Retail space analytics / Ahmed Ghoniem, Bacel Maddah, editors.

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Retail space analytics / Ahmed Ghoniem, Bacel Maddah, editors.

9783031270581 (electronic bk.)
3031270584 (electronic bk.)
3031270576
9783031270574

Cham : Springer, [2023]

©2023

English

1 online resource (xii, 181 pages) : illustrations.

10.1007/978-3-031-27058-1 doi

HF5429.15

381/.10285
658.4/03

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.

Includes bibliographical references.

Access limited to authorized users.

Description based on print version record.

International series in operations research & management science ; 339.

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