Deciding a Location: Navigating a Biometric Apparel Retailer’s Expansion from Online to Brick-and-Mortar
Journal
Business Data Decisions | Data Challenge
Type
case study
Date Issued
2024
Author(s)
Editor(s)
Caroline Glackin
Abstract
In the contemporary entrepreneurship landscape of retail startups, the transition from online to offline operations presents both challenges and opportunities for businesses seeking to expand their distribution network. This data challenge offers a comprehensive exploration of the strategic considerations and data-driven methodologies essential for a company to successfully choose optimal locations for opening its first physical retail outlet. Students will assume the role of Stefano Agnesi, a newly appointed Chief Physical Retail officer, tasked with guiding an e-commerce company called BioMetricWear in expanding into the realm of physical storefronts. Through the lens of data analytics, students will be introduced to a diverse array of metrics and variables critical to assessing optimal store locations. From demographic profiles and target market sizes to foot traffic patterns and competitive landscapes, the data challenge delves into the multifaceted dimensions that shape retail success. Drawing upon a fictitious curated dataset, students will engage in weighted scoring methods to identify prime locations for the company’s inaugural branded stores. Prior to this data challenge, students should be familiar with basic statistical analyses (like regression and cluster analysis), as well as know Z-standardization and weighted scoring methods.
Language
English (United States)
Publisher
SAGE Publications, Inc.
Subject(s)
Division(s)