Private versus verifiable interim performance evaluations under uncertainty

Terstiege, Stefan

doi:10.1016/j.econlet.2014.03.014

Cited by 3 publications

(1 citation statement)

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“…The allocation of weights significantly influences the ultimate selection of the preferred option. When making these judgments, there are two methods for determining the importance: One is subjective, based on personal opinion and the other is objective, based on facts or statistics (Terstiege, 2013).…”

Section: Introductionmentioning

confidence: 99%

Application of Preference Selection Index and TOPSIS in Product Aspect Extraction and Ranking

Alrababah,

Alsrehin

2024

Journal of Computer Science

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Decision-making methodologies can differentiate between several types of criterion weights. The subjective weights of decision-makers are prone to be influenced by various factors, including their level of knowledge, experience and competency. This may result in the wrong evaluation of the criteria due to the inherent ambiguity of human judgments, leading to unavoidable assessment errors. Beyond that, while assessing the decision alternatives, the majority of Multiple Criteria Decision Making (MCDM) take the evaluation criteria into consideration separately. However, in actual application, most of the criteria are not mutually exclusive. In the context of online customer reviews, it is essential to prioritize product aspects in order to facilitate the purchasing process for potential consumers. Selecting the appropriate product aspects is a difficult task due to the vast quantity of product reviews. This research develops an MCDM solution through the integration of the Preference Selection Index (PSI) with The approach for Order Preference by Similarity to an Ideal Solution (TOPSIS) method for decision-making. The contribution of this study is to enhance the TOPSIS ranking technique by incorporating PSI objective weights as an alternative to subjective weights. PSI offers the benefit of focusing on the convergence of the criteria involved rather than their divergence. This approach will improve the ranking process of TOPSIS by taking into account the interconnectedness of the criteria, hence facilitating the prioritization of significant aspects of a product based on online reviews. A dataset comprising four electronic products was utilized as a reference for conducting a statistical analysis. Through the examination of the outcomes utilizing the discount cumulative gain metric, it becomes apparent that the combination of the TOPSIS approach alongside PSI weights facilitates the identification of the suitable product aspects that effectively differentiate the one that aligns with consumer expectations.

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Section: Introductionmentioning

confidence: 99%