Characteristics and Trends in Big Data for Service Operations Management Research: A Blend of Descriptive and Bibliometric Analysis

Vincent Charles*, Tatiana Gherman, Ali Emrouznejad

*Corresponding author for this work

Research output: Contribution to Book/ReportChapterpeer-review

Abstract

The field of service operations management has a plethora of research opportunities to capitalise on, which are nowadays heightened by the presence of big data. In this research, we review and analyse the current state-of-the-art of the literature on big data for service operations management. To this aim, we use the Scopus database and the VOSviewer visualisation software for bibliometric analysis to highlight developments in research and application. Our analysis reveals patterns in scientific outputs and serves as a guide for global research trends in big data for service operations management. Some exciting directions for the future include research on building big data-driven analytical models which are deployable in the Cloud, as well as more interdisciplinary research that integrates traditional modes of enquiry with for example, behavioural approaches, with a blend of analytical and empirical methods.
Original languageEnglish
Title of host publicationBig Data and Blockchain for Service Operations Management
EditorsAli Emrouznejad, Vincent Charles
PublisherSpringer
Chapter1
Number of pages17
ISBN (Print)9783030873035
Publication statusAccepted/In press - 30 Sep 2021

Publication series

NameInternational Series in Studies in Big Data

Fingerprint

Dive into the research topics of 'Characteristics and Trends in Big Data for Service Operations Management Research: A Blend of Descriptive and Bibliometric Analysis'. Together they form a unique fingerprint.

Cite this