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The Implications of Adopting and Implementing Electronic Human Resource Management Practices on Job Performance

Received: 8 March 2020    Accepted: 24 March 2020    Published: 23 April 2020
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Abstract

Past literature supports positive links between electronic human resource management practices (E-HRM), and job performance. However, poor application of e-HRM practices in the Nigerian public sector resulted in poor job performance and unwholesome ethical practices. As a result, calls for further research have been suggested, particularly on the direct process through which the adoption and implementation of e-HRM practices such e-communication; e-compensation, e-training and e-performance appraisal are likely to influence job performance. Hence, the purpose of this research is to investigate the relationship between electronic Human resource Management (E-HRM) practices and job performance (i.e. task, contextual, adaptive performance, and counterproductive work behaviour at the individual level. We employed a quantitative approach with survey from 214 academic and non academic staff in five higher institutions in Northern part of Nigeria. Using partial least square structural equation modelling (PLS-SEM), the quantitative results indicated that some of the components of E-HRM practices were positively associated with job performance. For instance, both e-communication, and e-compensation were significantly and positively related to all the dimensions of job performance (i.e. task, contextual, adaptive, and counterproductive work behaviour. Also, e-training was found to be positively related to task and adaptive performance only. Similarly, results showed that e-performance appraisal practice was only related to contextual performance and counterproductive work behaviour. On the contrary, e-training practice demonstrated no significant effect on contextual performance and counterproductive work behaviour. Similarly, no significant direct effect was found between e-performance appraisal and task and adaptive performance. Implications of the findings for future research and practice, as well as the limitations of the study are highlighted.

Published in Journal of Human Resource Management (Volume 8, Issue 2)
DOI 10.11648/j.jhrm.201200802.17
Page(s) 96-108
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Job Performance, E-Hrm, E-Training, E-communication, E-compensation, E-performance Appraisal

References
[1] Ho, V. T., Wong, S., & Lee, C. H. (2011), A Tale of Passion: Linking Job Passion and Cognitive Engagement to Employee Work Performance: A Tale of Passion. Journal of Management Studies 48 (1): 26-47. DOI: 10.1111/j.1467-6486.2009.00878.x.
[2] Stone, D. L., Deadrick, D. L., Lukaszewski, K. M., & Johnson, R. (2015). The influence of technology on the future of human resource management. Human Resource Management Review, 25.
[3] Catano, V. M., Wiesner, W. H., Hackett, R. D., & Methot, L. L. (2009). Recruitment and Selection in Canada. New York: Cengage Learning Inc.
[4] Koopmans, L., Bernaards, C. M., Hildebrandt, V. H., Schaufeli, W. B., De Vet, H. C. W. & Van der Beek, A. J. (2011), “Conceptual frameworks of individual work performance–a systematic review”, Journal of Occupational and Environmental Medicine, l 53 (8), 856-66.
[5] Manu, J. S. (2004). Training and Development Techniques for Improving Organizational Performance for Ghanian Firms. United States: University of Wisconsin Stout Menomonie, WI 54751.
[6] Niazi, A. S. (2011). Training and Development Strategy and Its Role in Organizational Performance. Journal of Public Administration and Governance 1, 2.
[7] Decramer, A., Christiaens, J., & Vanderstraeten, A. (2008). Implementation Dynamics of Performance Management in Higher Education. 21st EIASM Workshop on Strategic Human Resource Management. Ghent, Belgium: University College Ghent, Voskenslaan 270, 9000.
[8] Pearce, J. L., & Randel, A. E. (2004). Expectations of organizational mobility, workplace social inclusion, and employee job performance. Journal of Organizational Behavior, 25 (1), 81–98. doi.org/10.1002/job.232\.
[9] Schreurs, B. H. J., Van Emmerik, I. H., Guenter, H., & Germeys, F. A weekly diary study on the buffering role of social support in the relationship between job insecurity and employee performance. Human Resource Management 51 (2): 259-279. DOI: 10.1002/hrm.21465.
[10] Sony, M., & Mekoth. (2016). The relationship between emotional intelligence, frontline employee adaptability, job satisfaction and job performance. Journal of Retailing and Consumer Services 30: 20-32. DOI: 10.1016/j.jr.
[11] Han, Y. (2007). The research about influence of organizational commitment on employees work performance, At Zhong nan university of economics and law journal, 03, 56.
[12] Ma, L., Xing, Y., Wang, Y., & Chen, H. T. (, 2013). Research on the Relationship among Enterprise Employee's Job Satisfaction, Organizational Commitment and Job Performance. Applied Mechanics and Materials, 411 (414), 2477-2480.
[13] Robertson, I. T., Birch, A. J. & Cooper, C. L. (2012) Job and Work Attitudes, Engagement and Employee Performance: Where Does Psychological Well-Being Fit in? Leadership & Organization Development Journal, 33, 224-232. doi: 10.1108/01437731211216443.
[14] Dalal, R. S., Baysinger, M., Brummel, B. J., & LeBreton, J. M. (2012). The relative importance of employee engagement, other job attitudes, and trait affect as predictors of job performance. Journal of Applied Social Psychology, 42 (1), 295–325. doi.org/10.1111/j.1559-1816.2012.01017.x.
[15] Borman, W. C. & Motowidlo, S. J. (1993), “Expanding the criterion domain to include elements of contextual performance”, in Schmitt, N. and Borman, W. C. (Eds), Personnel Selection in Organizations, Jossey Bass, San Francisco, CA, pp. 71-9822] Ebenebe, C. I., Anigbogu, C. C., Anizoba, M. A. and Ufele.
[16] Murphy, K. R. (1989). Dimensions of job performance. Teting: Applied and Theoretic Perspective, 218-247. New York: Praeger.
[17] Tsui, A., Pearce, J., Porter, L., & Tripoli, A. (1997). Alternative approaches to the employee-organization relationship: does investment in employees pay off? Academy of Management Journal, 40 (5), 1089-1121.
[18] Demortier, A.-L., Delobbe, N., & El Akremi, A. (2014). Opening the black box of hr practices - performance relationship: Testing a three pathways AMO model. Academy of Management Annual Meeting Proceedings, 1201-1206. doi: 10.5465/AMBPP.2014.102.
[19] Straub, Rai, & Klein, R. 2004. “Measuring Firm Performance at the Network Level: A Nomology of the Impact of Digital Supply Networks,” Journal of Management Information Systems, 21 (1) 83-114.
[20] Wareham, J., Mathiassen, L., Rai, A., Straub, D., & Klein, R. (2005). “The Business Value of Digital Supply Networks: A Program of Research on the Impacts of Globalization,” Journal of International Management, 11 (2), 201-227.
[21] Bondarouk, T. & Brewster, C. (2016). Conceptualising the future of HRM and technology research, The International Journal of Human Resource Management, 27 (21), 2652-2671: DOI: 10.1080/09585192.2016.1232296.
[22] Bondarouk, T. Harms, R. & Lepak, D. (2015) Does e-HRM lead to better HRM service? The International Journal of Human Resource Management, DOI: 10.1080/09585192.2015.1118139, 4 (3).
[23] Bondarouk, T., Parry, E, & Furtmueller, E. (2017). Electronic HRM: four decades of research on adoption and consequences, The International Journal of Human Resource Management, 1-34.
[24] Ulrich, D. & Dulebohn, J (2015). Are we there yet? What’s next for HR? Journal of Human Resource Management Review. 25 (2), 178-186.
[25] Stone, D. L., & Dulebohn, J. H. (2013). Emerging issues in theory and research on electronic human resource management (e-HRM). Human Resource Management Review, 23 (1), 1-5.
[26] Masum, A. K. M (2015) Adoption Factors of Electronic Human Resource Management (e-HRM) in Banking Industry of Bangladesh. Journal of Social Sciences, 11 (1), 1-6.
[27] Yusoff, Y. M., Ramayah, T., & Othman, N. (2015). "Why Examining Adoption Factors, HR Role and Attitude towards Using E-HRM is the Start-Off in Determining the Successfulness of Green HRM?," Journal of Advanced Management Science, 3 (4), 337-343.
[28] Dialoke I. & Goddey C. (2017). Electronic human resource management and ghost workers syndrome in Nigeria: A study of selected LGAs in IMO state, Advance Research Journal of Multidisciplinary Discoveries, 10 (2017): 52-57.
[29] Obasanjo, O. (2003). Presidential speech at the inauguration ceremony of the new members of the national assembly, on 5th june, 2003. Abuja, Nigeria.
[30] Suleiman, W. (2013). A Study of Causes of Poor Attitude to Work among workers of both Public and Private Sectors Organizations in Bauchi State-Nigeria. International Journal of Academic Research in Business and Social Sciences, 3 (7), 143-152.
[31] Koopmans, L., Bernaards, C. M., Hildebrandt, V. H., Schaufeli, W. B., De Vet, H. C. W. & Van der Beek, A. J., (2012)"Development of an individual work performance questionnaire", International Journal of Productivity and Performance Management, 62 (1), 6–28.
[32] Inyang, B. J., & Akaegbu, J. B. (2014). Redefining the Role of the Human Resource Professional (HRP) in the Nigerian Public Service for Enhanced Performance. International Journal of Business Administration, 5 (1), 90-98.
[33] Duarte, P. A. O., & Raposo, M. L. B. (2010). A PLS model to study brand preference: An application to the mobile phone market. In V. Esposito Vinzi, W. W. Chin, J. Henseler & H. Wang (Eds). In Handbook of Partial Least Squares: Concepts, methods and applications (pp. 449–485).). Berlin: Springer.
[34] Rotundo, M. & Sackett, P. R. (2002), “The relative importance of task, citizenship, and counterproductive performance to global ratings of performance: a policy-capturing approach”, Journal of Applied Psychology, 87 (1), 66-80.
[35] Jex (1998), Stress and Job Performance: Theory, Research, and Implications for Managerial Practice, Sage Publications, Thousand Oaks, CA.
[36] Chen, C. F. (2014), “The influences of university interns’ job characteristics, work value, and job performance”, Revista de Cercetare si Interventie Sociala, 47 (1), 204-219.
[37] Motowidlo, S. J. (2003). Job performance. In I. B. Weiner (Ed.), Handbook of psychology (Vol. 12). New Jersey: John Wiley & Sons Inc., Hoboken.
[38] Hunt S. T. (1996). Generic work behavior: an investigation into the dimensions of entry-level, hourly job performance. Personnel Psychology. 49: 51–83.
[39] Viswesvaran, C. & Ones, D. S. (2000), “Perspectives on models of job performance”, International Journal of Selection and Assessment, 8 (4), 216-26.
[40] Werner, J. M. (2000), “Implications of OCB and contextual performance for human resource management”, Human Resource Management Review, 10 (1), 3-24.
[41] Maxham J. G. I, Netemeyer, R. G, & Lichtenstein, D. R. (2008) The retail value chain: linking employee perceptions to employee performance, customer evaluations, and store performance. Market Sci. 27, 147–167.
[42] Frese, M., Garst, H., & Fay, D. (2007). Making things happen: Reciprocal relationships between work characteristics and personal initiative in a four-wave longitudinal structural equation model. Journal of Applied Psychology, 92, 1084-1102.
[43] Sonnentag, S., & Frese, M. (2002). Performance concepts and performance theory. Psychological management of individual performance, 23, 3-25.
[44] Bertua, C., Anderson, N., & Salgado, J. F. (2005). The predictive validity of cognitive ability tests: A UK meta-analysis. Journal of Occupational and Organizational Psychology, 78 (3), 387–409. doi.org/10.1348/096317905X26994.
[45] Bhatt, T. (2015), E-HRM review and implications, Journal of Advances in Business Management, 1 (4), 387-389. DOI; 10.14260/jadbm/2015/49.
[46] Strohmeier, S. (2007). ‘Research in e-HRM: Review and implications’. Human Resource Management Review, 17: 19-37.
[47] Marler, J. H., & Fisher, S. L. (2013). An evidence-based review of e-HRM and strategic human resource management. Human Resource Management Review, 23 (1), 18-36.
[48] Withers, M. Williamson, M. and Reddington, M (2010) Transforming HR Creating Value Through People. 2nd edition. London. Elsevier.
[49] Pradhan, S. K. & Chaudhury, S. K. (2012). A survey on Employee Performance Management and its Implication to their Retention in OCL India Ltd. Asian Journal of Research in Social Science & Humanities, 2 (4), 249-262.
[50] Van Scotter, J. R., Motowidlo, S. J. & Cross, T. C. (2000), “Effects of task and contextual performance on systematic rewards”, Journal of Applied Psychology, 85 (4), 526-535.
[51] Wilson, J 2005, Human resource development: learning & training for individuals and organizations, 2nd edn, Kogan Page.
[52] Cunningham, I. (2007). Talent management: Making it real. Development and Learning in Organisations, 21 (2), 4–6.
[53] Pratheepan S, Arulrajah A. (2012). Application of Electronic Human Resource Management (E-HRM) Practices and its Effectiveness in Selected Private Banks in Sri Lanka: An Exploration, the Seventh International Research Conference on Management and Finance, 159- 175.
[54] Mohsin, M., & Sulaiman, R. (2013). A Study on E-Training Adoption for Higher Learning Institutions. International Journal of Asian Social Science. 3 (9), 2006-2018.
[55] Hardman, W. & Robertson, L. (2012). What motivates employees to persist with online training? International Journal of Business Humanities and Technology, 2 (5), 66-78.
[56] Nenwani, P., & Raj, M. (2009). E-HRM Prospective in Present Scenario. International Journal, 1 (7), 2013.
[57] Welsh, E. T., Wanberg, C. R., Brown, K. G., & Simmering, M. J. (2003). E-learning: Emerging uses, empirical results and future directions. International Journal of Training and Development, 7, 245-258.
[58] Ensher, E. A., Nielson, T. R., & Grant-Vallone, E. (2002). Tales from the hiring. line: effects of the internet and technology on HR processes. Org. Dyn. 31 (3), 224–244.
[59] Kamal, K. B., Aghbari, M. A., & Atteia, M. (2016). E-training & employees’ performance a practical study on the ministry of education in the kingdom of Bahrain. Journal of Resources Development and Management. 18.
[60] Hilb, M. (1992). Management development in Western Europe in the 1990’s’ Journal of Human Resource Management, 3 (3): 575-84.
[61] Sambrook, S. (2003). E-learning in small organizations. Education and Training, 45 (8/9), 506.
[62] Gratton-Lavoie & Stanley, (2009) Teaching and Learning Principles of Microeconomics Online: An Empirical Assessment. Journal of Economic Education, 40 (1), 3-25.
[63] Lorenzetti, J. (2013.). Academic Administration - Running a MOOC: Secrets of the World’s Largest Distance Education Classes - Magna Publications.
[64] Ellis, F & Kuznia, K. (2014). Coporate E-Learning Impact on Employees. Global Journal of Business Research, 8 (4), 1-5.
[65] Chen, E. T. (2008) “Successful E-learning in corporations”. Communications of the IIMA, 8 (2), 45-II.
[66] Newton, R., & Doonga, N. (2007). “Corporate e-learning: Justification for implementation and evaluation of benefits. A study examining the views of training managers and training providers”. Education For Information, 25 (2), 111-130.
[67] Nguyen, T, (2015). The Effectiveness of Online Learning: Beyond No Significant Difference and Future Horizons, MERLOT Journal of Online Learning and Teaching, 11 (2), 309-319.
[68] Leković, B., & Berber, N. (2014). The Relationship Between Communication Practice and Organizational Performances in Organizations from Europe. Industrija, 42 (3), 101.
[69] Panayotopoulou, L., Vakola, M., & Galanaki, E. (2007). E‐HR adoption and the role of HRM: Evidence from Greece. Personnel Review, 36, 277–294.
[70] Fındıklı M. A. &, Bayarçelikb, E. B. (2015). Exploring the outcomes of Electronic Human Resource Management (E-HRM)? Social and Behavioral Sciences 207 (2015) 424–431.
[71] Mano R. S & Mesch G. S. (2010). E-mail characteristics, work performance and distress. Computers in Human Behavior 26 (2010) 61–69.
[72] Gartner. (2008). “Gartner Says Emerging Nations Will Make ICT Industry ‘Borderless’ by 2015,” Gartner Group, May 14 (http://www.gartner.com/it/page.jsp?id=669710; accessed November 24, 2008).
[73] Hill, N. S., Kang, J. H., & Seo, M.-G. (2014). The interactive effect of leader–member exchange and electronic communication on employee psychological empowerment and work outcomes. The Leadership Quarterly, 25 (4), 772–783.
[74] Zhang, X. & Venkatesh, V. (2014), Explaining Employee Job Performance: The Role of Online and Offline Workplace Communication Networks, MIS Quarterly 37 (3): 695-722.
[75] Kariznoee, A., Afshani, M., & Moghadam, M. R. H. (2012). To examine the effect of E-HRM on employee’s job performance. Advanced Research in Economic and Management Sciences (AREMS), 6, 275-282.
[76] Dulebohn, J. H., & Marler, J. H. (2005). E-Compensation: The potential to transform practice. In H. G. Gueutal, & D. L. Stone (Eds.), The brave new world of e HR: Human resources management in the digital age (pp. 166–189). San Francisco: Jossey Bass.
[77] Ukandu N. E., Iwu C. G., & Allen-lle C. O. K. (2014). Influence of E-HRM in decision making in selected tertiary institutions in South Africa. Problems and Perspectives in Management, 12 (4), 397-405.
[78] Akter N., & Husain, M. M., (2016). Effect of Compensation on Job Performance: An Empirical Study. International Journal of Engineering Technology, Management and Applied Sciences, 4 (8), 103-116.
[79] Onuorah, A. N., Okeke, M. N., & Ikechukwu, I. A. (2019). Compensation Management and Employee Performance in Nigeria. International Journal of Academic Research in Business and Socal Sciences, 9 (2), 384–398.
[80] Adewale O. O., Adenike A. A., Hezekiah O. F., & Heirsmac T. (2014). Compensation packages: a strategic tool for employees’ performance and retention. Leonardo Journal of Sciences, 25, 65-84.
[81] Piggot-Irvine E., (2003). Appraisal Training Focused on What Really Matters. International Journal of Educational Management, 17 (6), 254-261. DOI: 10.1108/09513540310487587.
[82] Johnson, R. D.& Gueutal, H. G.(2011). Transforming HR through technology: the use of hER and human resource information systems in organizations. Alexandria, VA: SHRM Effective Practice Guidelines Series.
[83] Summer, L. (2001). Web technologies for administering multisource feedback programs: In D Bracken, C. W. Timmreck & A. H Church (Eds). The handbook of multisource feedback (pp. 6165-180) San Francisco: Jossey-Bass.
[84] Kavanagh, M. J., Thite, M.& Johnson, R. D. (Eds.). (2015). Human resource information systems: basics, applications and future directions. 3rd Edition. Thousand Oaks, CA: Sage.
[85] Morgenson, F. P., Mumford, T. V., & Campion, M. A. (2005). Coming full circle: Using research and practice to address 27 questions about 360-degree feedback programs. Consulting Psychology Journal, 57, 196-209.
[86] Jarrar, Y., & Schiuma, G. (2007). Measuring performance in the public sector: challenges and trends. Measuring Business Excellence, 11 (4), 4-8.
[87] Al-Raisi, A., Amin, S., & Tahir, S. (2011), Evaluation of e-performance analysis and assessment in the United Arab Emirates (UAE) Organizations, Journal of Internet & Information System, 2 (2), 20 –27.
[88] Neary, D. B. (2002), “Creating a company-wide, on-line, performance management system: a case study at TRW Inc”, Human Resource Management, 41 (4), 491-8.
[89] Gueutal, H. G.& Falbe, C. M. (2005). E-HR: trends in delivery methods. In H. G. Gueutaland D. L. Stone (Eds.). The brave new world of e-HR: human resource management in the digital age (pp. 190–225). San Francisco, CA: Jossey-Bass.
[90] Stanton, J. M. (2000). Reactions to Employee Performance Monitoring: Framework, Review, and Research Directions. Human Performance, 13 (1): 85-113.
[91] Moorman, R. H., & Wells, D. L. (2003). Can electronic performance monitoring be fair? Exploring relationships among monitoring characteristics, perceived fairness, and job performance. Journal of Leadership and Organizational Studies, 10 (2), 2—16.
[92] Payne, S. C., Horner, M. T., Boswell, W. R., Schroeder, A. N. & Stine-Cheyne, K. J. (2009). Comparison of online and traditional performance appraisal systems. Journal of Managerial Psychology, 24 (6), 526–544.
[93] Petrakaki, D., Klecun, E., & Cornford, T. (2014). Changes in healthcare professional work afforded by technology: The introduction of a national electronic patient record in an English hospital.
[94] Qureshi, T. M., Akbar, A., & Khan, M. (2010). Do human resource management practices have an impact on financial performance of banks? African Journal of Business and Management, 4 (7), 1281-1288.
[95] Hair, J. F., Jr., Black, W. C., Babin, B. J., Andersen, R. E., & Tatham, R. L. (2010). Mutilvariate data analysis (7th ed). Upper Saddle River, NJ: Pearson Prentice Hall.
[96] Tabachnick, B. G. & Fidell, L. S. (2007). Using multivariate statistics (5th ed). Boston: Pearson Education Inc.
[97] Wold, H. (1974). Causal flows with latent variables: Partings of the ways in the light of NIPALS modelling. European Economic Review, 5, 67–86. doi: 10.1016/0014-2921.
[98] Chin, W. W., & Newsted, P. R. (1999). Structural equation modeling analysis with small samples using partial least squares. In R. Hoyle (Ed.). In Statistical strategies for small sample research (pp. 307–341).). Thousand Oaks, CA: Sage Publication.
[99] Reinartz, W. J., Haenlein, M., &, & Henseler, J. (2009). An Empirical Comparison of the Efficacy of Covariance-Based and Variance-Based SEM. International Journal of Research in Marketing, 26 (4), 332–344.
[100] Hair, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM). European Business Review, 26, 106–121. doi: doi: 10.1108/EBR-10-2013-0128.
[101] Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In R. R. Sinkovics & P. N. Ghauri (Eds.), Advances in International Marketing (Vol. 20, pp. 277–320). Bingley: Emerald.
[102] Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40, 414–433. doi: 10.1007/s11747-011-0261.
[103] Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2013). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Thousand Oaks: SAGE.
[104] Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strategic Management Journal, 20 (2), 195–204.
[105] Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16 (1), 74–94.
[106] Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement models. Journal of Marketing Research, 39–50.
[107] Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern Methods for Business Research (pp. 295–336). Mahwah, New Jersey: Laurence Erlbaum Associates.
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    Talatu Raiya Umar, Bilkisu Abdulkadir Yammama, Rashidat Otse Shaibu. (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

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    Talatu Raiya Umar; Bilkisu Abdulkadir Yammama; Rashidat Otse Shaibu. The Implications of Adopting and Implementing Electronic Human Resource Management Practices on Job Performance. J. Hum. Resour. Manag. 2020, 8(2), 96-108. doi: 10.11648/j.jhrm.201200802.17

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    AMA Style

    Talatu Raiya Umar, Bilkisu Abdulkadir Yammama, Rashidat Otse Shaibu. The Implications of Adopting and Implementing Electronic Human Resource Management Practices on Job Performance. J Hum Resour Manag. 2020;8(2):96-108. doi: 10.11648/j.jhrm.201200802.17

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  • @article{10.11648/j.jhrm.201200802.17,
      author = {Talatu Raiya Umar and Bilkisu Abdulkadir Yammama and Rashidat Otse Shaibu},
      title = {The Implications of Adopting and Implementing Electronic Human Resource Management Practices on Job Performance},
      journal = {Journal of Human Resource Management},
      volume = {8},
      number = {2},
      pages = {96-108},
      doi = {10.11648/j.jhrm.201200802.17},
      url = {https://doi.org/10.11648/j.jhrm.201200802.17},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jhrm.201200802.17},
      abstract = {Past literature supports positive links between electronic human resource management practices (E-HRM), and job performance. However, poor application of e-HRM practices in the Nigerian public sector resulted in poor job performance and unwholesome ethical practices. As a result, calls for further research have been suggested, particularly on the direct process through which the adoption and implementation of e-HRM practices such e-communication; e-compensation, e-training and e-performance appraisal are likely to influence job performance. Hence, the purpose of this research is to investigate the relationship between electronic Human resource Management (E-HRM) practices and job performance (i.e. task, contextual, adaptive performance, and counterproductive work behaviour at the individual level. We employed a quantitative approach with survey from 214 academic and non academic staff in five higher institutions in Northern part of Nigeria. Using partial least square structural equation modelling (PLS-SEM), the quantitative results indicated that some of the components of E-HRM practices were positively associated with job performance. For instance, both e-communication, and e-compensation were significantly and positively related to all the dimensions of job performance (i.e. task, contextual, adaptive, and counterproductive work behaviour. Also, e-training was found to be positively related to task and adaptive performance only. Similarly, results showed that e-performance appraisal practice was only related to contextual performance and counterproductive work behaviour. On the contrary, e-training practice demonstrated no significant effect on contextual performance and counterproductive work behaviour. Similarly, no significant direct effect was found between e-performance appraisal and task and adaptive performance. Implications of the findings for future research and practice, as well as the limitations of the study are highlighted.},
     year = {2020}
    }
    

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    AU  - Talatu Raiya Umar
    AU  - Bilkisu Abdulkadir Yammama
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    SN  - 2331-0715
    UR  - https://doi.org/10.11648/j.jhrm.201200802.17
    AB  - Past literature supports positive links between electronic human resource management practices (E-HRM), and job performance. However, poor application of e-HRM practices in the Nigerian public sector resulted in poor job performance and unwholesome ethical practices. As a result, calls for further research have been suggested, particularly on the direct process through which the adoption and implementation of e-HRM practices such e-communication; e-compensation, e-training and e-performance appraisal are likely to influence job performance. Hence, the purpose of this research is to investigate the relationship between electronic Human resource Management (E-HRM) practices and job performance (i.e. task, contextual, adaptive performance, and counterproductive work behaviour at the individual level. We employed a quantitative approach with survey from 214 academic and non academic staff in five higher institutions in Northern part of Nigeria. Using partial least square structural equation modelling (PLS-SEM), the quantitative results indicated that some of the components of E-HRM practices were positively associated with job performance. For instance, both e-communication, and e-compensation were significantly and positively related to all the dimensions of job performance (i.e. task, contextual, adaptive, and counterproductive work behaviour. Also, e-training was found to be positively related to task and adaptive performance only. Similarly, results showed that e-performance appraisal practice was only related to contextual performance and counterproductive work behaviour. On the contrary, e-training practice demonstrated no significant effect on contextual performance and counterproductive work behaviour. Similarly, no significant direct effect was found between e-performance appraisal and task and adaptive performance. Implications of the findings for future research and practice, as well as the limitations of the study are highlighted.
    VL  - 8
    IS  - 2
    ER  - 

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Author Information
  • Department of Management Studies, College of Business and Management Studies, Kaduna Polytechnic, Nigeria

  • Department of Social Sciences, College of Administrative Studies and Social Sciences, Kaduna Polytechnic, Nigeria

  • Department of Social Sciences, College of Administrative Studies and Social Sciences, Kaduna Polytechnic, Nigeria

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