Retail Space Analytics

Bacel Maddah

ISBN 10: 3031270576 / ISBN 13: 9783031270574

Published by Springer International Publishing, Springer Nature Switzerland, 2023

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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 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.

Seller Inventory # 9783031270574

Bibliographic Details

• Title: Retail Space Analytics
• Publisher: Springer International Publishing, Springer Nature Switzerland
• Publication Date: 2023
• Language: English
• ISBN 10: 3031270576
• ISBN 13: 9783031270574
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 17D millimeters 241 millimeters width by 160 millimeters height by 17 millimeters depth
• Weight: 465 grams

About this title

Synopsis

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 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.

About the Author

Ahmed Ghoniem is an Associate Professor of Operations and Information Management at the Isenberg School of Management, University of Massachusetts, Amherst, USA. His research interests include Retail Analytics, Supply Chain Management, Manufacturing & Service Operations Management, and Routing & Scheduling.

Bacel Maddah is Professor and Chair, Department of Industrial Engineering and Management, Faculty of Engineering and Architecture, American University of Beirut, Lebanon. His research interests include Retail Operations Management, Supply Chain Management and Stochastic Processes.