Use Intention of Marketing-Based Android Application among Small and Medium Enterprises in Indonesia

Dona Anggriani; Wayu Eko Yudiatmaja; Firman Firman

Authors

Dona Anggriani Universitas Maritim Raja Ali Haji
Wayu Eko Yudiatmaja Universitas Maritim Raja Ali Haji
Firman Firman Universitas Maritim Raja Ali Haji

Keywords:

Technology Acceptance Model, Personal Attractiveness, Attitude, Behavioral Intention, E-Marketing

Abstract

Although several studies have employed the technology acceptance model to examine the effect of perceived usefulness, perceived ease of use, and attitude on behavioral intention, a limited number of research investigate the impact of personal attractiveness in this relationship. This research aims to extend TAM by analyzing the effect of personal attractiveness and attitude on behavioral intention. This research used a survey approach. The data were collected through questionnaires on 45 sellers affiliated with Dagin Hub Market of Tanjungpinang. We analyzed the data using partial least square-structural equation modeling (PLS-SEM). The results show that personal attractiveness does not affect attitude, while personal attractiveness significantly affects perceived usefulness. This study contributes to TAM by highlighting the crucial role of personal attractiveness in shaping perceived usefulness. The results are also helpful in enhancing the quality of SMEs' Android applications.

References

Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckmann (Eds.), Action control: From cognition to behavior (pp. 11–39). Springer.

Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314–324. https://doi.org/10.1002/hbe2.195

Al-Gahtani, S. S. (2016). Empirical investigation of e-learning acceptance and assimilation: A structural equation model. Applied Computing and Informatics, 12(1), 27–50.

Al-Swidi, A., Huque, S. M. R., Hafeez, M. H., & Shariff, M. N. M. (2014). The role of subjective norms in the theory of planned behavior in the context of organic food consumption. British Food Journal, 116(10), 1561–1580.

Alharbi, N., Papadaki, M., & Dowland, P. (2017). The impact of security and its antecedents in behaviour intention of using e-government services. Behaviour & Information Technology, 36(6), 620–636.

Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results [Ph.D Thesis Massachusetts Institute of Technology]. https://doi.org/10.1126/science.146.3652.1648

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–339.

Davis, F. D. ., Bagozzi, R. P. ., & Warshaw, P. R. . (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111–1132. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x

Di Stefano, G., Ruggieri, S., Bonfanti, R. C., & Faraci, P. (2023). Entrepreneurship on social networking sites: The roles of attitude and perceived usefulness. Behavioral Sciences, 13(4), 323. https://doi.org/10.3390/bs13040323

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://www.jstor.org/stable/3151312

Fu, H., Mensah, I. K., Wang, R., Gui, L., Wang, J., & Xiao, Z. (2022). The predictors of mobile government services adoption through social media: A case of Chinese citizens. Information Development, 2. https://doi.org/10.1177/02666669221114649

Garcia II, J. M. S., Himang, M. M., Himang, C. M., Densing, G. R. R., Alit, M. J. B., Burgos, N. P., Bongo, M. F., & Ocampo, L. A. (2023). An extended technology adoption model with perceived visual attractiveness to assess academic web portals. Trends in Higher Education, 2(1), 152–167. https://doi.org/10.3390/higheredu2010010

Gefen, D., & Straub, D. (2000). The relative importance of perceived ease of use in IS adoption: A study of e-commerce adoption. Journal of the Association for Information Systems, 1(1), 1–30.

Ghapanchi, A. H., Purarjomandlangrudi, A., McAndrew, A., & Miao, Y. (2020). Investigating the impact of space design, visual attractiveness and perceived instructor presence on student adoption of learning management systems. Education and Information Technologies, 25(6), 5053–5066. https://doi.org/10.1007/s10639-020-10204-5

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th Ed.). Cengage.

Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Springer. https://doi.org/10.1080/10705511.2022.2108813

Haseeb, M., Hussain, H. I., Kot, S., Androniceanu, A., & Jermsittiparsert, K. (2019). Role of social and technological challenges in achieving a sustainable competitive advantage and sustainable business performance. Sustainability (Switzerland), 11(14), 1–23. https://doi.org/10.3390/su11143811

Hatamifar, P., Ghader, Z., & Nikjoo, A. (2021). Factors affecting international tourists’ intention to use local mobile apps in online purchase. Asia Pacific Journal of Tourism Research, 26(12), 1285–1301. https://doi.org/10.1080/10941665.2021.1983626

Hung, S. Y., Chang, C. M., & Yu, T. J. (2006). Determinants of user acceptance of the e-Government services: The case of online tax filing and payment system. Government Information Quarterly, 23(1), 97–122. https://doi.org/10.1016/j.giq.2005.11.005

Jadhav, G. G., Gaikwad, S. V., & Bapat, D. (2023). A systematic literature review: digital marketing and its impact on SMEs. Journal of Indian Business Research, 15(1), 76–91. https://doi.org/10.1108/JIBR-05-2022-0129

Kanchanatanee, K., Suwanno, N., & Jarernvongrayab, A. (2014). Effects of attitude toward using, perceived usefulness, perceived ease of use and perceived compatibility on intention to use e-marketing. Journal of Management Research, 6(3), 1–13. https://doi.org/10.5296/jmr.v6i3.5573

Kim, K. J., Shin, D. H., & Park, E. (2015). Can coolness predict technology adoption? Effects of perceived coolness on user acceptance of smartphones with curved screens. Cyberpsychology, Behavior, and Social Networking, 18(9), 528–533. https://doi.org/10.1089/cyber.2014.0675

Ming, K. L. Y., & Jais, M. (2022). Factors Affecting the Intention to Use E-Wallets During the COVID-19 Pandemic. Gadjah Mada International Journal of Business, 24(1), 82–100. https://doi.org/10.22146/gamaijb.64708

Munim, Z. H., & Noor, T. (2020). Young people’s perceived service quality and environmental performance of hybrid electric bus service. Travel Behaviour and Society, 20, 133–143.

Natarajan, T., Balasubramanian, S. A., & Kasilingam, D. L. (2018). The moderating role of device type and age of users on the intention to use mobile shopping applications. Technology in Society, 53, 79–90. https://doi.org/10.1016/j.techsoc.2018.01.003

Peng, M. Y. P., Xu, Y., & Xu, C. (2023). Enhancing students’ English language learning via M-learning: Integrating technology acceptance model and S-O-R model. Heliyon, 9(2), e13302. https://doi.org/10.1016/j.heliyon.2023.e13302

Qosasi, A., Permana, E., Muftiadi, A., Purnomo, M., & Maulina, E. (2019). Building SMEs’ competitive advantage and the organizational agility of apparel retailers in indonesia: The role of ICT as an initial trigger. Gadjah Mada International Journal of Business, 21(1), 69–90. https://doi.org/10.22146/gamaijb.39001

Raza, S. A., Umer, A., & Shah, N. (2017). New determinants of ease of use and perceived usefulness for mobile banking adoption. International Journal of Electronic Customer Relationship Management, 11(1), 44–65. https://doi.org/10.1504/ijecrm.2017.10007744

Ringle, C. M., Sarstedt, M., Sinkovics, N., & Sinkovics, R. R. (2023). A perspective on using partial least squares structural equation modelling in data articles. Data in Brief, 48. https://doi.org/10.1016/j.dib.2023.109074

Rogers, E. M. (1983). Diffusion of innovations (3rd Ed.). The Free Press.

Rogers, E. M. (2003). Diffusion of innovations (5th Ed.). The Free Press.

Roy, S. K., Balaji, M. S., & Nguyen, B. (2020). Consumer-computer interaction and in-store smart technology (IST) in the retail industry: The role of motivation, opportunity, and ability. Journal of Marketing Management, 36(3–4), 299–333.

Salameh, A. A. (2022). An intention to use mobile applications for medical supplies and equipment ordering in clinics. Frontiers in Public Health, 10. https://doi.org/10.3389/fpubh.2022.1021291

Salancik, G. R., & Pfeffer, J. (1978). A social information processing approach to job attitudes and task design. Administrative Science Quarterly, 23(2), 224–253.

Schein, E. H. (1984). Coming to a new awareness of organizational culture. Sloan Management Review, 25(2), 3–16.

Shah, H. J., & Attiq, S. (2018). Impact of technology quality, perceived ease of use and perceived usefulness in the formation of consumer’s satisfaction in the context of e-learning. Abasyn Journal of Social Sciences, 9(1), 124–140.

Shanmugam, A., Savarimuthu, M. T., & Wen, T. C. (2014). Factors affecting Malaysian behavioral intention to use mobile banking with mediating effects of attitude. Academic Research International, 5(2), 236–253.

Sondakh, J. J. (2017). Behavioral intention to use e-tax service system: An application of technology acceptance model. European Research Studies Journal, 20(2), 48–64.

Su, C. Y., & Chiu, C. H. (2021). Perceived enjoyment and attractiveness influence Taiwanese elementary school students’ intention to use interactive video learning. International Journal of Human-Computer Interaction, 37(6), 574–583. https://doi.org/10.1080/10447318.2020.1841423

Suki, N. M., & Suki, N. M. (2011). Exploring the relationship between perceived usefulness, perceived ease of use, perceived enjoyment, attitude and subscribers’ intention towards using 3G mobile services. Journal of Information Technology Management, 22(1), 1–7.

Susanty, A., Handoko, A., & Puspitasari, N. B. (2020). Push-pull-mooring framework for e-commerce adoption in small and medium enterprises. Journal of Enterprise Information Management, 33(2), 381–406. https://doi.org/10.1108/JEIM-08-2019-0227

Taiminen, H. M., & Karjaluoto, H. (2015). The usage of digital marketing channels in SMEs. Journal of Small Business and Enterprise Development, 22(4), 633–651. https://doi.org/10.1108/JSBED-05-2013-0073

Van der Heijden, H. (2003). Factors influencing the usage of websites: The case of a generic portal in The Netherlands. Information & Management, 40(6), 541–549.

Vroom, V. H. (1964). Work and motivation. Wiley.

Wilson, N., Keni, K., & Tan, P. H. P. (2021). The role of perceived usefulness and perceived ease-of-use toward satisfaction and trust which influence computer consumers’ loyalty in china. Gadjah Mada International Journal of Business, 23(3), 262–294. https://doi.org/10.22146/gamaijb.32106

Yudiatmaja, W. E. (2021). Public service motivation and service quality of local government employees: A moderated mediation analysis. Policy & Governance Review, 5(1), 33–49.

Yudiatmaja, W. E., Salomo, R. V., & Prasojo, E. (2021). Smart Technologies, Artificial Intelligence, Robotics, and Algorithms (STARA) competencies during COVID-19: A confirmatory factor analysis using SEM approach. Journal of Physics: Conference Series, 2049(1), 012014. https://doi.org/10.1088/1742-6596/2049/1/012014

Yudiatmaja, W. E., Salomo, R. V., & Prasojo, E. (2023). Fostering innovative behavior of millennial public employee through leadership styles and organizational trust. SAGE Open, 13(2), 1–17. https://doi.org/10.1177/21582440231178545

Yudiatmaja, W. E., Yoserizal, Y., Edison, E., Kristanti, D., Tovalini, K., Samnuzulsari, T., & Malek, J. A. (2022). Adoption of online learning in Indonesian higher education during the COVID-19 pandemic. The Journal of Behavioral Science, 17(2), 73–89. https://so06.tci-thaijo.org/index.php/IJBS/article/view/255171

Zeithaml, V. A. (2002). Service excellence in electronic channels. Managing Service Quality, 12(3), 135–139.

Zhao, H., Peng, H., & Li, W. (2022). Analysis of factors affecting individuals’ online consumer credit behavior: Evidence from China. Frontiers in Psychology, 13, 1–14. https://doi.org/10.3389/fpsyg.2022.922571