Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/29728
Title: Do interorganisational relationships and knowledge-management practices enhance collaborative commerce adoption?
Authors: Chong, AYL
Chan, FTS 
Goh, M
Tiwari, MK
Keywords: collaborative commerce
interorganisational relationships
knowledge management
neural network
technology adoption
Issue Date: 2013
Publisher: Taylor & Francis
Source: International journal of production research, 2013, v. 51, no. 7, p. 2006-2018 How to cite?
Journal: International journal of production research 
Abstract: This research aims to investigate the contributions of interorganisational relationships and knowledge-management practices as predictors of collaborative commerce (c-commerce) adoption. A non-compensatory adoption decision process was modelled using a neural network approach to examine the predictors of c-commerce adoption. A survey was undertaken in 136 firms for this research. The results showed that both interorganisational relationships and knowledge-management processes played an important role in predicting the adoption of c-commerce. In particular, variables from interorganisational relationships such as trust, communication, collaboration, and information sharing are found to contribute strongly to the predictive power of the model when compared with knowledge-management processes. This study provides insights for firms that would like to improve their supply-chain collaboration through the implementation of c-commerce. The findings lead to an understanding of what attributes of interorganisational relationships and knowledge-management processes can contribute to the improved adoption of c-commerce in the supply chain. Unlike past adoption studies which have tended to focus on technology, and organisational and environmental factors, this research examined interorganisational relationships and knowledge-management processes which are increasingly gaining the attention of researchers and practitioners. This study has also extended the existing literature by examining a non-compensatory model for technology adoption.
URI: http://hdl.handle.net/10397/29728
ISSN: 0020-7543
EISSN: 1366-588X
DOI: 10.1080/00207543.2012.701776
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