Exploring factors influencing mobile users' intention to adopt multimedia messaging service

While short messaging service (SMS) is discussed often in recent literature, multimedia messaging service (MMS), a media rich successor of SMS, is seldom heard or understood by mobile users in Taiwan. The adoption rates of MMS are far from satisfactory, implying that there might be some factors keeping the potential users away from using MMS. This research integrates a qualitative method, the Zaltman Metaphor Elicitation Technique, with the quantitative questionnaire survey to elicit and validate underlying factors which influence potential users' attitude and intention toward the adoption of MMS. A research model together with eight hypotheses was formulated, and a questionnaire based survey was administrated to mobile users knowledgeable about mobile messaging services for empirically validating the research model and testing the hypotheses. Our research findings show that relative advantage and ease of use are important factors significantly influencing mobile users' adoption of MMS but the other two antecedents, facilitating conditions and previous experience, do not have significant and direct impacts on mobile users' intention to use MMS. These study results can be referenced by service providers for designing and developing successful business applications to catch the valuable opportunity and benefit of MMS.

[1]  Dong Hee Shin,et al.  An empirical investigation of a modified technology acceptance model of IPTV , 2009, Behav. Inf. Technol..

[2]  H. V. Trijp,et al.  Consumer research in the early stages of new product development: a critical review of methods and techniques , 2005 .

[3]  Ritu Agarwal,et al.  A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology , 1998, Inf. Syst. Res..

[4]  David M. McCutcheon,et al.  Conducting case study research in operations management , 1993 .

[5]  Timo Koivumäki,et al.  The effects of information quality of mobile information services on user satisfaction and service acceptance–empirical evidence from Finland , 2008, Behav. Inf. Technol..

[6]  Jinwoo Kim,et al.  Architectural criteria for website evaluation – conceptual framework and empirical validation , 2004, Behav. Inf. Technol..

[7]  Wynne W. Chin.  The partial least squares approach for structural equation modeling. , 1998 .

[8]  Philip Sugai,et al.  Mapping the mind of the mobile consumer across borders , 2005 .

[9]  J. J. Po-An Hsieh,et al.  ScholarWorks @ Georgia State University , 2016 .

[10]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[11]  G. Zaltman.  How Customers Think: Essential Insights into the Mind of the Market , 2003 .

[12]  Arno Scharl,et al.  Diffusion and success factors of mobile marketing , 2005, Electron. Commer. Res. Appl..

[13]  Per E. Pedersen,et al.  Explaining intention to use mobile chat services: moderating effects of gender , 2005 .

[14]  Keith S. Coulter,et al.  Interpreting Consumer Perceptions of Advertising: An Application of the Zaltman Metaphor Elicitation Technique , 2001 .

[15]  Chiew Tong Lau,et al.  Wireless messaging services for mobile users , 2001, J. Netw. Comput. Appl..

[16]  Manuel J. Sánchez-Franco,et al.  Exploring the influence of gender on the web usage via partial least squares , 2006, Behav. Inf. Technol..

[17]  M. Sherif,et al.  The psychology of attitudes. , 1946, Psychological review.

[18]  Shuchih Ernest Chang,et al.  A user study of accessing web applications via voice cellular phone: a model comparison approach , 2009, Behav. Inf. Technol..

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

[20]  Detmar W. Straub,et al.  A Practical Guide To Factorial Validity Using PLS-Graph: Tutorial And Annotated Example , 2005, Commun. Assoc. Inf. Syst..

[21]  Ken Eason,et al.  Perceptions versus expectations of multimedia messaging service (MMS) , 2004, Personal and Ubiquitous Computing.

[22]  P. Lachenbruch.  Statistical Power Analysis for the Behavioral Sciences (2nd ed.) , 1989 .

[23]  Michel Tenenhaus,et al.  PLS path modeling , 2005, Comput. Stat. Data Anal..

[24]  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..

[25]  Phillip Olla,et al.  Developing a wireless reference model for interpreting complexity in wireless projects , 2004, Ind. Manag. Data Syst..

[26]  Viswanath Venkatesh,et al.  Predicting Different Conceptualizations of System Use: The Competing Roles of Behavioral Intention, Facilitating Conditions, and Behavioral Expectation , 2008, MIS Q..

[27]  Izak Benbasat,et al.  Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation , 1991, Inf. Syst. Res..

[28]  Graham K. Rand,et al.  Quantitative Applications in the Social Sciences , 1983 .

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

[30]  Minna Pura.  Linking perceived value and loyalty in location‐based mobile services , 2005 .

[31]  K. Keeling,et al.  Using ZMET to explore barriers to the adoption of 3G mobile banking services , 2003 .

[32]  Jacob Cohen.  Statistical Power Analysis for the Behavioral Sciences , 1969, The SAGE Encyclopedia of Research Design.

[33]  Julie A. Jacko,et al.  The effects of multimodal feedback on older adults' task performance given varying levels of computer experience , 2004, Behav. Inf. Technol..

[34]  H A P Archbold,et al.  The use of multi-media messaging in the referral of musculoskeletal limb injuries to a tertiary trauma unit using: a 1-month evaluation. , 2005, Injury.

[35]  Viswanath Venkatesh,et al.  Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model , 2000, Inf. Syst. Res..

[36]  R. Goldsmith,et al.  INNOVATIVENESS AND PRICE SENSITIVITY: MANAGERIAL, THEORETICAL AND METHODOLOGICAL ISSUES , 1997 .

[37]  Chien-Wen David Chen,et al.  Understanding consumer intention in online shopping: a respecification and validation of the DeLone and McLean model , 2009, Behav. Inf. Technol..

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

[39]  John Hulland,et al.  Use of partial least squares (PLS) in strategic management research: a review of four recent studies , 1999 .