Porcelain Publishing / JCHRM / Volume 15 / Issue 2 / DOI: 10.47297/wspchrmWSP2040-800501.20241502
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Elevating the Influence of HR Analytics on Organizational Performance: An Empirical Investigation in Hi-Tech Manufacturing Industry of a Developing Economy

Naveed Mushtaq 1 Xing Manjiang 2 Ayesha Bakhtawar 1 Muhammad Ali Mufti 1
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1 Malik Firoz Khan Noon Business School, University of Sargodha
2 Graduate School of Global Business, Kyonggi University, South Korea
© Invalid date by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Abstract

This study examines the influence of HR analytics on organizational performance by empirically evaluating the relationship between HR analytics, evidence-based management (EBM), and firm performance in the Hi-Tech manufacturing industry of a developing economy. Data was collected from HR managers via random sampling from Hi-Tech manufacturing firms. Using partial least squares analysis, the study reveals that HR technology plays a pivotal role in enabling HR analytics. Evidence-based management (EBM) was identified as a mediator in the positive relationship between HR analytics and organizational performance. However, the study finds that the Hi-Tech manufacturing industry faces challenges in adopting a data-driven culture, limiting the full potential of HR analytics and EBM. This research emphasizes the significance of HR technology in facilitating HR analytics and provides empirical evidence of its positive influence on firm performance through EBM mediation. It highlights the potential for organizations to achieve a sustainable competitive advantage through data-driven HR decision-making.

Keywords
HR analytics
Data-driven culture
Evidence-based management
Organizational performance
HR technology
References

[1] Abbasi, A., Sarker, S., & Chiang, R. H. L. (2016). Big data research in information systems: Toward an inclusive research agenda. Journal of the Association for Information Systems, 17(2),1-3. https://doi.org/10.17705/1jais.00423v

[2] Agrawal, A., & Choudhary, A. (2016). Perspective: Materials informatics and big data: Realization of the "fourth paradigm" of science in materials science. APL Materials, 4(5), 11-17. https://doi.org/10.1063/1.4946894

[3] Akter, S., Fosso Wamba, S., & Dewan, S. (2017).Why PLS-SEM is suitable for complex modeling? An empirical illustration in big data analytics quality. Production Planning and Control, 28(12), 1011-1021. https://doi.org/10.1080/09537287.2016.1267411

[4] Akter, S., & Wamba, S. F. (2016). Big data analytics in E-commerce: A systematic review and agenda for future research. Electronic Markets, 26(2), 173-194. https://doi.org/10.1007/s12525-016-0219-0

[5] Aloini, D., Cannavacciuolo, L., Gitto, S., Lettieri, E., Malighetti, P., & Visintin, F. (2018). Evidence-based management for performance improvement in healthcare. Management Decision, 56(10), 2063–2068. https://doi.org/10.1108/MD-10-2018-004

[6] Alsuliman, B. R. A., & Elrayah, M. (2021). The reasons that affect the implementation of HR analytics among HR professionals.Canadian Journal of Business and Information Studies, 3(2), 29-37. https://doi.org/10.34104/cjbis.021.029037

[7] Andersen, M. K. (2017). Human capital analytics: The winding road. Journal of Organizational Effectiveness, 4(2), 133-136. https://doi.org/10.1108/JOEPP-03-2017-0024

[8] Angrave, D., Charlwood, A., Kirkpatrick, I., Lawrence, M., & Stuart, M. (2016). HR and analytics: Why HR is set to fail the big data challenge. Human Resource Management Journal, 26(1), 1-11. https://doi.org/10.1111/1748-8583.12090

[9] Aral, S., Brynjolfsson, E., & Wu, L. (2012). Three-way complementarities: Performance pay, human resource analytics, and information technology. Management Science, 58(5), 913-931. https://doi.org/10.1287/mnsc.1110.1460

[10] Ardichvili, A., Maurer, M., Li, W., Wentling, T., & Stuedemann, R. (2006). Cultural influences on knowledge sharing through online communities of practice. Journal of Knowledge Management, 10(1), 94-107. https://doi.org/10.1108/13673270610650139

[11] Ashbaugh, S., & Miranda, R. (2002). Technology for human resources management: Seven questions and answers. Public Personnel Management, 31(1), 7-20. https://doi.org/10.1177/009102600203100102

[12] Aydin, R. A. B. (2018). The role of organizational culture on leadership styles.  MANAS Journal of Social Studies, 7(1), 267-280.

[13] Baba, V. V., & HakemZadeh, F. (2012). Toward a theory of evidence-based decision making. Management Decision, 50(5), 832–867. https://doi.org/10.1108/00251741211227546

[14] Baesens, B., De Winne, S., & Sels, L. (2017). Is your company ready for HR analytics? MIT Sloan Management Review, 58(2), 1-20. https://doi.org/10.7551/mitpress/11633.003.0011

[15] Barends, E. (2015). In search of evidence empirical findings and professional perspectives on evidence-based management. Journal of Management Development, 34(2), 122-136.

[16] Barney, J. B. (1991). The resource-based view of strategy: Origins, implications, and prospects. Journal of Management, 17(1), 97-211.

[17] Barney, J. B., & Arikan, A. M. (2005). The resource-based view: Origins and implications. In The blackwell handbook of strategic management (pp.124-188). Blackwell Publishing. https://doi.org/10.1111/b.9780631218616.2006.00006.x

[18] Bassi, L. (2011). Raging debates in HR analytics. People & Strategy, 34(2), 1-14.

[19] Bassi, L. J., Carpenter, R., & McMurrer, D. (2012). HR analytics handbook. Reed Business.

[20] Becker, J. M., Klein, K., & Wetzels, M. (2012). Hierarchical latent variable models in PLS-SEM: Guidelines for using reflective-formative type models. Long Range Planning, 45(6), 359-394. https://doi.org/10.1016/j.lrp.2012.10.001

[21] Ben Moussa, N., & El Arbi, R. (2020). The impact of human resources information systems on individual innovation capability in Tunisian companies: The moderating role of affective commitment. European Research on Management and Business Economics, 26(1), 18-25. https://doi.org/10.1016/j.iedeen.2019.12.001

[22] Boudreau, J. W., & Ramstad, P. M. (2007). Beyond HR: The new science of human capital. Harvard Business Press. https://doi.org/10.5860/choice.45-1552

[23] Bhatt, G. D., & Grover, V. (2005). Types of information technology capabilities and their role in competitive advantage: An empirical study. Journal of Management Information Systems, 22(2), 253-277. https://doi.org/10.1080/07421222.2005.11045844

[24] Biglan, A., & Ogden, T. (2008). The evolution of evidence-based practices. European Journal of Behavior Analysis, 9(1), 81-95. https://doi.org/10.1080/15021149.2008.11434297

[25] Black, J. S., & van Esch, P. (2020). AI-enabled recruiting: What is it and how should a manager use it? Business Horizons, 63(2), 215-226. https://doi.org/10.1016/j.bushor.2019.12.001

[26] Boakye, A., & Ayerki Lamptey, Y. (2020). The rise of HR analytics: Exploring its implications from a developing country perspective. Journal of Human Resource Management, 8(3), 181-189. https://doi.org/10.11648/j.jhrm.20200803.19

[27] Bondarouk, T., & Brewster, C. (2016). Conceptualising the future of HRM and technology research. International Journal of Human Resource Management, 27(21), 2652-2671. https://doi.org/10.1080/09585192.2016.1232296

[28] Bondarouk, T., Parry, E., & Furtmueller, E. (2017). Electronic HRM: Four decades of research on adoption and consequences. International Journal of Human Resource Management, 28(1), 98-131. https://doi.org/10.1080/09585192.2016.1245672

[29] Booker, L. D., Bontis, N., & Serenko, A. (2012). Evidence-based management and academic research relevance. Knowledge and Process Management, 19(3), 121-130. https://doi.org/10.1002/kpm.1392

[30] Boudreau, J., & Cascio, W. (2017). Human capital analytics: Why are we not there? Journal of Organizational Effectiveness, 4(2), 119-126. https://doi.org/10.1108/JOEPP-03-2017-0021

[31] Boudreau, J., & Jesuthasan, R. (2011). Transformative HR: How great companies use evidence-based change for sustainable advantage. John Wiley & Sons. https://doi.org/10.1111/peps.12031_4

[32] Briggs, H. E., & McBeath, B. (2009). Evidence-based management: Origins, challenges, and implications for social service administration. Administration in Social Work, 33(3), 242-261. https://doi.org/10.1080/03643100902987556

[33] Briner, R. B., Denyer, D., & Rousseau, D. M. (2009). Evidence-based management: Concept cleanup time? Academy of Management Perspectives, 23(4), 19-32. https://doi.org/10.5465/AMP.2009.45590138

[34] Bulmash, J. (2008). Human resource management and technology. In J. Cole (Ed.), Managing human resources (pp. 348-375). Pearson Education Canada.

[35] Buttner, E. H., & Tullar, W. L. (2018). A representative organizational diversity metric: A dashboard measure for executive action. Equality, Diversity and Inclusion, 37(3), 219–232. https://doi.org/10.1108/EDI-04-2017-0076

[36] Cappa, F., Oriani, R., Peruffo, E., & McCarthy, I. (2021). Big data for creating and capturing value in the digitalized environment: Unpacking the effects of volume, variety, and veracity on firm performance. Journal of Product Innovation Management, 38(1), 49-67. https://doi.org/10.1111/jpim.12545

[37] Cascio, W. F., & Montealegre, R. (2016). How technology is changing work and organizations. Annual Review of Organizational Psychology and Organizational Behavior, 3(1), 349-375. https://doi.org/10.1146/annurev-orgpsych-041015-062352

[38] Castro, L., Castro-Nogueira, M. Á., Villarroel, M., & Toro, M. Á. (2019). The role of assessor teaching in human culture. Biological Theory, 14(2), 112–121. https://doi.org/10.1007/s13752-018-00314-2

[39] Chahtalkhi, N. (2016). What challenges does HR face when implementing HR analytics and what actions have been taken to solve these challenges? (Master's thesis, University of Twente).

[40] Chalutz Ben-Gal, H. (2019).An ROI-based review of HR analytics:Practical implementation tools. In Personnel Review, 48(6), 1429-1448. https://doi.org/10.1108/PR-11-2017-0362

[41] Chan, L. L. M., Shaffer, M. A., & Snape, E. (2004). In search of sustained competitive advantage: The impact of organizational culture, competitive strategy and human resource management practices on firm performance. The International Journal of Human Resource Management, 15(1), 17-35. https://doi.org/10.1080/0958519032000157320

[42] Chatterjee, S., Chaudhuri, R., & Vrontis, D. (2021). Does data-driven culture impact innovation and performance of a firm? An empirical examination. Annals of Operations Research, 17(2), 1-26. https://doi.org/10.1007/s10479-020-03887-z

[43] Chaudhuri, R., Chatterjee, S., Vrontis, D., & Thrassou, A. (2021). Adoption of robust business analytics for product innovation and organizational performance: The mediating role of organizational data-driven culture. Annals of Operations Research, 13(3), 1-35. https://doi.org/10.1007/s10479-021-04407-3

[44] Chaudhuri, R., Chatterjee, S., Mariani, M. M., & Wamba, S. F. (2024). Assessing the influence of emerging technologies on organizational data driven culture and innovation capabilities: A sustainability performance perspective. Technological Forecasting and Social Change, 200, 123165.

[45] Chin, W. W. (2010). How to write up and report PLS analyses. In Handbook of partial least squares: Concepts, methods and applications (pp. 655-690). Springer.

[46] Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295-336.

[47] Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128-152. https://doi.org/10.2307/2393553

[48] Collins, L., Fineman, D., & Tsuchida, A. (2017). People analytics: Recalculating the route. In Rewriting the rules for the digital age: 2017 Deloitte global human capital trends (pp.56-61). Deloitte University Press.

[49] Cooper, D. R., & Schindler, P. S. (1995). Business research methods (5th ed.). McGraw-Hill.

[50] Coron, C. (2022). Quantifying human resource management: A literature review. Personnel Review, 51(4), 1386-1409. https://doi.org/10.1108/PR-05-2020-0322

[51] Cynthia, B., Becerra-Fernandez, I., Short, J., & Ross, J. (2012). Finding value in the information explosion. MIT Sloan Management Review, 53(4), 37-44.

[52] Dahlbom, P., Siikanen, N., Sajasalo, P., & Jarvenpää, M. (2020). Big data and HR analytics in the digital era. Baltic Journal of Management, 15(1), 120-138. https://doi.org/10.1108/BJM-11-2018-0393

[53] Daouk-Öyry, L., Sahakian, T., & van de Vijver, F. (2021). Evidence-based management competency model for managers in hospital settings. British Journal of Management, 32(4), 1384-1403. https://doi.org/10.1111/1467-8551.12434

[54] Davenport, T. H., Harris, J., & Shapiro, J. (2010). Competing talent on analytics. Harvard Business Review, 88(10), 52-58.

[55] Delaney, J. T., & Huselid, M. A. (1996). The impact of human resource management practices on perceptions of organizational performance. Academy of Management Journal, 39(4), 949-969. https://doi.org/10.2307/256718

[56] Dery, K., Grant, D., & Wiblen, S. (2009). Human resource information systems (HRIS ): Replacing or enhancing HRM. In Proceedings of the 15th World Congress of the International Industrial Relations Association IIRA (pp. 24-27). International Industrial Relations Association.

[57] Djerdjouri, M. (2020). Data and business intelligence systems for competitive advantage: Prospects, challenges, and real-world applications. Mercados y Negocios, 13(41), 5-18. https://doi.org/10.32870/myn.v0i41.7537

[58] Duan, L., & Da Xu, L. (2021). Data analytics in industry 4.0: A survey. Information Systems Frontiers, 23(3), 1-17. https://doi.org/10.1007/s10796-021-10190-0

[59] Dubey, R., Gunasekaran, A., Childe, S. J., Papadopoulos, T., Luo, Z., Wamba, S. F., & Roubaud, D. (2019). Can big data and predictive analytics improve social and environmental sustainability? Technological Forecasting and Social Change, 144(4), 534-545. https://doi.org/10.1016/j.techfore.2017.06.020

[60] Dulebohn, J. H., & Johnson, R. D. (2013). Human resource metrics and decision support: A classification framework. Human Resource Management Review, 23(1), 71-83. https://doi.org/10.1016/j.hrmr.2012.06.005

[61] Durai, D. S., Rudhramoorthy, K., & Sarkar, S. (2019). HR metrics and workforce analytics: It is a journey, not a destination. Human Resource Management International Digest, 27(1), 4-6. https://doi.org/10.1108/HRMID-08-2018-0167

[62] Efron, B., & Tibshirani, R. J. (1994). An introduction to the bootstrap. In An introduction to the bootstrap. CRC press. https://doi.org/10.1201/9780429246593

[63] Ergle, D., Ludviga, I., & Kalviņa, A. (2017). Turning data into valuable insights: The case study in aviation sector company. CBU International Conference Proceedings, 5(1), 145-154. https://doi.org/10.12955/cbup.v5.941

[64] Etukudo, R. (2019). Strategies for using analytics to improve human resource management (Doctoral dissertation, Walden University). ProQuest Dissertations and Theses.

[65] Falletta, S. (2014). In search of HR intelligence: Evidence-based HR analytics practices in high performing companies. People & Strategy, 36(4), 28-37.

[66] Falletta, S. V., & Combs, W. L. (2021). The HR analytics cycle: A seven-step process for building evidence-based and ethical HR analytics capabilities. Journal of Work-Applied Management, 13(1), 51-68. https://doi.org/10.1108/JWAM-03-2020-0020

[67] Fernandez, J. (2019). The ball of wax we call HR analytics. Strategic HR Review, 18(1), 21-25. https://doi.org/10.1108/shr-09-2018-0077

[68] Fernandez, V., & Gallardo-Gallardo, E. (2021). Tackling the HR digitalization challenge: key factors and barriers to HR analytics adoption. Competitiveness Review, 31(1), 162-187. https://doi.org/10.1108/CR-12-2019-0163

[69] Ferraris, A., Mazzoleni, A., Devalle, A., & Couturier, J. (2019). Big data analytics capabilities and knowledge management: Impact on firm performance. Management Decision, 57(8), 1923-1936. https://doi.org/10.1108/MD-07-2018-0825

[70] Florkowski, G. W., & Olivas-Luján, M. R. (2006). The diffusion of human-resource information-technology innovations in US and non-US firms. Personnel Review, 35(6), 684-710. https://doi.org/10.1108/00483480610702737

[71] Fornell, C., & Bookstein, F. L. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 19(4), 440-452. https://doi.org/10.1177/002224378201900406

[72] Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382-388. https://doi.org/10.1177/002224378101800313

[73] Fosso Wamba, S., Akter, S., Trinchera, L., & De Bourmont, M. (2019). Turning information quality into firm performance in the big data economy. Management Decision, 57(8), 1756-1783. https://doi.org/10.1108/MD-04-2018-0394

[74] Foster, S. (2010). Creating HR value through technology. Strategic Direction, 26(8), 3-5. https://doi.org/10.1108/02580541011055634

[75] Francis-Smythe, J., Robinson, L., & Ross, C. (2013). The role of evidence in general managers' decision-making. Journal of General Management, 38(4), 3-21. https://doi.org/10.1177/030630701303800402

[76] Fred, M. O. (2015). An overview of HR analytics to maximize human capital investment. International Journal of Advance Research and Innovative Ideas in Education, 1(4), 118-122.

[77] Fu, N., Flood, P. C., Bosak, J., Rousseau, D. M., Morris, T., & O Regan, P. (2017). High‐performance work systems in professional service firms: Examining the practices‐resources‐uses‐performance linkage. Human Resource Management, 56(2), 329-352. https://doi.org/10.1002/hrm.21767

[78] George, G., Haas, M. R., & Pentland, A. (2014). Big data and management. Academy of Management Journal, 57(2), 321–326. https://doi.org/10.5465/amj.2014.4002

[79] George, L., & Kamalanabhan, T. J. (2016). A study on the acceptance of HR analytics in organisations. International Journal of Innovative Research & Development, 5(2), 1-6.

[80] Ghasemaghaei, M., Ebrahimi, S., & Hassanein, K. (2018). Data analytics competency for improving firm decision making performance. Journal of Strategic Information Systems, 27(1), 101-113. https://doi.org/10.1016/j.jsis.2017.10.001

[81] Ghasemaghaei, M., Hassanein, K., & Turel, O. (2015). Impacts of big data analytics on organizations: A resource fit perspective. In 2015 Americas Conference on Information Systems (AMCIS 2015).

[82] Giauque, D., Anderfuhren-Biget, S., & Varone, F. (2013). HRM practices, intrinsic motivators, and organizational performance in the public sector. Public Personnel Management, 42(2), 123-150. https://doi.org/10.1177/0091026013487121

[83] Girotra, R., Kaushik, T., & Dean, A. (2018). Talent acquisition challenges faced by Indian e-commerce startups: Culture as a moderator. The IUP Journal of Entrepreneurship Development, 15(2), 24-43.

[84] Greasley, K., & Thomas, P. (2020). HR analytics: The onto-epistemology and politics of metricized HRM. Human Resource Management Journal, 30(4), 494-507. https://doi.org/10.1111/1748-8583.12283

[85] Green, D. (2017). The best practices to excel at people analytics. Journal of Organizational Effectiveness, 4(2), 137-144. https://doi.org/10.1108/JOEPP-03-2017-0027

[86] Guo, R., Berkshire, S. D., Fulton, L. V., & Hermanson, P. M. (2017). Use of evidence-based management in healthcare administration decision-making. Leadership in Health Services, 30(3), 54-63. https://doi.org/10.1108/LHS-07-2016-0033

[87] Gupta, M., & George, J. F. (2016). Toward the development of a big data analytics capability. Information and Management, 53(8), 1049-1064. https://doi.org/10.1016/j.im.2016.07.004

[88] Gurusinghe, R. N., Arachchige, B. J. H., & Dayarathna, D. (2021). Predictive HR analytics and talent management: A conceptual framework. Journal of Management Analytics, 8(2), 195-221. https://doi.org/10.1080/23270012.2021.1899857

[89] Hair, J. F., Ringle, C. M., & Sarstedt, M. (2012). Partial least squares: The better approach to structural equation modeling? Long Range Planning, 45(6), 312-319.

[90] HakemZadeh, F., & Baba, V. V. (2016). Measuring the actionability of evidence for evidence-based management. Management Decision, 54(5), 1183-1204. https://doi.org/10.1108/MD-01-2015-0001

[91] Hannon, J., Jelf, G., & Brandes, D. (1996). Human resource information systems: Operational issues and strategic considerations in a global environment. International Journal of Human Resource Management, 7(1),  245-269. https://doi.org/10.1080/09585199600000127

[92] Harris, J. G., Craig, E., & Light, D. A. (2011). Talent and analytics: New approaches, higher ROI. Journal of Business Strategy, 32(6), 1-18. https://doi.org/10.1108/02756661111180087

[93] Hawi, R. O., Alkhodary, D., & Hashem, T. (2015). Managerial competencies and organizations performance. International Journal of Management Sciences, 5(11), 723-735.

[94] Holloway, J. (2007). Where's the evidence for evidence-based management? Advancing Research in the Business and Management Field, 4(1), 145-164.

[95] Houghton, E., & Green, M. (2018). People analytics: Driving business performance with people data. Chartered Institute for Personnel Development (CIPD), 3(7), 135-194.

[96] Hovmand, P. S., & Gillespie, D. F. (2010). Implementation of evidence-based practice and organizational performance. Journal of Behavioral Health Services and Research, 37(1), 79-94. https://doi.org/10.1007/s11414-008-9154-y

[97] Huselid, M. A. (2018). The science and practice of workforce analytics: Introduction to the HRM special issue. Human Resource Management, 57(3), 679-684. https://doi.org/10.1002/hrm.21916

[98] Irfan, M., & Wang, M. (2019). Data-driven capabilities, supply chain integration, and competitive performance: Evidence from the food and beverages industry in Pakistan. British Food Journal, 121(11), 2565-2581. https://doi.org/10.1108/BFJ-02-2019-0131

[99] Jabir, B., Falih, N., & Rahmani, K. (2019). HR analytics a roadmap for decision making: Case study. Indonesian Journal of Electrical Engineering and Computer Science, 15(2), 1047-1056. https://doi.org/10.11591/ijeecs.v15.i2.pp979-990

[100] Jackson, S. E., Schuler, R. S., & Jiang, K. (2014). Strategic HRM: A review and framework. Academy of Management Annals, 8(1), 1-56.

[101] Jain, P., & Jain, P. (2020). Understanding the concept of HR analytics. International Journal on Emerging Technologies, 11(2), 170-176.

[102] Jalal, H. A., & Toulson, P. (2018). Knowledge sharing and organizational culture: The hidden moderator for competitive advantage. International Journal of Knowledge Management Studies, 9(4), 369-383. https://doi.org/10.1504/IJKMS.2018.096313

[103] Janati, A., Hasanpoor, E., Hajebrahimi, S., & Sadeghi-Bazargani, H. (2018). Evidence-based management – Healthcare manager viewpoints. International Journal of Health Care Quality Assurance, 31(5), 365-374. https://doi.org/10.1108/IJHCQA-08-2017-0143

[104] Jiang, Y., & Akdere, M. (2021). An operational conceptualization of human resource analytics: Implications for in human resource development. Industrial and Commercial Training, 54(1), 8-17. https://doi.org/10.1108/ICT-04-2021-0028

[105] Johnson, R. D., Lukaszewski, K. M., & Stone, D. L. (2016). The evolution of the field of human resource information systems: Co-Evolution of technology and HR processes. Communications of the Association for Information Systems, 38(1), 499-519. https://doi.org/10.17705/1CAIS.03828

[106] Kane, G. C. (2015). 'People analytics' through super-charged ID. MIT Sloan Management Review, 56(4), 7-9.

[107] Kapoor, B., & Sherif, J. (2012). Human resources in an enriched environment of business intelligence. Kybernetes, 41(10), 1572-1584. https://doi.org/10.1108/03684921211276792

[108] Karmańska, A. (2020). The benefits of HR analytics. Prace Naukowe Uniwersytetu Ekonomicznego We Wrocławiu, 64(8), 91-101. https://doi.org/10.15611/pn.2020.8.03

[109] Kim, S., Wang, Y., & Boon, C. (2021). Sixty years of research on technology and human resource management: Looking back and looking forward. Human Resource Management, 60(1), 5-24. https://doi.org/10.1002/hrm.22049

[110] King, K. G. (2016). Data analytics in human resources: A case study and critical review. Human Resource Development Review, 15(4), 455-477. https://doi.org/10.1177/1534484316675818

[111] Kiron, D., Ferguson, R. B., & Kirk Prentice, P. (2013). From value to vision: Reimagining the possible with data analytics. MIT Sloan Management Review, 54(3), 19-21.

[112] Kossek, E. E., Young, W., Gash, D. C., & Nichol, V. (1994). Waiting for innovation in the human resources department: Godot implements a human resource information system. Human Resource Management, 33(1), 135-159.  https://doi.org/10.1002/hrm.3930330108

[113] Kovner, A. R., Elton, J. J., & Billings, J. (2000). Evidence-based management. Frontiers of Health Services Management, 16(4), 3–24.

[114] Kovner, A. R., & Rundall, T. G. (2006). Evidence-based management reconsidered. Frontiers of Health Services Management, 22(3), 1-3.  https://doi.org/10.1097/01974520-200601000-00002

[115] Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607-610. https://doi.org/10.1177/001316447003000308

[116] Kryscynski, D., Reeves, C., Stice-Lusvardi, R., Ulrich, M., & Russell, G. (2018). Analytical abilities and the performance of HR professionals. Human Resource Management, 57(3), 715-738. https://doi.org/10.1002/hrm.21854

[117] Khan, W., Nisar, Q. A., Roomi, M. A., Nasir, S., Awan, U., & Rafiq, M. (2023). Green human resources management, green innovation and circular economy performance: The role of big data analytics and data-driven culture. Journal of Environmental Planning and Management, 1-26. https://doi.org/10.1080/09640568.2023.2189544

[118] LaValle, S., Lesser, E., Shockley, R., Hopkins, M. S., & Kruschwitz, N. (2010). Big data, analytics and the path from insights to value. MIT Sloan Management Review, 52(2), 86-101.

[119] Lawler III, E. E., & Mohrman, S. A. (2003). HR as a strategic partner: What does it take to make it happen? Human Resource Planning, 26(3), 15-29.

[120] Lengnick-Hall, M. L., & Moritz, S. (2003). The impact of e-HR on the human resource management function. Journal of Labor Research, 24(3), 300-365. https://doi.org/10.1007/s12122-003-1001-6

[121] Levenson, A., & Fink, A. (2017). Human capital analytics: Too much data and analysis, not enough models and business insights. Journal of Organizational Effectiveness, 4(2), 340-365. https://doi.org/10.1108/JOEPP-03-2017-0029

[122] Liang, Z., Blackstock, F. C., Howard, P. F., Briggs, D. S., Leggat, S. G., Wollersheim, D., Edvardsson, D., & Rahman, A. (2018). An evidence-based approach to understanding the competency development needs of the health service management workforce in Australia. BMC Health Services Research, 18(1), 1-12. https://doi.org/10.1186/s12913-018-3760-z

[123] Liu, L., Akkineni, S., Story, P., & Davis, C. (2020). Using HR analytics to support managerial decisions: A case study. ACMSE 2020 - Proceedings of the 2020 ACM Southeast Conference, 6(5), 168-175. https://doi.org/10.1145/3374135.3385281

[124] Liyuan, L., Meng, H., Yiyun, Z., & Reza, P. (2019). E2C-Chain: A two-stage incentive education employment and skill certification blockchain. Proceedings - 2019 2nd IEEE International Conference on Blockchain (Blockchain 2019) (pp. 140-147). https://doi.org/10.1109/Blockchain.2019.00027

[125] Lochab, A., Kumar, S., & Tomar, H. (2018). Impact of human resource analytics on organizational performance : A review of literature using R-software. International Journal of Management, Technology, and Engineering, 8(12), 2848-2852.

[126] Long, T. B., Blok, V., & Coninx, I. (2016). Barriers to the adoption and diffusion of technological innovations for climate-smart agriculture in Europe: Evidence from the Netherlands, France, Switzerland, and Italy. Journal of Cleaner Production, 112(6), 9-21. https://doi.org/10.1016/j.jclepro.2015.06.044

[127] Maamari, B. E., & Osta, A. (2021). The effect of HRIS implementation success on job involvement, job satisfaction, and work engagement in SMEs. International Journal of Organizational Analysis, 29(5), 1079-1098. https://doi.org/10.1108/IJOA-07-2020-2298

[128] Manogaran, G., Thota, C., & Lopez, D. (2022). Human-computer interaction with big data analytics. Research Anthology on Big Data Analytics, Architectures, and Applications, 7(4), 1578-1596. https://doi.org/10.4018/978-1-6684-3662-2.ch076

[129] Margherita, A. (2022). Human resources analytics: A systematization of research topics and directions for future research. Human Resource Management Review, 32(2), 750-795. https://doi.org/10.1016/j.hrmr.2020.100795

[130] Marler, J. H., & Boudreau, J. W. (2017). An evidence-based review of HR Analytics. International Journal of Human Resource Management, 28(1), 3-26. https://doi.org/10.1080/09585192.2016.1244699

[131] Marler, J. H., Cronemberger, F., & Tao, C. (2017). HR analytics: Here to stay or short-lived management fashion? Electronic HRM in the Smart Era, 7(4), 65-79. https://doi.org/10.1108/978-1-78714-315-920161003

[132] Martelli, P. F., & Hayirli, T. C. (2018). Three perspectives on evidence-based management: Rank, fit, and variety. Management Decision, 56(10), 2077-2093. https://doi.org/10.1108/MD-09-2017-0920

[133] McAfee, A., & Brynjolfsson, E. (2012). Big data: The management revolution. Harvard Business Review, 90(10), 60-68.

[134] 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. https://doi.org/10.1108/PR-12-2019-0670

[135] McIver, D., Lengnick-Hall, M. L., & Lengnick-Hall, C. A. (2018). A strategic approach to workforce analytics: Integrating science and agility. Business Horizons, 61(3), 397-407. https://doi.org/10.1016/j.bushor.2018.01.005

[136] Melnyk, B. M., Gallagher-Ford, L., Thomas, B. K., Troseth, M., Wyngarden, K., & Szalacha, L. (2016). A study of chief nurse executives indicates low prioritization of evidence-based practice and shortcomings in hospital performance metrics across the United States. Worldviews on Evidence-Based Nursing, 13(1), 6-14. https://doi.org/10.1111/wvn.12133

[137] Melnyk, B. M., Gallagher-Ford, L., Zellefrow, C., Tucker, S., Thomas, B., Sinnott, L. T., & Tan, A. (2018). The first U.S. study on nurses' evidence-based practice competencies indicates major deficits that threaten healthcare quality, safety, and patient outcomes. Worldviews on Evidence-Based Nursing, 15(1), 16–25. https://doi.org/10.1111/wvn.12269

[138] Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big data analytics and firm performance: Findings from a mixed-method approach. Journal of Business Research, 98(7), 261-276. https://doi.org/10.1016/j.jbusres.2019.01.044

[139] Minbaeva, D. (2017). Human capital analytics: Why aren't we there? Introduction to the special issue. Journal of Organizational Effectiveness, 4(2), 11-20. https://doi.org/10.1108/JOEPP-04-2017-0035

[140] Minbaeva, D. B. (2018). Building credible human capital analytics for organizational competitive advantage. Human Resource Management, 57(3),71-80. https://doi.org/10.1002/hrm.21848

[141] Mishra, S. N., Lama, D. R., & Pal, Y. (2016). Human resource predictive analytics (HRPA) for HR management in organizations. International Journal of Scientific & Technology Research, 5(5), 33-35.

[142] Mohammed, A. Q. (2019). HR analytics: A modern tool in HR for predictive decision making. Journal of Management, 6(3),14-23. https://doi.org/10.34218/jom.6.3.2019.007

[143] Momin, W. Y. (2016). HR analytics transforming human resource management. International Journal of Applied Research, 1(9), 688-692.

[144] Mondore, S., Douthitt, S., & Carson, M. (2011). Maximizing the impact and effectiveness of HR analytics to drive business outcomes. People and Strategy, 34(2), 1-20.

[145] Muhammad, R. N., Tasmin, R., & Nor Aziati, A. H. (2020). Sustainable competitive advantage of big data analytics in higher education sector: An overview. Journal of Physics: Conference Series, 1529(4), 421-457. https://doi.org/10.1088/1742-6596/1529/4/042100

[146] Naeem, M., Jamal, T., Diaz-Martinez, J., Butt, S. A., Montesano, N., Tariq, M. I., ... & De-La-Hoz-Valdiris, E. (2022). Trends and future perspective challenges in big data. Advances in Intelligent Data Analysis and Applications, 15(18), 309–325.

[147] Nicholls, J., Hair, J. F., Ragland, C. B., & Schimmel, K. E. (2013). Ethics, corporate social responsibility, and sustainability education in AACSB undergraduate and graduate marketing curricula: A benchmark study. Journal of Marketing Education, 35(2), 129-140. https://doi.org/10.1177/0273475313489557

[148] Nicola, M., O'Neill, N., Sohrabi, C., Khan, M., Agha, M., & Agha, R. (2020). Evidence based management guideline for the COVID-19 pandemic - Review article. International Journal of Surgery, 77(3), 206-216. https://doi.org/10.1016/j.ijsu.2020.04.001

[149] Opatha, H., & Uresha, K. (2020). HRM and its impact on employee happiness: An empirical study on Sri Lankan employees. Asian Journal of Social Sciences and Management Studies, 7(2), 114-123. https://doi.org/10.20448/journal.500.2020.72.114.123

[150] Opatha, H. (2020). HR analytics: A literature review and new conceptual model. International Journal of Scientific and Research Publications (IJSRP), 10(6), 130-141. https://doi.org/10.29322/ijsrp.10.06.2020.p10217

[151] Panayotopoulou, L., Vakola, M., & Galanaki, E. (2007). E-HR adoption and the role of HRM: Evidence from Greece. Personnel Review, 36(2), 277-294. https://doi.org/10.1108/00483480710726145

[152] Parry, E., & Tyson, S. (2011). Desired goals and actual outcomes of e-HRM. Human Resource Management Journal, 21(3), 335-354. https://doi.org/10.1111/j.1748-8583.2010.00149.x

[153] Peeters, T., Paauwe, J., & Van De Voorde, K. (2020). People analytics effectiveness: Developing a framework. Journal of Organizational Effectiveness, 7(2), 335-354. https://doi.org/10.1108/JOEPP-04-2020-0071

[154] Pfeffer, J., & Sutton, R. I. (2006). Management half-truths and nonsense: How to practice evidence-based management. California Management Review, 48(3), 77-100. https://doi.org/10.1177/000812560604800301

[155] Pipino, L. L., Lee, Y. W., Wang, R. Y., & Yang, R. Y. (2002). Data quality assessment, 45(4), 211-218. https://doi.org/doi:10.1145/505248.506010

[156] Provost, F., & Fawcett, T. (2013). Data science and its relationship to big data and data-driven decision making. Big Data, 1(1), 51-59. https://doi.org/10.1089/big.2013.1508

[157] Qamar, Y., & Samad, T. A. (2022). Human resource analytics: A review and bibliometric analysis. Personnel Review, 51(1), 251-283. https://doi.org/10.1108/PR-04-2020-0247

[158] Qureshi, T. M. (2020). HR analytics, fad or fashion for organizational sustainability. Advances in Science, Technology and Innovation, 1(2), 103-107. https://doi.org/10.1007/978-3-030-32922-8_9

[159] Rasmussen, T., & Ulrich, D. (2015). Learning from practice: How HR analytics avoids being a management fad. Organizational Dynamics, 44(3), 236-242.  https://doi.org/10.1016/j.orgdyn.2015.05.008

[160] Reay, T., Berta, W., & Kohn, M. K. (2009). What's the evidence on evidence-based management? Academy of Management Perspectives, 23(4), 236-242. https://doi.org/10.5465/AMP.2009.45590137

[161] Reddy, P. R., & Lakshmikeerthi, P. (2017). HR analytics'-An effective evidence based HRM tool. International Journal of Business and Management Invention, 6(7), 23-34.

[162] Richard, S. A., & Marilyn, M. H. (2002). Employee perceptions of the relationship between strategy, rewards and organizational performance. Journal of Business Strategies, 19(2), 115-139.

[163] Roshanghalb, A., Lettieri, E., Aloini, D., Cannavacciuolo, L., Gitto, S., & Visintin, F. (2018). What evidence on evidence-based management in healthcare? Management Decision, 56(10), 2069-2084. https://doi.org/10.1108/MD-10-2017-1022

[164] Rousseau, D. M. (2006). Is there such a thing as "evidence-based management"?  Academy of Management Review, 31(2), 256-269. https://doi.org/10.5465/AMR.2006.20208679

[165] Rousseau, D. M., & Barends, E. G. R. (2011). Becoming an evidence-based HR practitioner. Human Resource Management Journal, 21(3), 221-235. https://doi.org/10.1111/j.1748-8583.2011.00173.x

[166] Rousseau, D. M., & Gunia, B. C. (2016). Evidence-based practice: The psychology of EBP implementation. Annual Review of Psychology, 67(5) 667-692. https://doi.org/10.1146/annurev-psych-122414-033336

[167] Rousseau, D. M., & McCarthy, S. (2007). Educating managers from an evidence-based perspective. Academy of Management Learning and Education, 6(1), 84-101. https://doi.org/10.5465/AMLE.2007.24401705

[168] Russell, C., & Bennett, N. (2015). Big data and talent management: Using hard data to make the soft stuff easy. Business Horizons, 58(3), 237-242. https://doi.org/10.1016/j.bushor.2014.08.001

[169] Rynes, S. L., Giluk, T. L., & Brown, K. G. (2007). The very separate worlds of academic and practitioner periodicals in human resource management: Implications for evidence-based management. Academy of Management Journal, 50(5) 987-1008. https://doi.org/10.5465/AMJ.2007.27151939

[170] Rynes, S. L., Rousseau, D. M., & Barends, E. (2014). From the guest editors: Change the world: Teach evidence-based practice! Academy of Management Learning and Education, 13(3), 305-321. https://doi.org/10.5465/amle.2014.0203

[171] Salkind, N. J. (1997). Exploring research. Pearson Educación.

[172] Saltz, J. S. (2015). The need for new processes, methodologies and tools to support big data teams and improve big data project effectiveness. In Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015. https://doi.org/10.1109/BigData.2015.7363988

[173] Santoro, G., Fiano, F., Bertoldi, B., & Ciampi, F. (2019). Big data for business management in the retail industry. Management Decision, 57(8), 1980-1992. https://doi.org/10.1108/MD-07-2018-0829

[174] Sarstedt, M., Ringle, C. M., Smith, D., Reams, R., & Hair, J. F. (2014). Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers. Journal of Family Business Strategy, 5(1), 105-115. https://doi.org/10.1016/j.jfbs.2014.01.002

[175] Schiemann, W. A., Seibert, J. H., & Blankenship, M. H. (2018). Putting human capital analytics to work: Predicting and driving business success. Human Resource Management, 57(3), 795-807. https://doi.org/10.1002/hrm.21843

[176] Schramm, J. (2006). HR technology competencies: New Roles for HR Professionals. SHRM Research Quarterly, 1(3), 1-11.

[177] Seref, S., & Duygu, S. (2013). Big data: A review. In 2013 International Conference on Collaboration Technologies and Systems (CTS) (pp. 42-47). IEEE.  https://doi.org/10.1109/CTS.2013.6567202

[178] Shabbir, M. Q., & Gardezi, S. B. W. (2020). Application of big data analytics and organizational performance: The mediating role of knowledge management practices. Journal of Big Data, 7(1), 1-17. https://doi.org/10.1186/s40537-020-00317-6

[179] Shamim, S., Zeng, J., Shariq, S. M., & Khan, Z. (2019). Role of big data management in enhancing big data decision-making capability and quality among Chinese firms: A dynamic capabilities view. Information and Management, 56(6), 1-16. https://doi.org/10.1016/j.im.2018.12.003

[180] Shankaranarayanan, G., & Cai, Y. (2006). Supporting data quality management in decision-making. Decision Support Systems, 42(1), 5-14. https://doi.org/10.1016/j.dss.2004.12.006

[181] Shet, S. V., Poddar, T., Wamba Samuel, F., & Dwivedi, Y. K. (2021). Examining the determinants of successful adoption of data analytics in human resource management – A framework for implications. Journal of Business Research, 131(7), 311-326. https://doi.org/10.1016/j.jbusres.2021.03.054

[182] Simón, C., & Ferreiro, E. (2018). Workforce analytics: A case study of scholar–practitioner collaboration. Human Resource Management, 57(3), 15-26. https://doi.org/10.1002/hrm.21853

[183] 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),7-16. https://doi.org/10.18267/j.aop.321

[184] Sirmon, D. G., & Hitt, M. A. (2003). Managing resources: Linking unique resources, management, and wealth creation in family firms. Entrepreneurship Theory and Practice, 27(4),71-80. https://doi.org/10.1111/1540-8520.t01-1-00013

[185] Sirmon, D. G., Hitt, M. A., & Ireland, R. D. (2007). Managing firm resources in dynamic environments to create value: Looking inside the black box. Academy of Management Review, 32(1), 40-65. https://doi.org/10.5465/AMR.2007.23466005

[186] Sivathanu, B., & Pillai, R. (2020). Technology and talent analytics for talent management – A game changer for organizational performance. International Journal of Organizational Analysis, 28(2), 12-22. https://doi.org/10.1108/IJOA-01-2019-1634

[187] Snell, S. A., Shadur, M. A., & Wright, P. M. (2002). Human resources strategy: The era of our ways. The Blackwell Handbook of Strategic Management, 4(8),631-653. https://doi.org/10.1111/b.9780631218616.2006.00024.x

[188] 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(2), 15-30. https://doi.org/10.1016/j.hrmr.2015.01.002

[189] Swan, J., Clarke, A., Nicolini, D., Powell, J., Scarbrough, H., Roginski, C., Gkeredakis, E., Mills, P., & Taylor-Phillips, S. (2012). Evidence in Management Decisions (EMD)-Advancing Knowledge Utilization in Healthcare Management, 1(1), 19-28.

[190] Teece, D. J. (1982). Towards an economic theory of the multiproduct firm. Journal of Economic Behavior and Organization, 3(1), 35-40. https://doi.org/10.1016/0167-2681(82)90003-8

[191] Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509-533.

[192] Tenenhaus, M., Esposito Vinzi, V., Chatelin, Y.-M., & Lauro, C. (2005). PLS path modeling. Computational Statistics & Data Analysis, 48(1), 159-205.

[193] Tomar, S., & Gaur, M. (2020). HR analytics in business: Role, opportunities, and challenges of using it.  Journal of Xi'an University of Architecture & Technology, 12(7), 1299-1306.

[194] Tonidandel, S., King, E. B., & Cortina, J. M. (2018). Big data methods: Leveraging modern data analytic techniques to build organizational science. Organizational Research Methods, 21(3), 448-483.https://doi.org/10.1177/1094428116677299

[195] Tripathi, K., & Agrawal, M. (2014). Competency based management in organizational context : A literature review. Global Journal of Finance and Management, 6(4), 355-364.

[196] Tursunbayeva, A., Di Lauro, S., & Pagliari, C. (2018). People analytics—A scoping review of conceptual boundaries and value propositions. International Journal of Information Management, 8(43), 70-81. https://doi.org/10.1016/j.ijinfomgt.2018.08.002

[197] Ulrich, D., & Dulebohn, J. H. (2015). Are we there yet? What's next for HR?  Human Resource Management Review, 25(2), 188-204. https://doi.org/10.1016/j.hrmr.2015.01.004

[198] Van den Heuvel, S., & Bondarouk, T. (2017). The rise (and fall?) of HR analytics: A study into the future application, value, structure, and system support. Journal of Organizational Effectiveness, 4(2), 157-178. https://doi.org/10.1108/JOEPP-03-2017-0022

[199] Van der Togt, J., & Rasmussen, T. H. (2017). Toward evidence-based HR. Journal of Organizational Effectiveness, 4(2), 127–132. https://doi.org/10.1108/JOEPP-02-2017-0013

[200] Van Esch, P., & Black, J. S. (2019). Factors that influence new generation candidates to engage with and complete digital, AI-enabled recruiting. Business Horizons, 62(6), 729-739. https://doi.org/10.1016/j.bushor.2019.07.004

[201] Vidgen, R., Shaw, S., & Grant, D. B. (2017). Management challenges in creating value from business analytics. European Journal of Operational Research, 261(2), 626-639.  https://doi.org/10.1016/j.ejor.2017.02.023

[202] Walshe, K., & Rundall, T. G. (2001). Evidence-based management: From theory to practice in health care. Milbank Quarterly, 79(3), 429-457. https://doi.org/10.1111/1468-0009.00214

[203] Wan, T. T. H. (2006). Healthcare informatics research: From data to evidence-based management. Journal of Medical Systems, 30(1), 3-7. https://doi.org/10.1007/s10916-006-7397-9

[204] Wedel, M., & Kannan, P. K. (2016). Marketing analytics for data-rich environments. Journal of Marketing, 80(6), 97-121. https://doi.org/10.1509/jm.15.0413

[205] Wernerfelt, B. (1984). A resource‐based view of the firm. Strategic Management Journal, 5(2), 171-180. https://doi.org/10.1002/smj.4250050207

[206] Wetzels, M., Odekerken-Schröder, G., & Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Quarterly: Management Information Systems, 33(1), 177-195. https://doi.org/10.2307/20650284

[207] Yong, K. T., & Pheng, L. S. (2008). Organizational culture and TQM implementation in construction firms in Singapore. Construction Management and Economics, 26(3), 237-248. https://doi.org/10.1080/01446190701874397

[208] Yu, W., Wong, C. Y., Chavez, R., & Jacobs, M. A. (2021).Integrating big data analytics into supply chain finance: The roles of information processing and data-driven culture. International Journal of Production Economics, 236(1), 66-100. https://doi.org/10.1016/j.ijpe.2021.108135

[209] Zeidan, S., & Itani, N. (2020). HR analytics and organizational effectiveness. International Journal on Emerging Technologies, 11(2), 683–688.

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Journal of Chinese Human Resources Management, Electronic ISSN: 2040-8013 Print ISSN: 2040-8005, Published by Porcelain Publishing