The Interaction between E‐Shopping and Shopping Trips: An Analysis with 2017 NHTS

Abstract

Advances in information and communication technologies (ICT) have dramatically changed the nature of shopping and the way people travel. As this technology becomes deeply rooted in people’s lives, understanding the interplay between this way and personal travel is becoming increasingly important for planners. Using travel diary data from the 2017 National Household Travel Survey (NHTS) data for structural equation modeling (SEM) analysis, it revealed the interaction between e-shopping and shopping trips and the factors that affect this bidirectional relationship. Results show that e-shopping motivates shopping trips, and in-store shopping inhibits online shopping. It can be obtained that the increase of one standard deviation of e-shopping will increase the shopping trip by 0.17 standard deviation. When shopping trips increase by one standard deviation, e-shopping behavior also decreases by 0.12 standard deviation. The results also demonstrated that e-shopping and shopping travel behavior is heterogeneous across a variety of exogenous factors such as personal attributes, household characteristics, geography, travel distance/duration, and travel mode. Identifying the interaction may help formulate better transportation policies and lay the foundation for travel demand management strategies to reduce the stress on the transportation system and meet individual travel needs.

Impacts of E-commerce on Shopping Trips for Non-grocery Experience Goods

“…In addition, our results indicate that those with lower levels of education (i.e., having an associate degree or less) tended to shop online less frequently compared to in-store shopping, while those with a post-graduate degree showed the opposite effects (less in-store purchases compared to online purchases). These ndings are consistent with the literature (Cao et al, 2012;Lee et al, 2015;Ramirez, 2019;Xue et al, 2021). This could be attributed to the low tech-savviness of individuals with lower level of education (i.e., high school graduates) and post-graduate degree holders' less concern for unattended delivery.…”

“…Other factors that have been found to in uence shopping behavior are number of productive family members (Irawan & Wirza, 2015), possession of a driver's license (Xue et al, 2021;Zhen et al, 2016) or number of household members with drivers' license (Irawan & Wirza, 2015;Ramirez, 2019), the density of shoppers' residence areas (Ramirez, 2019), the variety or quantity of products to be purchased (Hess et al, 2013)…”

“…It may be that since those who have cars tend to be wealthier and have higher value of time, frequent commuting to physical stores is less desirable and often replaced by online shopping. Although results seem to differ by country, studies conducted in the U.S. have indicated that car ownership is not linked with a higher likelihood of online shopping and public transportation commuters may be more likely than others to make frequent online purchases (Farag et al, 2006;Ramirez, 2019;Xue et al, 2021).…”

Online and in-store shopping interactions for non-essential experience goods

“…Many studies have shown evidence of complementarity, that is, online shopping increased shopping travel (Cao, 2012;Cao et al, 2012;Ding & Lu, 2017;Etminani-Ghasrodashti & Hamidi, 2020;Farag et al, 2006;Hiselius et al, 2015;Ramirez, 2019;Xue et al, 2021;Zhen et al, 2016;Zhou & Wang, 2014). Contrastingly, some studies have found substitution effects (Irawan & Wirza, 2015;Shi et al, 2019;Zhen et al, 2018) and others have suggested neutrality or some form of modification effects on shopping duration, travel time, or trip distances (Hoogendoorn-Lanser et al, 2019;Kedia et al, 2019;Lachapelle & Jean-Germain, 2019).…”

“…Mixed results have also been recorded by studies that examined the reciprocal effects between online and in-store shopping. For example, studies like Ding and Lu (2017); Etminani-Ghasrodashti and Hamidi (2020);and Farag et al (2007) found that instore shopping led to more online shopping, while other studies like Zhou & Wang (2014); and Xue et al (2021) that analyzed the 2009 and 2017 National Household Travel Surveys (NHTS) datasets, respectively, indicated that in-store shopping frequency negatively affected online shopping frequency among U.S. residents. Among the many factors that could explain the mixed findings of past studies (e.g., the stage of the shopping process considered, specific shopping timeframe measured, the performance measures used, the research design and analysis methods, the geographical areas under study, sample characteristics, etc.…”