Charles, V., Gherman, T. and Emrouznejad, A. (2021) Characteristics and Trends in Big Data for Service Operations Management Research: A Blend of Descriptive and Bibliometric Analysis. In: Emrouznejad, A. and Charles, V. (eds.) Big Data and Blockchain for Service Operations Management :. Springer. (In Press)
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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.
Creators:
Charles, V., Gherman, T. and Emrouznejad, A.
Editors:
Emrouznejad, A. and Charles, V.
Publisher:
Springer
Faculties, Divisions and Institutes:
Date:
30 September 2021
Date Type:
Acceptance
Title of Book:
Big Data and Blockchain for Service Operations Management :
Series Name:
International Series in Studies in Big Data
Number of Pages:
17
Language:
English
ISBN:
9783030873035
Status:
In Press
Refereed:
Yes
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