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An ANP-multi-criteria-based methodology to construct maintenance networks for agricultural machinery cluster in a balanced scorecard context.
- Source :
-
Computers & Electronics in Agriculture . Mar2019, Vol. 158, p1-10. 10p. - Publication Year :
- 2019
-
Abstract
- Highlights • The maintenance network for agricultural machinery is defined. • A general framework is developed to select the service provider for maintenance network. • The integrated method of balanced score card and analytic network process is employed to analyze criteria. • The results of the case studies prove that the methodology is effective. Abstract Constructing maintenance networks is becoming an urgent requirement for ensuring the continuous reliable operation and fast response of agricultural machinery maintenance in busy farming seasons. According to dynamic characteristics, time variation, and the cooperativity of agricultural machinery cluster working, this paper proposes a service provider selection framework for the layout of dynamic maintenance network nodes. Furthermore, an integrated analytic network process (ANP) and balanced score card (BSC) service provider selection approach is provided to help construct the maintenance network. Concerning four determinants of BSC: service satisfaction, process capability, knowledge assets, and service cost, this method provides qualitative and quantitative indicators, four evaluative dimensions and a three-layer network evaluation system index. Moreover, this method is applied to maintenance services for agricultural machinery clusters working in cross-regional operations in China. The results indicate that process capability is the most important determinant for a service network, and the proposed method contributes to the ability of decision-makers to comprehend the complex relationship among factors during the service provider selection process. Meanwhile, this method improves the reliability of service provider selection during the construction of a maintenance network. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01681699
- Volume :
- 158
- Database :
- Academic Search Index
- Journal :
- Computers & Electronics in Agriculture
- Publication Type :
- Academic Journal
- Accession number :
- 134960887
- Full Text :
- https://doi.org/10.1016/j.compag.2019.01.031