Predicting HR Professionals’ Adoption of HR Analytics: An Extension of UTAUT Model

Ahmad, A. B., Butt, A. S., Chen, D., & Liu, B (2020). A mediated model of the effect of organizational culture on the intentions to engage in change-supportive behaviours: insights from the theory of planned behaviour. Journal of Management & Organization, 1-21. https://doi.org/10.1017/jmo.2020.4110.1017/jmo.2020.41 Search in Google Scholar

Ajzen, I. (1985). From intentions to actions: A theory of planned behaviour. In Action control (pp. 11-39). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-69746-3_210.1007/978-3-642-69746-3_2 Search in Google Scholar

Altalhi, M. (2021). Toward a model for acceptance of MOOCs in higher education: the modified UTAUT model for Saudi Arabia. Education and Information Technologies, 26(2), 1589-1605. https://doi.org/10.1007/s10639-020-10317-x10.1007/s10639-020-10317-x Search in Google Scholar

Ammenwerth, E. (2019). Technology acceptance models in health informatics: TAM and UTAUT. Stud Health Technol Inform, 263, 64-71. https://doi.org/10.3233/SHTI190111 Search in Google Scholar

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/10.1111/1748-8583.1209010.1111/1748-8583.12090 Search in Google Scholar

Attuquayefio, S., & Addo, H. (2014). Using the UTAUT model to analyze students’ ICT adoption. International Journal of Education and Development Using ICT, 10(3). https://www.learntechlib.org/p/148478/ Search in Google Scholar

Bankole, F. O., & Bankole, O. O. (2017). The effects of cultural dimension on ICT innovation: Empirical analysis of mobile phone services. Telematics and Informatics, 34(2), 490-505. https://doi.org/10.1016/j.tele.2016.08.00410.1016/j.tele.2016.08.004 Search in Google Scholar

Ben-Gal, H. C. (2019). An ROI-based review of HR analytics: practical implementation tools. Personnel Review 48(6),1429-1448. https://doi.org/10.1108/PR-11-2017-036210.1108/PR-11-2017-0362 Search in Google Scholar

Bindu, K. (2016). A Review of Poor HR Analytical Skills. International Journal of Innovative Research in Technology (IJIRT), 3 (1), 397-402. Search in Google Scholar

Borkovich, D. J., Skovira, R. J., & Breese-Vitelli, J. (2015). New technology adoption: embracing cultural influences. Issues in Information Systems, 16(3). https://doi.org/10.48009/3_iis_2015_138-14710.48009/3_iis_2015_138-147 Search in Google Scholar

Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295-336. Search in Google Scholar

Chin, W.W. (2010). How to write up and report PLS analyses. In: Handbook of Partial Least Squares, pp.655–690, Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32827-8_2910.1007/978-3-540-32827-8_29 Search in Google Scholar

Dwivedi, Y. K., Shareef, M. A., Simintiras, A. C., Lal, B., & Weerakkody, V. (2016). A generalised adoption model for services: A cross-country comparison of mobile health (m-health). Government Information Quarterly, 33(1), 174-187. https://doi.org/10.1016/j.giq.2015.06.00310.1016/j.giq.2015.06.003 Search in Google Scholar

Eskiler, E., Ekici, S., Soyer, F., & Sari, I. (2016). The relationship between organizational culture and innovative work behaviour for sports services in tourism enterprises. Physical Culture and Sport. Studies and Research, 69(1), 53-64. http://doi.org/10.1515/pcssr-2016-000710.1515/pcssr-2016-0007 Search in Google Scholar

Falk, R.F. and Miller, N.B. (1992). A Primer for Soft Modeling, University of Akron Press, Ohio, USA. Search in Google Scholar

Fernandez, V., & Gallardo-Gallardo, E. (2021). Tackling the HR digitalization challenge: key factors and barriers to HR analytics adoption. Competitiveness Review: An International Business Journal, 31(1) 162-187. https://doi.org/10.1108/CR-12-2019-016310.1108/CR-12-2019-0163 Search in Google Scholar

Fisk, R. P., Patricio, L., Lin, J. S. C., & Chang, H. C. (2011). The role of technology readiness in self-service technology acceptance. Managing Service Quality: An International Journal, 21(4), 424-444. https://doi.org/10.1108/0960452111114628910.1108/09604521111146289 Search in Google Scholar

Fitz-Enz, J. (2010). The new HR analytics: predicting the economicvalue of your company’s human capital investments. Amacom. Search in Google Scholar

Frambach, R.T. and Schillewaert, N. (2002). Organizational Innovation Adoption: A Multi-Level Framework of Determinants and Opportunities for Future Research. Journal of Business Research, 55, 163-176. https://doi.org/10.1016/S0148-2963(00)00152-110.1016/S0148-2963(00)00152-1 Search in Google Scholar

Gordon, G. G., & DiTomaso, N. (1992). Predicting corporate performance from organizational culture. Journal of Management Studies, 29(6), 783-798. https://doi.org/10.1111/j.1467-6486.1992.tb00689.x10.1111/j.1467-6486.1992.tb00689.x Search in Google Scholar

Hair Jr., J.F., Sarstedt, M., Ringle, C.M. and Gudergan, S.P. (2017). Advanced Issues in Partial Least Squares Structural Equation Modeling, Sage Publications, USA.10.1007/978-3-319-05542-8_15-1 Search in Google Scholar

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Planning, 46(1-2), 1-12. Https://doi.org/10.1016/j.lrp.2013.01.00110.1016/j.lrp.2013.01.001 Search in Google Scholar

Hair, J.F., Anderson, R.E., Tatham, R.L. and Black, W.C. (1998). Factorial Analysis. Multivariate Data Analysis, 5th ed., Prentice Hall, New Jersey. Search in Google Scholar

Hair, J. F., Hult, G. T. M., Ringle, C. M., and Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 3rd Ed., Sage: Thousand Oaks.10.1007/978-3-030-80519-7 Search in Google Scholar

Halper, F. (2014). Predictive analytics for business advantage. TDWI Research, 1-32. Available from https://vods.dm.ux.sap.com/previewhub/ITAnalyticsContentHubANZ/downloadasset.2014-03-mar-17-21.predictive-analytics-for-business-advantage-pdf.pdf Search in Google Scholar

Hofstede, G. (2001). Culture’s recent consequences: Using dimension scores in theory and research. International Journal of Cross Cultural Management, 1(1), 11-17. https://doi.org/10.1177%2F14705958011100210.1177/147059580111002 Search in Google Scholar

Kabra, G., Ramesh, A., Akhtar, P., & Dash, M. K. (2017). Understanding behavioural Intention to use information technology: Insights from humanitarian practitioners. Telematics and Informatics, 34(7), 1250-1261. https://doi.org/10.1016/j.tele.2017.05.01010.1016/j.tele.2017.05.010 Search in Google Scholar

Kariyapperuma, K. A. S. K. (2016). Role of organisational culture in open innovation: an empirical study of service sector organisations in Sri Lanka. Vidyodaya Journal of Management, 2(2), 55-76.10.31357/vjm.v2i2.3643 Search in Google Scholar

Khazanchi, S., Lewis, M. W., & Boyer, K. K. (2007). Innovation-supportive culture: The impact of organizational values on process innovation. Journal of Operations Management, 25(4), 871-884. https://doi.org/10.1016/j.jom.2006.08.00310.1016/j.jom.2006.08.003 Search in Google Scholar

Kline, R.B. (2011). Principles and Practice of Structural Equation Modelling, 3rd. ed., The Guilford Press. New York. Search in Google Scholar

Kock, N. (2015). Common method bias in PLS-SEM: a full collinearity assessment approach, International Journal of e-Collaboration (IJEC), 11(4),.1–10. http://doi.org/10.4018/ijec.201510010110.4018/ijec.2015100101 Search in Google Scholar

Liu, H., Ke, W., Wei, K. K., Gu, J., & Chen, H. (2010). The role of institutional pressures and organizational culture in the firm’s Intention to adopt internet-enabled supply chain management systems. Journal of Operations Management, 28(5), 372-384. https://doi.org/10.1016/j.jom.2009.11.01010.1016/j.jom.2009.11.010 Search in Google Scholar

Marler, J. H., & Boudreau, J. W. (2017). An evidence-based review of HR Analytics. The International Journal of Human Resource Management, 28(1), 3-26. https://doi.org/10.1080/09585192.2016.124469910.1080/09585192.2016.1244699 Search in Google Scholar

McAfee, A. (2002). The impact of enterprise information technology adoption on operational performance: An empirical investigation. Production and Operations Management, 11(1), 33-53. https://doi.org/10.1111/j.1937-5956.2002.tb00183.x10.1111/j.1937-5956.2002.tb00183.x Search in Google Scholar

Mohammed, D., & Quddus, A. (2019). HR Analytics: A modern tool in hr for predictive decision making. Journal of Management, 6(3). https://doi.org/10.34218/JOM.6.3.2019.00710.34218/JOM.6.3.2019.007 Search in Google Scholar

Mohtaramzadeh, M., Ramayah, T., & Jun-Hwa, C. (2018). B2B e-commerce adoption in Iranian manufacturing companies: Analyzing the moderating role of organizational culture. International Journal of Human–Computer Interaction, 34(7), 621-639. https://doi.org/10.1080/10447318.2017.138521210.1080/10447318.2017.1385212 Search in Google Scholar

O’Reilly III, C. A., Chatman, J., & Caldwell, D. F. (1991). People and organizational culture: A profile comparison approach to assessing person-organization fit. Academy of Management Journal, 34(3), 487-516. https://doi.org/10.5465/25640410.5465/256404 Search in Google Scholar

Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioural research: a critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879. https://doi.org/10.1037/0021-9010.88.5.87910.1037/0021-9010.88.5.879 Search in Google Scholar

Ringle, C. M., Sarstedt, M., & Straub, D. W. (2012). Editor’s comments: a critical look at the use of PLS-SEM in” MIS Quarterly”. MIS Quarterly, 36(1), iii-xiv. https://doi.org/10.2307/4141040210.2307/41410402 Search in Google Scholar

Sarstedt, M., Hair Jr., J.F., Cheah, J.H., Becker, J.M. and Ringle, C.M. (2019). How to specify, estimate, and validate higher-order constructs in PLS-SEM, Australasian Marketing Journal (AMJ), 27(3), 197–211. https://doi.org/10.1016/j.ausmj.2019.05.00310.1016/j.ausmj.2019.05.003 Search in Google Scholar

Srite, M. (2006). Culture as an explanation of technology acceptance differences: An empirical investigation of Chinese and US users. Australasian Journal of Information Systems, 14(1). https://doi.org/10.3127/ajis.v14i1.410.3127/ajis.v14i1.4 Search in Google Scholar

Sunny, S., Patrick, L., & Rob, L. (2019). Impact of cultural values on technology acceptance and technology readiness. International Journal of Hospitality Management, 77, 89-96. https://doi.org/10.1016/j.ijhm.2018.06.01710.1016/j.ijhm.2018.06.017 Search in Google Scholar

Talukder, M. (2012). Factors affecting the adoption of technological innovation by individual employees: An Australian Study. Procedia-Social and Behavioural Sciences, 40, 52-57. https://doi.org/10.1016/j.sbspro.2012.03.16010.1016/j.sbspro.2012.03.160 Search in Google Scholar

Tseng, S. M. (2017). Investigating the moderating effects of organizational culture and leadership style on IT-adoption and knowledge-sharing Intention. Journal of Enterprise Information Management. https://doi.org/10.1108/JEIM-04-2016-008110.1108/JEIM-04-2016-0081 Search in Google Scholar

Tsui, A. S., Wang, H., & Xin, K. R. (2006). Organizational culture in China: An analysis of culture dimensions and culture types. Management and Organization Review, 2(3), 345-376. https://doi.org/10.1111/j.1740-8784.2006.00050.x10.1111/j.1740-8784.2006.00050.x Search in Google Scholar

Van der Togt, J., & Rasmussen, T. H. (2017). Toward evidence-based HR. Journal of Organizational Effectiveness: People and Performance. https://doi.org/10.1108/JOEPP-02-2017-001310.1108/JOEPP-02-2017-0013 Search in Google Scholar

Vargas, R., Yurova, Y. V., Ruppel, C. P., Tworoger, L. C., & 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. https://doi.org/10.1080/09585192.2018.144618110.1080/09585192.2018.1446181 Search in Google Scholar

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.1192610.1287/mnsc.46.2.186.11926 Search in Google Scholar

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 425-478. https://doi.org/10.2307/3003654010.2307/30036540 Search in Google Scholar

Wandhe, P. (2020). HR Analytics: A Tool for Strategic Approach to HR Productivity. Available at SSRN 3700502. https://dx.doi.org/10.2139/ssrn.370050210.2139/ssrn.3700502 Search in Google Scholar

Wang, G., Lu, H., Hu, W., Gao, X., & Pishdad-Bozorgi, P. (2020). Understanding Behavioural Logic of Information and Communication Technology Adoption in Small-and Medium-Sized Construction Enterprises: Empirical Study from China. Journal of Management in Engineering, 36(6), 05020013. http://doi.org/10.1061/(asce)me.1943-5479.000084310.1061/(ASCE)ME.1943-5479.0000843 Search in Google Scholar

Weerakkody, V., Kapoor, K., Balta, M. E., Irani, Z., & Dwivedi, Y. K. (2017). Factors influencing user acceptance of public sector big open data. Production Planning & Control, 28(11-12), 891-905. https://doi.org/10.1080/09537287.2017.133680210.1080/09537287.2017.1336802 Search in Google Scholar