The article adds urban tourist demand into the classic production-constrained spatial interaction model (SIM) to improve performance predictions for both existing and new grocery stores in urban tourist areas.
The new tourist SIM model is built upon four disaggregated tourist grocery demand layers across London. The model is calibrated by using origin-destination flows from large-scale survey and social media data. The additional tourist SIM is used to estimate store-level revenue uplifts and operationalise three “what-if” scenarios for retail location planning.
The article shows the benefit of incorporating additional tourist demand within the retail planning process, highlighting the revenue uplift from tourism and how the tourist SIM offers deeper insights into local demand composition, assisting retail decision-making.
Due to the lack of empirical store sales and performance data, individual store calibration was limited.
The article includes implications for retail decision-making in destinations where urban tourist demand is common and important. Investment in areas with insufficient tourist food shopping provision may not only bring potential profit to local food retailers but could also improve the tourist experience.
The article addresses the importance of incorporating tourist demand into retail location analysis to provide more accurate and actionable insights for retail planning in urban destinations.
