependent on advertising campaigns and product categories.

Managerial Implications The findings of this study can also be helpful for multinational companies in dealing with the issue of the extent of standardization and adaptation in international advertising. First, quality survey research on local consumer attitudes toward brands can help international advertising managers understand, in considerable depth, the various brand personality associations in different countries or areas, which further assist the development of local advertising programs.

Second, in designing advertising messages that emphasize the COO image of a specific brand, international companies can, to a greater extent, standardize their advertising campaigns across world markets so as to save media and advertising costs.

Third, the effects of brand personality and COO image may vary across different advertising appeals and product categories. Thus, multinational companies need to gain insights into each product/brand category and conduct research on different advertising campaigns in order to determine the extent of standardization or adaptation in their advertising strategy.

Limitations and Future Research Limitations of this study, as well as directions for future research, need to be noted. We did not consider brand familiarity or brand involvement as control variables, which may influence the quality of our results. Some students may already hold favorable or unfavorable views toward the brands investigated. Future research should reduce this sample bias to achieve more generalizable results.

In addition, college students were used as our sample respondents, which may limit the generalizability of our results. For future research, it is desirable to recruit more diverse consumer segments in order to produce more insightful results. Another direction for future studies is to take product categories into consideration, since the effects of brand personality and COO image depend on product categories.

Finally, we recognize that there are other variables that can influence the extent of standardization and adaptation of international advertising, such as self-concept, personality-related constructs, and consumption patterns in different cultures; thus, future studies need to incorporate these as well as other factors to capture a more complete picture of this phenomenon.

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36

Asian Journal of Business Research

Volume 1

Number 2

2011

Impact of Quantity and Timeliness of EWOM Information on Consumer’s Online Purchase Intention under C2C Environment Fu Xiaorong, Zhang Bin, Xie Qinghong, Xiao Liuli, Che Yu. Southwestern University of Finance and Economics

Abstract Based on consumers’ “cognitive→affective→behavior” hierarchy theory of reaction, this paper builds the relational model of electronic word-of-mouth (eWOM) information (from two dimensions, quantity and timeliness), consumer trust, and purchase intention under C2C environment. The 2×2×2 between-subjects experiment on 320 undergraduates in Southwestern University of Finance and Economics illustrates that quantity and timeliness of eWOM information have significant influences on consumer trust, which has significantly positive influence on purchase intention; and the effect of the quantity and timeliness of eWOM information on consumer trust is also affected by the difference of product category. When buying fashion product (such as fashionable dress), the influence of quantity and timeliness of eWOM information on consumer trust is greater than that on functional products (such as books).

Keywords: C2C, WOM, Consumer trust, Purchase intention

Introduction Along with the booming of Internet and e-commerce, more and more people begin to shop on the Internet. Therefore, consumer’s online purchase behavior has attracted attention both from the academic circle and the business entities. Literature shows that features of eWOM information have strong influence on online purchase behaviors. Currently, eWOM information has two dimensions, quality and quantity. The quality dimension refers to the features which include path of communication, type, longevity, timeliness, etc (Kozinets, 1999; Park and Lee, 2007; Jin Liyin et. al, 2007). However, researches on timeliness of eWOM information were limited and divergent. Some researchers thought the higher the perceived timeliness of the message is, the greater the usefulness of the message is, and the greater the online purchase intention is (Doll and Torkzadeh, 1988; Madu and Madu, 2002; Cheung et al, 2008). However, Zheng 37

Xiaoping’s research (2008) found that this information feature has no significant influence on online purchase intention. Why are the research results different from each other? According to some researchers, product type will influence consumer’s reliance on online messages and further impact their online purchase behaviors (Nelson, 1970; Senecal, et al, 2004; Bei, 2004; Song, 2005). We have to consider whether the difference in product type is the factor resulting in this difference. And whether the influences of eWOM information quantity and timeliness on consumer trust and purchase intention are different when the consumers purchasing different products?

Therefore, this paper tried to introduce product type as a variable to analyze the integrated influence of product type, quality, and timeliness of eWOM information on consumer’s online purchase behaviors. With abundant information about the influence of eWOM information on consumer’s online purchase behaviors, this paper hopes to help e-commerce companies to process eWOM information effectively with limited resources, enhance consumer trust, satisfy their individual demands, and win more customers.

Literature Review A majority of researches argued that eWOM information has significant influence on online purchase behaviors. Kozinets (1999) stated that eWOM information could effectively decrease consumers’ doubts formed from online purchase such as perceived risk, information asymmetry, information absence, etc., so that it can help consumers make purchase decisions. According to Jupiter’s research in 1999, eWOM information is an important source for customers to get information about the product because 57% of customers would look through online consumer reviews (Godes, 2004). Forrester’s research (2000) indicated that more than 50% of young customers would purchase movies, CDs and games according to recommendations from eWOM information. Park and Lee (2007) argued that as a part of eWOM information, online consumer reviews on specific products are valuable information formed from their past experiences. Therefore, the reviews are quite influential and useful for other customers to make purchasing decisions.

The current research of eWOM influence mechanism How does eWOM influence consumer buying decision? Smith (2002) investigated the influence of consumers’ recommendations on consumer decision-making in virtual community in his doctoral dissertation. In this study, he used three variables (individual difference, features of recommendations and buying target) to describe the influence of eWOM on consumer decisions.

He thought that the trust is the mediator variable and target is the moderator variable in this process. His study drew two conclusions: First, trust was the mediator variable which helped to realize the influence of eWOM information on consumer decision; second, the influence of eWOM information on trust varied in different buying environments and for different products.

Smith Menon & Sivakumar(2005) further discussed the above mentioned results in their following researches. They carried out emulational decision-making experiment to study the influence of WOM on online consumer decision-making. The two empirical studies demonstrated that lots of online consumers would actively look for and accept related information to improve information searching efficiency. This indicated that consumers are always in the state of high involvement.

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Komiak (2003) studied the influence of Recommendation Agents (including features like internalization and familiarity) on consumer adoption intention and decision-making in e-commerce environment. The study argued that internalization and familiarity influence ability-based trust, benevolence-based trust, integrity-based trust and affection-based trust, therefore ultimately influence consumer adoption intention and cognition-assisted preference.

On the other hand, ability-based trust, benevolence-based trust, and integrity-based trust bring impact over affect-based trust.

Chen Beilei (2008) divided the factors which influence eWOM communication into three aspects: source, message, and acceptor. Source refers to the expertise, affability and creditability (Rogers, 1995), as well as religion, identity, status, ethics, etc.. Message includes opinions, appeals and conclusions. Acceptor encompasses its ideas, involvement, perusability and characteristics. These contributed to the influencing model of eWOM information on consumer purchasing decision.

Xu Lin (2007) illustrated the power of eWOM depending on its creditability. This study found five aspects that are strength of relationship between information publisher and reader, the reliance of reader on eWOM communication platform, readerâ&#x20AC;&#x2122;s perceived usefulness of web sites, risks involved and propensity to trust have significant positive impact on eWOM creditability.

Generally speaking, existing researches on eWOM model have drawn two conclusions: First, the influence of eWOM on consumer purchase intention depends on three factors: features of information contributor, features of information and recipientsâ&#x20AC;&#x2122; individual characteristics; second, in the influence mechanism of eWOM on buying intention, trust is the most important mediator variable. That is, the three variables influenced consumer trust first and then on buying intention. At the same time, product type played a moderating role in the process of trust development. Therefore, this paper focuses on the influence mechanism of eWOM information on consumer buying intention.

The current research of eWOM information Current studies have analyzed the influence of eWOM information on customer online purchase behaviors. Park and Lee (2009) used experimental study to analyze the influence of direction of eWOM, website reputation and product type on the effect of eWOM communication.

The research showed that the influence of negative WOM information is much greater than that of the positive one, the impact of WOM information from websites with reputation is much greater than that from websites without reputation, and product type plays a significant moderating role in the process. The empirical research on eWOM creditability carried out

by Xu Lin (2007) found that the strength of relationship between consumer and information publisher, consumer reliance on eWOM communication platform, their perceived usefulness of websites, risks involved, and propensity to trust have significant positive impact on eWOM creditability. Jin Liyinâ&#x20AC;&#x2122;s research (2007) indicated that type of word-of-mouth information, the direction of communication and the product involvement have significant positive influence on consumer purchase decisions. Furthermore, the interconnection among the three factors also has significant positive impact on the effect of eWOM communication. Zheng Xiaoping (2008) divided online consumer reviews into four types, which are content, creditability, timeliness, 39

and quantity. He found that content, creditability and quantity bring significant positive impact over buying decision, but timeliness has no significant influence on buying decision.

Xi He’s research (2008) illustrated that contributors’ expertise, recipients’ propensity to trust and perceived risk have significant influence on the effect of eWOM information. However, features of eWOM information and recipients’ expertise do not bring any significant impact over the effect of eWOM. Chen Mingliang and Zhang Jingjing’s research (2008) on factors which influence eWOM diffusion intention demonstrated that interestingness of content is the most important factor, followed by source creditability, recipients’ altruist motivation and the self-promotion motivation. However, the extroversion of recipients’ characteristics has no significant influence on eWOM diffusion intention.

The current literature has presented a large amount of analyses about the influence of eWOM information features on online purchase behaviors. However, the current researches have two shortcomings. On one hand, there are limited researches on the interconnection effect of quantity dimension and quality dimension, which are two dimensions of eWOM information.

On the other hand, the research on timeliness, the dimension that derives from information quality is also limited and divergent. Therefore, this paper hopes to investigate the influence of quantity and timeliness on consumer trust and purchase intention. Specifically, the quantity of eWOM information refers to the scale and amount of electronic comment on specific product or service. And timeliness of eWOM information means the length of interval between publishing and viewing online.

Consumer trust under C2C environment According to Social Exchange Theory, consumer trust under C2C environment plays a key role.

Social exchange theory is about the rules and regulations controlling resource exchange among people (Frenzen and Nakamoto, 1993). These resources include the economic value of tangible product, the related experience and symbolic value of intangible product or service. Therefore, word-of-mouth is also regarded as a form of social exchange (Gatignon and Robertson, 1986; Frenzen and Nakamoto, 1993). In this exchange, the status of trust will be promoted because of high uncertainties and risks (Molm, Takahasi and Peterson, 2000).

Under C2C environment, the participants undertake more risk than in the real world. Therefore, we give a new definition of consumer trust under C2C environment. Corritore and Kracher (2003) thought that “online trust is a kind of attitude, a trustworthy expectation that their vulnerability won’t be attacked in online environment.” Pavlou (2003) held the view that trusts in e-commerce trade includes the creditability and benevolence of the trustee. Some researchers proposed three dimensions of trust in e-commerce environment, which are the trustee’s ability, benevolence, and integrity (Bhattacherjee, 2002; Gefen, 2003). Based on the above mentioned definition, this paper adopts that consumer trust under C2C environment refers to consumers’ perceptions of online sellers’ ability, benevolence and integrity, and the consumers’ intentions and expectations which are based on the above aspects.

A lot of researchers thought the formation of consumer trust under C2C environment relies on three aspects, which are the formation of trust on process, feature, and institution (Zucker, 1986). Kim and Prabhakar (2002) demonstrated that consumers’ propensity to trust, word-ofmouth and security guarantee are the factors that influence consumer in forming initial trust.

Kim et.al (2005, 2008) constructed the process-oriented multi-dimensional model of online transaction. This model proposed four classifications that influence consumer trust and their 40

perceived risks of e-commerce entity, which includes cognition, emotion, experience and characteristics. This paper researches the influence of eWOM information on cognition-based consumer trust.

Consumer trust is regarded as the most important factor that influences the success of e-commerce transaction (Gefen et al, 2000). Due to uncertainty of seller’s behaviors or the perceived risks such as the loss of personal information through hacker attack, consumers often hesitate about the transaction with online sellers (McKnight et al, 2002). Therefore, trust plays a key role in helping consumer overcoming perceived risk and uncertainty. Gefen and Straub (2000) thought that the predictable variable that influences trust is a common phenomenon, and online trust formed in online service is positively related to consumer purchase intention (Cheung and Lee 2006; Gefen and Karahanna 2003; Kim and Steinfield 2008; Pavlou 2003; Pavlou and Gefen 2004; Suh and Han 2003).

Research model and research hypotheses Literature review about the influence of eWOM information on purchase intention discovered that consumers will actively look for and evaluate information (Smith Menon & Sivakumar, 2005). Their decisions are made with high involvement and trust is the most important mediator variable in the process. Therefore, based on consumers’ cognitive → affective → behavior hierarchy theory of reaction, this paper builds the relational model of eWOM information → consumer trust → purchase intention, and introduces product type as moderator variable to analyze the influence mechanism of eWOM information feature on online purchase behaviors.

The model is shown in Figure 1.

Figure 1: The model of eWOM information, consumer trust and purchase intention

eWOM information quantity eWOM information timeliness

Product type

H1 H2

H

H4

Consumer trust

H5

Purchase inetntion

Product type type

Control variable:

eWOM information direction is positive and of high quanlity eWOM information is positive valuation eWOM information is of adequate longevity

Cognitive

Affective

41

Behavior

The relationship among eWOM information quantity, timeliness, and trust Under C2C environment, people will feel that the majority’s behaviors are trustworthy when they are in uncertain context. Chen and Dhanasobhon (2007) carried out specific research on online transaction, pointing out that online evaluation message is helpful for consumer to make buying decision. Consumers would look through messages to evaluate the quality of the product online to eliminate doubts for online shopping and establish trust between buyers and sellers.

Ren Chunhua and Liu Yezheng’s empirical research (2009) found that eWOM information quantity is positively related to information creditability. Therefore, this research argues H1: The larger the quantity of eWOM information, the greater the extent of consumer trust.

Doll and Torkzadeh (1988) proposed that in online environment for end-users, eWOM information timeliness is one of the most important factors that influence perceived quality of products. Madu and Madu (2002) urged that when the web site is not updated consistently, the web site cannot deliver the expected performance and therefore provides no added value to users. Cheung et al’s research (2008) also proved that the higher the timeliness of message, the higher the creditability perceived by consumers. However, Zheng Xiaoping (2008) found that the influence of timeliness on online purchase behavior is insignificant. This paper holds the view that when consumer purchase product that will lose value rapidly as time goes by, they tend to think that today’s reviews are of different value from the reviews (with the same content) left one year ago. Based on the analysis, this research proposes that eWOM information timeliness has significant impact on consumer trust.

H2: The higher the timeliness of eWOM information, the greater the extent of consumer trust.

The moderating effect of product type Nelson (1970) thought that consumer relies heavily on recommendations when they are buying product whose quality could be confirmed only after the purchasing behavior. It is different from buying product whose quality could be confirmed before purchasing behaviors.

Senecal, et al (2004) proved this point through experimental study. Bei et.al’s research (2004) revealed that consumer who is buying experiencing products tends to rely heavily on eWOM information, while consumer who is buying searching products will not depend on eWOM information to a great extent because retailer and manufacturer’s introductions to searching product are more useful. Song (2005) argued that different product types will produce different influences to consumer. Consumers who buy experiencing product and entertainment product like movies are easier to be influenced by eWOM information. According to literature review, the experiencing product whose quality could be confirmed only after purchasing behavior is called fashion product, while the searching product whose quality could be confirmed in the process of information searching is called functional product. Based on the conclusion, this research argues H3: The influence of eWOM information quantity on consumer trust when buying fashional product is more significant than that of the functional product.

Zheng Xiaoping (2008) revealed in the empirical study that the influence of eWOM information timeliness on consumer purchase decision is insignificant. Try to consider if the value of today’s 42

reviews is the same or different when you are buying the fast-depreciating product and the slow-depreciating product. Therefore, this research proposes that due to difference in product type, the influence of eWOM information timeliness on consumer trust varies. Therefore, it is argued that H4: The influence of eWOM information timeliness on consumer trust when buying fashion product is stronger than that of functional product.

The relationship between trust and online purchase intention Azjen and Fishbein’s research (1980) found that trust and purchase intention is related. Bowen and Shoemaker (1998) argued that consumers are willing to positively publicize the firms they like and trust then they tend to repurchase the product and service the firms provide.

Gefen (2000) stated that consumer trust has direct influence on online purchase intention.

Furthermore, Kimery and Mccord (2002) argued that trust established in the process of online shopping helped to decrease consumers’ cognition of perceived risks. Trust is positively related to online purchase intention. Koufaris and Hampton-Sosa (2004) and Gefen and Straub (2003) suggested that trust could increase the extent of online users’ purchase intention. Liu Weijiang (2005) built a model from the perspective of the features of e-commerce, explaining consumer purchase behaviors in online environment. He thought that trust is the most important ingredient that influences consumer purchasing behavior, and trust is closely related to purchase intention.

Donna’s empirical research (2006) also demonstrated that trust is positively related to online shopping. Therefore, this paper proposes that H5: Consumer trust has positive influence on consumer purchase intention.

Method Overview The objective of this paper is to demonstrate that the influence of eWOM information quantity and timeliness on consumer purchase intention is different when the customers purchase different products. Therefore, we used a 2×2×2 between-subjects experimental design: eWOM information quantity (large, small), eWOM information timeliness (high, low), and product type (fashion product, functional product). It is designed to test the differences in consumer trust and purchase intention among these groups.

Method At the beginning of the experiment, participants looked through the product reviews in a web page. The product type was either fashion or functional. The information that participants read was different in terms of quantity and timeliness. After finishing reading the information, they expressed the degree of trust and their purchase intention.

Stimuli This experiment adopted expert interview method to choose products for experiment. 20 university students with abundant experience in C2C online shopping participated in the group interview. Based on the interview, we produced a product catalog. After the initial investigation at the aspects of fashion, function, and purchase frequency, we chose the costumes for youth (fashion product) and the books (functional product) as the products for experiment.

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This research used the Delphi investigation method to measure eWOM information quantity and timeliness. The 20 participants explained their understanding of the quantity and timeliness on online messages of fashion clothes and books through email and QQ (a popular communication tool on the Internet in China). The average calculated from the third investigation of 20 participants (the manipulated variable) is as follows: Table I The measurement of eWOM information quantity and timeliness Product type Costume (fashion product) Books (functional product) Costume (fashion product) Books (functional product)

The levels of eWOM information quantity and timeliness Large quantity Small quantity Large quantity

Results More than 38.5 pieces of messages Less than 6.1 pieces of messages More than 15.6 pieces of messages

Small quantity

Less than 3 pieces of messages

High timeliness Low timeliness High timeliness

Messages within 19.65 days Messages beyond 58.5 days Messages within 47.5 days

Low timeliness

Messages beyond 158.75 days

Procedure 320 undergraduates in Southwestern University of Finance and Economics participated in the experiment for extra course credit. Participants were randomly assigned to one of eight conditions of a 2Ă&#x2014;2Ă&#x2014;2 between-subjects experimental design: eWOM information quantity (large, small), eWOM information timeliness (high, low), and product type (fashion product, functional product).

We told the participants that the study was aimed at online films and the experimenters who are interested in how people form impressions based on product reviews. Followed by that, all participants read online product reviews. In the small quantity condition, participants had three minutes to read the reviews, while in the large quantity condition, they had six minutes. We also told the participants that in order to get stable measurements of their impressions, they should report their impressions at the same time.

40 undergraduates from the same subject product (the books) evaluated different information quantity along a scale from one to seven. Results confirmed that the online reviews including 16 pieces of massages (M=4.53) were significantly larger than that of 3 pieces of massages (M=2.03; F(1,78)=52.717; p<0.001). Also, the online reviews published within 48 days (M=4.85) were significantly more timely than that published over 159 days (M=2.78; F(1,78)=36.89; p<0.001).

In customs context, results confirmed that the online reviews including 36 pieces of massage (M=5.20) were significantly larger than that of 6 pieces of massages (M=2.75; F(1,78)=57.132; p<0.001). Also, the online reviews published within 20 days (M=5.98) were significantly more timely than that published over 59 days (M=3.73; F(1,78)=66.93; p<0.001).

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After finishing reading these online reviews, the participants finished questions about consumer trust and purchase intention. Consumer trust was measured by three dimensions proposed by Bhattacherjee (2002): ability, integrity, and benevolence. As for purchase intention, we adopted the four-item scale proposed by Jaeki Song et.al (2005).

Results Manipulation Checks Manipulation check is to assess whether online review’s quantity and timeliness are appropriately manipulated. It suggests that the quantity of online reviews perceived by customers is larger when it is presented in large quantity condition (M =4.77) than when it is presented in small quantity condition (M=2.39; F(1, 236)=121.553.6; p <0.001). Also, as expected, participants think online reviews are more timely when it is presented in high timeliness condition (M=5.49) than when it is presented in low timeliness condition (M=3.43; F(1, 236) =102.319; p <0 .01).

Trust Evaluations We expected that eWOM information quantity and eWOM information timeliness would affect significantly on customer trust, and product type also affects customer trust by interacting with information quantity and information timeliness. As shown in table 7, this is indeed the case.

The 2×2 ×2 ANOVA on consumer trust confirmes that the interaction of product type and eWOM information quantity is significant (F(1, 237)=5.258; p <0 .05), and the interaction of product type and eWOM information timeliness is also significant(F(1, 237)=3.028; p <0 .1).

The results shows the statistics of eWOM quantity (F=32.14, p＜0.01) and eWOM timeliness (F=21.15, p＜0.01) , indicating that the main effect of eWOM quantity and eWOM timeliness is significant at the 0.01 level, and the interaction effect of eWOM quantity and eWOM timeliness on consumer trust is insignificant (F=0.208, p=0.649＞0.05). Therefore, H1 and H2 are approved.

As expected, the results shows that when the two stimuli are highly related, participants’ evaluations of trust is significantly different between groups (as shown in figure 3).The means of fashion product (A1) and functional products (F1) to consumer trust are 0.401 and 0.891 respectively, t=-3.034, p<0.05, implying that in the conditions of large quantity and high timeliness, product type has significant moderating effect on consumer trust. In the test of A2 and F2, t=-2.637, p＜0.05, indicating that the means of product type to consumer trust are significantly different at the 0.05 level in the condition of small quantity and high timeliness. In the test of A3 and F3, t=-2.442, p＜0.05, indicating that the means of product type to consumer trust are significantly different at the 0.05 level in the condition of large quantity and low timeliness. In the test of A4 and F4, t= -0.378, p＞0.05, implying that the means of product type to consumer trust are insignificantly different at the 0.05 level in the condition of small quantity and low timeliness. These statistics demonstrate that consumer trust is low when eWOM information is of small quantity and low timeliness, no matter what kind of product consumer is going to buy online.

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Figure 2: The influence of eight experimental contexts on consumers trust

Purchase Intention test We adopted regression analysis to test H5. Based on regression analysis of eWOM information quantity, consumer trust and purchase intention, we prove that the influence of eWOM information quantity on purchase intention is realized through the mediator---consumer trust.

Consumer trust displays significant influence on purchase intention. Before the addition of the mediator---consumer trust, the influence of eWOM information quantity on purchase intention was significant (β=0.375, p<0.001, R2=0.138). After the introduction of consumer trust, the influence of eWOM information quantity on purchase intention is insignificant, while consumer trust brings significant influence over purchase intention (β=0.863, p<0.001, R2=0.705).

Furthermore, the model’s fitting degree has been improved (0.705>0.138), demonstrating that consumer trust is of good explanation of purchase intention, and consumer trust is a strong mediator between eWOM information quantity and purchase intention. On the other hand, the regression analysis among eWOM information timeliness, consumer trust, and purchase intention also proves that the influence of eWOM information timeliness on purchase intention is realized through the mediator---consumer trust. Consumer trust displayed significant influence to purchase intention. Before the addition of the mediator---consumer trust, the influence of eWOM information timeliness on purchase intention is significant (β=0.272, p<0.001, R2=0.071). After the introduction of consumer trust, the influence of eWOM information timeliness on purchase intention is insignificant, because the consumer trust brings significant influence over purchase intention (β=0.822, p<0.001, R2=0.710). Furthermore, the model’s fitting degree has also been improved (0.710>0.071), implying that consumer trust is of good explanation of purchase intention, and consumer trust is a strong mediator between eWOM information timeliness and purchase intention. Therefore, H5 is accepted.

46

Discussion and Conclusion The results of experiment confirm our expectation that the impacts of eWOM information quantity and timeliness on customer trust and purchase intention are stronger when buying fashion product. Thus, when participants read the online evaluation messages, they could be affected by their quantity and timeliness. That is to say, the larger the quantity and the higher the timeliness, the greater the extent of consumer trust and purchase intention. Meanwhile, when the consumers make buying decision about fashion product, the influence of eWOM information quantity and timeliness on consumer trust is more significant than that of functional product. The results of experiment have supported our hypotheses.

The experiment in this research proved that under C2C environment, eWOM quantity and timeliness have significant impact on consumer purchase intention. We have testified the five hypotheses and come to conclusions as follow.

Firstly, the larger the quantity of eWOM information, the greater the extent of consumer trust.

In online environment, consumers influence each other. Therefore, the influence on purchase intention would be stronger when a lot of consumers held the same opinion. The conformity effect and the effect of sheep flock have proved this point. In C2C environment, eWOM information quantity has significant positive influence on consumer trust and consumer trust is significantly positively related to purchase intention. That is to say, the larger the quantity of eWOM information, the greater the extent of consumer trust, and the stronger the consumer purchase intention.

Secondly, the higher the timeliness of eWOM information, the greater the extent of consumer trust. Internet is the main platform to publish information. In the complex network era, C2C firms ought to manage up-to-date messages and delete out-of-date messages. In C2C environment, eWOM timeliness is significantly positively related to consumer trust and consumer trust is significantly positively related to purchase intention. That is to say, the higher the eWOM timeliness, the greater the extent of consumer trust, and the stronger the purchase intention.

This research also finds that the influence of eWOM quantity on consumer trust is bigger than that of eWOM timeliness. When browsing online evaluation messages, consumers firstly focus on quantity and then move to timeliness.

Furthermore, because of the difference in product types, the influences of eWOM quantity and timeliness on consumer trust also differ. When buying different products, consumersâ&#x20AC;&#x2122; focuses differ from each other because they tend to focus on function or timeliness in different contexts.

For example, in buying a classical textbook, online evaluation message is not that important because of low perceived risk. In contrast, online evaluation message plays an important role in buying fashionable cloth because of the uncertainties in design, material, size, and color of the cloth. The experiment results also indicates that influences of eWOM quantity and timeliness on consumer trust and purchase intention in buying fashion product are stronger than these of functional product.

The research conclusion demonstrates that in order to satisfy the consumerâ&#x20AC;&#x2122;s individual needs and boost firmâ&#x20AC;&#x2122;s performance, business firms can strengthen online evaluation message management in the following perspectives: (1) adopt point-based system among consumers who are actively involved in online evaluation activity. The exchange between points and coupons will motivate customers to play a more active part in online evaluation activities, 47

so that eWOM information quantity and timeliness could be improved. (2) set up specific online evaluation message management department. Find someone who will be responsible for managing online evaluation message and dealing with customer complaints and suggestions in time, so that customer satisfaction and retention rate could be promoted.

Contributions and Limitations Based on the former researches, this paper contributes as follow: (1) based on consumers’ “cognitive→affective→behavior” hierarchy theory of reaction, this paper built the relational model of “eWOM information → consumer trust →purchase intention” to enrich eWOM information theoretical model; (2) researches in other countries divided product type into two classifications: the searching product and the experiencing product. And found that the influence of eWOM information on consumer purchase behavior differed because of the difference in product type. While in this research, product type was divided into fashion product and functional product due to cultural difference. Furthermore, product type was introduced as moderator variable to analyze the moderating effect of eWOM information on online purchase behavior; (3) this research adopted two dimensions of eWOM information, quantity, and timeliness to analyze their influences on consumer online purchase behavior, which contributed to the related research about the influence of timeliness on consumer online purchasing behaviors.

On the other hand, we concluded the limitations of this research as follows: (1) Focusing on a group of people with abundant online shopping experience, this research didn’t confirm the applicability of this model to people without online shopping experience. (2) eWOM information involved in this research were positive messages. However, we didn’t prove the influence on consumer trust and purchase intention when there was a proportion of negative online evaluation message (for example, when negative messages account for 20%, 50% or 80% of the total).

Future research directions This research only adopted two dimensions of eWOM information---quantity and timeliness--to analyze their influences on consumer trust and purchase intentions which are based on difference in product type. However, with the development of e-commerce, online evaluation message is becoming complex and diverse, and is calling for further discussion and research.

The directions for future research are as follows: (1) This paper only focuses on analysis of first-time online evaluation message. Some web sites allow second-time evaluation, namely, the subsidiary comment. Therefore the influence of this kind of online evaluation message also calls for further research.

(2) Integrate purchase is becoming popular among online shoppers. The influence of eWOM information on integrate purchase intention needs further discussion, too. Although the operations of various integrate purchase websites seem to be similar to each other, their sales volumes differ significantly. The number of people buying through integrate purchase method could reach 10 or 1000, and what are the factors resulting in such a big difference? In order to solve the problem, we hope that additional research could be conducted to explore the influencing mechanism of online evaluation message on 48

consumers, and put forward suggestions for business firms for products sold through integrate purchase method, so that more customers will be attracted and sales volumes will be promoted.

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52

Asian Journal of Business Research

Volume 1

Number 2

2011

Determinants of Internet Buying Behavior in India Ruchi Nayyar IILM Institute of Management Education S. L Gupta Birla Institute of Technology (Deemed Univ.)

Abstract Internet penetration in India has become more widespread on account of easy payment options, reduced hardware prices, faster and cost effective internet communication, and reliable technology. Internet applications such as emailing, e-banking, e-gaming, travel and entertainment bookings have become part and parcel of the growing tech-savvy population in India. Although new business models focusing on e-retailing are providing exciting services to satisfy e-consumersâ&#x20AC;&#x2122; demands, the Indian internet retail market is far behind its expected potential. It therefore becomes imperative to assess the important determinants of internet buying behavior. There has been a very limited research to study the internet shopping behavior and factors responsible for determining online purchase intentions in India. The aim of this research is to provide a view of the various demographic and psychographic factors influencing consumerâ&#x20AC;&#x2122;s willingness to purchase online. A new model based on Technology Acceptance Model (TAM) has been developed for the purpose of this research which incorporates consumer demographic factors and Perceived risk along with other TAM variables to explain the consumer acceptance of online shopping. The findings are expected to hold value for internet retailers as these are the simplest segmenting descriptors which will guide them in generating more effective business strategies for their organizations. Overall, this study seeks to provide productive insights into the factors determining the prospects of internet retailing in the country.

Keywords: Internet retailing, Technology Adaptation Model, B2C Ecommerce, demography, Perceived risk

Introduction Internet has made a significant contribution to our lifestyles on account of its abundance and diversity of information. Its penetration is rising markedly in India which has fuelled the growth of e-commerce in the economy. The term e-commerce or electronic commerce refers to shopping on the web. It incorporates a lot of other activities such as B2B transactions, and various internal processes that companies use to support their buying, selling, hiring and planning. In terms of magnitude, e-commerce market has grown from 8147 crores in 2007 to 31598 crores by the end of year 2010 (IAMAI, 2011). Broadband connectivity and increased usage of credit cards have provided a favorable infrastructure for the growth of online shopping 53

in India. Continued liberalization in the telecom sector has shown positive effects in the past few years. The Indian Telecom policy recognized the convergence of different media and permitted direct inter-connectivity amongst various service providers. This has paved the way to internet retailing which has become one of the most innovative and challenging contributions to the retail industry. It offers consumers an additional channel for information, service and purchasing along with additional benefits of choice, convenience and cost savings. Global online retailing has gained a significant share in overall retail sales over the past two decades.

B2C E-commerce has become a lucrative platform for e-marketers to attract potential e-buyers in India. On account of its diversity in culture, language and heritage, India can offer a favorable platform for innovative e-commerce based technologies. However, in comparison to wider acceptance of B2C retail in developed economies, internet retailing is still in its nascent stages in India. Indian consumers do not seem to be overly enthusiastic about online purchasing.

Delayed shipping, non favorable return policies and complicated cancellation processes seem to be some of the key factors that abstain potential customers to shop online. Owing to their age, gender, education, occupation and cultural instincts, the consumer buying behavior in India is still traditional. Indians prefer to have a feel of the product and spend time in buying. Lack of physical touch and inspection, security and privacy concerns are plaguing the growth of this market. Customers rely on purchasing familiar brands in order to reduce the risks associated with their purchase. Privacy concerns have dampened the online consumer enthusiasm in India.

There are a number of issues related to security and transaction frauds. High occurrences of failed payments deter the customer to revisit portals for shopping. With regard to the future of etailing in India, the views are divergent. Many experts believe that the future of internet business is very promising and expect its exponential growth in the coming times. Overall, Indian etail business is a rich business waiting to be exploited! It has become imperative for online retailers to understand the attitudes and preferences of the internet consumers and devise appropriate business strategies to gain competitive advantage. This study aims at improving the understanding of online consumer behavior by investigating various factors affecting intention to purchase online.

Literature Review The Technology Adoption Model (TAM), on account of its robustness, parsimony and explanatory powers, is believed to be the most effective model for understanding the adoption of technology. (Davis, Bagozzi, and Warshaw, 1989; Venkatesh and Davis, 2000; Venkatesh et al., 2003). TAM has been exceedingly successful in explaining technology adoption behavior and has been utilized by many researchers to understand consumersâ&#x20AC;&#x2122; online purchase behavior as well. However, investigations to understand the Indian consumer online behavior are still minimal. Therefore, this study aims to develop and test a modified TAM that is appropriate for the Indian context.

Technology Acceptance Model: A Theoretical Basis TAM provides an explanation of the determinants of computer acceptance that is general, capable of explaining user behavior across a broad range of end-user computing technologies and user populations (Davis et. al., 1989). TAM is based on the Theory of Reasoned Action (Fishbein and Ajzen, 1975) which suggests that attitude and intention drive an individualâ&#x20AC;&#x2122;s 54

social behavior. This means that within available time and context, individualsâ&#x20AC;&#x2122; behavior vary with respect to their intentions. TAM posits that the two primary antecedent variables determining attitude to adopt an information system include perceived usefulness and perceived ease of use. TAM specifies the causal relationships between system design features, perceived usefulness, perceived ease of use, attitude toward using, and actual usage behavior. In general, TAM provides an informative depiction of the mechanisms by which design choices influence user acceptance. It therefore helps in forecasting and evaluating user acceptance of technology related products and services. A number of researchers have used the constructs of perceived usefulness, perceived ease-of-use, and subjective norm to explain technology usage/acceptance for a variety of information systems such as online purchasing. The following TAM model depicts the conceptual model of this study.

Figure 1: Technology Acceptance Model (TAM)

Perceived usefulness refers to the degree to which a person believes that using the new technology will improve his or her performance or productivity (Davis, Bagozzi and Warshaw, 1989 and 1985).

Perceived ease of use on the other hand, indicates how the users perceive the ease of using the technology. It is defined as the degree to which a person believes that using a particular system would be free from effort (Davis, Bagozzi and Warshaw, 1989).

Behavioral Intention is defined as the degree to which a person has formulated conscious plans to perform or not perform some specific future behavior (Davis and Warshaw, 1985). It forms a strong predictor of actual system use. TAM posits that Behavioral Intention is a strong determinant of system use and is determined by Perceived Usefulness and Perceived Ease of Use. Based on TAM, following hypotheses have been formulated.

55

H1: Perceived usefulness is related to Behavioral Intention in an online shopping environment.

H2: Perceived ease of use is related to Behavioral Intention in an online shopping environment.

TAM also posits that perceived ease of use and perceived usefulness are closely linked. If applied to the context of internet shopping, if an internet user perceives internet purchase as hassle free, he/she will develop a tendency to perceive it as useful. Thus, H3: Perceived ease of use is related to Perceived Usefulness in an online shopping environment.

Online Shopping Orientation One of the setbacks of TAM is that it treats online purchasing at the outset of the technology. On account of its emphasis only on the cognitive determinants of IT use intention; TAM cannot be applied to the adoption of internet technology for purchase purpose. This research argues that Perceived risk and demography are critical factors forming the potential e-shopper’s intention on the shopping orientation of an e-shopper.

Perceived risk is defined as a functional or psychosocial risk a consumer feels he or she is taking when purchasing a product. Bauer (1960) has defined perceived risk as a combination of uncertainty plus seriousness of outcome involved. Peter & Ryan (1976) have defined perceived risk as the expectation of losses associated with purchase and acts as an inhibitor to purchase behavior. It’s observed that the perceived risk in e-commerce is greater than that of commerce at brick-and-mortar retail stores. Credit card security, lack of touch and feel, concerns related to return the item, and transaction security have prevented consumers against purchasing online (Bellman et al, 1999). Thus, the likelihood of purchasing on the Internet decreases with increase in consumers’ perceptions of risk. Perceived risk is extremely important to understand the online shopping behavior because it impacts other consumer perceptions including perceived ease of use and perceived usefulness (Lee et al., 2001). In an ecommerce environment, the combination of uncertainty (likelihood of loss) and danger (cost of the loss) which form the two components of the perceived risk have a negative influence on perceived ease of use and adoption (Chen et al, 2006).Therefore higher the perceived risk, the lower the perceived value of the system . Many previous researches have pointed out that ease of use reduces the uncertainty and risk of system use (Fetherman and Pavlou, 2003). This indicates that if a consumer perceives that internet services are easy to use then he would also perceive that other services related to the internet will perform well and he would be more willing to adopt them. Thus, H4: Perceived ease of use of Internet purchase has a negative influence on internet shoppers’ Perceived purchase risk.

Individual Differences Demography (age, gender, profession, education etc) affect how technology is used (Zmud, 1989; Assael, 1981). Hence, it’s important to study the impact of demographic variables on online shopping. The socio-economic status of early adopters is higher than late adopters (Rogers, 1995). Men and women also differ in their attitudes toward e-shopping. Traditional Indian women regard shopping as a social release. In most of the families, women are the chief decision makers (Dholakia, 1999). Men are more motivated toward utilitarian benefits of products and give lesser importance to social relations and personal contacts (Steenkamp et al., 56

1999). Many women perceive shopping as an entertainment channel to socialize and interact with other consumers. Hence, they get more satisfied purchasing from brick establishments rather than from online stores. Men lay more emphasis on hassle free purchases in the comfort of their homes or workplaces and mind less on the hedonistic benefits of store shopping. Hence their overall positive attitude towards internet shopping is higher compared to the fairer sex (Teo, 2001). Unlike women, men are less motivated by inspirational and stimulating effects of brick and mortar purchases. Thus, H5: Gender affects intention to purchase online.

Needs, interests and resources vary with age. In contrast to a tech-savvy younger generation, the older generation is more satisfied with conventional shopping methods (May and Greyser, 1989). There is less time constraint for the older community, thus tend to socialize more through traditional shopping medium. Younger generation has always exhibited a positive disposition towards adoption of a new innovation (Schiffman and Kanuk, 2003). Younger people are more ready to embrace innovative technology compared to the older group. The early adopters of internet technology are typically younger in age primarily on account of its utilitarian and hedonistic benefits (Bordeaux et al., 2002).It is also found that the younger generation is less concerned about the security and reliability aspects of internet technology ( Fogg et al., 2000).

Computers intimidate many elderly (Eastman and Iyer, 2004) leading to reduced internet activities amongst older population. Thus, H6: Age affects intentions to purchase online.

Educated and higher income group patronize internet retailing more than lower educated and lesser income group (Cunningham and Cunningham, 1973). Educated people make good innovators and early adopters of new technology (Teo, 2001; Zhao et al., 2002; Dillon and Reif, 2004). Less educated people tend to exhibit a higher degree of computer anxiety towards computer technology (Parasuram and Igbaria, 1989). Hence, their negativity towards electronic retailing as a direct form of retailing is inevitable. Thus, H7: Education affects intention to purchase online.

A large income encourages people to conduct more internet shopping (Fogg et al., 2001).

People at higher positions in their organizations embrace new and innovative technology faster compared to those at lower positions in their organizations. Higher the educational level, income, and occupation, higher would be the perception of internet retailing (Cunningham and Cunningham, 1973; Reynolds, 1974; Wotruba and Pribova, 1995). Many earlier researches have revealed that most of the internet shoppers are men, earning high incomes and owning a university education (Dholakia and Usitalo, 2002; Li et al., 1999; Vrechopoulos et al., 2001).

Thus, H8: Income affects intention to purchase online.

H9: Position in the organization affects intention to purchase online.

Research Framework

57

The following figure illustrates the modified TAM developed for this study to understand the determinants of internet buying behavior in the Indian context. As mentioned above, the attitude construct is removed from this research model while perceived risk and demography have been included.

Figure 2: Research Model DEMOGRAPHY

PERCEIVED USEFULNESS

H5, H6, H7, H8, H9

H2 INTERNET RETAILING INTENTION

H3 PERCEIVED EASE OF USE

H1

H4 PERCEIVED RISK

Research Methodology This study involves non-probabilistic convenience sampling. 500 customers were selected throughout the urban and semi urbanized locations of India. Questionnaires were distributed both manually and electronically through web. Quantitative data was collected from a selfadministered questionnaire. Utmost care was undertaken to ensure that there is insignificant sampling error and the results of the sample study can be applied, in general, for the universe with a reasonable level of confidence. The study used a variety of questions to find out complete information about the topic under research. Apart from dichotomous and multiple-choice questions, the questionnaire also included statements which the respondents were required to rate on the basis of different scales like the Likert scale and rating scale. The research instrument constituted a 5-section questionnaire that was modified from various resources in order to gather information related to demographics, perceived usefulness, perceived ease of use, perceived risk and behavioral intention to purchase online. Samples of measures and variables are shown below:

58

Table I: Questionnaire preparation Section Perceived Usefulness

Sample Questions I like internet shopping as it offers me round the clock shopping I like browsing online to preview products before purchasing Perceived Ease of I feel internet shopping is a fun filled experience Use I feel better quality products are offered on the internet I feel better quality products are offered on the internet Perceived Risk I find public knowledge of my purchases risky I feel internet retailers are not trustworthy

Source Adapted based Davis (1989)

Adapted based Davis (1989)

on

on

Baur (1960), Bellman et al. (1989), Chen et al. (2006) B e h a v i o r a l I feel shopping in the local markets is too time Adapted based on Intention consuming and problematic Ajzen and Fishbein I find internet shopping quite easy (1980), Davis and Warshaw (1985)

Pre-testing of the research instrument was carried out on a sample of 40 Management students from a reputed Indian Management Institute. Descriptive and frequency testing was employed on the quantitative data. Moreover, Factor analysis technique was deployed for identifying the structure of a set of variables and for data reduction (Hair et al., 1998).

Data Analysis and Results Most of the respondents are males (66%). The highest percentage of the respondents is salaried (65.9%), with 48.9% falling in the salary bracket of Rs. 2 to 4 lakhs per annum. The given sample comprises of internet users aged 15 and more. A larger percentage of the sample (79%) belongs to the age group of 22-29 years. While the least representative group of respondents is of age group of 40-49 years and above, there is no respondent aged 60 or above. This could be on account of lack of use and familiarity of computer technology. Finally 73% are postgraduates and 42% are graduates. Respondents were asked to pick up their recent online purchase. 74% have utilized internet to book tickets. Travel related purchases have totally dominated web shopping in the country. 55% respondents believe convenience as the reason influencing online purchase. Besides, privacy and security related issues are the chief stumbling blocks while making internet purchases.

R-type factor analysis is deployed to understand the structure of the psychographic variables.

Metric variables chosen for the purpose of this research constituting a homogenous set of perceptions are found to be most suitable for conducting factor analysis. The output of factor analysis indicates that the first three components are explaining 66.2% of the total variance.

Reliability of the multi-item scale for each dimension was measured using Cronbach alphas.

The measure of reliability for 20 number items on a sample size of 500 was observed to be 0.5986 which is above the recommended minimum standard of social science based researches.

The italicised variables are related negatively to the dependent variable. Hence, these variables 59

can be clubbed into group â&#x20AC;&#x2DC;Perceived riskâ&#x20AC;&#x2122;. Although, Factor Analysis does not generate a new factor for Perceived risk, the values support H4; Perceived ease of use of Internet purchase has a negative influence on internet shopperâ&#x20AC;&#x2122;s perceived Purchase risk.

Table II: Results of Factor Analysis Factor

Loading

Factor 1: Perceived Usefulness

Reliability 0.63

I like internet shopping as it offers me round the clock shopping

0.61

I like browsing online to preview products before purchasing

0.59

I think internet shopping offers better choices than local store

0.45

I think browsing on the internet saves a lot of my window shopping time

0.78

Factor 2 : Perceived Ease of Use

0.75

I find internet shopping is a new experience

0.43

I find internet shopping is a fun filled experience

0.58

I feel better quality products are offered on the internet

0.53

I get scared by identity thefts through credit cards while purchasing online

-0.84

I find public knowledge of my purchases risky

-0.72

I feel easy accessibility on computers threatens my credit card details

-0.86

I feel scared to buy things on internet

-0.8

I feel internet retailers are not trustworthy

-0.76

I like home delivery of products on online purchase

0.88

I like online shopping to avoid problems at local shopping centers

0.82

I prefer online shopping to avoid driving and parking hassles.

0.83

I like shopping online in the comfort of my home and surroundings

0.85

I like discounts and incentives schemes on the internet

0.83

Factor 3: Behavioral Intention

0.47

I feel shopping in the local market is too time consuming and problematic

-0.41

I find internet shopping quite easy

-0.38

I like going through product reviews and recommendations by other browsers

0.58

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Regression Analysis The concern of our model is whether the variables have an influence as hypothesized. To serve this purpose, three multiple regression analysis (MRS) were conducted. The first is used to analyze the relationship between PU and BI, the second between PEU and PU and the third between PEU and PU. Figure 3: Revised Model

DEMOGRAPHY

PERCEIVED USEFULNESS (PU)

R2=0.32

INTERNET RETAILING INTENTION (BI)

R2=0.44 PERCEIVED EASE OF USE (PEU)

R2=0.31

R2 values indicate presence of a strong relationship between PU and PEU. Therefore, H3 is supported. Between PU and BI, the relationship as indicated by the regression coefficients does not seem to be good. However, it appears that the hypothesis H2 is pointing in the right direction. Similarly, although the relationship between PEU and BI does not seem to be strong, but since the hypothesis is pointing in the right direction, H1 is accepted.

Impact of Demography on Behavioral Intention In order to study the impact of demography on Behavioral Intention, the interval data constituting BI was first modified into nominal data incorporating only 2 options – intended to shop online and not intended to shop online. Thereafter, Chi- square test was used to identify whether given two discrete variables are in a relationship or are independent. Results indicate that gender (χ2=29.642, p=0.000), age (χ2=18.387, p= 0.000), income (χ2=34.491, p=0.000) and position in the organization (χ2= 53.11, p=0.000) affect intention to purchase online positively, whereas education (χ2=4.626, p=0.099) is found to have no impact on internet purchase intention.

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Table III: Summary of results Hypothesis

Accepted/ Rejected Accepted Accepted Rejected Accepted Accepted Accepted Rejected Accepted Accepted

H1 H2 H3 H4 H5 H6 H7 H8 H9

Conclusions The results have displayed significant relationships between research variables. Perceived ease of use has a negative influence on perceived risk. Perceived ease of use is positively associated to perceived usefulness. The outcome of this research suggests that perceived ease of use and perceived usefulness are antecedents of intention to purchase online. However, results do not indicate a strong relationship between PEU-BI and PU-BI. This clearly shows that Indians are somewhat reluctant to transacting online. Indians look at shopping as an entertainment activity and consider visiting malls and brick and mortar outlets as an escape from their day-to-day routine. Other factors holding them back from online shopping include fear of identity and financial theft, product genuineness, lack of touch and feel, delivery time and fixed price format.

Itâ&#x20AC;&#x2122;s imperative for online vendors to understand the factors that may influence the formation of consumerâ&#x20AC;&#x2122;s behavioral intention toward online shopping. Increasing online brand presence may prove to be an effective solution. Most of the leading brands are either not present online or are present in a very non-friendly manner. Internet retailers can also increase their clientele by providing significant discounts across products. Attractive discounts by brands can act as a magnet in motivating consumers to buy online. Extensive market researches could enable online vendors to identify preferences of their major customer groups and adjust their website contexts accordingly. Latest technology can enable creation of attractive catalogues for offers and promotions. Easy going navigational features amalgamated with multiple payment options and running innovative customer reach programs could act as mascots for online retailers.

Frequently personalized information and exclusively personalized website could diminish perceived risk to a large extent.

The findings of this study have revealed a higher number of male internet shoppers than females.

The results are in consistence with the literature review. Men adopt computer technology much faster than females. In comparison to females, males are more prone to participate in internet activities predominantly emailing, information search or downloading and purchasing activities.

Females exhibit a higher degree of computer nervousness and technostress than males. Age has also been found to have an influence on internet retailing adoption. Internet usage has not diffused uniformly amongst all age groups, hence the difference in attitude towards online 62

purchase. Surprisingly, education has not shown any significant association to internet retailing.

It should be noted, however, in the present study that respondents are sufficiently educated, falling in the category of graduates and above. They constitute the PC literate population with higher exposure and awareness of internet. Another plausible justification could be that internet; with its high degree of user friendliness makes differences in educational levels insignificant.

Although, this population makes versatile use of various online applications such as emailing, messaging, online gaming, information research etc., but not internet retailing. This clearly indicates that online retailing is not the most appealing and convenient means of shopping amongst internet users in India. Annual household income affects internet retailing adoption.

Higher income motivates more purchasing. Similar justification holds good for the positive association obtained between position in the organization and internet retailing adoption. Higher position in an organization indicates more awareness of modern technology and opportunities that increases higher online retailing prospects.

Limitations of the research and Suggestions for future research Despite meeting the objective of the present research, a few limitations were identified in the course of this study. This research investigates the impact on internet retailing by various factors in Indian retail industry. Thus, the outcomes of this research are best suited to Indian e-commerce retail industry. These findings cannot be replicated to other nations owing to differences in terms of economy, culture and technology.

Though the sample size selected for this research is acceptable, a bigger sample size could have assessed behavioral and attitudinal perceptions in greater depth. Besides all respondents were internet savvy and sufficiently educated. Future research might examine the diverse internet users such as older, less internet savvy and less educated. Finally, this research is only confined to online shopping in India. Further research can be expanded to other shopping channels including phone shopping, catalog shopping or TV shopping.

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Asian Journal of Business Research

Volume 1

Number 2

2011

Online Shopper Behavior: Influences of Online Shopping Decision Chayapa Katawetawaraks SCG Trading Services Co. Ltd Cheng Lu Wang University of New Haven

Abstract Recent research has shown an interest in investigating consumer motivations that affect the online shopping behavior. It is yet to understand what factors influence online shopping decision process. The objective of this study is to provide an overview of online shopping decision process by comparing the offline and online decision making and identifying the factors that motivate online customers to decide or not to decide to buy online. It is found that marketing communication process differs between offline and online consumer decision. Managerial implications are developed for online stores to improve their website.

Keywords: Online shopping, online shopper behavior, online shopping decision

Introduction The internet has played a significant role in our daily life in that people can talk through the internet to one who is actually on the other side of the Earth, can send email around the clock, can search information, can play game with others, and even can buy things online. Meanwhile, Internet shopping has been widely accepted as a way of purchasing products and services It has become a more popular means in the Internet world ((Bourlakis et al., 2008)). It also provides consumer more information and choices to compare product and price, more choice, convenience, easier to find anything online ((Butler and Peppard, 1998)). Online shopping has been shown to provide more satisfaction to modern consumers seeking convenience and speed ((Yu and Wu, 2007)). On the other hand, some consumers still feel uncomfortable to buy online. Lack of trust, for instance, seems to be the major reason that impedes consumers to buy online. Also, consumers may have a need to exam and feel the products and to meet friends and get some more comments about the products before purchasing. Such factors may have negative influence on consumer decision to shop online.

This study first provides a theoretical and conceptual background that illustrates the differences between offline and online consumer behavior process. Then we identify some basic factors that drive consumers to decide to buy or not to buy through online channel. Finally, we draw managerial implications of how online sellers can use this knowledge to improve their online stores to be more attractive and get more online shoppers.

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Theoretical Background Offline and Online Consumer Decision-making Process The process of making decision are very similar whether the consumer is offline or online.

But one some major differences are shopping environment and marketing communication.

According to traditional consumer decision model, Consumer purchase decision typically starts with need awareness, then information search, alternative evaluations, deciding to purchase and finally, post-purchasing behavior.

In terms of online communication, when customers see banner ads or online promotion, these advertisements may attract customers’ attention and stimulate their interesting particular products. Before they decide to purchase, they will need additional information to help them out. If they do not have enough information, they will search through online channels, e.g., online catalogs, websites, or search engines ((Laudon and Traver, 2009)). When customers have enough information, they will need to compare those choices of products or services. In the search stage, they might look for the product reviews or customer comments. They will find out which brand or company offers them the best fit to their expectation. During this stage, well-organized web site structure and the attractive design are important things to persuade consumers to be interested in buying product and service ((Koo et al., 2008)). Moreover, the information sources’ nature may influence buyer behavior ((Bigné-Alcañiz et al., 2008)). The most useful characteristic of internet is that it supports the pre-purchase stage ((Maignan and Lukas, 1997)) as it helps customers compare different options ((Dickson, 2000)). During the purchasing stage, product assortment, sale services and information quality seem to be the most important point to help consumers decide what product they should select, or what seller they should buy from ((Koo et al., 2008)). Post-purchase behavior will become more important after their online purchase. Consumers sometimes have a problem or concern about the product, or they might want to change or return the product that they have bought. Thus, return and exchange services become more important at this stage (Liang and Lai, 2002).

All five stages described above are affected by external factors of risks and trusts (Comegys et al., 2009). The search process is a significant component of customer’s online shopping behavior (Seock and Norton, 2007). The source risk comes in the stage of information search and evaluation because the information in the web sites might contain some mistakes. Some websites require customers to register before searching their website. As such, in addition to product risk, consumers also face the risk of information security (Comegys et al., 2009; Wang et al., 2005). Because of the nature of online purchasing, customers take the risk as they are not able to examine the product before purchasing. They also take the risk in the payment process because they may need to provide personal information including their credit card number.

Security problem does not stop at the purchase stage but continues to the post-purchase stage because their personal information might be misused.

A Framework of Online Consumer Decision A framework that compares online consumer decision with offline decision making was developed by Laudon and Traver (2009), who suggest that a general consumer behavior framework requires some modification to take into account new factors.

When consumers want to buy product, they will look at the brand and the characteristics of 67

product or service. Some products can be purchased and shipped easily online such as, software, books. On the other hand, some products are hard to decide through online channel. Web site features, firm capabilities, marketing communication stimuli, and consumer skills are also important, in terms of the proposed framework (Laudon and Traver, 2009). When consumers want to buy product, they will look at the brand and the characteristics of product or service.

Some products can be purchased and shipped easily online such as, software, books. On the other hand, some products are hard to decide through online channel. Web Site feature is one of the important things that can influence consumers to buy product online. For example, online retailers can use high technology to improve their websites in order to influence consumer perceptions of the web environment (Prasad and Aryasri, 2009). If the web site is too slow, not navigability, or not safe enough, will have negatively impact consumer willingness to try or buy products from the website. Consumer experience with online shopping (Broekhuizen and Huizingh, 2009) or consumer skills, which refer to the knowledge that consumers have about product, and how online shopping works (Laudon and Traver, 2009) also influences online shopping behaviors. Clickstream behavior is another aspect that becomes more important in the online world. It refers to the behavior that consumers search for information through web sites many sites in the same time, then to a single site, then to a single page, and finally to a decision to purchase (Laudon and Traver, 2009). All these factors lead to specific attitudes and behaviors about online purchasing and a sense that they can control their purchasing environment thru the online world.

Influences of Online Shopping Decision Motivations that lead consumer to buy online There are many reasons why people shop online. For examples, consumers can buy anything at anytime without going to the store; they can find the same product at a lower price by comparing different websites at the same time; they sometime want to avoid pressure when having a face-to-face interaction with salespeople; they can avoid in store traffic jam, etc.

These factors can be summarized into four categoriesâ&#x20AC;&#x201D;convenience, information, available products and services, and cost and time efficiency.

Convenience: Empirical research shows that convenient of the internet is one of the impacts on consumersâ&#x20AC;&#x2122; willingness to buy online (Wang et al., 2005). Online shopping is available for customers around the clock comparing to traditional store as it is open 24 hours a day, 7 days a week (Hofacker, 2001; Wang et al., 2005). Research shows that 58 percent chose to shop online because they could shop after-hours, when the traditional stores are closed and 61 percent of the respondents selected to shop online because they want to avoid crowds and wailing lines, especially in holiday shopping (The Tech Faq, 2008). . Consumers not only look for products, but also for online services. Some companies have online customer services available 24 hours.

Therefore, even after business hours, customers can ask questions, get necessary support or assistance, which has provided convenience to consumers (Hermes, 2000).

Some customers use online channels just to escape from face-to-face interaction with salesperson because they pressure or uncomfortable when dealing with salespeople and do not want to be manipulated and controlled in the marketplace (Goldsmith and Flynn, 2005; Parks, 2008).

This is especially true for those customers who may have had negative experience with the salesperson, or they just want to be free and make decision by themselves without salespersonsâ&#x20AC;&#x2122; presence.

68

Information: The internet has made the data accessing easier (Wang et al., 2005). Given customers rarely have a chance to touch and feel product and service online before they make decision, online sellers normally provide more product information that customers can use when making a purchase (Lim and Dubinsky, 2004). Customers put the weight on the information that meets their information needs (Keency’s, 1999). In addition to get information from its website, consumers can also benefit from products’ reviews by other customers. They can read those reviews before they make a decision.

Available products and services: E-commerce has made a transaction easier than it was and online stores offer consumers benefits by providing more variety of products and services that they can choose from (Lim and Dubinsky, 2004; Prasad and Aryasri, 2009). Consumers can find all kinds of products which might be available only online from all over the world. Most companies have their own websites to offer products or services online, no matter whether they already have their front store or not. . Many traditional retailers sells certain products only available online to reduce their retailing costs or to offer customers with more choices of sizes, colors, or features. Boccia Titanium, for instance, has stores in many states but not in Connecticut. The company offers website to reach and to fulfill the need of Connecticut customers to order online. . Similarly, Yves Rocher, a French company, does not have the front store in the U.S. It offers the website so that U.S. customers can just add products they want into the online shopping cart and the product will be shipped to their house. Moreover, online shopping sometimes offer good payment plans (Amin, 2009) and options for customers.

Customers can decide their payment date and amount (Anonymous, 2009) in their own preference and convenience.

Cost and time efficiency: Because online shopping customers are often offered a better deal, they can get the same product as they buy at store at a lower price (Rox, 2007). Since online stores offer customers with variety of products and services. it gives customers more chances to compare price from different websites and find the products with lower prices than buying from local retailing stores (Lim and Dubinsky, 2004). Some websites, Ebay for example, offer customers auction or best offer option, so they can make a good deal for their product. It also makes shopping a real game of chance and treasure hunt and makes shopping a fun and entertainment (Prasad and Aryasri, 2009). Again, since online shopping can be anywhere and anytime, it make consumers’ life easier because they do not have to stuck in the traffic, look for parking spot, wait in checkout lines or be in crowd in store (Childers et al., 2001). As such, customers often find shop from the website that is offering convenience can reduce their psychological costs (Prasad and Aryasri, 2009).

Factors that Impede Consumers from online Shopping Major reason that impede consumers from online shopping include unsecured payment, slow shipping, unwanted product, spam or virus, bothersome emails and technology problem.

Business should be aware of such major problems which lead to dissatisfaction in online shopping.

Security: Since the payment modes in online shopping are most likely made with credit card, so customers sometime pay attention to seller’s information in order to protect themselves (Lim and Dubinsky, 2004). Customers tend to buy product and service from the seller who they trust, or brand that they are familiar with (Chen and He, 2003). Online trust is one of the most critical 69

issues that affect the success or failure of online retailers (Prasad and Aryasri, 2009). Security seems to be a big concern that prevent customers from shopping online (Laudon and Traver, 2009). because they worried that the online store will cheat them or misuse their personal information, especially their credit card (Comegys et al., 2009). For instance, report indicated that 70 percent of US web users are seriously worried about their personal information, transaction security, and misuse of private consumer data (Federal Trade Commission, 2001).

Intangibility of online product: Some products are less likely to be purchased online because of the intangible nature of the online products. . For example, customers are less likely to buy clothes through online channel (Goldsmith and Flynn, 2005) because they have no chance to try or examine actual product (Comegys et al., 2009). Customers viewing a product on computer screen can show a different effect than actually seeing it in the store (Federal Trade Commission, 2003). In sum, customers cannot see, hear, feel, touch, smell, or try the product that they want when using online channel. In many cases, customers prefer to examine the product first and then decide whether or not they want to buy (Junhong, 2009). Some people think the product information provided in website is not enough to make a decision. Online shoppers will be disappointed if the product information does not meet their expectation (Liu and Guo, 2008).

Social contact: While some customers likely to be free from salesperson pressure, many online shopping would feel difficult to make a choice and thus get frustrated if there is no experienced salespersonâ&#x20AC;&#x2122;s professional assistance (Prasad and Aryasri, 2009). Moreover, some customers are highly socially connected and rely on other peoplesâ&#x20AC;&#x2122; opinions when making purchase decision tend. There are also consumers who sometimes shop at traditional store because they want to fulfill their entertainment and social needs which are limited by online stores (Prasad and Aryasri, 2009).

Dissatisfaction with online shopping: customersâ&#x20AC;&#x2122; past online shopping experience often affect their future purchase decision. In online shopping, for example, they may get unwanted product or low quality products, product does match what is described or expected (Comegys et al., 2009).. The product may be fragile, wrong, or not working. Some online sellers may not agree to refund those products even though it is not what the customer wanted. Delivery is another thing that affects online purchasing decision. Slow or late shipping, for instance, makes customer walk away from online shopping (Comegys et al., 2009).

Implications Managerial Implications Online shopping is an important business model in e-commerce (Liu and Guo, 2008). If the online sellers want to persuade and retain online buyer, they need to know what the issues online buyers use to decide their online purchase (Lim and Dubinsky, 2004). To better understand online customer shopping behavior, seller can improve or create the effective marketing program for their customer (Lim and Dubinsky, 2004). There are couple ways that company or seller can do or should do to persuade those who do not shop online to become more interested, and, finally, to be a potential customer.

After looking at major motivations that lead customers to shop online, online sellers should keep those issues in mind and try to satisfy customer whenever possible. Also, understanding 70

what make some customers hesitate to shop online, sellers should find ways to reduce those negative aspects in order to gain more customers by building trustable and securer website, attractive and useful website, offering online service, and offering additional option.

Trustable and Securer website: Consumer willingness to buy and patronize online store are affected by consumer’s trust in giving personal information and security for payment through credit card transactions (Whysall, 2000). They also concern about transaction security and data safety when purchase online (Constantinides, 2004). Getting approved certificate from an organization such as eTrust is one of the ways to make a website more trustable (Korgaonkar and Karson, 2007). By doing so, a website will be more secure and it will increase customer confidence and lead to sale increase. For example, Scribendi, English language editing and proofreading services, bought SSL Certificate from VeriSign—the most trusted mark on the internet; by then site visitors who saw the green address bar made the sale leapt by 27% (Verisign, 2009). When the companies have this certificate, the address bar of their website will change to green color and the Web address will begin with https://; so customers know that the website is secure and trustable (Verisign, 2009).

Another way seller can do to reduce customers’ risk concern when purchasing online is to carry brand name product in the website or even have its own brand name such as Amazon (Korgaonkar and Karson, 2007). Holding and selling brand name product can improve the trust of the website. Brand name is one of the most important issues which affect customer’s buying decision (Lim and Dubinsky, 2004).

It is imperative for online companies to ensure customer that they will never use customers’ information to other purposes by clarifying customer privacy policy. This will at least ease consumer concern about their identify security. Online stores may use integrated mechanism in order to build the trust in safeguarding consumer’s personal information and avoidance of misuse of credit card mode of payments (Prasad and Aryasri, 2009).

User Friendly Website: Customers can be influenced by the image of the web site when they decide what website or buyer they should buy from (Lim and Dubinsky, 2004). Not only should companies create their secured website, but also should create it to be more attractive and more useful. Online stores can change a shopper into a buyer if the stores provide variety and useful information of product, good customer service, and easy-to-access website (Laudon and Traver, 2009). Their websites should have enough information but should not be too overwhelming.

Putting unstructured or useless information in the website can reduce internet usefulness and ease of use (Bigné-Alcañiz et al., 2008). Also, companies and sellers should double-check any single words in their website to reduce mistakes and customers’ misunderstanding. Information quality and visual design is important effect on repurchasing (Koo et al., 2008). The willingness to purchase online will be low if the online store lacks of ease in searching and comparing shopping, and product updates. Online store should make their website to be easy for consumers to search product and service. Making web designs and portals novel and sophisticated and web atmospherics friendly is a key to attract visitors. Moreover, if online stores want to convert visitor into buyer, they should improve their website by offering customer a comfortable, logical, interesting and hassle-free process and easy language by creating fast website with functional design as smooth as possible (Broekhuizen and Huizingh, 2009). Online payment process is another issue that should be taken care of because it affects the willingness to pay (Wang et al., 2005). Online stores should make their payment process to be as easy and secure 71

as possible. To sum, if online stores want to increase the customer, they should take care of their website design to be more user-friendly (Bigné-Alcañiz et al., 2008).

Online Service: Customer service is as important as quality of website (Liu and Guo, 2008).

According to Hermes (2000), 72 percent of online consumers revealed that customer service is a major factor in online shopping satisfaction. If the customer service is not available or reachable, customers will perceive that companies are trying to hide something or not intending to solve their problems. Online stores should provide the added-value of service to customers (Wang et al., 2005) and have customer feedback channel in their website (Yu and Wu, 2007).

There should be interactivity customer service in the website, so that customers can contact with the seller anywhere and anytime (Lim and Dubinsky, 2004). Software downloading, e-form inquiry, order status tracking, customer comment, and feedback are some of example that online sellers can use to fulfill their online service (Lim and Dubinsky, 2004).

Additional option: Because customers are not able to touch or try products before they buy, online store should offer them some additional options.. For instance, a money-back guarantee is one of the means to reduce customers’ concern (Comegys., 2009). Sellers might consider to offer money-back guarantee policy including shipping expenses refund to reduce purchasing risk In addition, to avoid shipping delay and product lost, , online store may cooperate with other companies with expertise in logistic to improve their distribution channels (Yu and Wu, 2007).

Offering customers more flexible prices and promotions or offering a one-stop shopping service are some more examples that online stores can use to make their business succeed (Yu and Wu, 2007). Online sellers may offer customers to use their bank account number, or stored-value card to complete their purchase. It is also suggested that online stores may offer customer an e-wallet which transfers balance from customer’s online bank account to the store payment system (Federal Trade Commission, 2003). This may help sellers to gain more sales from those who want to buy online products or services but do not have credit card or do not want to use their credit card online.

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Asian Journal of Business Research

Volume 1

Number 2

2011

Assessing Customer Satisfaction with Non-Profit Organizations: Evidence from Higher Education Lily Huang City University of Hong Kong Zhilin Yang Victoria University of Wellington Gerald Hampton New Mexico State University

Abstract This study empirically examines several key issues concerned with assessing customer satisfaction in the context of higher education. Data were obtained from 1475 students, with various characteristics, who were enrolled at four large universities. The results indicate that dissatisfied and satisfied students are significantly different when assessed in terms of five education service attributes. The performance model is found to be capable of explaining customer satisfaction more powerfully than either the disconfirmation or the multi-attribute model. In addition, some student characteristics are considered to be crucially important in their effects on expectation and performance of education service attributes, which, in turn, exert influence on assessment of customer satisfaction.

Keywords: Customer Satisfaction, Student Satisfaction, Performance Model, High Education

Introduction For the past three decades, increasing numbers of universities have perceived that students are important customers, and have utilized marketing thinking and practice to attract, satisfy, and retain students (Conant, Brown, and Mokwa, 1984; Ferguson, Wisner, and Discenza, 1986; Hampton, 1993; Douglas, McClelland, and John Davies, 2008; Gruber,et al, 2010).

Many administrators at post-secondary schools have realized that customer satisfaction is an indispensable means of creating a sustainable advantage in the competitive environment of higher education (Douglas, McClelland, and John Davies, 2008). The study of satisfaction, especially in the service industry, as Patterson et al (1996) have observed, is an important, yet underdeveloped area. The need to measure customer satisfaction is a corollary to effectively implementing the marketing concept. In the specific context of higher education, there have been some recent studies which have strived to assess satisfaction from customer perspectives (e.g. Hampton 1993; Douglas, McClelland, and John Davies, 2008; Gruber,et al, 2010). Due to 75

the complicated nature of higher education service, assessing student satisfaction with higher education still remains a huge challenge. The two essential issues are: (1) what attributes of student satisfaction should be assessed; and (2) how it can be assessed.

In this paper an attempt has been made to examine several issues involved in effectively assessing student satisfaction with higher education, employing cross-university surveys. For this purpose, the study will first examine the attributes of education service and the differences of education service attributes between satisfied and dissatisfied students. Then, it will evaluate whether most often used models or approaches can explain student satisfaction with higher education, and which one is the most powerful tool. Finally, it will examine whether student characteristics have significant effects on the performance of education service attributes, given that they are moderator variables.

This study has made several contributions to customer satisfaction knowledge: (1) it offers cross-sectional study of student satisfaction with higher education.; (2) it aims to identify service attributes based on marketing mix; (3) it examines some models of satisfactions including multi-attribute attitude theory, disconfirmation theory and gap analysis in the context of the higher education area; (4) it incorporates student variables as moderators through examination of effects on student expectations and perceived performance of service attributes.

Theory and Hypotheses Development Multi-Attribute Services and Satisfaction Satisfaction is defined as an effective state that is the emotional reaction to a service experience (Olive, 1980, Cadotte, Woodruff, and Jenkins 1987, Yang and Fang 2004). Service is inherently variable and lacks consistency because of its intangibility and the complicated needs and desires of customers. To overcome this weakness, multi-attribute attitude models, which are used to correctly identify the underlying dimensions with which a customer evaluates perceived service performance and expectations, was suggested in the context of customer satisfaction (Yang and Peterson 2004). This model has some advantages in the service area, both theoretical and managerial. First, customers are more likely to render evaluations of their service experiences of satisfaction at an attribute level, rather than at the product level (Gardial et al. 1994). Second, an attribute-based approach enables researchers to conceptualize commonly observed phenomena, such as customers experiencing mixed feelings toward a package of services. The attributelevel approach provides a simple and elegant solution: Mixed feelings toward a product exist because a customer may be satisfied with one attribute, but dissatisfied with another. Third, an attribute-level approach to satisfaction affords researchers a higher level of specificity and diagnostic usefulness compared with the product level or â&#x20AC;&#x153;overallâ&#x20AC;? approach (Yang, Peterson, and Huang, 2001; Yang, Peterson, and Cai, 2003). Finally, there is some evidence that attribute-level performance/disconfirmation and overall satisfaction are qualitatively different constructs (Oliva, Oliver, and Bearden 1995), and, if treated interchangeably, specific product issues may be hidden by global customer satisfaction responses (Oliva, Oliver, and Bearden 1995; Yang, Peterson, and Cai, 2003). Thus, studying satisfaction at the attribute level can help extend both conceptual and empirical understanding of the phenomenon. As to the context of higher education service, it is logical to regard service attributes as good bases of satisfaction evaluation.

76

Instead of searching for more appropriate service attributes, some studies in satisfaction research have tried to examine the effect of more moderate variables, such as information satisfaction, desire (Spreng, MacKenzie and Olshavsky, 1996), price satisfaction (Voss, Parasuraman, and Dhruv Grewal 1998), fairness (Patterson, Johnson, and Spreng, 1997). These variables are mostly related to some marketing mix variables. For example, information satisfaction is related to promotion, and attributes satisfaction is related to product.

Following their reasoning, we can even explore more contingent variables, such as package or place. Key reasons for searching for a wider range of moderators may reside in efforts to build a more universal model for satisfaction. However, we think that these moderate variables are often incorporated into service or product attributes by the customer and may be more appropriately listed as attributes other than moderate variables. Some scholars point out that different satisfaction processes operate under different conditions, such as across different product categories, for high versus lowâ&#x20AC;&#x2018;involvement products, or for products versus services, often yield conflict results (Anderson 1994; Bolton and Drew 1991b; Cadotte et al. 1987; Halstead et al. 1994; Oliver 1989; Spreng et al. 1996). Therefore, we would propose that, from a marketing perspective, service attributes should be based on marketing mix while recognizing the specific service characteristics.

In their study of reviewing the impact of service attributes on customer satisfaction and dissatisfaction, Iacobucci and Ostrom (1995) identified some marketing related aspects of service, notably price, level of quality, friendliness of the service personnel, the degree of customization of the service, all of which are efficient factors in explaining customer satisfaction. In the higher education context, there are many versions used to measure higher education service attributes; most are essentially related to marketing mix variables. For instance, a widely used and well-known one (e.g. DeVore and Handal, 1981; Hampton, 1993), which was created by Betz, Klingensmith and Menne (1970), includes five factors, namely, studying conditions, recognition, compensation, quality of education, and social life. These factors are essentially related to marketing mix variables: compensation is related to price, quality of education to product, social life to package, recognition and studying condition is related to place. Therefore, based on marketing mix variables, we construct education service attributes though revising the design of Betz, Klingensmith and Menne (1970).

Previous studies illustrate that different service attributes of higher education embody varying degrees when influencing student satisfaction. Basically, quality of education is the most important factor and is related directly to student satisfaction (Howard and Maxwell, 1980, Hampton, 1993). Other resources are somewhat confused, depending on the methods employed, the nature of colleges and the samples that researchers collected.

Once the primary attributes of education service are determined, the next relevant issues are: which group should we be carefully looking for? Satisfied students or dissatisfied students, or both? Most researches done to date in durable goods areas put emphasis on dissatisfied customers. However, quite a few studies in the service industry and the higher education area show that the causes of dissatisfaction are not necessarily linked to the observer of the (dis) satisfaction (e.g. Johnson, 1995, Yang and Fang 2004). Johnson (1995) suggests that it is more appropriate to study the causes of satisfaction instead of dissatisfaction for satisfaction in the 77

service industry. From a managerial standpoint, it is important for administrators to understand the different attributes between satisfied students and dissatisfied students (Yang and Fang, 2004). Therefore, we propose the following Hypotheses: H1a: All five marketing mix related higher education attributes are significantly related to customer satisfaction with higher education.

H1b: For these five service attributes, satisfied students will significantly differ from dissatisfied students.

Which Model Predicts Best?

Due to the complicated nature of higher education as a service industry, assessing student satisfaction with higher education still remains a frequently troublesome issue. Quite a few models have been employed to examine the causes of student satisfaction with college from customer perspectives (e.g. Barry, Gilly and Schucancy, 1982; Hampton 1983, 1993; Hawes and Gilsan 1983; Schmidt, Debevec, and Comm, 1996; Douglas, McClelland, and John Davies, 2008; Gruber,et al, 2010). Among these studies, the following three models or methods were heavily employed to measure student satisfaction with higher education: disconfirmation model (Conant, Brown, and Mokwa, 1984) or gap analysis (Hampton, 1993); multi-attributes approach (Douglas, McClelland, and John Davies, 2008; Gruber, et al, 2010).

Disconfirmation Model.

The dominant conceptual model in the satisfaction literature is the model of disconfirmation of expectation. This model theorized that satisfaction is a function of the discrepancy between a customerâ&#x20AC;&#x2122;s expectation about the performance of a product and obtained product performance (Oliver, 1978, Churchill & Surprenant, 1982; Tse & Wiltob, 1988; Yi, 1990, 1994). The expectation or disconfirmation model is also the most popular model for satisfaction studies in the higher education context (e.g. Conant, Johnson, and Mokwa, 1984; Hampton, 1993).

Hampton (1993) used gap analysis to detect the factors and items that are mostly concerned with student satisfaction.

Some customer satisfaction researchers have questioned the expectation model. La Tour and Peat have been highly critical of this approach taken by satisfaction research (1978). First, they suggest that this major methodological problem centers around researches measuring the impact of expectation on perceived product performance, rather than measuring the impact of expectation on satisfaction. This occurs because performance evaluations do not contain an evaluation component; and therefore, there is no way to ascertain whether the customer is satisfied or dissatisfied with the level of obtained performance. Furthermore, satisfaction is a relative phenomenon rather than an absolute one. Though the disconfirmation of expectation also assumes customer satisfaction is a relative one, it is too strict to account fully for customer satisfaction.

Multi-attributes weighted attributes model.

Multi-attribute attitude models have received considerable attention from marketing researchers and practitioners (Shocker and Srinivasan, 1979, Yang, Peterson, and Cai, 2003). The basic notion of these different models is that customers form attitudes toward products or services on the basis of their attributes, which in turn, are used to explain and/or predict product/brand, 78

service preference or choice. The multi-attributes model has actionable managerial implications because, as a diagnostic approach, it is useful in detecting factors that could improve overall satisfaction of the product or service.

Performance Model.

With regard to services, based on Oliver (1980), Jayanti and Jackson (1991) state that “when performance judgments tend to be subjective (as in services due to intangibility) expectations may play only a minor role in the formation of satisfaction” (p. 603). They suggest that satisfaction in services may be a function of performance alone. Performance alone could be enough to explain customer satisfaction.

Among the relative importance of the effects of performance, weighted attributes and disconfirmation on customer satisfaction, the empirical results are often conflicted. Churchill and Surprenant (1982) found that both disconfirmation and performance were significant antecedents of satisfaction for a low‑involvement product, but only performance was significant for a high‑involvement product. In other instances, Tse and Wilton (1988) found that both disconfimation and performance had significant effects for a high‑involvement product, but performance was stronger. Patterson (1993) also found the opposite pattern with a high‑involvement product (home heater), in that performance had a stronger effect than disconfirmation. This has prompted some scholars to suggest that different satisfaction processes operate under different conditions, such as across different product categories, for high versus low‑involvement products, or for products versus services (Anderson 1994; Bolton and Drew 1991b; Cadotte et al. 1987; Halstead et al. 1994; Oliver 1989; Spreng et al. 1996).

In the higher education context, most studies utilized the disconfirmation model and found that disconfirmation has significant impact on satisfaction (Hampton, 1993). There is a lack of consistent results, however, with some studies showing a stronger effect of performance, whereas others show a stronger effect of disconfirmation. Furthermore, it is surprising that there is a lack of studies comparing the relative effects of all three concept paradigms on student satisfaction.

Based on recent studies in the service area, Hypotheses 2 and 3 are proposed as the following: H2: Performances, Multi-attributes, Disconfirmations (Gaps) will have significant impact on student satisfaction.

H3: Performance directly accounts for student satisfaction with higher education and is the best predictor in the higher education context.

Student Characteristics as Moderators Empirically, customer satisfaction/dissatisfaction is found to be correlated with various socioeconomic and demographic variables, although the statistically significant relationship accounts for relatively small percentages of variance in customer satisfaction/dissatisfaction (Day and Bodur, 1977; Ash 1978). In their model of determinants of customer satisfaction with business-to-business professional service, Patterson, Johnson and Spreng (1996) found that the service attributes are all important to customer satisfaction/dissatisfaction, and that their importance varies with such moderators as purchase situation and individual level. Within 79

the context of higher education, Astin (1987) argued that student satisfaction with college is determined not only by service attributes, but by the impact of student characteristics. Some prior studies have examined the relationships between student variables, such as gender, major, age, ethnicity, GPA (Howes, Maxwell, 1980), part or full time status, and education service attributes (cf. Starr, Bertz, and Menne, 1972; Powers 1985; Darren et al, 1989; Stage 1988).

Sturtz (1971) found that older students pay more attention to their recognition and education quality than younger students. In addition, older students are likely to require less social life or informal activities on campus since the family unit plays a larger part in older studentsâ&#x20AC;&#x2122; lives (Hiltumen, 1965). According to Bean and Vesper (1981), recognition is more important for female students than male students.

Furthermore, some studies address the indirect effects of some student variables on student satisfaction with higher education. For example, Terkla and Pagano (1990) pointed out that financial situation affects student expectation for university education quality and influences their satisfaction with higher education. While examining the effects of major on satisfaction with college, Schmidt, Debevec and Comm (1987) find that different majors lead to various perceptions of service attributes, which, in turn, influence their perception of satisfaction with college.

However, no comprehensive investigations have been done on how student characteristics indirectly affect satisfaction with higher education via performance or expectation of service attributes. To investigate whether the importance or expectation of education service attributes (recognition, education quality, social life, compensation and studying condition) varies across contingency variables, studies should incorporate student characteristics into design as moderator variables. Since relatively few studies on these student variables impacting service attributes have been conducted previously in customer satisfaction literature in the higher education context, propositions of the relationship between these variables represented and satisfaction with higher education may be a step toward an integrated theory of student satisfaction with higher education. As a result, Hypotheses 3a and 3b are as follow: H3a: The effects of performance of education service on student satisfaction will vary on the basis of student characteristics.

H3b: The effects of expectation of education service on student satisfaction will vary on the basis of student characteristics.

Methodology Measures A questionnaire developed by Betz, Klingensmith and Menne (1971) was used as a guide to develop the survey for this study. Their findings showed that College Student Satisfaction Questionnaire (CCSQ) is one of the few psychometrically sound instruments for the measurement of student satisfaction within the context of higher education. In its present from, CSSQ consists of five scales, namely, studying conditions, recognition, compensation, quality of education, and social life. Their survey contained seventy statements relating to student education services and encounters.

80

Through a pretest procedure, this instrument was refined and condensed. Several classes of students, both graduate and undergraduate, were asked to determine which of these seventy statements were relevant to their educational experience. They were also asked to add attributes that were missing from the list. The final version contained nine items for each attribute of education service. Each item asked for two responses: performance and importance.

Performance was measured by having students respond to the items on a seven-point Likert scale that ranged from very satisfied to very dissatisfied. Importances were measured on a similar scale ranging from very important to very unimportant. Student expectation has been measured by the importance of all service attributes (Hampton, 1993; Polcyb, 1986).

The database contained measures for several constructs. There was one dependent measure for this analysis: overall satisfaction. A seven-point overall measure of how students felt about the performance of education service was utilized on a range from, “Overall I’m very satisfied”’ to “Overall I am very dissatisfied.” Furthermore, to evaluate the contingent effect of student characteristics on satisfaction, eleven student variables were listed as general information at the end of questionnaire: (1) major, (2) gender, (3) age, (4) class, (5) year in the school, (6) employment status, (7) financial aid, (8) GPA, (9) ethnicity, (10) religion (11) part versus full time job. Each variable was measured by number in terms of the order showed in questionnaire.

Sample Participants in this survey were students who were randomly selected from three major Universities in the USA, one business college in The Netherlands, and alumni from one of three universities. Using alumni as participants is also suggested by Gwinner and Beltramini, 1995.

Students were from different majors, and classes. This procedure was used in order to obtain a sample reasonably representative of students across different universities. Except for alumni to whom questionnaires were mailed, all the questionnaires were finished in class. Students were instructed before answering the questionnaire. The collected effective sample was 1475.

Model Construction Performance model. In this model, satisfaction is a function of performance of all attributes.

We call this model the “performance model” , which can be simply expressed as : n Sedu = Σ Pi I=1

where : Sedu = satisfaction with education serice; Pi = performance of attribute I;

n = number of attributes.

Disconfirmation Model (gaps model). The disconfirmation model in this study can be computed by the following formula, despite its complicated nature in some studies.

n Di = Σ Pi - Ii ) I=1

Where: Di = Disconfirmation with attribute I; Aj = attitude toward attribute I; Pi = performance of attribute I; n = number of attributes.

The satisfaction function using disconfirmation or gap as variable is formulated as 81

Sedu = f (Di ) Multi-attributes weighted attributes model. Although there are a variety of alternative specifications of the multi-attribute model, the most prominent one is the Fishbein model (Bettman, Capon and Lutz, 1975), which may be formulated as n A I = Σ Ii P i I=1

where : AI = attitude toward attribute I; Pi = performance of attribute I; Ii = important weight given attribute I; n = number of attributes.

Data Analysis and Findings Service Attribute. In Table I, reliability analysis was performed on the five subscales by using Cronbach alpha. The high alpha coefficients demonstrate good internal consistency for the various measurement scales used. Table I also contains the product moment correlations among five service attributes and overall satisfaction. Overall satisfaction has a significant, positive correlation with each of the five satisfaction dimensions (p<0.001). In particular, education quality, compensation and recognition have relatively higher correlation with overall satisfaction. Hence, Hypothesis 1a is supported.

Table I: Correlation matrix and Alpha Reliability Estimates for Factors

Correlation Matrix

Factors 1 Education Quality 2 Studying Facilitation 3 Social Life 4 Recognition 5 Compensation 6 Overall Satisfaction

1 1.00 0.46 0.24 0.73 0.72 0.56

2 1.00 0.54 0.39 0.43 0.33

3

4

1.00 0.15 1.00 0.22 0.71 0.31 0.41

Number of Cronbach’s 5 6 Items Alpha 9 0.817 9 0.700 9 0.835 9 0.856 1.00 9 0.864 0.48 1.00 9 /

Satisfied and dissatisfied. Two groups, satisfied and dissatisfied were formed based on the rated scale of “overall satisfaction”. For more clarity, we leave respondents with the media score “4” out of consideration. Thus, all respondents with a scale ranging from “1” to “3” are classified as “dissatisfied”, all respondents with scores ranging from “5” to “7” are classified as “satisfied”.

Table II shows the means of five primary attributes of higher education and overall satisfaction for satisfied and dissatisfied students. All of these dimensional means of satisfied students are significantly different from dissatisfied students at the level of p<0.001. Specifically, satisfied students gave higher scores for each service attribute than those of dissatisfied students.

The order is somewhat different, for example, education quality received the highest mean performance among satisfiers, but received the second lowest mean for the dissatisfied group.

The basic idea here is that these five service attributes are significantly related to both satisfied 82

and dissatisfied students. Moreover, dissatisfied customers are always reluctant to report, and the number of this group of respondents is quite a bit lower. In this study, only 156 students are classified as dissatisfied among 1475 students. Therefore, we should analyze both satisfied and dissatisfied, instead of the dissatisfied group alone. Overall, Hypothesis 1b is supported by the results.

Table II: Different Perceptions of Service Attributes Performance and Satisfaction Measures among Satisfied and Dissatisfied Students Satisfied Students Dimensions Overall Compensation Social Life Facilities Recognition Education Quality

Mean 5.58 4.84 4.56 4.26 4.67

4.91

Dissatisfied Students

S. D 0.66 0.77 0.83 0.75 0.93

Mean

0.77

3.56

S. D 0.71 0.91 0.93 0.86 0.91

T-Value 50.60 15.22 9.57 10.49 12.56

Sig. 0.00 0.00 0.00 0.00 0.00

0.87

19.21

0.00

2.55 3.82 3.86 3.52 3.65

Fit of Model Table III demonstrates the good fit of three models which are used to predict overall student satisfaction by employing the same database. The results suggest all three measures can significantly predict overall student satisfaction. Consistent with the statement of Jayanti and Jackson (1991), the R squares in Table III indicate that performance (0.447) can explain overall satisfaction better than both the multi-attributes and disconfirmation models.

83

Table III: Stepwise Regression Results Models Performance Model

Independent Variables

Beta

SIG.

Education quality Social life Compensation Studying condition Recognition

0.484 0.192 0.146 0.019 0.000

0.000 0.000 0.000 0.452 0.975

Fishbein MultiAttribute

0.368(p<0.001) Education quality Social life

0.436 0.187

0.000 0.000

Compensation Recognition Studying condition

0.127 -0.067 -0.030

0.000 0.047 0.289

Disconfirmations

Â

R2 0.447(p<0.001)

0.252(p<0.001) Education quality Compensation Recognition Social life Studying condition

0.442 0.098 0.055 0.046 0.006

0.000 0.000 0.078 0.063 0.836

Â

Hence, both our Hypotheses 3 and 4 are empirically confirmed. Additionally, perhaps the most interesting and surprising finding is that multi-attribute attitude has greater impact on satisfaction than the disconfirmation model has, although the disconfirmation model is the most popular one in the satisfaction research area.

Table III also sheds light on the relative importance of service attributes in effecting student satisfaction with higher education. All three methods indicate that the quality of education is the best predictor of student satisfaction, which is consistent with other findings (Hampton, 1993, Cook and Zallocco, 1979). As we previously mentioned, there is some diversity in the order and significance of four other attributes when using different models. For instance, social life significantly contributes to satisfaction in both the performance and multi-attributes models, whereas it is not significant in the disconfirmation model. Recognition is perceived to significantly explain the satisfaction only in the multi-attributes model. Also, compensation other than social life is in second position in the disconfirmation methods. This also explains why some conclusions conflict, even with the same database or similar research design while using different models. The rationale behind these differences needs be further studied and may yield some valuable findings. The relatively low R squares also indicate the difficulty of predicting student satisfaction, even with use of the best model and larger samples, due to its complexity and the diversity of student priorities and desires.

84

Student variables and service attributes.

For analytical convenience, and due to space limitation, some student aspects are omitted.

Eight characteristics are chosen for further consideration: age, gender, class, employment status, GPA, part-time work or full-time work; living on campus or not, part-time and full-time student. The findings in Table IV indicate that student characteristics have quite different effects on the performances and expectations of five education service attributes. Further discussion elucidates important points.

Studying facilities.

The result of a wide variety of students basically having no differences on the performance study, except for student with different GPA, is not surprising. However, as to expectation, students with different aspects obviously have various expectations for study facilities. Students who are younger, or in lower level classes, or non-working, or who have lower GPAs, or are part-time have higher expectations for study facilities than do others.

Education quality.

The performance of education quality received more attention by older, female students, or by students who were in a high level class, non-working, had higher GPAs, or lived on campus. The same thing happened for the expectation of education quality, except that there is correlation between part-time and full time studentsâ&#x20AC;&#x2122; expectation with quality. There is no significant difference between performance and expectation of education quality for specific students.

Recognition.

Students who are older, or female, or in a high level class, or working, or live off campus, or have high GPAs have a preference for being recognized by professors or education server providers. With regard to recognition, students with different ages, whether they are part-time or full time, have the same expectation in terms of recognition attributes.

85

86

Expectation

0.00

0.14

0.06

-0.15

-0.13

-0.12

-0.10

0.02

0.02

0.00

0.02

0.00

0.00

0.00

0.00

0.40

0.40

0.00

0.00 0.00

0.00

-0.34

-0.13

0.11

0.16

0.01

0.24

-0.31

0.00

0.00

0.00

0.00

0.82

0.00

0.00

-0.04 -0.10

0.09

0.25

0.19

0.11

-0.11

-0.16

-0.05

-0.19

0.19

0.03

-0.12

-0.21

0.00

0.00

0.00

0.00

0.05

0.00

0.00

0.20

0.00

0.00

-0.29

-0.08

0.01

0.07

0.02

0.06

-0.24

0.01

-0.04

0.02

Note: Age: 18 0r less: 0; 19-20: 1; 21-22: 2; 23-24: 3; 25-26: 4; 27-28; 5 29-30; 6; 31-32; 7; 33-34; 8; 35 or over: 9 Sex: Female: 1; Male 2: Class: Freshman; 1; Sophomore; 2; Junior: 3; Senior: 4; Graduate: 5; Alumni: 6.

Work: Working: 1; Nonworking: 2.; Timework: Part-time: 1; Full Time: 2.

Type: Full-time Students: 1; Part-time students: 2. ; Living: On Campus: 1; Off Campus: 2

-0.33

Performance -0.07 0.01

0.00

Expectation

0.08

0.00

0.06

Performance 0.14

0.05

0.00

0.00

-0.22

Expectation

Social Life

Education Quality

-0.18

0.044 0.093 -0.17

0.00

0.92

Expectation

Student Variables

0.00

0.02

0.66

0.05

0.57

0.10

0.00

0.79

0.22

0.57

-0.28

-0.20

0.19

0.19

0.04

0.32

-0.24

-0.08

0.17

0.31

0.00

0.00

0.00

0.00

0.20

0.00

0.00

0.00

0.00

0.00

-0.34

-0.30

0.16

0.18

0.08

0.24

-0.24

-0.05

0.17

0.28

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.08

0.00

0.00

-0.28

-0.04

-0.01

0.09

0.00

0.10

-0.21

0.05

-0.04

0.09

0.00

0.14

0.76

0.00

0.88

0.00

0.00

0.06

0.12

0.00

GenTimep test der p test Class p test Work P test work p test GPA p test Living p test Type p test

Performance 0.00

Expectation

Performance 0.17

Age

Compensation Performance 0.12

Studying Facility

Recognition

Attributes

Service

Table IV: Correlation Matrix: The Relationships Between Student Variables and the Effects of Performance and Expectation of Service Attributes on Satisfaction

Compensation.

Students who are older, female, in a high level, have a high GPA care more for compensation, i.e, the ratio of output and input. For expectation of compensation, there is no significant correlation between older and younger students, or between higher level and lower level class students, or between part-time and full-time students.

Social life.

Finally, social life is more attractive to students who are young, male, in a lower level class, non-working, working part-time, have a relatively low GPA, and who live on campus. The only difference between performance and expectation is that full-time students have higher expectation for social life than those of part-time students while their perceived performance denotes no significant difference.

These findings are interesting to those administrators who are particularly attentive to individual or specific groups and who know how to accommodate the priorities and needs of different student groups, based on their demographic characteristics.

Discussion The results of this research have implications for researchers as well as education administrators.

The marketing mix-based service attributes are significantly related to overall satisfaction. Our results suggest that, instead of paying attention to dissatisfied students alone, it may be more appropriate to derive deep insights into what leads to satisfaction in the context of a service area such as higher education, This is due to (1) satisfied students are in the majority; and (2) dissatisfied students share basically the same perspective of service attributes. In assessing student satisfaction with higher education, performance of service attributes is demonstrated as the best indictor of satisfaction. In addition, the multi-attribute model performs better in explaining satisfaction than the disconfirmation model or gap analysis. Using different models can yield certain differences, even utilizing the same database.

The paper also shows that individual student characteristics indirectly impact satisfaction by influencing the performance and expectation of service attributes. Incorporation of individual characteristics within a suitable theoretical structure, as moderating variables, would prove to be a more promising direction for future research pursuits. Administrators should devote more attention to the different priorities and desires of the particular groups based on their demographic aspects. From a practitioner’s standpoint, administrators need to adopt strategies to manage or positively influence the way in which students affect one another and to implement effective mechanisms by which they can support each other’s experience. These interactions tend to improve student satisfaction with the education experience.

The instinctive reaction of education service providers is to assume that customer-to-customer interactions are beyond their control. Nevertheless, particularly in educational environments where the customer spends a longer period of time in the environment, the significance of customer-to-customer interaction may be greater than that of the customer-to‑service‑agent interaction. Rowley (1996) explores some of the approaches to customer compatibility management in higher education. Fundamentally, any assessment of satisfaction needs to acknowledge the mutual influence among customers.

87

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