Please use this identifier to cite or link to this item:
Title: Big Data in an HR context: Exploring organizational change readiness, employee attitudes and behaviors
Authors: Shah, N
Irani, Z
Sharif, AM
Keywords: Organizational change;Employee readiness;Job satisfaction;Extrinsic and intrinsic satisfaction;Big data;HR predictive analytics
Issue Date: 2016
Publisher: Elsevier
Citation: Journal of Business Research, (2016)
Abstract: 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 behaviours and attitudes in the context of organisational 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 behaviours 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.
ISSN: 0148-2963
Appears in Collections:Brunel Business School Research Papers

Files in This Item:
File Description SizeFormat 
Fulltext.doc316 kBMicrosoft WordView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.