A perspective on applications of in-memory analytics in supply chain management

作者:

Highlights:

• In-memory analytics applications in SCM can be structured along four use cases.

• Real-time analytics is the predominant focus of emerging in-memory applications.

• Integrated data models further support functional integration in adjacent domains.

• Emerging applications do not substitute but complement current APS systems.

• A stochastic planning approach in APS systems still remains open for research.

摘要

Big data, advanced analytics, and in-memory database technology are on the agenda of top management since they are seen as key enablers for enhanced business decision-making. In this paper, we provide a comprehensive perspective on applications of in-memory analytics in the field of supply chain management (SCM) that use the aforementioned concepts. Our contribution is threefold: First, we develop a top-down framework to position in-memory analytics applications against extant IT systems in SCM. Second, we conduct a bottom-up categorization of 41 in-memory analytics applications in SCM to provide supporting empirical evidence of the efficacy of the framework. Third, by contrasting top-down and bottom-up perspectives we derive implications for research and industrial practice.

论文关键词:Business analytics,In-memory database systems,Supply chain management,Advanced planning,Business intelligence

论文评审过程:Available online 9 January 2015, Version of Record 12 July 2015.

论文官网地址:https://doi.org/10.1016/j.dss.2015.01.003