This study clarifies the previously unknown limitations of the entropy-based land-use mix index and suggests conditions under which the index is valid. The land-use mix index has an n-shaped relationship to dependent variables, which was evidenced by this study, but previous studies have ignored the problem. This study identified a non-linear relationship between the land-use mix index and a common dependent variable of interest, pedestrian volume. Pedestrian volume is a common measure of the vitality of a district and/or a city and a major goal of urban design and regeneration. Using mathematical analysis, simulation, and empirical analysis, this study found that the land-use mix index had an inconsistent quadratic relationship to pedestrian volume. It was confirmed that an analytical model using the land-use mix index, and that index squared, should be used together when samples representative of entire cities are tested. Otherwise, in samples from predominantly residential areas, the land-use mix index positively relates to pedestrian volume, whereas, in predominantly commercial areas, it will be negative. Previous studies failed to observe the hidden side of the entropy-based land-use mix index in commercial areas because their focus was mainly on residential areas or residents. Future studies should clarify the logical and theoretical relationships between the index and the outcome variable of interest, review the characteristics of the data and, then, implement appropriate statistical analyses by being aware of the hidden side.

This study confirmed the general belief of urban planners that mixed land use promotes walking in Seoul, a metropolis in East Asia, by analyzing the effect of mixed land use on the travel mode choice of housewives and unemployed people who make non-commuting trips on weekdays. Using binomial logistic regression of commuting data, it was found that the more mixed a neighborhood environment’s uses are, the more the pedestrians prefer to walk rather than drive. The nonlinear relationship between the land use mix index and the choice to walk was also confirmed. Although mixed land use in neighborhoods increased the probability of residents choosing walking over using cars, when the degree of complexity increased above a certain level, the opposite effect was observed. As the density of commercial areas increased, the probability of selecting walking increased. In addition to locational characteristics, income and housing type were also major factors affecting the choice to walk; i.e., when the residents’ neighborhood environment was controlled for higher income and living in an apartment rather than multi-family or single-family housing, they were more likely to choose driving over walking.

Placeness is believed to play a significant role in enhancing the well-being and place-use of individuals, contributing profoundly to how spaces are experienced and interacted with. Despite its perceived importance, there is ongoing debate and insufficient clarity about how exactly placeness influences people’s behavior. This study aims to bridge this gap by theorizing and investigating the pathways from placeness to people’s behavioral intentions, emphasizing the roles of personal place attachment and public place image as pivotal mediators in this relationship. To explore these dynamics, we conducted a survey in Japan, examining the complex interplay between placeness and behavioral intentions, given their rich cultural heritage and modern urban pressures. We employed the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach for path analysis. The analysis suggests that placeness influences behavioral intention through personal place attachment. While placeness does affect public place image, this public image does not have an impact on behavioral intention. The results demonstrated that an individual’s activities, experiences, and cognition of a place are significant factors in creating the intention to engage in word-of-mouth, recommendation, and revisiting behaviors. Policymakers, urban planners, and designers need to understand how to foster people’s behavioral intentions when creating a place imbued with placeness.

This study proposes an alternative to the conventional entropy-based land use mix index, which is generally used to measure the diversity of land use. Pedestrian volume was selected as the dependent variable as it represents the vitality of districts, which many recent urban studies now consider important. The study investigates an entropy-based weighted land use mix index, which is weighted by different land use types. For the index, different areas are needed to generate a unit of pedestrian volume, whose measure is m²/person/day. The study demonstrates that this alternative is more effective than the existing conventionally used entropy-based land use mix index for explaining pedestrian volume. The research confirms that the conventionally used entropy-based land use mix index can have a positive or negative impact depending on the land use characteristics of the survey points because the conventionally used entropy-based land use mix index has a non-linear relationship with pedestrian volume. By analysing 9727 surveyed locations of pedestrian volume in Seoul, Korea, the study demonstrates that the weighted land use mix index, rather than the conventionally used entropy-based land use mix index, can improve the explanatory power of the estimation model for the relationship between pedestrian volume and built environments, showing consistent results throughout the empirical analysis. In future built-environment studies, the utility of the weighted land use mix index is expected to improve if studies include how to find the accurate weighting of the land use in estimating the pedestrian volume.

In the context of China’s New Urbanization Strategy, it is of great practical significance to study rural–urban population migration from the perspective of house purchases by rural households. In this paper, the Huai’an Rural Survey Dataset (872,414 households) was used to study the heterogeneity of rural households’ house purchases in different classes of urban destinations, and its influencing factors were analyzed with GeoDetector. The results show that the urban house purchase destinations preferred by farmers were county towns, townships, foreign cities, and metropolitan areas, indicating that in situ urbanization has become the main path of urbanization for farmers in Huai’an. Among the environmental influencing factors, the rural environment had the greatest influence on house purchases locally (in the township and county town), and this influence decreased with the outward shift of house purchase destinations. The housing environment, the settlement environment, and the population and family environment were the main environmental impact elements. The natural environment and the policy environment had little influence on the house-purchasing behavior of farmers, and the location environment was critical in exotic locations (metropolitan areas and foreign cities). Therefore, this paper argues that a higher demand for housing is growing in China’s less developed rural areas, creating a situation in which the metropolitan area is the core and the county town is the main contributor. In terms of policy improvements, it is important to pay more attention to small cities such as counties and to offer housing concessions and welfare to “new citizens” from rural areas, as well as to significantly improve the housing, earnings, and public service environment for those who prefer to stay in the countryside.