Why Empirical Research Is Good for Operations Management, and What Is Good Empirical Operations Management?

Fisher, Marshall L.; Olivares, Marcelo; Staats, Bradley R.

doi:10.1287/msom.2019.0812

Cited by 38 publications

(19 citation statements)

References 80 publications

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“…Informed by recent works (see, Terwiesch, 2019;Fisher et al 2019), our main contributions are as follows:…”

Section: Discussionmentioning

confidence: 99%

“…Operations management research has a long-standing tradition of providing mathematical models to help managers improve decisions. For instance inventory, transportation, revenue and labour staffing are some of the areas in which classical models have positively impacted on the operations management practices (Fisher et al 2019). It is well understood that data analysis is needed as an input in order to implement these models.…”

Section: Implications For Managerial Practicementioning

confidence: 99%

See 1 more Smart Citation

Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations

Dubey

Gunasekaran

Childe

et al. 2020

International Journal of Production Economics

459

256

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“…Informed by recent works (see, Terwiesch, 2019;Fisher et al 2019), our main contributions are as follows:…”

Section: Discussionmentioning

confidence: 99%

Section: Implications For Managerial Practicementioning

confidence: 99%

Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations

Dubey

Gunasekaran

Childe

et al. 2020

International Journal of Production Economics

459

256

View full text Add to dashboard Cite

show abstract

“…We believe that this framework would bridge the gap between the theory and practice. As rightly pointed out by Terwiesch ( 2019 ), Fisher et al ( 2020 ) and Dubey et al ( 2020 ), the primary objective of any theory-based study is to identify its relevance in the practical-world and explore the differences in theory and practice. Thus, we make an attempt to offer some practical implications of our study.…”

Section: Discussionmentioning

confidence: 99%

RETRACTED ARTICLE: Prescriptive analytics applications in sustainable operations research: conceptual framework and future research challenges

et al. 2023

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In the broad sphere of Analytics, prescriptive analytics is one of the emerging areas of interest for both academicians and practitioners. As prescriptive analytics has transitioned from its inception to an emerging topic, there is a need to review existing literature in order to ascertain development in this area. There are a very few reviews in the related field but not specifically on the applications of prescriptive analytics in sustainable operations research using content analysis. To address this gap, we performed a review of 147 articles published in peer-reviewed academic journals from 2010 to August 2021. Using content analysis, we have identified the five emerging research themes. Through this study, we aim to contribute to the literature on prescriptive analytics by identifying and proposing emerging research themes and future research directions. Based on our literature review, we propose a conceptual framework for studying the impacts of the adoption of prescriptive analytics and its impact on sustainable supply chain resilience, sustainable supply chain performance and competitive advantage. Finally, the paper acknowledges the managerial implications, theoretical contribution and the limitations of this study.

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“…Last but not least, consistent with the recent call by various studies for the use of archival data in supply chain research (e.g. Fisher et al , 2019; Terwiesch et al , 2019), this study uses secondary panel data on intangible supply chain complexity and organizational structure, which makes methodological contribution to the supply chain complexity literature.…”

Section: Research Implications and Limitationsmentioning

confidence: 83%

Intangible supply chain complexity, organizational structure and firm performance

Pant

Dutta

Sarmah

2021

IJLM

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PurposeThe purpose of this paper is to conduct a large-sample empirical examination of how intangible supply chain complexity impacts firm performance in light of a firm's organizational structure.Design/methodology/approachThe study uses panel data from 2,580 Indian manufacturing firms and constructs empirical proxy for intangible supply chain complexity, i.e. CHQ distance from major cities. The proposed conceptual model is grounded in the dynamic capability view (DCV) and social network theory (SNT). Multivariate regression analyses are performed to investigate the effect of intangible complexity on firm performance.FindingsResults show that intangible supply chain complexity, as proxied by “CHQ distance from major cities”, negatively affects firm performance and a firm's organizational structure plays an important role in conceiving CHQ locational strategies. Firms with interconnected supply chain and social network (e.g. business group firms) have a higher propensity to locate their CHQs farther away from major cities, and business group firms that have more distantly located CHQs experience better financial performance compared to independent firms (with less network resources).Originality/valueIn light of the supply chain literature and relevant theories, the study conceptualizes intangible supply chain complexity as “CHQ distance from major cities” and deepens our understanding of the relationship between intangible complexity and firm performance in light of organizational structure. Further, it develops an objective understanding of intangible supply chain complexity by relying on secondary panel data.

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Why Empirical Research Is Good for Operations Management, and What Is Good Empirical Operations Management?

Abstract: Empirical research in operations management has increased steadily over the last 20 years. In this paper, we discuss why this is good for our field and offer some comments on the qualities we admire in an empirical operations management paper.

Cited by 38 publications

References 80 publications

Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations

Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations

RETRACTED ARTICLE: Prescriptive analytics applications in sustainable operations research: conceptual framework and future research challenges

Intangible supply chain complexity, organizational structure and firm performance

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