The Relationships Between Technology Adoption, HR Competencies, and HR Analytics of Large-Size Enterprises




Technology Adoption, HR Competencies, HR Analytics, Large-size Enterprises, Thailand


Purpose: The aim of this study is to explore the organizational construct that have relationship to HR Analytics in large-size organizations that operate their businesses in Thailand.


Theoretical framework: Technology Adoption and HR Competencies are the two organizational constructs that are introduced in this study to examine their relationship with the HR Analytics.


Design/methodology/approach: The study adopts a confirmatory factor analysis to develop the structural equation model through data collection from large-size organizations in Thailand.


Findings: The hypotheses of the proposed conceptual framework are confirmed at significant level of p < 0.01. In addition, the study also provided statistical confirmation of the role of Technology Adoption as a mediating factor of HR Competencies to HR Analytics.


Research, Practical & Social implications: The study gives the results to support the call from many authors around the area of HR Analytics and its influence on organization management.


Originality/value: The study offers pioneer views on the relationship of relevant organizational dimensions to the HR Analytics and helps to bridge the gaps on the existing studies.


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Bassi, L. (2011). Raging debates in HR Analytics. People & Strategy, 34 (2): 14–18.

Brown, T. A. (2006). Confirmatory factor analysis for applied research. The Guilford Press.

Chartered Institute of Personnel and Development (2018a). People analytics: driving business performance with people data. Global research report, June 2018

Chartered Institute of Personnel and Development (2018b). Getting started with people analytics: a practitioners’ guide. Guide, November 2018

Chartered Institute of Personnel and Development (2020). People analytics factsheet. March 2020

Dahlbom, P.; Siikanen, N.; Sajasalo, P.; Jarvenpää, M. (2019). Big data and HR analytics in the digital era. Baltic Journal of Management, 15 (1): 120-138.

Davenport, T.; Harris J.; Shapiro J. (2010). Competing on talent analytics. Harvard Business Review. 88(10):52-8, 150

Fernandez, V.; Gallardo, E.G. (2021). Tackling the HR digitalization challenge: key factors and barriers to HR analytics adoption. Competitiveness Review: An International Business Journal, 31 (1): 162-187.

Fornell, C.; Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18 (1): 39-50.

Wamba, S. F.; Akter, S.; De Bourmont, M. (2018). Quality dominant logic in big data analytics and firm performance. Business Process Management Journal, 24 (4): 923-942

Hair, J. F.; Black, W. C.; Babin, B. J.; Anderson, R. E. (2010). Multivariate Data Analysis (7th Edition). NJ: Prentice Hall.

Jeble, S.; Dubey, R.; Childe, S.J.; Papadopoulos, T.; Roubaud, D.; Prakash, A. (2018). Impact of big data and predictive analytics capability on supply chain sustainability. The International Journal of Logistics Management, 29 (2): 513-538.

Steven J. R.; Samuel F. W.; Shahriar A.; Rameshwar D.; Stephen J. C. (2016). Modelling quality dynamics, business value and firm performance in a big data analytics environment. International Journal of Production Research, 55 (17): 5011-5026.

Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling. Guilford Publications.

Kremer K. (2018). HR analytics and its moderating factors. Vezetéstudomány - Budapest Management Review, 49 (11): 62-68.

Lai, Y.; Sun, H.; Ren, J. (2018). Understanding the determinants of big data analytics (BDA) adoption in logistics and supply chain management: An empirical investigation. The International Journal of Logistics Management, 29 (2): 676-703.

Lawler, E. E.; Alec L.; John W. B. (2004). HR Metrics and Analytics - Uses and Impacts. Center for Effective Organizations, 27 (4): 1-22.

Lawler, E. E. (2003). Treat People Right. San Francisco: Jossey-Bass.

Janet H. M.; John W. B. (2017). An evidence-based review of HR Analytics. The International Journal of Human Resource Management, 28 (1): 3-26.

Maçada, A. C. G.; Freitas Junior, J. C. da S.; Brinkhues, R. A. ; Vasconcellos, S. de . (2021). Life interrupted, but performance improved: Rethinking the influence of technology-mediated interruptions at work and personal life. International Journal of Professional Business Review, 7(1): e0279.

McCartney, S.; Murphy, C.; Mccarthy, J. (2020). 21st century HR: a competency model for the emerging role of HR Analysts. Personnel Review, 50 (6): 1495-1513.

Minbaeva, D. (2017). Human capital analytics: why aren’t we there. Journal of Organizational Effectiveness: People and Performance, 4 (2): 110-118.

Mishra, D.; Luo, Z.; Hazen, B.; Hassini, E.; Foropon, C. (2019). Organizational capabilities that enable big data and predictive analytics diffusion and organizational performance: A resource-based perspective. Management Decision, 57 (8): 1734-1755.

Mokkink L.; Terwee C. B.; Patrick D.; Alonso J. (2010). The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: an international Delphi study. Quality of Life Research, 19 (4): 539-549.

Moore, D. S.; Notz, W. I; Flinger, M. A. (2013). The basic practice of statistics. 6th Ed. New York, NY: W. H. Freeman and Company, Page 138.

Nyutu, E. N.; Cobern, W. W.; Pleasants, B. A-S. (2021). Correlational study of student perceptions of their undergraduate laboratory environment with respect to gender and major. International Journal of Education in Mathematics, Science, and Technology, 9 (1): 83-102.

Peeters, T.; Paauwe, J.; Van De Voorde, K. (2020). People analytics effectiveness: developing a framework. Journal of Organizational Effectiveness: People and Performance, 7 (2): 203-219.

Pillai, R.; Sivathanu, B. (2020). Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations. Benchmarking: An International Journal, 27 (9): 2599-2629.

Rao, Y.; Guo, K.H.; Chen, Y. (2015). Information systems maturity, knowledge sharing, and firm performance. International Journal of Accounting & Information Management, 23 (2): 106-127.

Rasmussen, T.; Ulrich, D. (2015). Learning from practice: how HR analytics avoids being a management fad. Organizational Dynamics, 44 (3): 236-242.

Sharma, A.; Sharma, T. (2017). HR analytics and performance appraisal system: a conceptual framework for employee performance improvement. Management Research Review, 40 (6): 684-697

Singh, N.P.; Singh, S. (2019). Building supply chain risk resilience: Role of big data analytics in supply chain disruption mitigation. Benchmarking: An International Journal, 26 (7): 2318-2342.

Tavakol M.; Dennick R (2011). Making sense of Cronbach's alpha. International Journal of Medical Education, (27) 2: 53-55.

Vargas, R.; Yurova, Y.; Ruppel, C.; Tworoger, L.; Greenwood, R. (2018). Individual adoption of HR analytics: a fine grained view of the early stages leading to adoption. The International Journal of Human Resource Management, 29 (22): 3046-3067.

Verma, S.; Singh, V.; Bhattacharyya, S. S. (2021). Do big data-driven HR practices improve HR service quality and innovation competency of SMEs. International Journal of Organizational Analysis, 29 (4): 950-973.

Yoshikawa, N. K.; Filho, J. R. da C.; Penha, R.; Kniess, C. T.; Souza, J. B. de. (2020). Agile Approach As A Strategy In Digital Transformation Projects: A Bibliometric Review And Bibliographic Study. International Journal of Professional Business Review, 5(2): 272–287.




How to Cite

Penpokai, S., Vuthisopon, S., & Saengnoree, A. (2023). The Relationships Between Technology Adoption, HR Competencies, and HR Analytics of Large-Size Enterprises. International Journal of Professional Business Review, 8(3), e0971.