Factors Influencing the Adoption of Artificial Intelligence for Talent Acquisition in ITeS Organizations in Malaysia

Ilangovan Perumal, Partho Das, Sudhashini Nair, Kayalvily Tabiana, Stephen Sesaiah, Gopal Perumal

Abstract

Malaysia is an emerging economy worldwide, and talent acquisition plays a key role in the success of Malaysian IT and ITeS (Information Technology Enabled Services) organizations. AI-based technologies significantly contribute to attracting and hiring top talent while reducing overall costs and time. This research is intended to identify the factors affecting the adoption of AI for talent acquisition (ADP of AI for TA) in Malaysian IT and ITeS organizations. This study analyzes the ADP of AI for TA from an organizational perspective. Hence, this study investigated the views and opinions of all stakeholders in the human resource department of Malaysian IT and ITeS organizations. The study applied a quantitative approach to analyze data collected from 220 respondents using SPSS Version 29. The study used multiple regression analysis to investigate the relationship between the ADP of AI for TA and stickiness, relative advantage, HR readiness, and security and privacy concerns. The study found that the ADP of AI for TA is significantly affected by stickiness and relative advantage in Malaysian IT and ITeS organizations. The scientific novelty of the study lies in the test results concerning rationalization and ethical values, which contradict the findings of previous research. This investigation has significant implications for the field of study.

 

Keywords: Information Technology Enabled Services, Artificial intelligence, Talent acquisition, Human resource, Information technology.

 

DOI: https://doi.org/10.55463/hkjss.issn.1021-3619.63.36


Full Text:

PDF


References


AGARWAL, A. (2022). AI adoption by human resource management: a study of its antecedents and impact on HR system effectiveness. Foresight, 25(1), 67–81. https://doi.org/10.1108/fs-10-2021-0199

ALASHMAWY, A., & YAZDANIFARD, R. (2019). A Review of the Role of Marketing in Recruitment and Talent Acquisition. International Journal of Management, Accounting and Economics, 6(7), 569–581. Retrieved from https://www.ijmae.com/article_114604.html

BANDARA, U.C., & AMARASENA, T.S.M. (2018). Impact of Relative Advantage, Perceived Behavioural Control and Perceived Ease of Use on Intention to Adopt with Solar Energy Technology in Sri Lanka. Proceedings of the International Conference and Utility Exhibition on Green Energy for Sustainable Development, Phuket, 24-26 October 2018, pp. 1–9. https://doi.org/10.23919/ICUE-GESD.2018.8635706

BHAVE, D.P., TEO, L.H., & DALAL, R.S. (2019). Privacy at work: A review and a research agenda for a contested terrain. Journal of Management, 46(1), 127–164. https://doi.org/10.1177/0149206319878254

BILAL, H., & VARALLYAI, L. (2021). Artificial intelligence in talent acquisition, do we trust it? Journal of Agricultural Informatics, 12(1), 41–51. https://doi.org/10.17700/jai.2021.12.1.594

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

BUGHIN, J.R., KRETSCHMER, T., & VAN ZEEBROECK, N. (2019). Experimentation, learning and stress: The role of digital technologies in strategy change. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3328421

CHAM, T.H., CHEAH, J.H., CHENG, B.L., & LIM, X.J. (2021). I am too old for this! Barriers contributing to the non-adoption of mobile payment. International Journal of Bank Marketing, 40(5), 1017–1050. https://doi.org/10.1108/ijbm-06-2021-0283

CHATTERJEE, S., GHOSH, S.K., CHAUDHURI, R., & CHAUDHURI, S. (2021). Adoption of AI-integrated CRM system by Indian industry: From security and privacy perspective. Information & Computer Security, 29(1), 1–24. https://doi.org/10.1108/ics-02-2019-0029

CHRISTODOULAKIS, C., ASGARIAN, A., & EASTERBROOK, S. (2017). Barriers to adoption of information technology in healthcare. Proceedings of the 27th Annual International Conference on Computer Science and Software Engineering, Markham, 6-8 November 2017, pp. 66–75. Retrieved from https://dl.acm.org/doi/10.5555/3172795.3172804

CRUZ-JESUS, F., OLIVEIRA, T., & NARANJO, M. (2018). Understanding the Adoption of Business Analytics and Intelligence. Advances in Intelligent Systems and Computing, 745, 1094–1103. https://doi.org/10.1007/978-3-319-77703-0_106

DEROUS, E., & DE FRUYT, F. (2016). Developments in recruitment and selection research. International Journal of Selection and Assessment, 24(1), 1–3. https://doi.org/10.1111/ijsa.12123

DIGITAL NEWS ASIA (2019). AI to nearly double the rate of innovation in Malaysia by 2021. Retrieved from https://www.digitalnewsasia.com/digital-economy/ai-nearly-double-rate-innovation-malaysia-2021

DWIVEDI, Y.K., HUGHES, L., ISMAGILOVA, E., AARTS, G., COOMBS, C., CRICK, T., DUAN, Y., DWIVEDI, R., EDWARDS, J., EIRUG, A., GALANOS, V., ILAVARASAN, P.V., JANSSEN, M., JONES, P., KAR, A.K., KIZGIN, H., KRONEMANN, B., LAL, B., LUCINI, B., MEDAGLIA, R., LE MEUNIER-FITZHUGH, K., LE MEUNIER-FITZHUGH, L.C., MISRA, S., MOGAJI, E., SHARMA, S.K., SINGH, J.B., RAGHAVAN, V., RAMAN, R., RANA, N.P., SAMOTHRAKIS, S., SPENCER, J., TAMILMANI, K., TUBADJI, A., WALTON, P., & WILLIAMS, M.D. (2021). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002

ERRO-GARCES, A. (2019). Industry 4.0: Defining the research agenda. Benchmarking: An International Journal, 28(5), 1858–1882. https://doi.org/10.1108/bij-12-2018-0444

FRANKIEWICZ, B., & CHAMORRO-PREMUZIC, T. (2020). Digital transformation is about talent, not technology. Harvard Business Review. Retrieved from https://hbr.org/2020/05/digital-transformation-is-about-talent-not-technology

GILLESPIE, A., KRISHNA, M., OLIVER, C., OLSEN, K., & THIEL, M. (1999). Online behavior stickiness.

GRANDON, E.E., & PEARSON, J.M. (2004). Electronic commerce adoption: An empirical study of small and medium US businesses. Information & Management, 42(1), 197–216. https://doi.org/10.1016/j.im.2003.12.010

HOLMSTROM, J. (2022). From AI to Digital Transformation: The AI Readiness Framework. Business Horizons, 65(3), 329–339. https://doi.org/10.1016/j.bushor.2021.03.006

HSU, C.W., & YEH, C.C. (2017). Understanding the factors affecting the adoption of the internet of things. Technology Analysis & Strategic Management, 29(9), 1089–1102. https://doi.org/10.1080/09537325.2016.1269160

IFINEDO, P. (2011). An empirical analysis of factors influencing internet/e-business technologies adoption by SMEs in Canada. International Journal of Information Technology & Decision Making, 10(4), 731–766. https://doi.org/10.1142/s0219622011004543

INTERNATIONAL DATA CORPORATION (2021). Investment in Artificial Intelligence Solutions Will Accelerate as Businesses Seek Insights, Efficiency, and Innovation, According to a New IDC Spending Guide. Retrieved from https://www.businesswire.com/news/home/20210830005091/en/Investment-in-Artificial-Intelligence-Solutions-Will-Accelerate-as-Businesses-Seek-Insights-Efficiency-and-Innovation-According-to-a-New-IDC-Spending-Guide

JEDYNAK, M., CZAKON, W., KUŹNIARSKA, A., & MANIA, K. (2021). Digital transformation of organizations: What do we know and where to go next? Journal of Organizational Change Management, 34(3), 629–652. https://doi.org/10.1108/jocm-10-2020-0336

KHALID, M.A. (2021). Covid-19: Malaysia experience and key lessons. Asian Economic Papers, 20(2), 73–95. https://doi.org/10.1162/asep_a_00801

KIM, S., BAEK, T.H., KIM, Y.K., & YOO, K. (2016). Factors affecting stickiness and word of mouth in mobile applications. Journal of Research in Interactive Marketing, 10(3), 177–192. https://doi.org/10.1108/jrim-06-2015-0046

KITSIOS, F., & KAMARIOTOU, M. (2021). Artificial intelligence and business strategy towards digital transformation: a research agenda. Sustainability, 13(4), 2025. https://doi.org/10.3390/su13042025

KRETSCHMER, T., & KHASHABI, P. (2020). Digital transformation and organization design: An integrated approach. California Management Review, 62(4), 86–104. https://doi.org/10.1177/0008125620940296

LAURIM, V., ARPACI, S., PROMMEGGER, B., & KRCMAR, H. (2021). Computer, whom should I hire? – Acceptance criteria for artificial intelligence in the recruitment process. Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 5495-5504. https://doi.org/10.24251/hicss.2021.668

MALIK, A., PEREIRA, V., & BUDHWAR, P. (2021). HRM in the global information technology (IT) industry: Towards multivergent configurations in strategic business partnerships. Human Resource Management Review, 31(3), 100743. https://doi.org/10.1016/j.hrmr.2020.100743

MISHRA, P., PANDEY, C.M., SINGH, U., GUPTA, A., SAHU, C., & KESHRI, A. (2019). Descriptive statistics and normality tests for statistical data. Annals of Cardiac Anaesthesia, 22(1), 67-72. https://doi.org/10.4103/aca.aca_157_18

ORE, O., & SPOSATO, M. (2021). Opportunities and risks of artificial intelligence in recruitment and selection. International Journal of Organizational Analysis, 30(6), 1771–1782. https://doi.org/10.1108/ijoa-07-2020-2291

PAN, Y., FROESE, F., LIU, N., HU, Y., & YE, M. (2021). The adoption of artificial intelligence in employee recruitment: The influence of contextual factors. The International Journal of Human Resource Management, 33(6), 1125–1147. https://doi.org/10.1080/09585192.2021.1879206

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. https://doi.org/10.1108/bij-04-2020-0186

PUKLAVEC, B., OLIVEIRA, T., & POPOVIC, A. (2018). Understanding the determinants of business intelligence system adoption stages. Industrial Management & Data Systems, 118(1), 236–261. https://doi.org/10.1108/imds-05-2017-0170

PUMPLUN, L., TAUCHERT, C., & HEIDT, M. (2019). A new organizational chassis for artificial intelligence-exploring organizational readiness factors. Proceedings of the 27th European Conference on Information Systems, Stockholm & Uppsala, 8-14 June 2019, pp. 1-15. Retrieved from https://scholar.archive.org/work/ahgl6gh7zvhmdmoyoauitfvtaq/access/wayback/https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1105&context=ecis2019_rp

QUADDUS, M., & HOFMEYER, G. (2007). An investigation into the factors influencing the adoption of B2B trading exchanges in small businesses. European Journal of Information Systems, 16(3), 202–215. https://doi.org/10.1057/palgrave.ejis.3000671

QUEIROZ, M.M., PEREIRA, S.C., TELLES, R., & MACHADO, M.C. (2019). Industry 4.0 and digital supply chain capabilities. Benchmarking: An International Journal, 28(5), 1761–1782. https://doi.org/10.1108 /bij-12-2018-0435

RAHMAN, M.A., ISLAM, M.A., & QI, X. (2017). Barriers in adopting human resource information system (HRIS): An empirical study on selected Bangladeshi garments factories. International Business Research, 10(6), 98–103. https://doi.org/10.5539/ibr.v10n6p98

SALAM, M.A. (2019). Analyzing manufacturing strategies and Industry 4.0 supplier performance relationships from a resource-based perspective. Benchmarking: An International Journal, 28(5), 1697–1716. https://doi.org/10.1108/bij-12-2018-0428

SAVOLA, H., & TROQE, B. (2019). Recruiters just wanna have... AI?: Implications of implementing AI in HR recruitment. Master’s dissertation, Linkoping University. Retrieved from https://www.diva-portal.org/smash/record.jsf?pid=diva2%3A1333711&dswid=-6456

SEKARAN, U., & BOUGIE, R. (2016). Research Methods for Business: A Skill-Building Approach. 7th ed. West Sussex: Wiley & Sons.

SENARATHNA, I., YEOH, W., WARREN, M., & SALZMAN, S. (2016). Security and Privacy Concerns for Australian SMEs Cloud Adoption: Empirical Study of Metropolitan Vs Regional SMEs. Australasian Journal of Information Systems, 20, 1-20. https://doi.org/10.3127/ajis.v20i0.1193

SHAO, Z., ZHANG, L., CHEN, K., & ZHANG, C. (2020). Examining user satisfaction and stickiness in social networking sites from a technology affordance lens: Uncovering the moderating effect of user experience. Industrial Management & Data Systems, 120(7), 1331–1360. https://doi.org/10.1108/imds-11-2019-0614

TIWARI, P., RAJPUT, N., & GARG, V. (2022). Artificial Intelligence and Talent Acquisition-Role of HR Leaders in Adoption. Proceedings of the 3rd International Conference on Intelligent Engineering and Management, London, 27-29 April 2022, pp. 313–317. https://doi.org/10.1109/ICIEM54221.2022.9853104

TSAI, M.C., LEE, W., & WU, H.C. (2010). Determinants of RFID adoption intention: Evidence from Taiwanese retail chains. Information & Management, 47(5-6), 255–261. https://doi.org/10.1016/j.im.2010.05.001

VAN ESCH, P., BLACK, J.S., & FEROLIE, J. (2019). Marketing AI recruitment: The next phase in job application and selection. Computers in Human Behavior, 90, 215–222. https://doi.org/10.1016/j.chb.2018.09.009

VITENU-SACKEY, P.A., & BARFI, R. (2021). The impact of Covid-19 pandemic on the global economy: Emphasis on poverty alleviation and economic growth. The Economics and Finance Letters, 8(1), 32–43. https://doi.org/10.18488/journal.29.2021.81.32.43

VRONTIS, D., CHRISTOFI, M., PEREIRA, V., TARBA, S., MAKRIDES, A., & TRICHINA, E. (2021). Artificial intelligence, robotics, advanced technologies and human resource management: A systematic review. The International Journal of Human Resource Management, 33(6), 1237–1266. https://doi.org/10.1080/09585192.2020.1871398

WANG, H., BAH, M.J., & HAMMAD, M. (2019). Progress in Outlier Detection Techniques: A Survey. IEEE Access, 7, 107964–108000. https://doi.org/10.1109/access.2019.2932769

WUEST, T., KUSIAK, A., DAI, T., & TAYUR, S.R. (2020). Impact of Covid-19 on manufacturing and supply networks — the case for AI-inspired digital transformation. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3593540

ZAIED, A.N.H., GRIDA, M.O., & HUSSEIN, G.S. (2018). Evaluation of critical success factors for business intelligence systems using fuzzy AHP. Journal of Theoretical and Applied Information Technology, 96(19), 6406–6422. Retrieved from http://www.jatit.org/volumes/Vol96No19/12Vol96No19.pdf


Refbacks

  • There are currently no refbacks.