Abstract
This research focuses on understanding the impact of the type of shopping activity (general shopping goods, grocery, prepared meals) on shopping channel (in-person vs. online shopping) preferences. To better understand consumer decisions in the post-COVID era, this study used a large-scale consumer behaviour survey in New Delhi, India, with 1798 respondents to develop multivariate ordered probit models (MORP) involving in-person shopping travel frequencies (INFs) and online delivery frequencies (ONFs). Considering the online and physical shopping decision counterparts in a joint modelling framework enabled us to quantify the determinants of online shopping and in-person shopping frequencies and how they vary across consumption categories. The influences of demographic characteristics (e.g., car ownership, income, mode choice) and attitudes (e.g., tech-savviness, attitude towards perceived risks of online shopping) were delineated in the analysis by treating them as exogenous predictors. The model estimation results and discussions in this study are expected to help advance the understanding of how the emergence of online shopping and delivery-based services are influencing activity-travel patterns and choices in the aftermath of the pandemic.
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Pani, A., Unnikrishnan, A., Sinha, S. et al. Shopping Travel Behaviour Trade-Offs Between Physical Stores and Online Deliveries: Post-COVID Scenario in New Delhi, India. Transp. in Dev. Econ. 10, 17 (2024). https://doi.org/10.1007/s40890-024-00203-3
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DOI: https://doi.org/10.1007/s40890-024-00203-3