Fuzzy AHP as a tool for prioritization of key performance indicators

Kaganski, Sergei; Majak, Jüri; Karjust, Kristo

doi:10.1016/j.procir.2018.03.097

Cited by 78 publications

(34 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In this research, a pairwise comparison matrix was operated as triangular fuzzy numbers (TNFs) to assess the supplier for implementing green innovation in the sustainable supply chain system. Table 3 shows the TFN scale used in this study [46]. Strongly to very strongly dominant (5,6,7) 7…”

Section: Fahp Methodsmentioning

confidence: 99%

Supplier Selection for the Adoption of Green Innovation in Sustainable Supply Chain Management Practices: A Case of the Chinese Textile Manufacturing Industry

Yang

Wang

2020

Processes

View full text Add to dashboard Cite

Globally, increasing environmental issues are gaining attention to facilitate the adoption of green innovation for sustainable supply chain management (SSCM). Sustainable environmental practices have been well-considered in the literature; however, no study has focused on adopting green innovation practices for sustainable development. Thus, environmental management authorities are putting pressure on industries to implement green innovation criteria for SSCM operations. Moreover, it is important to select traditional suppliers to transform its practices to that of sustainable supply chains in order to achieve the industry’s sustainable supply chain goals. In response, this research identified and analyzed the green innovation criteria for SSCM and then selected a supplier that could implement green aspects in the SSCM. This study developed an integrated multi-criteria decision making (MCDM) model using the fuzzy analytical hierarchy process (FAHP) and the fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS). The objective of this study was to analyze suppliers to implement green innovation criteria for SSCM practices in the textile manufacturing companies of China. This study reviewed and identified three green innovation criteria and seventeen sub-criteria. Then, the FAHP technique was employed to analyze and rank green innovation criteria and sub-criteria. Finally, the FTOPSIS method was used to investigate and rank eight suppliers. The findings of the FAHP indicated that economic (EC) criteria were the most vital green innovation criteria in the SSCM. Furthermore, the FTOPSIS results revealed that supplier 5 was the most suitable supplier for implementing green innovation criteria in the SSCM. These findings will help managers, practitioners, and policymakers implement green innovation criteria in sustainable manufacturing supply chains.

show abstract

Section: Fahp Methodsmentioning

confidence: 99%

Supplier Selection for the Adoption of Green Innovation in Sustainable Supply Chain Management Practices: A Case of the Chinese Textile Manufacturing Industry

Yang

Wang

2020

Processes

View full text Add to dashboard Cite

show abstract

“…A fuzzy AHP method is selected as a factor-weighting model because studies have declared its effectiveness in prioritizing and ranking of factors, criteria, alternatives in construction management, and other various disciplines [42][43][44][45][46][47][48][49][50]. Fuzzy AHP can be applied in several ways.…”

Section: Fuzzy Ahp Methodmentioning

confidence: 99%

An Effective Approach to Input Variable Selection for Preliminary Cost Estimation of Construction Projects

Meharie

Gariy

Mutuku

et al. 2019

Advances in Civil Engineering

View full text Add to dashboard Cite

Accurate cost estimates are vital to the effective realisation of construction projects. Extended knowledge, wide-ranging information, substantial expertise, and continuous improvement are required to attain accurate cost estimation. Cost estimation at the preliminary phase of the project is always a challenge as only limited information is available. Hence, rational selection of input variables for preliminary cost estimation could be imperative. A systematic input variable selection approach for preliminary estimating using an integrated methodology of factor analysis and fuzzy AHP is presented in this paper. First, the factor analysis is used to classify and reduce the input variables and their variable coefficients are determined. Second, fuzzy AHP based on the geometric mean method is employed to determine the weights of input variables in a fuzzy environment where the subjectivity and vagueness are handled with natural language expressions parameterized by triangular fuzzy numbers. Then, the input variables are suggested to be selected starting with those having high coefficient and high importance weight. A set of three variables, one from each group, can be added to the estimating model at a time so that the problem of collinearity can vanish and good accuracy of the estimate can be ensured. The proposed approach enables cost estimators to better understand the complete input variable selection process at the early stage of project development and provide a more accurate, rational, and systematic decision support tool.

show abstract

“…Therefore, the real-time monitoring is needed in order to dealing with rapid change and effective control stock of inventory. Mahmood [19], Kaganski [20], Amrina & Yusof [21] proposed the concept of production evaluation in SME network using virtual enterprise. Key performance indicators (KPIs) is created which affect operation such as efficiency, utilization, and productivity.…”

Section: Sub-contractor Evaluationmentioning

confidence: 99%

Automotive Industrial Supply Chain Performance Evaluation under Uncertain Constraints on Cloud Computing System

Butdee¹

2021

Concepts, Applications and Emerging Opportunities in Industrial Engineering

View full text Add to dashboard Cite

Performance evaluation is a critical and complex task as well as uncertain demands for automotive supply chain. Several methods are applied and adopted to deal with current situations and maintain competitiveness such as fuzzy logic, neuro fuzzy, agent (multi) based evaluation, etc. However, such systems are not rapid enough to respond customer requirements by real-time on mobile cloud computing system. There are many companies that operate under the first tier company as subcontractors on the same goal. Cloud computing system is capable to monitor real-time production processes for every subcontractor to assist the 1st tier to make decision and respond customer effectively. Daily monitoring data of all subcontractors in the supply chain are stored in the central database and finally the performance evaluation can be done. The implication is cost reduction of the whole supply chain and increase competitiveness as well as continuous process improvement for all.

show abstract

Fuzzy AHP as a tool for prioritization of key performance indicators

Cited by 78 publications

References 18 publications

Supplier Selection for the Adoption of Green Innovation in Sustainable Supply Chain Management Practices: A Case of the Chinese Textile Manufacturing Industry

Supplier Selection for the Adoption of Green Innovation in Sustainable Supply Chain Management Practices: A Case of the Chinese Textile Manufacturing Industry

An Effective Approach to Input Variable Selection for Preliminary Cost Estimation of Construction Projects

Automotive Industrial Supply Chain Performance Evaluation under Uncertain Constraints on Cloud Computing System

Contact Info

Product

Resources

About