A Need-Based Approach for Modeling Recurrent Discretionary Activity Participation Patterns for Travel Demand Analysis

Abstract

As society advances and various technologies like AI and LLMs are further developed, the proportion of human labor contributing to the productivity of nations and societies is gradually decreasing. This has led to increased attention to the quality of life of individuals, and cases of implementing policies such as a four-day work week are on the rise. Therefore, the objective of this study was to analyze the patterns of how people are spending their increased leisure time amid this social trend and to identify the factors influencing these patterns. Building upon the need-based theory proposed in previous studies, this research analyzed people’s recurrent discretionary activity patterns. Multiday analysis was conducted considering the characteristics of leisure activity patterns, and a hazard-based duration model was estimated for statistical analysis. The research results revealed that people’s patterns of consecutive activities are influenced by various factors, such as socio-economic attributes, time–space budgets, previous activity experiences, and preferences for specific days of the week. Through this, we were able to confirm that socio-demographic and household characteristics, as well as attributes of time/space budgets, influence the growth speed and threshold of needs as suggested in need-based theory. Additionally, we observed a preference for specific days of the week for different types of activities. As a result, people tend to either postpone activities until specific days even when their need has accumulated sufficiently or engage in activities on specific days even when the need has not yet accumulated to the desired level. This study demonstrates novelty in that it utilizes the need-based theory proposed in prior research to identify factors influencing multiday activity participation patterns. Additionally, it presents the first study providing model estimation results from the perspective of need-based theory. The correlation between the time–space budget and discretionary activity patterns identified in this study is expected to serve as a guideline for future transportation-related policies, including regional balanced development. This study demonstrates a unique contribution compared to existing research in that it established that, with improvements in activity/travel conditions, there can be an induced demand for activities. This finding can contribute to the feasibility study of transportation projects and the establishment of policies related to regional balanced development.