Integrating Location Intelligence within Shopping Centre Reconfiguration: A Monte Carlo Simulation
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2025-01-07
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5233
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Technological advancements and evolving consumer behaviors have significantly transformed the retail landscape. Traditional shopping centers, now under pressure to innovate, are leveraging location intelligence—insights from geospatial data—to stay relevant. This study explores how spatial big data can enhance leasing decisions for store expansions using Monte Carlo simulations. Focusing on a fast-fashion retailer considering expanding from 14,000 sqft to 30,000 sqft within a shopping center, it examines the impacts on sales performance. Data from Wi-Fi beacons, capturing customer traffic and sales trends from January 2022 to December 2023, provides a robust basis for analysis. The study aims to offer a quantifiable method for shopping center landlords and retailers to make informed leasing decisions under uncertainty, with two primary research objectives: leveraging spatial big data to enhance store expansion decisions and understanding how increased retail square footage impacts sales performance.
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Geospatial Big Data Analytics, location intelligence; monte carlo simulation, retail location decision-making, retail location planning, shopping centres
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10
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Proceedings of the 58th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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