Retail space analytics
Author(s)
Bibliographic Information
Retail space analytics
(International series in operations research & management science, v. 339)
Springer, c2023
Available at 2 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
Includes bibliographical references
Description and Table of Contents
Description
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.
Table of 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
by "Nielsen BookData"