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Article
Publication date: 7 May 2024

Giovanna Culot, Matteo Podrecca and Guido Nassimbeni

This study analyzes the performance implications of adopting blockchain to support supply chain business processes. The technology holds as many promises as implementation…

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Abstract

Purpose

This study analyzes the performance implications of adopting blockchain to support supply chain business processes. The technology holds as many promises as implementation challenges, so interest in its impact on operational performance has grown steadily over the last few years.

Design/methodology/approach

Drawing on transaction cost economics and the contingency theory, we built a set of hypotheses. These were tested through a long-term event study and an ordinary least squares regression involving 130 adopters listed in North America.

Findings

Compared with the control sample, adopters displayed significant abnormal performance in terms of labor productivity, operating cycle and profitability, whereas sales appeared unaffected. Firms in regulated settings and closer to the end customer showed more positive effects. Neither industry-level competition nor the early involvement of a project partner emerged as relevant contextual factors.

Originality/value

This research presents the first extensive analysis of operational performance based on objective measures. In contrast to previous studies and theoretical predictions, the results indicate that blockchain adoption is not associated with sales improvement. This can be explained considering that secure data storage and sharing do not guarantee the factual credibility of recorded data, which needs to be proved to customers in alternative ways. Conversely, improvements in other operational performance dimensions confirm that blockchain can support inter-organizational transactions more efficiently. The results are relevant in times when, following hype, there are signs of disengagement with the technology.

Details

International Journal of Operations & Production Management, vol. 44 no. 13
Type: Research Article
ISSN: 0144-3577

Keywords

Article
Publication date: 10 September 2024

Weihua Liu, Shangsong Long and Jingkun Wang

As a disruptive technology, blockchain technology brings new opportunities and challenges to operations management. We aim to examine the influences of blockchain cooperation…

Abstract

Purpose

As a disruptive technology, blockchain technology brings new opportunities and challenges to operations management. We aim to examine the influences of blockchain cooperation project announcements (BCPAs) on firms’ stock market reactions in an emerging market. From 2016 to 2021, a total of 113 BCPAs of listed firms from the Chinese A-share market are selected as samples.

Design/methodology/approach

This study is based on the loose coupling theory and uses the event study method and probit regression analysis.

Findings

We find BCPAs positively affect the firm’s stock price on the day they are released. Compared with vertical BCPAs in a supply chain, horizontal BCPAs exert a more positive market reaction. Moreover, a BCPA with a partner within a shorter geographical distance exerts a more positive influence on market reaction. Contrary to the intuition of the decentralized blockchain feature that one-to-many cooperation leads to better benefits, one-to-one BCPAs exert a more positive effect on market reaction than one-to-many BCPAs. We further find that (1) industry type has a certain impact on cooperation mode selection, and (2) manufacturing firms are more inclined to choose one-to-one cooperation than those in service industry.

Originality/value

We focus on the impact of blockchain cooperative announcements and additionally use the probit regression models to analyze the influencing factors of cooperation mode selection and find the critical role of the industry type, which complements the existing empirical research on blockchain announcements and is conducive to provide decision-making reference for managers.

Details

Industrial Management & Data Systems, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0263-5577

Keywords

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