Comparative analysis of MCDM methods for product aspect ranking: TOPSIS and VIKOR

Abstract

The extracted product aspects (like “battery life”, “zoom”) from online customer reviews are dissimilar in their significances, some of these aspects have a great influence on the potential customer's decision likewise on the businesses' strategies for product enhancements. Supporting the probable customers with a list of the most representative product aspects will assist their purchasing decision and facilitate the comparative process among the presented products. For the firms, identifying critical product aspects creates a new perspective of product manufacturing and marketing strategies to be competitive and innovative. However the manual identification of the most representative product aspects from the huge amounts of the extracted product aspects in online reviews is a tedious and time-consuming task. Thus, ranking the extracted aspects becomes a necessity to identify the important product aspects mentioned in the customer reviews. The purpose of this study is to formulate the product aspect ranking problem as a decision making process using Multi-Criteria Decision Making (MCDM). In response, a comparative analysis between two different MCDM ranking approaches, namely; TOPSIS and VIKOR has been conducted to investigate their performances in prioritizing the most important product aspects in customer reviews. The experimental results on different product reviews demonstrate the effectiveness of these two methods in prioritizing the genuine product aspects in customer feedback.