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http://dx.doi.org/10.13106/jafeb.2020.vol7.no9.613

Measuring the Interest of Smartphone Usage by Using Technology Acceptance Model Approach  

WISMANTORO, Yohan (Business and Economics Faculty, Universitas Dian Nuswantoro)
HIMAWAN, Heribertus (Faculty of Computer Science, Universitas Dian Nuswantoro)
WIDIYATMOKO, Karis (Faculty of Computer Science, Universitas Dian Nuswantoro)
Publication Information
The Journal of Asian Finance, Economics and Business / v.7, no.9, 2020 , pp. 613-620 More about this Journal
Abstract
The development of mobile Internet services allows more consumers to adopt smartphones as their primary communication device. This study focused on the application of the Technology Acceptance Model (TAM) to determine the willingness of batik and textile craftsmen to use smartphones. The population of this study was batik and textile craftsmen in the Bayat, Klaten, Central Java, Indonesia. A total sample of 243 people had answered 30 questions on the questionnaire with a 5-point Likert scale. The results of data analysis using GSCA software showed that, from eight hypotheses proposed, two hypotheses had not been supported. Technical support was not significant for the ease-of-use. It is because the damage experienced can be easily resolved by a repair shop. The findings reinforce the importance of training during the implementation of new technology. This training can make the users understand how to use new technology. The findings of this study strengthen the theory of TAM. Management support further influences the usefulness. This finding supports the theory of Igbaria technology acceptance. However, social influence did not significant influence the usefulness. This was because this study was conducted when the smartphone was no longer said to be a new technology.
Keywords
Ease of use; Usefulness; Technology Acceptance Model;
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Times Cited By KSCI : 6  (Citation Analysis)
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1 Alqudah, A. A. (2014). Accepting Moodle by academic staff at the University of Jordan: Applying and extending TAM in technical support factors. European Scientific Journal, 10(18). https://doi.org/10.19044/esj.2014.v10n18p%25p
2 Ardiansah, M. N., Chariri, A., Rahardja, S., & Udin, U. (2020). The effect of electronic payments security on e-commerce consumer perception: An extended model of technology acceptance. Management Science Letters, 10(7), 1473-1480.
3 Bajwa, D. S., Rai, A., & Brennan, I. (1998). Key Antecedents of Executive Information System Success: A Path Analytic Approach. Decision Support Systems, 22(1), 31-43.   DOI
4 Barhoumi, C. (2016). User acceptance of the e-information service as information resource: a new extension of the technology acceptance model. New Library World, 117(9/10). http://dx.doi.org/10.1108/NLW-06-2016-0045.
5 Biljon V., & Kotze, P. (2009). Cultural factors in a mobile phone adoption and usage model. Journal of Universal Computer Science, 14(16), 2650-2679.
6 Nguyen, X. T., & Luu, Q. K. (2020). Factors Affecting Adoption of Industry 4.0 by Small-and Medium-Sized Enterprises: A Case in Ho Chi Minh City, Vietnam. Journal of Asian Finance, Economics, and Business, 7(6), 255-264. doi: https://doi.org/10.13106/jafeb.2020.vol7.no6.255   DOI
7 Pai, F. Y., & Huang, K. I. (2011). Applying the technology acceptance model to the introduction of healthcare information systems. Technological Forecasting and Social Change, 78(4), 650-660.   DOI
8 Park, H. E., Yap, S. F. C., & Makkar, M. (2019). A laddering study of motivational complexities in mobile shopping. Marketing Intelligence & Planning, 37(2), 182-196. https://doi.org/10.1108/MIP-03-2018-0104   DOI
9 Perez, M. P., Sanchez, A. M., de Luis Carnicer, P., & Jimenez, M. J. V. (2004). A technology acceptance model of innovation adoption: the case of teleworking. European Journal of Innovation Management, 7(4), 280-291.   DOI
10 Phan, D. T. T., Nguyen, T. T. H., & Bui, T. A. (2019). Going beyond Border? Intention to Use International Bank Cards in Vietnam. Journal of Asian Finance, Economics and Business, 6(3), 315-325. doi: https://doi.org/10.13106/jafeb.2019.vol6.no3.315   DOI
11 Pipitwanichakarn, T., & Wongtada, N. (2019). Mobile commerce adoption among the bottom of the pyramid: a case of street vendors in Thailand. Journal of Science and Technology Policy Management, 10(1), 193-213. https://doi.org/10.1108/JSTPM-12-2017-0074   DOI
12 Ragu-Nathan, B.S., Apigian, C.H., Ragu-Nathan, T.S., and Tu, Q. (2004). A path analytic study of the effect of top management support for information systems performance. Omega 32(6), 459-471   DOI
13 Rajan, C. A., & Baral, R. (2015). Adoption of ERP system: An empirical study of factors influencing the usage of ERP and its impact on end user. IIMB Management Review, 27(2), 105-117.   DOI
14 Cascio, R., Mariadoss, B. J., & Mouri, N. (2010). The impact of management commitment alignment on salespersons' adoption of sales force automation technologies: An empirical investigation. Industrial Marketing Management, 39(7), 1088-1096.   DOI
15 Choi, S. (2018). What promotes smartphone-based mobile commerce? Mobile-specific and self-service characteristics. Internet Research, 28(1), 105-122, https://doi.org/10.1108/IntR-10-2016-0287   DOI
16 Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-339.   DOI
17 Chtourou, M. S., & Souiden N. (2010). Rethinking the TAM model: time to consider fun. Journal of Consumer Marketing, 27(4), 336-344.   DOI
18 Costa, C. J., Ferreira, E., Bento, F., & Aparicio, M. (2016). Enterprise resource planning adoption and satisfaction determinants. Computers in Human Behavior, 63, 659-671.   DOI
19 Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35, 982-1003.   DOI
20 Davis, F. D., & Warshaw, P. R. (1992). Extrinsic and Intrinsic Motivation to Use Computers in the Workplace. Journal of Applied Social Psychology, 22(4), 1111-1132.   DOI
21 eMarketer. (2017). Worldwide ad spending: the eMarketer forecast for 2017. Retrieved February 20, 2019 from: https://bit.ly/2GwlrWR.
22 Escobar-Rodriguez, T., & Bartual-Sopena, L. (2015). Impact of cultural factors on attitude toward using ERP systems in public hospitals. Revista de Contabilidad, 18(2), 127-137.   DOI
23 Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behaviour: An Introduction to Theory and Research. Reading, MA: Addision-Wesley.
24 Taylor, S., & Todd, P. (1995). Assessing IT Usage: The Role of Prior Experience. MIS Quarterly, 19(2), 561 - 570.   DOI
25 Rodriguez, M., & Trainor, K. (2016). A conceptual model of the drivers and outcomes of mobile CRM application adoption. Journal of Research in Interactive Marketing, 10(1), 67-84.   DOI
26 Rogers, E. (1995). The Diffusion of Innovations. New York, NY: The Free Press.
27 Sagib, G. K., & Zapan, B. (2014). Bangladeshi mobile banking service quality and customer satisfaction and loyalty. Management & Marketing, 9(3), 331-346.
28 Sanchez, R. A., & Hueros, A. D. (2010). Motivational factors that influence the acceptance of Moodle using TAM. Computers in Human Behavior, 26(6), 1632-1640.   DOI
29 Son, H., Park, Y., Kim, C., & Chou, J.S. (2012). Toward an understanding of construction professionals' acceptance of mobile computing devices in South Korea: An extension of the technology acceptance model. Automation in Construction, 28, 82-90.   DOI
30 Venkatesh, V., & Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139.   DOI
31 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.   DOI
32 Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 186-204.   DOI
33 Venter, P., van Rensburg, J. M., & Davis, A. (2012). Drivers of learning management system use in a South African open and distance learning institution. Australasian Journal of Educational Technology, 28(2), 183-198.
34 Karjaluoto, H., Tollinen, A., Pirttiniemi, J., & Jayawardhena, C. (2014). Intention to use mobile customer relationship management systems. Industrial Management & Data Systems, 114(6), 966-978.   DOI
35 Grob, M. (2015). Mobile shopping: a classification framework and literature review. International Journal of Retail and Distribution Management, 43(3), 221-241.   DOI
36 Igbaria, M., Zinatelli, N., Cragg, P., & Cavaye, A.L.M. (1997). Personal computing acceptance factors in small firms: a structural equation model. MIS Quarterly, 21(3), 279-305.   DOI
37 Igbaria, M. (1994). An examination of the factors contributing to microcomputer technology acceptance. Account Management-Information Technology, 4(4), 205-224.   DOI
38 Kapoor, K., Dwivedi, Y, Nial, P. C., Lal, B., & Weerakkody V. (2014). RFID integrated systems in libraries: extending TAM model for empirically examining the use. Journal of Enterprise Information Management, 27(6), 731-758. http://dx.doi.org/10.1108/JEIM-10-2013-0079   DOI
39 Kwak, Y. H., Park, J., Chung, B. Y., & Ghosh, S. (2012). Understanding end-users' acceptance of enterprise resource planning (ERP) system in project-based sectors. IEEE Transactions on Engineering Management, 59(2), 266-277.   DOI
40 Lee, J. W., Becker, K., & Potluri, R. M. (2016). Antecedents of Corporate Adoption of Social Media and the Role of the Technology Acceptance Model in the Path. Journal of Asian Finance, Economics and Business, 3(2), 67-76. doi: https://doi.org/10.13106/jafeb.2016.vol3.no2.67   DOI
41 Lee, Y., Lee, J., & Lee, Z. (2006). Social influence on technology acceptance behavior: self-identity theory perspective. Database Advance Systems, 37(2), 60-75.   DOI
42 Marinkovic V., & Kalinic, Z. (2017). Antecedents of customer satisfaction in mobile commerce: Exploring the moderating effect of customization. Online Information Review, 41(2), 138-154. https://doi.org/10.1108/OIR-11-2015-0364   DOI
43 Lewis, W., Agarwal, R., & Sambamurthy, V. (2003). Sources of influence on beliefs about information technology use: an empirical study of knowledge workers. MIS Quarterly, 27(4), 657-678.   DOI
44 Lin, F., Fofanah, S. S., & Liang, D. (2011). Assessing citizen adoption of e-Government initiatives in Gambia: A validation of the technology acceptance model in information systems success. Government Information Quarterly, 28(2), 271-279.   DOI
45 Maier, C., Laumer, S., Eckhardt, A., & Weitzel, T. (2013). Analyzing the impact of HRIS implementations on HR personnel's job satisfaction and turnover intention. The Journal of Strategic Information Systems, 22(3), 193-207.   DOI
46 Marakarkandy B., Yajnik, N., & Dasgupta, C. (2017). Enabling internet banking adoption: An empirical examination with an augmented technology acceptance model (TAM). Journal of Enterprise Information Management, 30(2), 263-294. https://doi.org/10.1108/JEIM-10-2015-0094   DOI
47 Mariani, M. G., Curcuruto, M., & Gaetani, I. (2013). Training opportunities, technology acceptance, and job satisfaction: A study of Italian organizations. Journal of Workplace Learning, 25(7), 455-475.   DOI
48 Nguyen, O. T. (2020). Factors Affecting the Intention to Use Digital Banking in Vietnam. Journal of Asian Finance, Economics, and Business, 7(3), 303-310. doi: https://doi.org/10.13106/jafeb.2020.vol7.no3.303   DOI
49 Montazemi, A. R., & Saremi, H. Q. (2013). Factors Affecting Internet Banking Pre-Usage Expectation Formation. In: Proceedings of the 46th Hawaii International Conference on System Sciences (pp. 4666-4675). IEEE.
50 Ngai, E. W. T., Poon, J. K. L., & Chan, Y. H. C. (2007). Empirical examination of the adoption of WebCT using TAM. Computers in Education, 48(2), 250-267.   DOI
51 Abeka, S. O. (2012). Perceived Usefulness, Ease of Use, Organizational and Bank Support As Determinants of Adoption of Internet Banking in East Africa. International Journal of Academic Research in Business and Social Sciences, 2(10), 97-112.
52 Ajzen, I. (1985). From Intentions to Actions: A Theory of Planned Behavior. In: J. Kuhl (ed.), Action control: From cognition to behavior (pp. 11-39). New York, NY: Springer-Verlag.