A Study of Presentation Patterns of Multi-Attribute tables for Consumer Decision Support

2022 Fiscal Year Final Research Report

• Project/Area Number: 19K13844
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 07090:Commerce-related
• Research Institution: Tokyo University of Science (2022); Tokuyama University (2019-2021)
• Principal Investigator: Ideno Takashi 東京理科大学, 経営学部経営学科, 教授 (40805628)
• Project Period (FY): 2019-04-01 – 2023-03-31
• Keywords: 多属性意思決定 / 消費者行動 / 情報モニタリング法 / 意思決定方略 / 提示様式

Outline of Final Research Achievements

The purpose of this study was to examine the relationship between the presentation style of multi-attribute information and the decision-making process, and to propose a presentation style to support consumers' decision-making. This study 1) developed an experimental method that applies the information monitoring method to the examination of the decision-making process and an analysis method, and 2) created a platform that integrates both methods. Based on the results of experiments using this platform, we presented the influence of the decision-making process by the expression of attribute values of multi-attribute information and the layout of the table showing multi-attribute information on the ease of decision-making. In addition, based on data on information searching in the decision-making process, deep learning was used to formulate a decision-making strategy.

Free Research Field

消費者行動

Academic Significance and Societal Importance of the Research Achievements

これまでの意思決定研究では、選択の状況依存的な側面が強調されてきた一方、情報の呈示様式と意思決定との関連の検討はあまり進んでいない。今日の情報環境の進展を受け、さまざまな情報提示様式がe-コマースなどでは見られているが、どのような呈示様式が特定の意思決定方略と結びついているかを検討する枠組み、そして検討が進展していない。そこで、本研究では、図的表現を取り入れた多属性情報の呈示方法を開発して実験を行い、シミュレーションや深層学習を用いた意思決定方略を推定するという研究枠組みを開発した。