Big data in an HR context: Exploring organizational change readiness, employee attitudes and behaviors

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• 作者：Naimatullah Shah^a ; ^{Naimatullah.Shah@usindh.edu.pk" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Zahir Irani^b ; ^{Zahir.irani@brunel.ac.uk" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Amir M. Sharif^b ; ^{amir.sharif@brunel.ac.uk" class="auth_mail" title="E-mail the corresponding author}Author Vitae
• 关键词：Organizational change ; Employee readiness ; Job satisfaction ; Extrinsic and intrinsic satisfaction ; Big data ; HR predictive analytics
• 刊名：Journal of Business Research
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：70
• 期：Complete
• 页码：366-378
• 全文大小：628 K

文摘

This research highlights a contextual application for big data within a HR case study setting. This is achieved through the development of a normative conceptual model that seeks to envelop employee behaviors and attitudes in the context of organizational change readiness. This empirical application considers a data sample from a large public sector organization and through applying Structural Equation Modelling (SEM) identifies salary, job promotion, organizational loyalty and organizational identity influences on employee job satisfaction (suggesting and mediating employee readiness for organizational change). However in considering this specific context, the authors highlight how, where and why such a normative approach to employee factors may be limited and thus, proposes through a framework which brings together big data principles, implementation approaches and management commitment requirements can be applied and harnessed more effectively in order to assess employee attitudes and behaviors as part of wider HR predictive analytics (HRPA) approaches. The researchers conclude with a discussion on these research elements and a set of practical, conceptual and management implications of the findings along with recommendations for future research in the area.