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Blockchain-enabled supply chain operations and financing: the perspective of expectancy theory.
- Source :
- International Journal of Operations & Production Management; 2023, Vol. 43 Issue 12, p1943-1975, 33p
- Publication Year :
- 2023
-
Abstract
- Purpose: This study examines the cognitive factors of adopting blockchain technology in various supply chain scenarios and its role in reframing the distinctive values of supply chain financing. Based on expectancy theory, this study explores the different profiles underlying the components of expectancy, valence and instrumentality. Design/methodology/approach: This is a multiple-case study of four Fintech companies using blockchain technology to promote the performance of supply chain operations and financing. Findings: The results show that blockchain-enabled supply chain finance (BSCF) can be classified into four scenarios based on the scope and purpose of blockchain technology applications. The success of BSCF depends on the profiles of BSCF expectancy (the recognized purpose and scope of BSCF), instrumentality (identified blockchain attributes and other technology combinations) and valence (the perceived distinctive value of BSCF). Blockchain attributes help solve information asymmetry problems and enhance financing performance in two ways: one is supporting transparency, traceability and verification of transmissions and the other entails facilitating a transformation to new business models. Originality/value: This research applies a new perspective based on expectancy theory to study how cognitive factors affect Fintech companies' blockchain solutions under a given supply chain operation or financing activity. It explains the behavioral antecedents for applying blockchain technology, the situations appropriate for the different roles of blockchain technology and the profiles for realizing the value of blockchain technology. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01443577
- Volume :
- 43
- Issue :
- 12
- Database :
- Complementary Index
- Journal :
- International Journal of Operations & Production Management
- Publication Type :
- Academic Journal
- Accession number :
- 173861807
- Full Text :
- https://doi.org/10.1108/IJOPM-07-2022-0467