Supply chain digitalization and transparency: the privacy calculus perspective

Purpose With the growing attention of stakeholders on supply chain transparency, organizations face critical decisions regarding the disclosure of suppliers. However, there is limited research on the relationship of supply chain digitalization with the disclosure of suppliers (i.e. upstream supply chain transparency). Therefore, this study aims to investigate the influence of supply chain digitalization on supply chain transparency, as well as the moderating mechanisms involved. Design/methodology/approach Drawing on privacy calculus theory, this study focuses on A-share listed manufacturing companies and examines the impact of supply chain digitalization on supply chain transparency. This study also considers the moderating effects of data security orientation and supplier concentration. Regression models are constructed to test hypotheses. Findings The empirical results indicate a negative relationship between supply chain digitalization and supply chain transparency. Moreover, the study reveals that data security orientation and supplier concentration can neutralize such a negative relationship. Originality/value This study contributes to the literature about supply chain digitalization and supply chain transparency while also expanding the application of privacy computing theory in the supply chain context. It also provides valuable managerial insights for decision-makers, including strengthening data security management and optimizing supplier management strategies.

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Institutions

Publication Details

Journal
Industrial Management & Data Systems
Published
2025-11-14
DOI
https://doi.org/10.1108/imds-06-2025-0834
Citations
1
Primary Topic
Food Supply Chain Traceability
Type
article
Field-Weighted Citation Impact
1.16
Controls
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article

Supply chain digitalization and transparency: the privacy calculus perspective

Jiachen Xie, Baofeng Huo, Lu Yang, Minhao Gu et al.
1 citations
Industrial Management & Data Systems
Food Supply Chain Traceability
1.16
article

Supply chain digitalization and transparency: the privacy calculus perspective

Jiachen Xie, Baofeng Huo, Lu Yang, Minhao Gu, Yanming Zhang
article en
1 citations

Abstract

Purpose With the growing attention of stakeholders on supply chain transparency, organizations face critical decisions regarding the disclosure of suppliers. However, there is limited research on the relationship of supply chain digitalization with the disclosure of suppliers (i.e. upstream supply chain transparency). Therefore, this study aims to investigate the influence of supply chain digitalization on supply chain transparency, as well as the moderating mechanisms involved. Design/methodology/approach Drawing on privacy calculus theory, this study focuses on A-share listed manufacturing companies and examines the impact of supply chain digitalization on supply chain transparency. This study also considers the moderating effects of data security orientation and supplier concentration. Regression models are constructed to test hypotheses. Findings The empirical results indicate a negative relationship between supply chain digitalization and supply chain transparency. Moreover, the study reveals that data security orientation and supplier concentration can neutralize such a negative relationship. Originality/value This study contributes to the literature about supply chain digitalization and supply chain transparency while also expanding the application of privacy computing theory in the supply chain context. It also provides valuable managerial insights for decision-makers, including strengthening data security management and optimizing supplier management strategies.

Industrial Management & Data Systems
Chongqing Technology and Business University (CN), Chongqing University (CN), Tianjin University (CN), Huazhong University of Science and Technology (CN), Zhejiang University (CN)
Openalex Percentile: Top 16%
Food Supply Chain Traceability
1.16
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Supply chain digitalization and transparency: the privacy calculus perspective — Jiachen Xie, Baofeng Huo, et al. · Industrial Management & Data Systems (2025) | TGRS Research Map | TGRS