Understanding Consumer Intention to Use Go-Pay:  Development and Testing of Technology Acceptance Models for Consumers

Sugeng Purwanto; Sri Hartini; Gancar C Premananto

doi:10.26533/eksis.v14i1.423

Sugeng Purwanto University of Pembangunan Nasional Veteran East Java Indonesia
Sri Hartini Airlangga University Indonesia
Gancar C Premananto Airlangga University Indonesia

https://doi.org/10.26533/eksis.v14i1.423

Abstract views: 1418 ,

PDF downloads: 1245

Keywords: TAM, CAT, Pleasure, PAD, Prior experience, e-wallet, Go-pay

Abstract

The purpose of this study is to develop and test an integrated model of technology acceptance to determine the Intention of consumers to use e-wallet. The object used is the go-pay application wich is the relatively new technology products in Indonesia. Modeling in this study is integrating the Technology Acceotabce Model (TAM) model by involving affective factors namely Pleasure, Arousal, and Dominance (PAD) theory, and prior experience variables as a direct effect on perceiveid usefulness and Attitude toward usage, then its effect on adoption Intention. The sample in this study is millennial people age with a total sample of 270 respondents, analysis techniques using SmarPLS. The results of this study indicate that perceived usefulness, perceived easy of use, Pleasure, and Arousal have a positive effect on Attitude and Intention to use go-pay, while prior experience supports perceived usefulness, but does not support Attitude, and Dominance does not support the Attitude of using go-pay.

Downloads

Download data is not yet available.

References

Adesina, A. A., & Ayo, C. K. (2010). An empirical investigation of the level of users’ acceptance of e-banking in Nigeria. Journal of Internet Banking and Commerce, 15(1), 1–13.

Agag, G., & El-Masry, A. A. (2016). Understanding consumer intention to participate in online travel community and effects on consumer intention to purchase travel online and WOM: An integration of innovation diffusion theory and TAM with trust. Computers in Human Behavior, 60, 97–111.

Babin, B. J., Darden, W. R., & Griffin, M. (1994). Utilitarian shopping value. Journal of Consumer Research, 20(4), 644–657.

Baker, J., Levy, M., & Grewal, D. (1992). An Experimental Approach to Making Retail Store Environment Decisions. Journal of Retailing, 68(Winter), 445–460.

Bakker, I., van der Voordt, T., Vink, P., & de Boon, J. (2014). Pleasure, Arousal, Dominance: Mehrabian and Russell revisited. Current Psychology, 33(3), 405–421.

BankIndonesia. (2014). Bank Indonesia Mencanangkan Gerakan Nasional Non Tunai. Retrieved from http://gnnt.netcj.co.id/about

Bartneck, C., Suzuki, T., Kanda, T., & Nomura, T. (2007). The influence of people’s culture and prior experiences with Aibo on their attitude towards robots. AI and Society, 21(1), 217–230.

Batra, R., & Ray, M. L. (1986). Situational Effects of Advertising Repetition: The Moderating Influence of Motivation, Ability, and Opportunity to Respond. Journal of Consumer Research, 12(4), 432.

Ben Mansour, K. (2016). An analysis of business’ acceptance of internet banking: an integration of e-trust to the TAM. Journal of Business & Industrial Marketing, 31(8), 982–994.

Bruner, G. C., & Kumar, A. (2005). Explaining consumer acceptance of handheld Internet devices. Journal of Business Research, 58(5), 553–558.

Chen, J. V., Yen, D. C., & Chen, K. (2009). The acceptance and diffusion of the innovative smart phone use: A case study of a delivery service company in logistics. Information and Management, 46(4), 241–248.

Childers, T. L., Carr, C. L., & Carson, S. (2001). Hedonic and utilitrian motivations for online retail shopping behavior. Journal of Retailing, 77, 511–535.

Dabholkar, P. A., & Bagozzi, R. P. (2002). An Attitudinal Model of Technology - Based Self - Service: Moderating Effects of Consumer Traits and Situational Factors. Journal of the Academy of Marketing Science, 30(3), 184–201.

Davis, F., Bagozzi, R., & Warshaw, P. (1989). User Acceptance of Computer Technology: A Comparison of two Theoretical Models. Mangagement Science, 35(8), 982–1002.

Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Doctoral Dissertation. Cambridge, MA: MIT Sloan School of Management.

Dehghan, F., & Haghighi, A. (2015). E-money regulation for consumer protection. International Journal of Law and Management, 57(6), 610–620.

Dehghani, M., & Tumer, M. (2015). A research on effectiveness of Facebook advertising on enhancing purchase intention of consumers. Computers in Human Behavior, 49, 597–600.

Donovan, R. J., & Rossiter, J. R. (1994). Store Atmosphere and Purchasing Behavior. Journal of Retailing, 70, 283–294.

Fazio, R. H., & Zanna, M. P. (1978). Attitudinal qualities relating to the strength of the attitude-behavior relationship. Journal of Experimental Social Psychology, 14(4), 398–408.

Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Addison-Wesley Series in Social Psychology.

Gao, L., & Bai, X. (2014). A unified perspective on the factors influencing consumer acceptance of internet of things technology. Asia Pacific Journal of Marketing and Logistics, 26(2), 211–231.

Gentry, L., & Calantone, R. (2002). A Comparison of Three Models to Explain Shop-Bot Use on the Web. Psychology and Marketing, 19(11), 945–956.

Harris, R. W. (1999). Attitudes towards end-user computing: A structural equation model. Behaviour & Information Technology, 18(2), 109–125.

Hassanein, K., & Head, M. (2005). The impact of infusing social presence in the web interface: An investigation across product types. International Journal of Electronic Commerce, 10(2), 31–55. https://doi.org/10.2753/JEC1086-4415100202

Hirschman, E. C., & Holbrook, M. B. (1982). Hedonic Consumption: Emerging Concepts, Methods and Propositions. Journal of Marketing, 46(3), 92.

Holbrook, M. B., & Hirschman, E. C. (1982). The Experiential Aspects of Consumption: Consumer Fantasies, Feelings, and Fun. Journal of Consumer Research, 9(2), 132.

Igbaria, M., & Chakrabarti, A. (1990). Computer anxiety and attitudes towards microcomputer use. Behaviour and Information Technology, 9(3), 229–241.

Irani, T. (2000). Prior Experience, Perceived Usefulness and the Web: Factors Influencing Agricultural Audiences’ Adoption of Internet Communication Tools. Journal of Applied Communications, 84(2), 49–63.

Jackson, C. M., Chow, S., & Leitch, R. A. (1997). Toward an Understanding of the Behavioral Intention to Use an Information System. Decision Sciences, 28(2), 357–389.

Koufaris, M. (2002). Applying the Technology Acceptance Model and flow theory to online consumer behavior. Information Systems Researchnformation Systems Research, 13(2), 205–223.

Kulviwat, S., Bruner, G. C. I., Kumar, A., & Clark, S. A. N. and T. (2007). Toward a Unified Theory of Consumer Acceptance Technology. Psychology & Marketing, 24(12), 1059–1084.

Kulviwat, S., Bruner, G. C. I., & Neelankavil, J. P. (2014). Self-efficacy as an antecedent of cognition and affect in technology acceptance. Journal of Consumer Marketing, 31(3), 190–199.

Kulviwat, S., & Zhang, Y. (2016). Understanding consumer shopping behaviour : a comparison of three theories of emotions in predicting online flow. International Journal Electronic Marketing and Retailing, 7(1).

Kurnia, S., & Chien, A. J. (2003). The Acceptance of Online Grocery Shopping Developing a Conceptual Model of the Acceptance of OGS. 16th Bled ECommerce Conference ETransformation, 219–233.

Lee, M.-B., Suh, K.-S., & Whang, J. (2003). The impact of situation awareness information on consumer attitudes in the Internet shopping mall. Electronic Commerce Research and Applications, 2(3), 254–265.

Lee, Y., Kozar, K. A., & Larsen, K. R. T. (2003). The Technology Acceptance Model: Past, Present, and Future. Communications of the Association for Information Systems, 12(50), 752–780.

Li, D., Chau, P. Y. K., & Lou, H. (2005). Understanding Individual Adoption of Instant Messaging: An Empirical Investigation. Journal of the Association for Information Systems, 6(4), 102–129.

Liao, Z., & Cheung, M. T. (2002). Internet-based e-banking and consumer attitudes: An empirical study. Information and Management, 39(4), 283–295.

Lok, C. K. (2015). Adoption of Smart Card-Based E-Payment System for Retailing in Hong Kong Using an Extended Technology Acceptance Model. Advances in Business Marketing and Purchasing, 23, 7–290.

Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 173–191.

Mehrabian, A. (1995). Framework for a Comprehensive Description and Measurement of Emotional States. Genetic, Social, and General Psychology Monographs, 121(3), 339–361.

Mehrabian, A. (1996). Pleasure-arousal-dominance: A general framework for describing and measuring individual differences in Temperament. Current Psychology, 14(4), 261–292.

Mehrabian, A., & Russell, J. (1974). An approach to environmental psychology. Cambridge, MA: MIT Press.

Menon, S., & Kahn, B. (2002). Cross-Category Effects of Induced Arousal and Pleasure on the Internet Shopping Experience, 78(August), 31–40.

Mjølsnes, S. F., & Rong, C. (2003). On-Line E-Wallet System with Decentralized Credential Keepers, 87–99.

Mowen, J. C., & Michael Minor. (2002). Consumer Behavior (5th Edition). New York, McGraw-Hill.

Park, S. Y. (2009). An Analysis of the Technology Acceptance Model in Understanding University Students’ Behavioral Intention to Use e-Learning. Educational Technology & Society, 12(3), 150–162.

Pavelchak, M. A., Gardner, M. P., & Broach, V. C. (1991). Effect of Ad Pacing and Optimal Level of Arousal on Attitude Toward the Ad. Advances in Consumer Research, 18(Rebecca H. Holman and Michael R. Solomon, Provo, UT : Association for Consumer Research), 94–99. Retrieved from http://acrwebsite.org/volumes/7145/volumes/v18/NA-18

Pavlou, P. A. (2014). Consumer Acceptance of Electronic Commerce : Integrating Trust and Risk with the Technology Acceptance Model Integrating Trust and Risk with the Technology Acceptance Model Commerce : International Journal of Electronic Commerce, 7(3), 101–134.

Peter, J. P., & Olson, J. C. (2010). Consumer Behavior and Marketing Strategy (10th Edition). New York, McGraw-Hill.

Rouibah, K., & Abbas, H. (2006). A Modified Technology Acceptance Model for Camera Mobile Phone Adoption: Development and validation. 17th Australasian Conference on Information Systems, 1–11.

Russell, J. A., & Mehrabian, A. (1977). Evidence for a Three Factor Theory of Emotions. Journal of Research in Personality.

Schuette, R. A., & Fazio, R. H. (1995). Attitude Accessibility and Motivation as Determinants of Biased Processing: A Test of the MODE Model. Personality and Social Psychology Bulletin, 21(7), 704–710.

Sherman, E., Mathur, A., & Smith, R. B. R. (1997). Store Environment and Consumer Purchase Behavior: Mediating Role of Consumer Emotions. Psychology and Marketing, 14(4), 361–378.

Sova, K., & Sova, K. (2013). Electronic Money Trends in User ’s Perspective.

Taylor, S., & Todd, P. (1995). Assessing IT Usage: The Role of Prior Experience. MIS Quarterly, 19(4), 561.

Taylor, S., & Todd, P. (1995). Understanding information technology usage: A test of competing models. Information Systems Researcht, 6(2).

Varma, S. (2011). Prior computer experience and technology acceptance. Dissertation Abstracts International: Section B: The Sciences and Engineering. Retrieved from http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3432641%5Cnhttp://ovidsp.ovid.com/ovidweb.cgi?T=JS&PAGE=reference&D=psyc7&NEWS=N&AN=2011-99160-468

Vegas, L. (2005). Li, Na and Ping Zhang. Toward E-Commerce Website Evaluation and Use: An Affective Perspective. Post-ICIS’05 JAIS Theory Development Workshop, Las Vegas, NV, December 14, 2005. Evaluation, 1–32.

Venkatesh, V. (2000). Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, Acceptance Model. Information Systems Research, 11(4), 342–365.

Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decis Sci, 39(2), 273–315.

Venkatesh, V., & Davis, F. D. (2000). Theoretical Acceptance Extension Model : Field Four Studies of the Technology Longitudinal. Management Science, 46(2), 186–204.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance Of Information Technology : Toward A Unified View. MIS Quarterly, 27(3), 425–478.

Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157–178.

Understanding Consumer Intention to Use Go-Pay: Development and Testing of Technology Acceptance Models for Consumers

Abstract

Downloads

References

PlumX Metrics