| Description |
1 online resource (xii, 181 pages) : illustrations |
| Series |
International series in operations research & management science ; volume 339 |
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International series in operations research & management science ; 339.
|
| Contents |
Effect of Customer Travel Behavior on Grid Layout and Shelf -- A Solver-Free Heuristic for Store-wide Shelf Space Allocation -- In-Store Tra c Density Estimation -- A Simulation Based Tool to Guide Periodic Changes in a Supermarket Layout -- Data-Driven Analytical Grocery Store Design -- Optimizing Stock-Keeping Unit Selection for Promotional Display Space at Grocery Retailers -- Merchandise Placement Optimization -- Problems and Opportunities of Applied Optimization Models in Retail Space Planning |
| Summary |
This edited volume presents state-of-the-art research that can leverage large-scale sensory data collected in grocery/retail stores where a single customer visit may generate nearly 10,000 data points. For decades, retail shelf space optimization has been confined to the analysis of product allocation decisions over a limited number of shelves, often taken in isolation. Such models incorporated interesting concepts relating to space and cross-space elasticity in the design of planograms. Although useful, these models have not addressed the bigger picture of planning store shelf space in a more holistic manner. It is important to note that the space planning analytics in the book are particularly important in an era where e-commerce is on the rise and brick-and-mortar retailing is declining and experiencing severe crises (the retail apocalypse). This is the first research-oriented book that examines novel problems in store space analytics, triggered by modern-day sensory technologies, customer trackers, and transactional tools (point-of-sales, etc.). In fact, such transformative technologies have prompted the development of new and exciting business practices, accompanied by the need for powerful data-driven models and analyses in retail shelf space and layout planning. The book will facilitate developing algorithms and decision tools that allow a better leverage of the data collected from these mediums |
| Bibliography |
Includes bibliographical references |
| Notes |
Print version record |
| Subject |
Stores, Retail -- Data processing
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Business intelligence.
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Consumer behavior -- Data processing
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Business intelligence
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Consumer behavior -- Data processing
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| Form |
Electronic book
|
| Author |
Ghoniem, Ahmed, editor
|
|
Maddah, Bacel, editor
|
| ISBN |
9783031270581 |
|
3031270584 |
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