Retail Supply Chain Management : Quantitative Models and Empirical Studies / / edited by Narendra Agrawal, Stephen A. Smith

• Pubblicazione: New York, NY : , : Springer US : , : Imprint : Springer, , 2015
• Edizione: 2nd ed. 2015.
• Descrizione fisica: 1 online resource (454 p.)
• Disciplina: 330; 519.6; 658.40301; 658.5
• Soggetto topico: Operations research; Decision making; Management science; Production management; Operations Research/Decision Theory; Operations Research, Management Science; Operations Management
• Persona (resp. second.): AgrawalNarendra; SmithStephen A
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Overview of Chapters -- Supply Chain Planning Processes for Two Major Retailers -- The Effects of Firm Size and Sales Growth Rate on Inventory Turnover Performance in the U.S. Retail Sector -- The Role of Execution in Managing Product Availability -- Analytics for Operational Visibility in the Retail Store: The Cases of Censored Demand and Inventory Record Inaccuracy -- An Overview of Industry Practice and Empirical Research in Retail Workforce Management -- Category Captainship Practices in the Retail Industry -- Assortment Planning: Review of Literature and Industry Practice -- Fast Fashion: Business Model Overview and Research Opportunities -- Managing Variety on the Retail Shelf: Using Household Scanner Panel Data to Rationalize Assortments -- Optimizing Retail Assortment for Diverse Customer Preferences -- Multi-Location Inventory Models for Retail Supply Chain Management -- Manufacturer-to-Retailer Versus Manufacturer-to-Consumer Rebates in a Supply Chain -- Clearance Pricing in Retail Chains -- Markdown Competition.
• Sommario/riassunto: This new edition focuses on three crucial areas of retail supply chain management: (1) empirical studies of retail supply chain practices, (2) assortment and inventory planning and (3) integrating price optimization into retail supply chain decisions. The book has been fully updated, expanding on the distinguishing features of the original, while offering three new chapters on recent topics which reflect areas of great interest and relevance to the academic and professional communities alike - inventory management in the presence of data inaccuracies, retail workforce management, and fast fashion retail strategies. The innovations, lessons for practice, and new technological solutions for managing retail supply chains are important not just in retailing, but offer crucial insights and strategies for the ultimate effective management of supply chains in other industries as well. The retail industry has emerged as a fascinating choice for researchers in the field of supply chain management. It presents a vast array of stimulating challenges that have long provided the context of much of the research in the area of operations research and inventory management. However, in recent years, advances in computing capabilities and information technologies, hyper-competition in the retail industry, emergence of multiple retail formats and distribution channels, an ever increasing trend towards a globally dispersed retail network, and a better understanding of the importance of collaboration in the extended supply chain have led to a surge in academic research on topics in retail supply chain management. Many supply chain innovations (e.g., vendor managed inventory) were first conceived and successfully validated in this industry, and have since been adopted in others. Conversely, many retailers have been quick to adopt cutting edge practices that first originated in other industries. Retail Supply Chain Management: Quantitative Models and Empirical Studies, 2nd Ed. is an attempt to summarize the state of the art in this research, as well as offer a perspective on what new applications may lie ahead.
• Titolo autorizzato: Retail Supply Chain Management
• ISBN: 1-4899-7562-4
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910298501703321
• Lo trovi qui: Univ. Federico II
• Serie: International Series in Operations Research & Management Science, . 0884-8289 ; ; 223