Browse > Article
http://dx.doi.org/10.13106/jafeb.2021.vol8.no2.1079

Factors Determining Intention to Continue Using E-HRM  

NOERMAN, Teuku (Department of Business Administration, Faculty of Administrative Sciences, University of Brawijaya)
ERLANDO, Angga (Department of Economics, Faculty of Economics and Business, University of Airlangga)
RIYANTO, Feri Dwi (Department of Management, Faculty of Economics, Maulana Malik Ibrahim Islamic State University)
Publication Information
The Journal of Asian Finance, Economics and Business / v.8, no.2, 2021 , pp. 1079-1089 More about this Journal
Abstract
The development of information technology has promoted organizational transformation through the utilization of an electronic information system. This research aimed to identify factors that influence continuous intention to use E-HRM. This empirical research applies the Technology Acceptance Model and Cognitive Model for identifying significantly impacted areas of continuous intention to use E-HRM in a highly dynamic environment. The data were collected using questionnaires delivered directly to respondents. The sample was 100 employees of ESQ Group selected through random sampling. The variables used were subjective norms (X1), perceived behavioral control (X2), perceived innovativeness (Y1), cognitive absorption (Y2), satisfaction (Y3), and continuous intention to use E-HRM (Y4). Statistical analysis using Structural Equation Modelling (SEM) with Smart PLS was applied. The results revealed that behavioral control (X2) did not influence the continuous intention to use E-HRM (Y4) and that cognitive absorption (Y2) and satisfaction (Y3) did not significantly influence continuous intention to use E-HRM (Y4). Subjective norms (X1) significantly influenced both perceived innovativeness (Y1) and continuous intention to use E-HRM (Y4), perceived behavioral control (X2) significantly influenced both perceived innovativeness (Y1) and cognitive absorption (Y2), and perceived innovativeness (Y1) significantly influenced both satisfaction (Y3) and continuous intention to use E-HRM (Y4).
Keywords
E-HRM; Perceived Innovativeness; Cognitive Absorption; Satisfaction; Continuous Intention;
Citations & Related Records
연도 인용수 순위
  • Reference
1 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. https://doi.org/10.1016/j.jsis.2012.09.001   DOI
2 McNeish, J. (2015). Consumer trust and distrust: retaining paper bills in online banking. International Journal of Bank Marketing, 33(1), 5-22. https://doi.org/10.1108/IJBM-08-2013-0088   DOI
3 Ntiamoah, E. B., Li, D., & Sarpong, D. B. (2019). The effect of innovation practices on agribusiness performance: A structural equation modelling (SEM) approach. African Journal of Science, Technology, Innovation and Development, 11(6), 671-681. https://doi.org/10.1080/20421338.2019.1573958   DOI
4 Nurlina, N., Situmorang, J., Muhammad, A. K. O. B., Quilim, C. A., & Arfah, A. (2020). Influence of e-HRM and human resources service quality on employee performance. The Journal of Asian Finance, Economics and Business, 7(10), 391-399. https://doi.org/10.13106/jafeb.2020.vol7.no10.391   DOI
5 Olivas-lujan, miguel R., jacobo Ramirez, & Laura Zapata-cantu (2007). (e-HRM) in Mexico: adapting innovations for global competitiveness. International Journal of Manpower, 28(5), 418-434. https://doi.org/10.1108/01437720710778402   DOI
6 Oliver, R. L. (1980). A Cognitive Model for the Antecedents and Consequences of Satisfaction. Journal of Marketing Research, 17(4), 460-469. https://doi.org/10.2307/3150499   DOI
7 Oliver, R. L. (1993). Cognitive, affective, and attribute bases of the satisfaction response. Journal of Consumer Research, 20(3), 418-430. https://doi.org/10.1086/209358   DOI
8 Omran, K., & Anan, N. (2018). Studying the impact of using E-HRM on the effectiveness of HRM practices: An exploratory study for the internet service providers (ISP) in Egypt. International Journal of Academic Research in Business and Social Sciences, 8(4). https://doi.org/10.6007/ijarbss/v8-i4/4026   DOI
9 Peterman, N. E., & Kennedy, J. (2003). Enterprise education: Influencing students' perceptions of entrepreneurship. Entrepreneurship Theory and Practice, 28(2), 129-144. http://dx.doi.org/10.1046/j.1540-6520.2003.00035.x   DOI
10 Poba-Nzaou, P., Uwizeyemunugu, S., Gaha, khadija, & Laberge, M. (2020). Taxonomy of business value underlying motivations for e-HRM adoption. Business Process Management Journal, 26(6), 1661-1685. https://doi.org/10.1108/bpmj-06-2018-0150   DOI
11 Ha, Y. W., & Park, M. C. (2013). Antecedents of customer satisfaction and customer loyalty for emerging devices in the initial market of Korea: An equity framework. Psychology & Marketing, 30(8), 676-689. https://doi.org/10.1002/mar.20637   DOI
12 Haerani, S., Sumardi, Hakim, W., Hartini, & Putra, A. H. P. K. (2020). Structural Model of Developing Human Resources Performance: Empirical Study of Indonesia States Owned Enterprises. Journal of Asian Finance, Economics and Business, 7(3), 211-221. https://doi.org/10.13106/JAFEB.2020.VOL7.NO3.211   DOI
13 Hair, J.F., W.C. Black, B.J. Babin, & R.E. Anderson. (2010). Multivariate Data Analysis. Upper Saddle River, NJ: Prentice-Hall.
14 Holm, A. B. (2020). Virtual HRM and Virtual Organizing. Encyclopedia of Electronic HRM, 95. https://doi.org/10.1515/9783110633702   DOI
15 Ketokivi, M. (2019). Avoiding bias and fallacy in survey research: A behavioral multilevel approach. Journal of Operations Management, 65(4), 380-402. https://doi.org/10.1002/joom.1011   DOI
16 Hongdiyanto, C., Teofilus, T., Sutrisno, T. F., & Dewanti, P. S. P. (2020). The Effect of Entrepreneurial Learning towards Entrepreneurial Intention of Indonesian Women. The Journal of Asian Finance, Economics, and Business, 7(9), 573-582. https://doi.org/10.13106/jafeb.2020.vol7.no9.573   DOI
17 Hsu, M. H., & Chiu, C. M. (2004). Predicting electronic service continuance with a decomposed theory of planned behaviour. Behaviour & Information Technology, 23(5), 359-373. https://doi.org/10.1080/01449290410001669969   DOI
18 Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 183-213. https://doi.org/10.2307/249751   DOI
19 Knauer, T., Nikiforow, N., & Wagener, S. (2020). Determinants of information system quality and data quality in management accounting. Journal of Management Control, 1-25. https://doi.org/10.1007/s00187-020-00296-y   DOI
20 Kolvereid, L., Iakovleva, T., & Kickul, J. (2006). An integrated model of entrepreneurial intentions. Frontiers of Entrepreneurship Research, 26(8). https://doi.org/10.1504/IJBG.2009.021632   DOI
21 Lee, J. W., & Xuan, Y. (2019). Effects of Technology and Innovation Management and Total Factor Productivity on the Economic Growth of China. Journal of Asian Finance, Economics and Business, 6(2), 63-73. https://doi.org/10.13106/jafeb.2019.vol6.no2.63   DOI
22 Barnes, S. J., Pressey, A. D., & Scornavacca, E. (2019). Mobile ubiquity: Understanding the relationship between cognitive absorption, smartphone addiction and social network services. Computers in Human Behavior, 90, 246-258. https://doi.org/10.1016/j.chb.2018.09.013   DOI
23 Ghasemaghaei, M. (2020). The impact of in-depth online recommendation agents on consumer disorientation and cognitive absorption perceptions. Behaviour & Information Technology, 39(4), 414-430. https://doi.org/10.1080/0144929X.2019.1598496   DOI
24 Grant, D., & Newell, S. (2013). Realizing the strategic potential of e-HRM. The Journal of Strategic Information Systems, 22(3), 187-192. https://doi.org/10.1016/j.jsis.2013.07.001   DOI
25 Alaloul, W. S., Liew, M. S., Zawawi, N. A. W., Mohammed, B. S., Adamu, M., Musharat, M. A., & Latour, M. (2020). Structural equation modelling of construction project performance based on coordination factors. Cogent Engineering, 7(1), 1726069. https://doi.org/10.1080/23311916.2020.1726069   DOI
26 Alzhrani, A. M. (2020). The Use of Management Information System to Help Decision Making in Digital Firms. International Journal of Business and Management Future, 4(1), 21-26. https://doi.org/10.46281/ijbmf.v4i1.491   DOI
27 Armitage, C. J., & Conner, M. (2001). Efficacy of the theory of planned behaviour: A metaanalytic review. British Journal of Social Psychology, 40(4), 471-499. https://doi.org/10.1348/014466601164939   DOI
28 Ajzen, I. (2002). Perceived behavioral control, self‐efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 32(4), 665-683. https://doi.org/10.1111/j.1559-1816.2002.tb00236.x   DOI
29 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   DOI
30 Bhattacherjee, A. (2001). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, 25(3), 351-370. https://doi.org/10.2307/3250921   DOI
31 Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: Atheoretical model and longitudinal test. MIS Quarterly, 229-254. https://doi.org/10.2307/25148634   DOI
32 Bondarouk, T., Ruël, H., & van der Heijden, B. (2009). e-HRM effectiveness in a public sector organization: a multistakeholder perspective. The International Journal of Human Resource Management, 20(3), 578-590. https://doi.org/10.1080/09585190802707359   DOI
33 Gardner, S. D., Lepak, D. P., & Bartol, K. M. (2003). Virtual HR: The impact of information technology on the human resource professional. Journal of Vocational Behavior, 63(2), 159-179. https://doi.org/10.1016/S0001-8791(03)00039-3   DOI
34 Cheung, M. W. L., & Chan, W. (2005). Meta-analytic structural equation modeling: a two-stage approach. Psychological methods, 10(1), 40. https://doi.org/10.1037/1082-989X.10.1.40   DOI
35 Chulanova, Z. K., Satybaldin, A. A., & Koshanov, A. K. (2019). Methodology for Assessing the State of Human Capital in the Context of Innovative Development of the Economy: A ThreeLevel Approach. Journal of Asian Finance, Economics and Business, 6(1), 321-28. https://doi.org/10.13106/jafeb.2019.vol6.no1.321   DOI
36 Galanaki, E., Lazazzara, A., & Parry, E. (2019). A cross-national analysis of e-HRM configurations: integrating the information technology and HRM perspectives. In Organizing for Digital Innovation (pp. 261-276). Springer, Cham. https://doi.org/10.1007/978-3-319-90500-6_20   DOI
37 Venkatesh, V., Thong, J. Y., Chan, F. K., Hu, P. J. H., & Brown, S. A. (2011). Extending the two‐stage information systems continuance model: Incorporating UTAUT predictors and the role of context. Information Systems Journal, 21(6), 527-555. https://doi.org/10.1111/j.1365-2575.2011.00373.x   DOI
38 Umar, T. R., Yammama, B. A., & Shaibu, R. O. (2020). The Implications of Adopting and Implementing Electronic Human Resource Management Practices on Job Performance. Journal of Human Resource Management, 8(2), 96-108. https://doi.org/10.11648/j.jhrm.201200802.17   DOI
39 Wong, S. C., Lim, J. Y., Lim, C. S., & Hong, K. T. (2019). An Empirical Study on Career Choices Among Undergraduates: A PLS-SEM Hierarchical Component Model (HCM) Approach. International Journal of Human Resource Studies, 9(2), 276-298. https://doi.org/10.5296/ijhrs.v9i2.14841   DOI
40 Ruël, H. J. M., Bondarouk, T. V., & Van der Velde, M. (2007). The contribution of e‐HRM to HRM effectiveness. Employee Relations, 29(3), 280-291. https://doi.org/10.1108/01425450710741757   DOI
41 Saade, R., & Bahli, B. (2005). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: an extension of the technology acceptance model. Information & Management, 42(2), 317-327. https://doi.org/10.1016/j.im.2003.12.013   DOI
42 Sarstedt, M., & Cheah, J. H. (2019). Partial least squares structural equation modeling using SmartPLS: a software review. Journal of Marketing Analytics, 7(3), 196-202. https://doi.org/10.1057/s41270-019-00058-3   DOI
43 Schalk, R., Timmerman, V., & Van den Heuvel, S. (2013). How strategic considerations influence decision making on e-HRM applications. Human Resource Management Review, 23(1), 84- 92. https://doi.org/10.1016/j.hrmr.2012.06.008   DOI
44 Sekaran, U. (2003). Research Methods for Business: A SkillBuilding Approach. Fourth Edition, John Willey & Sons, Inc, New York.
45 Shilpa, V., & Gopal, R. (2011). The implications of implementing electronic-human resource management (e-HRM) systems in companies. Journal of Information Systems and Communication, 2(1), 10.
46 Strohmeier, S., & Kabst, R. (2009). Organizational Adopting of e-HRM in Europe. Journal of Man- agerial Psychology, 24(6), 482-501. https://doi.org/10.1108/02683940910974099   DOI
47 Sumaryati, A., Novitasari, E. P., & Machmuddah, Z. (2020). Accounting Information System, Internal Control System, Human Resource Competency and Quality of Local Government Financial Statements in Indonesia. The Journal of Asian Finance, Economics and Business, 7(10), 795-802. https://doi.org/10.13106/jafeb.2020.vol7.no12.809   DOI
48 Veciana, J. M., Aponte, M., & Urbano, D. (2005). University students' attitudes towards entrepreneurship: A two countries comparison. The International Entrepreneurship and Management Journal, 1(2), 165-182. https://doi.org/10.1007/s11365-005-1127-5   DOI
49 Swar, B., Hameed, T., & Reychav, I. (2017). Information overload, psychological ill-being, and behavioral intention to continue online healthcare information search. Computers in Human Behavior, 70, 416-425. https://doi.org/10.1016/j.chb.2016.12.068   DOI
50 Tominc, P. (2019). Perceived Innovativeness and Competitiveness of Early-Stage Entrepreneurs. Croatian Economic Survey, 21(1), 87-108. https://doi.org/10.15179/ces.21.1.3   DOI
51 Raymaekers, J., & Rousseeuw, P. J. (2019). Fast robust correlation for high-dimensional data. Technometrics, 1-15. https://doi.org/10.1080/00401706.2019.1677270   DOI
52 Reina, R., & Scarozza, D. (2020). Human Resource Management in the Public Administration. Organizational Development in Public Administration, 61-101. https://doi.org/10.1007/978-3-030-43799-2_3   DOI
53 Lin, L. H. (2011). Electronic human resource management and organizational innovation: the roles of information technology and virtual organizational structure. The International Journal of Human Resource Management, 22(02), 235-257. https://doi.org/10.1080/09585192.2011.540149   DOI
54 Luc, P. T. (2018). The relationship between perceived access to finance and social entrepreneurship intentions among university students in Vietnam. The Journal of Asian Finance, Economics and Business, 5(1), 63-72. https://doi.org/10.13106/jafeb.2018.vol5.no1.63   DOI