A framework for investigating the role of big data in service parts management

Increased demand for responsive, cost efficient, and sustainable operations requires service parts consideration and adoption of new business models and solutions that span the entire life-cycle of products. Many firms are turning to big data analytics. Though service parts managers have long relied on analysis & optimization, big data analytics are considered to be more encompassing and thus especially promising. Herein, big data and its related applications are proposed as a means of improving service parts management practices. More specifically, data collected from interviews with service parts managers is used to construct a framework depicting the challenges of service parts management. This framework then serves as the basis for big data related proposals for overcoming the highlighted challenges. Thus, the research answers the call for service parts management related frameworks while providing a number of suggestions for managerial consideration and scholarly investigation. Published by Elsevier Ltd.