IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v208y2024ics0040162524005079.html
   My bibliography  Save this article

Exploring the individual adoption of human resource analytics: Behavioural beliefs and the role of machine learning characteristics

Author

Listed:
  • Hülter, Svenja M.
  • Ertel, Christian
  • Heidemann, Ansgar

Abstract

The technological capabilities of Human Resource Analytics (HRA), enhanced by recent innovations in Machine Learning (ML), offer exciting opportunities. However, organisations often fail to realise these potentials because of a limited understanding of why individuals choose to adopt or disregard respective tools. Prior research on innovation adoption offers preliminary insights but fails to aggregate the determinants of individual adoption into actionable suggestions for decisions in the ML adoption process. Our study applies focused interviews to examine non-ML experts' reasoning for using a specific tool tailored to a public sector organisation, which corresponds to the usual end-user perspective of ML-based HRA adoption. By drawing from the HRA adoption framework, provided by Vargas et al. (2018), we contribute to the literature by identifying relevant beliefs and experiences influencing one's intention to adopt ML-based HRA and by qualitatively linking these beliefs to ML characteristics such as transparency, automation and fairness. For practitioners, we provide actionable guidance emphasising the need to ensure fairness proactively, as interviewees do not consider this aspect when deciding to adopt ML-based HRA.

Suggested Citation

  • Hülter, Svenja M. & Ertel, Christian & Heidemann, Ansgar, 2024. "Exploring the individual adoption of human resource analytics: Behavioural beliefs and the role of machine learning characteristics," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
    • Handle: RePEc:eee:tefoso:v:208:y:2024:i:c:s0040162524005079
    DOI: 10.1016/j.techfore.2024.123709
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162524005079
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2024.123709?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Akio Kawasaki & Ming Hsin Lin & Noriaki Matsushima, 2014. "Multi‐Market Competition, R&D, and Welfare in Oligopoly," Southern Economic Journal, John Wiley & Sons, vol. 80(3), pages 803-815, January.
    2. Prikshat, Verma & Islam, Mohammad & Patel, Parth & Malik, Ashish & Budhwar, Pawan & Gupta, Suraksha, 2023. "AI-Augmented HRM: Literature review and a proposed multilevel framework for future research," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    3. Desouza, Kevin C. & Dawson, Gregory S. & Chenok, Daniel, 2020. "Designing, developing, and deploying artificial intelligence systems: Lessons from and for the public sector," Business Horizons, Elsevier, vol. 63(2), pages 205-213.
    4. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    5. Mula, Claire & Zybura, Nora & Hipp, Thomas, 2024. "From digitalized start-up to scale-up: Opening the black box of scaling in digitalized firms towards a scaling process framework," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    6. Anna Lena Hunkenschroer & Christoph Luetge, 2022. "Ethics of AI-Enabled Recruiting and Selection: A Review and Research Agenda," Journal of Business Ethics, Springer, vol. 178(4), pages 977-1007, July.
    7. Qing He & Terence Tai‐Leung Chong & Li Li & Jun Zhang, 2010. "A Competing Risks Analysis of Corporate Survival," Financial Management, Financial Management Association International, vol. 39(4), pages 1697-1718, December.
    8. Berkeley J. Dietvorst & Joseph P. Simmons & Cade Massey, 2018. "Overcoming Algorithm Aversion: People Will Use Imperfect Algorithms If They Can (Even Slightly) Modify Them," Management Science, INFORMS, vol. 64(3), pages 1155-1170, March.
    9. Oecd, 2010. "Improving Competition in Real Estate Transactions," OECD Journal: Competition Law and Policy, OECD Publishing, vol. 10(2), pages 75-125.
    10. Oecd, 2010. "Energy Security and Competition Policy," OECD Journal: Competition Law and Policy, OECD Publishing, vol. 11(1), pages 7-90.
    11. Kalinichenko L. L., 2010. "Competitiveness of Ukraine: problems and prospects," Вісник економіки транспорту і промисловості, CyberLeninka;Украинская государственная академия железнодорожного транспорта, issue 31, pages 96-101.
    12. Friedman, Nicola & Ormiston, Jarrod, 2022. "Blockchain as a sustainability-oriented innovation?: Opportunities for and resistance to Blockchain technology as a driver of sustainability in global food supply chains," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    13. Daniel W. Apley & Jingyu Zhu, 2020. "Visualizing the effects of predictor variables in black box supervised learning models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(4), pages 1059-1086, September.
    14. Oecd, 2010. "Competition in Bidding Markets," OECD Journal: Competition Law and Policy, OECD Publishing, vol. 10(1), pages 69-151.
    15. Pumplun, Luisa & Tauchert, Christoph & Heidt, Margareta, 2019. "A New Organizational Chassis for Artificial Intelligence - Exploring Organizational Readiness Factors," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 112582, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    16. L. Li, 2010. "Free Trade Networks with Imperfect Competition," Review of Business and Economic Literature, Intersentia, vol. 0(4), pages 416-438, December.
    17. Omrani, Nessrine & Rivieccio, Giorgia & Fiore, Ugo & Schiavone, Francesco & Agreda, Sergio Garcia, 2022. "To trust or not to trust? An assessment of trust in AI-based systems: Concerns, ethics and contexts," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    18. L. Li, 2010. "Free Trade Networks with Imperfect Competition," Review of Business and Economic Literature, Intersentia, vol. 55(4), pages 416-438, December.
    19. Daniel Formolo & Luiz P. L. De Oliveira & Marcelo Sobottka, 2010. "A Competitive Searching-Based Chaotic Cipher," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 21(11), pages 1377-1390.
    20. Oecd, 2010. "Competition and Sports: Key findings, summary and notes," OECD Roundtables on Competition Policy Papers 149, OECD Publishing.
    21. Kim, Doha & Song, Yeosol & Kim, Songyie & Lee, Sewang & Wu, Yanqin & Shin, Jungwoo & Lee, Daeho, 2023. "How should the results of artificial intelligence be explained to users? - Research on consumer preferences in user-centered explainable artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    22. Chatterjee, Sheshadri & Rana, Nripendra P. & Dwivedi, Yogesh K. & Baabdullah, Abdullah M., 2021. "Understanding AI adoption in manufacturing and production firms using an integrated TAM-TOE model," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. OGREAN Claudia, 2015. "Business Models To Meet The Challenges Of The Global Economy. A Literature Review," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 67(6), pages 127-146, December.
    2. Manis, K.T. & Madhavaram, Sreedhar, 2023. "AI-Enabled marketing capabilities and the hierarchy of capabilities: Conceptualization, proposition development, and research avenues," Journal of Business Research, Elsevier, vol. 157(C).
    3. Anton, Roman, 2015. "Monetary Development and Transmission in the Eurosystem," MPRA Paper 67323, University Library of Munich, Germany, revised 08 Oct 2015.
    4. Jessica Müller-Pérez & Viridiana Sarahí Garza-Muñiz & Ángel Acevedo-Duque & Elizabeth Emperatriz García-Salirrosas & Jorge Alberto Esponda-Pérez & Rina Álvarez-Becerra, 2022. "The Future of Tamaulipas MSMEs after COVID-19: Intention to Adopt Inbound Marketing Tools," Sustainability, MDPI, vol. 14(19), pages 1-18, October.
    5. Jan Jöhnk & Malte Weißert & Katrin Wyrtki, 2021. "Ready or Not, AI Comes— An Interview Study of Organizational AI Readiness Factors," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(1), pages 5-20, February.
    6. Yogesh K. Dwivedi & A. Sharma & Nripendra P. Rana & M. Giannakis & P. Goel & Vincent Dutot, 2023. "Evolution of Artificial Intelligence Research in Technological Forecasting and Social Change: Research Topics, Trends, and Future Directions," Post-Print hal-04292607, HAL.
    7. Gheorghe MINCULETE & Maria-Ana CHISEGA-NEGRILÃ, 2014. "Marketing Management Relational Approaches Focused on Consumer’s and Customer’s Needs and Desires," Economia. Seria Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 17(2), pages 325-346, December.
    8. Baudier, Patricia & Kondrateva, Galina & Ammi, Chantal, 2023. "Can blockchain enhance motivation to donate: The moderating impact of religion on donors' behavior in the USA's charity organizations," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    9. Tödtling, Franz & Auer, Alexander & Sinozic, Tanja, 2014. "Driving factors for cluster development - Which kind of spatial rootedness and change?," SRE-Discussion Papers 2014/06, WU Vienna University of Economics and Business.
    10. Mariani, Marcello M. & Machado, Isa & Magrelli, Vittoria & Dwivedi, Yogesh K., 2023. "Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions," Technovation, Elsevier, vol. 122(C).
    11. Wang, Guoqiang & Tan, Garry Wei-Han & Yuan, Yunpeng & Ooi, Keng-Boon & Dwivedi, Yogesh K., 2022. "Revisiting TAM2 in behavioral targeting advertising: A deep learning-based dual-stage SEM-ANN analysis," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    12. Anton, Roman, 2014. "Sustainable Intrapreneurship - The GSI Concept and Strategy - Unfolding Competitive Advantage via Fair Entrepreneurship," MPRA Paper 69713, University Library of Munich, Germany, revised 01 Feb 2015.
    13. Deriu, Valerio & Pozharliev, Rumen & De Angelis, Matteo, 2024. "How trust and attachment styles jointly shape job candidates’ AI receptivity," Journal of Business Research, Elsevier, vol. 179(C).
    14. Stepan Zemtsov & Vera Barinova & Alexey Pankratov & Evgeniy Kutsenko, 2016. "Potential High-Tech Ñlusters in Russian Regions: From Current Policy to New Growth Areas," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 10(3), pages 34-52.
    15. Iversen, Evald Bundgaard & Cuskelly, Graham, 2015. "Effects of different policy approaches on sport facility utilisation strategies," Sport Management Review, Elsevier, vol. 18(4), pages 529-541.
    16. repec:pra:mprapa:67187 is not listed on IDEAS
    17. Thompson, Ian & Pech, Richard & Oh, Kok Boon & Marjoribanks, Timothy, 2016. "An assessment of delivery changes for UK terminal air navigation services," Journal of Air Transport Management, Elsevier, vol. 57(C), pages 155-167.
    18. Kim, Jiwhan & Nam, Changi, 2019. "Analyzing continuance intention of recommendation algorithms," 30th European Regional ITS Conference, Helsinki 2019 205190, International Telecommunications Society (ITS).
    19. Manuela Jr., Wilfred S. & Rhoades, Dawna L. & Curtis, Tamilla, 2016. "An analysis of Delta Air Lines' oil refinery acquisition," Research in Transportation Economics, Elsevier, vol. 56(C), pages 50-63.
    20. Maria Andersson & Ola Eriksson & Chris Von Borgstede, 2012. "The Effects of Environmental Management Systems on Source Separation in the Work and Home Settings," Sustainability, MDPI, vol. 4(6), pages 1-17, June.
    21. Tran Huy Phuong & Thanh Trung Hieu, 2015. "Predictors of Entrepreneurial Intentions of Undergraduate Students in Vietnam: An Empirical Study," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 5(8), pages 46-55, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:208:y:2024:i:c:s0040162524005079. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.