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Digital Technologies and Supply Chain Sustainability: Signalling, Disclosure, and Traceability

Vinayavekhin, S. (2024). Digital Technologies and Supply Chain Sustainability: Signalling, Disclosure, and Traceability. (Unpublished Doctoral thesis, City, University of London)

Abstract

In supply chain management (SCM), digital technologies have been integrated to shape sustainability practices. This dissertation comprises three distinctive papers that examine how digital technologies influence sustainable practices in supply chains.

The first paper is a systematic literature review (SLR) of signalling theory applications in SCM research. Despite then widespread use of signalling theory in SCM, a study of its applications has been lacking. This paper identifies seven core elements of signalling theory: signaller, receiver, signal, feedback, signalling process, signalling outcome, and signalling environment. It then responds to current industry priorities, emphasising the increasing reliance on digital technology solutions to enhance insights, fortify sustainability efforts, and mitigate supply chain risks. Finally, it proposes avenues for future research that leverage signalling theory to provide new insights into diverse phenomena and contribute to the advancement of SCM practices.

The second paper explores how buyers assess the importance of different attributes of supply chain sustainability disclosed by suppliers. These attributes encompass the nature of disclosure, method of verification, scope of disclosure, and attributes associated with blockchain-based information disclosure. Drawing on signalling theory and inter-organisational trust concepts, this research uses a choice-based conjoint experimental design to collect responses from managers with procurement responsibilities. The findings underscore the significance of how sustainability information is disclosed, emphasising buyer trust in self-disclosure and a preference for comprehensive, regularly updated information. This paper reveals that buyers prefer suppliers with sustainability signals spanning different types of disclosure and methods, clarifying the nuanced dynamics of buyer preferences and their willingness to pay.

The third paper investigates the adoption of digital traceability systems for managing greenhouse gas (GHG) emissions in complex supply chains. Drawing on technology adoption and supply chain complexity literature, the paper categorises influential factors into technology characteristics and supply chain complexity. Specifically, for supply chain complexity, this paper builds on the tenets of system theory and explores three dimensions of complexity: detailnumerosity, detail-variety, and dynamic at two levels of analysis: internal operations and upstream supply chains. Through a choice-based conjoint experimental design involving manufacturing sector managers, the findings reveal critical factors influencing firms' consideration for implementing digital traceability systems. This includes lower technology costs, shorter implementation time, and the comprehensive coverage of scope 1, 2, and 3 emissions. The nuanced impact of the dynamic dimension on internal operations and the upstream supply chain emphasises the multifaceted nature of supply chain complexity.

Overall, this dissertation makes significant contributions across three literature domains. In terms of signalling theory, this dissertation extends its application in SCM, uncovering SCMspecific factors and suggesting future directions for digital and sustainable supply chain research. For sustainable supply chain literature, empirical evidence is provided for sustainable supply chain transparency and traceability. Finally, in technology adoption literature, the role of supply chain technologies is explored, highlighting the influence of supply chain characteristics such as complexity on technology adoption. Areas for future research are indicated the end of each chapter and in the conclusions.

Publication Type: Thesis (Doctoral)
Subjects: T Technology > T Technology (General)
Departments: Bayes Business School > Bayes Business School Doctoral Theses
Bayes Business School > Management
Doctoral Theses
[thumbnail of Vinayavekhin thesis 2024 redacted PDF-A.pdf] Text - Accepted Version
This document is not freely accessible until 31 May 2027 due to copyright restrictions.

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