Impact of different shopping stages on shopping-related travel behaviour: analyses of the Netherlands Mobility Panel data

From the moment e-shopping emerged, there have been speculations about its impact on personal mobility. A fair amount of research has already been carried out on Internet shopping itself as well as on its consequences for mobility. Most studies focus on the overall impact of online shopping on personal mobility. However, little is known about how personal shopping mobility can be characterised when differentiating its constituent stages, being browsing/orienting, comparing, selecting and purchasing products, and how this is affected by e-shopping. This will be the main topic of this paper. We will investigate this using recently collected data from the Netherlands Mobility Panel [in Dutch: MobiliteitsPanel Nederland (MPN)]. It is the unique combination of reported shopping trips in the three-day travel diary, the large amount of personal and household characteristics combined with the detailed information from the e-shopping questionnaire that enables us to perform this research. Using factor analysis, we explore the underlying factors related to the browsing and selection behaviour prior to the purchase of a product. Using these factors as a starting point, we apply cluster analysis resulting in three homogeneous groups of shoppers with different pre-purchase shopping behaviour. The groups differ clearly with respect to personal and household characteristics, in the frequency with which they buy and sell products online and in their perception of (dis-)advantages of online shopping. Once relevant groups have been distinguished and characterised, differences in shopping-related mobility between them are studied in two different ways. Firstly, we analyse statements from shoppers on how their shopping-related mobility has changed. Secondly, we analyse shopping trips reported in the three-day travel diary. Only one group, which consists of shoppers that rely on the Internet to search for product information, compare prices and get new product ideas, states that their shopping-related travel behaviour has changed since they started shopping online. Approximately 50% of all shoppers experienced no difference in their shopping mobility. The analysis of actual shopping mobility using the travel diary data showed only minor differences in shopping-related travel behaviour between the identified groups. Finally, we fit a multi-variate linear regression model of shopping trip distance to determine if (e)-shopping characteristics influence trip distances. The frequency with which people shop online as well as some stated changes in shopping-related travel behaviour (shopping in a similar manner and shopping longer) turn out to influence non-grocery shopping trip distance. No significant influence could be found of shopping cluster membership on shopping trip distances.