Theorizing Supply Chains with Qualitative Big Data and Topic Modeling

Bansal, Pratima; Gualandris, Jury; Kim, Nahyun

doi:10.1111/jscm.12224

Cited by 35 publications

(28 citation statements)

References 49 publications

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“…Third, and related, we do not measure what intervening mechanisms explain the association between supply chain structure and supply chain transparency. As illustrated in recent research (Bansal et al, 2020), qualitative big data analyzed via unsupervised machine learning could help to disentangle these hidden mechanisms. For example, our findings on interconnectedness align well with the social theory of network closure proposed by Coleman (1990) and its application to collective action problems (Ostrom, 1998).…”

Section: Limitations and Future Developmentsmentioning

confidence: 99%

The association between supply chain structure and transparency: A large‐scale empirical study

Gualandris

Longoni

Luzzini

et al. 2021

J of Ops Management

Self Cite

102

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An emerging body of work acknowledges the challenges focal firms face in gathering material information about their extended supply chains and begins to point to the role of supply chain structure in influencing supply chain transparency. Still, large-scale empirical evidence on this complex association remains elusive, especially at the supply chain level of analysis. We begin to bridge this empirical gap by examining whether supply chain structure systematically associates to supply chain transparency in the context of the collective public environmental, social, and governance (ESG) disclosures made by a focal firm's customers, suppliers, and subsuppliers. To shed light on this underexplored empirical phenomenon, we gather Bloomberg SPLC data and Bloomberg ESG data about 4803 firms and 20,504 contractual ties organized in 187 extended supply chains. We find that supply chain density positively associates with supply chain transparency, whereas supply chain clustering holds a negative association. We also find that supply chain geographical heterogeneity positively associates with supply chain transparency. Our results significantly expand the literature on supply chain transparency and are relevant to supply chain professionals because they emphasize the central role of supply chain structure in enabling or constraining supply chain transparency.

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Section: Limitations and Future Developmentsmentioning

confidence: 99%

The association between supply chain structure and transparency: A large‐scale empirical study

Gualandris

Longoni

Luzzini

et al. 2021

J of Ops Management

Self Cite

102

View full text Add to dashboard Cite

show abstract

“…A general question is whether these various theoretical lenses can supplement each other and whether technological solutions may be applied to provide smallholder farmers and organizations in the Global South with a greater voice and improved stakeholder salience. Although these theories may be considered in future research, the lack of theoretical positioning in the research on the circular economy field is a major concern [ 20 ].…”

Section: Pathway (1): Connecting Output With Input Needs In a Global mentioning

confidence: 99%

From Sustainable Global Value Chains to Circular Economy—Different Silos, Different Perspectives, but Many Opportunities to Build Bridges

et al. 2021

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A growing interest in the circular economy concept has pushed the discourse in various management-related disciplines beyond established boundaries, with calls to better address how such a model may be developed in a world of global value chains. Still, the conventional linear economy model continues to dominate business, society, and research. While the concept of better connecting physical output and input flows at multiple production or consumption levels is becoming more accepted, it remains unclear how to make this happen while ensuring that sustainability targets are met or exceeded. Multiple scientific communities contribute different perspectives to this discourse, with promising opportunities for research. Circular economy and sustainability from business and economics perspectives are multifaceted. The existing body of knowledge needs to be advanced to assist private individuals, business managers, investors, or policymakers in making informed decisions. In this article for the inaugural issue, we provide a snapshot of the discourses among those who have studied the circular economy and its related topics. We outline conceptual inroads and potential research questions to encourage further circular economy and sustainability research and discourse from business or economics perspectives as well as from the broader transdisciplinary angle. We propose three research pathways: (1) connecting output with input needs in a global circular economy; (2) beyond today’s business logic for a global circular economy; and (3) inclusion of the Global South in North-dominated circular economies. For each, we propose concepts, theories, or methodological approaches and offer various perspectives from the micro, macro, and meso levels.

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“…Similarly, textual data from nontraditional sources of empirical evidence published by industry associations, NGOs, governments, and organizations can be a potent source of empirical evidence. In “Theorizing Supply Chains with Qualitative Big Data and Topic Modeling,” Tima Bansal, Jury Gualandris, and Nahyun Kim explore the application of topic modeling to develop supply chain theory from qualitative textual big data evidence (Bansal et al, 2020). New constructs emerge through machine learning analysis of co‐occurring words, using data visualization to reveal emergent relationships and understanding changes in relationships over time.…”

Section: Featured Articlesmentioning

confidence: 99%

From the Editors: Introduction to the Emerging Discourse Incubator on the Topic of Emerging Approaches for Developing Supply Chain Management Theory

Flynn

Pagell

Fugate

2020

J Supply Chain Manag

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The Journal of Supply Chain Management’s 2020 Emerging Discourse Incubator hopes to stimulate the development of supply chain specific theory. Well‐executed case‐based research will always be an appropriate means for developing supply chain theory. However, this EDI seeks to highlight emerging approaches to theory building that provide alternatives to case‐based research or can be used as a source of triangulation with it. To start that discourse, this issue offers three emergent approaches. In “Theorizing Supply Chains with Qualitative Big Data and Topic Modeling,” Tima Bansal, Jury Gualandris, and Nahyun Kim explore the application of topic modeling to develop supply chain theory from qualitative textual big data evidence. Anne Touboulic, Lucy McCarthy, and Lee Matthews illustrate the use of critical engaged research to develop supply chain theory in “Re‐Imagining Supply Chain Challenges Through Critical Engaged Research.” In “A New Methodology for Supply Chain Management: Discourse Analysis and its Potential for Theoretical Advancement,” Cynthia Hardy, Vikram Bhakoo, and Steve Maguire describe the potential for discourse analysis for developing supply chain management theory. These are but a few examples of potential approaches to developing supply chain theory. We welcome submissions on additional approaches and sources of data that are used in other disciplines, but have yet to be applied in the context of developing supply chain theory, and submissions on approaches that are emergent in the social sciences, in general. JSCM welcomes submissions for this EDI through the end of 2020.

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Theorizing Supply Chains with Qualitative Big Data and Topic Modeling

Cited by 35 publications

References 49 publications

The association between supply chain structure and transparency: A large‐scale empirical study

The association between supply chain structure and transparency: A large‐scale empirical study

From Sustainable Global Value Chains to Circular Economy—Different Silos, Different Perspectives, but Many Opportunities to Build Bridges

From the Editors: Introduction to the Emerging Discourse Incubator on the Topic of Emerging Approaches for Developing Supply Chain Management Theory

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