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Information Journal Paper

Title

Determine the Optimal Marketing Strategy Using the ANP and TOPSIS Techniques in the Hotel Industry

Pages

  134-155

Abstract

 The present study seeks to select the optimal marketing strategy using the multicriteria decision-making (analytic network process and TOPSIS approach) in the luxury hotels of Kermanshah and Santandaj cities. The statistical population of the study is senior managers of different levels, Due to the limited number of these hotels, all of them were examined. A questionnaire (in the form of a pairwise matrix) was used to collect the data and for data analysis, the Super decision software and MCDM engine and excel (TOPSIS) were used. The examining criteria in this study are managerial capabilities, customer relationship capabilities, market innovation capabilities, human resource assets, and credit and good reputation assets. Also Slater and Olson's strategies as options for the most optimal strategy were examined. The results showed that in TOPSIS approach, aggressive marketing, and in the analytic network process (ANP) approach, the value marketing strategy were the most effective marketing strategy. The results provide guidance to private hotel managers on marketing strategies that can help them to obtain a competitive advantage by evaluating their specific and limited marketing resources.

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    APA: Copy

    Vafaie, Farhad, & NASIRI, SOMAYEH. (2020). Determine the Optimal Marketing Strategy Using the ANP and TOPSIS Techniques in the Hotel Industry. CONSUMER BEHAVIOR STUDIES, 7(2 ), 134-155. SID. https://sid.ir/paper/963285/en

    Vancouver: Copy

    Vafaie Farhad, NASIRI SOMAYEH. Determine the Optimal Marketing Strategy Using the ANP and TOPSIS Techniques in the Hotel Industry. CONSUMER BEHAVIOR STUDIES[Internet]. 2020;7(2 ):134-155. Available from: https://sid.ir/paper/963285/en

    IEEE: Copy

    Farhad Vafaie, and SOMAYEH NASIRI, “Determine the Optimal Marketing Strategy Using the ANP and TOPSIS Techniques in the Hotel Industry,” CONSUMER BEHAVIOR STUDIES, vol. 7, no. 2 , pp. 134–155, 2020, [Online]. Available: https://sid.ir/paper/963285/en

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