Purpose: The aim of this study is applying a new method for Industrial robotic system selection. Design/methodology/approach: In this paper, the weights of each criterion are calculated using fuzzy Shannon's Entropy. After that, fuzzy TOPSIS is utilized to rank the alternatives. After that we compare the result of Fuzzy TOPSIS with Fuzzy VIKOR method. Then we select the best Industrial Robotic System based on these results. Findings: The outcome of this research is ranking and selecting industrial robotic systems with the help of Fuzzy Shannon's Entropy and Fuzzy TOPSIS techniques. Originality/value: This paper offers a new integrated method for industrial robotic system selection.
Competitive environment of today’s organizations, more than ever, is extensive, and the major concern for managers is to preserve and promote the sustainable competitive advantage. Companies have an obligation to improve their product quality and have extensive and close cooperation with other companies involved in the supply chain of products. Supply chain quality management (SCQM) is a systematic approach to improve the performance that integrates supply chain partners and uses the opportunity in the best way, establish linkages between upstream and downstream flows, and investigate on creating value and satisfaction of intermediaries and final customers. Furthermore, achieving competitive advantages enables an organization to create a remarkable position in market and differentiate itself from competitors. This paper aims to understand the relationships between SCQM and competitive advantage. Sixty-eight experts of 25 companies in Sahami Alyaf (SA) supply chain has been participated in this research. The research method used for this article is descriptive correlation. To assess the relationships between the criteria, canonical correlation analysis was used. The result shows that the SCQM and competitive advantages have a meaningful relationship. It also shows that most important variable in the linear combination of SCQM and competitive advantages are “customer focus and quality,” respectively.
Suitable project manager has a significant impact on successful accomplishment of the project. Managers should possess such skills in order to effectively cope with the competition. In this respect, selecting managers based on their skills can lead to a competitive advantage towards the achievement of organizational goals. selection of the suitable project manager can be viewed as a multi-criteria decision making (MCDM) problem and an extensive evaluation of criteria, such as Technical skills, experience skills, Personal qualities and the related criteria must be considered in the selection process of project manager. The fuzzy set theory and MCDM methods appears as an essential tools to provide a decision framework that incorporates imprecise judgments and multi criteria nature of project manager selection process inherent in this process. This paper proposes the joint use of the Fuzzy DEMATEL (FDEMATEL) and Fuzzy VIKOR methods for the decision-making process of selecting the most suitable managers for projects. First, with the opinions of the senior managers based on project management competency model (ICB-IPMA), all the criteria required for the selection are gathered. Then the FDEMATEL method is used to prioritize the importance of various criteria and FVIKOR used to rank the alternatives in a preferred order to select the best project managers from a number of alternatives. Next, a real case study used to illustrate the process of the proposed method. Finally, some conclusions are discussed at the end of this study.
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