Journal Press India^®

Author Details ( * ) denotes Corresponding author

Purpose: The purpose of this paper is to review and reconcile the enablers affecting effective implementation of EHRM. Further, this paper also aims at formulating a comprehensive model describing the interplay of enablers of effective EHRM (EHRMEs), with the help of ISM methodology

Methodology: Experts from industries and academics were referred in order to design ISM, which explains the contextual relationship among various enablers of effective E-HRM. The result of ISM was futher used for MICMAC analysis in order to determine driving, linkage, dependent variables.

Findings: This paper has identified 18 key enablers of E-HRM (EHRMEs) which facilitate the efficacy of E-HRM practices in an organisation. The authors have additionally established relationships between all identified EHRMEs utilizing Interpretive Structural Modelling methodology. This is an attempt to examine the E-HRM enablers by utilizing MICMAC analysis.

Research Limitations: The weightage allotted in ISM Methodology is solely dependent on the judgment of the academicians and industry experts. Thus empirical research is to be conducted to verify the proposed relationship. Practical Implications: This study would help the academicians and the managers to have the broader picture of various enablers of EHRM.

Originality/Value: The results would help the HR managers to effectively managevarious enablers of EHRMs, especially during the implementation of digital HR practices in the organisation.

Keywords

ISM, Digital HR Practices, MICMAC, Enablers of E-HRM

1. Agarwal, A., Shankar, R., & Tiwari, M. K. (2007). Modeling Agility of Supply Chain. Industrial Marketing Management 36(4), 443-457.
2. Agarwal, R., & Prasad, J. (1997). The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decision Sciences, 28(3), 557-582.
3. Alleyn, C., Kakbadse, A., & Kakbadse, N. (2007). Using the Hr Intranet: An exploratory analysis of its impact on managerial satisfaction with the HR function. Personnel Review, 36(2), 295-310.
4. Amoroso, D. L., & Cheney, P. H. (1991). Testing a causal model of end-user application effectiveness. Journal of MIS, 8(1), 63-89.
5. Belardo, S., & Kavanagh, M. J. (2012). Human resource information systems project management, in Kavanagh, M. J., Thite, M., & Johnson, R. D. (Eds), Human Resource Information Systems: Basics, Applications and Future Directions, 2nd eds, Sage Publications Ltd, Thousand Oaks, CA, 210-233.
6. Bondarouk, T. V., & Looise, J. K. (2009). A contingency perspective on the implementation of e-performance management, in Torres-Coronas, T. and Arias-Oliva, M. (Eds), Encyclopedia of HRIS: Challenges in e-HRM, Information Science Reference, Hershey, New York, NY, 197-202.
7. Burbach, R. (2011). The diffusion of global human resource information technology in the subsidiaries in of a US multinational corporation. National University of Ireland, Galway. Retrieved from file: ///C:/Users/User/Downloads/2012burbachphd.pdf, Accessed on June 10, 2018.
8. Burbach, R., & Dundon, T. (2005). The strategic potential of human resource information systems: evidence from the republic of Ireland. International Employment Relations Review, 11(1-2), 97-118.
9. Cakmak, A. F., Benk, S., & Budak, T. (2011). The Acceptance of tax office automation system (VEDOP) by employees: Factorial validation of Turkish adapted Technology Acceptance Model (TAM). International Journal of Economics and Finance, 3(6), 107-116.
10. Chaudhary, J., & Sindhu, S. (2015). Modelling the enablers of innovative leadership: An ISM approach. International Journal of Innovations in Engineering and Management, 4(1), 65-74.
11. Chien, S. W., & Tsaur, S. M. (2007). Investigating the success of ERP systems: Case studies in three Taiwanese high-tech industries. Computers in Industry, 58(8), 783-793.
12. David, W. M. (1975). An introduction to the application of interpretive structural modeling ISM. Proceedings of the IEEE 63(3), 397-404.
13. 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. 
14. 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.
15. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
16. Garaèa, Z. (2011). Factors related to the intended use of ERP systems. Management- Journal of Contemporary Management Issues, 16(2), 23-42. 
17. Gupta, N., & Singh, A. K. (2013). An empirical analysis of key components of measurement of human asset. Delhi Business Review,14(2), 34-55.
18. Haines, V. Y., & Lafleur, G. (2008). Information technology usage and human resource roles and effectiveness. Human Resource Management, 47(3), 525-540.
19. Heikkila¨, J. P., & Smale, A. (2011). The effects of ‘language standardization’ on the acceptance and use of e-HRM systems in foreign subsidiaries. Journal of World Business, 46(3), 305-313.
20. Hsieh, J., & Liao, P. (2011). Antecedents and moderators of online shopping behavior in undergraduate students. Social Behavior and Personality: An international Journal, 39(9), 1271-1280.
21. 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.
22. Laumer, S., Eckhardt, A., & Weitzel, T. (2010). Electronic human resources management in an e-business environment. Journal of Electronic Commerce Research, 11(4), 240-250.
23. Leng, G., Lada, S., Muhammad, M. Z., Ibrahim, A. A. H. A., & Amboala, T. (2011). Journal of Internet Banking and Commerce, 16(2), 1-27.
24. Lippert, S. K., & Swiercz, P. (2005). Human resource information systems (HRIS) and technology trust. Journal of Information Science, 31(5), 340-353.
25. Mahmood, M. A., Burn, J. M., Gemoets, L. A., & Jacquez, C. (2000). Variables affecting information technology end-user satisfaction: A meta-analysis of the empirical literature. International Journal of Human-Computer Studies, 52(4), 751-771.
26. Marler, J. H., Fisher, S., & Ke, W. (2009). Employee self-service technology acceptance: A comparison of pre-implementation and post-implementation relationships. Personnel Psychology, 62(2), 327-341.
27. Marler, J. H., Liang, X., & Dulebohn, J. H. (2006). The effect of technology training on technology acceptance. Journal of Management, 32(6), 721-742.
28. Masum, A. K. M., Bhuiyan, F., & Kabir, R. (2013). HRIS Practices in Universities: An Exploratory Study on the Private Universities in Bangladesh. Global Journal of Human-Social Science Research, 13(7), 25-29.
29. Mohapatra, S. (2012). Unique HR practices in the Indian IT industry: A research agenda. Delhi Business Review, 13(1), 50-65.
30. Ngai, E.W.T., Law, C. C. H., & Wat, F. K. T. (2008). Examining the critical success factors in the adoption of enterprise resource planning. Computers in Industry, 59(6), 548-564.
31. Rodríguez, J. M., & Ventura, J. (2003). Human resource management systems and organizational performance: An analysis of the Spanish manufacturing industry. International Journal of Human Resource Management, 14(7), 1206-1226.
32. Ruël, H. J. M., Bondarouk, T. V., & Van der Velde, M. (2007). The contribution of E-HRM to HRM effectiveness. Human Relations, 29(3), 280-291.
33. Sachdeva, S., & Singh, A. K. (2017). Interpersonal behaviour - Significance and training and development programme assessment. Training & Development Journal, 8(2), 95-102.
34. Sage, A. P., & Smith, T. J. (1977). On group assessment of utility and worth attributes using interpretive structural modelling. Computer & Electrical Engineering, 4(3), 185-198.
35. Seddon, K. R. (1997). Ionic liquids for clean technology. Journal of Chemical Technology and Biotechnology, 68(4), 351-356.
36. Sheu, C., Chae, B., & Yang, C. L. (2004). National differences and ERP implementation: Issues and challenges. Omega, 32(5), 361-371.
37. Singh, A. K. (2013). HRM practices and managerial effectiveness in Indian business organisations. Delhi Business Review, 14(1), 79-90.
38. Sinha, S., Singh, A. K., Gupta, N., & Dutt, R. (2010). Impact of work culture on motivation and performance level of employees in private sector companies. Acta Oeconomica Pragensia, 18(6), 49-67.
39. Stone, R. A. (2012). Change management: Implementation, integration, and maintenance of the HRIS, in Kavanagh, M. J., Thite, M., & Johnson, R. D. (Eds), Human Resource Information Systems: Basics, Applications and Future Directions, 2nd ed., Sage Publications Ltd, Thousand Oaks, CA, 236-276.
40. Teo, T. S. H., Lim, G. S., & Fedric, S. A. (2007). The adoption and diffusion of human resources information systems in Singapore. Asia Pacific Journal of Human Resources, 45(1), 44-62.
41. Udo, G. J., & Bagchi, K. K. (2011). Understanding the influence of espoused culture onacceptance of online services in a developing country. Journal of Information Technology and Theory, 12(2), 25-46.
42. Voermans, M., & Veldhoven, M. V. (2007). Attitude towards E HRM: An empirical study at Philips. Personnel Review, 36(6), 887-902.
43. Yoon, C. (2009). The effects of organizational citizenship behaviors on ERP system success. Computers in Human Behavior, 25(2), 421-428.
44. Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality. Journal of Marketing, 60(2), 31-46.
45. Zhang, X., & Prybutok, V. R. (2005). A consumer perspective of E-service quality.
46. Zhu, Y., Li, Y.,Wang, W., & Chen, J. (2010). What leads to post-implementation success of ERP? An empirical study of the Chinese retail industry. International Journal of Information Management, 30(3), 265-276.