Development of joint models for channel, store, and travel mode choice: Grocery shopping in London

Abstract

The nature of shopping activity is changing in response to innovation in retailing and the growth in online channels. There is a growing interest from transport researchers, policy makers, marketing and retail businesses in understanding the implications of this change. However, existing tools and techniques developed for analysing behaviour in traditional retail environments do not adequately represent emerging complexities resulting from digital innovation. In this paper, we advance existing destination and mode choice models by incorporating online channels in a unified framework. This is a critical extension to existing transport literature on destination choice which largely ignores online activity. Specifically, we develop discrete choice models using elemental store (including both online and in-store) alternatives for joint choice of channel, store, and travel mode. We demonstrate the use of a widely-accepted consumer panel dataset with minor modifications, for the first time in transport research, together with API based data mining tools that offer great potential for enrichment.The analysis focuses on grocery shopping and uses consumer data collected from two selected boroughs in London; results from multinomial logit and nested logit estimations are reported. The extension presented here provides the tools to quantify the effects of increased online shopping on traditional store formats and travel patterns. Our results showed virtual alternatives currently offer an attractive substitute among early adopters for large basket shopping mostly for high income groups. This might suggest a significant reduction in shopping trips to hypermarkets often associated with large basket shopping potentially leading to store closures. Online deliveries mostly draw from driving trips and less so from walking and public transport trips. The present study also confirmed previous findings related to smaller stores and longer travel distances being associated with declining utilities, agglomeration and competition significantly influencing store choice.