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The best of times and the worst of times: empirical operations and supply chain management research

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  • Steven A. Melnyk
  • Barbara B. Flynn
  • Amrou Awaysheh

Abstract

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.

Suggested Citation

  • Steven A. Melnyk & Barbara B. Flynn & Amrou Awaysheh, 2018. "The best of times and the worst of times: empirical operations and supply chain management research," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 164-192, January.
    • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:164-192
    DOI: 10.1080/00207543.2017.1391423
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    Cited by:

    1. Sunil Mithas & Yanzhen Chen & Yatang Lin & Alysson De Oliveira Silveira, 2022. "On the causality and plausibility of treatment effects in operations management research," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4558-4571, December.
    2. Cheng, Hao & Wu, Boyu & Jiang, Xiaokun, 2024. "Study on the spatial network structure of energy carbon emission efficiency and its driving factors in Chinese cities," Applied Energy, Elsevier, vol. 371(C).
    3. de Souza, Michele & Pereira, Giancarlo Medeiros & Lopes de Sousa Jabbour, Ana Beatriz & Chiappetta Jabbour, Charbel Jose & Trento, Luiz Reni & Borchardt, Miriam & Zvirtes, Leandro, 2021. "A digitally enabled circular economy for mitigating food waste: Understanding innovative marketing strategies in the context of an emerging economy," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    4. Jon Bokrantz & Jan Dul, 2023. "Building and testing necessity theories in supply chain management," Journal of Supply Chain Management, Institute for Supply Management, vol. 59(1), pages 48-65, January.
    5. Mansour Alyahya & Meqbel Aliedan & Gomaa Agag & Ziad H. Abdelmoety, 2023. "Understanding the Relationship between Big Data Analytics Capabilities and Sustainable Performance: The Role of Strategic Agility and Firm Creativity," Sustainability, MDPI, vol. 15(9), pages 1-17, May.

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