- Title
- The best of times and the worst of times: empirical operations and supply chain management research
- Creator
- Melnyk, Steven A.; Flynn, Barbara B.; Awaysheh, Amrou
- Relation
- International Journal of Production Research Vol. 56, Issue 1-2, p. 164-192
- Publisher Link
- http://dx.doi.org/10.1080/00207543.2017.1391423
- Publisher
- Taylor & Francis
- Resource Type
- journal article
- Date
- 2018
- Description
- We assess the current state of empirical research in operations and supply chain management (OSM), using Dickens’ contrast between the best of times and the worst of times as a frame. The best of times refers to the future that empirical OSM research is now entering, with exciting opportunities available using big data and other new data sources, new empirical approaches and analytical techniques and innovative tools for developing theory. These are well aligned with new research questions related to the digital economy, Industry 4.0, the impact of the millennial generation as consumers, social media, 3D printing, etc. However, we also explore how it is the worst of times, focusing on the challenges and problems that plague empirical OSM research. Our goal is to show how OSM researchers can learn from the worst of times, in order to be poised to take advantage of the best of times. We introduce the research diamond as a vehicle for emphasising the importance of a balanced research perspective that treats the research problem, theory, data collection and data analysis as equally important, requiring alignment between them. By learning and addressing the issues in this period of the best of times and the worst of times, we can take advantage of the opportunities facing our field to generate research that is balanced, insightful, rigorous, relevant, impactful and interesting.
- Subject
- operations management; supply chain management; empirical study; big data; economics; behavioral operations management; SDG 3; SDG 9; Sustainable Development Goals
- Identifier
- http://hdl.handle.net/1959.13/1441479
- Identifier
- uon:41439
- Identifier
- ISSN:0020-7543
- Language
- eng
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