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

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Big Data and Blockchain for Service Operations Management

Part of the book series: Studies in Big Data ((SBD,volume 98))

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.

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Acknowledgements

The authors are thankful to the reviewers for their valuable comments on the previous version of this work.

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Correspondence to Vincent Charles .

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Charles, V., Gherman, T., Emrouznejad, A. (2022). Characteristics and Trends in Big Data for Service Operations Management Research: A Blend of Descriptive Statistics and Bibliometric Analysis. In: Emrouznejad, A., Charles, V. (eds) Big Data and Blockchain for Service Operations Management. Studies in Big Data, vol 98. Springer, Cham. https://doi.org/10.1007/978-3-030-87304-2_1

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