Asia Pacific Advances in Consumer Research

VOLUME 6

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without prior written permission of the publisher.

International Standard Book Number (ISBN): 0-915552-52-3

Young-Won Ha and Youjae Yi, Editors

Asia Pacific Advances in Consumer Research, Volume 6

(Duluth, MN: Association for Consumer Research, 2005)

ii Preface

The sixth Asia-Pacific Association for Consumer Research (ACR) Conference was held at the Sheraton Walker Hill Hotel in Seoul, Korea, May 13-15, 2004. It was the first time that an ACR conference was held in Korea. The theme of the conference was Brand and Consumer Behavior. Over 200 individuals from 18 countries attended the conference. Given global attendance, we believe most attendees experienced a rich academic and non-academic cross-cultural event.

This volume of the Asia Pacific Advances in Consumer Research is comprised of the presentations made at the conference. The program of the conference reflects the diversity of the membership and their interests in both theoretical and applied research. There were 72 competitive papers presented in 19 sessions; each of these papers is contained in this volume. In addition, there were two presentations made in a plenary session and 20 presentations made in 5 special topic sessions. Abstracts or complete papers of these sessions are also contained.

Many people contributed to the success of the 2004 Asia-Pacific ACR Seoul Conference and to this volume of the Asia Pacific Advances in Consumer Research. The major contribution was made by the authors of the papers, the organizers of the special sessions, and the discussants. Our 19-member Program Committee provided valuable feedback concerning the Special Topics session proposals. 100 reviewers evaluated competitive paper submissions. Their names are listed in the program.

Also to be thanked are those individuals who provided us with administrative help. We thoroughly enjoyed working with Eun-Joo Yoon and Byeong-Uk Cheong at Sogang University and Moonkyung Cha at Seoul National University for many months. Graduate students from Sogang University and Seoul National University provided excellent assistance in the Conference registration booth. We are indebted to ACR Executive Director Jim Muncy, who assisted us resolving difficult problems that we faced preparing for the Conference. A word of thanks also goes to Carol Barnett for her help in the assembly and production of this volume.

Finally, we thank the former ACR President Steve Hoch for asking us to chair the conference. We would like to extend our deep gratitude to the company sponsors for their generous support: Samsung Electronics, Samsung Engineering and Construction, AmorePacific, TNS Asia Pacific, Brand Science Institute, Binggrae and Interbrand. Our special thanks go to Steve Hoch and Rick Bagozzi for making wonderful presentations at the plenary session of the conference. We would also like to thank ACR President Debbie MacInnis for her insightful keynote speech at the presidential luncheon.

Young-Won Ha, Sogang University Youjae Yi, Seoul National University 2004 Asia-Pacific ACR Conference Co-Chairs/Proceedings Editors

iii Conference Committees

CONFERENCE CHAIRS

Young-Won Ha, Sogang University Youjae Yi, Seoul National University

PROGRAM COMMITTEE

Kwangho Ahn, Inha University Rajeev Batra, University of Michigan Hans Baumgartner, Penn State Dae Ryun Chang, Yonsei University Sang-man Han, Sungkyunkwan University Curtis Haugtvedt, Ohio State University Sung-Tai Hong, Hanyang University Sungyul Jun, Sogang University Jill Klein, INSEAD Hakshik Lee, Hongik University Janghyuk Lee, HEC Jinyong Lee, Seoul Natl. University of Technology Naresh K. Malhotra, Georgia Tech Rajan Nataraajan, Auburn University C. Whan Park, University of Southern California Heungsoo Park, Yonsei University Jongwon Park, Korea University Sharon Shavitt, University of Illinois Changjo Yoo, Dongguk University

SPECIAL THANKS TO

Eun-Joo Yoon, Sogang University Moonkyung Cha, Seoul National University Byeong-Uk Cheong, Sogang University Jim Muncy, Valdosta State University

iv COMPETITIVE PAPER REVIEWERS

Pankaj Aggarwal, University of Toronto Jinyong Lee, Seoul National University of Technology Kwangho Ahn, Inha University Moonkyu Lee, Yonsei University Sowon Ahn, Sungkyunkyan University Sukekyu Lee, Hankuk University of Foreign Studies Yeqing Bao, University of Alabama in Huntsville Wei-Na Lee, University of Texas at Austin Virginie De Barnier, Edhec Business School Chae-Un Lim, Sogang University Russell Belk, University of Utah Chyong-Ling Lin, Lunghwa University Jim Burroughs, University of Virginia Wing-sun Liu, The Hong Kong Polytechnic University Taihoon Cha, Hankuk University of Foreign Studies Sandra Loeb, Europa-Universität Viadrina Frankfurt Joseph W. Chang, University of Regina Tina M. Lowrey, University of Texas at San Antonio Subimal Chatterjee, Binghamton University Harri T. Luomala, University of Vaasa/Epanet Ed Chung, St. Norbert College. Virginie Maille, CERAM Sophia-Antipolis Jaihak Chung, Sogang University Robyn McGuiggan, Sydney Graduate School of Management Mariëlle Creusen, Delft University of Technology Dwight Merunka, Aix University and Euromed Marseille Terry Daugherty, University of Texas at Austin Kyeong Sam Min, University of South Dakota Timothy Dewhirst, University of Saskatchewan Sangkil Moon, NC State University Martin, Eisend, Freie Universität Berlin George Moschis, Georgia State University Jean-Marc Ferrandi, University of Dijon Woonbong Na, Kyunghee University Robert J. Fisher, University of Western Ontario Shintaro Okazaki, Universidad Autonoma de Madrid Jim Gentry, University of Nebraska-Lincoln JungKun Park, Purdue University Maggie Geuens, Universiteit Gent, Netherlands Sehoon Park, Sungkyunkyan University Zeynep Gürhan-Canlı, University of Michigan Seong-Yeon Park, Ewha Women’s University Rebecca Hamilton, University of Maryland Laura A. Peracchio, University of Wisconsin-Milwaukee Sang-Lin Han, Hanyang University Ian Phau ,Curtin Business School Flemming Hansen, Copenhagen Business School W. Fred van Raaij, University of Tilburg Håvard Hansen, Norwegian School of Management Aric Rindfleisch, University of Wisconsin-Madison Curtis P. Haugtvedt, Ohio State University Anne L. Roggeveen, Babson College Jung Suk Hyun, Cheju University Russell Ruiters, HTC Industries Yong J. Hyun, KAIST Gangseog Ryu, Korea University Frederic Jallat, European School of Management Nicola E. Sauer, University of Mannheim Jin Gyo Kim, Massachusetts Institute of Technology Chuan-Fong Shih, Wake Forest University Sung Youl Jun, Sogang University Miyuri Shirai, Yokohama National University Sunkyu Jun, Hongik University Lee C. Simmons, Nanyang Technological University Jae Min Jung, North Dakota State University Itamar Simonson, Stanford University Kwon Jung, KDI School of Public Policy and Management Sangeeta Singh, Norwegian School of Management Sungwoo Jung, State University of New York at Oneonta. Surendra N. Singh, University of Kansas Yong-Soon Kang, SUNY-Binghamton Chan Joo Suh, Sookmyung Women’s University Jufei Kao, The City University of New York Siok Kuan Tambyah, NUS Business School Byung-Do Kim, Seoul National University John Thøgersen, The Aarhus School of Business Donghoon Kim, Yonsei University Ana Valenzuela, San Francisco State University Jae-Il Kim, Seoul National University Pierre Valette-Florence, UPMF Ju Yong Kim, Kookmin University Peeter W.J. Verlegh, Erasmus University Rotterdam Sang Yong Kim, Korea University Paul Z. Wang, University of Technology Sydney Susan Schultz Kleine, Bowling Green State University Yun-Oh Whang, University of Central Florida Even J. Lanseng, Agricultural University of Norway Jin-Tsann Yeh, Vanung University Garold Lantz, Monmouth University Changjo Yoo, Dongguk University Anne M. Lavack, University of Regina Sung-Joon Yoon, Kyonggi University Keun S. Lee, Hofstra University Yeosun Yoon, Rice University Chol Lee, Sogang University Shi Zhang, UCLA Dongdae Lee, Tongmyong University of IT Xin Zhao, University of Utah Haksik Lee, Hongik University Lianxi Zhou, Lingnan University

v Table of Contents and Conference Program

Preface ...... iii

ACR Conference Committee and Reviewers ...... iv

Table of Contents and Conference Program ...... v

Author Index ...... 393

ASSOCIATION FOR CONSUMER RSEARCH 2004 ASIA PACIFIC CONFERENCE

May 13-15, 2004 Sheraton Walkerhill Hotel Seoul, Korea

Thursday, May 13

ACR WELCOMING RECEPTION 6:00 p.m. – 8:00 p.m.

Friday, May 14

SESSION 1 9:00 a.m. – 10:15 a.m.

1.1 Plenary Session: Multiple Perspectives in Consumer Behavior

Chair: Young-Won Ha, Sogang University, Korea

Goal-Directed Behavior, Emotion, and Social Identity in Consumer Research ...... 1 Richard P. Bagozzi, Rice University, U.S.A.

Anchoring and Adjustment in Non-linear Pricing ...... 2 Stephen J. Hoch, University of Pennsylvania, U.S.A.

vi Friday, May 14

SESSION 2 10:45 a.m. – 12:30 p.m.

2.1 Special Session: Lessons from Outstanding Companies

Chair: Youjae Yi, Seoul National University, Korea

Samsung Electronics Samsung Engineering and Construction AmorePacific TNS Korea

SPECIAL SESSION SUMMARY Lessons from Outstanding Companies ...... 3 Youjae Yi, Seoul National University, Korea

Brand Strategy Behind the Rising Samsung Hyunsuk Chung, Vice President, Samsung Electronics

‘Raemian’ Legend: Strengthening Consumer-Brand Bonds Jung-Chae Suh, (On behalf of) Samsung Engineering & Construction

AmorePacific: People Serving with Cosmetics Jeff Luddington, AmorePacific

Taking the Guru Mystique out of Motivational Research David Richardson, Regional Director, TNS Asia Pacific

2.2 Competitive Paper Session: Electronic Marketing

Chair: Shintaro Okazaki, Universidad Autónoma de Madrid, Spain

External Search, Content Credibility and Intrinsic Gratifiers Influencing Attitude Toward Wireless Ads ...... 5 Shintaro Okazaki, Universidad Autónoma de Madrid, Spain

Habits as a Key Predictor of Internet Email Behavior ...... 13 Desmond Lam, University of Western Australia, Australia Dick Mizerski, University of Western Australia, Australia

An Empirical Examination on External Consumer Information Search on the Internet ...... 21 Byung-Kwan Lee, The University of Texas at Austin, U.S.A. TaiWoong Yun, The University of Texas at Austin, U.S.A. Wei-Na Lee, The University of Texas at Austin, U.S.A.

Identifying Success Factors of Mobile Marketing ...... 28 Parissa Haghirian, Kyushu Sangyo University, Japan Astrid Dickinger, Vienna University of Economics and Business Administration, Austria

vii 2.3 Competitive Paper Session: Brand Personality, Brand Loyalty, and Applications of Attitude Models

Chair: Jinyong Lee, Seoul National University of Technology, Korea

How Well does Brand Personality Predict Brand Choice? A Measurement Scale and Analysis using Binary Regression Models ...... 30 Laure Ambroise, ESA Grenoble, France Jean-Marc Ferrandi, CERMAB University of Dijon, France Dwight Merunka, University of Aix en Provence, France Pierre Vallette-Florence, ESA, France Virginie De Barnier, EDHEC, France

Congruence between Brand Personality and Self-Image, and the Mediating Roles of Satisfaction and Consumer- Brand Relationship on Brand Loyalty ...... 39 Seong-Yeon Park, Ewha Woman’s University, Korea Eun Mi Lee, Ewha Woman’s University, Korea

Factors of Household Recycling and Waste Reduction Behavior ...... 46 Chizuru Nishio, University of Tsukuba, Japan Toshie Takeuchi, Hosei University, Japan

Antecedents of “Brand Loyalty” in 401(k) Plans As Clues to Purchase Criteria for Retirement Investments ...... 52 Magdalena Cismaru, University of Regina, Canada Betsy Gelb, University of Houston, U.S.A.

Friday, May 14

ACR PRESIDENTIAL LUNCHEON 12:30 p.m. – 1:50 p.m.

Keynote Speech

“A Brand is a Brand is a Brand-Or is it?: Thoughts on Clarifying Branding Constructs”

Debbie MacInnis

Friday, May 14

SESSION 3 2:00 p.m. – 3:45 p.m.

3.1 Special Session: Technology and Marketing

Chair: Roger Marshall, Nanyang Business School, Singapore Discussion Leader: Byungjun Moon, Kyunghee University, Korea

Platform Innovation and the Evolution of Technologies ...... 56 Ashish Sood, University of Southern California, U.S.A. Gerard J. Tellis, University of Southern California, U.S.A.

Information Technology and the Sales Function ...... 57 Peter Reday, Ashland University, U.S.A. Na WoonBong, Kyunghee University, South Korea

viii Why Functional Specialists Should Be Encouraged to Use the Internet: The Changing Pattern of Influence in Buying Centers ...... 64 Roger Marshall, Nanyang Business School, Singapore Na Woon Bong, Kyunghee University, Korea Park ChanWook, Kyunghee University, Korea Peter Reday, Ashland University, U.S.A.

Internet-Enabled Knowledge Acquisition and Power in Family Decisions ...... 70 Roger Marshall, Nanyang Technological University, Singapore Peter Alan Reday, Ashland University, U.S.A. Na WoonBong, Kyunghee University, South Korea

3.2 Competitive Paper Session: Consumer Judgment and Decision Making

Chair: Shi Zhang, University of California at Los Angeles, U.S.A.

Form vs. Function: Emotional and Behavioral Consequences of Hedonic vs. Functional Tradeoffs ...... 74 Ravi Chitturi, Lehigh University, U.S.A. Raj Raghunathan, University of Texas at Austin, U.S.A. Vijay Mahajan, University of Texas at Austin, U.S.A.

Consumer Confusion of Percent Differences: When Less is More and More is Less ...... 76 Patrick Vargas, University of Illinois at Urbana-Champaign, U.S.A. Justin Kruger, University of Illinois at Urbana-Champaign, U.S.A.

The Effect of Consumer Literacy on Product Choice ...... 77 Haeran Jae, University of Kentucky, U.S.A. Devon DelVecchio, University of Kentucky, U.S.A.

The Effect of Compatibility between Benefit and Payment Patterns in Evaluating Financing Decisions: A Test of the Alignment Hypothesis ...... 78 Seigyoung Auh, Brock University, Canada Chuan-Fong Shih, Wake Forest University, U.S.A.

Brand Switching in Clothing as a Manifestation of Variety-Seeking Behavior ...... 79 Nina Michaelidou, Nottingham Business School UK Sally Dibb, Warwick Business School, UK David Arnott, Warwick Business School, UK

3.3 Competitive Paper Session: Branding, Co-Branding, and Brand Extension

Chair: Changjo Yoo, Dongguk University, Korea

Does Competition Matter in the Evaluation of Brand Extensions? ...... 86 Harish Kapoor, Carleton University, Canada Louise A. Heslop, Carleton University, Canada Statia Elliot, Carleton University, Canada

Retain the Meaning, the Sound, or Both? Effectiveness of Brand Name Translations in a Chinese-English Bilingual Context ...... 87 Yih Hwai Lee, National University of Singapore, Singapore Cheng Qiu, National University of Singapore, Singapore

Do Co-Branding Products Increase Consumers’ Purchase Behaviors in Taiwan? ...... 89 Mengkuan Lai, Naitonal Chengkung University, Taiwan

ix Branding of Japanese Organic Supermarket and the Characteristics of Consumer Behavior in Its User Segments ...... 96 Osamu Sakai, Tokyo Metropolitan Government, Japan Kosuke Ogawa, Hosei University, Japan

The Influences of the Consumer-Brand Relationship on the Evaluations of Extended Brands ...... 103 Yung-Shin Sung, Korea University, Korea Eun-A Park, Korea Broadcasting Advertising Corporation, Korea Tae-Hyung Kim, CJ Corporation, Korea

Friday, May 14

SESSION 4 4:15 p.m. – 6:00 p.m.

4.1 Special Session: Managing Service and Brand Relationships

Chair: Moonkyu Lee, Yonsei University, Korea Discussion Leader: Francis M. Ulgado, Georgia Institute of Technology, U.S.A.

Customer Retention Online: The Influence of Switching Barriers ...... 104 Betsy B. Holloway, Samford University, U.S.A. Sharon E. Beatty, University of Alabama, U.S.A.

Stages in the Development of Consumers’ Trust for Service Providers ...... 105 Lenard C. Huff, Brigham Young University - Hawaii, U.S.A.

Brand Personality, Self-Congruity and Consumer-Brand Relationship ...... 111 Hae Ryong Kim, Konkuk University, Korea Moonkyu Lee, Yonsei University, Korea Francis M. Ulgado, Georgia Institute of Technology, U.S.A.

Developing a Scale for Measuring Brand Relationship Quality ...... 118 Hyun Kyung Kim, Yonsei University, Korea Moonkyu Lee, Yonsei University, Korea Yoon Won Lee, TNS Korea

4.2 Competitive Paper Session: Cross Cultural Research

Chair: Ana Valenzuela, San Francisco State University, U.S.A.

Unraveling Cross-cultural Differences: Effects of Observability, Self Monitoring and Desire for Unique Consumer Products on Tendency to Seek Variety ...... 127 Nur Halimah Chew Abdullah, Nanyang Technological University, Singapore Bharadhwaj Sivakumaran, Nanyang Technological University, Singapore

Made for a Man or a Woman? An Exploratory Comparison of Virginia Slims™ Advertising in the United States and Korea ...... 136 Timothy Dewhirst, University of Saskatchewan, Canada Wonkyong Beth Lee, University of Waterloo, Canada

A Structural Analysis of Value Orientations, Price Perceptions, and Mall Shopping Behaviors: A Cross-cultural Study of American and Korean Consumers ...... 137 Kittichai Watchravesringkan, University of Arizona, U.S.A. Jennifer Yurchisin, University of Arizona, U.S.A. Miwoo Nam, Seokyeong University, Korea x A Cross-cultural Study of the Persuasive Effects of Sexual and Fear Appealing Messages: A Comparison Between France, Denmark, Thailand and Mexico ...... 140 Virginie De Barnier, EDHEC Business School, France Virginie Maille, CERAM, France Pierre Valette-Florence, Université Pierre Mendès-France, France Karine Gallopel, Maître de Conférences, France

Self-Indulgence or Loss of Self-Control? Or, is it a Bit of Both? Investigating Cross-cultural Aspects of Impulse Buying Behavior ...... 151 Piyush Sharma, Nanyang Business School, Singapore

4.3 Competitive Paper Session: Brand Commitment, Brand Loyalty, and Brand Value

Chair: Even J. Lanseng, Agricultural University of Norway, Norway

Religiosity and Brand Commitment: A Multicultural Perspective ...... 153 Aric Rindfleisch, University of Wisconsin-Madison, U.S.A. James E. Burroughs, University of Virginia, U.S.A. Nancy Wong, Georgia Institute of Technology, U.S.A.

Effects of Secondary Associations on Brand Value: An Experimental Study of The Relationship Between Corporate Image Dimensions and Consumers’ Willingness to Pay ...... 155 Even J. Lanseng, Agricultural University of Norway, Norway Santa Masandaviciute, JSC Market Stimulating Systems, Lithuania

The Influences of the Brand Personality on Brand Attachment and Brand Loyalty: Centered on the Differences Between the Brand Community Members and Non-members ...... 156 Yung-shin Sung, Korea University, Korea Euna Park, Korea Broadcasting Advertising Corp., Korea Min-kyung Han, Research International, Korea

True Value of Brand Loyalty ...... 157 Desmond Lam, University of Western Australia, Australia

Saturday, May 15

SESSION 5 8:30 a.m. – 10:15 a.m

5.1 Special Session: Customer Perception of Service Quality

Chair: Youjae Yi, Seoul National University, Korea

Korean-Standard Service Quality Index: Development and Application ...... 164 Youjae Yi, Seoul National University, Korea Jun Yeob Lee, Kyunghee Cyber University, Korea

Perceived Risk and Risk-Reduction Strategies for High-Technology Services ...... 171 Hyun Kyung Kim, Yonsei University, Korea Moonkyu Lee, Yonsei University, Korea Mi Jung, TNS Korea

Service Quality in the Public Sector: Seoul Service Index ...... 180 Youjae Yi, Seoul National University, Korea Suna La, Seoul National University, Korea xi Service Quality at Hospitals ...... 188 Sungjin Yoo, Inje University, Korea

5.2 Competitive Paper Session: Quantitative Approaches to Consumer Behavior

Chair: Dong-Hoon Kim, Yonsei University, Korea

Developing a Product Recommendation Model Using Spatial Statistics and Joint Space Mapping ...... 194 Sangkil Moon, North Carolina State University, U.S.A. Gary J. Russell, University of Iowa, U.S.A.

Asymmetric Consumer Learning and Inventory Competition ...... 196 Vishal Gaur, New York University, U.S.A. Young-Hoon Park, Cornell University, U.S.A.

A Simultaneous Approach to Constrained Multiple Correspondence Analysis and Cluster Analysis for Market Segmentation ...... 197 Heungsun Hwang, HEC Montreal, Canada Byunghwa Yang, University of Michigan, U.S.A. Yoshio Takane, McGill University, Canada

Long-term Advertising Effects and Optimal Budgeting ...... 200 Flemming Hansen, Copenhagen Business School, Denmark Lars Bech Christensen, Copenhagen Business School, Denmark

Latent Growth Curve Modeling of the Relationships among Revenue, Loyalty, and Customer Satisfaction by Generalized Structured Component Analysis (GSCA) ...... 215 Heungsun Hwang, HEC Montreal, Canada Young Chan Kim, Yonsei University, Korea Marc A. Tomiuk, HEC Montreal, Canada

5.3 Competitive Paper Session: Cultural Context

Chair: Siok Kuan Tambyah, National University of Singapore, Singapore

Measuring Status Orientations: Scale Development and Validation In the Context of a Transitional Economy ...... 218 Thi Tuyet Mai Nguyen, National Economics University, Vietnam Kwon Jung, KDI School of Public Policy and Management, Korea Siok Kuan Tambyah, National University of Singapore, Singapore

The Role of Cultural Orientation in Bargaining under Incomplete Information: Differences in Causal Attributions...... 220 Ana Valenzuela, San Francisco State University, U.S.A. Joydeep Srivastava, University of Maryland, U.S.A. Seonsu Lee, Wonkwang University, Korea

Impact of Self-Construal and Consumer Susceptibility to Interpersonal Influence on Consumer Assertiveness/Aggressiveness: Cross-National Investigation Using Thai and U.S. Samples ...... 222 Kawpong Polyorat, Khonkaen University, Thailand Jae Min Jung, North Dakota State University, U.S.A. Eugene S. Kim, University of Hawaii, U.S.A. Somyot Ongkhluap, Khonkaen University, Thailand

Assessing Conspicuous Consumption Behavior in a Multicultural Society: A Mediation Approach of Acculturation Dimensions on Chinese Ethnic Identification ...... 224 Joseph Chen, Millward Brown Goldfarb, Canada May Aung, University of Guelph, Canada Lianxi Zhou, University of Guelph, Canada Viany Kanetkar, University of Guelph, Canada xii The Foreign Model Effect and Its Interaction with Product Type in Catalog Home Shopping: Moderating Role of Ethnic Identification ...... 232 Dong-Il Lee, The Catholic University of Korea, Korea Ji-Hyun Lee, Seoul National University, Korea

Saturday, May 15

SESSION 6 10:45 a.m. – 12:30 p.m.

6.1 Special Session: Internet Marketing

Chair: Janghyuk Lee, HEC School of Management, France

Net Generation: the Growing Dominant Consumer Group in Network Society ...... 239 Seong-Yeon Park, Ewha Women’s University, Korea Eun Mi Lee, Ewha Women’s University, Korea

How to Generate Affective Reactions through Social and Spatial Immersion on a Merchant Website : Proposal of an Integrative Model ...... 244 Brice Pablo de Diesbach, ESSEC / IAE Aix-en-Provence, France Anne-Cécile Jeandrain, Catholic Univerisity of Louvain, Belgium

The Effect of Scarcity Message on Consumer’s Purchase Intention in the Internet Shopping Mall ...... 252 Yun kyoung Bae, Hankook University of Foreign Studies, Korea Sukekyu Lee, Sungkyunkwan University, Korea

Exploring Repeat Exposure Effects of Internet Advertising ...... 259 Janghyuk Lee, HEC School of Management, France Donnel A. Briley, Hong Kong University of Science and Technology, Hong Kong

6.2 Competitive Paper Session: Information Processing

Chair: Naresh Malhotra, Georgia Institute of Technology, U.S.A.

Kill Two Birds with One Soap: The Multifinality Pursuit and the Need for Closure ...... 261 Woo Young Chun, University of Maryland, U.S.A. Arie W. Kruglanski, University of Maryland, U.S.A.

The Impact of Inconsistent Word of Mouth on Brand Attitude ...... 262 JunSang Lim, University of Alabama, U.S.A. Sharon E. Beatty, University of Alabama, U.S.A.

The Effects of Typicality of Product Types on Schema Change ...... 271 Sowon Ahn, Sungkyunkwan University, Korea Young-Won Ha, Sogang University, Korea

Feeling Happier When Paying More: The Role of Promotional Framing of Prices and Counterfactual Thinking in Consumer Affect ...... 272 Sukki Yoon, University of Illinois at Urbana-Champaign, U.S.A. Patrick T. Vargas, University of Illinois at Urbana-Champaign, U.S.A

xiii 6.3 Competitive Paper Session: Understanding Asian Consumers

Chair: Chan-Joo Suh, Sookmyung Women’s University, Korea

Consumer Ethnocentrism Portrayed in the Advertisings and Meanings Actualized by Consumers: A Case of Turkey ...... 274 Aya Ozhan Dedeoglu, Ege University, Turkey Ipek Savasci, Ege University, Turkey Keti Ventura, Ege University, Turkey

Innovativeness and Mobile Phone Replacement: An Empirical Study in Taiwan ...... 280 Chih-Chien Wang, National Taipei University, Taiwan Li-Chuan Wang, ICAT Technology, Taiwan Yann-Jy Yang, National Chengchi University, Taiwan

The Effectiveness of Joint-Venture and Local Lifestyle Magazines in China ...... 284 Flora Fang Gu, University of Hong Kong, Hong Kong Kineta Hung, University of Hong Kong, Hong Kong David K. Tse, University of Hong Kong, Hong Kong

Business Gift Giving in Vietnam Within and Between Organizations ...... 286 Garold Lantz, Monmouth University, U.S.A. Sandra G. Loeb, Europa University–Viadrina, Germany Linh Thi My Le, National Economic University, Vietnam

Capturing Moment of Consumption with Smartphone: Case Study from “Capturing Meal and Snack Consumption Scenes among Japanese Female University Students” ...... 291 Satoshi Hosoe, Keio University, Japan

Saturday, May 15

ACR LUNCHEON 12:30 p.m. – 1:50 p.m.

Best Competitive Paper Award

Post-Luncheon Event Emile Choir

Saturday, May 15

SESSION 7 2:00 p.m. – 3:45 p.m.

7.1 Competitive Paper Session: Pricing, Switching Costs, and Consumer Characteristics

Chair: Subin Im, San Francisco State University, U.S.A

The Relationship between Internal Reference Price and Three Aspects of Dealing Patterns: Frequency, Depth, and Depth Variation ...... 299 Miyuri Shirai, Yokohama National University, Japan

xiv The Role of Switching Costs in Technology Commitment: The Case of High Technology Market ...... 303 Jung Suk Hyun, Cheju National University, Korea Jae H. Pae, Hong Kong Polytechnic University, Hong Kong

The Role of Innate Consumer Innovativeness in New Product and Service Adoption Behavior: A Longitudinal Reexamination and Empirical Extension ...... 309 Subin Im, San Francisco State University, U.S.A. Charlotte H. Mason, University of North Carolina, U.S.A. Mark B. Houston, University of Missouri-Columbia, U.S.A.

Personality and Personal Values in Travel Destination Preference...... 311 Lynn R. Kahle, University of Oregon, U.S.A. Yukiko Matsuura, University of Oregon, U.S.A. Jeffrey Stinson, University of Oregon, U.S.A.

7.2 Competitive Paper Session: Consumer Satisfaction, Post-Purchase Affects, and Attitudes

Chair: Lianxi Zhou, Lingnan University, Hong Kong

Satisfaction Processes: Antecedents and Consequences of Differential Judgment Input ...... 312 Yong-Soon Kang, Binghamton University–SUNY, U.S.A. Subimal Chatterjee, Binghamton University–SUNY, U.S.A.

The Influence of Postpurchase Consumer Affects on Repurchase Intentions ...... 314 Chien-Huang Lin, National Central University, Taiwan Wen-Hsien Huang, National Central University, Taiwan

Effects of Service Quality on Customer Retention and Word-of-Mouth in a Retail Setting: Comparative Study of Different Scales ...... 316 Sang-Lin Han, Hanyang University, Korea Sung-Tai Hong, Hanyang University, Korea

An Analysis of Determinants of Consumer’s Recycling Behavior ...... 322 Michiyo Aoki, Tamagwa University, Japan

The Impact of Consumers’ Perceptions of Relationship Quality on Key Relational Constructs ...... 326 Amy Wong, Universitas 21 Global, Singapore Lianxi Zhou, Lingnan University, Hong Kong

7.3 Competitive Paper Session: Emerging Issues in Consumer Research

Chair: Peisan Yu, Tung-Hai University, Taiwan

Can We identify the Research Hypothesis with the Alternative Hypothesis? ...... 329 Hyunchul Cho, Hanyang University, Republic of Korea Shuzo Abe, Yokohama National University, Japan

A Study of Stress and Changes in Consumer Behavior ...... 330 George P. Moschis, Georgia State University, U.S.A. Euehun Lee, Information and Communications University, Korea Anil Mathur, Hofstra University, U.S.A.

Ritual Aspects of Sports Consumption: How Do Sports Fans Become Ritualized? ...... 331 Seungwoo Chun, University of Nebraska-Lincoln, U.S.A. James W. Gentry, University of Nebraska-Lincoln, U.S.A. Lee P. McGinnis, Washburn University, U.S.A.

xv A Focused Conversation Model in Consumer Research: The Incorporation of Group Facilitation Paradigm in In-Depth Interviews ...... 337 Peisan Yu, Tung-Hai University, Taiwan

Gender Differences in Unrealistic Optimism About Marriage and Divorce: Are Men More Optimistic and Women More Realistic? ...... 345 Ying-Ching Lin, National Chi Nan University, Taiwan Priya Raghubir, University of California at Berkeley, U.S.A.

Saturday, May 15

SESSION 8 4:15 p.m. – 6:00 p.m.

8.1 Competitive Paper Session: Post-Material and Postmodern Perspectives on Consumption

Chair: Russell W. Belk, University of Utah, U.S.A.

A Post-material Perspective: The Influence of Financial Detachment on Consumers’ Happiness...... 347 Hélène Cherrier, University of Westminster, UK

Consumption and the “Modern Woman” in China: A Conceptual Framework ...... 349 Kineta Hung, University of Hong Kong, Hong Kong Yiyan Li, University of Hong Kong, Hong Kong Russell W. Belk, University of Utah, U.S.A.

Buy Nothing Day: Resistance to Consumption in the Age of Digital Information ...... 354 Hélène Cherrier, University of Westminster, UK Ivo Belohoubek, University of Arkansas, U.S.A.

Christmas in Japan: A Global and Local Consumption Holiday ...... 356 Junko Kimura, Hagoromo University, Japan Russell W. Belk, University of Utah, U.S.A.

8.2 Competitive Paper Session: Communication and Persuasion

Chair: Curtis P. Haugtvedt, The Ohio State University, U.S.A.

Gender Differences in Processing Comparative Advertising in a Competitive Context-Evidence for Differential Strategies ...... 357 Chingching Chang, National Chengchi University, Taiwan

Understanding Consumer Confusion on Brand Origin in a Globalizing World ...... 359 Lianxi Zhou, Lingnan University, Hong Kong

Effects of Global Cultural Positioning Advertisements ...... 364 Sunkyu Jun, Hongik University, Korea Haksik Lee, Hongik University, Korea James W. Gentry, University of Nebraska-Lincoln, U.S.A.

Prompting Elaboration by Restricting Choice ...... 369 Richard J. Shakarchi, Ohio State University, U.S.A. Curtis P. Haugtvedt, Ohio State University, U.S.A.

xvi 8.3 Competitive Paper Session: Online Shopping

Chair: Kyeong Sam Min, University of South Dakota, U.S.A.

Creating Value for Online Shoppers: Implications for Satisfaction and Loyalty ...... 370 Eun-Ju Lee, California State University-Los Angeles, U.S.A.

Effects of 3-D Visualization on Persuasion in Online Shopping Sites: A Moderating Role of Product Knowledge ...... 371 Kihan Kim, University of Texas at Austin, U.S.A. Terry Daugherty, University of Texas at Austin, U.S.A.

Personal Value (LOV) and Consumers’ Acceptance of Web Marketing Facilities (AWMF) – The Case of Consumers in Macau - The Special Administrative Region of China ...... 378 NG, Sio Wang, Macao Polytechnic Institute, Macao

The Effect of Internet Service Quality on Internet Store Loyalty: Mediating Role of Internet Store Satisfaction and Internet Store Image ...... 386 Euehun Lee, Information and Communications University, Korea Dong-Il Lee, The Catholic University of Korea, Korea

Author Index ...... 393

xvii Goal-Directed Behavior, Emotion, and Social Identity in Consumer Research Richard P. Bagozzi, Rice University, U.S.A.

ABSTRACT Consumer research has made many advances over the years. Most of this work has contributed to our knowledge of information processing. In the vast majority of cases, focus has been placed on studying cognitive processes, with the dependent variable being either attitudes, beliefs, or some other internal mental state. Much less research has investigated consumer action, which will be the topic of this talk. My objective will be to describe a program of research that I and others have pursued to better understand consumer action.

ABSTRACT Marketers frequently price services in a non-linear fashion such that the cost for each additional unit depends on total usage. This forces consumers to calculate a weighted average to determine their effective price per unit. Our research indicates that consumers exhibit predictable biases in price estimation and revealed preferences for different pricing plans. Consumers rely on two anchors when evaluating non-linear pricing plans. First, consumers frequently overly anchor on the rate associated with the last volume tier a consumer expects to reach. This causes consumers to under- estimate the effective price for plans where the marginal rate decreases with usage (direction bias). Second, consumers overly anchor their estimates on the simple average of the rates across the different usage tiers. This produces an underestimation of the effective price for plans with a larger percentage of the volume at higher rates (simple average bias).

Why are a select few companies better at marketing and brand price control. This deregulation shifted market power from suppliers activities than their competitors? This is a question that has been to buyers. Faced with the demand-oriented market, Raemian needed raised by a number of marketing researchers and practitioners over a brand for differentiation. With CEO, SangDae Lee’s strong the years. Although there may be many approaches to this issue, one support, Raemian successfully developed and implemented a brand way might be to observe closely what outstanding companies are strategy. actually doing. We can then gain insights into best practices and Raemian’s logo consists of three Chinese characters against learn lessons from the role models in the field. three columns, gray and light green. The first Chinese letter, Rae The objective of this session is thus to bring together companies means future. Mi means beauty, and Ahn means comfort. Great care that are well known for their excellence in marketing and brand has been taken to this logo. For example, originally developed by strategies. Four leading companies are selected and featured in this Interbrand, the logo’s color has been changed from three colors to session: Samsung Electronics, Samsung Engineering and two. Uniqueness, Pride, and Trend-setting are Raemian’ brand Construction, AmorePacific, and TNS Asia Pacific. They range essence that are incorporated into Raemian’s marketing messages, from electronics such as mobile phones, housing industry including such as advertisements. apartments, cosmetics and household products, to marketing research Raemian’s target consumers are 30-40 years old, upper middle firms. By providing in-depth case analyses as well as describing class women who live in the urban and metropolitan areas. The overall marketing and brand strategies, these companies present brand personality is set to be sophisticated, intelligent, and sincere. “what they do” as well as “how they do it” in order to achieve To strengthen brand commitment, Raemian implements its brand excellence. We are eternally grateful to these companies for their strategy. It has divided the market into two: Residents and cooperation, their trust, and their willingness to share their own Nonresidents. Ramian’s brand strategy for residents focuses on experiences. customer satisfaction from direct experience. Since 2000 when they This session will be particularly interesting to those who wish first launched the brand, it has systematically constructed the to understand key factors for successful brand strategies as well as database. Based upon the detailed information stored in the database, marketing research processes. This session covers a number of it works on marketing activities to increase brand commitment issues that are important to consumer researchers, brand managers, among residents. One of the examples is Raemian Festival. The and marketing managers. These issues include brand value, brand programs of the festival are carefully choreographed to reflect equity, product leadership, sports marketing, product placements, Raemian’s brand concepts and image, along with the messages of needs-based segmentation, differentiated marketing strategies, the banners, “Raemian is your name.” “Be proud to be a Raemianse.” corporate brand management, consumer-brand bonds, brand Raemian also provides cultural experiences in “Raemian Academy.” personality, brand commitment, globalization strategy, motivational The brand strategy for nonresidents focuses on advertising and research, layers of brand image, etc. corporate image management. Another strategy for nonresidents is Brief descriptions of the four presentations are given below. through “intelligent apartment”, a model house where potential consumers experience Raemian’s future offerings. “Brand Strategy Behind the Rising Samsung” These splendid brand strategies and successful implementation Hyunsuk Chung, Vice President, Samsung Electronics brings us to terrific market performance. According to Park and Over the past several years Samsung Electronics’ brand value Srinivasan’s survey method (Journal of Marketing Research 1994), has increased dramatically, placing Samsung at #25 in Interbrand’s Raemian Brand Value is 1.4 billion dollars. According to the KS- 2003 Brand Value Survey and registering Samsung as the fastest SQI (The Korean Standard- Service Quality Index), Raemian ranks growing brand in the world among its peers. In the process, highest. According to K-BPI (Korea Brand Power Index) and NCSI Samsung’s brand reputation has changed from a mass marketer of (National Customer Satisfaction Index), Raemian has marked cheap TVs and VCRs to a leader in innovation and design com- highest for the four consecutive years. Faced with keen competition manding a premium price. In order to achieve such phenomenal from burgeoning competitors, Remain continues its saga by growth in its brand equity, Samsung has used a number of key brand providing upscale offerings, such as health, digital convergence, strategies and tactics, including product leadership, corporate brand and environmental quality. management and differentiated marketing activities Raemian’s brand strategy of strengthening consumer-brand bonds has worked and will continue to maintain its position as the “‘Raemian’ Legend: Strengthening Consumer-Brand leader in the housing industry. Bonds” Jung-Chae Suh, (On behalf of) Samsung Engineering & “AmorePacific: People Serving with Cosmetics” Construction Jeff Luddington, AmorePacific “Raemian Legend” is the successful brand management story AmorePacific is the name of the No. 1 cosmetic company in in the housing industry. It is also one of the fabulous examples of Korea, and the name of our brand (AmorePacific) in the global putting the textbook brand theory into best practice. The company market. The purpose of AmorePacific is to develop a new engine of started business in 1974. In 2000, it launched the brand, “Raemian.” growth based on our competencies in order not only to satisfy with Over the few years it has become the industry leader in the housing the present position of No. 1 in the domestic market, but also to be industry. a constantly growing enterprise. In this presentation you will see the After the 1997 Asian Economic meltdown, the Korean housing globalization strategy of AmorePacific in U.S. AmorePacific pro- market was deteriorating. Many housing businesses went bankrupt. motes Korean beauty and culture abroad through the brand of To revive the housing market, the Korean government deregulated AmorePacific. 3 Asia Pacific Advances in Consumer Research Volume 6, © 2005 4 / Lessons from Outstanding Companies “Taking the Guru Mystique out of Motivational Research” David Richardson, Regional Director, TNS Asia Pacific Marketing is based on meeting consumer needs. Motivational research which began with great promise when Ernest Dichter introduced needs based research in the 1950’s and 60’s to the marketing community devolved into the more common prosaic form of research which became synonymous with the focus group it craze of the 1980’s. In the process motivational research became needlessly discredited. Paul Heylen, a friend and disciple of Dichter, not only promoted the use of these models but was also visionary in his ability to link biological/neurological drivers to consumer behavior and by doing so created a framework for the various quantitative needs-based models. By structuring the research around this model the overwhelming importance of the moderator was reduced taking the “guru” mystique out of motivational research. To illustrate the structure and insights provided by the model we present a case example from the Korean market. External Search, Content Credibility and Intrinsic Gratifiers Influencing Attitude Toward Wireless Ads Shintaro Okazaki, Universidad Autónoma de Madrid, Spain

ABSTRACT an overview of the research methodology is provided and followed Wireless Internet is becoming increasingly important in con- by a presentation of the study’s findings. After primary implica- sumer behavior research. This study explores factors affecting tions are discussed, the paper is concluded with some suggestions mobile users’ attitude toward wireless advertising platform. Exter- for further work in the area. nal search, content credibility, perceived infotainment, and perceived irritation are hypothesized as antecedents, while willingness THEORETICAL FRAMEWORK AND to access is proposed as a consequence of attitude toward wireless HYPOTHESES DEVELOPMENT text banner ads. The proposed constructs are operationalized through So far, little attention has been given in the literature to a structured questionnaire. An empirical survey conducted in the consumers’ acceptance of wireless pull advertising. While the greater Tokyo area produced 590 usable responses. The findings literature emphasizes strategic m-commerce issues, most of the support the basic propositions regarding the links between the studies have tended to focus on wireless push advertising or SMS- constructs. The perceived infotainment was found to be the most based marketing while there are excellent conceptualizations (e.g., significant factor influencing attitude toward wireless ads, which in see Balasubramanian, Peterson and Jarvenpaa 2002; Watson et al. turn determines users’ behavioral intention to click the ads. How- 2002). Among them, one study attempted to empirically test theo- ever, the external search shows no effects on attitudinal dimension. retical propositions about WAP (Wireless Application Protocol) adoption on the basis of the theory of planned behavior and INTRODUCTION innovation diffusion theory (Hung, Ku and Chang 2003). However, As the world rapidly approaches the landmark of one billion research on wireless marketing communications is still in its mobile users, mobile commerce (m-commerce) is attracting more infancy. and more attention from online marketers. This is especially true in Given the almost non-existent research on consumers’ accep- Asian and Nordic countries, such as Japan, Korea, Finland and tance of wireless pull advertising, this study attempts to integrate Sweden, where wireless Internet platforms which allow the use of past research relevant to major explanatory variables into a system- the emerging set of applications and services are now firmly atic conceptual framework. Figure 1 presents our proposed model, established (Sadeh 2002). In 1999, the largest mobile operator in “wireless advertising acceptance model” to be verified in this study. Japan, NTT DoCoMo, launched “i-mode,” which offers a broad “Willingness to access” is a dependent variable, while “ongoing range of Internet services, including email, transaction services external search”, “wireless content credibility”, “perceived such as ticket reservations, and banking, shopping, infotainment infotainment”, “perceived irritation”, and “attitude toward wireless services and directory services (NTT DoCoMo 2003). By March ads” are independent variables. In this model, consumers’ accep- 2003, “i-mode” subscribers had reached 38 million, and NTT tance is examined by attitude toward wireless ads and willingness DoCoMo had expanded their European user base through partner- to access, but not by actual access, because wireless Internet is “still ships with key mobile operators. at an early stage, characterized by limited adoption and use” (Lu et The i-mode manages a critical mass of numerous “official” al. 2003). In what follows, the associations among the six constructs content providers, who create official i-mode sites. Subscribers to are explained in detail, on which twelve hypotheses are formulated. i-mode can access these official sites directly through the i-mode menu, and also subscribe to receive further optional information. Ongoing external search Among these, “Tokusuru Menu” (“beneficial menu” in Japanese) The reasons contributing to consumers’ acceptance of new is one of the most popular optional sites. It provides text banner ads information technology vary according to the type of device, target regarding promotional campaigns, discount coupons, presents, et users, and context (Moon and Kim 2001). Since mobile handsets are cetera. It has been asserted that the Tokusuru Menu exemplifies an seen as a relatively new device, consumers’ behavioral decision can effective form of pull advertising, because the promotional mes- be fundamentally based on the level of motivation to seek external sages are available to any i-mode subscribers looking for quick information, before intrinsic and affective factors are taken into solutions and timely benefits. In fact, D2 Communication (2002) account. In our proposed model this motivational factor consists of reported click-through and call-through rates ranging between 10 the “ongoing external search,” which can be defined as “the and 15%, notably higher than those of the regular wired Internet. strength of consumers’ effort to engage in a continuous search of However, as consumers’ initial curiosity has faded, wireless adver- outside information sources.” tisers are facing a serious credibility issue (Computer Times 2002). The ongoing external search occurs on a regular and continual Moreover, it is largely unknown which factors are most important basis, even when problem recognition is not activated (Bloch, in inducing consumers to “click” text banner ads in order to access Sherrell and Ridgway 1986). According to Hawkins, Best and wireless sites. Coney (2001), consumers conduct ongoing external search to The purpose of this exploratory study is two-fold. First, the acquire information for possible later use, while enjoying the study attempts to introduce a research model in terms of the basic process of information seeking itself. In particular, there are a group constructs affecting mobile users’ attitudinal and behavioral di- of individuals called “market mavens,” who “appear to have infor- mensions. Second, the study seeks to provide empirical insights mation about many kinds of products, places to shop, and other into the links between these constructs by conducting a large-scale aspects of markets” (Hawkins et al. 2001). Furthermore, the market survey with non-student samples. mavens are thought to be extensive users of media who possess The remainder of the paper is organized as follows. Initially, greater motivation, ability, and opportunity to process information the relevant literature is summarized and a basic research model is (Hoyer and MacInnis 2001). We argue that the extent of ongoing proposed by linking attitudinal and behavioral dimensions. Next, external search can be a useful measure of consumer readiness to 5 Asia Pacific Advances in Consumer Research Volume 6, © 2005 6 / External Search, Content Credibility and Intrinsic Gratifiers Influencing Attitude Toward Wireless Ads FIGURE 1 Proposed Model

accept wireless information, because the mobile device can be credibility, which is defined as “consumers’ perceptions of the considered as the ultimate mode for searching for information truthfulness and believability of advertising in general” (McKenzie regardless of time and location. For example, using third-genera- and Lutz 1989). In the light of our first construct, if consumers tion mobile technology, JNAvi, “users (in Japan) enter a phone actively exercise active ongoing external search, there will be more number, address, or landmark and then search the area within a 500- chances to collect relevant resources associated with ad credibility. meter radius” (Watson et al. 2002). Such mobile users tend to Therefore, expend the effort necessary to make an optimal, rather than a satisfactory, decision, in the attempt to “stay informed about the H2: wireless content credibility is positively related to on- market because they enjoy this activity and the social rewards going external search. derived from sharing the results of their searches with others” (Hawkins et al. 2001). As seen in the preceding section, Tokusuru Menu is a pull advertising, which requires consumers’ judgment of the service to H1: Attitude toward wireless ads is positively related to be believable prior to further access. Furthermore, as the menu ongoing external search. continually delivers an abundant and diverse range of promotional information, consumers will “click” only what is thought to be Wireless content credibility useful and trustworthy for fulfilling their needs. Given the limited Content creation has been asserted as one of the most impor- space in mobile screen, recognition of sponsor name with high tant stages in m-commerce value chain (Barnes 2002). The concept reputation may lead to subsequent access of the content site. of digital content creation and delivery is essentially the same in Therefore, the following hypotheses are formulated: wireless internet advertising as wired internet advertising, while the specific format will be necessarily different because of the nature of H3: Attitude toward wireless ads is positively related to mobile devices (Choi, Stahl and Whinston 1997). As a range of wireless content credibility. digital content should be tailored to the consumer needs and wants, H4: Willingness to access is positively related to wireless acceptance of such information largely depends upon the trustwor- content credibility. thiness it delivers (Computer Times 2002). Batra et al. (1996) suggest that the credibility of a source Intrinsic gratifiers should be recognized as consisting of two primary dimensions, a The uses and gratifications theory examines audience decision cognitive and an affective dimension. The former includes judg- making with regard to the psychological needs that motivate people ments about the power, prestige, and competence (expertise), while to engage in media use behaviors. It assumes that these psychologi- the latter concerns judgments about trustworthiness, attractiveness, cal needs “prompt the audience to purposefully select certain media and dynamism. MacKenzie and Lutz (1989) define ad credibility as and media contents for consumption in order to satisfy a set of “the extent to which the consumer perceives claims made about the psychological needs behind those motives” (Lin 1999). In the brand in the ad to be truthful and believable.” They suggest that tradition of this theory, the media audience is assumed to consist of there is the ad credibility subsystem, consisting of perceived ad goal-oriented, active media users fully aware of their needs (Katz, claim discrepancy, advertiser credibility, and advertising credibil- Blumler and Gurevitch 1974). This basic assumption has encour- ity. In this study, only the latter two are included in a single aged researchers to apply the uses and gratifications theory to construct, “wireless content credibility.” Thus, this construct con- interactive media, because the Internet requires high consumer cerns advertiser credibility, which refers to “the perceived truthful- involvement. As a result, the theory has been applied to a wide range ness or honesty of the sponsor of the ad”, as well as advertising of consumer experiences associated with Web sites (Chen and Asia Pacific Advances in Consumer Research (Volume 6) / 7 Wells 1999; Eighmey and McCord 1998; Korgaonkar and Wolin sites. Here, “intention to access” is meant to be the intention to 1999; Lin 1999; Luo 2002). However, little empirical research has “click” the hyperlinks of text banner ads sent to mobile device. addressed the topic of mobile uses and gratifications. Before clinking, consumers are likely to form affective responses to It has been asserted that the most important dimensions of wireless ads. Thus, based on this assumption, it is hypothesized: online uses and gratifications theory are informativeness, entertainment, and irritation (Chen and Wells 1999; Eighmey 1997; Eighmey H12: Willingness to access is positively related to attitude and McCord 1998; Korgaonkar and Wolin 1999; Lin 1999; Luo toward wireless advertising. 2002; Rubin 1994). Here, perceived informativeness refers to “the extent to which the web provides users with resourceful and helpful METHODOLOGY information” (Chen and Wells 1999; Ducoffe 1995). In a pioneer- The present study was carried out during April through May, ing study of attitudes toward websites, Chen and Wells (1999) 2003, in Japan. The respondents were chosen by stratified random argue that informativeness is positively and directly related to sampling on the basis of age and gender distribution, using the attitude. Perceived entertainment is a consequence of fun and Citizens Registration Book as of March 31, 2003. Questionnaires enjoyable experience proceeding from the media use (Eighmey and were distributed by personal visit to 1,623 residents between 15 and McCord 1998). Lou (2002) argues that “the value of media enter- 65 years old living within 30 km of the center of the Tokyo tainment lies in its ability to fulfill users’ needs for escapism, metropolitan area. Seven hundred and eighty-six questionnaires hedonistic pleasure, aesthetic enjoyment, or emotional release.” were collected, of which 738 were usable. The response rate was This study proposes to combine informativeness and entertainment 48.4%. Given the nature of the study theme, only those who into a single construct, “perceived infotainment,” because the two indicated that they habitually use mobile handsets were selected. Of concepts are inseparable in terms of mobile users’ motives. For the 738 surveys collected, 590 were used for the analyses in this example, a recent survey reveals that as many as 50% of all i-mode research. users visit entertainment sites, such as games, screen savers, and The questionnaire consisted of two main sections. The first ring-tone downloads (Mizukoshi, Okuno and Tardy 2001). Fur- section included questions on respondents’ demographic character- thermore, another recent survey finds that as many as 72% of i- istics, such as age, gender, occupation, monthly disposable income, mode subscribers use mobile games (Infoplant 2003). In this vein, and monthly household income. In addition, data associated with Baldi and Thaung (2002) argue that mobile-delivered entertain- the habitual usage of email-magazines and email via mobile devices ment is a crucial factor in i-mode’s success in Japan. If pull-type was also collected, together with wired Internet connection fre- wireless ads are posted by credible advertisers and contain quency. The second section comprised measures of the major “infotaining” content, consumers who are actively engaged in constructs, including ongoing external search, perceived ongoing external search are more likely to encounter such informa- infotainment, perceived irritation, wireless content credibility, atti- tion and display a positive attitude to it, which leads to a positive tude toward wireless ads, and willingness to click. intention to “click” to the subsequent information sites. Our unit of analysis is the content of text banner ads in Tokusuru Menu on the official i-mode platform. Respondents were H5: Perceived infotainment is positively related to ongoing not asked to connect to Tokusuru Menu, but mobile screen pictures external search. of its front page were provided on the questionnaire, to show H6: Perceived infotainment is positively related to wireless respondents exactly what the questions were about, thereby en- content credibility. abling them to understand the questions better and to answer them H7: Attitude toward wireless ads is positively related to more accurately (Figure 2). perceived infotainment. All constructs proposed in this study were assessed using H8: Willingness to access is positively related to perceived multiple item scales. Most of the construct measures, except ongo- infotainment. ing external search, were adapted from prior research. Wireless content credibility was assessed on a five-item, seven-point seman- Similarly, irritation has been defined as the extent to which tic differential scale anchored “strongly disagree/agree.” This mea- consumers perceive the wired Internet as messy and irritating sure asked how reliable the wireless ads were in terms of their (Eighmey and McCord 1998). Similarly, “perceived irritation” content and advertisers (Choi and Rifon 2002; Lafferty and Gold- refers to a negative emotion induced by annoying text banner ads smith 1999). Perceived infotainment was assessed on a six-item, sent to mobile device. Ducofee (1999) contends that irritation seven-point semantic differential scale, by asking how helpful or negatively affects the ad value and attitude toward Web advertising. useful respondents thought the wireless ads were. Perceived irrita- If pull-type wireless ads come from unknown or untrustworthy tion was measured on how confusing or annoying the wireless ads source, consumers may become irritated in that he or she is wasting were (Chen and Wells 1999; Korgaonkar and Wolin 1999; Luo airtime to catch the message which may not be trustworthy. As 2002). Attitudes toward wireless ads were measured on a four-item, such, the following hypotheses associated with are offered: seven-point scale (“wireless ads are good/bad; favorable/unfavor- able; advantageous/not advantageous; wise/foolish”), and willing- H9: Perceived irritation is negatively related to wireless ness to click was examined on a two-item, seven-point scale (“If I content credibility. receive an interesting promotion to my mobile, I will access the sites H10: Perceived infotainment is negatively related to per- to check a further detail,” and, “If I see an interesting campaign on ceived irritation. my mobile, I will access the sites to apply for it”). For each H11: Attitude toward wireless ads is negatively related to construct, items were summed and averaged to create an index. perceived irritation. MEASUREMENT ASSESSMENT Lastly, “attitude toward wireless ads” acts as an antecedent of Table 1 summarizes the reliability and factorial validity for the “willingness to access.” Positive attitude toward wireless ads proposed scales. For all the constructs, Cronbach’s alphas were should lead to likely intention to access the subsequent information computed in order to assess the internal consistency of the scales. 8 / External Search, Content Credibility and Intrinsic Gratifiers Influencing Attitude Toward Wireless Ads FIGURE 2 Wireless Advertising Platform

Reproduced with permission of D2 Communications, http://www.d2c.co.jp

With one exception, all the constructs have a coefficient alpha through plots of ZRESID against ZPRED; and (3) independent superior to .80. Only “ongoing external search” has a coefficient errors through Durbin-Watson statistic. alpha below .70, perhaps because this scale was newly developed The model (1) tests Hypotheses 1, 3, 7 and 11, which examine for this study. Given the exploratory nature of the study, the the relation between attitude toward wireless ads and its four reliability scores are deemed to be relevant and adequate for the antecedents, ongoing external search, wireless content credibility, purposes of our study (Hair et al. 1998). perceived infotainment, and perceived irritation. The results sug- To test construct validity, a principal component analysis of gest that attitude toward wireless ads is strongly related to all wireless content credibility, perceived infotainment, and perceived antecedents, except ongoing external search. A stepwise regression irritation was conducted by the maximum likelihood extraction analysis found that 48.4 percent of the variance associated with method, with varimax rotation. In order to decide the number of attitude toward wireless is explained by perceived infotainment factors to be extracted and rotated in the model, three methods were (β=.413, t-value=8.63, p<.001), perceived irritation (β=-.251, t- used: 1) a cut point of .60 and no significant cross loading criteria, value=-7.50, p<.001), and wireless content credibility (β=.156, t- 2) scree plot tests, and 3) Eigenvalues greater than 1 and consider- value=3.36, p<.001), but ongoing external search was excluded. A ation of discontinuity (Hair et al. 1998). The principal component subsequent forced entry analysis, which included all four con- analysis yielded a clean four-factor solution after five rotations, structs, improved R-squared from .484 to .486. However, R- corresponding to the constructs of ongoing external search, wire- squared change for ongoing external search was statistically insig- less content credibility, perceived infotainment and perceived irri- nificant (β=-.045, t-value=-1.50, p=.135). Therefore, Hypotheses tation proposed in this study. The total variance explained by the 3, 7 and 11 were supported, while Hypotheses 1 was rejected. four factors is 80.27%. To validate the appropriateness of the Next, Hypotheses 4, 8, and 12 examine the relationship principal component analysis, two measures examined the entire between willingness to access, and the three antecedents: attitude correlation mix. First, Bartlett’s test of sphericity (p<.001) indi- toward wireless ads, wireless content credibility, and perceived cates the statistical probability that the correlation matrix has infotainment. As can be seen in Table 2, the model (2) was significant correlations among at least some of the variables. statistically significant at p<.001, indicating that our data strongly Second, the Kaiser-Meyer-Olkin measure of sampling adequacy support the basic proposition of behavioral intention to “click” (.908) showed superb sampling adequacy. As Table 1 indicates, all wireless ads. The R-squared (.449) is almost identical to the item loadings exceed .60 for each construct, demonstrating ad- adjusted value (.446), which indicates a good cross-validity of this equate convergent validity. model. Willingness to access is significantly related to attitude toward wireless ads (β=.333, t-value=8.17, p<.001), perceived RESULTS infotainment (β=.282 , t-value=5.41, p<.001), and wireless content A stepwise multiple regression analysis was conducted to test credibility (β=.143, t-value=2.95, p=.003). Therefore, Hypotheses the hypothesized relationships between the constructs (Table 2). 4, 8 and 12 were supported in this study, concluding that attitude Entering all variables in a single block, each time a predictor is toward wireless ads was found to be the most influencing predictor added to the equation, a removal test is made of the least useful of willingness to access. predictor. Looking at the significance value of the t-test for that Hypotheses 5, 6 and 10 investigate the links among perceived predictor assesses the contribution of each predictor. To draw infotainment, perceived irritation, and wireless content credibility. conclusions based on the regression analysis, it was assured that the As can be seen in Table 2, the model (3) explains as much as 62 per following assumptions have been met: (1) no perfect multicollinearity cent of the variance associated with perceived infotainment. per- through the average VIF and tolerance statistics; (2) homoscedasticity ceived infotainment is significantly and positively related to ongo- Asia Pacific Advances in Consumer Research (Volume 6) / 9 TABLE 1 Scale Reliability and Factorial Validity

Scale items Cronbach’s α Factor 1 Factor 2 Factor 3 Factor 4

Wireless content credibility .95 The content of wireless ads can be believed. .818 Promotional information on wireless ads can be trusted. .827 The campaigns offered in wireless ads meet my expectations. .802 The company sponsoring wireless ads has a good reputation. .810 Companies named in wireless ads keep their promises. .834

Perceived infotainment .95 I think wireless ads are informative. .691 I usually learn a lot from wireless ads. .706 Information I obtain from wireless ads is useful. .724 Wireless ads really entertain me. .847 I think the content of wireless ads is fun. .851 I feel excited when receiving wireless ads. .730

Perceived irritation .84 I find wireless ads irritating. .849 Wireless ads annoy me. .838 I find wireless ads confusing. .807

Ongoing external search .66 Fashion is always important to me. .714 I am anxious to try new products before my friends do. .773 Advertising always attracts my attention. .697 I collect a lot of information before I buy. .612 Eigenvalues 8.557 1.968 1.692 1.065 Percentage of variance explained 47.537 10.932 9.402 5.918 Cumulative percentage 47.537 58.469 67.871 73.789

Note: Extraction method: Principal component analysis. Rotation method: Varimax normalization with Kaiser. Suppress absolute values < .60

ing external search (β=.081, t-value=3.18, p=.002) and wireless ness to access was conceptualized as the consequences of wireless content credibility (β=.688, t-value=24.65, p<.001), but negatively content credibility, perceived infotainment and attitude toward associated with perceived irritation (β=-.177, t-value=-6.39, p<.001). wireless ads, while wireless content credibility, perceived Therefore, Hypotheses 5, 6 and 10 all gained support. infotainment, and perceived irritation are the antecedents of attitude The model (4) investigates Hypothesis 9, which addresses the toward wireless ads. This proposed model was tested with a relation between perceived irritation and wireless content credibil- multiple regression approach. Overall, our proposed model was ity. As seen in Table 2, the former was found to be a negative strongly supported by the empirical data obtained from non-student function of the latter (β=-.404, t-value=-10.69, p<.001). Thus, samples. Hypothesis 9 was supported. As far as the behavioral intention to access wireless ads, Finally, the model (5) relates to Hypothesis 2, which examines Japanese consumers are prone to heavily rely on “infotainment” the effects of ongoing external search on wireless content credibil- nature of wireless advertising. In assessing the willingness to ity. The proposed model explains only a small portion of the access, attitude toward wireless ads, wireless content credibility variance associated with wireless content credibility, although and perceived infotainment explain a moderate portion of the ongoing external search significantly affects the construct (β=.109, willingness to access (R2= .45). Yet, the main effect comes from t-value=2.67, p=.008). Thus, ongoing external search influences perceived infotainment (R2 change= .37), while the other con- wireless content credibility, but perhaps there should be other structs seem to exhibit only a marginal effect on users´ behavioral factors which influence the formation of wireless content credibil- intention. Similarly, attitude toward wireless ads was explained by ity. perceived infotainment, perceived irritation and wireless content Table 3 summarizes the results of hypotheses testing. credibility, being perceived infotainment a principal effect (R2 change= .42). These findings are consistent with prior research on DISCUSSION wired Internet adoption (Cheng and Wells 1999; Lin 1999). As This study attempted to explore the influence of wireless Choi et al. (1997) argue, the basic concept of digital content creation content credibility, perceived infotainment, and perceived irritation in wireless Internet seem similar to that in wired Internet. That is, on attitude toward wireless ads and willingness to access. Willing- the content of text banner ads for delivery via the wireless Internet, 10 / External Search, Content Credibility and Intrinsic Gratifiers Influencing Attitude Toward Wireless Ads TABLE 2 Results of Multiple Regression Analysis

Proposed model R2 R2 change β

(1) Attitude toward wireless ads A=OES + PINF + WCC + PIRR + errors .484a OES - -.045 PINF .420*** .413*** PIRR .054*** -.251*** WCC .010*** .156***

(2) Willingness to access W=A + INF + WCC + errors .449*** A .072*** .333*** PINF .369*** .282*** WCC .008** .143**

(3) Perceived infotainment PINF=OES + PIRR + WCC + errors .622*** WCC .590*** .688*** PIRR .026*** -.177*** OES .007** .081**

(4) Perceived irritation PIRR=WCC + errors .163*** -.404***

(5) Wireless content credibility WCC=OES + errors .012** .109**

Note: a R2 value from a forced entry regression analysis, which was statistically significant at p<.001. OES: Ongoing external search, WCC=Wireless content credibility, PINF=Perceived infotainment, PIRR=Perceived irritation, A=Attitude toward wireless ads, W=Willingness to access. ** p<.05 *** p<.001

TABLE 3 Hypotheses Testing

Hypotheses Results

H1: Attitude toward wireless ads is positively related to ongoing external search. Not supported H2: Wireless content credibility is positively related to ongoing external search. Supported H3: Attitude toward wireless ads is positively related to wireless content credibility. Supported H4: Willingness to access is positively related to wireless content credibility. Supported H5: Perceived infotainment is positively related to ongoing external search. Supported H6: Perceived infotainment is positively related to wireless content credibility. Supported H7: Attitude toward wireless ads is positively related to perceived infotainment. Supported H8: Willingness to access is positively related to perceived infotainment. Supported H9: Perceived irritation is negatively related to wireless content credibility. Supported H10: Perceived infotainment is negatively related to perceived irritation. Supported H11: Attitude toward wireless ads is negatively related to perceived irritation. Supported H12: Willingness to access is positively related to attitude toward wireless ads. Supported Asia Pacific Advances in Consumer Research (Volume 6) / 11 such as the i-mode service, needs to combine two of the major Batra, R., Myers, J. G. and Aaker, D. A. (1996) Advertising constructs from uses and gratifications theory: informativeness and Management (5th ed.). Upper Saddle River, NJ: Prentice entertainment. On the other hand, it was somehow surprising that Hall. individuals’ effort in a continuous information search had no effect Bloch, P.H., Sherrell, D.L. and Ridgway, N.M. (1986), “Con- on attitude toward wireless ads. The reason for this being that sumer search: An extended framework,” Journal of Con- mobile users may be more sensitive to subjective norms, rather than sumer Research, 13 (June), 119-126. the individual level of information seeking, with regard to their Chen, Q. and Wells, W.D. (1999), “Attitude toward the site,” adoption of the technology. Providing the Japanese cultural ten- Journal of Advertising Research, 39 (5), 27-37. dency toward collectivist conformity, normative beliefs from im- Choi, S. Y., Stahl, D.O. and Whinston, A.B. (1997), “Interme- portant friends, colleagues, or family members may be a strong diation, Contracts and Micropayments in Electronic basis for their information source (Barnes and Huff 2003). Commerce,” Electronic Markets Newsletter, 4, Available One implication of this research is that marketing managers from http://cism.bus.utexas.edu/works/articles/em.html. should look carefully at whether an “infotaining” content should be Choi, S.M. and Rifon, N.J. (2002), “Antecedents and conse- sought at the cost of timely and necessary information. Although quences of Web advertising credibility: A study of consumer aggressively linking up the wireless advertising platform with eye- response to banner ads,” Journal of Interactive Advertising, 3 catching, attention-getting games, coupons, ring-tone downloads, (1). Available http://www.jiad.or/. et cetera. may produce a higher click-through in the short term, this Computer Times (2002), “Promoting or trespassing? Credibility could harm evaluations of the content, and by implication, the is crucial if marketing via SMS is to succeed,” IT Asiaone, sponsors’ reputation in the long term. The obvious analogy is with January 16, Available: http://it.asia1.com.sg/specials/m- the explosive emergence of the wired banner ads, which provided spam20020116_003.html/. numerous lessons to be learnt from mistakes. This study urges D2 Communication (2002), “Our lines of business,” Available: marketing managers to heed those lessons, if they are to succeed in http://www.d2c.co.jp/english/business_e/ main.html the wireless Internet. Ducoffe, R.H. (1996), “Advertising value and advertising on the Web,” Journal of Advertising Research, 36 (5), 21-35. LIMITATIONS AND FUTURE RESEARCH Eighmey, J. (1997), “Profiling user responses to commercial DIRECTIONS Web sites,” Journal of Advertising Research, 37 (2), 59-66. Although this study provides significantly new insights, it is Eighmey, J. and McCord, L. (1998), “Adding value in the not without its limitations. One limitation of the current study is that information age: Uses and gratifications of sites on the World only a limited number of question items were included in the Wide Web,” Journal of Business Research, 41, 187-194. survey. Future research should expand on the current findings by Hair, J.F, Jr., Anderson, R.E., Tatham, R.L. and Black W.C. using more comprehensive sets of constructs to identify factors (1998), Multivariate Data Analysis, Englewood Cliffs, NJ: affecting the adoption of wireless advertising. Second, although Prentice Hall. inserting a photographic image of wireless advertising platform in Hawkins, D.I., Best, R.J. and Coney, K.A. (2001) Consumer the questionnaire provided a reasonable validity to the findings, the Behavior: Building Marketing Strategy. New York, NY: respondents’ answers may have been left to their imagination. In McGraw-Hill. this vein, some experimental studies are needed to test their “true” Hoyer, W.D. and MacInnis, D. (2001), Consumer Behavior (2nd intentions to access wireless advertising. Finally, this study adopted ed.), Boston, MA: Houghton Mifflin. many measures from prior research on wired Internet. However, Info plant (2003), “Keitai denwa de geemu wa yuuzaa no while it is important to extend existing theories to explain mobile nanawari” (Seventy percent of mobile users enjoy gaming), innovation diffusion outcomes, more rigorous efforts should be Available: http://www.info-plant.com (in Japanese). made in focusing on important differences, rather than similarities, Katz, E., Blumler, J. G. and Gurevitch, M. (1974), “Utilization between wired and wireless advertising adoption. of mass communication by the individual,” The uses of mass communications: Current perspectives on gratifications ACKNOWLEDGEMENTS research, eds. J. G. Blumler and E. Katz, Beverly Hills, CA: The author thanks the Yoshida Hideo Memorial Foundation Sage. (Tokyo) for providing financial support for this project, as well as Korgaonkar, P.K. and Wolin, L.D. (1999), “A multivariate Dentsu Research (Tokyo) for their data collection. analysis of Web usage,” Journal of Advertising Research, 39 (2), 53-68. REFERENCES Lafferty, B.A. and Goldsmith, R.E. (1999), “Corporate Balasubramanian, S., Peterson, R.A. and Jarvenpaa, S.L. (2002), credibility’s role in consumers’ attitude and purchase “Exploring the implications of M-commerce for markets and intentions when a high versus a low credibility endorser is marketing,” Journal of the Academy of Marketing Science, used in the ad,” Journal of Business Research, 44, 109-116. 30 (4), 348-361. Lin, C. (1999), “Online-service adoption likelihood,” Journal of Baldi, S. and Thaung, P.P. (2002), “The entertaining way to M- Advertising Research, 39 (2), 79-89. commerce: Japan’s approach to the mobile Internet–A model Lu, F., Yu, C.S., Liu, C. and Yao, F.E. (2003), “Technology for Europe?” Electronic Markets, 12 (1), 6-13. acceptance model for wireless Internet,” Internet Research, Barnes, S.J. (2002), “The mobile commerce value chain: 13 (3), 206-222. Analysis and future developments,” International Journal of Luo, X. 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(2002) M-Commerce: Technologies, services, and business models. New York, NY: John Wiley and Sons. Watson, R.T., Pitt, L.F., Berthon, P. and Zinkhan, G.M. (2002), “U-commerce: Expanding the universe of marketing,” Journal of the Academy of Marketing Science, 30 (4), 333- 347. Habit as a Key Predictor of Internet Email Behavior Desmond Lam, University of Western Australia, Australia Dick Mizerski, University of Western Australia, Australia

ABSTRACT Habitual behaviors are now thought to be an important com- Habit is an important component of consumer behavior and is ponent of consumer brand loyalty (Olsen 1995; East 1997). When often used interchangbly with the effect of past behavior. One of the one considers consumers in aggregate, one will find that many simplest models that provides a good representation of consumer consumer markets are relatively stable and appear to follow some behavior for repetitive choices is the Negative Binomial Distribu- simple empirical marketing laws (Ehrenberg 1971). This means it tion (NBD) model. This exploratory study investigated the ability is common to find regularity in the behavior of consumers (East of the NBD model to explain reported Internet email behavior. It 1997) in their frequency of patronage and purchasing (Ehrenberg found that the model was able to provide a good fit to the online 1972, 1988). Consumers are said to have habits when they repeat- behavioral data. Moreover, the study found no differences in edly produce the same behavior under similar contexts (East 1997). demographics, psychographics, Internet use and perceptions be- According to Ehrenberg (1988), consumers’ tendencies to produce tween light and heavy email user groups. The implications of these such repeated behaviors can be modeled as a stochastic process findings to marketing and Internet policies were discussed. without referring to any cognitive components. For example, Kanvil and Umeb (2000)’s study on consumers’ motivation to smoke INTRODUCTION cigarettes found that past behavior explained most (70%) of the The Internet is probably the fastest growing medium in the variation, and that health cognitions explained only a small propor- human history. It offers many benefits to the modern community tion (3%) of that variation. In another example, Barwise and and may be the most widely-used medium for communication. Ehrenberg (1988), in their study of television viewing, found the According to Nua Internet survey, there are now more than 600 daily pattern of television viewing across large populations very million Internet users worldwide (Nua.com, 2003). The figure has steady over different days. According to them, there was a tendency been growing at an exponential rate since the last decade. This rapid for people who view television at one period to also view at the next adoption of the Internet has greatly increased the amount and period (Ehrenberg 1971). diversity of information online (Levene and Poulovassilis, 2001). Models that analyze patterns of human behavior are com- According to eMarketer, the worldwide ecommerce revenues are monly known as stochastic preference models (Morrison and expected to total US$ 2.7 trillion by 2004 (Nua.com 2003). While Schmittlein 1988; Wagner and Taudes 1987). These models are about 70 percent of companies in U.S. have experimented with often very accurate in describing past usage and predicting future purchasing online, only less than 10 percent of their total spending responses simply based on observed or reported behavior. One of is currently being channeled via the Internet. Thus, it seems that the simplest and most widely-reported stochastic models that faced with the explosive growth of the Internet and e-commerce, provides a reasonable representation of observed consumer buying marketers and policymakers are still investigating the optimal ways patterns is the Negative Binominal Distribution (NBD) model. The to use and regulate this relatively new business and communication NBD model, first examined by Greenwood and Yule (1920) in medium (Sheehan and Hoy 2000). To date, the majority of research terms of the incidence of recurring diseases and accidents, was on consumers’ behavior on the Internet have been from a psycho- introduced to marketing by Andrew Ehrenberg in 1959. It is a logical point of view, focusing on cognitive factors such as attitudes simple mathematical model used to predict repeat purchases using toward websites (Balabanis and Vassileiou 1999) and toward information on the penetration, purchase frequency, and period Internet advertising (Kwak, Fox, and Zinkhan 2002), shopping (East 1997). The NBD model is also the basis of the Dirichlet experiences and search (Ward and Lee 2000), influences of online model, which is used to predict brand shares in a product category information (Chatterjee 2001), website brand loyalty (Holland and (Uncles and Ehenberg 1990). Both the NBD and the Dirichlet Baker 2001), trust and reputation (Xu and Yadav 2003), and models have been applied to a wide range of goods and services perceptions toward email (Gefen and Straub 1997; Gattiker, Pedersen (Uncles, Ehrenberg and Hammond 1995), and have demonstrated and Perlusz 2002; Marinova, Murphy and Massey 2002). However, the existence of stable buying propensities of frequently-purchased there is no reported empirical-based research on the effect of products in stationary markets (Morrison and Schmittlein 1988). habitual responses on users’ Internet behavior. This study will use Despite the ability to explain and predict market phenomenon, the a stochastic paradigm to explain online consumer behavior. “plain-vanilla” NBD model does not require the inputs of any marketing (e.g. pricing or promotion expenditures) or attitudinal HABITUAL BEHAVIOR AND THE NBD MODEL (e.g. perceptions, beliefs or intentions) variables. It provides a While habitual behavior has been studied for well over eighty probability density function that is based solely on the penetration years (i.e. Watson 1919, and Allport 1924) and is viewed as an of the market (i.e. percent of the population purchasing), the important component of consumer behavior, the effect of habits is average frequency of those that purchase, and the time period over often overlooked in marketing. Triandis (1977) defines habitual which the purchase is reported. behavior as equivalent to past behavior due to its repetitive nature. Although each individual in a market may use a cognitive basis He included habit in his attitude-behavior model as a joint predictor for their decision, the population of individuals can often be of intention to future behavior. Allport (1985) also see habit as a accurately described with a stochastic model using only past basic driver of behavior, which can be defined by “choose what one behavior (Ehrenberg 1972). The patterns of behavior predicted or chose last time” heuristic (Bettman, Johnson, and Payne 1991). derived by an NBD model can be used to gauge the impact of Many recent researchers have now used habit interchangeably with marketing activities by providing a baseline for buyers and their past behavior and have recognized the importance of habits in usage. This baseline forms the “benchmark” for comparing with humans’ everyday lives (East 1997; Ouellette and Wood 1998). data about that behavior under conditions of these marketing

13 Asia Pacific Advances in Consumer Research Volume 6, © 2005 14 / Habit as a Key Predictor of Internet Email Behavior activities. In a sense, the NBD reflects the influence of past, hence users could differ in their Internet use according to their locus of habitual, repetitive behavior in a market. As noted earlier, past control requirement (Hoffman, Novak and Schlosser 2003). While behavior or habit is seen as the major cause of future behavior no research has been conducted that studied the differences be- (Ouellette and Wood 1998). tween light and heavy email users in terms of their reported general Like many consumer products and media use, Internet usage Internet perception toward privacy and general usage pattern, one may have reached a relatively high frequency of repetitious behav- expects these factors to have no significant effects on email usage ior (Said and Mizerski 2002) since its mass adoption in the early behavior in an NBD-or habit-driven environment. Thus, 1990s. The markets for frequently-purchased products may reach maturity within a relatively short time frame. For example, a study H3: There will be no significant differences between the light by Mizerski and Mizerski (2001) found the U.S. Florida’s lotto and heavy email users in their reported Internet use and market had reached maturity within the first three years of its perceptions toward privacy. introduction and a stochastic pattern of play was established within the first six months of Lotto introduction. Hence, one may also Internet users’ cultural and personal values may also affect expect consumers’ Internet email usage to have reached a relatively their behavior on the Internet. For example, Chau et al. (2002) found stationary condition such that it may follow the same NBD pattern significant behavioral differences between Internet users from of behavior. This behavior, on an aggregate level, may reflect an Hong Kong and U.S.A. Similarly, Hoffman, Novak and Schlosser underlying stochastic pattern often observed in many consumer and (2003) found that consumers on the Internet behaved differently industrial markets involving frequent purchases of multiple brands according to their locus of control. However, in a habit-driven (Ehrenberg 1972; East 1997). A strong habitual response may environment, the effect of past behavior is expected to predomi- provide a better empirical explanation of Internet email behavior nant. If the Internet email environment is in fact driven by habits, the than demographics and/or the other more cognitive paradigms effects of cultural and personality values are expected to conform (Ehrenberg 1959; Ehrenberg et al. 1994; East 1997). Hence, this to the NBD-based expectations. Hence, study will investigate whether the NBD fits reported email behavior and provide an alternative explanation of Internet behavior. H4: There will be no significant differences between light and heavy email users in term of their cultural dimensions and HYPOTHESIS locus of control. The objective of this study is to determine if there is evidence to support that Internet email behavior follows a habitual pattern METHODOLOGY and, hence, conforms to the NBD model. As mentioned earlier, the The data used for this study (n=122) was collected from a NBD model had been used in numerous occasions and, in most convenience sample of undergraduates. A survey was used to cases, the NBD model fitted the data very well and was able to measure their students’ perceptions and reported behavior when forecast future behavioral patterns with high accuracy (Ehrenberg using the Internet. The respondents were business undergraduates 1971; East 1997). If an NBD is applied to Internet email behavioral at an Australian university. The age of the respondents ranged from data, then one will expect no significant differences between the 18 to 31 years old, with a median age of 21 years old. Approximately proportion of users derived from the NBD model and the reported 62% of the respondents were female. or observed data. Hence, Each respondent was given a questionnaire with items on their cultural values, external locus of control, Internet perceptions, and H1: There will be no significant difference between the their email behaviors. In order to obtain data on Internet email usage reported proportion of email use and the expected NBD. behavior, the respondents were asked to state the number of emails they have forwarded and sent in the last 24 hours. These two items Moreover, one closely associated theme to the NBD patterns formed the dependent variables in this study. Information on is that there are usually few or no demographic differences between demographics was also collected, which included age, gender, the light and heavy users. For example, Barwise and Ehrenberg number of years on the Internet, and number of years in Australia. (1988) found that there was very little variation in the way different The respondents also provided information on their cultural values, subgroups of the population allocate their viewing across the personal values in terms of external locus of control, and Internet different program categories. The composition of the audience for perceptions and usage. These items were measured on a 1 (strongly most programs was similar in demographics or television-usage disagree) to 5 (strongly agree) scale. The items on Internet privacy terms and these programs were positively liked by nearly all of their and usage were adapted from ninth’s GVU’s WWW survey (1998). viewers except a few. Such observations of indifferences were in- The items on cultural values were adapted from Dorfman and line with those reported by other behavioral researchers such as Howell (1988), which were based on Hofstede (1966)’s four main Hammond et al. (1996).One will find that in any stochastic or habit- cultural dimensions, namely, Individualism, Uncertainty Avoid- driven processes where the effects of past behaviors are strong and ance, Masculinity, and Power Distance. The items on locus of predominated over other factors such as demographics. Hence, control were selectively adopted from Levenson (1974)’s original scale and measured the extent of external locus of control. The locus H2: There will be no significant differences between light and of control construct is one of the most widely-studied personality heavy email users in their reported age, gender, and concepts (Matsumoto 2000). People can differ in term of how much number of years on the Internet. control they believe they have over their behavior and their environment. In locus of control concept, outcomes are seen either as Internet users’ perception towards online privacy may poten- dependent on one’s own actions or determined by fate, chance or tially affect their behavior on the Internet (Korgaonkar and Wolin powerful others (Rotter 1966). 1999). About 69% of consumers in a recent survey did not use the A series of factor analysis and subsequent reliability tests were Internet for commercial purposes because they were afraid that performed on these items with the results shown in table 1 below. their personal information would not be kept private (NFO Interac- The obtained alphas ranged from 0.540 to 0.862. According to tive 1999). Moreover, some researchers had found that Internet Nunnally (1967), reliabilities in the range of 0.5 to 0.6 are satisfac- Asia Pacific Advances in Consumer Research (Volume 6) / 15 tory in the early stages of research. Hence, the obtained coefficients rally, one would expect little differences between the groups were deemed sufficient given the exploratory nature of this study. because of the clear evidence of stochastic pattern. The lack of The variables were obtained by taking simple averages of the significant differences on all but one of these independent variables constituted items. supports the second (hypothesis 2) and fourth (hypothesis 4) hypotheses. While the third hypothesis (hypothesis 3) was sup- ANALYSIS AND FINDINGS ported in the case of Internet email forwarding, it was not so in the The NBD analysis was conducted using software obtained case of Internet email sending. Nevertheless, the overall findings from Wright (1999). Three variables are required in each NBD had provided sound evidence for a stochastic or habitual pattern in analysis, namely, the penetration, the frequency of use and the Internet email use. period of use. The penetration figures for the reported observed and the NBD expected Internet email use were obtained, along with the DISCUSSION AND CONCLUSION average number of emails forwarded and sent. For the case of The results have shown that the NBD model fit the reported Internet email forwarding, the penetration was 34.4% (out of 122 Internet email use. Moreover, except for a single case, there were no respondents) with an average frequency of 6.45 emails. Internet significant differences between the light and heavy users in terms email sending had a much higher penetration of 76.9% (out of 122 of their demographics, cultural values, personal values, Internet respondents) and an average frequency of 5.85 emails. The fit of the usage and perceptions. In essence, the two user groups in each case each NBD model was tested with a regression analysis, comparing appear to be very similar except for the number of emails that they the observed distributions to the NBD-derived theoretical distribu- forwarded or sent. These findings reinforce the proposition that tions (Morrison & Schmittlein 1988). The correlations were rela- online behavior such as forwarding and sending emails appears to tively high for both cases of Internet email forwarding and Internet reflect a stochastic process much like product purchases in matured email sending; R=0.695, p<.001 for email forwarded and R=0.895, markets (Ehrenberg 1959), television viewing (Goodhardt et al. p<.01 for email sent (see figure 1). The results showed that there 1975; 1987) and gambling behavior (Mizerski, Mizerski and Miller were some deviations between the observed and NBD-derived 2000). distributions. These deviations may be largely the result of respon- While the Internet is a relatively new medium, past studies dents simplifying their reporting by rounding up their answers, have shown that rapidly-evolving industries may show sign of which is an apparent weakness of self-reporting survey on usage maturity quickly within a few years of introduction (Mizerski and (Nisbett and Wilson 1977). Nonetheless, the results support the Mizerski 2001). The fact that online habitual effects were detected existence of potentially strong habitual effect of Internet email use. now meant that one would likely to see even stronger habitual The respondents were then median split into light and heavy effects on the Internet in future. That there is an NBD pattern of users in terms of both Internet email forwarding (median=3 emails) reported online behavior has important implications to marketers and sending (median=4 emails). Chi-square statistics were used to and Internet policy makers. The findings suggest that habit or past test for the goodness-of-fit between the observed and theoretical/ behavior is a strong driver of Internet email usage behavior. An NBD-derived distributions. Table 2 summarizes the results of the earlier study by Jolly (2003) on the relative strength of habit and tests. No significant differences were found in both cases (p>.05). cognitive-based intentions in online gambling had shown that the The finding, hence, supports first hypothesis that there is a strong habit construct had greater explanatory and predictive power then habitual element in Internet email use. cognitions. A strong habitual response suggests that changing the Given the close approximations of the NBD to reported email patterns of Internet email use may be very difficult. user distributions, one may suspect that the demographics, cultural For government policy makers or corporations alike who want and personality background of the light and heavy user groups to to encourage the adoption of the Internet email system as the major have strong effects on the results. Table 4 and 5 show the results of communication tool so as to achieve a paperless environment, these comparisons between the light and heavy user groups in terms of findings have several implications. To encourage a change in online these variables using MANOVA. Prior to that, a multiple analysis habits, they will need to implement strategies to initiate the habit of of covariance (Table 3) was performed with the demographic using emails as a main source of communication. It is understand- variables age, number of years of online experience, and number of able that in a habitual environment, any cognitive-based strategies years in Australia treated as potential covariates and tested for will not likely to be effective. This is based on extensive research potential effects over other variables. No significant effects were on promotion efforts with NBD-type markets such as the consumer found (p>.05). packages good (c.f. Ehrenberg et al. 1994) where few examples of Given the insignificant effects of these possible covariates, a success can be found. The success of traditional advertising or final MANOVA was conducted including all the variables so as to communication methods, by working through the buyers’ cognitive compare the differences between light and heavy user groups in structure, has had little support for long-term brand building in both cases of Internet email forwarding and sending. The results of NBD-type markets (Barwise & Ehrenberg 1988). The usual gener- the MANOVA are shown in Table 4 and 5 below. A chi-square test alization in NBD markets is that one should increase penetration of was also performed to test for the gender differences between the the market and frequency of purchase will follow (East 1997). In groups in both cases. The results showed no significant differences order to promote email usage, regulators may have to provide in either cases (p<.05). For the case of email forwarded, 41% of incentives strong enough to switch behavior such as encourage light users were male as opposed to 35% among the heavy users quicker tax return if annual tax filing are done through the Internet (X2=0.155, df=1, p=.694); for the case of email sent, 40.4% of light email system or make departmental queries significantly faster users were male as opposed to 42% among the heavy users through emails. Based on reinforcement theory, the purpose is to (X2=0.011,df=1,p=.916). encourage email usage through incentives, stimulating a new habit Interestingly, the comparison between the light and heavy user or switching from an old one for a given period of time such that groups in both cases did not yield any significant differences when incentives are retracted, new behavior still follows. (p>.05) in demographics (hypothesis 2), and cultural and personal Very often, the desire of corporations as well as government values (hypothesis 4). However, Internet usage appeared to be Internet public policy makers is to stop the forwarding of nuisance different between light and heavy groups of email senders. Natu- emails on a massive scale such as spamming and deadly Internet 16 / Habit as a Key Predictor of Internet Email Behavior TABLE 1 Variables along with their factor and reliability tests results

Factor Cronbach's % Vsariable Item Eigenvalue Loading Alpha Variances

I am concerned that someone could be reading my 0.937 emails on the Internet. 1) Concern for Internet Privacy 07.862 13.75 87.84 I am concerned that someone could be monitoring 0.937 what I do on the Internet. I0use the Internet for research pertaining to studies. 0.64

I1use the Internet to communicate with others. 0.81 2A) Usage 1 I7use the Internet to gather product information. 0.74 04.654 23.76 46.07 Internet Usage I9use the Internet for educational purposes. 0.77 I9use the Internet for entertainment purposes. 0.72 2.B) Usage 2 I4use the Internet to meet new people 0-.93 17.12 418.73 Group welfare is more important than individual 0.785 rewards.

Group success is more important than individual 3A) Collectivism 0.802 01.540 18.80 11.25 success. Individual may be expected to give up their goals in 0.529 order to benefit group success. It is important to have task requirements and instructions spelled out in detail so that those who are 0.600 working on the tasks always know what they are expected to do.

Rules and regulations are important because they 3B) Uncertainty inform those are working what the organization 0.570 00.543 19.91 11.93 Avoidance expects of them. Hofstede's Standard operating procedures are helpful to those on Cultural 0.409 Dimensions the job. Instructions for operations are important for those on 0.767 the job.

Meetings are usually run more effectively when they 0.823 are chaired by a man. Solving difficult problems usually requires an active 3C) Masculinity 0.733 06.700 27.27 14.22 forcible approach which is typical of men. It is important for men to have a professional career 0.707 than it is for women.

Those in charge should make most decisions without 0.667 consulting those who are not. 3D) Power Distance 06.588 27.03 12.72 Those not in charge should not disagree with the 0.673 decisions of those in charge.

To a great extent, my life is controlled by accidental 0.699 happenings.

When I get what I want, it's usually because I'm 0.626 lucky. It's not always wise for me to plan too far ahead 4) External Locus of Control 04.764 25.51 41.89 because many things turn out to be a matter of good 0.658 or bad luck. I feel like what happens in my life is mostly 0.778 determined by powerful people. M0y life is chiefly controlled by powerful others. 0.77 Asia Pacific Advances in Consumer Research (Volume 6) / 17 FIGURE 1 NBD-derived results versus observed data for forwarding and sending emails

TABLE 2 Statistical test of significance between observed and NBD-derived results

Observed NBD-derived Vpariable Grou (%) (%)

No. of emails forwarded in last L4ight user (1-3 emails) 532. 52. 24 hours H6eavy user (>3 emails) 477. 47. χ2=0.000, df=1, p=.988

No. of emails sent in last 24 L9ight user (1-4 emails) 585. 54. hours H1eavy user (>4 emails) 424. 45. χ2=0.054, df=1, p=.817

TABLE 3 Effects of Covariates

Veariables WFfilks’ Lambda Valu H.ypothesis d Sig

A0ge 02.90 05.71 17.76 N3o. of years in Australia 03.82 15.37 16.17 N0o. of years online 07.81 15.49 12.12

viruses. The current findings will help them to implement more to the governmental control on compulsive gambling and alcohol effective policies. Generally, more heavy-handed behavioral-based drinking. methods such as fines will be needed to discourage or prevent the Despite the conclusions, the results that were based on a habits of forwarding such emails. Online advertising or warning relatively small sample size should also be read with caution. messages are unlikely to have any significant effects. The discovery Extrapolation of the results must be made cautiously given that the of a strong habitual behavior in email use would provide support for current exploratory study was conducted on a single country and tougher legislations and more governmental control over the Internet only represented by a sample of higher-education student popula- as opposed to the self-regulatory frameworks adopted by many tion. While the NBD model was able to explain the proportion of western countries such as Australia and USA. This is much similar email activities, these results were based on self-reports. These 18 / Habit as a Key Predictor of Internet Email Behavior TABLE 4 MANOVA results for the case of forwarding Internet email

Vrariables Lright Use HF.eavy Use Sig

A0ge 201.25 292.20 16.38 .24 N9o. of years in Australia 76.76 67.64 08.18 .66 N0o. of year online 66.15 74.24 21.26 .14

15) Concern for Internet Privacy 30.22 36.35 06.10 .74

20A) Usage 1 40.21 38.95 04.95 .33 Internet Usage 20B) Usage 2 20.50 28.90 09.93 .33

33A) Collectivism 33.23 34.18 08.05 .81 3B) Uncertainty 35.762 34.67 06.21 .64 Hofstede's Cultural Avoidance Dimensions 37C) Masculinity 25.81 29.72 07.08 .76 30D) Power Distance 25.20 22.62 16.73 .19 40) External Locus of Control 20.50 29.64 00.32 .57

TABLE 5 MANOVA results for the case of sending Internet email

Vrariables Lright Use HF.eavy Use Sig

A0ge 271.00 261.70 11.99 .16

N9o. of years in Australia 191.37 97.45 10.08 .30

N7o. of year online 68.03 60.87 35.25 .07

10) Concern for Internet Privacy 22.82 39.23 23.70 .10

20A) Usage 1 42.18 48.10 00.24 .62 Internet Usage 20B) Usage 2 23.04 26.68 60.97 .01

37A) Collectivism 33.24 34.07 12.51 .22 3B) Uncertainty 31.775 38.67 00.99 .32 Hofstede's Cultural Avoidance Dimensions 37C) Masculinity 29.32 24.67 25.85 .09 30D) Power Distance 29.09 22.32 19.67 .19 47) External Locus of Control 29.45 23.44 07.00 .95

types of data have a tendency to produce “lazy survey responses” examined in this study. Moreover, Internet users’ behaviors may (Nisbett and Wilson 1977). Future research will attempt to measure change depending on the types of product or corporate emails that “real-time” behavior of an enlarged number of participants in order they received. Research into these areas will likely to provide to enhance internal and external validity. Furthermore, the support further insights to current study. If Internet users’ email usage of the NBD does not rule out other explanations and theoretical follows an NBD pattern of behavior, one may also suspect these paradigms (cf. East 1997) of Internet behavior. Situational or users’ online purchasing behavior to conform to the stochastic contextual effects and other personality constructs have not been theory. 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TaiWoong Yun, The University of Texas at Austin, U.S.A. Wei-Na Lee, The University of Texas at Austin, U.S.A.

ABSTRACT External information search encompasses both goal-directed, There is little doubt that the Internet contributes to, and will prepurchase activities and ongoing search activities (Peterson and continue to affect, consumer information search. However, a Merino, 2003). Most research on information search has focused on comprehensive understanding of what motivates and mediates prepurchase search which involves consumer’s cognitive effort to information search behavior on the Internet is relatively lacking. reduce uncertainty (Beatty and Smith, 1987; Punj and Staelin, This study sought to identify antecedent factors affecting external 1983). Meanwhile, ongoing search is generally considered to be search on the Internet in a multivariate setting. The study found that related to nonfunctional motives such as entertainment (Bellenger subjects with high situational involvement, low objective knowledge, and Korgoankar, 1980; Holbrook and Hirschman, 1982) and prod- and no purchase experience were likely to spend more time and uct interests (Bloch, Sherrell, and Ridgway, 1986). For example, consider a larger number of brands during search. The study also Bloch et al. (1986) found that the perceived enjoyment of shopping found that subjects with high objective knowledge examined a and enduring involvement are related to ongoing search and that larger set of attributes than those with low objective knowledge. heavy ongoing searchers tend to be heavy spenders within the product class. INTRODUCTION However, few researchers have attempted to develop a causal Information search is an integral part of consumer decision model to delineate the relationships among these factors for making process. The Internet contributes to this function by provid- information search behavior (Moore and Lehmann, 1980; Punj and ing an efficient and convenient tool to search for vast amount of Staelin, 1983; Schmidt and Spreng, 1996). Most of the empirical product or service related information (Haubl and Trifts, 2000). studies have examined direct effects of various antecedents on While the Internet is quickly becoming a major source of informa- information search in bivariate situations (Guo, 2001; Lee and tion, it is also evolving into a significant channel for business Hogarth, 2000). While the direct relationship between external transaction and distribution (Peterson, Balasubramanian, and search and its determinants is in and of itself important to Bronnenberg, 1997). A recent report estimates that online retail understanding consumer information search behavior, the complex revenue will grow from $95.7 billion in 2003 to $229.9 billion in nature of information search behavior will require investigating the 2008 which will account for 10% of total retail sales (Forrester relationships between various factors and information search in a Research, 2003). multivariate setting. External information search is influenced by a With the increasing popularity of the Internet, more consumers number of determinants and, in a multivariate setting, the magnitude are using the Internet for information search than before. In a and direction of the relationships between search and antecedents national survey with online consumers, Burke (2002) found that will vary. Several researchers have argued that ability, motivation, those consumers used the Internet mainly for information search and cost and benefit mediate the effects of various antecedent (93%) and comparing and evaluating alternatives (83%). Most factors on information search activities and suggested models for recently, Ratchford, Lee, and Talukdar (2003) showed that among testing (Punj and Staelin, 1983; Srinivasan and Ratchford, 1991). those who recently purchased a new car, 39% used the Internet to obtain product information. As more and more consumers search Information Search on the Internet for information online, marketers need to better understand this The Internet provides benefits to consumers by offering phenomenon in order to help aid consumers in their decision- powerful search and screening tools (Haubl and Trifts, 2000), an making. Although several attempts have been made to provide a abundance of product information (Dholakia and Bagozzi, 2001; conceptual model for examining consumer online information Peterson and Merino, 2003), and a wide range of product selections search (Klein, 1998; Peterson and Merino, 2003; Rowley, 2000), and prices (Bakos, 1997). With the increasing popularity of the empirical studies in this area are still lacking. Internet as a viable information source and a transaction channel, Hence, the purpose of the study is to empirically examine what researchers have begun to turn their attention to the nature of factors affect consumer online information search. These factors information search on the Web either by examining information include Internet specific variables (i.e., Internet skills, online pur- search patterns on the Web (Hölscher and Strube, 2000) or by chase experience, Internet attitude) along with other personal, exploring factors affecting online information search (Klein and situational, and media-related variables. Ford, 2002; Liang and Huang, 1998). These two streams of research suggest that there are different patterns of information search on the LITERATURE REVIEW Web and, more importantly, there seem to be several additional factors (e.g., shopping attitude, experience, perceived control and Information Search Behavior skills, Internet availability) that influence consumer information Consumers engage in both internal and external search for search activities on the Web. These researchers, however, have product information (Newman, 1977). Internal information search focused on a limited set of factors and therefore fall short of involves consumer retrieval of memory that stores product knowl- providing a comprehensive understanding of what motivates edge. External information search refers to activities other than consumers to navigate the Web for shopping purposes. memory, such as consulting with salespeople, friends, reading other Although the general models from traditional information sources, looking at ads, direct observation and so on. Consumers search studies provide a good starting point for investigating often employ both types of search in a sequential and iterative information search behavior in an online environment, several fashion when making purchases. factors of particular relevance to the Internet may need to be

developed. These factors include characteristics of the Internet Mothersbaugh, and Feick, 1994). Objective knowledge is related to (e.g., accessibility, interactivity, flow, customization) and Internet specific product information and consumers with high objective skills and experience (Liang and Huang, 1998; Ratchford, Lee, and knowledge have a well-organized information structure and rich Talukdar, 2003). product information which enable them to comprehend and process As discussed, there are a number of factors that may affect external information easier (Brucks, 1985). Experienced consum- online consumer information search including situational, indi- ers have product knowledge about various alternatives and they do vidual, environmental, product-related, and media factors. This not need to search more information from external sources (Raju, study attempts to empirically test the effects of a complete set of Lonial, and Mangold, 1995). Two hypotheses are suggested to test factors on online information search activity with a special focus on these relationships: the effect of Internet-related factors. Figure 1 provides a proposed theoretical model examined in the study. H2a: Objective knowledge decreases search time on the Internet. HYPOTHESES H2b: Objective knowledge decreases the number of brands examined. Internet Skills Novak, Hoffman, and Young (2000) assert that consumer It is likely that prior knowledge facilitates search in a more online navigation and interaction are influenced by his/her online efficient way by making it easier to process new information in a skills. They found that the higher the levels of online skills, the more prepurchase situation (Brucks, 1985; Ozanne, Brucks, and Grewal, positive the experience consumers achieve from the Internet. Based 1992). For example, Brucks (1985) found that objective knowledge on the economic perspective on information search, Ratchford, is positively related to the number of attributes examined. There- Talukdar, and Lee (2001) posit that increases in Internet skills will fore, the following hypothesis is provided: reduce the marginal cost of acquiring a predetermined level of benefit of search, making external search more likely to increase. H2c: Objective knowledge increases the number of attributes Schmidt and Spreng (1996) also suggest that skills are positively examined. related to perceived ability which in turn is likely to increase external search. Therefore, the following hypothesis is proposed: Subjective knowledge is related to perception of and confidence in the ability to do product-related tasks and past product experience H1: Internet skills increase search time on the Internet. (Park et al., 1994). Consumers with high subjective knowledge will recognize heightened confidence in their ability when performing Objective and Subjective Knowledge information search for product purchase (Duncan and Olshavsky, Researchers suggest that objective knowledge and subjective 1982). Consumers who are confident in product purchase are likely knowledge will have different effects on information search (Park, to engage in less external search because they feel less need for any Asia Pacific Advances in Consumer Research (Volume 6) / 23 more information (Johnson and Russo, 1984). Lee et al. (1999) H5a: Situational involvement increases search time on the found that high knowledge consumers examined less information Internet. than low knowledge consumers. Consequently, the following H5b: Situational involvement increases the number of brands hypotheses are suggested: examined. H5c: Situational involvement increases the number of at- H3a: Subjective knowledge decreases search time on the tributes examined. Internet. H3b: Subjective knowledge decreases the number of brands Enduring Involvement examined. Enduring involvement refers to the persistent interest in an H3c: Subjective knowledge decreases the number of attributes object and its importance (Zaichkowsky, 1994). Prior research examined. (Srinivasan and Ratchford, 1991) suggests a positive relationship between interest and search. With respect to the effect of involve- Prior Purchase Experience ment on search behavior, Beatty and Smith (1987) found that a Consumers with prior purchase experience tend to have pro- higher level of ego involvement led to a greater amount of informa- cedures for simplifying the decision and reducing the amount of tion search. Celsi and Olson (1988) also found that consumers spent information (Newman and Staelin, 1972; Punj and Staelin, 1983; more time attending to information as their involvement increased. Srinivasan and Ratchford, 1991). For example, Newman and Staelin Hence, enduring involvement might be positively related to exter- (1972) found that when purchasing a new car or appliances, nal search for information from various sources. Thus, the follow- consumers with prior purchase experience tended to spend less time ing hypotheses are proposed: to make a decision. It seems that previous purchase experience on the Internet will reduce perceived benefits of search, which will H6a: Enduring involvement increases search time on the consequently decrease external search effort on the Internet for Internet. information source. Thus, it is suggested that: H6b: Enduring involvement increases the number of brands examined. H4a: Prior purchase experience decreases search time on the H6c: Enduring involvement increases the number of attributes Internet. examined.

Purchase experience also leads to less amount of information Attitude toward the Internet examined during search. Moore and Lehmann (1980) found that as Li, Kuo, and Russell (1999) found that frequent online shop- the number of purchasing bread increases people tend to search for pers tended to have more positive perception of channel attributes less information. In a recent study, experience seems to lead to a than non users. They assert that frequent online users perceive the slight decrease in the number of Web sites visited for air travel Web to be significantly higher in the three aspects of channel (Johnson, Moe, Fader, Bellman, and Lohse, 2002). However, attributes (communication, distribution, accessibility). One of the Moorthy et al. (1997) found that as purchase experience increases important attributes of the Internet is its easy access and ubiquitous- the number of attributes based on which consumers compare brands ness. The ease of gathering product information on the Internet is increases whereas the number of brands decreases. It seems that likely to increase consumer intention to search and process because consumers become experts with experience who can make fine the more available the information is to consumers, the lower the distinction based on a large set of attributes. It is therefore hypoth- cost of search will be (Schmidt and Spreng, 1996). Similarly, in his esized that: interaction model of information search, Klein (1998) posits that characteristics of the Internet such as user control and interactivity, H4b: Prior purchase experience decreases the number of customizability, and accessibility will influence perceived benefits brands examined. of search and external search activity. Hence, the following hypoth- H4c: Prior purchase experience increases the number of esis is proposed: attributes examined. H7: Positive attitude toward the Internet increases search Situational Involvement time on the Internet. Many researchers agree on the important role of involvement in determining consumer prepurchase search for brand information METHODOLOGY and suggest that situational involvement will increase processing A convenient sample of 72 undergraduate students from a effort (Beatty and Smith, 1987). If the personal relevance of a southwestern state university was recruited for this study. The specific purchase under consideration is increased, consumers tend students were given extra credit points as incentives for their to allocate more cognitive resources and are more motivated to participation in the study. Students participated in the study by process or search for relevant information extensively. completing an online information search task in small group ses- Beatty and Smith (1987) suggest that consumers who perceive sions during a two-week period. The sessions were held in a more relevancy and importance in decision-making tend to exert laboratory. The laboratory room was equipped with desktop com- more search effort than those with low involvement. They found puters and Ethernet connection. Each session was run by an that across several product categories, consumers with high pur- administrator. chase involvement spent more time and examined more brands. Lee Participants were randomly assigned to either high situational et al. (1999) found that consumers with high issue involvement involvement (SI) or low SI conditions. SI was manipulated by searched for more product information than low involvement varying the level of personal relevance and task importance through consumers. In their study, when asked to find information about instruction. High SI group was told that their college would require laptop PCs, subjects in high situational involvement situation all the students to purchase a laptop computer. They were told that examined a larger number of brands and attributes than subjects in their input was needed to have a better understanding of students’ low involvement. Hence it is hypothesized that: preference for laptops. On the other hand, low SI group was told that 24 / An Empirical Examination on External Consumer Information Search on the Internet they were being surveyed to provide helpful information for a of the antecedents of external search was examined by regressing all distant university that is considering requiring its students to the antecedents on time spent on search. As shown in Table 1, purchase a laptop computer soon. search time was influenced by the composite of the antecedents entered (F=2.90, df=(7, 64), p≤.05). According to this model, the Measures antecedents explains 24% of total variation in search time (R2=.24). In addition to the SI manipulation, there were six independent A closer examination of standardized coefficients of the anteced- variables examined in this study; Internet skills (number of items; ents shows that situational involvement, objective knowledge, and 4), objective knowledge (5), subjective knowledge (2), prior online prior purchase experience were significantly related to search time. purchase experience (1), enduring involvement (10), and percep- Situational involvement was most highly related to external search tion of the Internet attributes (12). Items yielded a moderate to high on the Internet (B=.401, p≤.05). This indicates that consumers in level of reliability. The primary dependent variable was the amount high situational involvement condition spent more time on search of external search. Many studies have introduced different mea- on the Internet than those in low situational involvement condition. sures of information search activity (Srinivasan, 1990). However, Therefore, H5a is supported. Objective knowledge was negatively most of the studies have relied on self-report (Li et al., 1999; related to search time (B=-.251, p≤.10). Subjects with high objec- Ratchford et al., 1997; Srinivasan and Ratchford, 1991) or search tive knowledge about laptop PCs spent less time on search on the intention (Shim, Eastlick, Lotz, and Warrington, 2001), which Internet, which supported H2a. Also as expected, purchase experi- seems to be subject to distortion and unreliability. To overcome this ence (B=-.240, p≤.05) showed a negative relationship with external difficulty of measuring search and provide a more accurate and search time. Subjects who have purchased any laptop PC during the objective measure, this study utilizes a measure of accurate time last 12 months tended to spent less time on information search than spent for external search on the Internet using a software those who have no online purchase experience. H4a is therefore (WinWhatWhere Investigator) that captures real time search activ- supported. However, the other variables such as Internet skills, ity. In addition, the number of brands and attributes considered, subjective knowledge, enduring involvement, and Internet attitude satisfaction, and choice confidence were measured. were not significantly related to external search amount.

Data Collection Number of Brands Examined At the beginning of each session, participants were told that To test what determines the number of brands considered this was a study to collect information that would help the Dean of during search on the Internet, a multiple regression analysis was their college (high SI) or a distant university (low SI) to make a conducted with objective and subjective knowledge, prior purchase decision on which laptop to require students to purchase. A study experience, situational and enduring involvement entered as inde- administrator explained the procedures to make sure that all partici- pendent variables. The regression result indicates that the anteced- pants followed the instructions properly. ents significantly affect the number of brands considered during First, study participants were asked to fill out Part I of an online search (F=2.28, df=(5, 66), p≤.05). An examination of standardized survey questionnaire that asked about their online experience coefficients of the antecedents reveals that situational involvement, (skills, objective and subjective knowledge, past online purchase objective knowledge, and purchase experience are significant de- experience, enduring involvement, perceived Internet terminants of the number of brands considered. As shown in Table attitude).Afterwards, participants were told that they could go 1, situational involvement was the most important determinant of online and shop for a full size laptop computer within a given price the number of brands considered (B=.282, p≤.05), indicating that range. During this phase of the study, participants were given no subjects in high situational involvement condition examined more specific direction for information search and they were free to visit brands than those in low situational involvement condition. There- any Web sites with no time limit. A software program that monitors fore, H5b is supported. computer activities and records the data in Excel-like file was Objective knowledge and purchase experience were found to turned on for each participant’s PC. Upon completion of their be marginally negatively related to the number of brands consid- shopping task, participants filled out Part II of the online survey ered. Subjects with high objective knowledge tended to consider which asked for their recommended brand choice, number of less number of brands during search than low objective knowledge brands and attributes during search, motivation to search, and subjects. Therefore H2b is supported. As expected, subjects with demographic information. Upon completion of all sessions, sub- prior purchase experience were likely to consider less number of jects were briefed on the purpose of the study. brands than those with no purchase experience, which supported H4b. However, the regression result found that subjective knowl- RESULTS edge and enduring involvement were not significantly related to the number of brands, failing to support H3b and H6b, respectively. Manipulation Check A seven-point Likert-type item checked the manipulation of Number of Attributes Examined situational involvement: “To what degree do you think information Similarly, objective and subjective knowledge, prior purchase search on the Internet was interesting?” The ANOVA result shows experience, situational and enduring involvement were regressed that subjects in high SI condition were more interested in informa- on the number of attributes considered during search. Results in tion search on the Internet than subjects in low SI condition (Mhigh Table 1 reveal that there is a marginally significant relationship SI=5.3 and Mlow SI=4.4; F(1, 70)=6.46, p<.05). between the composite antecedents and the number of attributes considered (F=1.88, df=(5, 66), p=.10). The regression analysis Time Spent on Search also found that objective knowledge is the only variable which is Multiple regression analysis was performed to assess the significantly related to the number of attributes considered (B=.320, effect of various antecedents on time spent on search on the Internet. p≤.05). Therefore, H2c is supported. This indicates that subjects These antecedents include Internet skills, objective and subjective with high objective knowledge considered more attributes than knowledge, prior purchase experience, situational and enduring subjects with low objective knowledge. involvement, and Internet attitude. The relative importance of each Asia Pacific Advances in Consumer Research (Volume 6) / 25 TABLE 1 Multiple Regression Results

Antecedents Search Time Number of Brands Number of Attributes

Internet Skills -.011(H1) N.A. N.A. Objective Knowledge -.251(H2a)* -.264(H2b)* .320(H2c)** Subjective Knowledge -.001(H3a) .219(H3b) .076(H3c) Purchase Experience -.240(H4a)** -.216(H4b)* .008(H4c) Situational Involvement .401(H5a)** .282(H5b)** .023(H5c) Enduring Involvement -.014(H6a) .072(H6b) -.048(H6c) Internet Attitude -.005(H7) N.A. N.A.

F 2.90** 2.28** 1.88* R2 .24 .15 .12

* p<.10, ** p<.05

SUMMARY AND DISCUSSION This study found that objective knowledge was the only This study sought to identify antecedent factors affecting variable that determined the number of attributes examined during external search on the Internet in a multivariate setting. It was search. This result is consistent with Brucks’ (1985) finding that, in postulated that various factors such as personal, situational, and searching for information about sewing machines, high objective Internet related variables would affect external search on the knowledge consumers examined a larger number of attributes than Internet in terms of search time, number of brands and attributes those with low objective knowledge. Given the result that high examined. Some of the relationships hypothesized were supported objective knowledge subjects consider a smaller number of and they are provided in Figure 2. alternatives but examine a larger set of product attributes, it seems Situational involvement, objective knowledge, and purchase that consumers become more expert-like as they gain more objective experience were found to influence search time on the Internet. knowledge in that they feel more certain about individual brands When subjects were highly involved in the search task, they spent (thus they feel less need for information about various alternatives) more time searching for information. This result is consistent with and the ability to consider a larger set of attributes (thus they tend prior research suggesting that if the personal relevance of the issue to process product information deeply by considering more or task is increased, people are motivated to exert more effort and attributes). process information more thoroughly (Beatty and Smith, 1987; The lack of effects of other variables such as subjective Petty, Cacioppo, and Schumann, 1983). Information search on the knowledge, enduring involvement, Internet skills, and Internet Internet, however, is negatively related to objective knowledge and attitude on external search in this study needs further discussion. prior purchase experience. That is, subjects with high objective For instance, the null effect of subjective knowledge might be in knowledge and prior purchase experience spent less time on infor- part due to a relatively high correlation between objective and mation search than those with low objective knowledge and pur- subjective knowledge. Or, a finer conceptualization of different chase experience. This appears reasonable because increased prod- types of knowledge should have been used in this study. As uct knowledge and purchase experience reduce perceived benefit of discussed, the role of knowledge on external search is equivocal and search resulting in less search effort (Newman and Staelin, 1972; further elaboration on the effect of different types of knowledge Schmidt and Spreng, 1996). seems necessary to resolve this. For example, rather than relying on Similarly, the number of brands considered during search was objective and subjective knowledge distinction, Fiske, Luebbehusen, determined by situational involvement, objective knowledge, and Miyazaki, and Urbany (1994) suggest a distinction between general purchase experience. Situational involvement has the strongest product category knowledge and specific brand knowledge for impact on the number of brands considered. It seems that high explaining mixed results. They assert that general product category purchase concern increases benefits of search, which results in knowledge tends to increase external search whereas specific brand increased motivation to examine a larger set of brands (Lee et al., knowledge (purchase experience) decreases search effort. In a 1999). The number of brands seems related to the lack of objective similar vein, additional work is required on conceptualizing and knowledge and purchase experience. This suggests that subjects operationalizing enduring involvement, Internet skills, and Internet with high objective knowledge and purchase experience examined attitude. fewer brands than those with low knowledge and purchase In summary, this study found that people who were more experience. Consumers who are knowledgeable and have purchased involved in the purchase task, those who had lower objective a certain product tend to have rich information about various knowledge and had not purchased a laptop PC were likely to spend alternatives and feel less need for additional information. more time and consider a larger number of brands during search. 26 / An Empirical Examination on External Consumer Information Search on the Internet FIGURE 2 A Working Model

This study also found that people with higher objective knowledge Bellenger, Danny N. and Pradeep K. Korgaonkar (1980), examined a larger set of attributes than those with lower objective “Profiling the Recreational Shopper,” Journal of Retailing, knowledge. 56 (Fall), 77–92. Bloch, Peter H., Daniel L. Sherrell, and Nancy M. Ridgway LIMITATIONS AND SUGGESTIONS FOR FUTURE (1986), “Consumer Search: An Extended Framework,” RESEARCH Journal of Consumer Research, 13 (1), 119-126. In an attempt to increase our understanding of what determines Brucks, Merrie (1985), “The Effects of Product Class Knowl- information search on the Internet, an experimental study was edge on Information Search Behavior,” Journal of Consumer carried out. Although useful results have been presented, there are Research, 12 (1), 1–16. several limitations in this study. First, this study used laptop PCs as Burke, Raymond R. 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ABSTRACT GartnerGroup.com (2001). Multimedia Mobile Messaging: A Mobile Marketing promises new opportunities for marketers Marketeer´s Delight, GartnerGroup Research Note, to communicate with customers. Short Message Service is the first www.gartnergroup.com. and easiest forms of mobile data transmission, enjoying popularity Godin, S. (2001). Permission Marketing; Wie Sie aus Fremden with users in all age groups. With mobile marketing activities still Freunde machen und wie Freunde zu treuen Kunden werden. in an experimental phase and little scientific literature, businesses München, Finanzverlag. need evidence on how in applying marketing measures using SMS. Golem.de (2002). “Werbung per SMS wird immer beliebter”. There is also little scientific research done on this subject so far. Handelsblatt (2001). 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How Well does Brand Personality Predict Brand Choice? A Measurement Scale and Analysis using Binary Regression Models Laure Ambroise, ESA Grenoble, France Jean-Marc Ferrandi, CERMAB University of Dijon, France Dwight Merunka, University of Aix en Provence and EUROMED Marseille, France Pierre Vallette-Florence, ESA Grenoble, France Virginie De Barnier, EDHEC, France

ABSTRACT different types of human characters and associated behaviors. The research proposes a methodology allowing both the However, in spite of the long research tradition, no unique and construction of a brand personality scale and the test of the ability universally accepted definition of human personality traits prevails. of the scale to predict brand choice. A brand personality scale is Generally, they are defined as “tendencies to show consistent developed and tested via exploratory and confirmatory analyses. A patterns of thoughts, feelings and actions” (Costa and McCrae, brand personality structure composed of 12 facets is uncovered and 1998). They are understood as being psychological cues that allows clearly differentiating brands belonging to the same market. determine human action and experiences. Following the work of Predictive power of the scale is then tested using binary regression Allport (1937), Cattell (1950) and Eysenck (1960) considered as models. the founders of the dominant approach, a number of psychologists believe that the best representation of personality trait structure is INTRODUCTION given by the five-factor model, factors generally named the “Big Brands belong to the daily life of individuals who might be Five” (John, 1990). This dominant paradigm describes personality attached, committed or loyal to some of them. The concept and through five basic dimensions that summarize a great number of reality of brand relationship leads managers to develop positioning distinct and specific characteristics of human personality. The Big strategies and marketing tactics directed at reinforcing the strength Five are usually labeled O.C.E.A.N.: Openness to experiences, of the relationships between brands and their consumers. Recent Conscientiousness, Extraversion, Agreeableness and Neuroticism. research in this area has been devoted to understand both the nature These factors have been identified through two main approaches: of the brand-consumer relationships and the influence these rela- the lexical approach and the hierarchical approach. In both ap- tionships could have on consumer behavior. The concept of brand proaches, the objective is to uncover the factorial structure of personality revived by Aaker is interesting in that it might explain personality traits. The lexical approach (Goldberg, 1990) is based the strength of brand-consumer relationships and consumer buying on the hypothesis that all important traits must have been encoded behavior such as brand choice or brand loyalty. Aaker’s important in natural language due to the centrality of these personality traits. contribution (1997) has been followed by other studies aiming at A factor analysis of words used to describe personality traits must better defining or measuring the concept of brand personality enable to uncover the structure and to identify fundamental dimen- (Caprara et al., 2001, Ferrandi and Valette-Florence, 2002). sions of personality. This approach first applied in the English Research on brand personality is recent and further work is still language is now sustained by emic studies conducted in numerous needed in terms of concept definition and measurement, particu- cultures. However, the lexical approach is difficult to implement larly within different settings or cultures. One certainly needs to because of the vast number of words to be analyzed. better understand the impact of brand personality on brand choice The hierarchical approach considers that personality is struc- and buying behavior. This article is a contribution to that field of tured around a limited number of factors, each factor being com- research. We develop a brand personality scale and test its validity. posed of characteristics. The personality factors are situated at the We apply the scale to two well-known international brands and most abstract level of the hierarchy and can be divided into facets, show the differences of the two brands in terms of personality. themselves composed of basic personality traits. In spite of differ- Finally, we test the explanatory power of the personality scale on ences in terms of education, social structures, religion, age and brand choice. The article is composed of three parts. We first language itself, it seems that all individuals can be described and present the conceptual framework and the definition of brand differentiated along five basic personality dimensions (McCrae, personality we will use in this study. We then present the method- 2000). However, this hierarchical conceptualization of human ology allowing the development and test of the personality scale. personality has been criticized (Block 1995). Problems such as the We finally show the results of the application of the scale to two stability of the number of factors, their interpretation and meaning international competing cola brands (Coke and Pepsi) and present or the existence of culture-specific factors are yet to be solved. their brand personality profiles. We also test the explanatory power of the scale on brand choice with a binary regression model. Brand Personality In spite of the impressive number of studies conducted in CONCEPTUAL FRAMEWORK psychology aimed at conceptualizing and measuring the structure Human personality conceptualization and measurements have of human personality, no parallel research has been conducted in been developed for decades particularly in the domain of psychol- the field of consumer behavior before the seminal contribution of ogy. This will be rapidly reviewed, followed by the transposition of Aaker (1997). We review the bases for the brand personality the personality concept to brands proposed recently (mainly by metaphor and highlight underlying limitations. Aaker in 1997) and the problems linked to this transposition. We Concept foundations propose a definition of the brand personality concept and guidelines Theories on self-reinforcement (Grubb and Grathwohl, 1967) for the development of a measurement tool. and on congruence between self-image and brand image (Sirgy, 1982) postulate that consumer behavior is determined by the Human personality traits interaction between the personality of the consumer and the percep- The origin of personality traits research is ancient since it can tions of the products which he prefers or purchases. It is along these be traced back to Théophraste (4th century B.C.) who described lines that the concept of brand personality has emerged. Individuals 30 Asia Pacific Advances in Consumer Research Volume 6, © 2005 Asia Pacific Advances in Consumer Research (Volume 6) / 31 tend to behave in accordance with the image that they have from nal scale in different contexts (Aaker et al., 2001, Ferrandi themselves or that they wish to convey to others. Brands can be et al, 2000). thought as a means to communicate these images (Belk, 1988, Schutz-Kleine et al., 1995) and the connexion between brands and (2) A lexical approach use by Caprara et al. (2001) who personal identity has been conceptualized as a brand-consumer applied to brands the human personality scale they devel- relationship (Fournier, 1998). oped in Italy. Results lead the authors to question the Animism theories consider that Humans need to anthropo- transferability of a human personality scale to brands. morphize objects in order to facilitate their interaction with the world. Thus, consumers assign personalities to brands and may (3) The direct application of a human personality scale to think of brands as possessing human personality traits. However, brands. Ferrandi and Valette-Florence (2002 a, b) have projecting personality traits on a brand is not enough to create a real applied to brands the Mini-Markers human personality consumer-brand relationship. Brands need to be active partners in scale developed by Saucier (1994). After having purified the possible relationship. Marketing activities of the brands such as the original scale and retained the items having a positive communications can create this partnership and may be perceived, meaning, the authors show some congruence between analyzed and considered by consumers as being behaviors and human personality of individuals and brand personality personality traits as those of a Human being (Plummer, 1984, of brands purchased. Blackston, 1993). Hence, just as individuals synthesize information on behaviors of others persons in terms of personality traits, Semantics. The question remains whether items retained to consumers might project personality traits to brands (Caprara et al., describe human personality and brand personality can be identical. 2001). Managers rely on the image of the typical brand user or the Although the concepts of human and brand personalities might be set of human characteristics that consumers associate with the similar, both constructs are different in their antecedents and in the typical user, on endorsement by celebrities, on product attributes, roles they play. Human personality traits are created and commu- symbols, logos and slogans or any means of personification to nicated to others via attitudes, behaviors or physical characteristics develop the associations of brand personality (Batra et al., 1993; (Park, 1986). They are thus inferred directly by others. By contrast, Levy, 1959; McCracken, 1989). Contrarily to product attributes brands are inanimate objects which are associated with personality which are mainly functional, brand personality tends to have a traits essentially through marketing communications (Plummer, symbolic function and one of self-expression (Keller, 1993, Phau 1984) and brand usage by oneself or by others. However, brand and Lau, 2001). personality and human personality do exhibit similarities: both are Problems linked to the concept of brand personality durable and might, at least under given conditions, help explain and These problems pertain to three domains: conceptualization, predict the actions of individuals belonging to the target (see measurement and semantics. Fournier, 1998 and Aaker et al., 2001 for brand personality and Conceptualization. If brand personality is a convenient meta- Park, 1986 for human personality). Therefore, there could be some phor to describe stable characteristics associated to brands, the semantic similarities between human and brand personality con- concept originally used by advertising agencies has not been cepts. Ferrandi and Valette-Florence (2002a) have tested this hy- defined properly before the work of Aaker (1997). Aaker defines pothesis in applying the Saucier human personality scale to both brand personality as “the set of human characteristics associated brand users and brands. They uncovered a similar scale structure, with a brand”. However, this definition seems too general and may although the original scale had to be purified and reduced. lead to the inclusion, within the brand personality concept, of items Considering the remaining questions concerning the meaning having no equivalent at the human level, as indeed revealed in the and measurement issues linked to brand personality, the objective results of Aaker’s work (items such as provincial or aristocratic of this research is to develop and test a new brand personality scale. which can be considered as social judgments). Moreover, contrast- The methodology followed is to construct a scale based on pub- ing with the concept of brand image (a generic term corresponding lished findings (items used in previous research) and to generate to the whole set of representations the consumer has with respect to new brand personality items. Scale purification and validation are a brand -Dobni et Zinkhan, 1990-), brand personality should be conducted. The capacity of the scale to clearly differentiate brands more specific and should be defined through traits utilized to and to explain brand choice is then tested. characterize an individual. It should offer the opportunity to transfer meaning from human personality of consumers to brand person- SCALE DEVELOPMENT AND TESTING ality of the brands they prefer, purchase or reject. Therefore, we The classical steps (item generation, purification of the scale define brand personality as “the set of human personality traits and validity tests) were followed. associated with a brand”. Measurements. Brand personality scales have been developed Generation of items based on human personality measurements. Three types of method- Generation of items was performed through a two-step ologies have been applied: procedure:

(1) A hierarchical approach used by Aaker (1997) or Costa – Selection of items from existing scales: we gathered 112 and McCrae (1998). Aaker identifies 42 traits and five items from the scales developed by Aaker et al., 2001, brand personality factors: sincerity, excitement, compe- Caprara et al., 2001, Ferrandi et al., 2000 and Ferrandi and tence, sophistication and ruggedness. This model origi- Valette-Florence, 2002a). A convenience sample of 161 nally developed in the English language and with data business students evaluated these items in terms of their collected on American respondents has allowed differen- ability to describe brands or perceptions about brands. tiating products, services and retail brands (Bauer et al., 2000, d’Astous et al. 2003, Siguaw et al., 1999). How- – Generation of new items by consumers and experts: we ever, some studies question the applicability of the origi- used the technique of nominal groups (Claxton at al., 32 / How Well does Brand Personality Predict Brand Choice? TABLE 1 Structure of the Brand Personality Measurement Scale Ltoading Ltoadin g

GLAMOROUS CHEERFUL Charming .805 40.75 Trendy .772 39.99 Sophisticated .628 24.38 Joyful .664 26.01 Voluptuous .804 46.03 Spirited .776 54.06

ELEGANT RIGOROUS Elegant .782 35.66 Determined .745 40.42 Stylish .737 35.98 Efficient .578 19.93 Good Looking .795 43.76 Intelligent .747 33.99

EXCITING MATURE Funny .750 35.45 Adult .523 14.13 Imaginative .717 32.62 Discreet .635 21.24 Original .722 31.65 Thoughtful .619 16.74

RELIABLE MISCHIEVOUS Comforting .727 39.20 Youthful .442 14.70 Robust .670 32.14 Comical .760 21.38 Secure .737 36.29

NATURAL SECURE Environmentally-friendly .570 14.68 Reliable .561 14.35 Natural .776 19.12 Successful .595 17.60

SWEET OUTGOING Likable .790 44.61 Lively .753 33.09 Affectionate .795 45.79 Popular .627 25.36 Friendly .771 37.01 Sporty .697 29.36

1980) to induce consumers and experts to elicit words they Scale Testing would use to describe brand personalities. Three The scale of 69 items was tested with four brands selected for experiments were conducted with a group of six university their awareness and penetration levels so that virtually all respondents experts and two groups of eight consumers. The mean would have a reliable judgment of brand personalities. The 4 brands number of items generated by each group was 130. Each are composed of two pairs of brands, each pair competing on the group participant was asked to evaluate individually, on a same market (Coca-Cola and Pepsi-Cola on the one hand, Nike and 7-point scale, the semantic content of each item and their Adidas on the other hand). ability to describe a brand as a person (both items generated Data were collected on a sample of 387 business students from by the groups and items selected from existing scales). a French university who were asked to furnish their judgments of brand personality for the 4 brands on the list of items, using a 1 to Selection of items 7 Likert scale. Items purification was completed through two steps: The personality scale structure was then tested. Based on results obtained after performing principal component factor analy- – Selection of items based on item evaluations. Items from sis with promax rotation, an iterative procedure allowed purifica- existing scales were retained if the mean evaluation score tion of the measurements through successive elimination of items was greater than 4 (on a 5 point scale). Items from the list ill-represented on the factors (communality inferior to 0.5). This led generated by experts or consumers were selected if mean to an order 1 structure composed of 33 items loading on 12 score was greater than 5.5 (on a 7 point scale). After this dimensions (see Table 1). first purification phase, 88 items were kept for further Lastly, validity of scale structure was tested by means of trait analysis. validity performed through a confirmatory factor analysis, the results of which were validated via a systematic bootstrap proce- – Elimination of identical or redundant items. Experts dure. Trait validity and discriminant validity were assessed (t tests eliminated items judged as identical and grouped items associated to each factorial weight, mean extracted variance and the judged as very similar. Among group of items judged ρ internal coherence coefficient of Jöreskog). In table 2 appear the similar, only the item best evaluated was retained. indicators of convergent validity and reliability. Results are satisfactory and show good trait validity for the uncovered personality At the end of this phase was obtained a final list of 69 items best scale. The scale contains some of the factors proposed by Aaker able to describe brand personality. (1997) as well as new ones. Asia Pacific Advances in Consumer Research (Volume 6) / 33 TABLE 2 Reliability and Validity of the Scale

Validity indexes

RMSEA .0765 GFI .862 AGFI .804 ρ ρ Convergent validity VC (t>2 for all 's) GLAMOROUS .56 SECURE .33 OUTGOING .48 SWEET .62 EXCITING .53 ELEGANT .60 MISCHIEVOUS .39 CHEERFUL .55 MATURE .35 NATURAL .46 RIGOROUS .48 RELIABLE .51 Reliability (Jöreskog's ρ)

GLAMOROUS .79 SECURE .50 OUTGOING .74 SWEET .83 EXCITING .77 ELEGANT .82 MISCHIEVOUS .54 CHEERFUL .78 MATURE .62 NATURAL .63 RIGOROUS .73 RELIABLE .76

DESCRIPTION OF BRAND PERSONALITIES eration (presence or not in the consideration set), preference or The measurement of brand personality is managerially choice. We collected choice data asking respondents to indicate the interesting if it allows description of the personality of the brands product they would choose on next purchase occasion. Choice data and differentiating competing brands. Managers may better was analyzed using binary regression trees which were preferred to understand major brand associations and identify target groups discriminant and logit analyses. These two analyses consider all sensitive to some personality traits. The difference in brand variables at once whereas the binary classification model is a personalities for brands Pepsi and Coke was tested through an hierarchical and recursive approach with which variables are con- analysis of variance. The analysis was conducted on the factor sidered sequentially at each classification step. A same explanatory scores obtained for the two brands on the 12 personality dimensions. variable might be selected more than once at different stages of the Results show that the two brands exhibit specific personality traits analysis. At each stage, the variable allowing to best explain choice (see table 3 for results of analysis of variance). Figure 1 shows brand is selected. A measure of the relative importance of explanatory personality structure of the two brands. The two brands differ on 8 variables has been proposed by Breiman et al. (1984). Applying the personality traits (out of 12). The four facets on which there is no binary regression model to the data allows correct classification of difference between the brands (at p<0.05) are natural, mature, 76.9% of the cases for brand Coke and of 59.4% of the cases for exciting and mischievous. brand Pepsi (see table 4). These results largely outperform those of Typical of the French market on which Coke has a very the traditional discriminant and logit analysis (correct classification dominant position (it has more buyers than Pepsi and Coke buyers of cases is 58.5% and 34.2% for Coke and Pepsi with discriminant purchase more), brand Coca-Cola is better perceived than Pepsi on analysis and 95% and 15% with the logit). the 8 personality facets on which there is a difference between the Interpretation of data is based on the identification of explana- two brands. tory variables selected in the hierarchical tree. Beyond this description which allows understanding of the choice process, results of the EXPLANATION OF CHOICE BEHAVIOR analysis should be interpreted following three main criteria: (1) An important question is that of the power of brand personality stability of the solution, (2) parsimony of the classification tree and to explain consumer behavior measurements such as brand consid- (3) relative importance of each predictive variable. 34 / How Well does Brand Personality Predict Brand Choice? TABLE 3 Results of the Analysis of Variance

BF.rand Personality Factors Sign

G2LAMOROUS 51.33 .02 S8ECURE 108.73 .00 O9UTGOING 43.55 .03 S9WEET 84.13 .00 E8XCITING 35.18 .07 E0LEGANT 43.11 .04 M0ISCHIEVOUS 29.31 .12 C6HEERFUL 84.32 .00 M4ATURE 07.02 .87 N1ATURAL 08.12 .72 R2IGOROUS 62.33 .01 R9ELIABLE 84.36 .00

FIGURE 1 Personality Profiles of Coke and Pepsi (total sample mean scores)

Stability of the solution is assessed through a classical be more important than others (secure, mature, mischievous and systematic cross-validation procedure so as to avoid the risk of exciting). The classification tree (Figure 3) is quite parsimonious capitalizing on chance (Breiman et al., 1984). In our case, the high since it is composed of 9 terminal nods. This allows having a clear rate of correct classification remains unchanged, which guarantees understanding of the hierarchical process explaining choices be- the reliability of the results. Breiman’s procedure was applied to tween Coke and Pepsi. The tree also indicates that consumers do not compute the relative importance of each variable (see Figure 2). have a unique choice process and allows identification of groups of Globally all personality traits contribute to explain the choice consumer sharing the same process. between the two brands. However, four personality facets appear to Asia Pacific Advances in Consumer Research (Volume 6) / 35 TABLE 4 Choice Confusion Matrix

Coke Pepsi (observed) (observed)

Coke 432 84 (predicted) (76.2%)

Pepsi 1335 12 (predicted) (59.4%)

T7otal 56 207 (100%) (100%)

FIGURE 2 Importance of Brand Personality Facets for Explanation of Brand Choice

Interpretation of results separation of the groups is also indicated. This value is the factor The tree should be interpreted by looking at the variable which score of individuals resulting from the factor analysis with which best explains choice. For example, at the first level of the hierarchy, we identified the 12 personality facets. For predominantly Coke- it is the variable “secure” that best distinguishes consumers choosing chosen cases, the mean factor score value on dimension “secure” is predominantly Coke from consumers choosing predominantly Pepsi. greater than -.516 and is inferior or equal to that level for the At each level is also indicated the number of cases. Total number of predominantly Pepsi-chosen cases. cases is twice the number of consumers since are associated two Interpretation of the choice processes is quite straightforward observations per consumer (the brand chosen and the brand not when beginning by the ending nodes of the tree. For example, on the chosen). At the first level of the hierarchy, there are 568 cases where left side of the tree, what best explains the choice of Coke or Pepsi Coke is predominantly chosen and 206 cases where Pepsi is is the personality trait “mischievous”, where the scores of Coke are predominantly chosen. The value of the variable which allows high compared to those of Pepsi. This choice process concerns 206 36 / How Well does Brand Personality Predict Brand Choice? FIGURE 3 Binary Regression Tree explaining Brand Choice

(G1: designates consumer group number 1)

cases out of 774 or 27%. For these cases the perceived level on ality have an impact on choice. The experimental design allows personality trait “secure” is quite low for both products (inferior to controlling some of these variables such as availability, but it is -.52). Analysis of the right hand side of the tree indicates that for a clear that key variables such as taste have not been included in the big number of cases, brands are chosen based on the trait “secure”. model. For 270 cases (with a level on dimension “secure” greater than -.52 and a level on dimension “cheerful” smaller than .40), 26 are in Description of consumer groups favor of Pepsi because of a high perceived level on the personality Another interesting result is that the methodology leads to the trait “secure” (consumer group 5). Security also explains the choice identification of different choice patterns based on personality between Coke and Pepsi for the remaining 298 cases. Coke (215 perceptions: cases) is dominantly chosen for high levels of that dimension (>.29). For the 83 cases with a predominant choice for Pepsi – Among the cases with low levels on dimension “secure” (consumer group 6), Pepsi has satisfactory level on dimension the sole personality facet “mischievous” allows to explain “secure” (between -.52–first level of the hierarchy–and .29–third choice. This process is quite simple. level). Pepsi is considered “cheerful” (greater than .40). The 215 Coke cases are then re-decomposed: 117 cases correspond to a – Among the cases with higher levels on security, the choice of Coke (consumer group 7), the brand not being considered personality facet “cheerful” allows a further split (albeit no highly “exciting” (scores<.79). The 98 cases for which Coke is direct explanation of choice). For low levels of “cheerful”, considered very exciting, what distinguishes the choice between it is again perceived security which explains choice. This Coke (74 cases–consumer group 9) and Pepsi (24 cases–consumer process is also simple. For higher levels of cheerfulness, group 8) is the level of perception on the “natural” personality trait. the personality facet “exciting” and “natural” explain The relative parsimony of the tree shows that among all choices. This choice process involving 4 personality facets personality traits, few have real explanatory power in terms of is more complex. choice. Although the two brands have different personalities on 8 of the 12 personality facets of the proposed scale, only 4 of these CONCLUSIONS traits really play an important role in explaining choice behavior This research proposes a brand personality measurement scale (secure, exciting, mature and mischievous). The decomposition developed in France. Our goal was to try to answer some criticism tree includes the facets that were previously identified as important on personality scales applying semantics originally developed for (shown in Figure 2) but for the facet “mature”. The tree allows the measurement of Human personality. The structure uncovered identification of the facets that best distinguish the Coke choices here is composed of 12 personality facets and the scale shows good from the Pepsi ones. The facet “mature” does not clearly contrast levels both of reliability and validity. However, the number of the cases within the partitions obtained. It is however important at dimensions is well above the number of facets (five) proposed by the aggregate level. Of course, one should also bear in mind that Aaker (albeit quite close to the 15 facets she proposed) and above other variables not considered here and not linked to brand person- the 5 facets found in the “Big Five” Human measurement tools. Asia Pacific Advances in Consumer Research (Volume 6) / 37 Brand personality measurements might depend on cultures and BATRA R., LEHMANN D.R. and SINGH D. (1993), The Brand languages as has been already been found in previous research. It Personality Component of Brand Goodwill: Some Anteced- could also be that a higher order analysis conducts to a more limited ents and Consequences, in Brand Equity and Advertising, number of personality facets. This was not the case with our data set edited by AAKER and BIEL, Hillsdale, NJ: Lawrence but indeed other data sets should be used for re-testing of the scale Erlbaum Associates, 83-96. structure. Also, we believe that the classical analysis used here in BAUER H.H., MÄDER R. and KELLER T. (2000), An terms of scale development and testing could be further refined. A Investigation of the Brand Personality Scale Assessment of direction could be to verify whether the selected traits and items Validity and Implications with Regard to Brand Policy in would apply to any brands (as Human personality scales apply to all European Cultural Domains, Multicultural Marketing Humans). Universality of brand personality scales is certainly an Conference, Academy of Marketing Science, Hong-Kong. issue in terms of consumer types, usage occasions and brands. We BELK R.W. (1988), Possessions and the Extended Self, Journal strongly recommend further research in this direction. of Consumer Research, 15, 2, 139-168. From a more operational standpoint, we also believe that BIEL A. (1993), Converting Image into Equity, in Brand Equity questions linked to the use and effects of brand personality are an and Advertising, edited by AAKER and BIEL, Hillsdale, NJ: important area of research. We have tested here the impact of brand Lawrence Erlbaum Associates, 67-82. personality measurements on choice in an experimental setting. BLACKSTON M. (1993), Beyond Brand Personality: Building This is an interesting first step. This test has raised an important Brand Relationships, Brand equity and advertising, edited by methodological question which is that of the analytical method that AAKER and BIEL, NJ: Lawrence Erlbaum Associates, 113- could be used to measure how brand personality explains consumer 124. behavior (choice in our case). Traditional methods such as discrimi- BLOCK J. (1995), A Contrarian View of the Five-Factor nant analysis or logit models did not give good explanatory results Approach to Personality Description, Psychological Bulletin, which is certainly linked to the heterogeneity in the decision 117, 2, 187-215. processes of the consumers. We applied a binary regression model BREIMAN L., FRIEDMAN J. H., OSHEN R. A. and STONE C. which offered some insights concerning consumer heterogeneity J. (1984), Classification and Regression Trees, Monterey, and also results concerning what brand personality traits affect CA: Wadsworth & Brooks/Cole Advanced Books & choice. Application of this method allowed correct classification of Software. almost 72% of binary choices. Of course, our results are linked to CAPRARA G.V., BARBARANELLI C. and GUIDO G. (2001), the brands studied here (the Cola market, although the results for Brand Personality: How to Make the Metaphor Fit?, Journal Nike and Adidas, not shown here in order to preserve space, were of Economic Psychology, 22, 3, 377-395. even better). But beyond the particular results of this study, what we CATTELL R.B. (1950), Personality: A Systematic Theoretical found is that a limited number of personality facets do play a role and Factual Study, New York: McGraw-Hill. in explaining choice. This is probably the case for other product CLAXTON J.D., BRENT RTICHIE J.R. and ZAICHKOWSKI categories although the explanatory brand personality facets will J. (1980), The Nominal Group Technique: Its Potential for surely vary across categories. This again will raise the question of Consumer Research, Journal of Consumer Research, 7, 4, the universality of the brand personality concept. What is important 308-313. in terms of brand management is to identify the important facets for COSTA Jr. P.T. and McCRAE R.R. (1998), Trait Theories of the particular category under study. It is on these brand personality Personality, in Advanced Personality, edited by BARONE facets that the managers should concentrate their attention. Other D.F., HERSEN M. and VAN HASSELT V.B., Plenum Press, dependent variables could also be studied. Moreover, future re- New-York, 103-121. searches could also extend the present study by including attributes D’ASTOUS A. and LEVESQUE M. 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Congruence between Brand Personality and Self-Image, and the Mediating Roles of Satisfaction and Consumer-Brand Relationship on Brand Loyalty Seong-Yeon Park, Ewha Womans University, Korea Eun Mi Lee, Ewha Womans University, Korea

ABSTRACT consistent with their actual self-concept are likely to feel motivated This study examines how the congruence between brand to purchase and consume that product. Therefore, congruence personality and self-image influences brand loyalty through such between self-image and product image may have a greater influ- mediating variables as consumer-brand relationship and consumer ence on consumers’ preference, purchase intention, ownership, satisfaction. In addition, this study compares the proposed model usage and loyalty to products and brands. under high/low involvement situations to examine the moderating Graeff (1996) analyzes the influence of the congruence be- influence of involvement. tween brand-image and self-image on brand evaluation relating to According to the results, the congruence between brand per- promotion message. It suggests that under the promotion message sonality and self-image increases not only consumer satisfaction that reminds consumers of their own self-image, consumers give but also the consumer-brand relationship. For high involvement more positive evaluations of brands congruent with their own self- products the consumer-brand relationship quality mediates the image. In one of his other studies that employed beer product effect of satisfaction on consumers’ brand loyalties, but for low brands, he suggests that positive brand attitude and purchase involvement products satisfaction directly influences brand loy- intention increase as the congruence between self-image and brand- alty. image increases (Graeff 1997). Recently, several studies have been conducted about the I. INTRODUCTION congruence between self-image and brand personality. Brand per- Brand loyalty has been one of the most important issues in sonality refers to human characteristics associated with a brand. marketing since consumers tend to make purchase decisions by Keller (1993) regards brand personality as the category of brand- brand images that have already been formed in their minds rather image made by brand user and usage imagery attributes. Plummer than from original attributes or characteristics of the product itself (1985) asserts that one component of brand-image is the personality (Dick, Chakravarti, and Biehal 1990). Creating unique brand iden- or character of the brand itself. He summarizes his research demon- tity is a key issue for brand equity management (Aaker 1996). strating that brands can be characterized by personality descriptions Because brand identity is represented by brand personality, it is a such as “youthful,” “colorful,” and “gentle.” Aaker (1991, 1996) growing perception that brand personality can differentiate a focal connects brand-image to brand personality as a component of brand brand from its competitors by creating unique brand associations. equity, and defines brand personality as the set of human character- Brand personality thus influences consumers’ preference, usage, istics associated with a brand. According to Aaker (1997), brand emotional attachment, trust, and loyalty (Biel 1993; Fournier 1998; personality consists of five dimensions: competence, sincerity, Sirgy 1982). excitement, sophistication, and ruggedness. According to previous studies (Birdwell 1968; Bellenger, Consumers use products/brands as a symbol and they prefer Steinberg, and Stanton 1976; Dolich 1969; Hughes and Guerrero brands with images or personalities that are congruent with their 1971; Munson 1973; Sirgy 1980; Stern, Bush, and Hair 1977), the self-image or brand personality. Aaker (1999) suggests when self- congruence between self-image and brand-image eventually plays schema is congruent with brand personality, the brand attitude of a an important role in improving brand loyalty. However, previous low self-monitor is more favorable, and when the situation is studies did not show how the congruence between brand-image and congruent with self-schema, the brand attitude of a high self- self-image influences brand loyalty. monitor is more favorable. According to Chang, Park, and Choi Therefore, this study examines the processes by which con- (2001), consumers exhibit favorable feeling toward a brand when gruence between brand personality and self-image influences brand the brand personality is congruent with their own self-image. loyalty through such mediating variables as consumer-brand rela- Especially, the congruence between brand personality and self- tionship and consumer satisfaction. In addition, this study com- image increases positive attitude of consumers who have high pares the proposed model under high/low involvement situations to hedonic attitude and emphasize symbolic values. Yi and La (2002) examine the moderating influence of involvement. suggest that brand personality influences brand identification, and then brand identification has a direct impact on brand loyalty, as II. THEORETICAL BACKGROUND & RESEARCH well as an indirect impact via brand relationship satisfaction. HYPOTHESES Therefore, it can be inferred that the congruence between brand personality and self-image has a positive effect on consumer 2.1 The Congruence between Brand Personality and Self- satisfaction, consumer-brand relationship, and brand loyalty. Image The studies on the congruence between consumers’ self- H1: The congruence between brand personality and self- concept and brand image try to explain consumer choice such as image increases consumer satisfaction. brand preference, purchase intention or usage and loyalty (Birdwell H2: The congruence between brand personality and self- 1968; Bellenger, Steinberg, and Stanton 1976; Dolich 1969; Health image increases consumer-brand relationship quality. and Scott 1998; Hughes and Guerrero 1971; Munson 1973; Sirgy H3: The congruence between brand personality and self- 1980; Stern, Bush, and Hair 1977). image increases brand loyalty. Sirgy (1982) suggests congruity theory and he argues that product cues involving images usually activate a self-schema 2.2 Consumer Satisfaction involving the same images. Also, Sirgy (1982, 1986) outlines the In general, the brand offers opportunities to build relationships importance of self-concept theory in consumer behavior research with consumers (Wester 2000). That is, consumers want to build a by explaining that consumers who perceive the product image to be relationship with a certain brand when they regard the brand as 39 Asia Pacific Advances in Consumer Research Volume 6, © 2005 40 / Congruence between Brand Personality and Self-Image TABLE 1 Dimensions of brand personality

Nsame Variable

Shincerity Honest, sincere, dawn-to-eart Eexcitement Exciting, daring, unique, up-to-dat Clompetence Intelligent, technical, confident, successfu Ssophistication High class, charming, glamorou Rduggedness Masculine, strong, outdoorsy, rugge

TABLE 2 Six-dimensions of brand relationship quality (BRQ)

Affective & Socioemotive Love and Passion Attachment Self-connection Interdependence Behavioral Ties Commitment

Supportive Cognitive Intimacy Beliefs Brand partner quality

beneficial or valuable to them. Thus, if consumers feel that they are pendence, commitment, intimacy and brand partner quality. Table getting a good value and are satisfied after initially using the brand, 2 shows the six dimensions of brand relationship quality suggested they want to build a relationship with it. by Fournier (1998). The attainment of consumer satisfaction is an antecedent to Aaker (1997) suggests that the ultimate objective of the brand building strong brand equity. Kotler (2000) suggests that perceived identity system is the development of a strong brand relationship consumer satisfaction has a positive effect on brand loyalty. Oliver between consumers and brands, and consumer-brand relationship and Bearden (1983) suggest that consumer satisfaction affects builds up brand loyalty. attitude after purchase and this attitude continuously influences the However, the consumer-brand relationship has been tested repurchase intention. Therefore, the following hypotheses are pro- with limited products, and it is not clear whether the consumer- posed: brand relationship still influences brand loyalty in low involvement contextual circumstances. That is, contrary to high involvement H4: Consumer satisfaction increases consumer-brand rela- situations such as purchasing cars, computers, etc., brand switching tionship quality. and impulsive buying are more frequent, and products are pur- H5: Consumer satisfaction increases brand loyalty. chased habitually without much thought and cognitive processing in low involvement situations. Therefore, it is reasonable to infer 2.3 Consumer-Brand Relationship that the consumer-brand relationship plays a more critical role in Blackston (1991) suggests that consumer-brand relationship brand loyalty building under high involvement situation. is a combination of cognitive, emotional, behavioral processes that occur between consumers and brands. Fournier (1998) suggests H6: Consumer-brand relationship quality increases brand that consumers build an individual relationship with product/brand loyalty more in high involvement situations than low they purchase in much the same way that people initiate and nurture involvement situations. relationships with other people. Hence, consumer-brand relationship indicates that consumers and brands contribute to each other in III. METHODOLOGY a win-win partnership. Consumers have a relationship with many brands in everyday 3.1 Research Model life, and what makes for a strong consumer-brand relationship is This study examines how the congruence between brand brand relationship quality (BRQ). This relationship construct is personality and self-image influences brand loyalty through the multi-dimensional and encompasses cognitive, affective, and be- mediating variables of consumer-brand relationship and consumer havioral aspects. Fournier (1998) introduces six dimensions of satisfaction. Figure 1 shows the research model of this study. brand relationship quality: love/passion, self-connection, interde- Asia Pacific Advances in Consumer Research (Volume 6) / 41 FIGURE 1 The research model of this study

3.2 Scale Developments and Measurement This extensive set of pretests yielded scales for use in the Even though Aaker (1997) provides brand personality scales overall study. The questionnaires employed 7-point Likert scales and Fournier (1994) provides the scales of consumer-brand rela- for all of the measures. tionship quality, some of the scales cannot be assimilated into the To test the moderating effect of involvement, a simple experi- Korean culture and language. Therefore, a rigorous scale adjust- mental design was used. The sample was evenly divided into two ment process is necessary. groups. A brand of a computer notebook was given to the people in The goal of Pretest 1 is to develop the scales of brand high involvement situation, and a detergent brand was given to personality. Fifty undergraduate students participated in Pretest 1. those in low involvement situation. The brands and product do- The pretest used a principal component factor analysis, with varimax mains were also selected through pretesting. rotational procedures. Twenty-four items were discarded and only eighteen items were drawn from the forty-two items. IV. DATA ANALYSIS AND RESEARCH RESULTS To assess the congruence of brand personality and self-image, the absolute-difference model suggested by Sirgy (1982) was used. 4.1 Data Collection and Analysis The absolute-difference model calculates the absolute distance This study had a convenience sample of 600 people aged from between consumer self-image and brand personality. According to 20s to 30s in Seoul, Korea. A total of 565 usable responses were previous research, the same scales as brand-image can measure obtained, and the sample size of high vs. low involvement situation self-image (Malhotra 1981). Therefore, the eighteen-items of brand is 286: 279. SPSSWIN v. 11.0 was used for reliability and validity personality were used to measure self-image. The absolute-differ- tests and a latent-variable structural equation modeling was em- ence model is shown as follows: ployed to examine the research model. Amos 4.0 was used for this analysis. n − ∑ BPij SI ij 4.1.1 Respondents’ demographic profiles i=1 The demographic profiles of the respondents are illustrated as BPij = brand personality (i) of individual (j) follows: SIij = actual self image (i) of individual (j) The sample consisted of 62.1% female and 32.9% male. In age distribution, 20s (61.3 %) and early 30s (21.4 %) represent the The goal of Pretest 2 is to develop the scales of consumer- majority of the sample. 45.5% of the respondents were undergradu- brand relationship quality. The forty-seven items, which were ate students and 50.3% had at least Bachelor’s degrees. The modified scales according to Korean situation, were tested. Fifty demographic profiles of high and low involvement group did not undergraduate students participated in Pretest 2 and a principal differ significantly. component factor analysis was used with varimax rotational procedures. Eighteen items of love & passion, self-connection, interde- 4.1.2 Reliability and validity tests pendence, commitment, intimacy, brand partner quality were fi- a) Brand personality nally selected. In terms of Reliability testing, all of the four factors (sincerity, To assess consumer satisfaction, overall satisfaction about excitement, competence/sophistication, and ruggedness) have co- buying the brand (Oliver 1980) and the degree of delight and efficient alphas larger than .7, which suggests a sufficient degree of excitement by using the brand were used. In addition, to assess internal consistency of the scales (Nunnally 1978). brand loyalty, repurchase intention (Chaudhuri and Holbrook 2001) To test construct validity, a principal component factor analy- and recommendation intention (Zeithmal, Berry, and Parasuraman sis was used with varimax rotational procedures, and four items 1996) were used. were additionally discarded. 42 / Congruence between Brand Personality and Self-Image TABLE 3 Reliability and validity analysis of brand personality scales

Csomponent Communalitie F2actor 1 F3actor F4actor Factor H5onest .410 .16 .870 .6179 .82 S4incere .613 .17 .884 .0168 .86 D0awn-to-earth .519 .22 .714 -9.152 .61 E2xciting -23.773E-0 .530 .23 .690 .623 D3aring .220 83.964E-0 3.543E-0 .872 .809 U7nique .710 .321 -3.601E-0 .859 .796 T2echnical 7.590E-0 .785 .2243 .214 .70 C2onfident .11 .834 .8178 .117 .77 S4uccessful .15 .767 .2164 52.063E-0 .64 H4igh class -.10 .701 45.345E-02 .334 .62

Masculine .854 42.951E-02 22.157E-0 34.712E-0 .73

Strong .906 42.614E-02 72.425E-0 40.121E-0 .83

Outdoorsy .769 10.512E-02 .312 .522 .65

Rugged .700 .0145 .329 -54.108E-0 .59

E1igenvalue 49.75 20.37 16.78 1.17

Percent of 303.937 166.99 182.71 8.39 Variance C6ronbach's alpha .5846 .4823 .9813 .805

Although Aaker (1997) suggests five factors, four factors were self-connection, ‘behavioral ties’ such as interdependency and found in this study: sincerity, excitement, competence/sophistica- commitment, ‘supportive/cognitive beliefs’ such as intimacy and tion, and ruggedness. That is, Korean consumers perceive compe- brand partner quality. That is, Korean consumers perceive con- tence and sophistication as identical factors. To interpret the reason, sumer-brand relationship in terms of affective, behavioral, and in-depth interviews were conducted. As a result of the interviews, cognitive dimensions. Korean consumers integrate love/passion it was discovered that the informants perceived competence and and self-connection as affective and socioemotive attachments, sophistication as identical factors (“I feel that those who are which implies that when consumers feel love/passion about a competent and successful are generally high-class, sophisticated brand, they feel the brand and they are connected emotionally. and elegant.” “If someone is a competent person, he probably Interdependence and commitment can explain the behavioral attains wealth as a consequence, therefore, it follows that he ties also (Fournier 1998). Committed consumers have a tendency to becomes high-class, glamorous, and elegant naturally.” “People purchase one brand continuously even though they have an alterna- usually possess both sophistication and high-class characteristics tive, and they feel interdependent with the brand after all. together through developing their ability and achieving success. Intimacy and brand partner quality represent supportive/cog- They consequently seem charming to others.”). Finally, since nitive beliefs (Fournier 1998). If consumers feel intimate and Korean consumers perceive competence and sophistication as familiar with a brand, they highly evaluate the relationship quality identical factors, therefore, competent people are often considered with the brand. to be sophisticated, intelligent and elegant. The reliability of consumer satisfaction and brand loyalty was b) Consumer-brand relationship quality assessed, and the Cronbach’s entire alpha exceeded .80. In consumer-brand relationship, all the factors show Cronbach’s alphas larger than .80, and a principal component factor analysis 4.2 Research Results was run with varimax rotational procedures. Two items were additionally discarded. 4.2.1 Model fit testing In this research, consumer-brand relationship quality consists The results show low model fit according to χ2 values. But χ2 of three factors instead of the six suggested by Fournier (1998): tests are not widely used any more because it has too strict ‘affective and socioemotive attachments’ such as love/passion and assumptions and easily rejects the model. In addition, it is largely Asia Pacific Advances in Consumer Research (Volume 6) / 43 TABLE 4 Reliability and validity analysis of consumer-brand relationship quality scale

Csomponent Communalitie

F2actor 1 F3actor Factor

L9ove and passion 1 .23 .842 .9152 .78

L9ove and passion 2 .25 .841 .9123 .78

L9ove and passion 3 .36 .713 .7150 .66

L1ove and passion 4 .31 .767 .4199 .72

S3elf connection 1 .28 .742 .5273 .70

S7elf connection 2 .24 .792 .2211 .73

Interdependence 1 .804 .0313 .314 .76

Interdependence 2 .822 .3292 .418 .79

Commitment 1 .842 .2283 .512 .80 Commitment 2 .799 .8315 .516 .76 Commitment 3 .674 .0318 .827 .62 I0ntimacy 1 .738 .27 .639 .630 I9ntimacy 2 .314 .14 .821 .717 I2ntimacy 3 82.704E-0 .17 .876 .805 B5rand partner quality 1 .257 .29 .573 .743 B1rand partner quality 2 .262 .23 .521 .710 E2igenvalue 89.76 18.62 1.37 P0ercent of variance 524.76 120.18 8.61 C5ronbach's alpha .0919 .9925 .868

affected by the sample size. Alternative indexes of model fit are relationship quality and satisfaction influence brand loyalty. The widely used these days (Hong 2000). The overall fit of the model is results show the influence of consumer-brand relationship (.591) is excellent. much stronger than that of satisfaction (.293) on loyalty. Therefore, it is clear that consumer-brand relationship building is very impor- 4.2.2 Hypotheses testing tant for high involvement products. All the hypotheses except Hypothesis 3 were supported. This finding indicates that the congruence between brand personality V. CONCLUSIONS and self-image does not influence brand loyalty directly, but via According to the results, the congruence between brand per- consumer-brand relationship or satisfaction. This result is consis- sonality and self-image increases not only consumer satisfaction tent over the cases of both high and low involvement. but also consumer-brand relationship. That is, when consumers As Hypothesis 6 suggests, consumer-brand relationship qual- perceive brand personality is congruent with their self-image, their ity significantly influences brand loyalty more in high involvement satisfaction increases and consumer-brand relationship quality situations. The coefficient of the path in high involvement is much develops. stronger than that of pooled data, where the influence of consumer- For high involvement products, brand loyalty increases via brand relationship quality is diluted because of low involvement consumer-brand relationship quality. Therefore, marketing efforts samples. to build and strengthen the relationship with customers are re- Therefore, in the case of low involvement, the congruence quired. Since consumer-brand relationship is also affected by between brand personality and self-image influences brand loyalty satisfaction, satisfying consumers is important for marketers as only through satisfaction. Becuase low involvement brands do not well. build consumer-brand relationship, satisfaction strongly influences However, for low involvement products, marketers do not loyalty (.897) in low involvement situation. have to make much effort to build a strong relationship with However, for high involvement brands, both consumer-brand customers. Rather, satisfying consumers with a variety of benefits 44 / Congruence between Brand Personality and Self-Image TABLE 5 Research model fit indexes

FXix index 2 dIf GIF AIGF CIF NF

Total 1864.65* 3308.95 08.91 07.95 0.94 High involvement 1817.138* 3507.93 02.88 01.95 0.93 Low involvement 985.860* 3301.94 09.90 03.95 0.94

* p<0.001

TABLE 6 Tests of hypotheses Ttotal Hwigh involvemen Lo involvement

P.ath PTath coeff PTath coeff . PTath coeff . Brand-Self congruity → -2.334* -*.281 -64.491 -*.33 -03.757 -.20 Consumer satisfaction Brand-Self congruity → -*.240 -25.210 -*.12 -02.072 -*.36 -4.913 Consumer-brand relationship Consumer satisfaction → .*800 108.849 .*84 193.938 .*76 12.822 Consumer-brand relationship Brand-Self congruity → -1.349 -5.025 29.91 -2.02 -10.52 -.14 Brand loyalty Consumer satisfaction → 4.779* .*566 53.754 .*29 27.265 .89 Brand loyalty Consumer-brand relationship → -.291 .*318 -10.512 .*59 42.231 -.06 Brand loyalty

* p<0.05

such as product attributes, functional quality, price, etc. will be a Aaker, Jennifer (1997), “Dimensions of Brand Personality,” more powerful strategy for low involvement products. Journal of Marketing Research, 34 (August), 347-357. Even though this study proposed an integrated model of brand Aaker, Jennifer (1999), “The Malleable Self: The Role of Self- loyalty and suggests practical marketing implications, it has some expression in Persuasion,” Journal of Marketing Research, limitations as well. According to multi-self-structure-theory, it February, 45-50. consists of actual self-image, ideal self-image, and social self- Aaker, Jennifer (2000), “Accessibility or Diagnostic? Disentan- image (Park and Mittal 1985). In this research, only actual self- gling the Influence of Culture on Persuasion Processes and image was considered. But various dimensions of self-image can be Attitudes,” Journal of Consumer Research, 26 (March), 340- compared in the future research. 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Factors of Household Recycling and Waste Reduction Behavior Chizuru Nishio, University of Tsukuba, Japan Toshie Takeuchi, Hosei University, Japan

ABSTRACT Perceived Consumer Effectiveness This study examines the antecedents of recycling and reducing Perceived consumer effectiveness (PCE) is defined as a do- household waste based on an integrated waste reduction model. The main-specific belief that the efforts of an individual can make a model was tested using Japanese household recycling and reducing difference in the solution to an environmental problem. PCE is waste data. The results suggest that this model fits the data well and related to the concept of perceived behavioral control such as locus confirms the hypothesized causal relationships. Especially, attitude of control and self-efficacy. PCE was initially considered a measure toward waste reduction behavior has a strongly effect on both or element of the attitude itself (e.g. Kinnear et al. 1974, Webster recycling and reducing waste behavior. Attitude toward waste 1975, Antil 1984). However, most researchers today define an reduction is also determined by ecological involvement, perceived attitude as simply an evaluation of problems and issues, whereas cost and benefit, accessibility of a recycling program, and subjective PCE is as a belief of the extent to which individual ecological norm. activities contribute to a solution to the environmental problem and moderates environmental attitude and behavior (e.g. Ellen et al. INTRODUCTION 1991, Berger & Corbin 1992). Berger & Corbin (1992) analyzed not Various laws promoting waste reduction and resource recycling only the influence of faith in the efficacy of individual behavior, but have been enacted, and environmental and waste management also the influence of faith in the efficacy of others (FIO) such as systems have become a key concern of the government, the general technology/scientific ability and the next generation. They also public and industries. However, as waste disposal depends on the reported that the high FIO consumers show willingness to pay the efficiency of the waste disposal facility operated by the local environmental cost and support for the regulatory action. On the government in Japan, there are discrepancies in rules and disposal basis of these results, this research also picks up on PCE as the methods between local governments. Although it is largely mediator of environmental attitude. anticipated that degree of reception of the consumer waste reduction behavior is strongly influenced by waste separation rules and waste Perceived Cost and Benefit collection methods determined by local governments, the effect is It is said that environmental problems in recent years are due not sufficiently understood. to a life style of mass production, mass consumption and mass The purpose of the study proposes an integrated waste reduction disposal. Therefore, recycling and reducing household waste is model based on previous research, and analyzes the mechanism of different from the present lifestyle in that it requires extra time, consumer’s waste reduction behavior. Waste reduction behavior is action, and costs. It has been reported that the perceived costs of roughly classified as waste that can be recycled into a resource price increases (e.g. Crosby et al. 1981, Vining & Ebreo 1990), and (recycling), and the attempt to reduce waste generated in the home inconvenience (e.g. McCarty & Shrum 1994) toward environmen- through packaging reduction and refusing wasteful purchases tal behavior negatively affect recycling attitudes and behaviors. (reducing household waste). The object of this research is waste On the other hand, waste reduction behavior and purchase reduction behavior, which combines both of these classifications. of substitution products has the beneficial results of preventing unnecessary consumption and reducing living expenses. Werner & FACTORS OF CONSUMER WASTE REDUCTION Makela (1998) suggested that recycling behavior is necessary but BEHAVIOR a boring task and therefore it is important to express it from a viewpoint of benefit and profit for the consumer, and to make the Ecological Involvement consumer feel that it is an interesting and attractive task. Thus, the Previous studies have reported that the sense of social presentation of beneficial information increases recycling attitudes responsibility that represents individual’s feeling of duty or and the participation in recycling programs. obligation to help the environment has engaged in responsible In previous research, perceived cost and benefit were not environmental attitude and behavior (e.g. Kassarjian 1971, Anti considered individually; rather the sense of balance obtained from 1984, Hines et al. 1986, Webster 1975). However, in this research, the required cost of putting into practice and the benefit of labor ecological involvement is given as the more strongly mediator for compensation was established. However, according to an analysis pro-environmental attitude and behavior. The reason why we by Nishio (2002), there is a difference among consumers toward choose ecological involvement as a substitute for social responsibility perceived cost and benefit of ecological behavior. For many con- is because, with the increase of environmental problems in recent sumers, cost perception occurs separately from benefit perception. years, most consumers now feel a duty and obligation to It was found that ecological behavior was not evaluated with a “cost environmental protection. In spite of this, pro-environmental attitude to benefit” comparison. Therefore, in this research it is decided to and behavior has not yet reached sufficient levels. In order to take up perceived costs and perceived benefits separately. change the consumer’s lifestyle to one of environmental preservation, a feeling of obligation such as social responsibility will not be Rule acceptability enough. Rather, we believe that ecological involvement has more Waste separation and collection for recycling not only re- powerful motivation to pro-environmental behavior, because it is quires extra time and effort, it also depends on recycling technology possible to enjoy an environmentally friendly lifestyle through the and waste disposal methods. Then, ease of implementation such as creation of a strong relationship between individual values and pro- intelligibility of rules, ease of task, and ready access to environmen- environmental behavior. tal programs, has a large influence on consumer’s behavior and attitude. According to Nishio (2002), the most important accelera-

46 Asia Pacific Advances in Consumer Research Volume 6, © 2005 Asia Pacific Advances in Consumer Research (Volume 6) / 47 tive factor of environmental behavior, not only recycling, but also According to the agenda-setting function of mass media all other ecological behaviors, is acceptability of the environmental (McCombs & Shaw, 1972), a topic or discussion is emphasized in rules/programs and cooperation/participation at one’s own pace. the mass media is strongly affects on individual interest and Then, in this research, rule acceptability is the direct influencer of perceived importance of the topic or discussion. It has been shown household waste reduction attitude. that even for environmental problems, consumer interest and sense of crisis toward environmental problems is readily influenced by Subjective Norm information from the mass media (Nonami et al. 1997, Nishio Because environmental problems have a social dilemma,1 2002). Thus, we assume that consumer’s interest in environmental individual environmental attitude and behavior is influenced by the problems in relation to the level of media contact has a positive norm of social groups such as friends and family (e.g. Oskamp et al. influence on the formation of consumer ecological involvement. 1991, Granzin & Olsen 1991, Hopper & Nielsen 1991, Jackson et al. 1993, Taylor & Todd 1995, Nonami et al. 1997). Granzin & METHOD Olsen (1991) reported that the behavior such as newspaper recycling, The questionnaires consisted of all variables as shown in reuse of clothes and the furniture, and walking instead of using the Figure 1. The ecological involvement scale consists of 4 items car for the sake of preserving the environment is subject to normative referencing the consumer involvement scales (Aoki et al., 1988). influence from friends and associates. In addition, Taylor & Todd The level of media contact scale is composed of 5 items representing (1995) examined the influence of internal and external normative the contact level of different types of environmental informational belief to waste composting behavior and found that both groups media such as the mass media, books, city advertisements and have equal influence. This research, similar to Taylor & Todd events, and corporate pamphlets. The perceived consumer (1995), deals with both belief of the internal family normative and effectiveness scale contains 5scales representing not only of the the external friends/acquaintances normative. perceived effectiveness toward individual behavior (Ellen et al. 1991, Nonami et al. 1997), but also the influence of faith in the Attitude toward Ecological Behavior efficacy of others according to the findings of Berger & Corbin Environmental attitude is considered to be the most important (1992). The perceived cost scale is composed of 3 items that variable as a predictor of ecological behavior (e.g. Hines et al. 1987, measure effort, labor, inconvenience and sense of burden to lifestyle Shrum et al. 1994, Fransson & Garling 1999, Kaiser et al. 1999). based on the research of Vining & Ebreo (1990) and McCarty & Environmental attitude is roughly classified as that which measures Shrum (1994). The perceived benefit scale contains 2 items that is overall attitude toward the environment/environmental problems, generated by referencing Nisho’s open-ended question analysis and that which measures attitudes toward specific ecological behavior (2002). The rule acceptability scale is also derived from responses such as recycling and energy conservation. The overall attitude to Nisho’s findings (2002), and is composed of 3 items related to the toward the environment is generally considered as ecological degree of individual discretion such as the intelligibility of waste concern, and is presented in various measurements as either single separation/recycling rules, and cooperation at ones own pace. The dimensional or multi-dimensional scales(e.g. Weigel & Weigel subjective norm scale is composed both the influence of internal 1978, Dunlap & Van Liere 1978, Stern et al. 1993 ). However, since family norm and external friends/acquaintances norm based on the there is a discrepancy between measurement scales in the concept findings of Taylor & Todd (1995). The waste reduction attitude of ecological attitude, the degree of relation between the ecological scale is composed of 3 items representing an evaluation and an attitude and ecological behavior is also very different between intention toward doing waste reduction behavior. The participation measurement scales (Tarrant & Cordell 1997). Hines et al. (1987) in waste reduction behavior scale contains 2 aspects; (1) participation and many other studies have been reported that the attitude toward in recycling behavior (5 items) and (2) participation in household specific environmental behavior is more predictor than the overall waste reduction behavior (6 items) as we discussed above. These attitude toward the environment. Therefore, this research will focus every questions are all measured on a 5-point Likert scales. not on the overall attitude toward the environment, but rather on the attitude toward waste reduction behavior. RESULTS Based on previous research as seen above, the integrated waste The data was obtained from a survey of 3,000 representatively reduction model is proposed as shown in Figure 1. The most selected individuals, living in a Tokyo suburb2 in August 2002. important variable as a predictor of waste reduction is the attitude These 3000 samples were chosen using the random sampling toward it’s behavior. The attitude is also formed by ecological method based on the resident database of that city which has about involvement, perceived consumer effectiveness, perceived cost, 30,000 households’ data. The response rate for the survey was perceived benefit, rule acceptability, and subjective norm. It is 39.3%, resulting in a sample of 1179 respondents.3 assumed that perceived cost is a hindrance factor with all others Factor analysis was performed on each scale to confirm the assumed to be promotional factors. single dimensional structure of the scale. We also calculated Consumer involvement has been considered as a strongly Cronbach’s alpha coefficient to check the reliability of each scale. mediator that determine his/her behavior and information processing (e.g. Laaksonen 1994). Then, we hypothesize that ecological 2 involvement which is motivational effects on perceived consumer At the time of the survey of waste collection for Yokkaido city, effectiveness, perceived risk, perceived benefit, rule acceptability, waste seperation along the following lines was implemented: subjective norm and formation of waste reduction attitude. noninflammable waste, inflammable waste, resource waste (alu- minum cans, steel cans, bottles and paper), and bulk waste. 3We used random sampling method, however, respndents’ charac- 1The social dilemma is a situation which results in a loss of ter weren’t well-balanced such that 60% of respondents were society’s common profits in spite of the fact that consumer female, 23% were in their 50’s, 38% were in their 60’s (the largest behavior tends to maximizes profit based on personal prefer- bracket), occupation classification showed 31% of respondents as ence, and the results would be even worse if that behavior was stay-at-home wife/husband, 19% as unemployed, and 18% as not evident. office workers. 48 / Factors of Household Recycling and Waste Reduction Behavior FIGURE 1 The Integrated Waste Reduction Model

As a result is shown in Table 1, each scale was summarized benefit, rule acceptability, subjective norm and negatively effect on with a factor of 1 and the reliable coefficient (Cronbach’s alpha) perceived cost, but also predominantly effect on forming the was approximately 0.7. However, the perceived consumer attitude directly. In addition, ecological involvement is strongly effectiveness scale couldn’t be confirmed to the hypothetical positively influenced the level of media contact. structure. It was also rejected in the test for normality of the specific Furthermore, through the exploratory analysis, a direct factor variable with the prerequisite for the structural equation positively causal relation was discovered between rule acceptability modeling because of the extreme deviation in response for the scale. and recycling behavior (See Figure 2). Direct causality from rule Therefore, below we examine the model which removes the factor acceptability is not seen in reducing household waste that is waste of perceived consumer effectiveness from the hypothesized model reduction behavior of another side. These findings indicate that is shown in Figure 1. acceptability of the city’s waste separation and recycling rules The model was formulated as a structural equation model and increase the consumer’s participation to recycling behavior as estimated with the AMOS program. The hypothesized model that habitual behavior. However, it is necessary to perform the waste was specified in the above-mentioned method shows the goodness reduction attitude to do reducing household waste such as packaging of fit indices as shown by Table2. However, the alternative model reduction and refusing wasteful purchases. which adds the path form rule acceptability to recycling on the hypothesized model suggests fits the data significantly, because the CONCLUSION deference of chi-square between the hypothesized model and the In this research, the integrated consumer waste reduction alternative model is χ2(1)=25.769(p<0.01). The other fit indices behavior model was proposed. As a result of data analysis, the are also high such as the goodness of fit index (GFI) of 0.901, the presented model fits well with actual consumer data, and the causal adjusted goodness of fit index (AGFI) of 0.885, and the root mean relations hypothesized in the model was accepted with the excep- square error of approximation (RMSEA) of 0.050. Figure 2 gives tion of perceived consumer effectiveness. It became clear that the standardized parameter estimates for the alternative model. attitude toward waste reduction was the most important variable as As indicated in Figure 2, all path coefficients in the model were a predictor of waste reduction behavior. In addition, it was shown significant. Both recycling and household waste reduction behavior that the city’s recycling rules and systems was also important to are determined by the strong path coefficient from attitude toward perform consumer’s recycling behavior. This provides policymakers waste reduction. The attitude is positively influenced by ecological with useful advice on approaches to influence waste management involvement, perceived benefit, rule acceptability, and subjective behavior. norm but is negatively influenced by perceived cost. Especially, Future topics are listed below. First, perceived consumer ecological involvement has not only positively effect on perceived effectiveness which has been considered an important factor of Asia Pacific Advances in Consumer Research (Volume 6) / 49 TABLE 1 Results of Factor Analysis for Survey Measures

Survey Measures Factor Cronbach Loading Alpha

Media Contact I usually watch television programs and read newspaper articles about environmental problems. 0.654 0.788 I usually read books about environmental problems. 0.657 I usually read my city advertisement and pamphlets, and know my city’s environmental policy and strategy. 0.592 I usually visit the environment related corner at industrial exhibitions. 0.738 I usually read environmental related articles and pamphlets of corporations, and know their environmental policy 0.738 and strategy.

Ecological Involvement I try various innovations in leading an environmental friendly life. 0.715 0.714 When I buy products, I usually think about the effect those products will have on the environment. 0.676 I have a special interest in waste problems within all the various environmental problems. 0.466 I think I have an in-depth knowledge of recycling. 0.629

Perceived Risk I feel that reducing waste and recycling is time consuming and bothersome. 0.562 0.671 I believe that waste separation and recycling is ineffective in relation to the effort and cost it takes. 0.593 I think that waste reduction and recycling is difficult while maintaining a convenient and comfortable lifestyle. 0.498

Perceived Benefit I believe that the effort to reduce waste reduces wastefulness, and leads to a quality lifestyle. 0.672 0.625 I believe that the effort to reduce waste is related to controlling household budget expenses, and is rational behavior. 0.666

Rule acceptability Since waste reduction and recycling can be done at ones own pace, it is easy. 0.527 0.650 It is easy to understanding the city’s waste separation and recycling rules. 0.404 Waste reduction and recycling has become a custom and is not bothersome. 0.681

Subjective Norm My family has a positive attitude to waste reduction and recycling. 0.652 0.746 My friends and acquaintances have a positive attitude to waste reduction and recycling. 0.807 My living area has a positive attitude to waste reduction and recycling. 0.670

Attitude toward Waste Reduction I like recycling and waste reduction. 0.642 0.716 I intend to participate in area recycle and environmental clean-up activities. 0.776 I communicate the importance of, and recommend cooperating with, recycling and waste reduction to those around one. 0.662

Recycling I don’t use the disposable products such as a paper cup and chopsticks. 0.462 0.657 I thoroughly separate waste to make recycling easy. 0.644 I consider empty bottles and cans not as nonflammable waste but as recyclable products. 0.535 I take rinsed PET bottles and disposable plastic tray to the appointed waste collection area. 0.516 I use broken products for a long time by repairing them. 0.520

Reducing Household Waste I take a shopping bag when you go shopping. 0.514 0.724 I make a shopping list so that you won’t buy unnecessary products. 0.493 I choose products that come in a reusable container. 0.450 I choose perishable foods not contained in disposable plastic tray. 0.650 I choose products that come in reusable containers (beer bottle etc). 0.696 I choose recycled products such as toilet paper made from waste paper. 0.560

consumer ecological behavior in previous studies, couldn’t be necessary to develop more precise measurement and method of identified and examined for it’s effect in this research due to the lack perceived consumer effectiveness for waste and recycling prob- of a reliable scale. Presently, legal arrangements for environmental lems. preservation have been advanced and adopting ecological behavior In addition, it was found that the possibility of differences in is required by public opinion. Because waste separation and recy- motivation and causal structure which is the background for waste cling behavior is probably most familiar and acceptable ecological reduction behavior and recycling behavior. In particular, partici- behavior to consumers, most respondents showed strongly belief to pants of recycling behavior consist of both groups of people who perceived effectiveness of waste and recycling problems. It is have the positive attitude towards environmental preservation 50 / Factors of Household Recycling and Waste Reduction Behavior TABLE 2 Test Statistics for the Models Tested

Chi-square df P GFI AGFI CFI RMSEA AIC

Hypothesized model 2045.886 515 0.000 0.899 0.883 0.862 0.053 2205.886

Alternative model 2020.117 514 0.000 0.901 0.885 0.864 0.050 2182.117

Note: The alternative model is shown in Figure 2, which adds the path from rule acceptability to recycling on the hypothesized model.

FIGURE 2 The Standardized Parameter Estimates for the Final Trimmed Model

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As the United States Congress considers various changes in tax dollars. The payoff has been viewed as providing for employee the policies governing investment of pension funds, at least two control and ability to tailor a savings strategy to meet individual issues emerge concerning purchase criteria for retirement invest- needs for retirement. However, these employees incur the higher ments. One pits those who say that employees will do better than the risks associated with higher rewards. In contrast to pension plans, federal government has done in investing Social Security dollars vs. which are insured by the American Pension Benefit Guaranty those who say they will do less well. The other, a consequence of Corporation, a federal agency, to provide a specified amount to the bankruptcies at Enron and other highly visible companies, simply beneficiary if an employer or its pension plan goes under, 401(k) emphasizes giving employees more freedom to divest stock given plans had, as of spring of 2002, no safety net. Thus, 401(k) investors to them by their employers as a means of funding their 401(k) had no way to recoup their funds even if they were lost because of pension plans. corruption or malfeasance (Consumer Reports 2002). Consideration of both issues would benefit from clues con- Therefore, the United States Congress in 2002, the year cerning the degree to which employees with freedom to select following Enron and other conspicuous corporate bankruptcies, retirement investments will or will not concentrate those invest- was offered legislation to give employees freedom to divest com- ments in their employers’ own stock, vs. diversifying. For many pany stock after three to five years of employment, instead of years, economists and financial advisors have been trying to edu- waiting until age 50 or 55, as was common practice among compa- cate employees about the need to diversify their portfolios, espe- nies before 2002. The proposed legislation also required that cially targeting those with heavy concentrations in any one instru- workers receive quarterly statements showing the value of their ment or company (Knutson 2002). In spite of this advice, the Enron retirement investments with a prominent reminder about the ben- collapse revealed an unexpected situation: thousands of employees efits of diversification. Additionally, it provided for worker educa- had invested their entire 401(k) in only one company’s stock–the tion concerning their investment options and advice to help them company they work for. achieve their goals, according to presentation from a supporting Given awareness by marketers of the reality of brand loyalty group representing mutual finds (Investment Company Institute in purchases ranging from automobiles to cereal, despite economic 2002). In sum, the proposal did not limit the ability of an employee incentives to diversify brand choice, it seems plausible that non- to concentrate his or her plan in an employer’s stock; it simply economic factors might also be associated with consumer invest- provided communication concerning the merits of acting other- ment behavior reflected in concentration of one stock in retirement wise. plan portfolios. The purpose of the research to be described here However, it should be noted that even had such legislation was to identify factors associated with this particular demonstration existed in 2001, it would not have precluded financial catastrophe of “brand loyalty,” making this study an investigation of a particular for many Enron employees. Many who could have divested their type of buyer behavior with public policy consequences. A variable Enron shares chose not to, and until 2002, the majority of company that economists would predict as important in this context is the stock represented voluntary purchases by employees (Wilcox 2002). company’s financial performance. However, we also considered The concentration of 401(k) plan assets was certainly not company size and age, because studies show that people are more limited to Enron, where 57.7% plan assets were invested in the likely to trust a larger company and an older one. Finally, but not the company’s stock. A study conducted by the American Institute of least important, we considered a measure indicating employee Management and Administration (IOMA) showed that of 220 sastisfaction with the company, taking into account the possibility company 401(k) plans analyzed, 25 had more than 60% of their that more satisfied workers would be more likely to trust the assets wrapped up in company stock (2001). Three plans among company and invest money in its assets, or at least let their funds those researched by IOMA had in excess of 90% of employee assets remain in company stock provided by their employer as a “match” in company stock: Procter & Gamble, 94.6%; Sherwin-Williams, to employee contributions. 91.6%; and Abbott Laboratories, 90.2%. The paper is organized as follows: first, we define terms and Of course, many such buyer choices proved unwise. Enron emphasize the importance of this issue, which exemplifies the stock fell in value by 98.8% in calendar 2001. Other substantial intersection of consumer behavior and public policy in marketing. declines during the same period were Coca-Cola Co. (81.5% of Then we explain the variables in our model and the basis for their 401(k) assets in company stock) down 22.3%; Texas Instruments inclusion. Later sections list our hypothesis and describe the data- (75.6% in company stock) down 32.3%; Williams Cos., Inc. (75% bases used, method, results and conclusions. in company stock) down 33.1%; and McDonald’s Corp. (74.3% in company stock) down 21.1% (IOMA 2001). Even when experienc- BACKGROUND ing such losses, however, many employees kept company stock, A 401(k) plan enables employees to deduct money from their according to an issue brief of the asset allocation, account balances paychecks to fund their personal retirement plans. According to and loan activity covering 11.8 million 401(k) participants Consumer Reports (2002), an estimated 55 million American (VanDerhei 2002). Thus, the relationship between a company’s workers, 75 percent of those whose employers offered retirement financial performance and buyer response when those buyers are plans, participate in 401(k) or other tax-deferred, defined contribu- employees who owned stock seems weak, at least on a short term. tion plans. It therefore makes sense to examine other variables. Job In contrast to a pension plan, which relies on the employer to satisfaction is one way to predict employee commitment to a contribute money toward an employee’s retirement resources, a company (Barling, Wade and Fullagar 1990; Caldwell, Chatman 401(k) is built from the employee’s investment decisions and pre- and O’Reilly 1990; Fullagar and Barling 1991). Often, it is corre- 52 Asia Pacific Advances in Consumer Research Volume 6, © 2005 Asia Pacific Advances in Consumer Research (Volume 6) / 53 lated with compensation, and compensation is in turn a common • DC Plan Investing Database was used to asses the correlate of company size, according to Hewitt Associates (1999). company’s financial performance. This database provided The third variable examined was company age, given that it is returns of investment data for three years (1999, 2000, and viewed as a subtle indication of worthiness and reliability, particu- 2001) (www.ioma.com/products/prod_detail.php?prodid= larly for companies in less than venerable industries; e.g., high tech 12). (Rieck 2000). EMPIRICAL MODEL HYPOTHESES We employed a linear model to test the effect of the employ- Such reasoning led to the development of the hypotheses ees’ satisfaction, company’s age, size and performance on the tested in this study. percentage of 401(k) invested in the company’s stock. The selection of the dependent variable (percentage of 401(k) invested in the H1: All else equal, satisfied employees invest a larger per- company’s stock) and the independent variables (company’s size centage of their 401(k) in the stock of the company they and age, employees’ satisfaction, and company’s financial perfor- work for in comparison with less satisfied employees. mance measured by returns of investment) were based on literature reviewed here. All the variables are metric with the exception of H2: Employees invest a larger percentage of their 401(k) in satisfaction which is dichotomous (on the Fortune list or not). firms with higher business longevity in comparison with The model tested was: firms with lower business longevity. α δ δ δ δ ε Perc401(K)i= + 1Sati + 2Agei + 3Sizei + 4Finperfi + I, H3: Employees invest a larger percentage of their 401(k) in larger firms in comparison with smaller companies. where

H4: The company’s financial performance lacks a significant Perc401(K)i=Percentage of 401(K) invested in the company’s impact on the employees’ decisions to invest their 401(k) stock for a company i in its stock. Sati=Employees’ satisfaction toward the company i (present in the Best Company to Work For Fortune list or not) Thus, our basic prediction was: the concentration of 401(k) in Agei=Age of the company i (number of years since the the company’s stock is determined by employees’ satisfaction with company was founded) the company and the company’s age and size, rather than by the Sizei=Size of the company i (revenue in millions) company’s financial performance. Finperfi=Financial performance of the company i (return of investment) METHOD The databases used to test these hypotheses began with the DC RESULTS Plan Investing published by IOMA (www.ioma.com/products/ To determine the relative importance of each independent prod_detail.php?prodid=12), which was used to assess the 401(k) variable in predicting the dependent variable, multiple regression plan assets invested in the company stock. The data provided was analysis was employed. Specifically, the regression analysis per- the last reported company stock as percent of Defined Contribution mitted examination of the variance in the percentage of 401(k) plan company stock holdings, December 2001, for 220 companies. invested in company’s stock explained by the size and age of the These companies became the sample employed for analysis, and we company, the satisfaction of the employees (a Fortune leader or not) sought predictive data concerning them, as follows: and the financial performance of the company. We examined standardized regression coefficients (beta coef- • Fortune–Best Companies to Work for Database was used ficients) to assess the relative strength of each independent variable as a proxy measure of employees’ satisfaction with their in the equation. Consistent with our first hypothesis, we found that job (www.fortune.com/lists/bestcompanies). While this the presence of an employer on a list indicating high employee list is not based on employee survey data, it emphasizes satisfaction significantly predicts a greater proportion of 401(k) elements of compensation, which are often used as con- funds invested in the company’s stock. We employed several tributing to satisfaction with one’s employer (Hewitt As- models that took into consideration the satisfaction proxy and in all sociates, 1999). The data was also for year 2001. Only 13 of them we found the categorization of a company as “best to work from the 220 listed in IOMA DC Plan Investing were for” had an important and a significant influence on the percent of included in this Fortune list, however. 401(k) invested in the stock (p’s<.004). Our second hypothesis predicted that a company’s age would • Fortune 500 America’s Largest Corporations was used to have a positive impact on the percent of 401(k) invested in the assess the size of the companies (www.fortune.com/ company’s stock: the older the company, more likely that employ- indexw.jhtml) together with Business & Company Re- ees will invest in the company’s stock. Although the relationship source Center Database (www.galenet.galegroup.com/ was in the direction expected, the coefficient did not reach statisti- servlet/BCRC?locID=txshracd2588), for revenues in mil- cal significance (p>.3). Thus, starting with the second model we lions. The data was also for the end of 2001. excluded company age from the analysis. The third hypothesis, stating that employees invest a larger • Fortune 500 America’s Largest Corporations percentage of their 401(k) in bigger firms in comparison with (www.fortune.com/indexw.jhtml) was used to assess the smaller companies, found support, using sales revenue as the age of the companies together with Business & Company indicator of size. The sales revenue beta coefficient reached signifi- Resource Center Database (www.galenet.galegroup.com/ cance in all models employed (p’s<.005). servlet/BCRC?locID=txshracd2588) (year founded). 54 / Antecedents of “Brand Loyalty” in 401(k) Plans As Clues to Purchase Criteria for Retirement Investments TABLE 1 Comparative Regression Results among the Models Employed

Model 1 Model 2 Model 3 Model 4 Model 5

Beta Sig. Beta Sig. Beta Sig. Beta Sig. Beta Sig.

Finper .087 .212 .052 .437 .074 .283 .069 .312 Age -.070 .332 Sat .214 .004 .208 .003 .212 .002 Size .244 .001 .228 .001 .226 .001 .295 .005 .276 .000 F 7.452 .000 8.949 .000 13.14 .000 5.868 .001 8.570 .000 R .377 .348 .344 .291 .284 R Square .142 .121 .118 .085 .080 N 185 199 199 1 194 198

Recall that we expected that a company’s financial perfor- might be done by finding secondary research data on employee mance to have a less than significant effect on the percent of 401(k) satisfaction studies that have correlated this construct with the age invested in the company’s stock, even if the relationship is positive. of the company in which the employee worked. In addition, In other words, we expected to find that satisfaction and company observation of “best company to work for” is limited to 13 compa- size and age have a bigger influence on the percentages of 401(k) nies out of 190 in the sample. Also, with the exception of financial invested in the company than the financial performance of the returns, it was not possible to find data for several years for the other company. We found support for this hypothesis. Although the beta variables. Thus, one can draw conclusions only on the basis of a coefficient for returns was positive, its level did not reach signifi- very limited set of companies. cance in any of the models (p’s>.2). Moreover, in this study, control variables could not as a We also excluded the satisfaction dummy variable from the practical matter be considered, such as how long each company analysis to see the contribution of the other variables in its absence requires investors to hold shares contributed by the company before (Model 4 and Model 5). We found that revenues, which represent allowing them to diversify, average size of employees’ assets, or company size, remained an important predictor of our dependent information about the length of time workers have been employed variable (p<.005). In contrast, financial return was insignificant at the firm. It might be possible that companies with relatively again (p>.2). Thus, this additional analysis also supported our young workers would have fewer dollars in such plans and therefore hypotheses. be more likely to have a higher percentage of their assets invested Finally, in Model 5, we redid the analysis with all variables as in company stock. In contrast, companies where most workers have dummies. Since we had expressed satisfaction as a dummy vari- been employed for a long period of time would be more likely to able, because of the small number of companies found in the 100 have reached a level where they are able, under plan rules, to sell Best Companies to Work For, we were concerned that we might company stock to purchase other assets to diversify their portfolio. have forced the difference and that this methodological issue Keeping these limitations in mind, however, these findings explained why satisfaction was found to be an important predictor. suggest that a Congressional decision to give employees freedom to Thus, by making all variables dummies we tried to assure equal divest themselves of company stock after three or five years of chances for all our variables in the model. We obtained the same service, instead of waiting until age 50 or 55, might have less impact results as before. than expected. Since company financial performance appears to The F values and the significance values showed that all our have only a minimal impact on employee decisions to invest in their models provided a good fit. However, seeking parsimony we company’s stock, giving employees freedom to sell their stock after considered the second model to be best. In this model, only two three years might not make a difference in preventing disasters such variables, size of the company and employees’ satisfaction, made as Lucent and Enron. Consequently, although it might constitute an a significant contribution in predicting the dependent variable, administrative headache and could prompt employers to cut back whereas financial performance represented by return on investment on contributions (Wilcox 2002), measures like limiting the amount had an insignificant role. of company stock that 401(k) participants may own to a fixed percentage (say 10% or 20% of their account), in addition to DISCUSSION education programs about the risk of overconcentration, might Limitations of a study of this kind include the problem that constitute a better way to help prevent overwhelming loss of causality can only be inferred after the fact. There is no way to say savings. that viewing a company as a good place to work, or trust in that There is a broader marketing policy implication, also, in the company based on its size, led to the level of purchase employed evidence presented here that investment purchases are like the here as a dependent variable. purchases of cars, cereal, or magazine subscriptions in the role Employee satisfaction is not measured directly but through played by factors beyond economic calculations. In a sense, em- “best company to work for” database. A validation of this measure ployees may be “buying” comfort with the purchase of something Asia Pacific Advances in Consumer Research (Volume 6) / 55 familiar, the virtuous feeling of supporting their employer, and the avoidance of choosing among a complex set of possible investment vehicles when they concentrate 401(k) purchases in the stock of their employer. Those considering turning over the investment of funds now invested through a central Social Security system might take these findings into account. In fact, any legislation concerning the purchase of any investment vehicle will presumably benefit from greater understanding of how such choices are made.

REFERENCES Barling, Julian, Bill Wade and Clive Fullagar (1990), “Predicting Employee Commitment to Company and Union: Divergent Models,” Journal of Occupational & Organizational Psychology, 63 (September), 49-68. Caldwell, David F., Jennifer A. Chatman and Charles A. O’Reilly (1990), “Building Organizational Commitment: A Multifirm Study,” Journal of Occupational & Organiza- tional Psychology, 63 (September), 245-68. Consumer Reports (2002), “Investing for Tough Times: Shoring up your 401(k),” 67 (March), 36-38. Fullagar, Clive and Julian Barling (1991), “Predictors and Outcomes of Different Patterns of Organizational and Union Loyalty,” Journal of Occupational & Organizational Psychology, 64 (October), 129-148. Hewitt Associates (1999), “Large firms continue to offer generous benefits packages: Hewitt Survey,” Employee Benefit Plan Review, 53 (June), 57. Investment Company Institute (2002), “The 401(k): An Oportunity for Americans, An Opportunity for Congress,” advertisement, multiple publications, September 30. IOMA’s DC Plan Investing (2001), “Enron Debacle Will Force Clean Up of Company Stock Use in DC Plans,” Report of Investment Management Performance, (December), 1-7. Knutson, L. Lawrence (2002), “Bush Promotes Proposed 401(k) Change,” Associated Press Online, (February), www.ap.org/ pages/indnews/. Rieck, Dean (2000), “Direct Mail - No Testimonials? No Problem! How to Build Unbeatable Credibility with Little Creativity,” Direct Marketing, 63 (October), 24-29. VanDerhei, Jack L. (2002), “EBRI Special Report. Company Stock in 401 (k) Plans: Results of a Survey of ISCEBS Members,” Employee Benefit Research Institute, (January), 1-23, www.ebri.org. Wilcox, Melynda D. (2002), “The New Look of Pensions,” Kiplinger’s Personal Finance Magazine, 56 (April), 23-24. Understanding the Seeds of Growth: Technological Evolution and Product Innovation Ashish Sood, University of Southern California, U.S.A. Gerard J. Tellis, University of Southern California, U.S.A.

Many marketers think market segmentation is the most impor- faster than the old technology and finally overtakes it in perfor- tant engine of growth. On the contrary, it is technological change mance. Hence we expect a series of S-curves with single crossing, that is perhaps the most powerful engine of growth. Numerous new attack always from below and each ending at higher level. examples can be cited from the industry to support this claim. First, However we find no support for these hypotheses. Most new the growth of Microsoft from a fledging company to the colossus of technologies performed better than the old technology, right from the computer industry was enabled by technological change. Sec- the time they were introduced while others never improved. Also, ond, emergence of internet-enabled products, walkman, washers some technologies exhibited multiple crossings as dominance etc. suggest that technological creates new growth markets. Third, shifted interchangeably between the two. the meteoric rise of Amazon and Dell suggests that it is technologi- Past research suggests that competition occurs systematically cal change that also propels small outsiders into market leaders. and sequentially along four generic dimensions of inter-technologi- However, firms can not gain from technological change if they cal competition: functionality, reliability, convenience, and cost do not understand it well. Specifically they need to understand how (Christensen 1999). On the contrary our results suggest a sequence new technologies evolve, including any underlying patterns. It is of random, unpredictable secondary dimensions in each of the six also important to know the dimensions of competition between categories e.g. brightness–color index–life–compactness in light- technologies, the process of transition between old and new, and the ing. source of innovations. Currently, the main sources of answers to all There is evidence of both increasing pace and constant pace of these questions are limited findings in the technology management technological change in prior literature. However most of the literature (e.g. Foster 1986; Utterback 1994; Christensen 1997). studies employ indirect measures due to lack of data. Our rich data These sources promote a theory commonly known as the Theory of allows using three direct measures of the rate of technological S curves. Our study seeks to confirm whether this commonly change–the pace of introduction of new technologies, of techno- accepted model of technological evolution promoted by these logical improvements within each platform and the annual rate of sources holds. improvement for each technology. Tests of all three measures One of the reasons for limited research in this area is the lack support an increasing pace of technological change. of readymade data. We had to painstakingly collect data over a large The conventional wisdom is that small outsiders are more portfolio of categories using historical method (Golder 2000; likely to introduce new technologies. Although these small firms Golder and Tellis 1993). We define three types of innovations– are ridiculed and ignored by incumbents in the beginning, they platform, design and component innovations–strictly based on the eventually become successful and large incumbents with more intrinsic characteristics of the technology. These definitions avoid opportunity and resources for innovations. However, size and the error of circular reasoning created if definitions based on market incumbency lead to complacency and technological inertia. Hence outcomes of innovations are used to predict market outcomes. A we expect innovations to come from small outsiders and large platform innovation is the emergence of an entirely new technology incumbents. We find strong support for both these hypotheses. based on scientific principles distinctly different from those of the To summarize, we failed to find support for many prevailing existing technologies e.g. the compact disk. Design and component beliefs about technological change. We conducted a series of innovations incorporate changes in materials and layout respec- robustness tests to validate our findings on shape, path, and crossing tively within the same platform innovation. patterns. First we redid all analyses for two different reference We selected a mix of old and new categories allowing both points–first technology in each category, the dominant technology comparison and validation. Existence of at least two platform- in each category in addition to the one just prior. Second, we innovations in each category and ease of data availability were other examined the effect of using benefits per dollar as a metric instead criteria. Our sample includes 23 technologies in external lighting, of only benefits. Finally, we also tested the hypotheses using data transfer, computer memory, desktop printers, display moni- multiple dimensions of performance simultaneously. tors, and analgesics. We first identified all the platform innovations This study has several implications for managers. First, using and then recorded the maximum performance of products for each the S-curve to predict the performance of a technology is quite risky year from its year of introduction till 2001, and details of the firm and may be misleading. Second, the continuous emergence of new that introduced it. technologies and the steady growth of most technologies suggest Prior literature (Foster 1986, Sahal 1981) suggests that tech- that relying on the status quo is deadly for any firm. Third, another nologies evolve through an initial period of slow growth, followed threat to incumbents is the emergence of secondary dimensions of by one of fast growth culminating in a plateau. When plotted against competition. Fourth, large firms are not doomed to extinction. More time, the path resembles an S curve. To test these hypotheses, we details and results are available in Sood, Ashish and Gerard J. Tellis plotted performance of technologies over time and also fitted the (2005), “Technological Evolution and Radical Innovation,” Jour- generalized logistic function using nonlinear regression techniques nal of Marketing. in SAS to estimate the model, but found little support for the hypothesis. In majority of technologies we found long periods of static performance interspersed with abrupt improvements in performance. Some technologies even showed no change in performance since introduction. The theory of S curves suggests that sometime during the life of the first technology, a new one emerges and initially it also performs worse than the old technology. With time, it improves

ABSTRACT Changes in communication-related technology was the stron- This research considers the impact of technology on the gest new trend reported in a salespeople’s focus group study salesperson’s activities. The study integrates a literature survey conducted by Marshall, Moncrief and Lassk (1999). Communica- with quantitative research to uncover the relationship between the tion technologies such as email and cellular phones have been found usage of technology and the alignment of salespeople’s time within to be useful communication tools that increase salespeople’s pro- the HR services industry. A survey of 50 HR sales consultants was ductivity and aid in the provision of higher levels of customer conducted and it was found that these salespeople do save time by service (Marshall et al. 1999). In addition, e-mail allows messages using mobile technologies, but channel their additional time into to be sent almost instantaneously to any number of recipients. E- selling activities instead of building stronger relationships with mails have the additional advantage of being able to send person- existing customers. Discussion addresses the possible reasons for alized messages to customers. Even fax programs, such as WinFax, salespeople not redirecting their time toward customer relationship enables HR sales personnel to bypass the traditional fax machines, marketing, as it was postulated they would. hence saving time. The Internet is proving to be a powerful and low-cost way to TECHNOLOGY AND EFFICIENCY communicate with customers. The key to staying competitive is to provide timely and detailed information to consumers, and Internet Hardware access has become widely used with almost every company having Many companies have been providing their staff with infor- its own website for consumers or other stakeholders to gain access mation technology (IT) as it becomes available based on the to updated information about the company and the products. One of assumption that it will lead to an increase in productivity and other the most popular sales uses of the internet is in generating prospects. long run benefits for the company. Various studies of IT and Salespeople are becoming increasingly cyber-savvy to make con- performance/productivity have been conducted, but most of these tacts and subtly promote their products online (Success 1996). studies seem to be more concerned with the effects of IT on Also, distributing customer support information through the internet productivity at the industry/economy level. The findings from these is a cost-efficient and time-saving way of delivering information to studies are often contradictory in any case, and have led to the thousands of current and prospective customers (Taylor 1994). discussion of the “IT productivity paradox.” This paradox was Handheld device technology is rapidly becoming the standard formulated by Nobel laureate Robert Solow in response to the equipment for many mobile workers and for executives who are massive investments in IT that started began in 1980 yet seemed to frequently away from their desks. Many companies encourage their have limited positive effects on productivity growth (Solow 1987). employees to make use of PDAs because they are believed to be However, it was also argued that many of these studies suffered able to boost productivity away from the office (Lewis 2002). It has from methodological flaws in that they do not regard differences also been suggested that wireless applications may even make between firms or industries. business more proactive. The access to real-time data by remote Limited academic research has been devoted to the study of the service staff and the instant information on parts, inventory, and effect of technology on salespeople’s performance. However, early order status available to the salespeople will significantly improve case studies have shown the potential benefits of technology for service quality and reduce the transaction times (Xu, Yen, Lin, and salespeople (Cronin and Davenport 1990; Moriarty and Swartz Chou 2002). With more places providing wireless networking 1989). Still, little insight has been provided as to whether the use of infrastructure, mobile technology such as PDAs and WAP-enabled technology can add value. The objective of this research is to mobile phones are gaining popularity as they can support anytime/ examine the usage of IT among salespeople. More specifically, an anywhere access via networking. endeavor is made to find out whether higher usage of technology As technology advances rapidly, companies have provided results in a “better” alignment of time spent on the various activities technological equipment to their staff in order to stay competitive. in which salespeople are involved. As a result, desktop computers and laptops and other forms of IT Hammer and Champy claimed that the real power of technol- hardware have become fundamental tools in almost every com- ogy is not that it can make the old processes work better but that it pany. Personal computers have enabled the sales force to provide enables organizations to break old rules and create new ways of high quality customer service by having quick access to timely and working (Hammer and Champy 1993). This is evident in the role updated information (Futrell 2001). that the salesperson plays, which seems to have changed over the Anderson argued that notebook computers equipped with years as salespeople are no longer simply promoting their goods and various Sales Force Automation software applications have helped services to the consumers on a transactional basis in a bid to increase to reduce much of the paper work, helped to manage accounts, and sales. Many salespeople have evolved from transactional selling to helped to control sales administration tasks (Anderson 1996). Early become managers of customer relationships, and technology has in the last decade, laptop computers were shown to have the played a part in this transition by facilitating buyer-seller interac- potential to deliver substantial benefits (Moncreif, Charles W. tions, building stronger customer relationships and allowing easier Lamb, and Mackay 1991). Later, laptop computers were reported to access to critical sales information. Technology is thus increasing empower salespeople by allowing them to quickly and easily access the efficiency and effectiveness of salespeople through their ability their companies’ computer databases instead of going through their to improve communications between the salespeople, the selling sales managers or any other headquarters’ sources (Seideman organization and the customers (Taylor 1993). 1994). Hence mobile computing is generally seen as a valuable tool

Factor Activity Composition

Selling function Select appropriate customers, understand them sufficiently to plan appropriate presentations, select appropriate products for sales calls, make sales presentations, overcome objections, plan selling activities, introduce new products, identify buying center members, prospect for new customers, call on new accounts, help clients plan.

Working with Correct erroneous orders, expedite orders, handle back orders, and facilitate correction of shipment people within problems. own organization

Servicing the Test equipment, be present during repairs, supervise installation, learn about product usage/misusage product from customer’s technician, perform maintenance, make delivery using product, order accessories, teach safety instructions, train customers (and their customers) to use product.

Information Provide feedback to supervisors, receive feedback from clients, check-in with superiors, read trade Management publications, provide technical information.

Servicing the Inventory, set-up point of purchase displays, handle local advertising, stock shelves. Account

Conferences and Attend sales conferences and regional sales meetings, assist clients in managing conferences, meetings exhibitions, trade shows; , attend corporate and client training sessions.

Training and Recruit new sales representatives, train and mentor new representatives, assist sales management in recruiting planning future selling activities.

Entertaining Entertain customers and their customers in an interesting and appropriate manner.

Traveling Travel to visit customers both at home and away from home.

Working with Sell to distributors, train distributor sales people and technicians, establish relations with Distributors distributors, help them manage their inventories, extend credit, collect past due accounts.

for increasing the level of productivity and a competitive weapon thousand words” seems to still be true today, computer graphics can for organizations be very effective in creating an impact and capturing the attention of the clients during presentations. Software For a salesperson, maximizing time for daily accomplish- Alignment of Salespeople’s Time ments is essential for consistent sales performance. Time manage- A preliminary research project concerning the alignment of ment software enables the sales person to spend more time in front salespeople’s time revealed that their time is mainly spent as of the ‘right’ customers, plan his presentation and utilize non- follows (1996; O’Connell and Keenan 1990): Selling activities selling time in a more productive way. This improvement of time (56%), which is divided between face-to-face selling (31%) and management directly increases productivity. Contact management selling via telephone (25%). Traveling/waiting time accounts for is a listing of all the customer contacts. Contact management the second highest time usage (18%). Next is administration (15%) software such as the electronic address book enables the salesper- and account service/coordination (11%). These classifications of son to retrieve this information easily in a variety of formats. activities are rather broad, however, and provide little detail. In an Customers can be categorized into groups and assigned to salesper- earlier study reported by Moncrief (1986), 121 sales activities were sons, so that salespersons can perform tasks such as prioritize, identified. These activities are classified under ten headings shown schedule follow-up actions and update information easily. in Table 1. Microsoft PowerPoint is one of the most commonly used Several selling activities–product testing, installation supervi- presentation software packages which allows sales personnel to sion, accessory ordering, recruiting and training new sales rep and create dramatic and interactive computer based presentations at traveling with them, did not show up in a later study (Duncan and relatively low cost. As the old adage of “A picture is worth a Moriarty 1998), resulting in the elimination of one of the factors; Asia Pacific Advances in Consumer Research (Volume 6) / 59 “training and recruiting.” Furthermore, in their 1998 study, 49 new firms in Singapore. Face-to-face in-office interviews ensure a lower selling activities were identified in addition to the 121 selling non-response rate, and facilitate clarification of survey questions. activities uncovered in the previous 1985 study–and of the 49 new selling activities that were identified, 25 of them were technology- Questionnaire Development related (Marshall et al. 1999). Questions one and two of the survey probe into the kinds of IT that HR personnel use. Specifically, question one examines the HYPOTHESES DEVELOPMENT types of hardware used, whereas question two relates to the types of Technology is believed to make the selling process more software programs used. Question three uses a seven-point Likert efficient by automating highly repetitive support tasks, reduce the scale to assess the perceptions that HR personnel have on the time salespeople spend on non-selling tasks and thus give sales- relationship between technology and time management, as it was people more time to sell (Moriarty and Swartz 1989). IT should thought that attitudes might play a role in technology usage. generally ease and speed the sales persons’ information and com- In order to obtain a more specific proportion of time spent on munication processes and their performance. Therefore, IT-savvy each activity, respondents were asked to distribute a scale of 100% sales people will have the ability to build stronger customer rela- in accordance to the relative time they spend doing each item on the tionships, provide better customer service and enhance their pro- list of activities given to them. This constant sum scale was chosen ductivity (Colombo 1994; Duncan and Moriarty 1998; Keillor, for the ease of completion and understanding by respondents. Bashaw, and Pettijohn 1997). The generation of the list of activities for the respondents was Even though the number of activities identified as required for based largely on the findings of the research of Marshall, Moncrief successful performance of the sales task has generally increased et al. (1999), although these activities have been reclassified to suit (Marshall et al. 1999), the use of appropriate technology should still the nature of the human resource industry. Activities that are not improve salespeople’s productivity, freeing time from mundane relevant in this industry, such as “Working with Distributors,” are and repetitive tasks and allowing more time for selling. This is thus omitted. It is difficult to draw a distinct line between the presumably because salespeople who use technological tools will product and the client in the services industry; therefore, “Servicing spend less time on administrative tasks and are thus able to spend the Account” and “Servicing the Candidate (Product)” are com- more time on selling, providing customer service and developing bined and renamed as “After-Sales Service.” The terminology of customer relationships. Hence the related research hypotheses some of the activity-groupings have also been changed, to ease follow: respondents’ understanding. The list of activity classifications, as well as their activity composition, is shown in Table 2. Order taking H1: The use of mobile technology decreases the proportion of and order processing, and information processing and management time spent on administrative activities. are considered as administrative activities, as stated in hypothesis H2: The use of technology increases the proportion of time H1. spent on selling. A pretest of the procedures and the instrument was conducted H3: The use of technology increases the proportion of time with ten HR consultants from the target group, after which several spent on providing after-sales service. minor adjustments to the questionnaire were made. For instance, H4: The use of technology increases the proportion of time the constant-sum scale was changed from 100-hours to 100 percent, spent on developing customer relationships. because the pretest group expressed difficulty in allocating in terms of a 100-hours scale. It has also been suggested that mobile computing devices, telecommunication software and internet access are enabling sales- RESEARCH FINDINGS people to become virtually self-sufficient, thereby eliminating the need to travel (Anderson 1996). Therefore, we predict that as IT Tools that HR Consultants Use salespeople make more use of the available technology, they will Table 3 shows the percentages of HR consultants who use the spend less time on traveling. various IT tools. The survey showed that desktop PCs, word processors, web browsers and communication software (e.g.: email H5: There is a negative relationship between the level of clients) are the most popular technologies used by the HR consult- technology usage and time spent on traveling ants. It was also found that less than 50% of the respondents actually use mobile IT devices (e.g. cellular handphones, laptops, PDAs and RESEARCH METHOD WAP ’phones) on the job. To facilitate the testing of the hypotheses, the respondents are Sample and Data Collection first separated into two groups. Based on the survey data, users of The nature of selling activities differs among industries lead- WAP, PDAs or laptops are separated from non-users. From the ing to differences in the time allocated to various activities per- former group (users of WAP, PDAs or laptops), those who use Time formed by salespeople in these different industries. The sample Management Software (TMS), Contact Management Software frame consisted of 50 respondents from the human resource indus- (CMS) or web browsers are selected. This final classification of the try only. In this light, our focus is on the salespeople within that HR consultants in the sample, consists of 29 respondents classified industry (i.e. the HR consultants who are selling HR services). The as hi-tech users while the remaining 21 respondents fall under the objective of focusing on a single industry is to isolate the effects that low-tech users group. inter-industry differences would have on the time allocated to various activities. The relative usage level of technology by the Respondents’ Perceptions of Technology respondents is used to enable classification into hi-tech and lo-tech This variable was, unfortunately, not very helpful, as there is groups. an almost unanimous agreement that technology helps productiv- The survey was conducted through in-office interviews, using ity–in retrospect the social acceptability bias should, perhaps have a convenience sample of respondents from various head-hunting been avoided in the question framing. The 7-point scale mean 60 / Information Technology and the Sales Function TABLE 2 Classification of Selling Activities in the Human Resource Services Industry

Classification Activity Composition

Selling Function Screening potential candidates; making sales presentations; calling on potential accounts; planning selling activities; preparing sales presentations; identifying person in authority; searching out leads; call on new accounts; help clients plan; preparing candidate resume; etc.

Order Taking and Writing up orders; keeping track of invoices; handing over orders to support staff for processing; Order Processing calculating payments due from clients; verifying commissions; etc.

After-sale service Orientating selected candidates; visiting selected candidates; checking back on selected candidates’ performance; candidate replacement; etc.

Information Processing Generating sales activity reports; monitoring competitors; updating and maintaining a database of and Management clients & candidates; collecting customer feedback; etc.

Conferences / meetings Attending sales conferences; attending regional sales meetings; setting up exhibitions & trade shows; attending training sessions; etc.

CRM Sending letters & greeting cards; calling on existing clients, entertaining them.

Traveling Traveling to client’s location; traveling to meeting & conferences venue.

TABLE 3 Percentage of HR Consultants who use IT tools

IT Tools % of HR IT Tools % of HR Consultants Consultants

Desktop PC 96 Laptop 30 Word Processors 96 Contacts Management Software 28 Web Browsers 80 Personal Website 28 Communication software 76 Payroll Software 14 Cellular telephones 48 PDA 10 Presentation Software 42 WAP telephones 8 Time Management Software 32 Other software 4

(where “7”=agreement that technology the use of personal technol- service, traveling time, administration and, oddly, customer rela- ogy has enabled them to better manage and allocate their time) is tionship marketing activities. 5.2, the mode 5, and only three respondents answered below the mid-point of the scale. Hypotheses testing Hypothesis 1 states that the use of technology reduces the time Percentage Time Spent on Various Sales Activities spent on administrative activities. Analysis by ANOVA, where the The means, standard deviations and confidence intervals of dependent variable is time spent on selling and the independent is the percentage time spent on the respective activities are tabulated high- or low-technology usage, reveals an effect in the expected and presented in Table 4. direction (Mean(hi-tech)=13.5, Mean(low-tech)=10.6; F=.88, p=.05). An exploratory investigation of the relationships between Using Cohen’s classification of effect size and Hay’s Omega time spend on the respective activities was undertaken using squared (w2=.054) then this significant effect is on the cusp of being correlation analysis. Table 5 contains a summary of the correlations a small or medium effect (Cohen, 1977). between the variables included in this study, which are sufficiently H2 states that the use of technology increases the proportion of encouraging to encourage hypothesis testing. In particular, a strong time spent on selling; this hypothesis can also be tested by ANOVA negative correlation can be seen between selling and after-sales using the hi- and low technology categorizations as the independent Asia Pacific Advances in Consumer Research (Volume 6) / 61 TABLE 4 Descriptive statistics for the High- and Low-tech groups

Percentage Time 95% Confidence Interval Spent on: Group Mean SD Std. Error Upper Bound Lower Bound

Selling Lo 24.52 15.883 3.466 17.29 31.75 Hi 33.79 16.565 3.076 27.49 40.09

Order Taking & Order Lo 13.00 8.216 1.793 9.26 16.74 Processing Hi 11.03 7.835 1.455 8.05 14.01

Information Processing & Lo 14.00 9.899 2.160 9.49 18.51 Management Hi 10.10 6.253 1.161 7.73 12.48

Administrative Lo 13.50 5.718 1.247 10.90 16.10 Hi 10.57 4.779 0.887 8.75 12.39

After-sale Service Lo 17.86 12.204 2.663 12.30 23.41 Hi 15.17 7.960 1.478 12.14 18.20

Attending Conferences & Lo 5.24 4.867 1.062 3.02 7.45 Meetings Hi 7.00 5.292 .983 4.99 9.01

Traveling Lo 4.95 4.695 1.025 2.82 7.09 Hi 7.00 4.536 .842 5.27 8.73

CRM Lo 20.43 20.750 4.528 10.98 29.87 Hi 15.52 9.855 1.830 11.77 19.27

TABLE 5 Correlation matrix showing relationships between HR consultants’ time expenditures

Activity Selling After-sales Conferences Traveling CRM Admin. (as a % of total) service & meetings

Selling 1 -.327* -.178 -.339** -.525** -.299**

After-sales service 1 -.2 -.279* -.183 .067

Conferences/meetings 1 .382** -.135 .019

Traveling 1 .094 .042

CRM 1 -.410**

Admin 1

Note: *=correlation is significant at the 0.05 level (2-tailed). **=correlation is significant at the 0.01 level (2-tailed).

variable and selling time as the dependent. Again, the hypothesis is Hypotheses 3, 4 and 5 pertain to the use of high-technology supported (Mean(hi-tech)=33.79, Mean(low-tech)=24.42; F=3.94, allowing more time to be spent on after-sales service, customer p=.05). In this instance w2=0.056, another significant effect on the relationship management and less on traveling, but all three are not cusp of being small and medium-sized. supported statistically. 62 / Information Technology and the Sales Function DISCUSSION only might there be some real confusion here (certainly in the minds of the respondents, at least) about the real differences, but maybe Summary what we are seeing here is merely a short-term, rather than a long- The use of computer technology is becoming part of the life of term, sales concept at work? HR consultants, as it is for salespeople other industries all over the World. Whether it takes the form of computer-based contact man- Managerial implications agement, electronic mail or searching for information on the World The use of technology will eventually lead to a decrease in the Wide Web, all of the HR consultants in this study are using proportion of time being spent on mundane tasks by salespeople technology on the job in one way or another. In fact, the overall whether it is deliberately sought or not. However, sales managers usage figures surprised, as they seem somewhat low. Unfortunately could take a proactive stance and push to advocate the use of the data does not allow speculation as to whether this is an industry technology among salespeople; maybe financial incentives could effect (maybe HR consultants feel reluctant to use the technology, be used to this end, to subsidize the cost of personal technology preferring a face-to-face contact?) or a national one (the research purchases by sales personnel. Certainly, the company could pro- was conducted in an Asian city and thus may not reflect Western vide relevant hardware and software and training to its (HR) sales levels of usage). personnel. The results suggest a statistically significant negative correla- The freed-up time of HR consultants with the use of technol- tion between percentage of HR consultants’ time spent on selling ogy apparently does not necessary lead to more time being allocated activities and time spent on after-sale service, time spent on to developing and maintaining customer relationships. The fact that traveling, time spent on developing and maintaining customer time saving was not channeled to customer relationships mainte- relationships and time spent on administrative activities. The re- nance and after sale services meant that there is a possibility that the sults also suggest significant negative correlations between time HR consultants are not catching on to either the fact that productive spent on after-sale service and time spent on traveling, time spent time can be freed by technology, or that there is a general misunder- on developing and maintaining customer relationships and time standing, or disagreement, about the value of building and main- spent on administrative activities. In addition, a positive correlation taining a strong relationship with (certain) customers. There seems between the time spent on attending conference and meetings and an opportunity for companies to first of all establish their priorities, time spent on traveling was found. and then consciously direct the HR/sales personnel in the desired The study findings do not support the overall assertion that a direction–either a short-term sales orientation or to forgo one-time salesperson spends the time freed up from repetitive tasks for sales transactions and focus on building a long term relationship developing and maintaining customer relationships. As expected, with the customers. though, “hi-tech” HR consultants spend significantly less time on administrative activities than their “low-tech” counterparts, and Future research this represents an important finding. The second major discovery This is exploratory research that uses a local convenience here is that time freed up on administrative efficiency due to sample and descriptive research methods. Clearly, confirmatory technical sophistication is spent mainly on more selling. research on a larger scale, which could lead to wider generaliza- tions, would be of great value. Furthermore, the use of a nominal Implications for Theory scale to judge technical sophistication is crude; an equal-interview As in previous research with salespeople, it was found here scale would not only allow more sophisticated statistical analysis that the average HR consultant spends the greatest proportion of his/ but also allow the extent of adoption to be more accurately gauged. her time selling. An average HR consultant also devotes more than Furthermore, the list of software and hardware which we 30% of his/her time to after-sales service and customer relationship consider in our study now are limited only to those basic off-the development. In addition, a significant proportion of time is spent shelf products. With the introduction of 3G technology and Multi- on information processing, information management, order taking media Messaging Service (MMS), a broader list of hardware and and order processing. Only a small fraction of the HR consultants’ software can be developed. The list could also be extended to time is spent on traveling or attending conferences and meetings. include customized software and Sales Force Automation (SFA) Although it seems a truism, selling is, then, still the most important products on an organization level. aspect of a salespersons’ job. Nevertheless, a useful contribution has been made. That busy The literature had seems to suggest, though, that sales consult- salespeople can save time on administration by using mobile ants are spending more time on customer relationship management technologies has been empirically demonstrated, and the options of and after-sale services activities. In this customer relationship spending that “found” time on short-term sales efforts or on longer marketing era, it is a little puzzling that the HR consultants surveyed customer relationship activities has been highlighted as an issue for are not spending more time on developing customer relationships sales managers to ponder. and providing better service. Two speculations are tempting. First, in the tough economic REFERENCES climate prevalent in Singapore a short-term sales view may be (1996). Sales Force Compensation Survey. Chicago: Dartnell dominant. Again, it would be really interesting to find out if this is Corp. an industry or a national phenomenon; is lip-service only being paid Anderson, Rolph E. (1996). Personal Selling and Sales Manage- to customer relationship marketing in tough times, or is this a only ment in the New Millennium. Journal of Personal Selling a local issue? and Sales Management, 16 (4), 17-32. 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Keillor, B., E. Bashaw, and C. Pettijohn (1997). Salesforce Automation Issues Prior to Implementation: The relationship between attitudes towards technology, experience and productivity. Journal of Business and Industrial Marketing, 13 (3/4), 209-19. Lewis, Peter (2002). The Best PDAs for Business. in Fortune. Marshall, Greg W., William C. Moncrief, and Felicia G. Lassk (1999). The Current State of Sales Force Activities. Indus- trial Marketing Management, 28, 87-98. Moncreif, William C., Jr. Charles W. Lamb, and Jane M. Mackay (1991). Laptop Computers in Industrial Sales. Industrial Marketing Management, 20 (1), 279-85. Moncrief, William C. (1986). Ten Key Selling Activities of Industrial Salespeople. Industrial Marketing Management, 15, 309-17. Moriarty, Rowlan T. and Gordon S. Swartz (1989). Automation to Boost Sales and Marketing. in Harvard Business Review Vol. 67. O’Connell, William A. and William Keenan, Jr. (1990). The Shape Of Things To Come. in Sales and Marketing Manage- ment. Seideman, Tony (1994). Who Need Managers. Sales and Marketing Management, Part 2 (June), 15. Solow, Robert L. (1987). We’d Better Watch Out. in New York Times Book Review. Success, Selling (1996). Rent a Sales Superstar. in Selling Success. Taylor, Thayer C. (1993). Laptop Fever Grips Marketers. in Sales and Marketing Management Vol. 1993. (1994). Marketing: The Next Generation. in Sales & Marketing Management. Xu, Yurong, David C. Yen, Binshan Lin, and David C. Chou (2002). Adopting Customer Relationship Management Technology. Industrial Management and Data Systems, 102 (8), 442-52. Why Functional Specialists Should Be Encouraged to Use the Internet: The Changing Pattern of Influence in Buying Centers Roger Marshall, Nanyang Technological University, Singapore Na WoonBong, Kyunghee University, South Korea Park ChanWook, Kyunghee University, South Korea Peter Allan Reday, Ashland University, U.S.A.

ABSTRACT company or product/service image. At a firm level, organizations It is hypothesized that the influence structure of industrial are thus often faced with a number of escalating concerns. Basic purchasing centers will vary depending upon whether or not the costs are rising, technical complexity of the media decision is company is Internet-enabled as functional specialists will become increasing, the use of Internet, inratranet and extranet to further more knowledgeable. Analysis of the research data shows that the develop customer relationships and expedite operations all call for marketing managers in the Internet-enabled companies are signifi- further image co-ordination. All this, plus the fact that few firms cantly more influential over the stages of the decision compared to have the internal expertise to manage this communication process both their counterparts in non Internet-enabled companies and to themselves so find it necessary to entrust the reputation and image their CEOs. of the company to the hands of another organization– it is little wonder that the selection of advertising agency service is so PROBLEM ORIENTATION important. For decades, ever since the importance of the group purchase As long ago as 1988 a call was made to delineate the organi- process within industrial organizations was identified and encapsu- zational decision process that results in an advertising agency being lated into models of industrial purchase behavior, research has been hired, and to identify the key participants in it (Harvey and Rupert carried out with regard to the power structure and size of organiza- 1988). This call has oft been heeded, and so we have fairly detailed tional buying centers. It is our belief, however, that a sweeping answers (Cagley, et al. 1984; Cagley 1986; Lynn 1987; Harvey and change is taking place in the structure of company buying centers Rupert 1988; Marshall and Na 1994; Kim and Waller 1999; Na, because of the impact of Internet. Marshall et al. 1999; Na and Marshall 2001). These, and other It is often said that we live in an information age. The important appropriate papers, will be inspected shortly as the research hypoth- implication of the statement is that those who have information eses are develop. have power, should they choose to use the information. It is a basic premise of Internet business models that information is readily HYPOTHESES DEVELOPMENT available to anyone who cares to tap into the appropriate network; thus the hierarchical nature of information diffusion within organi- Size of the Buying Center zations (and, thus, the traditional power structure) is no longer The buying center includes all members of the organization necessarily applicable. This idea is neatly encapsulated in the work who are involved in the buying process. The structure of this group of Evans and Wurster (Evans and Wurster 1997), who emphasize fluctuates as expertise is required, or time-pressure is felt. As the possibility of almost immediate diffusion of information within purchasing groups are usually informal in nature, there is often no either an intranet system or on the World Wide Web. audit trail to enable the precise structure of buying centers to be This suggests to us the possibility that everyone in the buying defined. Over the years, however, many studies have been con- center–who cares to seek for it, at least–can now have access to ducted to investigate the mean size of buying centers in various information that was exclusive to information gatekeepers in the types of organizations. Variables such as the size of the organiza- past. Past studies have documented the typical influence of various tion (Bellizzi 1981; Crow and Lindquist 1985); the value or impor- role players in industrial buying centers, but it seems likely to us that tance of the purchase made (Johnston and Bonoma 1981); the in this new information age new patterns may begin to appear. It is length of time a buying relationship has existed (Lynn 1987) and the the primary purpose of the research reported here to speculate what type of industry the purchasing firm operates in (Crow and Lindquist these patterns might be and to conduct some preliminary field work 1985) have been included in these studies to investigate their impact to test these speculations. on the size of an organization’s buying center. A summary of the figures from current research is presented in Table 1. SELECTION OF A SPECIFIC SERVICE It can be seen, from a scrutiny of the Table, that buying centers To facilitate this study of the influence of Internet on buying concerned with purchasing advertising agency services are signifi- centers, we have selected advertising as the service to be purchased cantly smaller than those for most industrial goods. There seems a by industrial buying centers. The rationale for this choice is based consensus that this is mainly because of the specialized nature of the not only upon the importance of the decision but, mainly, the service being purchased. convenience of having specific, published, recent data about the None of this research has taken explicit notice of the use, or size and influence structure within such selection teams (as this lack of use, of Internet, and what impact on the size of the buying literature calls corporate buying centers purchasing advertising center this factor might have. Thus there is no guide whatsoever in agency services). this matter, other than the development of a logical argument from Few would argue with the statement that advertising expenses our current observations. It is quite clear that anybody in the buying are generally increasing. Among the many reasons for this must be center can gather any amount of information about almost any the availability of a wider, technology-enabled media selection, agency anywhere in the world, should they so desire. As few have plus increasing competition in so many markets, and the need to the motivation to search for this particular information, however, reach diverse and wider markets with globalization that must place we cannot see that the size of the buying center should differ pressure upon the structure and maintenance of an appropriate whether Internet is widely used by company executives or not. That

Study Scope Buying center size

Speckman and Stern [20] Industrial goods purchase, USA 6.20

Lynn [6] CPA services purchase, USA 3.53

Marshall and Na [7] Advertising agency selection, New Zealand 2.98

Na & Marshall [8] Advertising Agency selection, South Korea 4.44

is, it is interest that probably drives extended search behavior, and players in the process, the CEO and the marketing manager. In we believe that few people other than those explicitly involved in situations where there is an advertising manager, then s/he tends to the advertising agency purchase situation would have that interest. supplement or complement the marketing manager’s influence This logic is especially compelling in the agency situation, where (Marshall and Na 1994; Na and Marshall 2001). The pattern of it has already been noted that the specialized purchase topic results influence suggested by this latter research follows a fairly common- in a smaller than usual purchase team. Hence: sense path; the CEO is most influential during the initiation and the final stages of the decision, whilst the marketing manager has the Hypothesis 1: No significant difference exists in the sizes greatest influence during the identification of potential agencies of buying centers of companies that widely and the review process. use the Internet and those that do not. The pattern of influence that might evolve with the widespread adoption of Internet within a firm, we believe, is that the marketing The structure of Influence within Buying Centers manager (or advertising manager if there is one) will generally Although we do not believe that the size of agency buying become more powerful. This is because although more information centers will vary with the introduction of Internet usage, the same is available to both the marketing manager and the CEO, it seems is not true for the influence structure within centers. Again, there is unlikely that a general manager could be bothered to seek it out. On no specific literature to help formulate our ideas about what this the other hand, a marketing manager is probably interested in the change might be, so we will again weave a picture of what may be information for it’s own sake, in the acquisition of knowledge that going on here, using only the woof of logic and the warp of will add to his/her stock of expertise, and in gaining credibility in observation. That there will be some sort of differential impact the eyes of his/her employer. caused through the level of technology utilized by companies within which buying centers operate, however, can be justified by Hypothesis 2: Marketing Managers will have more influ- reference to the established literature. Right from the beginning of ence throughout the advertising agency se- academic interest in buying centers, it has been postulated by a lection process in companies that widely use number of authors that the structure of the buying center will be the Internet than in those companies who do affected by the environmental factors surrounding it. Webster and not. Wind (1972) and Sheth (1973), in their early models, postulated that different types of influence surround the center like the skins of an The corollary of this situation is straightforward–the CEO of onion; with physical, economic and legal environmental factors the companies using Internet extensively will have less influence than outer layer, and then organizational, technical, economic and cul- their counterparts in companies that make less use of Internet. This tural factors in successive layers of influence getting ever closer to is because gaining and losing influence within any buying center is the buying center itself. The same set of factors, albeit presented a zero-sum game; power gained by one player must be at the rather differently, figure in the models and lists of later authors also expense of another and, as we have seen, there are few powerful (see, for instance Hart (1984)). None of these authors tell us just players in this particular purchase situation. Thus our final research what to expect in this specific situation, where the technological hypothesis: factors are so critical, however; but none could have possibly imagined the sweeping power of the Internet, either. Hypothesis 3: CEOs will have less influence throughout There is strong evidence that information empowers the holder the advertising agency selection process in in situations such as this. The Technology Gatekeeper idea of Allen companies that widely use the Internet than (1984), as well as the well-developed Opinion Leadership construct in those companies who do not. (e.g. Childers (1986)), are predicated on this principle. It has been noted above that the buying center for advertising agency services RESEARCH METHODOLOGY is small, as the interest and the knowledge required to participate in the purchase process is limited. Thus it seems likely that the Overview influence structure with the buying center will vary according to the An initial survey was distributed to interested MBA students, acquisition of specialist knowledge by interested parties. studying on a part-time basis. With their cooperation contact was The literature about advertising agency selection is very made with the Marketing Managers of a number of companies. specific about these influence structures. There are two main These company officers were given a questionnaire that helped 66 / Why Functional Specialists Should Be Encouraged to Use the Internet TABLE 2 Profile of two sample groups

Variable Low Internet usage group (15) High Internet usage group (21)

Type – Industrial 53% 43% – Consumer 33 33 – Not classified 14 24

Number of employees – Under 50 33 33 – 51–100 33 43 – 101–300 20 19 – Over 300 14 5

Sales – $3m –5m 27 19 – $5m–10m 27 19 – $10–20m 33 33 – Over $20m 13 28

Advertising as percentage of sales – 1% 33 28 – 2% 40 33 – 3% 20 33 – 4% 6 5

identify the influence structure over stages of the advertising identification and evaluation of possible agencies into two stages as agency selection process. Consequent analysis breaks them into it was felt that the two processes are actually different and, if they two groups, high and low Internet usage, then compares their were to be collected separately, accuracy of the findings would be decision structures. enhanced. The second questionnaire (meant for the Marketing Manag- Sample ers) comprises of three sections. The first is used to identify the team The sample is a convenient quota sample–responses were members participating in the advertising agency selection. The collected until we had a reasonable balance of companies, in terms identification of participants was by free elicitation, which is of Internet usage. Data from 36 companies were finally used; claimed to minimize the bias imposed by forced choice scale and to profiles of the companies, sorted into their operational categoriza- allow the flexibility to cope with the complex structures involved tion, are contained in Table 2. There is some evidence of a (Robles 1984). When identified, a constant-sum technique is used difference between the two groups–the low-user companies tend to in the second section of the instrument, where 100 points are be larger in terms of employee numbers but smaller in terms of distributed between all the identified selection-team members. This dollar sales and advertising expenditures as a percentage of sales – is not a classical “snowball” technique, where the responses of all this might indicate that the high users are in a more high-tech members of the buying center are solicited then averaged, to better environment, which is not, of course, surprising. The literature on arrive at a fair rating of influence, but is entirely the subjective advertising agency selection has not related any of these factors to opinion of the marketing managers. In this preliminary work we do influence structure, so this difference in the sample is ignored. not think that this bias matters, as it is the same for all the companies surveyed and we are interested in the comparison between the two Research Instrument groups rather than the absolute levels of influence. Initial survey cum letter The third section of the instrument elicits information to allow The preliminary instrument was distributed to MBA students, differentiation between companies that use Internet in the selection and simply contained an explanation and a few questions to classify process of advertising agencies and companies that do not. Three, the companies for whom they worked. This was to minimize the 5-point Likert-style questions are used, to enable a scale to be amount of information needed to be collected from the marketing developed. managers. Main survey instrument Procedure Naumann, Lincoln and McWilliams (Naumann, Lincoln et al. As mentioned above, a strictly convenient basis was used for 1984) set the precedent of breaking the buying process for adver- selecting companies, asking part-time MBA students to provide the tising agency services into four stages; initiating the selection or contact to their companies. It is hard to obtain this type of data and change of an agency, establishment of objectives and need configu- the method used is far from ideal. The working principle, however, ration, identification and evaluation of possible agencies, and the is that if there really is as much difference between Internet-users final selection. Others have followed this lead, (e.g. (Harvey and and non-Internet-users as anticipated, then it will show despite the Rupert 1988; Marshall and Na 1994; Kim and Waller 1999; Na and less-than-ideal sample. The MBA students made contact with their Marshall 2001). It was nevertheless decided to further split the colleagues and passed the relevant questionnaire to them, along Asia Pacific Advances in Consumer Research (Volume 6) / 67 FIGURE 1

Relative influence of marketing managers and CEOs in companies extensively using internet and those not

1A) Companies who do not make 1B) Companies who do make extensive use of Internet extensive use of Internet 10 10 9 9 8 8 7 7 6 6 5 5 4 4 3 3 2 2 1 1 0 0 12345 12345 Stage of decision Stage of decision

Note: Broken line = Marketing Manager Unbroken = CEO

with a stamped, addressed envelope for their response. The ques- mean influence of the marketing managers and CEOs are statisti- tionnaire was short, easy to answer and asked nothing of a confiden- cally different. Thus marketing managers with greater information tial nature; consequently there was a very low refusal rate and no access (in high Internet-usage companies) gain power at the begin- apparent lack of understanding. ning and end of the process and only show no such increase in the middle part, where they are already the strongest player anyway. RESULTS CEOs’ influence loss is ubiquitous. Both Hypothesis 2 and 3 are strongly supported. Preliminary matters Cronbach’s alpha for the three-item, 5-point scale used to DISCUSSION ascertain Internet usage is 0.945, suggesting that the items do form This simple research illustrates an idea that most people are a reliable scale. The single item consequently formed from the scale already familiar with–that ownership of information can lead to mean value was then used to divide the respondent companies into power. Actually, the idea is just a little more complex than this–it two groups, high and low Internet usage. A t-test between the is reputed that Einstein said that imagination is more powerful than Internet usage variable of the two groups (high and low usage) knowledge; we understand this to mean that knowledge/informa- shows that separation was achieved (Mean(High use)=4.5, Mean(Low tion only leads to power if it is applied. This idea is neatly use)=1.83, t=18.28, p<0.001). demonstrated here in that the information that marketing managers seem to have acquired has indeed led them to a more powerful Hypothesis testing position when applied in a very practical decision situation. A further t-test reveals that, as suspected, the mean size of The finding reported here make intuitive sense–CEOs are advertising agency selection teams between the two groups is usually not really that interested in advertising matters per se; under statistically no different (Mean size(High use)=2.95, Mean size(Low pre-Internet conditions they merely wanted to be assured that an use)=3.00, t=0.128, p=0.899). This was as anticipated (in Hypoth- optimal decision is made and therefore seemed to retain control of esis 1), and that the overall mean size of the selection teams is 2.97 the all but the “donkey-work” of the advertising agency purchase adds credibility to the findings, as this is in line with previous decision. In the high Internet-usage situation, where their market- findings. ing manager is seen to be very knowledgeable about the matter, it appears that they are prepared to empower the expert, thus freeing Effect of Internet usage on the influence of Marketing Manag- their own valuable time for other, more appropriate, matters. ers (By Stages) The guesswork above is linked to the fact that the information The data presented in Figures 1A and 1B sum up the difference enabling marketing managers in high Internet-usage organizations in influence structure between the two groups of companies. As can to gain influence is also available to their CEOs. As stated in the be seen, the marketing managers are empowered in the companies introduction, however, it seems improbable that CEOs would in which Internet is used extensively. To give statistical support to bother, as the Internet offers them–in turn–a wealth of other, more the charts, Table 3 shows the stages of the decision for which the critical, information of a more strategic than operational nature. 68 / Why Functional Specialists Should Be Encouraged to Use the Internet

TABLE 3 Significance of between-group influence differences

Stage 1 Stage 2 Stage 3 Stage 4 Stage 5

Fp Fp Fp Fp Fp

Mktg. Mgr. 11.04 .002 6.33 .017 .49 .485 2.34 .135 14.29 .001

CEO 17.60 <.001 20.22 <.001 6.45 .016 7.87 .008 15.41 <.001

IMPLICATIONS REFERENCES Decision-making is the central operational business of busi- Allen, T. J. (1984). Managing the Flow of Technology. Cam- ness, therefore anything that can add to the efficiency of the process bridge, MIT Press. Information gate-keeper book is valuable. It is obvious that the availability of good information Bellizzi, J. A. (1981). “Organizational size and buying influ- makes decisions easier to make, it is also fairly obvious that the ence.” Industrial Marketing Management 10(1): 17-22. Internet should make a great deal of information available to aid Cagley, J. W. (1986). “A comparison of advertising agency with these decisions. What is not quite as clear is that a distinction selection factors: Advertiser and agency perceptions.” needs to be made between Internet information that provides Journal of Advertisng Research 26(3): 39-44. support for operational decisions and that which supports strategic, Cagley, J. W., , et al. (1984). “Criteria for Advertising Agency more competitive decisions. Functional, middle-management spe- selection: An objective appraisal.” Journal of Advertising cialists should, perhaps, concentrate on the acquisition of the Research 24(2): 27-31. former information type, which will lead them to become more Childers, T. (1986). “Assessment of the psychometric properties expert, while strategists should try to avoid getting overwhelmed by of an opinion leadership scale.” Journal of marketing the information needed at this operational level. research 23(May). This is merely another restatement of the fact that managers Crow, L. E. and J. D. Lindquist (1985). “Impact of organiza- already understand, the need for specialization. However, deliber- tional and buyer characteristics on the buying center.” ately using the Internet to reinforce this process is, perhaps, not as Industrial Marketing Management 14(1): 49-58. commonly understood. That this is true is witnessed by the fact that Evans, P. B. and T. S. Wurster (1997). “Strategy and the new we found 15 of the 36 companies we conveniently selected not to economics of information.” Harvard Business Review 75(5): be going through this process. Furthermore, the fact that the 70-82. companies we worked with were already enlightened enough to Hart, N. A. (1984). The Marketing of Industrial Products. New encourage their staff to undertake part-time MBA studies may well York, McGraw Hill. have contributed to the higher proportion of companies we found Harvey, M. G. and J. P. Rupert (1988). “Selecting an Industrial that do make quite extensive use of Internet. Finally, it has to be said Advertising Agency.” Industrial Marketing Management that we have no means of telling whether the empowerment that 17(2): 119-127. seems to be taking place is planned, or is simply happening as a Johnston, W. J. and T. V. Bonoma (1981). “The buying centre: positive spin-off from Internet usage. Structure and interaction patterns.” Journal of Marketing The obvious marketing message this research holds is the 45(Summer): 143-56. empirical fact that the target executive for advertising agents is the Kim, S. F. and d. Waller (1999). “Factors in winning accounts: CEO when Internet is not widely used, and the marketing/advertis- The views of agency account directors in New Zealand.” ing manager when Internet is widely used. Thus the ideas of Sheth Journal of Advertising Research 39(3): 21-32. and the other, earlier marketing writers is justified, and the environ- Lynn, S. A. (1987). “Identifying buying influences for a mental factors do impinge upon buying center dynamics, and in a professional service: Implications for marketing efforts.” far more dramatic way than they can possibly have imagined. Industrial Marketing Management 16: 119-130. Of course, we have only checked one decision situation. It Marshall, R. and W. Na (1994). “The advertising agency seems very probable to us that the same situation is true for the selection process.” International Journal of Advertising purchase of other professional services (the advertising agency 13(3): 217-227. selection situation has already been shown to be very similar to the Na, W. B. and R. Marshall (2001). “A Cross-cultural Assess- accounting services selection decision (Lynn 1987; Harvey and ment of the Advertising Agency Selection Process: An Rupert 1988). The extent to which the findings reported here empirical test in Korea and New Zealand.” International generalize to the wider buying center situation is an entirely open Journal of Advertising 20(1): 49-66. question, but there seems no reason why the logic should not be Na, W. B., R. Marshall, et al. (1999). “An assessment of transferred. Advertising Agency Service Quality.” Journal of Advertising Research 39(3): 33-41. Asia Pacific Advances in Consumer Research (Volume 6) / 69 Naumann, E., D. J. Lincoln, et al. (1984). “The purchase of components: Functional areas of influence.” Industrial Marketing Management 13(2): 113-122. Robles, F. (1984). “Buying in a matrix organization.” Industrial Marketing Management 13(3): 201-208. Sheth, J. N. (1973). “A model of industrial buying behavior.” Journal of Marketing 37(October): 50-56. Webster, F. E. J. and Y. Wind (1972). “A general model for understanding organizational buying behavior.” Journal of Marketing April: 12-19. Internet-Enabled Knowledge Acquisition and Power in Family Decisions Roger Marshall, Nanyang Technological University, Singapore Peter Alan Reday, Ashland University, U.S.A. Na WoonBong, Kyunghee University, South Korea

ABSTRACT marketing people in the same way that direct mail (electronic or not) The relationship between knowledge and power appears and interpersonal communication channels are. Even the reach of assumptive in marketing, the study reported here is designed to information contained in advertising materials is generally under- justify this assumption. The study is set in a family decision context. stood by marketers, but there is no way, at this time, that the Internet Families are divided according to the domain-specific Internet use habits of specific role-players in decision groups can be predicted of sons, then family decision-power patterns are inspected for a satisfactorily. If knowledge acquisition is enhanced through Internet range of products. The relationship between the Internet enabled, use and knowledge does indeed lead to power, then the familiar domain-specific acquisition of knowledge and power in group patterns of power in group purchase decision centers may well be decisions is supported. disrupted in hard-to-forecast ways. A search of the literature (not just the marketing literature, but several related literatures as well) DEVELOPING THE RESEARCH ISSUE reveals that the issue of knowledge and power in group decisions The relationship between knowledge and power has been a has remained assumptive; rigorous attempts to verify the relation- matter of more than just academic interest for centuries. Sun Tzu ship have never been reported. This gap in the literature provides an discussed the power of information within a military context some motivation and a focus for this research. 300 years before Christ. In the late Sixteenth Century, when Francis Bacon wrote of knowledge being power, he was a herald for an RESEARCH METHOD industrial age when knowledge was no longer to be hoarded by an elite few, but was to become far more widely shared and applied. Hypothesis development The application of the rapidly-growing body of knowledge, mostly The basic contention under consideration is that domain- as technology, led to the rapid growth of physical power, produc- specific information acquisition will lead to an increase of decision- tivity, profits and standards of living for those who harnessed it. The power in purchase situations involving the specific domain. To test link between organized, useful information (hereafter called knowl- this idea data is gathered from families which are carefully matched edge) and power in a scientific, technical sense is well-entrenched, on a number of relevant dimensions, in order to minimize contami- and a scan of the technical innovation literature shows that the nation from alternative explanations. First, the Internet usage of relationship is still deemed to be relevant (Carter and Scarbrough adolescent sons with respect to their parents is ascertained and, 2001; Hislop, Newell, Scarbrough, and Swan 2000). second, the family buying power patterns exhibited for thirteen Closer to marketing, negotiators speak of knowledge as giving products are identified. There is, once again, only a single, simple power, too. It is widely recognized that information about the research hypothesis: objects of negotiation and opponents in a negotiation situation can lead to a clear advantage to a negotiator (e.g. Weingart, Hyder, and H1: The acquisition of domain-specific knowledge by an Prietula 1996). The Internet and computer technology have lead to individual will enhance the power of that person, within yet another tightening of the relationship between knowledge and the relevant domain, in a group-decision situation. power, as companies have moved to knowledge-management and data-based marketing in order to optimize the use of the flood of Sample information that has become so readily available to them. The As the drive of this research is to build theory and not simply relationship is clearly recognized in both the popular literature (e.g. to provide empirical information, representation of the sample was Teresko 1996) and in the academic literature (e.g. Grimshaw 2001). sacrificed in favor of control. The literature on family decision The objective of the research reported here is to find out making is well established, and a number of factors have emerged whether or not an assumption can be made by marketers that which are understood to exert an influence on the power of the organized information, or knowledge, leads to power in group family decision role-players. Control of these factors is discussed purchasing decisions. Logic certainly supports such a view. If a below. group decision can be viewed as a negotiation (and it often is, if the Adolescent boys were selected as the focus for the research for marketing literature is taken at face value) then the acquisition of several reasons. In order to give the effect under consideration a pertinent information not held by others in the group should lead to good chance to show, adolescents were chosen as they are more the information-gatherer gaining power in the decision. Again, the likely to have input in family decisions than their younger siblings whole rationale for information gatekeepers and opinion leaders is (Foxman, Tansuhaj, and Ekstrom 1989; Lee and Beatty 2002). This based upon the idea that relevant information assists persuasion is particularly pertinent as the knowledge under consideration is through either adding to the persuader’s perceived credibility or by being acquired via the Internet; adolescent children are more likely controlling the flow of information (Allen 1984; Childers 1986). to be Internet users than their younger siblings, especially with The topic takes on a new relevance and importance when the respect to the use of the Internet for purchase-related search. Boys possible impact of the Internet on group purchase decisions is were selected, rather than girls, as a control measure. Given that the considered. Patterns of influence are fairly well understood, in focus falls on families whose eldest child is a 13 to 15 year old son, general, in both industrial and family group decisions. But–if the the family life cycle (which has been shown to have a strong impact knowledge-power link is indeed real–then the emergence of the on family decision patterns) is also effectively controlled. Internet has brought a whole new perspective to bear on group Ethnicity obviously does have an influence on family decision decision power structures, as Internet access is not controlled by patterns, as much empirical research has demonstrated (e.g. (Lee

70 Asia Pacific Advances in Consumer Research Volume 6, © 2005 Asia Pacific Advances in Consumer Research (Volume 6) / 71 and Marshall 1998; Na, Marshall, and Son 2003). An attempt was lies (mean Sons’ Comparative Internet Usage=49.2, SD=7.6). This made to optimize control by limiting even sub-cultural ethnic represents a significant difference in comparative Internet usage participation, so that whatever effect emerges can be reasonably (t=19.7, p<.001). ascribed to the information-acquisition manipulation and not to a Dependent variable, Decision Power contaminant. Consequently, responses from minority ethnic groups Measurement of decision power follows documented prior were removed, so all 255 nuclear families providing data are from research (Lee and Beatty 2002; Mangleburg 1990). Data were the same ethnic group. collected from each of the three family members, on a 100-point, Social class is strongly related to culture, and there is an constant sum scale, regarding the perception of each others’ (and established literature that shows that lower- and upper-class fami- their own) decision power for 13 products, over three decision lies tend to exhibit a stronger, more traditional sex-role orientation stages (Initiation, negotiation and final decision). Means were then than the more liberal, middle and upper-middle classes, resulting in calculated across each decision stage to yield a single number a more democratic process in family decisions (Lee and Marshall representing the mean power of each family member for each 1998). As social class is such a difficult construct to operationalize product. an employment proxy was used here, and all the respondent families were drawn from the white-collar group, who are more ANALYSIS likely to have Internet access than blue-collared. The analytical focus Data Preparation First, it should be noted that the decision topics selected were Independent variable, Comparative Internet usage deliberately chosen, from topics used previously, to offer a range of The extent of Internet usage, for the purposes of acquiring products with regard to the expected change of influence of an purchase-related information, is quite hard to assess objectively. adolescent son (Mangleburg 1990), particularly when he becomes The first item collected was a straightforward question asking more Internet enabled. Thus it was thought that sons would try to respondents to state the average number of hours per month which exert influence in the selection of their own sports clothing, music were spent seeking product/service-specific information on the CDs, computer hardware/software and computer games. It was Internet. Although this measure has strong face validity, there are further considered that these are not “bookish” young people, so a number of problems with it regarding reliability, as not only is it books might not be important to them and neither might family difficult to accurately recall the “average hours” spent doing almost activities such as eating out, going to the movies or going on family anything, but also it is very hard to distinguish between directed holidays. Although family decisions–such as the purchase of TV search and casual surfing. A single item is, in any case, intrinsically and audio equipment–are less easy to hypothesize about, there unreliable. Consequently, a seven-item scale was also constructed, seems at least a possibility that these products might come under the asking each son, mother and father about their preferences and influence of a maturing, Internet-savvy young son. Certainly it was willingness to search for information prior to purchase. not expected that their parents’ clothing or banking activities would After deleting one (reverse-scored) item the scale has an Alpha hold the remotest interest for these teenagers! of .82 for sons, and .92 for both mothers’ and fathers’ usage. In order to test the validity of the usage scales, they were compared to the Factor analysis, purchasing power relevant single-item statements concerning the number of hours Factor analysis of the purchasing power of sons for the 13 each respondent claimed to spend searching for data in an average products was undertaken using SPSS. This is a Q-type analysis, month. In each case there is a low, but positive and significant where there is an assumption about an underlying change of correlation between them (Sons’ r=.24, p=<.001; Fathers’ r=.34, behavior of the respondents in relationship to the type of product p=<.001 Mothers’ r=.48, p<.001). Even the fact that sons’ corre- being considered, rather than an R-type where the relationship lation is lower adds to the validity, as it seems likely that sons would between the factors is of primary importance. The Kaiser-Meyer- have greater difficulty than their parents in sorting out in their minds Olkin measure of sampling adequacy is .77, and Bartlett’s test of the difference between searching for domain-specific information sphericity is both high (806.4) and highly significant p<.001). and Internet cruising. Furthermore, the number of observations is 168 and the number of Furthermore, there is a need to compare comparative, rather variables (products) is only 13; giving a satisfactory observations- than absolute usage of the Internet for information search purposes, to-item ratio (see, for instance, Hair et al (1995)). of the adolescents. That is, if one son has an absolute high usage rate General Least Squares analysis was used to extract the factors, but his parents have an even higher exposure, then his real, com- as there are only 13 items in the variable list and several fail to reach parative Internet usage is less than another son with an absolutely the .6 communality level suggested by Gorsuch (1983). An or- lower usage but whose parents barely use the medium. Thus sons’ thogonal rotation was used, because uncorrelated factors are a Internet usage was re-expressed as a proportion of the total family preferable output of the analysis which is intended for use in further Internet use. analysis by ANOVA. A VARIMAX rotation was selected, (al- An inspection of this scale for Sons shows the distribution to though a test showed that neither EQUIMAX, PROMAX nor be somewhat leptokurtic (kurtosis=1.59), and slightly skewed QUARTIMAX yield significantly different factor solutions). (skewness=.76). This centralizing tendency was expected both Three factors emerged from the analysis, with Eigenvalues of because of the homogeneity of the respondent families and the large 3.74, 2.79 and 1.45 respectively; the total variance explained is sample size. There do not seem to be any natural breaks in the 62%. The Rotated Factor Matrix is shown in the Table. At a distribution of the variable, however, so the data set was divided significance level of 0.05 and a power level of 80%, the sample size into three equal groups and only the two extreme groups were used of 168 would conservatively suggest that loadings exceeding .45 in consequent analysis. Thus, the final sample is composed of two should be considered as significant. homogenous groups of nuclear families, each fulfilling the sample There is little ambiguity in the data displayed in the Table; the requirements concerning ethnicity, family life cycle and social factors seem quite clear and are easy to name. Factor 1, “Youth- class. Group 1 consists of 83 families (mean Sons’ Comparative centric”, consists of the few product decisions that it was considered Internet Usage=30.1, SD=4.5); while Group 2 consists of 85 fami- adolescent males would care to exert an influence on and where 72 / Internet-Enabled Knowledge Acquisition and Power in Family Decisions TABLE Factor Loadings

Variable Factor 1 Factor 2 Factor 3

Music CDs for young person .85 Computer games for young person .79 Sports products for young person .78 .20 Non-educational books for young person .78 Computer hardware/software .62 .37 Mothers’ clothing -.21 .79 Fathers’ clothing -.20 .78 Family car .67 .23 Financial services .67 -.32 Home entertainment (TV, audio equipment) .23 .63 .36 Restaurant for family meal .86 Family holiday .39 .64 Family movie .31 .63

Note: Loadings under .20 have been suppressed

their new-found knowledge might give them an edge, although Negotiation(Low)=51, F=8.7, p=.004; Final(High)=43, books do feature on the list and were not expected to. The second Final(Low)=35, F=9.0, p=.003). factor, “Parent-dominated”, consists of items where a youth would normally be excluded from participation (later analysis shows a DISCUSSION mean comparative purchase influence for sons of only 12%). The The study reported above offers strong evidence that the final factor, “Syncratic”, represents the joint decisions that are acquisition of information specific to a purchase domain, which made in the light of fairly extensive product knowledge of all the increases an individual’s knowledge, will add influence to that participants, whether or not they access the Internet (again, later individual in a group decision situation. The precise mechanics analysis shows a fairly equal decision influence here). involved–that lead from information acquisition to power in group The inclusion of books in Factor 1 surprised. Hence, an decision-making–are not clear for the research. It seems probable investigation was undertaken, by t-test, to gauge the extent to which that new knowledge merely aids it’s owner to negotiate his/her Internet empowerment effects the influence children have in the point of view more persuasively, but it is also possible that the selection of books, and it was found that there is no change knowledge provides more credibility to the role-player in the eyes whatsoever. This could, perhaps, be a function of their already- of his/her fellow decision-group members. Nevertheless, the fact strong influence in the area (in excess of 50% of the family’s that there does seem to be a significant change in the balance of decision weight). It was consequently determined to remove this power in group (family, at least) decisions based upon the informa- item and form a new “Youth-centric” factor, consisting of CDs, tion-acquisition strategies of the decision protagonists is of interest computer games, sports products and computer hardware/software. and importance in itself.

Testing the hypothesis; Change in Influence Implications for marketing practice Three separate ANOVA models are run to test for differences As the main research reported here is fundamentally of a in power-structure of sons between the two groups. There is no theory-development rather than empirical nature, the sample de- significant difference for either the Parent dominant or the Syncratic sign focused on control rather than representation and thereby factors, but the mean difference for the Youth-centric factor be- sacrificed much empirical relevance. The fact that the research tween the high-Internet group and low is significant (M(High design used worked so well, though, holds real promise for any χ2 usage)=57, M(Low usage)=48; p<.001, F=13.66). Hay’s reveals company marketing products or services which might be purchased an effect size of .07 for the Youth-centric factor; Cohen describes in a situation where group influence comes into play. It is not this as “medium-sized”. complicated research to replicate for a particular product/service situation and inspection of the results of a similar survey with an Decision stages appropriate sample and decision-objects would reveal very valu- The decision influence data were collected over three stages; able strategic information about not only the influence structures at Initiation, Negotiation and Final decision. The effect of Internet- play but also the effect of providing information to particular role- enabled knowledge is significant at each stage (Initiation(High)=68, players. Initiation(Low)=59, F=12.3, p=.001; Negotiation(High)=59, Asia Pacific Advances in Consumer Research (Volume 6) / 73 Implications for marketing theory Information acquisition does lead to power-enhancement in group decisions. Although this important fact has hitherto simply been assumed, it seems as if it is a reality. Moreover, the relationship does not always hold, as was evidenced above by the failure of sons’ knowledge enhancement to affect their decision power for products in which his parents were equally, or more, powerful and interested. This effect requires yet more rigorous research–possibly using more sophisticated modeling techniques–to fully unravel precisely what variables do intervene between knowledge and power and moderate the knowledge-power relationship. Another aspect of interest is the emergence of Internet as a knowledge-enhancement vehicle. The interest stems from the dif- ficulties surrounding assessment of individual’s exposure to Internet. Thus it seems as if further research could also be fruitfully conducted to ascertain the relative importance of this new vehicle vis- à-vis other, more conventional media.

REFERENCES Allen, Thomas J. (1984). Managing the Flow of Technology. Cambridge: MIT Press. Carter, Charles and Harry Scarbrough (2001). Regimes of knowledge, stories of power: A treatise on knowledge management. Creativity and Innovation Management, 10 (3), 34-45. Childers, T. (1986). Assessment of the psychometric properties of an opinion leadership scale. Journal of marketing research, 23 (May). Foxman, Ellen R., Patriya S. Tansuhaj, and Karin M. Ekstrom (1989). Family members’ perception of adolescents’ influence in family decision making. Journal of Consumer Research, 15 (March), 482-91. Gorsuch, Richard L. (1983). Factor Analysis. Hillsdale, NJ: Erlbaum. Grimshaw, Davis J. (2001). Harnessing the power of geographic knowledge; The potential for data integration in an SME. International Journal of Information Management, 21 (3), 14-27. Hair, Joseph F., Rolph E. Anderson and Ronald L. Tatham (1995). Multivariate data analysis: with readings (4th ed.). Englewood Cliffs.NJ: Prentice Hall. Hislop, David, Simon Newell, Harry Scarbrough, and John Swan (2000). Networks, Knowledge and Power: Decision making, politics and the process of innovation. Technology Analysis & Strategic Management, 3 (12), 21-29. Lee, Christina Kwai Choi and Sharon E. Beatty (2002). Family structure and Influence in family decision making. Journal of Consumer Marketing, 19 (1), 24-41. Lee, Christina Kwai Choi and Roger Marshall (1998). Measur- ing influence in the family decision making process using an observational approach. Qualitative Market Research, 1 (2), 88-98. Mangleburg, Tamara (1990). Childrens’ influence in purchasing decisions: A review and critique. Advances in Consumer Research, 17, 813-25. Na, WoonBong, Roger Marshall, and Youngseok Son (2003). Purchase role structure in Korean families: Revisited. Psychology & Marketing, 20 (1), 47-57. Teresko, John (1996). Data warehouses; build them for decision- making power. in Industry Week. Weingart, Laurie R., Elaine B. Hyder, and Michael J. Prietula (1996). Knowledge matters: The effect of tactical descriptions on negotiation behavior and outcome. Journal of Personality and Social Psychology, 70 (6), 1205-17. Form vs. Function: Emotional and Behavioral Consequences of Hedonic vs. Functional Tradeoffs Ravi Chitturi, Lehigh University, U.S.A. Raj Raghunathan, University of Texas at Austin, U.S.A. Vijay Mahajan, University of Texas at Austin, U.S.A.

EXTENDED ABSTRACT expected that, 1) trading functionality for hedonics will generate Most important decisions, including consumption decisions, feelings of guilt, 2) trading hedonics for functionality will generate involve making trade-offs. In the process of making difficult trade- feelings of sadness (Higgins 1997). offs, consumers experience significant negative affect (e.g., Luce In this research, we report findings from three experiments 1998; Luce, Payne and Bettman 1999). For example, decisions that were conducted to test for emotional and behavioral conse- involving a trade-off between safety of a car (high vs. low) and its quences of making such trade-offs. In the first experiment, the price (low vs. high) may induce negative emotions that, in turn, consumers were asked to consider choosing between a hedonically influence subsequent behavior (Luce, Payne and Bettman 2001). In superior (functionally inferior) cell-phone and a functionally supe- general, decisions involving difficult trade-offs have been found to rior (hedonically inferior) one. They were asked to report the level induce decision avoidance—the tendency to postpone purchase— of guilt and sadness with the choice of each cell-phone in the choice presumably because consumers feel uneasy about taking a decision set. The results from the first experiment show: 1) consumers feel without first having resolved the negative emotions evoked by that significantly higher level of guilt with the choice of a hedonically decision-situation (Luce 1998; see Luce, Bettman and Payne 2001, superior and functionally inferior product, 2) they report greater for a review). sadness with the choice of a hedonically inferior and functionally Previous research (e.g., Luce, Bettman and Payne 2001) has superior alternative. In the second experiment, the moderating found that, in decisions involving price-quality trade-offs, people influence of functional needs (cut-offs) on the intensities of guilt tend to choose the option higher in quality. To formulate a more and sadness was tested. The same choice set was used, but the general theory, however, it is important to incorporate dimensions subjects were treated to two different conditions. In the first other than price or quality, since consumers often face decisions condition the subjects were told that they need high level of involving a trade-off between two equally priced alternatives of hedonics and functionality in their cell-phone. In the second condi- equal overall quality (e.g., a Dell vs. Compaq) that differ on other tion, the subjects were told that they need low level of hedonics and attributes. This research looks at the emotional and behavioral functionality. The results from the second experiment show: 1) consequences of tradeoffs involving hedonic and functional at- intensity of guilt is lower with a hedonically superior product when tributes. Choosing between products that are a combination of it meets functional cut-offs compared to when it does not meet hedonic and functional attributes requires a tradeoff between two functional cut-off, 2) intensity of sadness is higher with the choice types of goals. One set of goals that are fulfilled by hedonic of a functionally superior product, when the hedonically superior attributes and the other set of goals that are fulfilled by functional alternative in the choice set meets functional cutoffs compared to attributes. Based on regulatory focus theory (Higgins 1997), it is when it does not. In the third experiment, we wanted to show that suggested that hedonic attributes help meet promotion focus goals relative intensities of guilt and sadness with each product choice in of “aspirations and advancement” and functional attributes help the choice set can explain consumer choice behavior. In this meet prevention focus goals of “security and responsibility”. When experiment, the subjects were asked to report the level of guilt and the goals of security and responsibility are compromised, it leads to sadness with each product choice and were also asked to choose one a discrepancy between “ought to behave” vs. “actual behavior”. of the two products from the choice set. The results show: 1) choice This discrepancy generates feelings of guilt (Roseman 1991; Higgins of a functionally superior alternative is mediated by the higher 1989). On the other hand, when the goals of aspirations and intensity of guilt compared to sadness with the hedonically superior advancement are compromised, it leads to a discrepancy between alternative, 2) choice of a hedonically superior alternative is medi- “ideal state vs. actual state”. This discrepancy generates feelings of ated by the higher intensity of sadness compared to guilt with the sadness (Roseman 1991; Higgins 1989). choice of a functionally superior alternative. Together, these results Marketing literature provides conceptual support for the idea suggest that designers and marketers must monitor the intensities of that the utilitarian and hedonic dimensions capture important as- emotions and design products with an optimal combination of pects of product differences (e.g., Batra and Ahtola 1990; Dhar and hedonic and functional attributes that minimize guilt and sadness Wertenbroch 2000; Holbrook and Hirschmann 1982). However, with a product choice compared to the alternative. little research pertains directly to the emotional and behavioral Overall, our results suggest that manufacturers should focus impact of making decisions involving trade-offs between utilitarian on satisfying functional “cut-offs” first, and that, once this goal is vs. hedonic attributes. The focus of this research is on the emotions met, focus should shift to maximizing the hedonic appeal of their induced by decisions involving trade-offs between utilitarian vs. offerings. This recommendation, however, may be easier said than hedonic attributes—which refer to the functional (utilitarian) and done, given that consumers’ perceptions of what they think is an aesthetic (hedonic) aspects of products, respectively—and the acceptable (cut-off) level of functionality is likely to evolve. In effect of these emotions on purchase behavior. For example, it is general, it is reasonable to assume that consumers will expect and unclear, from previous research, whether and to what extent nega- “need” higher and higher levels of overall quality—including tive emotions are induced in decisions involving a choice between, functional performance—with the passage of time. A recom- say, a highly functional computer that does not look good and one mended strategy would, therefore, be to make a conservative that is low on functionality, but is aesthetically pleasing. Based on prediction of the level of functionality consumers will find accept- a suggested correspondence between functional attributes and able in the future and ensure that this level of functionality is prevention focus, and hedonic attributes and promotion focus, it is provided. Thereafter, attention should be directed to enhancing the

REFERENCES Batra, Rajeev, O. T. Ahtola (1990), “Measuring the Hedonic and Utilitarian Sources of Consumer Attitudes.” Marketing Letters, 2(2), 159-170. Dhar, Ravi and Klaus Wertenbroch (2000), “Consumer Choice Between Hedonic and Utilitarian Goods,” Journal of Marketing Research, 37 (1), 60–71. Higgins, E. Tory (1989), “Self-discrepancy Theory: What Patterns of Self-beliefs Cause People to Suffer?,” in Leonard Berkowitz (Ed.), Advances in Experimental Social Psychol- ogy, Vol. 22, pp. 93–1 136, New York: Academic Press. Higgins, E. Tory (1998), “Promotion and Prevention: Regulatory Focus as a Motivational Principle,” in Mark. P. Zanna (Ed.), Advances in Experimental Social Psychology, Vol. 30, pp. 1– 46, New York: Academic Press. Holbrook, Morris B., and Elizabeth C. Hirschman (1982), “The Experiential Aspects of Consumption: Consumer Fantasies, Feelings, and Fun,” Journal of Consumer Research, Vol. 9(2), 130-142. Luce, Mary Frances (1998), “Choosing to Avoid: Coping with Negatively Emotion-laden Consumer Decisions,” Journal of Consumer Research, 24(4), 409-433. Luce, Mary Frances, James R. Bettman, and John W. Payne (2001), “Emotional Decisions,” in Deborah Roedder John (Ed.), Monographs of the Journal of Consumer Research, Vol. 1, University of Chicago Press. Luce, Mary Frances, John W. Payne, and James R. Bettman (1999), “Emotional Trade-off Difficulty and Choice,” Journal of Marketing Research, 36(2), 143-159. Roseman, Ira J. (1991), “Appraisal Determinants of Discrete Emotions,” Cognition and Emotion, 5(3), 161-200. Consumer Confusion of Percent Differences: When Less is More and More is Less Patrick Vargas, University of Illinois at Urbana-Champaign, U.S.A. Justin Kruger, University of Illinois at Urbana-Champaign, U.S.A.

ABSTRACT If A is 33 percent less than B, then B is 50 percent more than A. What is the effect of this counterintuitive mathematical tautol- ogy on consumers evaluating price and value? In four experiments, perceived price differences were greater when the cheaper of two products was the referent of the comparison (e.g., B is 50% more than A) than when it was the target of the comparison (e.g., A is 33% less than B). Products that were the same price were perceived as a different price, and products that differed in price (by as much as several hundred dollars) were perceived as the same price.

76 Asia Pacific Advances in Consumer Research Volume 6, © 2005 The Effect of Consumer Literacy on Product Choice Haeran Jae, University of Kentucky, U.S.A. Devon DelVecchio, University of Kentucky, U.S.A.

EXTENDED ABSTRACT Forty-four million people in the United States cannot read a newspaper or fill out a job application and another fifty million more cannot read or comprehend above the eighth grade level (Kirsch et al, 1993). Illiteracy is rampant in many emerging markets. For instance, the adult illiteracy rate in India and China is 44% and 17% respectively. Even wealthier nations with high purchasing power, such as in Saudi Arabia and United Arab Emirates, suffer 25% illiteracy rates (World Bank, 2001). Yet, consumer research assumes implicitly that consumers possess sufficient levels of literacy to comprehend available information. With the increase in literacy, research on the topic within marketing has declined to an almost non-existent level (Wallendorf, 2001). Thus, marketing researchers have apparently drawn their cue from the increasing rate of literacy rather than the continued large size of the low- literacy market segment. Even more alarming, literacy also appears to be assumed by marketing practitioners who do little to aid decision-making by low-literacy consumers. In the absence of aid from retailers and/or consumer product manufacturers, consumers with low literacy often engage in decision-making with poor results such as buying substandard products or paying price premiums (Wallendorf, 2001). Such outcomes suggest that low-literacy consumers systematically differ from high-literacy consumers in decision-making processes. Therefore, the dual goals of this paper are to a) apply existing theory to explain the choice process of low-literacy consumers and b) demonstrate how the presence of a decision aid at the point-of- purchase can improve choice by allowing low-literacy consumers to better use information. We explore the influence of literacy on consumers’ decision- making behavior in a choice environment by conducting a simple experiment in which the underlying cognitive process that drives product choice is compared across low- and high-literacy consumers. More specifically we employ the Elabo- ration Likelihood Model (Petty and Cacioppo, 1981, 1984) to predict the outcome of a shopping task and demonstrate that providing a visual decision aid can reduce differences in decision- making between low- and high-literacy consumers. Eighty subjects comprise of the sample for the experiment. Forty-one subjects with low literacy were recruited from local reading center. For the purpose of our study, low-literacy adults are those who possess literacy skills of Level 1 or Level 2 (see Adkins, 2001 for the same interpretation). All of the low-literacy subjects have been tested at a Level 1 or Level 2 literacy level by the reading center. Thirty-nine high-literacy subjects were recruited from the staff members of a large southeastern university. As series of four logit log-linear analyses was used to analyze the differences in the rate of choice of the peripheral cue brand by low- and high-literacy consumer groups across the two choice conditions (written decision aid/ visual decision aid). The findings of the current study support the main premise that, given adequate involvement, high-literacy consumers tend to choose a product based on central cues while low-literacy consumers tend to choose a product based on peripheral cues. The findings also indicate that presenting a visual aid improves the ability of low- literacy consumers to make normative decisions. From a policy standpoint, the findings speak to the need for simple visual product descriptions to enable low literacy consumers to make more informed decisions. 77 Asia Pacific Advances in Consumer Research Volume 6, © 2005 The Effect of Compatibility between Benefit and Payment Patterns in Evaluating Financing Decisions: A Test of the Alignment Hypothesis Seigyoung Auh, Brock University, Canada Chuan-Fong Shih, Wake Forest University, U.S.A.

EXTENDED ABSTRACT REFERENCES As consumers increasingly use debt and installment payments Hirst, D. Eric, Edward J. Joyce, and Michael S. Schadewald to finance durable goods, understanding of how financing decisions (1994), “Mental Accounting and Outcome Contiguity in are made can allow marketers to better design financing schemes Consumer-Borrowing Decisions,” Organizational Behavior that will stimulate purchases. and Human Decision Processes, 58, 136-152. In a typical financing scenario, the consumer makes payments Prelec, Drazan and George Loewenstein (1998), “The Red and for an agreed upon time period and in exchange uses the product and the Black: Mental Accounting of Savings and Debt,” reaps the benefits that are derived from consumption. Research has Marketing Science, 17 (1), 4-28. shown that consumers prefer to match the cost stream associated with the financing payments with the benefit streams that accrue from using the product (Hirst, Joyce, and Schadewald 1994; Prelec and Loewenstein 1998). When unbalance between the two types of stream occur, people are less likely to choose financing as a method of payment. This has been one of the primary reasons for people’s hesitance for financing services such as vacations since the benefits terminate once the trip is over but the payments used for financing the trip continue (Hirst, Joyce, and Schadewald 1994). First, we attempt to capture how consumers prefer to match the length of benefit streams with the length of cost streams (experiment 1). We specifically address this in the context of a widely used and accepted promotion, payment deferrals. Second, whereas prior research has found a linear pattern for mental depreciation of durable goods, we contest this and suggest a non-linear mental depreciation pattern for high-tech products (experiment 2). Third, past research has been solely focused on the temporal contiguity of costs and benefits thereby suggesting that as long as the benefit stream coincides and overlaps with the cost stream, consumers will be favorable towards financing (Hirst, Joyce, and Schadewald 1994). We build and extend this argument by asserting that it is not only the length of cost and benefit streams that are relevant but also the pattern of costs and benefits that is of utmost importance in determining consumer’s preference for financing (experiment 3). Thus, we tested the presence and validity of the matching between the benefit and payment streams, the alignment hypothesis, in a series of three experiments. In three experiments, we confirmed the presence of the alignment hypothesis in consumer financing decisions. Experiment 1 confirmed consumer’s preference for temporal contiguity between the benefits accrued from using products with the payments resulting from using a financing scheme. In experiment 2, we examine the alignment hypothesis by testing for the possibility of non-linearity in the benefits that accrue from using high-tech products or more generally, products that become obsolete quickly over time. Our study found that durable products may have a different rate of mental depreciation. Products with a high newness premium such as computers have a kinked mental depreciation curve such that there is greater depreciation early in the product’s life than in the later parts. Products which provide stable benefits in its life cycle instead exhibit a linear depreciation curve. Finally, in experiment 3, we build on this non-linear benefit pattern to explicitly test our alignment hypothesis and find that consumers prefer to align their payment stream to their product’s mental depreciation pattern.

78 Asia Pacific Advances in Consumer Research Volume 6, © 2005 Brand Switching in Clothing as a Manifestation of Variety-Seeking Behavior Nina Michaelidou, Nottingham Business School, UK Sally Dibb, Warwick Business School, UK David Arnott, Warwick Business School, UK

ABSTRACT which are not related to the desire for variety (e.g., multiple needs, The paper examines the relationship between consumers’ multiple users or multiple situations). Direct variation, on the other general need for variety in their lives and their brand switching hand, is the result of ‘intra-personal’ motives such as the need for behavior when shopping for clothes. A review of the various stimulation or because of satiation with a product’s attributes. motivations of variety-seeking behavior is offered. However, the Based on McAlister and Pessemier (1982), Kahn (1995) research described in the paper focuses solely on the consumers’ developed an integrating framework exploring why consumers internal need for stimulation (optimal stimulation level) as an seek variety. This framework classified VSB into three categories: antecedent of variety-seeking behavior and brand switching. This ‘satiation/stimulation’, ‘external situation’ and ‘future preference relationship is tested in the context of consumer shopping for uncertainty’. The first two categories correspond with McAlister clothes, measuring variety seeking levels and investigating their and Pessemier’s explanation. The third is based on the notion that effect on brand switching behavior. The findings indicate no variety-seeking is observed when consumers make purchases for relationship between VSB and brand switching; suggesting that future consumption. These categorizations (Kahn 1995) are now brand switching in clothing purchases is likely to be driven by used for classifying the motivations for VSB proposed in the factors other than ‘the need for variety’. literature. The discussion, which is divided into two parts, is based on two different schools of thought for conceptualizing VSB: The underlying premise of variety-seeking behavior (VSB) is inexplicable (or stochastic) and explicable (or deterministic). that ‘under certain conditions we all need variety in our lives’ (Faison 1977). This conflicts with classical theories of learned Inexplicable or Stochastic Conceptualizations behavior which describe consumer behavior as a series of needs According to the theory of stochastic preference, VSB is which are met by activities which then become learned responses to viewed as inexplicable and is attributed to ‘a stochastic element in be repeated as the needs recur. However, research suggests that the brain’ (Bass 1974). Various models were developed during the variety-seeking is likely to account for brand switching in consumer 1960s and 1970s to describe the statistical properties of buying choice (Bass, Pessemier, and Lehman 1972). Twenty years ago behavior (e.g., Bass et al. 1974). Such models do not incorporate researchers were preoccupied with understanding VSB, resulting in explanatory factors (e.g., product attributes, marketing mix vari- a proliferation of explanations and models for the phenomenon, its ables etc.). Rather, they propose a probability model based on the antecedents and manifestations. In a recent resurgence in interest, economic theory of utility, emphasizing that future preference is researchers have been keen to synthesize the literature and further affected by past experience. Despite their limited application, these explore the VSB concept (Kahn 1995; Ratner, Kahn, and Kahneman models inspired the evolution of a second generation of models 1999). incorporating variables to explain the probabilities. Thus first Although previous research indicates a relationship between generation models predict VSB using probabilities and assump- the need for variety and brand switching behavior, these studies tions of ‘static’ market conditions (e.g., Bass et al. 1974). Later tend not to consider how product category affects the relationship. models, however, incorporate various consumer and market vari- Yet brand switching is a situation and product-specific phenom- ables such as the effect of promotions (Kahn and Louie 1990; Kahn enon; therefore its underlying motivations vary across situations and Raju 1991) and the degree of similarity between two or more and different product groups. What causes brand switching in one brands (Feinberg et al.1994). Little by little this has caused the product class may not be the same as in another. More research is stochastic and deterministic traditions to converge (Kahn, Kalwani, therefore needed to determine the impact of product class on brand and Morrison 1986). switching behavior. This paper addresses this concern, examining the relationship between consumers’ need for variety in their lives Explicable or Deterministic Conceptualizations and their brand switching behavior when shopping for clothes. The Despite the view that choice behavior might include stochastic literature review considers various motivations for VSB, focusing or random components, most consumer behavior research assumes on the consumers’ internal need for stimulation (Optimal Stimula- that behavior is caused, and therefore is ‘explicable’. These deter- tion Level) as an antecedent of VSB and brand switching. Research ministic paradigms for explaining VSB can be categorized accord- findings are then presented which address the relationship between ing to whether they are based on psychological or other explana- VSB and brand switching for clothing consumers. tions. Psychological Explanations. Psychologists recognize variety MOTIVES OR ANTECEDENTS OF VARIETY- as a basic human need under the general rubric of exploratory SEEKING BEHAVIOR behavior. Exploratory behavior refers to behavior that ‘results from The concept of variety-seeking behavior (VSB) originated in motives that do not seem to conform to general expectations’ (Raju psychology and was introduced in 1955 separately by Leuba and 1981). A number of theories have explored what motivates explor- Hebb. Since then, psychologists, marketers and economists have atory behavior. Although there is considerable disagreement, an examined the antecedents of VSB and considered its implications area of common ground is that individuals prefer an ‘intermediate for individual and household choice behaviors. However, inconsis- level’ of environmental stimulation. The dominant explanation of tencies in the evolving literature arose because the term ‘variety’ VSB is based on the notion of ‘optimal stimulation level’ (OSL) was defined inconsistently. McAlister and Pessemier (1982) added [Hebb 1955; Leuba 1955]. This maintains that individuals have a order to the literature by categorizing ‘varied behavior’ as either preferred or optimal level of environmental stimulation. When the derived or direct. Derived variation results from external motives actual level of environmental stimulation is above or below the 79 Asia Pacific Advances in Consumer Research Volume 6, © 2005 80 / Brand Switching in Clothing as a Manifestation of Variety-Seeking Behavior optimal, individuals will try to adjust it through exploration (e.g., In a few instances, brand switching has also been modeled as a VSB) or avoidance behavior (e.g., inertia) (Raju 1980, 1981). function of marketing variables (see Carpenter and Lehman 1985). Alternative psychological explanations of VSB include: ‘arousal Such models predict brand switching using the effects of past potential’, ‘variation, ambiguity and intensity of the environmental purchases, price and promotional activities to investigate changes stimuli’, the ‘incongruity concept’ and the ‘general incongruity in the market shares of brands over a period of time (Ansari, Bawa, adaptation level’ (Berlyne 1960; Fiske and Maddi 1961). Although and Ghosh 1995). Some authors have also combined the effects of these theories differ in their interpretation of the relationship variables, including variety-seeking, inertia, marketing variables, between environmental stimulation and individual preference, they and customer characteristics (e.g., demographics), within the same basically agree that OSL is a cause of exploratory behavior (e.g., model (Ansari et al. 1995). VSB). They also agree that OSL varies among individuals and that Brand switching is viewed here as resulting from the internal it can determine the degree of individual exploratory tendencies need for variety which is explained by optimal stimulation level. across many situations (Raju 1980). The objective is to examine the relationship between OSL (which Other Explanations. Other explanations of VSB relate to the determines individual variety-seeking levels) and brand switching. internal and external factors which influence VSB and which lead Although this relationship has previously been addressed by Raju to various behaviors such as brand switching, innovating and (1980), a re-examination exploring the manifestations of VSB in information seeking. specific product classes is needed. The focus of the research is Explanations involving internal factors include the notion of therefore on the product category, with measures being developed satiation with product attributes and future uncertainty (Jeuland at a product rather than a brand level. The product examined by the 1978; McAlister 1982). Satiation arises when familiarity with a research is clothing. Given the ‘product-oriented’ focus, brand stimulus causes decline in the stimulation potential because it is no switching is considered to be the consumer disposition to exhibit longer novel to the consumer (Berlyne 1960). Future uncertainty switching patterns in clothing. explanations focus on the idea that variety-seeking is sought not because of the utility for diversity per se, but because of uncertainty THE MEASURES about future preferences (Kahn 1995). This may be particularly The notion of optimal stimulation level (OSL) was used as the pertinent to consumers faced with making multiple purchases for basis for measuring consumers’ need for variety in their lives. As future consumption who may use VSB as a risk-reduction strategy. already mentioned, individuals possess a variable need for stimula- Various external factors, including changes in usage situation which indicates their propensity to look for variety (Hoyer and tions, price promotions and the retail environment, have been Ridgway 1984). OSL has been found to determine the extent of shown to motivate VSB in some contexts. For example, research individual variety-seeking (or novelty-seeking) tendencies in a indicates that price promotions have a positive effect on VSB (Kahn consumer context (Raju 1980, 1983). In particular, Raju (1980) and Raju 1991). In an experiment into brand choice and price found a positive relationship between OSL and various behaviors promotions Kahn and Louie (1990) found that respondents sought such as brand switching, information seeking and the adoption of variety when promotional activity was involved and were loyal to new products. their preferred brands when the price promotions were retracted. Measuring Optimal Stimulation Level MANIFESTATIONS OF VARIETY-SEEKING In measuring OSL, three scaling procedures which utilize BEHAVIOR statements and which derive from the psychology literature were Having reviewed the antecedents or motivations for VSB, it is considered (Garlington and Shimota 1964; Mehrabian and Russell important to consider its ‘symptoms’ or how it is manifested. Three 1974; Zuckerman 1964). Of these three, the ‘arousal seeking types of behavior have been cited as potential manifestations of tendency’ scale or AST (Mehrabian and Russell 1974) was pre- VSB (Price and Ridgway 1982). These include: ferred. This scale, which is the most recent and concise, is the easiest to administer (Raju, 1980). The scale has been extensively applied 1. Exploratory purchase behavior: Examples of such behav- in the consumer behavior literature and construct validity is indi- ior involve brand switching and innovating. Thus an cated (Raju 1980; Wahlers and Etzel 1990). To ensure the scale’s image-conscious twenty year-old may enjoy experiment- fitness in the context of the present research, some modifications ing with a variety of different cosmetics and hair-care have been made. These include some instances of word replace- products. ment, rephrasing and item reversing. In addition, for purposes of 2. Vicarious exploratory behavior: This type of behavior parsimony, some items were eliminated as overlapping. This meant does not involve product purchase although it may be an that 26 out of the original 40 items from the original instrument were outcome. Examples include reading about, talking to oth- retained. Another three items have been added which originate ers or window-shopping for new or unfamiliar products. from Raju’s (1980) ‘exploratory tendencies in consumer behavior Eg: a student seeking a new CD mini system may refer to scale’ to bring the scale closer to the context of shopping. specialist magazines or seek advice from friends. 3. Use innovativeness: Examples include using a previously Measuring Brand Switching adopted product in a novel manner or using a current Brand switching is operationalized in this research as the product in a wide variety of ways. Eg: someone buying a consumer propensity to exhibit switching patterns. Two variables food processor for mixing cakes might extend its’ use to served as surrogate measures of brand switching including 1) the pureeing fruit and vegetables for soups and sauces. degree of importance the individuals attach to the brand name and 2) the individuals’ commitment to their favorite brand of clothes. In this paper the focus is exclusively on brand switching as a manifestation of VSB. Most variety-seeking research uses prob- METHODOLOGY AND ANALYSIS ability theory and focuses on modeling brand switching as a The choice of clothing in this study is justified on the basis that phenomenon of VSB (caused by internal factors) [Feinberg, Kahn, clothing has been linked with various psychological concepts like and McAlister 1992; Jeuland 1978; Trivedi, Bass, and Rao 1994]. perceived risk and involvement (Hawes and Lumpkin 1986; Tiger, Asia Pacific Advances in Consumer Research (Volume 6) / 81 Ring, and King 1976). These concepts are said to affect VSB in Brand Switching Potential (BSP): A combination of two product choice (Hoyer and Ridgway 1984). In addition, as clothing measures was used to assess brand switching. Respondents were shoppers, the sample population was likely to be interested in this asked to indicate on bi-polar five-point scales 1) the importance product category and this would encourage participation in the they attach to brand name when shopping for clothes and 2) their survey. Another, but equally important consideration is that cloth- commitment to their favorite clothing brand. While this is not a ing as a product category has not previously been used to examine rigorous measure of brand switching, in this exploratory study the VSB levels. aim is simply to seek indicators of a link (or its absence) as opposed The decision about the most appropriate data collection method to developing a predictive, associative model. involved reviewing the relative merits of different approaches. The To investigate the relationship between optimal stimulation speed and cost advantages of the questionnaire over other data level and brand switching behavior in clothing an equation was collection methods were particularly attractive. Similarly, the use derived using regression analysis. The goal of this approach is to of e-mail as a method of administration ensures fast transmission establish a relationship which predicts the values of the dependent and convenient response handling (Dibb, Rushmer, and Stern variable of brand switching using the independent OSL factors. A 2001). An online questionnaire was directed to a random sample of number of statistics were used to examine linearity including 3000 individuals in the UK. The sample was derived from the descriptives, the R2 goodness of fit, the standard error of the customer database of NEXT Plc, one of the biggest and best known estimate, ANOVA, collinearity statistics and finally the t-statistic UK clothing manufacturers and retailers. The company agreed to (see tables 2, 3, 4). co-operate with the research. The statistics show no relationship between brand switching in Potential respondents received a URL address in the form of clothing and OSL. For example, the R2 equals .015 and the adjusted a hypertext link included in an e-mail message sent by the retailer. R2 is .007. Similarly Beta values (table 4) are significantly low and The e-mail invited the receivers to visit the web page to complete a linear relationship is therefore doubtful. The possibility that the the questionnaire. A three week cut-off point was set, but an data may not be suitable for a linear model has been examined, with overwhelming 41.3% of responses arrived on the day of transmis- the likelihood of a non-linear relationship between the two ad- sion. The response rate over the first week was steady so that by the dressed through data transformations. A number of equations end of this period 90% of the responses had been received. Overall, [addressing non-linearity] have been derived, indicating that a the response rate was 19%, generating 557 usable questionnaires. relationship between OSL and brand switching in clothing might be The ‘normal’ level of response rates to Internet questionnaires has ‘inherently impossible’. yet to be established. However, this return rate provided sufficient The possibility that the scale offers a superior interpretation cases for conducting multivariate data analysis and seemed to because it uses a summated OSL scale rather than the factors scores compare well with consumer response rates in general. has also been investigated. The five point Likert scale for OSL items To establish whether there were problems caused by non- meant that a simple summated score was deemed an appropriate response bias, a series of independent sample t-tests was initiated indicator of overall OSL. Possible scores ranged from 29 x one (i.e. for the 29 variables measuring OSL. These tests examined the 29) to 29 x five (i.e. 145), although the actual range recorded was responses for early and late respondents. No significant differences zero to110. Observations with incomplete OSL responses (<29) were identified between the two groups indicating that the sample were excluded from the analysis. A regression analysis of the brand originated from a single population and that non-response bias switching potential against the summated OSL scores revealed no should not be a problem. significant relationship with a near zero R-squared (R2=0.001, Optimal Stimulation Level: As the 29-item OSL measure p=0.594) (see table 5). Furthermore, an independent-samples t-test derived from a proposed uni-dimensional scale (Mehrabian and comparing the brand switching potential of the lowest and highest Russell 1974), tests of its robustness and possible direct relation- OSL quartiles showed no significant differences in the mean value ship with brand switching were conducted. Although in this paper of brand switching potential (table 6). Thus, there is little evidence the contention is that OSL is a multi-dimensional concept, the of a link between OSL and brand switching irrespective of whether robustness of the scale as uni-dimensional cannot be discounted a single scale or one broken into its various components is used. without further investigation. A Cronbach alpha reliability test This leads to the conclusion that, counter to other literature, if OSL indicted a value of 0.96 which, by any standards is exceptional affects brand switching at all it is at best a category specific variable. (Nunnally, 1968). Of course, Chronbach alpha is susceptible to Further research is needed to identify susceptible and non-suscep- positive distortion as the number of items increases, so this high tible categories. value may partly be caused by the number of scale items. Neverthe- Brand switching has been argued to be a manifestation of the less, it would appear that the scale is relatively robust as originally need for variety explained by optimal stimulation level (Hoyer and proposed. Later in this section the possibility that the scale as a uni- Rigway 1984; Raju 1980). In this respect, individuals with a dimensional measure may offer a superior interpretation to the relatively high need for variety in their lives are expected to show multi-dimensional view of OSL proposed here is considered fur- brand switching propensities in their choice behavior (Raju 1980, ther. The dimensionality of OSL was explored by submitting the 1981). However, the results indicate that brand switching in clothes scale items to factor analysis with varimax rotation. The final factor is not related to consumers’ need for variety. This implies that while solution indicates four distinct factors explaining 59% of the consumers need variety in their lives, they do not satisfy this need variance. The reliability analysis yielded alpha values of .73, .62, through brand switching in their clothing choice. In other words, the .56, .51. brand switching observed may be the result of other factors than the The four factors shown in table 1 correspond to the four need for variety. sources of stimulation reflected in the factor labels. These are 1) As pointed out earlier, there are various possible internal and new and unfamiliar stimuli, 2) change stimuli, 3) risk stimuli and 4) external factors that explain brand switching. In this study of activity stimuli. This interpretation of the factor solution is consis- clothing purchases, the OSL factor was explored, and found not to tent with the original scale (Mehrabian and Russell 1974). These explain the brand switching observed. It is therefore important to results suggest that OSL is a multidimensional construct with fairly revisit the other factors which might explain brand switching in reliable dimensions. clothing purchases. 82 / Brand Switching in Clothing as a Manifestation of Variety-Seeking Behavior TABLE 1 Rotated Component Matrix of OSL

Items Factors 1234

Factor 1: New and Unfamiliar Stimuli When things get boring I look for new and unfamiliar experiences .764 I actively seek new ideas and experiences .688 I like novelty and change in my daily routine .647 I like people who give me new ideas .654 I like to go somewhere different nearly every day .533 As a child, I often imagine exploring the world .533

Factor 2: Change Stimuli I prefer friends who are reliable and predictable .852 I am happiest when I feel safe and secure .780

Factor 3: Risk Stimuli I sometimes like to do things that are a little frightening .769 I would not enjoy risky sports such as mountain climbing or sky diving .768

Factor 4: Activity Stimuli I avoid busy, noisy places .820 I do not like to have lots of activity around me .747

TABLE 2 Summary of Brand Switching-OSL Model

Model R R Square Adjusted R Std. Error of Square the Estimate

1 .121 .015 .007 .6165

TABLE 3 Analysis of Variance of Brand Switching-OSL Model

Model R Sum of Squares df Mean Square F Sig.

1 Regression 2.936 4 .734 1.931 .104 Residual 198.401 522 .380 Total 201.336 526

First, satiation with the brand or its attributes is considered as become bored with the quality or fit of a given brand but because the a major drive for VSB. Consumers become satiated by the con- combination of permanent characteristics is perceived as unsatis- sumption of a particular brand and look for alternatives. In the case factory. Under such circumstances the consumer is likely to switch of clothing [and in contrast to some other products] clothing brands to other brands of clothes. Of course, it is also important to are characterized by a set of attributes which are subject to change recognize that this brand switching will probably be achieved due to fashion trends. However there are also certain attributes that within the context of the portfolio of clothing brands preferred by become permanent features and which are retained by the manufac- the consumer. In other words, most consumers will not confine their turer to shape the image of the brand. Such attributes are likely to clothing purchase to a single brand. be quality, fit, style, and perhaps fashionability. The manufacturer A second internal factor is future uncertainty. This factor may and retailer hope that a satisfactory combination of these attributes explain brand switching in product categories other than clothing. will encourage the consumer to remain loyal to the brand. Satiation VSB and brand switching as a result of future uncertainty is most with the brand is likely to occur not because the consumer has often observed in purchase of food products, where consumers Asia Pacific Advances in Consumer Research (Volume 6) / 83 TABLE 4 Coefficients Table of Brand Switching-OSL Model

Model Unstandardized Standardized Collinearity Coefficients Coefficients Statistics

1 B Std. Beta t Sig. Tolerance VIF Error

(Constant) 1.834 .160 11.481 .000 New and 1.678E-02 .043 .018 .393 .695 .872 1.147 Unfamiliar stimuli Change Stimuli 4.512E-02 .035 .059 1.301 .194 .904 1.106 Risk Stimuli -5.99E-02 .026 -.109 -2.315 .021 .855 1.169 Activity Stimuli -2.88E-02 .031 -.043 -.941 .341 .889 1.125

TABLE 5 Regression of Summated OSL Score vs. Brand Switching Potential

R R Square Adjusted R Square Std. Error Beta t Sig.

.029 .001 -.002 4.5606 0.29 0.534 0.594

TABLE 6 Independent Samples T-Test for Equality of Means: Brand Switching Potential (BSP)

Group BSP Mean t df Sig. (2-tailed)

OSL Quartile 1 10.38 1.231 159 .220 OSL Quartile 4 9.50

switch brands as a way of reducing the risk of future taste changes. between brand switching and OSL: “..the results suggest that In the case of clothing, consumers do not employ brand switching people who have higher OSL’s are generally more likely to manifest as a risk reduction strategy but try to handle the risk through other exploratory behaviors in the consumer behavior context. The methods like loyalty and information search. exploratory tendencies are more likely to be manifested as risk Certain external factors might also explain brand switching in taking and innovativeness somewhat likely to be manifested as clothing purchases. However in this study the focus was on the brand switching” (p279). internal motivations of VSB and brand switching. External factors Raju’s (1980) findings confirm a relationship between brand such as discounts and price promotions have been found to encour- switching and optimal stimulation level in general, but do not age brand switching behavior for a short period of time. Research consider the effect of product type. Where this relationship is indicates that the effect of promotions declines once these are examined in a specific product class, product type is expected to retracted (Kahn and Louie 1990). The effect of promotions has only explain variations in switching behavior. This is because brand been investigated in certain product categories such as groceries. It switching is a product-specific phenomenon and therefore its is therefore unknown in the literature whether external factors have motivations presumably vary by product class. an effect on VSB and brand switching in clothing. The paper has explained the many motivations for VSB, Finally, it is important to acknowledge that an alternative including internal (OSL, satiation, future uncertainty) and external explanation for the null effect of OSL on brand switching behavior (price promotions, discounts, out-of-stock conditions etc.) How- in clothing may relate to limitations in brand switching measures. ever, these explanations do not consider the role of the product class The surrogate measures used to capture brand switching may have in determining the occurrence of brand switching. Since brand been insufficiently sensitive to detect any effect of OSL on brand switching is product-specific, these explanations are therefore switching behavior. arguably limited in scope. As a result, there is a lack of differentiation in the motivations of brand switching across product catego- CONCLUSIONS ries. The research reviewed in this paper seems to suggest that, Previous research suggests a relationship between the need for contrary to non-product specific research findings on VSB, clothes variety (explained by OSL) and brand switching behavior (Raju shoppers’ general need for variety in their lives does not appear to 1980). As Raju explains, his research found a significant correlation affect their brand choice. Of course, this does not mean that the 84 / Brand Switching in Clothing as a Manifestation of Variety-Seeking Behavior purchase behavior of these individuals in other product classes Kahn, Barbara E. (1995), “Consumer Variety Seeking Among follows the same pattern. Indeed, these findings highlight the need Goods and Services”, Journal of Retailing and Consumer for further research. In particular, additional research is required to Services, 2 (3), 139-148. examine the conditions when brand switching is a manifestation of Kahn Barbara E. and Donald R. Lehmann (1991), “Modeling internal sources of VSB behavior. This could involve using a Choice Assortments”, Journal of Retailing, 67, (Fall), 274- framework which can predict when OSL or other internal sources 299. are related to or explain brand switching behavior. Both the present Kahn, Barbara E. and Theresa A. Louie (1990), “Effects of study and the earlier research findings of Raju could be regarded as Retraction of Price Promotions on Brand Choice Behavior preliminary steps in this research direction. for Variety-Seeking and Last-Purchase-Loyal Consumers”, Journal of Marketing Research, 27 (August), 279-289. REFERENCES Kahn Barbara E. and Jagmohan S. 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EXTENDED ABSTRACT ended questions asked respondents to list their favorite brand in the This study reviews the literature on the evaluation of brand extension category and the reasons for their liking or disliking the extensions, and reports the findings of an experiment that explores proposed brand extension. whether or not existing competing brands affect the evaluation of Paired t-tests were conducted on the evaluation of brand brand extensions, taking into account the perceived relevance or fit extensions before and after the competitive comparison was in- of the extension to the parent brand. Results indicate that competi- duced. In six out of eight cases, paired t-tests indicated that when the tion does indeed affect the evaluation of brand extensions but that extension is perceived to be of high relevance, cuing of the compe- the impact depends on the perceived congruency of the extension fit tition adversely affected the evaluation of the brand extension. with the parent brand. These results indicate that the evaluations of brand extensions are Brand extensions are often used to enter a well-established or affected by the competing brands, particularly when relevance of rapidly growing product category under the assumption that when the brand extension is high. It is important to note that relevance (fit) consumers’ attitude toward the parent brand is positive, this attitude of the brand extension with the parent brand in the brand extension is transferred to the extension. While the evaluation of brand evaluation process becomes unimportant once competing brands extensions has been widely researched, most efforts fail to recog- are introduced. This suggests that either the measures of fit used to nize the pre-existence of competing brands in the extension cat- assess the relevance of an extension to its parent brand were egory and do not account for their impact on the evaluation process. inadequate to capture the fit in the presence of competing brands or, Considering the expense of new product introductions, a manage- possibly, the notion of fit between a parent brand and its extension rially relevant and theoretically significant research effort would is not an indicator of an extension’s success in the target category. examine brand extensions in the presence of competing brands. The results of our study can be explained using the “attraction This study represents a first step towards the understanding of how effect” that posits that the introduction of a new brand in a category competing brands affect the evaluation of brand extensions. affects the attractiveness of the existing brands due to “data and The literature on the evaluation of brand extensions has cognitive deficiencies” (Pan and Lehman 1993; Malaviya and significantly contributed to the understanding of how brand exten- Sivakumar 2002). The findings of our study imply that brand sions are evaluated, but has focused on product and brand attributes, extension programs should take into account the effects of competi- ignoring the competition. In most product categories, especially tive comparisons while planning to introduce a brand extension. consumer goods categories, numerous brands compete and con- Future studies should examine the impact of target category struc- sumers do not make purchase decisions in a “competitive vacuum” ture, intensity of competition, and relative strengths of the parent (Han 1998) and their attitudes are affected by competitor activity brand and competing brand attitudes on the evaluation of brand (Czellar 2003). Research on extension evaluation has focused on extensions vis-à-vis existing brands. the fit between the parent brand and the extension. Relatively little is known about the role and influence of competing brands on brand REFERENCES extension evaluation. Han, J. K. (1998), “Brand Extensions in a Competitive Context: The authors argue that the evaluation of a brand extension will Effects of Competitive Targets and Product Attribute be adversely affected by existing competing brands even when the Typicality on Perceived Quality,” Academy of Marketing fit between the parent brand and its extension is high. To test this Science Review, http://www.amsreview.org/articles/han01- hypothesis, an experiment was conducted to explore the evaluation 1998.pdf of brand extensions when taking into account both perceived fit Czellar, S. (2003), “Consumer Attitude Toward Brand Exten- with the parent brand, and competing brands. sions: An Integrative Model and Research Propositions,” Five brands that possessed dominant brand associations were International Journal of Research in Marketing, 20, Vol. 20, selected, and a total of eight brand extensions were chosen for the pp. 97-115. experiment. Of the resulting eight extensions, four were associated Malaviya, P. and K. Sivakumar (2002), “The Influence of with complex products and four with routine product categories. Choice Justification and Stimulus Meaningfulness on the Two versions of questionnaires were developed, each with two Attraction Effect,” Journal of Marketing Theory and complex and two routine product categories, and randomly allo- Practice, (Fall), pp. 20-29. cated to one hundred and three participants who were undergradu- Pan, Yigang and Donald R. Lehman (1993), “The Influence of ate students enrolled in marketing courses at a Canadian university. New Brand Entry on Subjective Brand Judgments,” Journal Questions using a nine-point Likert scale captured respon- of Consumer Marketing, Vol. 20 (June), pp. 76-86. dents’ familiarity with the parent brand, relevance of the brand extension used as a measure of fit, and attitude toward the brand extension. Respondents were then asked to list existing major brands and their brand associations in the extension category in order to induce competitive comparison effects. Following this, two questions based on a nine-point Likert scale captured attitudes toward the brand extension in comparison to existing brands, and how well respondents felt the brand extension would fare in the target category compared to the existing brands. Finally, two open-

86 Asia Pacific Advances in Consumer Research Volume 6, © 2005 Retain the Meaning, the Sound, or Both? Effectiveness of Brand-Name Translations in a Chinese-English Bilingual Context Yih Hwai Lee, National University of Singapore, Singapore Cheng Qiu, National University of Singapore, Singapore

EXTENDED ABSTRACT among bilingual students from an Asian university. Hypotheses As linguistic labels, brand names should be subjected to about the main effects of language proficiency on consumers’ structural differences among language systems. Thus, the unique preference for brand-name translations are supported. Regarding linguistic characteristics which govern each language may poten- the interaction between situational prime and language proficiency, tially affect the effectiveness of brand-name translations. Along the results are mixed. As predicted, with subtle phonological this line, Zhang and Schmitt (2001) prescribed a framework to priming where participants were informed that the product’s target elucidate issues in English to Chinese brand-name translation, customers were proficient in English, those who were strong in highlighting the notion that brand naming should take linguistic English, regardless of their Chinese proficiency level, were found factors into consideration. Following this effort, our study investi- to evaluate phonetic-English translation most favorably; those who gates bilingual consumers’ evaluation of brand-name translations were weak in English but strong in Chinese were found to evaluate from logographic Chinese characters to alphabetic scripts. We Hanyu Pinyin translation most favorably. However, with obvious propose that the effectiveness of four possible methods of transla- phonological priming where participants were told that the prior tion—semantic-English translation, phonetic-English translation, translation method in the product category was phonetic-English, phonesemantic-English translation, and Hanyu Pinyin (a Romanized those who were weak in English but strong in Chinese rated phonetic system of Chinese) translation—may vary with bilingual phonetic-English translation most highly, which is inconsistent consumers’ chronic differences in language proficiency as well as with our hypothesis. As predicted, with subtle semantic priming the presence of situational primes. where participants were informed that the product’s target custom- We extend the bilingual perspective (Zhang and Schmitt 2001, ers were proficient in Chinese, those who were strong in both 2004) to include a complete and in-depth examination of language English and Chinese regarded semantic-English translation most proficiency effects. We hypothesize that consumers who are profi- highly; those who were weak in English but strong in Chinese cient in both English and Chinese tend to engage in both phonologi- preferred Hanyu Pinyin translation to other methods. Participants cal and semantic processing of words and hence prefer strong in English but weak in Chinese were found to evaluate phonosemantic-English brand-name translation to other translation semantic-English translation most favorably (directionally consis- methods. On the other hand, consumers who are proficient in tent but insignificant). In contrast, supporting our hypothesis, those English but weak in Chinese tend to engage in phonological who were strong in English but weak in Chinese rated semantic- processing and hence prefer phonetic-English translation to other English translation most highly with obvious semantic priming translation methods. In contrast, consumers who are weak in where they were told that the prior translation method in the product English but strong in Chinese tend to engage in semantic processing category was semantic-English. Inconsistent with our hypothesis, and regard Hanyu Pinyin translation most highly since Hanyu those who were strong in Chinese but weak in English preferred Pinyin translation not only provides immediate mapping to the semantic-English translation to other methods. The different pat- precise semantic meaning of the original brand name but also tern of findings we obtain using subtle and obvious prime implies involves orthographic rules that this group of bilinguals are familiar that the outcome of the interplay between innate and primed with. preference may depend on the relative preference-intensities. Furthermore, we suggest that bilingual consumers’ preference Our study offers insights on Chinese brand-name translation for brand-name translations may be affected by situational primes in a bilingual context by demonstrating the impact of the different which create contexts for the subsequent evaluation of brand mental representation of English and Chinese on brand-name names. We examine two factors in the marketplace that may serve translation preference, by revealing the interaction between as prior contexts for influencing consumer’s sensitivity towards situational priming and chronically preferred mental mode, by phonetic/semantic features of a translated brand name. The first is introducing and examining the phonetic/semantic features of Hanyu the prior translation methods used in the marketplace (adapted from Pinyin translations which are distinct from those of the three Zhang and Schmitt 2001) and the second is the target market of the English-based translations, and by uncovering the profound influence brand (whether the consumers are predominantly English- or of priming intensity on experimental conditions. Future research Chinese-speaking). We propose that an English “prior context” will may be conducted to further shed light on the processing mechanism prime phonological encoding whereas a Chinese “prior context” of Hanyu Pinyin and to explore the generalization of the current will prime visual encoding. The effects of these temporarily activated findings to the translation of other logographic systems (e.g., processing modes may be additive to or outweigh bilingual Korean Hancha, Japanese Kanji) into alphabetic scripts (e.g., consumers’ chronically nurtured inclinations, leading to another set English, Romanized Korean, Romanized Japanese). of hypotheses regarding the interplay between primed and innate preferences. REFERENCES A 3 (Bilingual Language Proficiency: strong in both lan- Aaker, Jennifer L. and Angela Y. 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ABSTRACT Successful brands could generate higher return on investment This study examines the effect of co-branding strategy on and quality, and service rather than advertising are the optimal consumers’ evaluation of the extension products. Co-branding is strategies to build brands (Doyle 1990). Therefore, manufacturers operated based on the brand strength, similarity/complementary of value the potential value and power of their brands while realizing parent brands. The results indicate that, for high involvement that every brand has its limitations (Boad 1999). Under this product, brand strength rather than similarity/complementary of circumstance, many successful brands re-concentrate on their core parent brands play a critical role in the evaluations of co-branding business and become conservative in brand stretching. Alternatively, products. The evaluations of co-branding product influence the alliances have become a preferred strategy by increasing number of brand equity. Discussions, contributions, and suggestions to future marketers compared to engaging in high risk and cost brand research and practitioners are addressed. extension, expansion or diversification (Boad 1999). Brand alliances refer to the collaboration between two existing As the market becomes increasingly competitive and more brands in order to produce a new product. The alliance parties could variety of products available to consumers, brands can facilitate be of either the same level (e.g., manufacturer to manufacturer) or consumers in decision process and enhance effectiveness (Doyle different levels (e.g., manufacturer and retailers) in the marketing 1990). Brand extension has been a widely applied strategy by channels (Park, Jun, and Shocker 1996) that cooperate with each marketers in introducing new products to reduce the risks and costs other on the 4Ps. Brand alliance is the optimal collaboration mode and leverage on brand equity. Seventy-eight percent of new products between two corporations since alliance makes the relationship introduced in 1998 were based on line extension however their highly visible and the reputation of the involved parties are affected success rate (28%) was lower than new products (47%) (Ernst and by the results of alliance (Park, Jun, and Shocker, 1996). When the Young 1998, cited from Simms 2000). Co-branding among characteristics between the alliance parties are inconsistent, marketers from either same or different distribution levels and consumers would be confused (Park, Jun, and Shocker 1996). across industries has become a viable strategy. Few researches have focused on co-branding. Thus, the primary purpose of this study is Brand Strength and Purchase Intentions of Co-branding to investigate the effects of parent brands’ brand equity on the Products evaluations of co-branding products. Strong brand can enhance brand familiarity and knowledge Affect and Purchase Intension thus generates association between brand and quality (Smith and Affect is an individual’s evaluation of a particular stimulus on Park 1992), which, in turn, reduce perceived risks and increase its meanings, causes, consequences, and personal implications purchase intention of the extension (Aaker and Keller 1990; Reddy, (Westbrook 1987, p. 259). Affect is a primal motive that could be Holak, and Bhat 1994). Park, Jun and Shocker (1996) claimed that viewed as a crucial determinant in product choices (Chaudhuri the strength of the header positively impact the evaluation of co- 1997). Although various definitions of affect could be found in branding products. However, the strength of parent brands both literature, researchers agree that it is a mental phenomenon influence the evaluation of co-branding product. characterized by continuous experiences with emotions and moods and subjective affect states (Westbrook 1987). Both positive and H1: The strength of the parent brands both positively impacts negative affect influence purchase intention. Different affects are the evaluations (i.e., affect and purchase intention) of co- produced by different causes. Consumer purchases are often branding product. emotionally (Curry-Swann 1998), substantial impacts on cognitive process and social behaviors occur even with mild changes in Similarity or Fit of Parent Brands. Brand similarity is viewed emotional states (Aaker, Stayman, and Hagerty 1986). In addition, as the shared salient attributes of abstract product concept or actual researches (Ajzen and Fishbein 1980; Miniard and Cohen 1979; product attributes between the core brand and the extension (Loken Warshaw 1980) point out that purchase intention is a more valid and Ward 1990). Although co-branding related literature tends to predictor to behavior compared with attitude that can substitute be reports on business cases and its effects, the success of co- behavior in developing models (Ryan and Bonfield 1980; Eroglu branding does rely on the brand equity of the parent brands. 1992). Accordingly, both affect and purchase intention are dependent Research has found the similarity or fit between parent brand and variables of this study. extension to have significant impact on the evaluation and purchase intention of its extension (Aaker and Keller 1990; Boush and Loken Brand, Alliance, and Consumer Attitudes 1991) since consumers presume that their knowledge on parent Consumers tend to rely on external (e.g., price and brand) brand can be transferred to the extension (Keller and Aaker 1992). rather than internal (e.g., quality) product information while making Brand equity exerts even higher value in organizational portfolio decision since external information is easier for them to obtain and than presents alone (Barwise and Robertson 1992). In other words, judge. Brand simplifies decision process by providing consumers the overall performance of an organization can enhance brand with a sense of safety and consistency (Barwise and Robertson value. When the characteristics of parent brands of the co-branding 1992). In most transactions, especially consumer products, brand is partners are inconsistent, consumers will be confused (Park, Jun, a crucial factor (Barwise and Robertson 1992). and Shocker 1996). Park, Jun, and Shocker (1996) studied composite brand in terms of complementary and concluded that parent brands compensate each other generate more positive evaluation on the 1The author thanks National Science Council, Taiwan for support- extension when compared to rely on the strong brand in introducing ing this research. extension.

89 Asia Pacific Advances in Consumer Research Volume 6, © 2005 90 / Do Co-Branding Products Increase Consumers’ Purchase Behaviors in Taiwan? H2a: The higher the similarity between the parent brands the The Development of Formal Questionnaire more positive the evaluations (i.e., affect and purchase The questionnaire includes an advertising of a coming to intention) of co-branding products. market cell phone PDA, manipulation checks, and items measuring H2b: Parent brands compensate each other will have a positive affect, function, and demographics. The content of the ads includes impact on the evaluation (i.e., affect and purchase the co-branding name, cell phone PDA photo, and product attributes. intension) of co-branding products. Seventeen advertising scenarios (2 cell phone parent brands x 4 notebook parent brands x order of co-branding, plus one control Brand serves as a signal of product quality (Rao, Qu, and groups) were developed. Manipulation check items asked Ruekert, 1999) that consumers utilize to evaluate new product respondents the main products produced by each of the parent (Cohen and Golden 1972). Brand with established equity could be brand. Affect is measured with a 17 semantic differential scale (Lai used in expanding new products. However, the failure of the and Liu 2001) modified from Watson, Clark, and Tellegen’s extension will undermine the image of high equity parent brand (1988). Product function is measured with 8 items. Consumer- (Keller and Aaker 1992). Attitudes toward brand alliance positively based brand equity scale (Lassar, Mittal, and Sharma 1995) was impact on the brand equity of parent brands (Simonin and Ruth used to measure brand equity of parent brand and co-brand. 1998). Accordingly, this study hypothesizes, RESULTS H3: The evaluations of co-branding product will have a Considering the characteristics and price of the research positive impact on the brand equity of parent brands. product, cell phone PDA, respondents were people with full-time job. Among the 647 questionnaires distributed, 508 are valid. The METHOD sample distributions are 59% male, 85% aged between 23 and 40, A 2 (order of the co-branding brands) x 2 (high versus low 38.9% has monthly income of $885~$1475, 22.7% in manufacture, brand strength) x 2 (fit and complimentary of parent brands) 18.8% are government employees, and 17.8% in service industry. factorial design was used to test the hypotheses. The similarity and Item-to-total analysis and factor analysis were used to extract compliment of parent brands were determined based on respondents’ factors. Single factor was extracted for function and purchase evaluation of parent brands’ brand equity. Control group with intention with the explained variance of 59% and 81% and α value product name and model but no brand name appeared on the ad was of .85 and .88, respectively. Positive and negative affects were included in the experiment. Two steps involved in the development extracted from affect measurement and the α values are both .87. As of measurements—selection of co-branding product and parent to the brand equity measures, factor results after deleting item 1 and brand and the development of formal questionnaire. 4 are the same as reported by Lassar, Mittal, and Sharma (1997), indicating construct validity (Zaichowsky 1985). The α values of Selection of Co-branding Product and Parent Brand social image, attachment, trust, and performance are .92, .94, .80, Since Park, Jun, and Shocker (1996) studied co-branding and .80, respectively. The measurement is valid and reliable. equity with low involvement product, this study chose high Each variable index is the sum of item multiplies its corre- involvement product to test the effect of co-branding. Considering sponding loading and percentage of variance explained by that market potential in the future, this study selected cell phone PDA as factor if there are more than one factors compose the variable co-branding product of cell phone and notebook. A pretest was (Anastasi and Urbina 1997, p. 302). The study then analyzed the carried out to decide the parent brands. The respondents were first components and overall brand equity of parent brands to decide on asked about the importance of the parent products (cell phone and the similar and complementary co-branding partners. The ranks of notebook) and the important product attributes. Then they indicated overall brand equity, from high to low, are Toshiba, Nokia, IBM, whether they recognized the brands and select the three most ASUS, OKWAP, and Twinhead. For the co-branding based on the favorable and three least favorable brands from a list of all the brand similarity of parent brands, the two brands are both rated high (or name and its logs of cell phone (31) and notebook (26) available in low) on all the components and overall brand equity and their the market at the time of the data collection. One hundred and 20 differences are not statistically different. For the complementary questionnaires were distributed. High and relatively low brand co-branding, one of the co-branding partners is rated high while the awareness was determined based on the rate of recognition and other is rated low on all the components and overall brand equity consensus among respondents on the degree of favorableness of the and the differences are statistically significant. As a result, the high brands. As a result, the high and relatively low strength brands were and relative low brands strength of notebook parent brands is Nokia and Okwap for cell phone and IBM, Asus, Toshiba and Toshiba and Twinhead, respectively. The high and relative low Twinhead for notebook, respectively. brand strength of cell phone parent brands is Nokia and Okwap, The second pretest was to select the photo of cell phone PDA respectively. The similar co-branding groups are Toshiba Nokia to be placed in the advertising in the formal experiment. Six cell and Twinhead Okap. The complementary co-branding groups are phone PDA photos were chosen from more than 20 prototypes Toshiba Okwap and Tiwnhead Nokia. Table 1 list the brand equity collected. Each of the six photos was presented to respondents by of each co-branding group. power point. Respondents were asked to evaluate each cell phone PDA as it was an actual product on six semantic differential scale Hypothesis testing items (like/dislike, great/poor function, attractive/unattractive, good/ H1 is tested by GLM where the independent variable is the bad quality, in/out of style, and buy/not buy). Finally, respondents strength of parent brands. Only the main effect of the brand strength were presented with the six photos appeared on the same page and of cell phone is significant on the functional evaluation of co- asked to select the most favorable one. The photo with the highest branding product (see table 2). Nokia generates higher functional means of all the items was selected based on the responses from 44 evaluation than that of Okwap. Hypothesis 1 is partially supported. valid questionnaires collected. GLM is used to test hypothesis 2 where the independent variable is the co-branding groups plus control group. The results Asia Pacific Advances in Consumer Research (Volume 6) / 91 TABLE 1 Brand equity of co-branding brands

Co-branding n Performance Social image Trust Attachment Overall Toshiba Nokia 58 4.09 4.83 4.79 5.20 4.73 Toshiba Okwap 58 3.97 4.36 4.39 4.91 4.41 Twinhead Nokia 59 4.11 4.64 4.56 5.03 4.59 Twinhead Okwap 62 3.58 4.28 4.40 4.77 4.24 Control group 28 3.30 3.90 3.70 4.67 3.89

TABLE 2 GLM Results–Dependent variables=f (brand strength of cell phone and notebook)

Source df SS MS F p-value

Positive affect intercept 1 5615.62 5615.62 7060.48 0.000 notebook 1 2.53 2.53 3.18 0.076 cell phone 1 .38 .38 .47 .492 notebook x cell phone 1 .315 .315 .40 .530 Error 233 185.32 .80 Total 236 5803.41

Negative affect intercept 1 1609.24 1609.24 1479.24 0.000 notebook 1 .78 .78 .72 0.398 cell phone 1 .66 .66 .60 .483 notebook x cell phone 1 .844 .844 .78 .379 error 233 253.48 1.09 Total 236 1864.78

Functional intercept 1 6769.28 6769.28 8835.98 0.000 evaluation notebook 1 9.481E-02 9.481E-02 .12 0.725 cell phone 1 9.13 9.13 11.92 .001 notebook x cell phone 1 .12 .12 .156 .693 error 233 178.50 .77 Total 236 6954.17

Purchase intercept 1 4644.90 4644.90 2141.61 0.000 intention notebook 1 1.41 1.41 .65 0.422 cell phone 1 .60 .60 .28 .599 notebook x cell phone 1 .11 .11 .05 .821 error 233 505.35 2.17 Total 236 5150.56

(see table 3) show that except for purchase intention, the main effect the two parent brands composing the co-brand. For instance, Nokia of co-branding is significant at .05 for positive and negative affect Toshiba is classified as Toshiba group since Toshiba has higher and function evaluation. Scheffe tests indicate that on positive brand equity than Nokia. Four groups resulted form the classification- affect evaluation, Toshiba Nokia is significant higher than control Toshiba, Nokia, Okwap, and control group. The results of GLM group. Toshiba Nokia generates significantly lower negative affect analyses show that the main effects are significant at .05 except that than control group. Both Toshiba Nokia and Tiwnhead Nokia are for purchase intention. Scheffe tests found that Toshiba group rated higher on function when compared to control group. generates higher positive affect than control group does. Both The results do not completely support hypothesis 2. The Toshiba and Nokia groups generate higher functional evaluation reason could be that respondents consider only the strong co- than control group does. branding partner when evaluating co-branding products. Thus, the To test whether the strong brand placed as the header or co-branding groups were re-classified based on the strong brand of modifier has a significant effect on the evaluation of co-branding 92 / Do Co-Branding Products Increase Consumers’ Purchase Behaviors in Taiwan? TABLE 3 GLM Results: (positive affect, negative affect, functional evaluation, and purchase intention = f (co-branding groups)

Source df SS MS F p-value

Positive affect intercept 1 5470.449 5470.449 6688.704 0.000 Co-branding 4 11.532 2.883 3.525 0.008 error 260 212.645 0.818 Total 265 6346.245

Negative affect intercept 1 1498.191 1498.191 1451.509 0.000 Co-branding 4 11.074 2.768 2.682 0.032 error 260 268.362 1.032 Total 265 1993.007

Functional intercept 1 6665.326 6665.326 8970.471 0.000 evaluation Co-branding 4 15.481 3.870 5.209 0.000 error 260 193.188 0.743 Total 265 7627.806

Purchase intercept 1 4570.790 4570.790 2190.333 0.000 intention Co-branding 4 6.461 1.615 0.774 0.543 error 260 542.568 2.087 Total 265 5638.444

product, a 2-way GLM was performed to analyze the data. The similar for the three dependent variable measures (R2 ranges from results show that the interaction effect of order of the strong brand .31 to .61). Functional evaluation accounts for most of the variance in the co-branding and similar/complementary parent brands on the explained by the independent variables for the performance evaluation of co-branding products is not significant. Only the main component of brand equity (about 25%). Purchase intention explains effects of order of the strong brand in the co-branding on negative most of the variances of social image component of brand equity affect and the similar/complementary parent brands on the evaluation (around 45%). Positive affect accounts for the most variances of of co-branding products are significant. When strong brand is trust (about 23%) and attachment (about 30%) component and placed as the header, co-branding product arouses less negative overall brand equity (about 40%). It appears that the dependent affect to respondents. Twinhead Nokia generates higher functional variable is most affected by its relevant independent variable. evaluation than Twinhead Okwap. Both are similarity groups. It seems that respondents consider only the strong partner CONCLUSIONS instead of the relationships between the two partners when evaluating This study simulates a new product, cell phone PDA, to co-branding product. Thus, this study examined whether the strong investigate the effects of brand strength, similarity/complementary brand partner with different levels of brand equity partner influence co-branding partners on the evaluations of co-branding products. the evaluation of co-branding products. The results of t-test show The results of this study show that, on brand strength, only cell that there is no difference on the evaluation of co-branding product phone parent brand affect the evaluation of function of co-branding whether Toshiba co-brands with Nokia or Okwap. product. The similarity/complementary partners have effects on the Hypotheses relating to purchase intention are not supported. It evaluation of function of the co-branding product is partially could be that 97.9% and 18.8% of respondents already own a cell supported. It could be that co-branding strategy is still not common phone and a PDA, respectively. Thus, this study examines the in Taiwan. At the time of data collecting, there is only one effects of respondents’ intention on replacing their current cell recognizable co-branding–Sony Ericsson which is the merge of cell phone and PDA on the dependent variables (four groups resulted). phone divisions of Sony and Ericsson. Respondents base their The results show that, compared with no intention of replacing both evaluation of the co-branding product on the strong partner under cell phone and PDA, respondents intend to replace both have higher this circumstance. A further test provides evidence that strong positive affect, function evaluation, and purchase intention toward partner plays the major role in co-branding. co-branding product. All the effects of independent variable on the purchase intention Stepwise regression is used to test whether the evaluations of are not significant. A further analyses show that those effects will co-branding products (i.e., positive affect, negative affect, function, be significant if respondents are considering replacing their current and purchase intention) have positive impact on the evaluation of cell phone or PDA. original brand. Three different measures of brand equity were used As to the effect of co-branding equity on the equity of parent in the regression models, brand equity of co-branding, brand equity brands, the regression results show that each brand equity component of co-branding minus that of the strong brand partner, brand equity is affected most by its relevant evaluation dimension of co-branding of co-branding minus that of the control group. Similar patterns of product. Specifically, evaluation of function accounts for independent variables entering the regression model are observed performance component, purchase intention accounts for social with different measures of brand equity (see table 4). The variances image, and positive affect influence trust and attachment component of dependent variable explained by the independent variables are and overall brand equity. Asia Pacific Advances in Consumer Research (Volume 6) / 93

1.22

1.41 1.44

1.22 1.35

1.44

1.25

1.22

0.28 0.26

0.39

0.29 1.44

VIF

(n=265)

Adj-R

0.27 0.27 1.00 0.32 0.32 1.22

0.33 0.33 1.35

0.45 0.44 1.00 0.56 0.56 1.22

0.61 0.61 1.41

0.25 0.24 1.00 0.33 0.32 1.25

0.28 0.28 1.00 0.39 0.39 1.22

0.44 0.43 1.35

0.40 0.40 0.64 0.53 0.53 0.47

0.58 0.58 0.39

positive affect

control group

–

** ** ** ** ** **

** **

** ** **

** **

** ** **

** **

** ** **

co-branding

purchase intention + b

1.20 0.24 4.29

1.30 0.13 2.08

1.42 0.51 11.23

1.31 0.38 8.38

1.23 0.26 5.67

1.31 0.32 5.58

1.40 0.37 6.99

1.31 0.37 6.99

1.20 0.26 4.62

1.31 0.47 9.70

1.42 0.39 8.35

1.20 0.28 5.81

VIF

(n=265)

Adj-R

performance + b

0.25 0.24 1.0 0.52 10.00

0.29 0.28 1.20 0.42 7.47

0.38 0.37 1.0 0.38 6.52 0.46 0.46 1.30 0.20 3.28

0.50 0.49 1.39 0.67 14.56

0.19 0.18 1.00 0.41 9.02

0.25 0.25 1.23 0.30 6.17

0.24 0.24 1.00 0.50 9.26

0.32 0.32 1.31 0.35 6.24

0.36 0.35 1.43 0.53 10.15

0.31 0.30 1.00 0.30 5.50 0.42 0.42 1.20 0.28 5.09

0.48 0.47 1.39 0.64 13.33

0.25 0.24 1.00 0.39 8.30

0.29 0.28 1.20 0.29 6.16

strong brand

–

** **

** ** **

** ** ** **

** **

TABLE 4

co-branding

1.22 0.24 3.89

1.41 0.45 8.24 1.44 0.34 6.16

1.22 0.21 3.87

1.34 0.31 4.89

1.43 0.29 4.58

1.25 0.33 5.42

1.22 0.22 3.73

1.41 0.40 7.36

1.44 0.37 6.83

1.22 0.28 4.87

1.40 0.40 6.59

1.44 0.24 3.89

VIF

Brand equity of co-branding = a + b

–

Adj-R

n=264

0.26 0.26 1.00 0.50 8.73 0.31 0.30 1.22 0.40 6.59

0.32 0.31 1.35 0.61 11.88

0.44 0.44 1.00 0.40 7.21 0.56 0.56 1.22 0.28 4.97

0.61 0.60 1.40 0.43 7.30

0.24 0.23 1.00 0.49 8.65

0.32 0.31 1.25 0.33 5.27

0.30 0.29 1.00 0.27 4.25 0.41 0.41 1.22 0.27 4.28

0.45 0.45 1.35 0.55 10.16

0.40 0.40 1.00 0.30 5.34 0.54 0.54 1.22 0.30 5.46

0.60 0.60 1.34 0.50 8.73

** ** ** ** **

** ** ** ** ** **

** ** **

** ** ** ** ** **

co-branding

The Results of Stepwise Regression

PI 0.24 4.24

PIP. effect 0.14 0.19 2.31 3.15

P. affect 0.38 8.31

function 0.26 5.62 P. affect 0.30 6.66

function 0.32 5.66

PI 0.37 7.13

PI 0.29 5.26 function 0.25 4.50

function 0.41 8.97

functionPI 0.31 6.74 0.29 6.09

. P. affect is positive affect; PI is purchase intention

2 function 0.41 7.18 Performance 1 function 0.51 9.64

3 function 0.37 6.19 2 PI 0.51 11.15

Social image 1 PI 0.67 14.43

3 PI 0.41 8.97

Trust 1 P. affect 0.49 9.00

2 P. affect 0.34 5.97

Attachment 1 affect P 0.55 10.53

2 P. affect 0.39 7.34 3 P. affect 0.31 5.87

Overall Brand Equity 1 P. affect 0.64 13.30

2 P. affect 0.50 9.94 3 P. affect 0.38 8.26

step variable

Note *: p<.05; **: p<.01 a. Hair, Anderson, Tatham and Black (1998) suggested that VIF should be small than 10. 94 / Do Co-Branding Products Increase Consumers’ Purchase Behaviors in Taiwan? Contributions Ajzen, Icek and Martin Fishbein (1980), Understanding The results of this study contribute to the co-branding literature. Attitudes and Predicting Social Behavior, Prentice-Hall, Co-branding has been a common marketing practice but not many Englewood Cliffs, N J. researches have been focus on this subject. Park, Jun, and Shocker Anastasi, Anna and Sussan Urbina (1997), Psychology Testing, (1996) concluded that complementary brands generate better New Jersey: Prentice Hall. attribute evaluations than solely rely on the extension of a strong Barwise, Patrick and Thomas Robertson (1992), “Brand brand. They used a low involvement product. However, the results Portfolio,” European Management Journal, 10 (3), 277-285. of this study suggest that respondents probably depend on their Boad, Bob (1999), “Co-branding comes of age,” Managing perceptions on the strong partner to evaluate the co-branding Intellectual Property, 94, 20-26 product. The first reason could be that respondents are not familiar Boush, David M. and Barbara Loken (1991), “A Process– with the co-branding strategies. In fact, some respondents indicated Tracing Study of Brand Extension,” Journal of Marketing that they did not notice the research product was marketed by two Research, 28 (February), 16-28. manufactures. The second reason could be that respondents believe Chaudhuri, Arjun (1998), “Product Class Effects on Perceived in well-established brand (or brand-oriented) in making decision Risk: The Role of Emotion,” International Journal of especially for high involvement product, cell phone PDA in this Research in Marketing, 15 (2), 157-168. study. They only focus on the one brand that appeals to them. Thus, Cohen, Joe B. and Ellen Golden (1972), “Informational Social the order of co-branding partners has no significant effect on the Influence and Product Evaluation,” Journal of Applied evaluation of co-branding product. As to the effect of the evaluation Psychology, 56 (1), 54-59. of the co-branding extension on the brand equity of parent brands, Curry-Swann, Lynne (1998), “Capture elusive sales,” The the results of this study are similar to previous research (e.g., Rao, American Salesman, 11-13. Qu, and Ruekest 1999; Simonir and Ruth 1998). Dagnoli, Judann and Scott Hume (1991), “Food brands team with fast-food,” Advertising age, (62) 30, 40. Suggestions to practitioners Doyle, Peter (1990), “Building successful brands: The strategic Co-branding strategy makes the relationship between the options,” The Journal of Consumer Marketing, 7 (2), 5-20. alliance partners highly visible (Park, Jun, and Shocker 1996), thus Eroglu, Sevgin (1992), “The Internationalization Process of increase the awareness level. The reputation of co-branding partners Franchise Systems: A Conceptual Model,” International certainly would impact the success of co-branding strategy. The Marketing Review, 9 (5), 19-30 . following suggestions are based on the findings of this research. Hair, Joseph F., Ronald L. Tatham, Rolph E. Anderson, and First, the results of this study show that both similarity and William C. Black (1998), Multivariate data analysis, (5th complementary partners enhance the positive evaluation of co- ed.). New Jersey: Prentice-Hall. branding product. Since co-branding is a market expansion strategy Kotler, Philip and Gary Armstrong (1996), Principles of (Kotler and Armstrong 1996) and a differentiation strategy in the Marketing (7th ed.), Englewood Cliffs, NJ: Prentice-Hall, mature market (Dagnoli and Hum, 1991). Thus, marketers could Inc. pursue partners that are either comparable or complementary on the Keller, Kevin Lane and David A. Aaker (1992), “The Effects of marketing mix to develop new markets. For marketers with an Sequential Introduction of Brand Extensions,” Journal of average-rated brand equity, pursuing high brand equity partner in Marketing Research, 29 (February), 35-50. establishing co-branding strategy seem to be more viable when Lai, Mengkuan and Shu-Huang Liu (2001), “The Trend of potential buyers are not familiar with co-branding or aspiring to Advertising Culture Appeals in Taiwan and the Effect of brand name products. Advertising Cultural Appeals on Affect and Attitudes toward Second, the study found that respondents have higher evaluation Advertising,” Journal of Management, 18 (3), 377-394. of co-branding product when they have the intention to replace their Loken, Barbara and James Ward (1990), “Alternative on current related product. Thus, marketers need to arouse consumers’ Approach to Understanding the Determinants of Typicality,” interest in the new product before co-branding strategy can generate Journal of Consumer Research, 17 (Sep.), 11-26. profits. Marketers need to recognize the need and switch cost of Miniard, Paul W. and Joel B. Cohen (1979), “Isolating Attitudi- consumers to introduce attractive co-branding product. nal and Normative Influences in Behavioral Intentions Models,” Journal of Marketing Research, 16(1), 102-110. Suggestions for future research Park, C. Whan, Jun, Sung Y., and Allan A. Shocker (1996), This study manipulates the similarity/complementary of co- “Composite Branding Alliances: An investigation of branding partners by the evaluations of brand equity, future research extension and feedback effects,” Journal of Marketing may consider co-branding of the marketing mix; for example, the Research, 18 (November), 453-466. co-branding of channel operator and product brand. The results of Rao, Akshay R, Lu Qu and Robert W. Ruekert (1999), “Signaling this study propose that brand strength is more effective than unobservable product quality through a brand ally,” Journal similarity/complementary alliance to extend to new product for of Marketing Research, 36 (May), 258-268 high involvement products. Future research could test whether Reddy, Srinivas. K., Holak, Susan L., and Subodh Bhat. (1994), product category does impact on the co-branding strategy. “To Extend or not to Extend: Success Determinants of Line Extensions, ”Journal of Marketing Research, 31 (May),. 243- REFERENCES 262. Aaker, David A. and Kevin Lane Keller (1990), “Consumer Ryan, Michale. J. and E. H. Bonfield (1980), “Fishbein’s Response to Brand Extension,” Journal of Marketing, 54 Intentions Model: A Test of External and Pragmatic (January), 27-41. Validity,” Journal of Marketing, 44 (2), 82-95. Aaker, David A., Stayman, Douglas M., and Michael R. Hagerty Simms, Jane. (Oct. 19, 2000), “Stretching Core Value,” (1986), “Warmth in advertising: Measurement, impact, and Marketing, 49-50. sequence effects,” Journal of Consumer Research, 12 (4), 365-381. Asia Pacific Advances in Consumer Research (Volume 6) / 95 Smith, Daniel C. and C. Whan Park (1992), “The Effects of Brand Extensions on Market Share and Advertising Efficiency,” Journal of Marketing Research, 29 (August), 296-313 Warshaw, Paul R. (1980), “A New Model for Predicting Behavioral Intentions: An Alternative to Fishbein,” Journal of Marketing Research, 17, 153-172. Westbrook, Robert. A. (1987), “Product/Consumption-based affective responses and postpurchase process,” Journal of Marketing Research, 24(3), 258-270. Zaichkowsky, Judice L. (1985), “Measuring the Involvement Construct,” Journal of Consumer Research, 12 (Dec.), 341- 352. Branding of Japanese Organic Supermarket and the Characteristics of Consumer Behavior in Its User Segments1,2 Osamu Sakai, Tokyo Metropolitan Government, Japan Kosuke Ogawa, Hosei University, Japan

BACKGROUND contributing to develop the brand management of organic Over the past few years, the interest in health-conscious supermarkets in Japan. organic food has remarkably increased. Behind this trend is a The purpose of this paper is to demonstrate consumer behavior growing concern for issues concerning health or the environment, in organic supermarkets. Based on the discoveries obtained from and an increase in the number of children with allergies. Organic this research, we will discuss future development strategies of the food is gradually attracting the attention of people who previously organic food market. We shall particularly offer some important had little interest in them. Statistic data confirms the presence of implications inferred from an in-store questionnaire survey data. active consumers who choose organic food, even if prices remain comparatively high. DATA In Japan, the organic food industry has mainly developed We hypothesized that the population for this questionnaire through the home delivery system (Ogawa, 1999, 2001; Tokue, survey would be the customers of a specific organic food 1999). So far, the exclusive, membership based home delivery supermarket. To grasp the general trends of the customers of this system was the dominant distribution channel for organic products. store, we sampled some of the visitors who purchased food items. However, this trend is gradually shifting towards the open, retail Accordingly, the actual population for this research is the total system, where the general run of consumers can have easy access amount of customers who visited this store on the day of the survey. to organic products. A total of 103 samples were selected among 990 visitors via random In addition, organic food is finally being acknowledged by the sampling. general public, as the enactment of the revised Japanese Agricultural The field investigators conducted questionnaire surveys by Standards for organic products in June 2000 symbolizes. The interviewing and filling out the answers given by the informants on enforcement of the law introduced the full-fledged certification the questionnaire form. The survey points were set at the opposite system of organic produce, which is likely to expand business side of cash registers so that field investigators could interview opportunities for the organic food market. customers who actually purchased items. Although there are many articles that discuss consumer behavior The majority of respondents were female (84.2%) and towards organic food in other countries, little is known about housewives accounted for 70.9%. Most of the respondents were in Japanese organic food consumers. their 30’s(43.7%). Since the increase in organic food-conscious consumers in many countries, a number of studies have investigated consumer CONSUMER CHARACTERISTICS IN THE behavior towards organic food in the European and U.S markets. QUESTIONNAIRE SURVEY For example, in 2001, Squires et al. presented a cross-cultural study of organic food consumption comparing Denmark and New Zealand. High Frequency of Visit and High Per-Customer Expenditure Gardyn analyzed the U.S organic market in 2002. In 1995, Grunert Out of 103 valid samples, 30 were heavy users, who visit the et al. took an interest in Danish schoolteachers buying organic food. store more than 3 times a week (Table 1). By combining them with In contrast, studies on Japanese consumer behavior towards organic the users who use the store “once or twice a week,” we can estimate food quite limited. that “frequent users” consist of 77.2% of the total customers. The average (median) expenditure per customer is 2,000 yen (Table 2), RESEARCH OBJECTIVES which is quite high for a supermarket that only sells food. According As an open distribution channel, organic supermarkets are to the consumer monitor research conducted by the Ministry of expected to become a major driving force for the growth of Japan’s Agriculture in 2000, the mode expenditure per customer is between organic food market. This pioneering study identifies the 400-499 yen for vegetables, and between 700–999 yen for meat characteristics of organic supermarket users, in expectation of products. We estimate that the general consumer spends approximately 1,500 yen per visit. The prices of vegetables sold in the organic supermarket we 1The English version of this paper is financially supported by the researched were approximately 30% higher than an ordinary Grant-in Aid for Scientific Research of the Ministry of Education, supermarket in that neighborhood. Culture, Sports, Science and Technology, Japanese Government, A number of studies point out that there is a willingness to pay program No.B (1) 32675-3702, 2003-2004. premium prices for eco-products and organic food (c.f. Loureiro et 2Acknowledgements: This paper is based on “In-store Research at al., 2002; Thompson, 1998; Weir and Calverler, 2002) . Organic Supermarket MOTHER’S, Fujigaoka Branch”, conducted on 25 November 2000 by Kohsuke Ogawa and The Center for Consumers’ Motivations for shopping at MOTHER’S Business and Industrial Research of Hosei University. We appre- Table 3 shows that “shopping at a natural food specialty store” ciate special co-operation by “Wise System Corp.” and “Yume was the most popular motivation for organic supermarket users Ichiba co.”. We owe particular thanks to Mr.Aso, manager of (72.8%). “High quality” was the second most answered reason, MOTHER’S Fujigaoka branch, who provided us with precious chosen by 57 people (55.3%). Both of these two choices are related suggestions and information on the competing organic (natural to the quality of product itself. Given the facts that customers chose food) supermarkets, store management and supply of goods, by MOTHER’S because it is a natural food shop or because the quality interview and hearing. of the products is high, we can assume that consumers have a strong