Multipurpose shopping is a prominent and relevant feature of shopping behavior. However, no methodology is available to assess empirically how the demand for multipurpose shopping depends on retail agglomeration or, in general, the characteristics of retail supply, such as the numbers and types of stores in a shopping center or the number of categories in a supermarket. The authors propose a nested-logit model that captures retail agglomeration effects on consumer choice of shopping trip purpose (what to buy) and destination (where to buy). The authors estimate parameters representing trip purpose-adjustment and between-store attraction effects on shopping trip data collected from a sample of 1704 households in The Netherlands. Both effects are significant for each of the three categories for which the model is estimated. This is consistent with the idea of agglomeration effects. The findings suggest that agglomeration helps attract not only multipurpose but also single-purpose trips. A comparison of multi- and single-purpose trip model predictions shows that single-purpose models underpredict the number of trips to larger shopping centers.

Consumers are widely adopting Artificially Intelligent Voice Assistants (AIVAs). AIVAs now handle many different everyday tasks and are also increasingly assisting consumers with purchasing decisions, making AIVAs a rich topic for marketing researchers. We develop a series of propositions regarding how consumer decision-making processes may change when moved from traditional online purchase environments to AI-powered voice-based dialogs, in the hopes of encouraging further academic thinking and research in this rapidly developing, high impact area of consumer-firm interaction. We also provide suggestions for marketing managers and policymakers on points to pay attention to when they respond to the proposed effects of AIVAs on consumer decisions.

Over the past decades, the use of mobile technology has increased and the attitude towards work has changed, making it possible to work anywhere at any time. However, workers still seek work environments that stimulate networking and collaboration possibilities. This has led to the growing popularity of co-working spaces. However, little is known about the specific preferences of co-working space users. The aim of this research is to analyse user preferences for co-working space characteristics. Stated choice data were collected by means of a questionnaire which was completed by 219 respondents of 25 co-working spaces in the Netherlands. A mixed-multinomial logit model was used to analyse the user preferences. Results show that the main motivations for co-workers to work in a co-working space were that they were looking for a workplace outside their home that allows them to work in an inspiring work environment where the accommodation is affordable. Accessibility and atmosphere/interior are the most important characteristics when choosing a specific co-working space. These results provide owners or managers of co-working spaces with clear insights about how to cope with co-worker preferences by offering co-working spaces with good accessibility by car and public transport, a semi-open layout and a homelike interior.