AHP AND DEA: AN ALTERNATIVE APPROACH TO EVALUATING ONLINE REVIEWS
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Abstract
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The use of the Internet and its applications has radically transformed the ways in which consumers communicate, obtain information and make purchasing decisions. This work aims to identify innovative solutions to facilitate and make the process of searching and booking restaurant services by users who use digital platforms more efficient. The main objective is to analyze the intrinsic complexity of the user’s decision-making process, highlighting the main critical issues and difficulties with perception and possible information distortions, in order to design a support tool capable of offering a highly personalized and high-quality choice experience. The contribution proposes an advanced decision-making model that integrates the use of two multi-criteria methodologies: the Analytic Hierarchy Process (AHP) and the Data Envelopment Analysis (DEA). These tools make it possible to simultaneously consider a multiplicity of qualitative and quantitative criteria, configuring an evaluation much more adherent to the real preferences of users. The combined adoption of these two approaches constitutes a methodological innovation capable of providing each user with a dynamic, personalized and efficient search path, significantly improving the quality of decisions and the level of perceived satisfaction. This model, which overcomes the limitations of traditional recommendation systems based on simple averages is proposed as a reference tool for the design of online platforms dedicated to catering, with potential extensions to other service sectors.
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AHP, DEA, EFFICIENCY, MCDM, customer satisfaction
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