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Samdantsoodol, A., Cang, S. 
ORCID: 0000-0002-7984-0728, Yu, H., Eardley, A. and Buyantsogt, A.,
2017.
Predicting the relationships between virtual enterprises and agility in supply chains.
Expert Systems with Applications, 84, pp. 58-73.
ISSN 0957-4174
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Abstract
In the recent advanced information communications and technology (ICT) era, collaborating virtually and temporarily in supply chains (SCs) to receive mutual benefits such as agility while sharing resources and information becomes an important strategy for enterprises that seek to increase their competitiveness and to optimise their processes and resource usage. As a dynamic and temporary form of alliance from the resource perspective, virtual enterprises (VEs) may contribute network resource heterogeneity and sustain competitive advantage. In addition, agility is suggested as a rare, valuable, network resource that is difficult to imitate and that cannot easily be substituted by other attributes.
Although many researchers have investigated VEs and their agility, the research pays less attention to the relationship between VEs and agility in complex SC situations. This paper therefore investigates the relationship between VE and agility in SCs (ASCs) and explores drivers and enablers of agility and outcomes. To clarify the relationships between factors a structural equation model (SEM) is adopted to examine the model fit according to the measurement variables and supporting hypotheses. The results provide rich empirical evidence of the beneficial impact of VEs on ASCs, and theoretical and managerial insights that can be used to strengthen the drivers, enablers and capabilities to enhance the effectiveness of VE collaboration in ASCs in a global and dynamic context. Also, the analysis results can aid a decision maker which ones of the factors are the important ones that he or she should devote more resources and efforts on.
| Item Type: | Journal article | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Publication Title: | Expert Systems with Applications | ||||||||
| Creators: | Samdantsoodol, A., Cang, S., Yu, H., Eardley, A. and Buyantsogt, A. | ||||||||
| Publisher: | Elsevier | ||||||||
| Date: | 30 October 2017 | ||||||||
| Volume: | 84 | ||||||||
| ISSN: | 0957-4174 | ||||||||
| Identifiers: |
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| Divisions: | Schools > School of Science and Technology | ||||||||
| Record created by: | Linda Sullivan | ||||||||
| Date Added: | 26 Aug 2020 15:18 | ||||||||
| Last Modified: | 31 May 2021 15:17 | ||||||||
| URI: | https://irep.ntu.ac.uk/id/eprint/40532 |
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