Combined CFPR and VIKOR Model for Enhancing the Competencies of Domestic Chain Hotel Groups

2019 ◽  
Vol 18 (03) ◽  
pp. 901-927
Author(s):  
Chui-Hua Liu ◽  
Gwo-Hshiung Tzeng ◽  
Po-Yen Lee

Hotel competency is inherently intangible and multivariate. It involves a multiple-criteria decision-making problem. Particularly in the currently rapidly shrinking hotel market in Taiwan, what determines domestic chain hotel groups’ (DCHGs’) competence and survival involves more complex and multiple factors. A practical and effective tool is urgently required for making appropriate decisions. This paper thus proposes a combined consistent fuzzy preference relations (CFPR) and the VIKOR model, aiming to prioritize criteria and solution alternatives for hotel managers. In contrast to prior studies that have used mathematical programming, the model here is also tested using real-world hotel management cases and expert consultation. First, based upon the resource-based view, we propose 21 criteria and six dimensions as the determinants of DCHG competencies. Then, VIKOR is applied to produce the most appropriate alternatives with the corresponding weights obtained using the CFPR method. The combined method successfully manages the problems of linguistic ambiguity and consistency, determines the relative weights of the different factors and provides a ranking priority. The result is compared with some similar methods and is shown to be more useful and reliable. Finally, the verified model can be used to produce strategies. A decision-maker can make selection(s) from the solution formula. Our study may thus contribute to the hotel industry with the efficient decision-making tool of resource-based view (RSV) and two-phase methodologies.

Author(s):  
Reza Farzipoor Saen

Supplier selection is a multiple criteria decision making problem that the selection process mainly involves evaluating a number of suppliers according to a set of common criteria for selecting suppliers to meet business needs. Suppliers usually offer volume discounts to encourage the buyers to order more. To select suppliers in the presence of both volume discounts and imprecise data, this chapter proposes an optimization method. A numerical example demonstrates the application of the proposed method.


2019 ◽  
Vol 18 (06) ◽  
pp. 1875-1908
Author(s):  
Akshay Hinduja ◽  
Manju Pandey

ERP system is a software package that integrates and manages all the facets of the business and deeply influences the success of a business endeavor. The increasing competition in the market, rapidly changing demands, and increasing intricacy of business procedures induce enterprises to adopt ERP solutions. Adopting an ERP solution increases synchronization between business activities and reinforces managerial decision-making. However, it also involves a large investment, a significant amount of human resources and time, and risk of failure. Therefore, the selection of an ERP solution is a crucial decision for enterprises. To address this decision-making problem, we propose a four-stage multi-criteria decision-making approach in this paper. Three prevalent MCDM techniques, DEMATEL, IF-ANP, and IF-AHP, are used in different stages of the methodology to achieve better outcomes. The methodology incorporates the intuitionistic fuzzy sets to capture uncertainty and hesitancy involved in decision makers’ judgments. In addition, we develop a novel priority method to derive weights from the intuitionistic fuzzy preference relations. To validate the feasibility of the proposed approach, a case study is carried out on the selection of cloud-based ERP system for SMEs in the Chhattisgarh state of India, which indicates that the proposed four-stage approach effectively handles the ERP selection problem.


2021 ◽  
Vol 19 (3) ◽  
pp. 579
Author(s):  
Sarfaraz Hashemkhani Zolfani ◽  
Ramin Bazrafshan ◽  
Parnian Akaberi ◽  
Morteza Yazdani ◽  
Fatih Ecer

Suitability-Feasibility-Acceptability (SFA) is a fundamental tool for the development and selection of strategy. Any type of decision-making problem can be resolved by Multiple Criteria Decision Making (MCDM) methods. In this research, we explore the complexity of determining the proper goal market for the Chilean fish market. This study proposed a combined approach of SFA with MCDM methods in a real case study. The proposed structure helps to assign the best market for Chilean export fish to West Asia. Three countries (Saudi Arabia, the United Arab Emirates, and Oman) are selected as a target market in this region, and then related criteria are obtained from various sources. In order to develop a new market for the Chilean fishery industry, five major criteria, including the potential of a target market, region's economic attractiveness, consumption of the seafood, location, cost of transportation, and country risks, were selected based on the SFA framework. Calculating the criteria weights is performed by the Best-Worst (BWM) method, and ordering the alternatives is operated by Measurement Alternatives and Ranking according to compromise Solution (MARCOS) methods. The results showed that Oman is the best destination (importer) for the Chilean fish market (Salmon fish as the case).


Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Luis Pérez-Domínguez ◽  
Luis Alberto Rodríguez-Picón ◽  
Alejandro Alvarado-Iniesta ◽  
David Luviano Cruz ◽  
Zeshui Xu

The multiobjective optimization on the basis of ratio analysis (MOORA) method captures diverse features such as the criteria and alternatives of appraising a multiple criteria decision-making (MCDM) problem. At the same time, the multiple criteria problem includes a set of decision makers with diverse expertise and preferences. In fact, the literature lists numerous approaches to aid in this problematic task of choosing the best alternative. Nevertheless, in the MCDM field, there is a challenge regarding intangible information which is commonly involved in multiple criteria decision-making problem; hence, it is substantial in order to advance beyond the research related to this field. Thus, the objective of this paper is to present a fused method between multiobjective optimization on the basis of ratio analysis and Pythagorean fuzzy sets for the choice of an alternative. Besides, multiobjective optimization on the basis of ratio analysis is utilized to choose the best alternatives. Finally, two decision-making problems are applied to illustrate the feasibility and practicality of the proposed method.


2006 ◽  
Vol 2006 ◽  
pp. 1-26 ◽  
Author(s):  
P. Kousalya ◽  
V. Ravindranath ◽  
K. VizayaKumar

The present study illustrates the application of analytical hierarchy process (AHP) to a decision-making problem. AHP is a popular and powerful method for solving multiple criteria decision-making (MCDM) problems. An attempt is made here to initialize the use of multicriteria decision-making methods for ranking alternatives that curb student absenteeism. Through the expert opinions, the criteria that cause student absenteeism are identified and the criteria hierarchy was developed. The relative importance of those criteria for Indian environment is obtained through the opinion survey. Alternatives that curb student absenteeism in engineering colleges like counseling, infrastructure, making lecture more attractive, and so forth were collected from literature, journals' surveys and experts' opinions. Alternatives are evaluated based on the criteria, and the preferential weights and ranks are obtained. The experts' opinions are validated by Saaty's inconsistency test method. “Involvement of parents” is the best alternative given by the group of experts. Parents have to know their ward's day-to-day progress in college. The second best alternative is “counseling,” as many criteria that cause student absenteeism are reduced by counseling.


2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
R. Roostaee ◽  
M. Izadikhah ◽  
F. Hosseinzadeh Lotfi

Decisions in the real-world contexts are often made in the presence of multiple, conflicting, and incommensurate criteria. Multiobjective programming methods such as multiple objective linear programming (MOLP) are techniques used to solve such multiple-criteria decision-making (MCDM) problems. One of the first interactive procedures to solve MOLP is STEM method. In this paper we try to improve STEM method in a way that we search a point in reduced feasible region whose criterion vector is closest to positive ideal criterion vector and furthest to negative ideal criterion vector. Therefore the presented method tries to increase the rate of satisfactoriness of the obtained solution. Finally, a numerical example for illustration of the new method is given to clarify the main results developed in this paper.


2016 ◽  
Vol 15 (05) ◽  
pp. 1157-1179 ◽  
Author(s):  
N. Thillaigovindan ◽  
S. Anita Shanthi ◽  
J. Vadivel Naidu

This paper considers a multiple criteria decision-making (MCDM) problem under risk in fuzzy environment in its general form. There are m alternatives which need to be ranked on the basis of a set of n criteria. The alternatives and the criteria are evaluated based on a set of l characteristics. The entire data is presented in the form of interval valued intuitionistic fuzzy soft set of root type. In addition each criterion is assigned a subjective criterion weight based on expert’s evaluation and each characteristic is assigned a probability weight on the basis of decision maker’s knowlege and understanding of the importance of the characteristic. This problem may be called as a MCDM problem under risk in fuzzy environment in its general form. A method for ranking the alternatives using the new score functions, prospect theory and method of determining the optimum criteria weights is explained. An algorithm is developed for this purpose and its working illustrated with a suitable example.


Sign in / Sign up

Export Citation Format

Share Document