Mapping domain characteristics influencing analytics initiatives: the example of supply chain analytics
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Purpose: Analytics research is increasingly divided by the domains in which Analytics is applied. Although the execution of Analytics initiatives is similar across domains and similar issues occur, current literature offers little understanding of whether the investigation of aspects such as success factors, barriers, and management of Analytics must be domain-specific. This article investigates characteristics of the execution of Analytics initiatives that are distinct within domains and can guide future research collaboration and focus. The research was conducted on the example of Logistics and Supply Chain Management and the respective domain-specific Analytics subfield of Supply Chain Analytics. The field of Logistics and Supply Chain Management was recognized as an early adopter of Analytics, but has fallen back to a midfield position in comparison to other domains. Design/methodology/approach: This research uses Grounded Theory based on 12 semi-structured interviews, creating a map of domain characteristics based of the paradigm scheme of Strauss and Corbin. Findings: The study identified a total of 34 characteristics of Analytics initiatives that distinguish domains in the execution of initiatives, which are mapped and explained. As a blueprint for further research, the domain specifics of Logistics and Supply Chain Management are presented and discussed. Originality/value: The results of this research should stimulate cross-domain research on Analytics issues and prompt further research on the identified characteristics for a broader understanding of their impact on Analytics initiatives. The study also describes the status quo in Analytics. Further, the results can help managers to control the environment of Analytics initiatives and design more successful initiatives.
CitationHerden, T. T. Mapping domain characteristics influencing analytics initiatives: the example of supply chain analytics. "Journal of Industrial Engineering and Management", Abril 2020, vol. 13, núm. 1, p. 56-78.