No abstract

This study explores the aging population’s behavior toward the adoption of and willingness to pay (WTP) for autonomous vehicles (AVs), with a focus on the roles of attitudes and land use variables. A structural equation model with interaction effects was developed to explore the impacts of socioeconomic and demographic attributes, mobility profiles, attitudes collected through a user behavior survey, and land use variables extracted from the Smart Location database. Among different structures tested, a direct causal effect from adoption to WTP shows the best model fit, implying that any parameter affecting the adoption will indirectly affect WTP in the same direction. Focusing on the older population, the model results show that they were positively affected by their interest in driving assistance and safety features. Older adults also seemed to be more sensitive to mobility costs compared with younger travelers. We further explored the impact of land use characteristics. In general, it appears that living in areas associated with higher population density and higher centrality index (based on auto accessibility) tends to lower AV adoption rates. Comparing the older population with younger people, no significant difference was observed in view of land use impacts on AV adoption. However, the older population’s WTP tends to increase in urban areas with higher roadway network densities (e.g., urban areas) and is likely to decrease in neighborhoods with higher employment density and higher percentage of single-vehicle households. We suggest that the latter effect might be associated with other micro-level attributes such as their income and lifestyle patterns.

No abstract

The rise in e-commerce adoption and decline in in-store shopping at the peak of the COVID-19 pandemic sparked optimism among researchers and transport planners on the potential of e-commerce in reducing shopping trips. However, fluctuations in consumers’ attitudes and shopping habits across the COVID-19 timeline add to the mix and necessitate an investigation into the travel effects of consumers’ evolving shopping behavior. In this regard, this study examines the interactions between the frequency of online shopping and shopping trips and the mediating effects of shoppers’ attitudes in early 2021. Over 2,000 Florida residents were surveyed to explore how various socio-economic, demographic and household characteristics, and attitudes influenced their shopping behavior for four types of non-grocery experience goods, namely clothing, shoes, watches, and jewelry (CSWJ); beauty and health products (BH); toys, kids, and baby supplies (TKB); home, garden, and tools (HGT). Structural equation models were developed to analyze their shopping patterns for each of the products, and results showed that the interactions between online and in-store purchase frequencies for CSWJ and TKB exhibited complementarity effects in both directions. For the other product types, online shopping had positive effects on in-store shopping frequency, but no effects were found in the reverse direction. Results also showed that personal attitudes played important roles in individuals’ shopping decisions, and there were significant mediating effects for a number of personal and household attributes. Tech savviness and the preferences toward alternative modes and online shopping benefits had direct positive influences on online shopping frequency, while the joy of shopping (i.e., shopping for leisure) and privacy and security concerns tended to increase in-store shopping frequency. Concerns regarding unattended delivery had negative impacts on online shopping frequency, while preferences toward the benefits of online shopping showed negative impacts on in-store shopping frequency. Based on these findings, the traffic implications of the expected higher delivery demand and passenger travel are discussed.

No abstract