A case-based reasoning approach for evaluating and selecting human resource management information systems projects

This paper presents a case-based reasoning (CBR) approach for evaluating and selecting human resource management information systems (IS) projects in an organization. The concept on case-based distance is introduced for measuring the degree of similarity between each case in the case base and the new case. To avoid the inconsistency of the decision maker’s subjective assessment, an induction technique is applied to help assign the importance of the criteria in the similarity measure. A human resource management IS project evaluation and selection problem is presented to demonstrate the effectiveness of the approach

Fuzzy multiattribute evaluation of green supply chain performance

This paper presents a fuzzy multiattribute decision making approach for evaluating the performance of green supply chain alternatives. Assessments for qualitative measures and attribute weights are represented by triangular fuzzy numbers, obtained from the decision maker using linguistic terms. An effective algorithm based on the concept of dominance is developed for calculating the overall performance index of each green supply chain alternative. As a result, this would help organizations understand the comparative level of their green supply chain alternatives’ performance. An example is presented for demonstrating the applicability of the approach in dealing with the green supply chain performance evaluation problem

Evaluating and selecting hospital locations using fuzzy multicriteria decision making

The hospital location evaluation and selection process is complexand challenging owing to the multi-dimensional nature of the process and the presence of uncertainty and imprecision inherent in the decision making process. To ensure effective decisions are made, this paper presents a new approach for evaluating and selecting hospital locations. The evaluation problem is formulated as a multicriteria decision making problem, and a fuzzy multicriteria decision making algorithm is developed for evaluating and selecting hospital location alternatives. Linguistic terms approximated by fuzzy numbers are used to represent the subjective assessments of the decision maker. To avoid the complex and unreliable process of comparing fuzzy numbers usually required in fuzzy multicriteria decision making, a new algorithm is developed based on the concept of ideal solutions. A hospital location selection problem is presented to demonstrate the effectiveness of the approach

Evaluating intelligent building systems performance in multicriteria group decision making problem

This paper develops a performance evaluation approach for evaluating intelligent building systems in terms of their contribution to the building's operational effectiveness and efficiency in the multicriteria group decision making problem. A fuzzy pairwise comparison process is adopted for reducing the cognitive burden of decision makers in the evaluation process. A fuzzy technique for order preference by similarity to ideal solution (TOPSIS) is used for determining the performance score of available alternatives. An example is given for demonstrating the applicability of the proposed approach for solving the multicriteria group decision making problem in real world situations

Interval-valued intuitionistic fuzzy multicriteria group decision making approach for hotel selection

Evaluating and selecting the most suitable hotel location for development is complex and challenging. To effectively deal with this problem, this paper presents an interval-valued intuitionistic fuzzy multicriteria group decision making approach for evaluating and selecting hotel locations. The subjectiveness and imprecision of the decision making process are adequately modeled by the use of interval-valued based intuitionistic fuzzy numbers. The concept of ideal solutions is adopted for determining the overall performance of each alternative hotel location across all the selection criteria on which the final decision is made. An example is presented for demonstrating the applicability of the proposed approach for solving real world hotel location selection problems

A new sustainability index for evaluating the sustainability performance of mining companies

This paper develops a new sustainability index for evaluating the sustainability performance of mining companies. The index indicates a mining company’s overall performance level, relative to other companies in terms of its sustainability performance. To facilitate the use of the index as a sustainability performance management tool, three most important criteria for measuring the sustainability-related performance of mining companies are identified. With the use of linguistic terms, subjective assessments of qualitative performance measures are represented with fuzzy numbers. Based on the concept of optimality, a fuzzy multicriteria decision making approach is developed to obtain a sustainability performance index for each company. This sustainability performance index helps mining companies to understand their strengths and weaknesses in terms of sustainability performance criteria, and identify relevant areas for sustainability improvement

A fuzzy approach for evaluating the performance of supply chain based on Internet of Things

This paper presents a fuzzy approach for evaluating the performance of supply chain based on Internet of Things (IoT). The multi-dimensional nature of the evaluation process is handled in the context of multicriteria analysis. Linguistic terms approximated by triangular fuzzy numbers are used to tackle the subjectiveness and imprecision of the human evaluation process. An efficient algorithm is developed for producing a performance index for every supply chain based on IoT alternative across all selection criteria. A multicriteria decision support system is proposed to facilitate the evaluation process. An example is presented for demonstrating the applicability of the approach

A Fuzzy multicriteria group decision making approach for improving the degree of confidence in supplier selection

This paper presents a fuzzy multicriteria group decision making approach for effectively considering the degree of confidence of decision makers (DMs) in solving the supplier selection problem. Linguistic variables approximated by fuzzy numbers are used to represent the DM’s subjective assessments so that the uncertainty and imprecision in the selection process are adequately handled in a less cognitively demanding manner. To avoid the complicated and unreliable process of comparing and ranking fuzzy utilities often required in fuzzy multicriteria analysis, the concept of the degree of dominance between alternatives is introduced for calculating an overall performance index for every alternative supplier across all criteria. An example is presented to demonstrate the applicability of the proposed approach for solving the supplier selection problem in real world settings

A group decision model for evaluating and selecting intelligent building systems under uncertainty

This paper presents a group decision model for evaluating and selecting intelligent building systems under uncertainty. Linguistic variables approximated by fuzzy numbers are used for dealing with the decision maker’s subjective assessments. Pairwise comparison is adopted for reducing the cognitive burden of the decision maker in the evaluation process. A group decision model is developed for producing the performance index of available alternatives on which the overall ranking of alternatives can be obtained. As a result, effective decisions can be made. An example is presented for demonstrating the applicability of the group decision model

Fuzzy multicriteria analysis for performance evaluation of internet-of-things-based supply chains

This paper presents a fuzzy multicriteria analysis model for evaluating the performance of Internet of Things (IoT)-based supply chains. The inherent uncertainty and imprecision of the performance evaluation process was handled by using intuitionistic fuzzy numbers. A new fuzzy multicriteria group decision making algorithm based on the technique ordered preference by similarity to the ideal solution (TOPSIS) approach, and the concept of similarity measures was developed for determining the overall performance of each alternative. The advantage of the proposed fuzzy multicriteria analysis model is that it can overcome the limitations of the existing approaches in an intuitionistic fuzzy environment. The fuzzy multicriteria group decision-making model provides organizations with the ability to evaluate the performance of their IoT-based supply chains for improving their competitiveness. An example is presented to highlight the usefulness of the proposed model for tackling a real world IoT performance evaluation problem. © 2018 by the authors