Utilizing Case-based Reasoning for Consumer Choice Prediction based on the Similarity of Compared Alternative Sets

• 발행기관: 한국유통과학회
• 저자명: Sang Yun SEO Sang Duck KIM Seong Chan JO
• 간행물 정보: 『The Journal of Asian Finance, Economics and Business(JAFEB)』Vol. 7 No.2, 221~228쪽, 전체 8쪽
• 주제분류: 경제경영 > 경제학
• 파일형태: PDF
• 발행일자: 2020.02.28

영문 초록

This study suggests an alternative to the conventional collaborative filtering method for predicting consumer choice, using case-based reasoning. The algorithm of case-based reasoning determines the similarity between the alternative sets that each subject chooses. Case-based reasoning uses the inverse of the normalized Euclidian distance as a similarity measurement. This normalized distance is calculated by the ratio of difference between each attribute level relative to the maximum range between the lowest and highest level. The alternative case-based reasoning based on similarity predicts a target subject’s choice by applying the utility values of the subjects most similar to the target subject to calculate the utility of the profiles that the target subject chooses. This approach assumes that subjects who deliberate in a similar alternative set may have similar preferences for each attribute level in decision making. The result shows the similarity between comparable alternatives the consumers consider buying is a significant factor to predict the consumer choice. Also the interaction effect has a positive influence on the predictive accuracy. This implies the consumers who looked into the same alternatives can probably pick up the same product at the end. The suggested alternative requires fewer predictors than conjoint analysis for predicting customer choices.

목차

1. Introduction

2. Literature Review

3. Research Methods

4. Empirical Study

5. Conclusion

References

키워드

Similarity of choice alternative set Case-based reasoning Choice prediction, Product recommendation Conjoint analysis