The Effects of Personality Traits on User Acceptance of Mobile Commerce

Existing research on user acceptance of mobile commerce has found that technological perceptions—such as perceived usefulness, perceived ease of use, and perceived compatibility—had significant effects on user behavior. However, the effects of personality traits have seldom been examined. The purpose of this research is to examine the effects of five personality traits of extraversion, agreeableness, openness to experience, conscientiousness, and neuroticism on user adoption of mobile commerce. Partial least squares was employed to conduct data analysis. The results show that extraversion has a strong effect on trust, whereas neuroticism has significantly negative effects on trust and perceived usefulness, both of which determine user intention to adopt mobile commerce.

[1]  Dong Hee Shin,et al.  Understanding User Acceptance of DMB in South Korea Using the Modified Technology Acceptance Model , 2009, Int. J. Hum. Comput. Interact..

[2]  Norman A. Johnson,et al.  Personality traits and concern for privacy: an empirical study in the context of location-based services , 2008, Eur. J. Inf. Syst..

[3]  Upkar Varshney,et al.  Mobile Commerce: Framework, Applications and Networking Support , 2002, Mob. Networks Appl..

[4]  Detmar W. Straub,et al.  Validation in Information Systems Research: A State-of-the-Art Assessment , 2001, MIS Q..

[5]  J. George,et al.  When openness to experience and conscientiousness are related to creative behavior: an interactional approach. , 2001, The Journal of applied psychology.

[6]  Imsook Ha,et al.  Determinants of adoption of mobile games under mobile broadband wireless access environment , 2007, Inf. Manag..

[7]  Wynne W. Chin,et al.  A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic - Mail Emotion/Adoption Study , 2003, Inf. Syst. Res..

[8]  ThaeMin Lee,et al.  THE IMPACT OF PERCEPTIONS OF INTERACTIVITY ON CUSTOMER TRUST AND TRANSACTION INTENTIONS IN MOBILE COMMERCE , 2005 .

[9]  Detmar W. Straub,et al.  Validation Guidelines for IS Positivist Research , 2004, Commun. Assoc. Inf. Syst..

[10]  Alexander Hars,et al.  Web Based Knowledge Infrastructures for the Sciences: An Adaptive Document , 2000, Commun. Assoc. Inf. Syst..

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

[12]  Carla Ruiz-Mafé,et al.  Exploring individual personality factors as drivers of M-shopping acceptance , 2009, Ind. Manag. Data Syst..

[13]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[14]  Cheol Lee,et al.  A Usability Checklist for the Usability Evaluation of Mobile Phone User Interface , 2006, Int. J. Hum. Comput. Interact..

[15]  S. Gosling,et al.  A very brief measure of the Big-Five personality domains , 2003 .

[16]  Izak Benbasat,et al.  A Framework for the Study of Customer Interface Design for Mobile Commerce , 2004, Int. J. Electron. Commer..

[17]  Richard T. Watson,et al.  Task-technology fit for mobile locatable information systems , 2008, Decis. Support Syst..

[18]  P. Costa,et al.  Revised NEO Personality Inventory (NEO-PI-R) and NEO-Five-Factor Inventory (NEO-FFI) , 1992 .

[19]  Sumeet Gupta,et al.  The effects of privacy concerns and personal innovativeness on potential and experienced customers’ adoption of location-based services , 2009, Electron. Mark..

[20]  Ying-Feng Kuo,et al.  Towards an understanding of the behavioral intention to use 3G mobile value-added services , 2009, Comput. Hum. Behav..

[21]  Niina Mallat,et al.  Exploring consumer adoption of mobile payments - A qualitative study , 2007, J. Strateg. Inf. Syst..

[22]  J. M. Digman PERSONALITY STRUCTURE: EMERGENCE OF THE FIVE-FACTOR MODEL , 1990 .

[23]  I. Ajzen The theory of planned behavior , 1991 .

[24]  Hsing Kenneth Cheng,et al.  An empirical study of mobile commerce in insurance industry: Task-technology fit and individual differences , 2007, Decis. Support Syst..

[25]  Pruthikrai Mahatanankoon,et al.  The Effects of Personality Traits and Optimum Stimulation Level on Text-Messaging Activities and M-commerce Intention , 2007, Int. J. Electron. Commer..

[26]  Xinran Y. Lehto,et al.  Adoption of Mobile Technologies for Chinese Consumers , 2007 .

[27]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[28]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[29]  Felix B. Tan,et al.  The Relationship Between Mobile Service Quality, Perceived Technology Compatibility, and Users' Perceived Playfulness in the Context of Mobile Information and Entertainment Services , 2008, Int. J. Hum. Comput. Interact..

[30]  D. A. Kenny,et al.  The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. , 1986, Journal of personality and social psychology.

[31]  Robert F. Easley,et al.  Research Note - How Does Personality Matter? Relating the Five-Factor Model to Technology Acceptance and Use , 2008, Inf. Syst. Res..

[32]  Peter A. Rosen,et al.  The Impact of the Big Five Personality Traits on the Acceptance of Social Networking Website , 2008, AMCIS.

[33]  Chin-Lung Hsu,et al.  Adoption of the mobile Internet: An empirical study of multimedia message service (MMS) , 2007 .

[34]  Gi Mun Kim,et al.  Understanding dynamics between initial trust and usage intentions of mobile banking , 2009, Inf. Syst. J..

[35]  Dale Goodhue,et al.  Task-Technology Fit and Individual Performance , 1995, MIS Q..

[36]  Bongsik Shin,et al.  Examining influencing factors of post-adoption usage of mobile internet: Focus on the user perception of supplier-side attributes , 2010, Inf. Syst. Frontiers.

[37]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[38]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

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

[40]  S. Briggs,et al.  Assessing the five-factor model of personality description. , 1992, Journal of personality.

[41]  J. H. Davis,et al.  An Integrative Model Of Organizational Trust , 1995 .

[42]  Matti Rossi,et al.  The impact of use context on mobile services acceptance: The case of mobile ticketing , 2009, Inf. Manag..

[43]  Rita Walczuch,et al.  Psychological antecedents of institution-based consumer trust in e-retailing , 2004, Inf. Manag..

[44]  Detmar W. Straub,et al.  Trust and TAM in Online Shopping: An Integrated Model , 2003, MIS Q..

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

[46]  Naresh K. Malhotra,et al.  Common Method Variance in IS Research: A Comparison of Alternative Approaches and a Reanalysis of Past Research , 2006, Manag. Sci..

[47]  Yu-Chen Chen,et al.  Extrinsic versus intrinsic motivations for consumers to shop on-line , 2005, Inf. Manag..

[48]  Sonja Wiley-Patton,et al.  Consumer adoption of mobile TV: Examining psychological flow and media content , 2009, Comput. Hum. Behav..

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

[50]  Christer Carlsson,et al.  Adoption of Mobile Devices/Services — Searching for Answers with the UTAUT , 2006, Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06).

[51]  Paul A. Pavlou,et al.  Consumer Acceptance of Electronic Commerce: Integrating Trust and Risk with the Technology Acceptance Model , 2003, Int. J. Electron. Commer..

[52]  Key Pousttchi,et al.  Mobile word-of-mouth – A grounded theory of mobile viral marketing , 2009, J. Inf. Technol..

[53]  Qingfei Min,et al.  Mobile commerce user acceptance study in China: A revised UTAUT model , 2008 .

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

[55]  P. Costa,et al.  NEO inventories for the NEO Personality Inventory-3 (NEO-PI-3), NEO Five-Factor Inventory-3 (NEO-FFI-3), NEO Personality Inventory-Revised (NEO PI-R) : professional manual , 2010 .

[56]  Detmar W. Straub,et al.  Structural Equation Modeling and Regression: Guidelines for Research Practice , 2000, Commun. Assoc. Inf. Syst..

[57]  Scott B. MacKenzie,et al.  Common method biases in behavioral research: a critical review of the literature and recommended remedies. , 2003, The Journal of applied psychology.

[58]  George M. Giaglis,et al.  Perceived Value and Usage Patterns of Mobile Data Services: A Cross-Cultural Study , 2007, Electron. Mark..

[59]  Barbara H Wixom,et al.  A Theoretical Integration of User Satisfaction and Technology Acceptance , 2005, Inf. Syst. Res..

[60]  Murray R. Barrick,et al.  Personality and Performance at the Beginning of the New Millennium: What Do We Know and Where Do We Go Next? , 2001 .

[61]  Charles J. Kacmar,et al.  Developing and Validating Trust Measures for e-Commerce: An Integrative Typology , 2002, Inf. Syst. Res..