“…(8) Checking any inconsistency and modify the developed ISM. (Quezada et al 2018). The relationships among causal and effect are changedin the DEMATEL form.…”
Supply Chain Management (SCM) is one of the key aspects of making agriculture sector more competitive in India. India and other developing countries arefacing issues for coordination of their Agriculture Food Supply Chain Management (AFSCM) as not having technical and resources support; especially in natural disaster condition like recent COVID-19 outbreak. The purpose of this research is to develop anInternet of Things (IoT) based efficient and supportive coordinating system for enhancing the coordinating mechanism in AFSC under natural outbreaks. With the help of a literature review and experts' inputs, seven enablers have been identified by grouping thirty sub enablers. Further, ISM methodology has been employed for developing a framework for enablers' relationships to improve the coordination in the AFSC for taking strategic and operational decisions. After that, DEMATELtechnique is utilised to develop the causal and effectrelationships between all the identified enablers of a coordination system in IoT based AFSC. It has been noticed that'Top Management Support (TMS)' is the main driver by MICMAC analysis and categorised in a cause group based on (R-C) value. Further, the coordination index of the entire model is calculated based on the Cleveland theory. This paper also discussed a case study of the sugar mill industry. This paper also discussed stakeholder theory in developing IoT based coordination system of AFSC. Further, theoretical contribution may also guide the managers of the organisation in developing their strategies by using Strengths-Weaknesses-Opportunities-Threats (SWOT) analysis based on Cleveland index. Keywords COVID-19. Internet of things (IoT). Agriculture food supply chain (AFSC). DEMATEL. Coordination index
“…(8) Checking any inconsistency and modify the developed ISM. (Quezada et al 2018). The relationships among causal and effect are changedin the DEMATEL form.…”
Supply Chain Management (SCM) is one of the key aspects of making agriculture sector more competitive in India. India and other developing countries arefacing issues for coordination of their Agriculture Food Supply Chain Management (AFSCM) as not having technical and resources support; especially in natural disaster condition like recent COVID-19 outbreak. The purpose of this research is to develop anInternet of Things (IoT) based efficient and supportive coordinating system for enhancing the coordinating mechanism in AFSC under natural outbreaks. With the help of a literature review and experts' inputs, seven enablers have been identified by grouping thirty sub enablers. Further, ISM methodology has been employed for developing a framework for enablers' relationships to improve the coordination in the AFSC for taking strategic and operational decisions. After that, DEMATELtechnique is utilised to develop the causal and effectrelationships between all the identified enablers of a coordination system in IoT based AFSC. It has been noticed that'Top Management Support (TMS)' is the main driver by MICMAC analysis and categorised in a cause group based on (R-C) value. Further, the coordination index of the entire model is calculated based on the Cleveland theory. This paper also discussed a case study of the sugar mill industry. This paper also discussed stakeholder theory in developing IoT based coordination system of AFSC. Further, theoretical contribution may also guide the managers of the organisation in developing their strategies by using Strengths-Weaknesses-Opportunities-Threats (SWOT) analysis based on Cleveland index. Keywords COVID-19. Internet of things (IoT). Agriculture food supply chain (AFSC). DEMATEL. Coordination index
“…In contrast, ANP can handle decision problems modeled as a network. In such a way, interdependence can be considered [54]. ANP applied in diverse areas can be utilized to make decision problems that cannot be structured hierarchically and without the independent assumptions [55].…”
Tourism has been identified as one of the sectors that will contribute to Taiwan’s economic development. Online travel agencies’ role in producing economic value in the hospitality industry continues to grow. The hotel industry is used in this study as the research context to help managers of hot spring hotels select the optimal online travel agencies (OTAs) using a hybrid multi-criteria decision-making (MCDM) model. The aim of this paper is threefold: first, to obtain selection criteria for OTAs based on the fuzzy Delphi method; second, to extract interdependencies between the perspectives using decision making trial and evaluation laboratory (DEMATEL); and third, according to interdependencies between the perspectives, to rank the alternatives by analytic network process (ANP). Based on the proposed model, a real-world company was conducted and demonstrated OTAs selection problem; the results demonstrated the proficiencies and effectiveness of this model.
“…This issue was addressed in the decision-making trial and evaluation laboratory (DEMATEL) by constructing the interrelations among clusters and deriving the weight of each cluster [24]. This methodology has been successfully applied to various decision-making problems, such as identifying causal relationships in strategy maps, evaluating green suppliers, creating brand values in brand marketing, and improving the partner selection process in customer relationship management [25], [26].…”
Analytic network process (ANP) is a significant multiple criteria decision making (MCDM) method. Although lots of efforts have been spent on improving the ANP, there still exist the four aspects of problems to be solved such as too many comparison times, unconsidering expert knowledge structure, ignoring consensus level of experts' group and ineffectively determining holistic information of the group. This study focuses on providing a simplified group ANP with consensus reaching named as DS/ANP method which incorporates the Dempster-Shafer theory of evidence (DS) with the ANP. An expert information extraction mechanism with the help of knowledge matrix and basic probability assignment function is introduced to simplify comparisons of group ANP and reflect expert knowledge structure. Then Shafer's discounting and Dempster's rule are both used to get the holistic information of the group, in which three levels of consensus indices (element level, cluster level, and holism level) are defined in terms of Jousselme distance. A group ANP method with consensus reaching and its corresponding algorithm are both established by following the principles of ANP. Finally, a numerical example is presented to make comparisons and discussions for the proposed method. INDEX TERMS Analytic network process, consensus reaching, Dempster's rule, group decision making, knowledge matrix.
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