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A hybrid framework for ranking the knowledge management solutions adoption in supply chains
- Source :
- VINE Journal of Information and Knowledge Management Systems. 50:1-19
- Publication Year :
- 2019
- Publisher :
- Emerald, 2019.
-
Abstract
- Purpose This paper aims to select and rank the solutions of knowledge management and apply them to the supply chain for boosting its performance. Therefore, organizations can focus on the high-priority solutions and assign the resources to the strategies related to these solutions. Design/methodology/approach A decision making trial and evaluation laboratory-based analytic network process method is first used to rank the barriers of implementing the knowledge solutions and preference ranking organization method for enrichment evaluations technique is then used to rank the knowledge-based solutions which improve the overall performance of the supply chain. Then, a mathematical model is proposed to select the best solutions where the effectiveness and fairness are maximized while the cost and risk are minimized. The proposed model is implemented over a dairy supply chain in Iran. The solutions are obtained using the literature and the experts’ panel of the supply chain. Findings Lack of trust and commitment of supply chain members, besides different interests, values and cultures of the supply chain members, is the most challenging barrier to knowledge management solution. Strengthening the cooperation culture in the chain, setting up a transparent workflow or open-door policy, setting up enough incentives and reward and punishment and setting up positive leadership toward knowledge management are the most important strategies for removing the existing barriers or decreasing their impact on the supply chain. Originality/value Solutions with the highest priority are not necessarily the best solutions for implementation; the requirements of organizations must also be considered. Mathematical model in this study helped to select solutions based on their cost and risk, as well as their priority level.
- Subjects :
- Boosting (machine learning)
Knowledge management
Computer Networks and Communications
Computer science
business.industry
Analytic network process
Supply chain
05 social sciences
02 engineering and technology
Library and Information Sciences
Computer Science Applications
Workflow
Incentive
Management of Technology and Innovation
0502 economics and business
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Overall performance
business
050203 business & management
Information Systems
Subjects
Details
- ISSN :
- 20595891
- Volume :
- 50
- Database :
- OpenAIRE
- Journal :
- VINE Journal of Information and Knowledge Management Systems
- Accession number :
- edsair.doi...........72e4031ebd47d86d2b0e1887618b9677
- Full Text :
- https://doi.org/10.1108/vjikms-06-2019-0090