Asymmetrical impact of service attribute performance on consumer satisfaction: an asymmetric impact-attention-performance analysis

Abstract

Analyzing the asymmetrical effects of service attribute performance on customer satisfaction can identify the different effects of service attributes on overall satisfaction at different levels of performance; it can compensate for the shortcomings of conventional linear regression analysis. Previous research on the asymmetrical relationship between restaurant attribute performance and satisfaction has lacked an assessment of market segmentation differences; it has also adopted an attribute priority division method based on the asymmetrical relationship, ignoring consumers’ attention to attributes. This paper presents a method to analyze the asymmetrical impact of service attributes performance on satisfaction based on online reviews. First, the sentiment score of the restaurant attributes were calculated by aspect-based sentiment classification and a clustering algorithm. Second, the asymmetrical influence of attribute performance on satisfaction was explored according to the sentiment score of the attributes. Finally, consumers’ attention to attributes was measured according to the frequency of attribute mentions and the priority of attribute promotion was investigated by integrating the asymmetrical impact-attention-performance analysis (AIAPA) model of attention. Based on the analysis of 92,904 online restaurant reviews in Tokyo collected on TripAdvisor using the proposed method, this research founds that the performance of most restaurant attributes has an asymmetrical effect on satisfaction. The asymmetrical effect of restaurant attribute performance on satisfaction varies by seasons and market segments. Using the AIAPA model, this research identifies the attribute priority of different restaurant types in different seasons.