Information sharing through digitalisation in decentralised supply chains

Zissis, Dimitris ORCID: https://orcid.org/0000-0002-6957-3494 (2023) Information sharing through digitalisation in decentralised supply chains. Annals of Operations Research, 327 (2). 763–778. ISSN 0254-5330

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Abstract

This study investigates the impact of private information on decision making process and how emerging technologies can facilitate information sharing and reduce misinformation in decentralised settings. Focusing on business environments, we examine if information sharing between distinct partners can be a mutually beneficial option. In principle, information affects the preferences and the actions of decision makers and usually contributes to inefficiencies for the entire system. A supply chain with two rational firms is considered; the firms have conflicting objectives and possess information that cannot be verified. Real-time communication through a cloud platform is allowed, before the firms finalise their strategies. During the communication phase, both firms are free to report whatever information optimises their individual objectives, even fake. Misinformation seems a plausible option, especially in competitive environments, since the firms may take advantages from such behaviour. We demonstrate that sharing the actual information can be beneficial for both, under the implementation of an appropriate mechanism that considers the welfare of the entire chain. Despite the individualistic behaviour of independent decision makers, it is doable to eliminate entirely information asymmetry and misinformation. This happens by including sufficient incentives on a mechanism that induce firms to reveal their information, because it is in their self-interest to do so. The value of information and the expected benefits of the voluntary information sharing are calculated, indicating the potential improvement.

Item Type: Article
Uncontrolled Keywords: cloud platform technologies,coordination,incentive compatibility,mediator system,misinformation,win–win situation,decision sciences(all),management science and operations research ,/dk/atira/pure/subjectarea/asjc/1800
Faculty \ School: Faculty of Social Sciences > Norwich Business School
UEA Research Groups: Faculty of Social Sciences > Research Groups > Innovation, Technology and Operations Management
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 23 Jan 2023 15:30
Last Modified: 03 Aug 2023 08:31
URI: https://ueaeprints.uea.ac.uk/id/eprint/90705
DOI: 10.1007/s10479-022-05105-4

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