Employees Intentions to Use Performance Management System in Regional Bank: Perspective from Generation-X

Authors

DOI:

https://doi.org/10.34306/att.v6i3.445

Keywords:

Self-Efficacy, Perceived Usefulness, Attitude, Intention to Use, Effective Institution

Abstract

Amidst a scarcity of literature on the adoption of information technology among Generation X employees within the banking sector, this study aims to delve into the factors influencing their intention to use Performance Management Systems (PMS). Drawing upon the Technology Acceptance Model, this study endeavors to analyze the impact of self-efficacy, perceived usefulness, and attitude towards PMS on the intention to use such systems among Generation X bank employees. Employing a quantitative methodology, the study engaged 158 participants from a regional bank in Indonesia, selected through purposive sampling. Data gathered via online questionnaires underwent analysis using Partial Least Square-Structural Equation Modeling via SmartPLS 4.0 to evaluate ten research hypotheses. The findings revealed that while self-efficacy in PMS did not directly influence the intention to use PMS, perceived usefulness of PMS and attitude to PMS acted as mediators, facilitating the effect of self-efficacy on intention. These results can be attributed to the inherent skepticism and pragmatism of Generation X individuals towards novel technologies. Consequently, this study yields significant insights for both the advancement of technology acceptance literature and the strategic preparedness of banking institutions in adopting new technologies.

References

R. Shanti, W. Avianto, and W. A. Wibowo, “A systematic review on banking digital transformation,” Jurnal Administrare: Jurnal Pemikiran Ilmiah Dan Pendidikan Administrasi Perkantoran, vol. 9, no. 2, 2022.

Y. Evdokimova, “Digitalization of the financial sector: Background and specifics,” in 2nd International Scientific and Practical Conference on Digital Economy (ISCDE 2020). Atlantis Press, 2020, pp. 179–183.

S. Lissitsa and T. Laor, “Baby boomers, generation x and generation y: Identifying generational differences in effects of personality traits in on-demand radio use,” Technology in society, vol. 64, p. 101526, 2021.

O. T. Nguyen, “Factors affecting the intention to use digital banking in vietnam,” The Journal of Asian Finance, Economics and Business, vol. 7, no. 3, pp. 303–310, 2020.

E. A. Firmansyah, M. Masri, M. Anshari, and M. H. A. Besar, “Factors affecting fintech adoption: a systematic literature review,” FinTech, vol. 2, no. 1, pp. 21–33, 2022.

O. Atabek, “Associations between emotional states, self-efficacy for and attitude towards using educational technology.” International Journal of Progressive Education, vol. 16, no. 2, pp. 175–194, 2020.

A. Bastari, A. Eliyana, A. Syabarrudin, Z. Arief, and A. P. Emur, “Digitalization in banking sector: the role of intrinsic motivation,” Heliyon, vol. 6, no. 12, 2020.

K.-D. Pham, “Factors determining customers’ intention to use digital banking-the case of vietnam,” in International Conference on Science, Engineering Management and Information Technology. Springer, 2022, pp. 279–286.

R. Jena, “Factors impacting senior citizens’ adoption of e-banking post covid-19 pandemic: an empirical study from india,” Journal of Risk and Financial Management, vol. 16, no. 9, p. 380, 2023.

D. E. E. Saputra, V. Maulida Rahma, A. Eliyana, A. S. Pratama, R. D. Anggraini, N. L. M. Kamil, and I. Ismail, “Do system quality and information quality affect job performance? the mediation role of users’ perceptions,” Plos one, vol. 18, no. 6, p. e0285293, 2023.

M. Khalil, K. F. Khawaja, and M. Sarfraz, “The adoption of blockchain technology in the financial sector during the era of fourth industrial revolution: a moderated mediated model,” Quality & Quantity, vol. 56, no. 4, pp. 2435–2452, 2022.

A. Al-Madadha, M. H. Al Khasawneh, O. Al Haddid, and A. S. Al-Adwan, “Adoption of telecommuting in the banking industry: A technology acceptance model approach,” Interdisciplinary Journal of Information, Knowledge, and Management, vol. 17, pp. 443–470, 2022.

A. A. AlQudah, M. Al-Emran, and K. Shaalan, “Technology acceptance in healthcare: a systematic review,” Applied Sciences, vol. 11, no. 22, p. 10537, 2021.

Y. El Archi and B. Benbba, “The applications of technology acceptance models in tourism and hospitality research: A systematic literature review,” Journal of Environmental Management & Tourism, vol. 14, no. 2, pp. 379–391, 2023.

H. G. Musa, I. Fatmawati, N. Nuryakin, and M. Suyanto, “Marketing research trends using technology acceptance model (tam): A comprehensive review of researches (2002–2022),” Cogent business & management, vol. 11, no. 1, p. 2329375, 2024.

L. Menant, D. Gilibert, and C. Sauvezon, “The application of acceptance models to human resource information systems: a literature review,” Frontiers in Psychology, vol. 12, p. 659421, 2021.

M. Y.-P. Peng, Y. Xu, and C. Xu, “Enhancing students’ english language learning via m-learning: Integrating technology acceptance model and sor model,” Heliyon, vol. 9, no. 2, 2023.

J. D. Saville and L. L. Foster, “Does technology self-efficacy influence the effect of training presentation mode on training self-efficacy?” Computers in Human Behavior Reports, vol. 4, p. 100124, 2021.

K.-T. Wong, M. Muhammad, and N. Abdullah, “Exploring the drivers of intention to use interactive whiteboards among malaysia university students: Does technology self-efficacy matter?” International Journal of Emerging Technologies in Learning (iJET), vol. 15, no. 1, pp. 163–175, 2020.

A. S. Al-Adwan, N. Li, A. Al-Adwan, G. A. Abbasi, N. A. Albelbisi, and A. Habibi, “Extending the technology acceptance model (tam) to predict university students’ intentions to use metaverse-based learning platforms,” Education and Information Technologies, vol. 28, no. 11, pp. 15 381–15 413, 2023.

J. Yoon, N. S. Vonortas, and S. Han, “Do-it-yourself laboratories and attitude toward use: The effects of self-efficacy and the perception of security and privacy,” Technological Forecasting and Social Change, vol. 159, p. 120192, 2020.

J. Chahal and N. Rani, “Exploring the acceptance for e-learning among higher education students in india: combining technology acceptance model with external variables,” Journal of Computing in Higher Education, vol. 34, no. 3, pp. 844–867, 2022.

A. Alsyouf, A. Lutfi, N. Alsubahi, F. N. Alhazmi, K. Al-Mugheed, R. J. Anshasi, N. I. Alharbi, and M. Albugami, “The use of a technology acceptance model (tam) to predict patients’ usage of a personal health record system: the role of security, privacy, and usability,” International journal of environmental research and public health, vol. 20, no. 2, p. 1347, 2023.

D. L. Kasilingam, “Understanding the attitude and intention to use smartphone chatbots for shopping,” Technology in society, vol. 62, p. 101280, 2020.

M. Divianjella, I. Muslichah, Z. H. A. Ariff et al., “Do religiosity and knowledge affect the attitude and intention to use halal cosmetic products? evidence from indonesia,” Asian Journal of Islamic Management (AJIM), pp. 71–81, 2020.

S. Rezaei, M. Amin, and H. Herjanto, “Pay-per-click (ppc) advertising and continuous banking service intentions,” Journal of Financial Services Marketing, pp. 1–17, 2024.

A. Alzahrani et al., “An analysis of the technology acceptance model tam in understanding faculty’s behavioral intention to use internet of things iot,” IJERI: International Journal of Educational Research and Innovation, no. 19, pp. 153–169, 2023.

Y. Tang and H. Tseng, “Exploring academic librarians’ perception of oer through the lens of technology acceptance model,” The Journal of Academic Librarianship, vol. 49, no. 5, p. 102769, 2023.

K. Tolani, R. Sao, P. Bhadade, and S. Chandak, “Money and generations: Financial choices made by gen x and gen y,” International Journal of Management (IJM), vol. 11, no. 4, pp. 657–672, 2020.

X. Pan, “Technology acceptance, technological self-efficacy, and attitude toward technology-based self-directed learning: learning motivation as a mediator,” Frontiers in Psychology, vol. 11, p. 564294, 2020.

Q. Ali, S. Parveen, H. Yaacob, and Z. Zaini, “Cardless banking system in malaysia: An extended tam,” Risks, vol. 9, no. 2, p. 41, 2021.

M. Sarstedt, C. M. Ringle, and J. F. Hair, “Partial least squares structural equation modeling,” in Handbook of market research. Springer, 2021, pp. 587–632.

Y. T. Prasetyo, E. M. Calino, M. N. Young, I. D. Ayuwati, and S. F. Persada, “Determining factors affecting mobile banking loyalty in the philippines: Integrating extended technology acceptance model and delone & mclean is success model,” in Proceedings of the 7th International Conference on Education and Multimedia Technology, 2023, pp. 403–409.

C. Calvo-Porral and R. Pesqueira-Sanchez, “Generational differences in technology behaviour: comparing millennials and generation x,” Kybernetes, vol. 49, no. 11, pp. 2755–2772, 2020.

Downloads

Published

2024-12-03

How to Cite

Saputra, D. E. E., Susita, D., Eliyana, A., Pratama, A. S., Muzakki, M. H., & Yazid, Z. (2024). Employees Intentions to Use Performance Management System in Regional Bank: Perspective from Generation-X. Aptisi Transactions on Technopreneurship (ATT), 6(3), 550−561. https://doi.org/10.34306/att.v6i3.445

Issue

Section

Articles