Lessons learned from i-mode: What makes consumers click wireless banner ads?

This paper attempts to propose a structural model that integrates various factors influencing attitude towards wireless banner ads and intention to access them. This model is applied to empirical data of Japanese mobile users sampled in the greater Tokyo area. First, structural equation modelling is used to test the baseline model. The results show that the model explains mobile users' perceptual antecedents and consequences well, with all structural paths statistically significant. Second, in the attempt to identify different mobile user groups, a probabilistic cluster analysis is performed. This results in three-cluster groups, consisting of (1) housewives and part-timers, (2) middle-aged white-collar workers and professionals, and (3) students and ''parasite singles''. Finally, multigroup analysis is used to examine whether the model operates invariantly across the three-cluster groups. The results indicate significant differences in the paths associated with consumer innovativeness and perceived entertainment between the groups. In closing, managerial implications and future research directions are discussed, while important limitations are recognised.

[1]  S. Jarvenpaa,et al.  Exploring the implications of m-commerce for markets and marketing , 2002 .

[2]  Xueming Luo Uses and Gratifications Theory and E-Consumer Behaviors , 2002 .

[3]  Timo Koivumäki Consumer Attitudes and Mobile Travel Portal , 2002, Electron. Mark..

[4]  Ross D. Petty,et al.  Wireless Advertising Messaging: Legal Analysis and Public Policy Issues , 2003 .

[5]  Micael Dahlen Wireless Advertising Effectiveness Evaluation of an SMS Advertising Trial , 2000 .

[6]  R. Bagozzi,et al.  A Social Influence Model of Consumer Participation in Network- and Small-Group-Based Virtual Communities , 2004 .

[7]  Fred D. Davis User Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioral Impacts , 1993, Int. J. Man Mach. Stud..

[8]  E. Rogers Diffusion of Innovations , 1962 .

[9]  James C. Anderson,et al.  STRUCTURAL EQUATION MODELING IN PRACTICE: A REVIEW AND RECOMMENDED TWO-STEP APPROACH , 1988 .

[10]  J. Walther,et al.  Information-Seeking Strategies, Uncertainty, and Computer-Mediated Communication toward a Conceptual Model , 2002 .

[11]  Stuart J. Barnes,et al.  The mobile commerce value chain: analysis and future developments , 2002, Int. J. Inf. Manag..

[12]  P. Rössler,et al.  Mobile schriftliche Kommunikation oder: E-Mail für das Handy. Die Bedeutung elektronischer Kurznachrichten (Short Message Service) am Beispiel jugendlicher Handynutzer , 2001 .

[13]  Stuart J. Barnes,et al.  Rising sun: iMode and the wireless Internet , 2003, CACM.

[14]  Peter A. Todd,et al.  Understanding Information Technology Usage: A Test of Competing Models , 1995, Inf. Syst. Res..

[15]  Yao Wang,et al.  A robust and scalable clustering algorithm for mixed type attributes in large database environment , 2001, KDD '01.

[16]  Keng Siau,et al.  Building customer trust in mobile commerce , 2003, CACM.

[17]  Shin-Yuan Hung,et al.  Critical factors of WAP services adoption: an empirical study , 2003, Electron. Commer. Res. Appl..

[18]  Ritu Agarwal,et al.  The Role of Innovation Characteristics and Perceived Voluntariness in the Acceptance of Information Technologies , 1997 .

[19]  Karl G. Jöreskog,et al.  Lisrel 8: Structural Equation Modeling With the Simplis Command Language , 1993 .

[20]  Norman Sadeh,et al.  M-Commerce: Technologies, Services, and Business Models , 2002 .

[21]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[22]  Robert C. Nickerson,et al.  Issues in Mobile E-Commerce , 2002, Commun. Assoc. Inf. Syst..

[23]  Robert H. Ducoffe ADVERTISING VALUE AND ADVERTISING ON THE WEB , 1996 .

[24]  C. Lin Online-Service Adoption Likelihood , 1999 .

[25]  R. Bagozzi,et al.  On the evaluation of structural equation models , 1988 .

[26]  Barbara M. Byrne,et al.  Structural equation modeling with EQS : basic concepts, applications, and programming , 2000 .

[27]  Lana K. Brackett,et al.  Cyberspace Advertising vs. Other Media: Consumer vs. Mature Student Attitudes , 2001, Journal of Advertising Research.

[28]  Paul A. Pavlou,et al.  Predicting E-Services Adoption: A Perceived Risk Facets Perspective , 2002, Int. J. Hum. Comput. Stud..

[29]  Andrew Gemino,et al.  Evaluating modeling techniques based on models of learning , 2003, CACM.

[30]  David L. Mothersbaugh,et al.  Consumer Behavior: Building Marketing Strategy , 1997 .

[31]  Chang Liu,et al.  Technology acceptance model for wireless Internet , 2003, Internet Res..

[32]  Matthew S. Eastin,et al.  Credibility Assessments of Online Health Information: The Effects of Source Expertise and Knowledge of Content , 2006, J. Comput. Mediat. Commun..

[33]  Kenneth A. Bollen,et al.  Structural Equations with Latent Variables , 1989 .

[34]  Charlotte H. Mason,et al.  An empirical study of innate consumer innovativeness, personal characteristics, and new-product adoption behavior , 2003 .

[35]  Marija J. Norusis,et al.  SPSS 16.0 Statistical Procedures Companion , 2003 .

[36]  Miriam J. Metzger,et al.  Internet use in the contemporary media environment. , 2001 .

[37]  Stefan Baldi,et al.  The Entertaining Way to M-Commerce: Japan's Approach to the Mobile Internet - A Model for Europe? , 2002, Electron. Mark..

[38]  Andrea Rangone,et al.  Mobile Internet: An Empirical Study of B2C WAP Applications in Italy , 2002, Electron. Mark..

[39]  J. Hair Multivariate data analysis , 1972 .