A Time and Income Allocation Model for Consumer's Cross Media Usage Based on Statistical Data

2023 Fiscal Year Final Research Report

• Project/Area Number: 18K01902
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 07090:Commerce-related
• Research Institution: Kwansei Gakuin University
• Principal Investigator: YAMADA TAKAKO 関西学院大学, 総合政策学部, 教授 (80272053)
• Project Period (FY): 2018-04-01 – 2024-03-31
• Keywords: 調査データ / 消費者 / 時間配分 / メディア接触

Outline of Final Research Achievements

I worked on analyzing consumer time-use behavior in 2019 before Covid-19 and during 2020 amid Covid-19. Home and outside activities were classified into four clusters pre and post-pandemic which reveal different time consumption patterns. I conducted attribute comparisons such as age, income, marital status, etc., among the clusters and proceeded to generate artificial consumer time-use data using machine learning based on these results. The study elucidated how consumer time allocation behaviors shifted due to Covid-19. Though my research encountered unexpected disruptions, including interruptions due to Covid-19, the impact on time allocation behaviors became evident. I am currently engaged in analysis to continue developing income allocation models.

Free Research Field

商学

Academic Significance and Societal Importance of the Research Achievements

Covid-19による生活者のライフスタイルの変化を調査データから明らかにした。特に時間帯別在宅外出の生活パターンがCovid-19で生じた変化をクラスタ分析で明らかにし、クラスタ別の年齢、性別、職業など特徴の違いも明らかにした。本研究から、世界的パンデミックが日本人にもたらした生活行動の変化を、定量的データで示すとともに、機械学習手法を用いて、このような時間帯別生活行動の人工的なデータ生成が限定的な時間帯行動データから可能であることを確認した。これらの成果は、データプログラミングでもあり、人工的な消費者データ生成の第一歩と考えている。