Prioritization of Revenue Management Factors: A Synthetic Extent Analysis Approach

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Purpose: This paper presents a novel approach for revealing the success factors of revenue management practices in hospitality industry. Our study aims to point out the favorably contributing ‘ingredients’ of a successful revenue management application. We investigate what revenue managers have learned from their past experience by using real empirical data and fuzzy synthetic evaluation procedure. Researchers and practitioners may regard this work as a functional benchmark analyzing a function (revenue management) which is widely used in those companies belongs to a particular industry (hospitality industry). Design/methodology/approach: Revenue managers’ judgments about the underlying success factors are highly subjective and qualitative in nature. In order to capture this imprecision, we employed the fuzzy synthetic extent analysis and provided with a sensible prioritization of the success factors. Research limitations/implications: Employing fuzzy concepts within a prioritization procedure requires constructing a fuzzy linguistic variable set and as-signing a fuzzy conversion scale to it. Usually the implementation steps in fuzzy techniques are more cumbersome when compared to the conventional multi attribute techniques (i.e. conventional AHP). Originality/value: This paper discusses the prioritization of effective factors that concede to a successful revenue management application in hospitality industry with a synthetic extent analysis approach. This paper provides with a ‘snapshot’ of the current practice in the area and serves for researchers and practitioners.

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Fuzzy prioritization , synthetic extent analysis , revenue management , hospitality industry.

Ege Academic Review (EAR)

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Ege Academic Review (EAR)