DATAFICATION IN HRM: Implications of technological evolution in people management
DOI:
https://doi.org/10.13037/gr.vol42.e202610034Keywords:
Datafication, Algorithmic Decision, Control, Surveillance, DehumanizationAbstract
Human Resource Management, as well as other organizational units, are in full technological evolution, and the incorporation of data analysis, known as datafication, emerges as a significant trend. This study investigates the implications of this datafication in Human Resource Management, exploring its potential to optimize and challenge organizational processes. Through a literature review, we analyzed 68 articles, the research aimed to identify the implications of the application of datafication in people management. The results reveal that, although data analysis promotes efficiency and provides valuable insights, it also raises concerns related to information security, the potential dehumanization of labor relations, and the risk of excessive surveillance. It is concluded that the technological evolution of HRM demands a parsimonious approach that maximizes the benefits of datafication without neglecting the ethical and human aspects of people management.
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References
Adams-Prassl, J., Rakshita, S., Abraha, H., & Silberman, M. S. (2024). Towards an International Standard for Regulating Algorithmic Management: A Blueprint. SSRN Electronic Journal.
Alaimo, C. (2022). From People to Objects: The digital transformation of fields. Organization Studies, 43(7), 1091-1114.
Alaimo, C., & Kallinikos, J. (2024). Data Rules: Reinventing the Market Economy (Issue July). The MIT Press.
Arcidiacono, D., & Sartori, L. (2024). Algorithmic Management: Invisible Boss or Ghost Work? In Disruptive Digitalisation and Platforms (pp. 77-99). Routledge.
Aria, M., & Cucurullo, C. (2008). Bibliometrix. https://bibliometrix.org/index.html
Ayokanmbi, F. M. (2021). The impact of big data analytics on decision-making. International Journal of Management, IT, and Engineering, 11(4), 1-5.
Bahuguna, P. C., Srivastava, R., & Tiwari, S. (2024). Human resources analytics: where do we go from here? Benchmarking, 31(2), 640-668.
Bal, M., Brookes, A., Hack-Polay, D., Kordowicz, M., & Mendy, J. (2023). From Hypernormalization of Workplace Inequality to Dehumanization: A Way Out for Human Resource Management. In The Absurd Workplace (pp. 79-115). Springer International Publishing.
Baldissarri, C., Valtorta, R. R., Andrighetto, L., & Volpato, C. (2017). Workers as objects: The nature of working objectification and the role of perceived alienation. TPM - Testing, Psychometrics, Methodology in Applied Psychology, 24(2), 153-166.
Baumgart, L., Boos, P., & Eckstein, B. (2023). Datafication and algorithmic contingency - how agile organisations deal with technical systems. Work Organisation, Labour & Globalisation, 17(1).
Beer, D. (2017). Envisioning the power of data analytics. Information, Communication & Society, 21(3), 1-16.
Begkos, C., Antonopoulou, K., & Ronzani, M. (2024). To datafication and beyond: Digital transformation and accounting technologies in the healthcare sector. British Accounting Review, 56(4), 101259.
Blattner, L., Nelson, S., & Spiess, J. (2024). Unpacking the Black Box: Regulating Algorithmic Decisions. In General Economics (pp. 1-39).
Böhmer, N., & Schinnenburg, H. (2023). Critical exploration of AI-driven HRM to build up organizational capabilities. Employee Relations, 45(5), 1057-1082.
Brison, N., Stinglhamber, F., & Caesens, G. (2022). Organizational Dehumanization. In Oxford Research Encyclopedia of Psychology. Oxford University Press.
Bucher, E. L., Schou, P. K., & Waldkirch, M. (2021). Pacifying the algorithm - Anticipatory compliance in the face of algorithmic management in the gig economy. Organization, 28(1), 44-67.
Calzada, I. (2024). Democratic Erosion of Data-Opolies: Decentralized Web3 Technological Paradigm Shift Amidst AI Disruption. Big Data and Cognitive Computing, 8(3).
Carmichael, D. G. (2018). Organisations as systems - difficulties in model development and validation. Civil Engineering and Environmental Systems, 35(1-4), 41-56.
Christenson, A. P., & Goldstein, W. S. (2022). Impact of data analytics in transforming the decision-making process. Business & IT, XII(1), 74-82.
Cieslik, K., & Margocsy, D. (2022). Datafication, Power and Control in Development: A Historical Perspective on the Perils and Longevity of Data. Progress in Development Studies, 22(4), 352-373.
Congiu, L., & Moscati, I. (2022). A review of nudges: Definitions, justifications, effectiveness. Journal of Economic Surveys, 36(1), 188-213.
Cöster, M., Danielson, M., Ekenberg, L., Gullberg, C., Titlestad, G., Westelius, A., & Wettergren, G. (2023). 4. The Organisation of Digitisation (pp. 77-124).
Dasari, S. R., & Devi, V. R. (2024). Organizational Adoption Factors of HR Analytics: A Practitioner's Perspective. Management and Labour Studies.
Davenport, T. H., & Mittal, N. (2023). All in on AI: How Smart Companies Win Big with Artificial Inteligence. Harvard Business Scholl Plublishing. www.hbr.org
Devi, V. R. (2023). Addressing impediments to HR analytics adoption: guide to HRD professionals. Human Resource Development International, 1-10.
Edwards, M. R., Charlwood, A., Guenole, N., & Marler, J. (2022). HR analytics: An emerging field finding its place in the world alongside simmering ethical challenges. Human Resource Management Journal, December 2021, 1-11.
Espindola, D., & Wright, M. W. (2021). The Exponential Era: Strategies to Stay Ahead of the Curve in a Era os Chaotic Changes and Disruptive Forces. In The Exponential Era. John Wiley & Sons, Inc.
Ferrar, J., & Green, D. (2021). Excellence in People Analytics; How To Use Workforce Data to Create Business Value. Kogan Page Limited.
Ferrer-Conill, R., Sjøvaag, H., & Olsen, R. K. (2023). Datafied Societies: Digital Infrastructures, Data Power, and Regulations. Media and Communication, 11(2), 291-295.
Fisch, C., & Block, J. (2018). Six tips for your (systematic) literature review in business and management research. Management Review Quarterly, 68(2), 103-106.
Galhotra, S., Pradhan, R., & Salimi, B. (2021). Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals. Proceedings of the 2021 International Conference on Management of Data, 577-590.
Galliers, R. D., Newell, S., Shanks, G., & Topi, H. (2017). Datification and its human, organizational and societal effects: The strategic opportunities and challenges of algorithmic decision-making. Journal of Strategic Information Systems, 26(3), 185-190.
Gaur, D., Sharma, S. C., & Vij, A. (2024). People analytics: A future perspective. In V. K. Shukla, P. Kulkarni, D. Gaur, P. N., J. P. G. Lacap, & A. Omrane (Eds.), Industry 4.0 and People Analytics: A Technical Perspective of HRM (1st ed., pp. 299-309). Apple Academic Press Inc.
Giermindl, L. M. L. M. L. M., Strich, F., Christ, O., Leicht-Deobald, U., & Redzepi, A. (2022). The dark sides of people analytics: reviewing the perils for organisations and employees. European Journal of Information Systems, 31(3), 410-435.
Gobble, M. M. (2017). The Datification of Human Resources. Research-Technology Management, 60(5), 59-63. https://doi.org/10.1080/08956308.2017.1348143
Granulo, A., Caprioli, S., Fuchs, C., & Puntoni, S. (2023). Deployment of Algorithms in Management Tasks Reduces Prosocial Motivation. Computers in Human Behavi, 152(108094), 1-8.
Gupta, M., Hassan, Y., Pandey, J., & Kushwaha, A. (2022). Decoding the dark shades of electronic human resource management. International Journal of Manpower, 43(1), 12-31.
Gupta, R. (2024). Impact of Artificial Intelligence (AI) on Human Resource Management (HRM). In International Journal For Multidisciplinary Research (Vol. 6, Issue 3).
Hamilton, R. H., & Davison, H. K. (2022). Legal and Ethical Challenges for HR in Machine Learning. Employee Responsibilities and Rights Journal, 34(1), 19-39.
Hassenstein, M. J., & Vanella, P. (2022). Data Quality—Concepts and Problems. Encyclopedia, 2(1), 498-510. https://doi.org/10.3390/encyclopedia2010032
Heiland, H. (2022). Black Box Power: Zones of Uncertainty in Algorithmic Management. In Digital Platforms and Algorithmic Subjectivities (pp. 75-86). University of Westminster Press.
Helzlsouer, K., Meerzaman, D., Taplin, S., & Dunn, B. K. (2020). Humanizing Big Data: Recognizing the Human Aspect of Big Data. Frontiers in Oncology, 10(10), 186.
Henninger, A. (2024). Data Governance. Enablers, Inhibitors, Practices, and Outcomes.
Hoeyer, K., & Wadmann, S. (2020). 'Meaningless work': How the datafication of health reconfigures knowledge about work and erodes professional judgement. Economy and Society, 49(3), 433-454.
Horgan, L., & Dourish, P. (2018). Ambiguity, Ambivalence, and Activism: Data Organizing Inside the Institution. Krisis | Journal for Contemporary Philosophy, 38(1), 72-84.
Jansen, B. J., Aldous, K. K., Salminen, J., Almerekhi, H., & Jung, S. (2023). A Discussion of the Validity of Data Analytics. In Synthesis Lectures on Information Concepts, Retrieval, and Services (pp. 139-145).
Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577-586.
Jarrahi, M. H., Newlands, G., Lee, M. K., Wolf, C. T., Kinder, E., & Sutherland, W. (2021). Algorithmic management in a work context. Big Data & Society, 8(2), 205395172110203.
Jha, S. (2022). Data Privacy and Security Issues in HR Analytics: Challenges and the Road Ahead. In Expert Clouds and Application:Proceedings of ICOECA 2021 (pp. 199-206).
Kakulapati, V. (2021). Secure Privacy Analysis of HR Analytics—A Machine Learning Approach. In Intelligent Manufacturing and Energy Sustainability: Proceedings of ICIMES 2020 (1st ed., pp. 299-306). Springer.
Kalpokas, I. (2019). Data: The Premise of New Governance (pp. 11-25).
Khan, A. H. (2024). Effective Decision Making Using Data Analytics. International Journal of Scientific Research in Engineering and Management, 08(04), 1-5.
Kolb, D. G., Dery, K., Huysman, M., & Metiu, A. (2020). Connectivity in and around Organizations: Waves, tensions and trade-offs. Organization Studies, 41(12), 1589-1599.
Konovalova, V. G., Aghgashyan, R. V, & Galazova, S. S. (2021). Perspectives and Restraining Factors of HR Analytics in the Conditions of Digitization of Human Resources Management. In Socio-economic Systems: Paradigms for the Future (pp. 1015-1024).
Kumar, A. (2024). An Analysis of Artificial Intelligence Adoption in the Human Resource Management. International Journal of Scientific Research in Engineering and Management, 08(04), 1-5.
Kumar, G., Saha, R., Gupta, M., & Kim, T. H. (2024). BRON: A blockchained framework for privacy information retrieval in human resource management. Heliyon, 10(13), e33393.
Kumar, M., Shenbagaraman, V. M., Shaw, R. N., & Ghosh, A. (2020). Predictive Data Analysis for Energy Management of a Smart Factory Leading to Sustainability. In M. N. Favorskaya, S. Mekhilef, R. K. Pandey, & N. Singh (Eds.), Innovations in Electrical and Electronic Engineering (Vol. 661, pp. 765-773). Springer Singapore.
Lagios, C., Caesens, G., Nguyen, N., & Stinglhamber, F. (2022). Explaining the Negative Consequences of Organizational Dehumanization. Journal of Personnel Psychology, 21(2), 86-93.
Lagios, C., Nguyen, N., Stinglhamber, F., & Caesens, G. (2023). Dysfunctional rules in organizations: The mediating role of organizational dehumanization in the relationship between red tape and employees' outcomes. European Management Journal, 41(5), 802-813.
Lavazza, A., & Farina, M. (2023). Infosphere, Datafication, and Decision-Making Processes in the AI Era. Topoi, 42(3), 843-856.
Leonardi, P. M., & Treem, J. W. (2020). Behavioral Visibility: A new paradigm for organization studies in the age of digitization, digitalization, and datafication. Organization Studies, 41(12), 1601-1625.
Lukaszewski, K., Stone, D., & Johnson, R. (2016). Impact of Human Resource Information System Policies on Privacy. AIS Transactions on Human-Computer Interaction, 8(2), 58-73.
Mahmudi, B. (2024). Exploring the Landscape of Big Data Analytics in Financial Decision Making. Accounting Studies and Tax Journal (COUNT), 1(2), 167-177.
Mai, J. E. (2016). Big data privacy: The datafication of personal information. Information Society, 32(3), 192-199.
Manresa, A., Bikfalvi, A., Ligthart, P. E. M., & Kok, R. A. W. (2024). Insights into the digitalization-performance relationship: the role of flexibility and quality enhancing organizational practices. Production Planning & Control, 1-17.
Marjanovic, O., & Cecez-Kecmanovic, D. (2017). Exploring the tension between transparency and datification effects of open government IS through the lens of Complex Adaptive Systems. Journal of Strategic Information Systems, 26(3), 210-232.
Marler, J. H., & Boudreau, J. W. (2017). An evidence-based review of HR Analytics. International Journal of Human Resource Management, 28(1), 3-26.
Mazharunnisa, M., P Y, N., Apoorva, K., Poojasri, K., Jain, D., & Shalini, G. (2024). Blockchain In Human Resources: Ensuring Data Privacy And Transparency In Employee Management. 2024 2nd International Conference on Disruptive Technologies (ICDT), 90-95.
Megoran, N. (2022). Being 'human' under regimes of Human Resource Management: Using black theology to illuminate humanisation and dehumanisation in the workplace. African Journal of Business Ethics, 16(1).
Milan, S., & Beraldo, D. (2024). Data in movement: the social movement society in the age of datafication. Social Movement Studies, 23(3), 265-284.
Minbaeva, D. B. (2021). Disrupted HR? Human Resource Management Review, 31, 1-8.
Misut, M., & Jurik, P. (2021). Datafication as a Necessary Step in the Processing of Big Data in Decision-Making Tasks of Business. Proceedings of CBU in Natural Sciences and ICT, 2, 75-80.
Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Pettcrew, M., Shekekke, P., & Stewart, L. A. (2015). Preferred reporting items for systematic review and meta-analysis protocols. Systematic Reviews, 4(1), 1-9.
Mollick, E. (2024). Co-Intelligence: Living and Working with AI. Penguin Randon House LLC. https://lccn.loc.gov/202304947
Nawaz, N., Arunachalam, H., Pathi, B. K., & Gajenderan, V. (2024). The adoption of artificial intelligence in human resources management practices. International Journal of Information Management Data Insights, 4(1), 1-11.
Noponen, N., Feshchenko, P., Auvinen, T., Luoma-aho, V., & Abrahamsson, P. (2023). Taylorism on steroids or enabling autonomy? A systematic review of algorithmic management. Management Review Quarterly, 1-27.
Parth Chopra. (2023). Applications, Challenges, and Implications of data processing models in Human Capital Management. International Journal for Modern Trends in Science and Technology, 9(02), 26-32.
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.
Pellegrino, G. (2019). Inside "the Below": Ambivalences of Datafication and Infrastructuring of Everyday Life. 10(1), 89-96.
Piasna, A. (2024). Algorithms of time: how algorithmic management changes the temporalities of work and prospects for working time reduction. Cambridge Journal of Economics, 48(1), 115-132.
Rashmi, Sood, S., Prashar, T., Shravan, M., Sivaprasad, K. I., & Lourens, M. (2023). Blockchain and Data Privacy in Human Resource Management. 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 97-101.
Rasmussen, T. H., Ulrich, M., & Ulrich, D. (2024). Moving People Analytics From Insight to Impact. Human Resource Development Review, 0(0), 1-19.
Rigamonti, E., Colaiacovo, B., Gastaldi, L., & Corso, M. (2024). HR analytics and the data collection process: the role of attributions and perceived legitimacy in explaining employees' fear of datafication. Journal of Organizational Effectiveness.
Roberts, T., & Zheng, Y. (2022). Datafication, Dehumanisation and Participatory Development. In IFIP Advances in Information and Communication Technology: Vol. 657 IFIP (Issue March, pp. 377-396).
Rosanas, J. M. (2020). The dehumanization and demoralization of Management Control Systems: Can we possibly re-humanize and re- moralize them? European Accounting and Management Review, 6(2), 56-80.
Rubbab, E., Khattak, S. A., Shahab, H., & Akhter, N. (2022). Impact of Organizational Dehumanization on Employee Knowledge Hiding. Frontiers in Psychology, 13.
Salminen, J., Salminen, J., Milencović, M., & Jansen, B. J. (2017). Problems of data science in organizations: An explorative qualitative analysis of business professionals' concerns. International Conference on Eletronic Business, December, 192-201.
Schultz, M., Clegg, M., Hofstetter, R., & Seele, P. (2022). Managing Dehumanization? A Technology and Ethics Account on the Future of Work and Consumption. Academy of Management Proceedings, 2022(1).
Sharma, D. (2020). Hr Analytics As Catalyst for Transformation. The Straits of Success in a Vuca World, 12.
Stinglhamber, F., Nguyen, N., Ohana, M., Lagios, C., Demoulin, S., & Maurage, P. (2023). For whom and why organizational dehumanization is linked to deviant behaviours. Journal of Occupational and Organizational Psychology, 96(1), 203-229.
Strohmeier, S. (2022). Handbook of Artificial Intelligence in Human Resource Management. In Edward Elgar Publishing (Vol. 01, Issue 1). Edward Elgar Publishing.
Strong, D. M., Lee, Y. W., & Wang, R. Y. (1997). Data quality in context. Communications of the ACM, 40(5), 103-110.
Subramaniyan, S., Thite, M., & Sampathkumar, S. (2018). Information security and privacy in e-HRM. In e-HRM (pp. 250-267). Routledge.
Thaler, R. H., & Sunstein, C. R. (2008). Nudge:Improving Decisions about Helth, Wealth, and Happiness. In Revista Brasileira de Linguística Aplicada (Vol. 5, Issue 1). Caravan book. www.caravanbooks.org
Thorpe, M., & Sellar, S. (2023). Datafication. In International Encyclopedia of Education(Fourth Edition) (pp. 673-681). Elsevier.
Tranfield, D., Denyer, D., & Smart, P. (2003). A Systematic Review of Literature on Offshoring of Value Chain Activities. Journal of International Management, 14, 207-222.
Tursunbayeva, A. (2019). Human resource technology disruptions and their implications for human resources management in healthcare organizations. BMC Health Services Research, 19(1).
Tursunbayeva, A., Pagliari, C., Di Lauro, S., & Antonelli, G. (2021). The ethics of people analytics: risks, opportunities and recommendations. Personnel Review, 51(3), 900-921.
Vantrepotte, Q., Berberian, B., Pagliari, M., & Chambon, V. (2022). Leveraging human agency to improve confidence and acceptability in human-machine interactions. Cognition, 222(May 2021).
Varzoni, G., & Amorim, W. A. (2024). Relações de trabalho e gestão estratégica de recursos humanos sob o ponto de vista de empresas e sindicatos. Gestão & Regionalidade, 40, e20247979, (fluxo contínuo), 1-15.
Väyrynen, T., & Laari-Salmela, S. (2018). Men, Mammals, or Machines? Dehumanization Embedded in Organizational Practices. Journal of Business Ethics, 147(1), 95-113.
Vidhya K, D., & Sangeetha P, D. (2024). Futuristic Trends in Management Blockchain in HR: Secure Identity and Records. In Futuristic Trends in Management Volume 3 Book 28 (pp. 120-131). Iterative International Publisher, Selfypage Developers Pvt Ltd.
Vieira, A. M., Mendonça Neto, O. R., & Antunes, M. T. P. (2015). Aspectos da resistência na atividade docente. Educação e Pesquisa, 41(3), 743-56.
Wahdaniah, Sucianti, R., Ambalele, E., & Tellu, A. H. (2023). Human Resource Management Transformation in the Digital Age: Recent Trends and Implications.
Webster, J., & Watson, R. T. (2002). Analyzing the Past to Prepare for the Future: Writing a Literature Review. MIS Quarterly, 26(2), xiii-xxiii.
Zhao, Y. (2020). Application of K-means clustering algorithm in human resource data informatization. Proceedings of the 2020 International Conference on Cyberspace Innovation of Advanced Technologies, 12-16.
Zhou, Y., & Wang, Q. (2024). Algorithmic Decisions in Debt Collection. SSRN Electronic Journal.
ŽlahtiÄ, B., ZavrÅ¡nik, J., Blažun VoÅ¡ner, H., & Kokol, P. (2024). Transferring Black-Box Decision Making to a White-Box Model. Electronics, 13(10), 1895.
Zorić, A. B. (2019). Data science: fundamental principles. 19.
Zuboff, S. (2021). A era do capitalismo de vigilância: a luta por um futuro humano na nova fronteira do poder. Trad. G. Schlesinger. 1ª. ed. Rio de Janeiro: Intrínseca.
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