APJIS Asia Pacific Journal of Information Systems


The Journal for Information Professionals

Asia Pacific Journal of Information Systems (APJIS), a Scopus and ABDC indexed journal, is a
flagship journal of the information systems (IS) field in the Asia Pacific region.

ISSN 2288-5404 (Print) / ISSN 2288-6818 (Online)

Editor : Seung Hyun Kim

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Current Issue

Date December 2023
Vol. No. Vol. 33 No. 4
DOI https://doi.org/10.14329/apjis.2023.33.4.1171
Page 1171~1187
Title Lessons Learned from Institutionalization of ML(Machine Learning) Supported HR Services in the Existence of Multiple Institutional Logics
Author Gyeung-min Kim, Heesun Kim
Keyword Machine Learning (ML), ML-supported HR Service, Technology Adoption, Organizational Change, Institutional Framework
Abstract This study explores how an organization has successfully implemented ML-supported HR services to resolve high employee turnover problems in the IT sector. The empirical setting of the research is contradicting institutional logics exist among technical, HR, and business groups regarding the ML model development and use of the model predictions in HR services. Institutional framework is used to identify the roles of organizational actors and the legitimacy structures in the organizational environments that can shape or constrain the ML led organizational changes. In institutional theories, technology adoption and organizational change are not only constrained by organizational context, but also fostered through organizational actors’ roles and efforts to increase the legitimacy for the change. This research found that when multiple contradicting institutional logics exist, legitimizing the establishment of an enabling environment for multiple logics to reconcile and for the project to move forward is critical. Industry-wide conditions, previous experiences with the pilot ML project, forming a TFT with clearly defined roles and responsibilities, and relevant KPIs are found to legitimize the HR team and the business division to collaborate with the technical personnel to launch ML-supported HR services.

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