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Titlebook: Retail Space Analytics; Ahmed Ghoniem,Bacel Maddah Book 2023 The Editor(s) (if applicable) and The Author(s), under exclusive license to S

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書目名稱Retail Space Analytics
編輯Ahmed Ghoniem,Bacel Maddah
視頻videohttp://file.papertrans.cn/829/828944/828944.mp4
概述The first research-oriented book that examines novel problems in store space analytics.Editors and chapter authors are among the most actively published in the field.Presents state-of-the-art research
叢書名稱International Series in Operations Research & Management Science
圖書封面Titlebook: Retail Space Analytics;  Ahmed Ghoniem,Bacel Maddah Book 2023 The Editor(s) (if applicable) and The Author(s), under exclusive license to S
描述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 sensorytechnologies, 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
出版日期Book 2023
關(guān)鍵詞retail analytics; shelf space optimization; retail store layout; in-store traffic; promotional displays;
版次1
doihttps://doi.org/10.1007/978-3-031-27058-1
isbn_softcover978-3-031-27060-4
isbn_ebook978-3-031-27058-1Series ISSN 0884-8289 Series E-ISSN 2214-7934
issn_series 0884-8289
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Book 2023tomer 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-spa
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A Solver-Free Heuristic for Store-Wide Shelf Space Allocation,ct categories to the store shelves. Based on the extant literature, in-store traffic is captured via a complex predictive model as a function of both allocation decisions and the store layout. We demonstrate that a solver-free heuristic yields promising solutions that can alternatively be obtained a
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Data-Driven Analytical Grocery Store Design, operate under high competition. A key element of traditional retailing is the store layout. This chapter investigates the influence of the store layout configuration on sales and in store traffic in a grocery store environment. A bi-objective optimization approach, combined with data mining techniq
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發(fā)表于 2025-3-23 06:44:03 | 只看該作者
Optimizing Stock-Keeping Unit Selection for Promotional Display Space at Grocery Retailers, yet affordable tool to boost profit. In this study, we examine a store manager’s choice of which stock-keeping units (SKUs) from a given category to assign to a promotional display space. While the academic literature and retail software solution providers offer a variety of optimization solutions
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