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Author: Joonkyum Lee
Publisher:
ISBN:
Category :
Languages : en
Pages : 43
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Book Description
We demonstrate the value of utility-based choice models to estimate demand and plan inventory for new and used textbooks in the presence of consumer choice and stockout-based substitution at a university textbook retailer. Demand information is censored, the exact time of stockout is not observed, and the short selling season often does not allow for replenishment. Using data for 26,749 book titles from 2007 to 2011 and a simulation experiment calibrated on real data, we show that an attribute-based choice model generates accurate demand estimates (mean absolute percentage error less than 1%) even when nearly 90% of the textbooks in the fit sample experience stockout. This performance is driven by the heterogeneity of product attributes and is robust to the occurrence of product returns. We implement this model at the bookstore in a controlled field experiment and obtain over 10% increase in profit. The results show that accounting for asymmetric and stockout-based substitution in demand estimation and inventory planning enables us to make systematic corrections in inventory mix and inventory level compared to the existing process.
Author: Joonkyum Lee
Publisher:
ISBN:
Category :
Languages : en
Pages : 43
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Book Description
We demonstrate the value of utility-based choice models to estimate demand and plan inventory for new and used textbooks in the presence of consumer choice and stockout-based substitution at a university textbook retailer. Demand information is censored, the exact time of stockout is not observed, and the short selling season often does not allow for replenishment. Using data for 26,749 book titles from 2007 to 2011 and a simulation experiment calibrated on real data, we show that an attribute-based choice model generates accurate demand estimates (mean absolute percentage error less than 1%) even when nearly 90% of the textbooks in the fit sample experience stockout. This performance is driven by the heterogeneity of product attributes and is robust to the occurrence of product returns. We implement this model at the bookstore in a controlled field experiment and obtain over 10% increase in profit. The results show that accounting for asymmetric and stockout-based substitution in demand estimation and inventory planning enables us to make systematic corrections in inventory mix and inventory level compared to the existing process.
Author: Jingwei Zhang
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
We study the joint assortment and inventory planning problem with stockout-based substitution. In this problem, we pick the number of units to stock for the products at the beginning of the selling horizon. Each arriving customer makes a choice among the set of products with remaining on-hand inventories. Our goal is to pick the stocking quantities to maximize the total expected revenue from the sales net of the stocking cost. Using a fluid approximation for the problem, we give solutions with performance guarantees that significantly improve earlier results. Letting $T$ be the number of time periods in the selling horizon and $n$ be the number of products, when customers choose under a general choice model, we show that we can round the solution to the fluid approximation to obtain stocking quantities with an optimality gap of $O(n + sqrt{nT})$, improving earlier optimality gaps by a logarithmic factor. More importantly, when customers choose under the multinomial logit model, we develop a rounding scheme that uses the solution to the fluid approximation to generate stocking quantities with an optimality gap of $O( log T sqrt{T log T})$. The optimality gap that we give under the multinomial logit model is the first one that does not depend on the number of products. Such an optimality gap has important implications in the many-products regime. Earlier results cannot guarantee that the stocking quantities generated by the fluid approximation perform well when both the demand volume and number of products are large, which is a regime becoming more relevant for online retail applications with large product variety. In contrast, we can guarantee that the stocking quantities generated by our rounding scheme perform well when both the demand volume and number of products are large.
Author: Martin K. Starr
Publisher: Taylor & Francis
ISBN: 1317419243
Category : Business & Economics
Languages : en
Pages : 712
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Book Description
This remarkable volume highlights the importance of Production and Operations Management (POM) as a field of study and research contributing to substantial business and social growth. The editors emphasize how POM works with a range of systems—agriculture, disaster management, e-commerce, healthcare, hospitality, military systems, not-for-profit, retail, sports, sustainability, telecommunications, and transport—and how it contributes to the growth of each. Martin K. Starr and Sushil K. Gupta gather an international team of experts to provide researchers and students with a panoramic vision of the field. Divided into eight parts, the book presents the history of POM, and establishes the foundation upon which POM has been built while also revisiting and revitalizing topics that have long been essential. It examines the significance of processes and projects to the fundamental growth of the POM field. Critical emerging themes and new research are examined with open minds and this is followed by opportunities to interface with other business functions. Finally, the next era is discussed in ways that combine practical skill with philosophy in its analysis of POM, including traditional and nontraditional applications, before concluding with the editors’ thoughts on the future of the discipline. Students of POM will find this a comprehensive, definitive resource on the state of the discipline and its future directions.
Author: Jack Muckstadt
Publisher: Springer Nature
ISBN: 3031661125
Category :
Languages : en
Pages : 277
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Book Description
Author: Santiago Gallino
Publisher: Springer Nature
ISBN: 3030201198
Category : Business & Economics
Languages : en
Pages : 353
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Book Description
The world of retailing has changed dramatically in the past decade. Sales originating at online channels have been steadily increasing, and even for sales transacted at brick-and-mortar channels, a much larger fraction of sales is affected by online channels in different touch points during the customer journey. Shopper behavior and expectations have been evolving along with the growth of digital channels, challenging retailers to redesign their fulfillment and execution processes, to better serve their customers. This edited book examines the challenges and opportunities arising from the shift towards omni- channel retail. We examine these issues through the lenses of operations management, emphasizing the supply chain transformations associated with fulfilling an omni-channel demand. The book is divided into three parts. In the first part, “Omni-channel business models”, we present four studies that explore how retailers are adjusting their fundamental business models to the new omni-channel landscape. The second part, “Data-driven decisions in an omni-channel world”, includes five chapters that study the evolving data opportunities enabled by omni-channel retail and present specific examples of data-driven analyses. Finally, in the third part, “Case studies in Omni-channel retailing”, we include four studies that provide a deep dive into how specific industries, companies and markets are navigating the omni-channel world. Ultimately, this book introduces the reader to the fundamentals of operations in an omni-channel context and highlights the different innovative research ideas on the topic using a variety of methodologies.
Author: Dorothee Honhon
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
We present an efficient dynamic programming algorithm to determine the optimal assortment and inventory levels in a single-period problem with stockout-based substitution. In our model, total customer demand is random and comprises of a fixed proportion of customers of different types. Customer preferences are modeled through the definition of these types. Each customer type corresponds to a specific preference ordering amongst products. A customer purchases the highest ranked product according to his type (if any) that is available at the time of his visit to the store (stockout-based substitution). We solve the optimal assortment problem using a dynamic programming formulation. We establish structural properties of the value function of the dynamic program that, in particular, help characterize multiple local maxima. We use the properties of the optima to construct a method for efficiently solving the problem in pseudopolynomial time. Our algorithm also gives a heuristic for the general case, i.e., when the proportion of customers of each type is random. In numerical tests, this heuristic performs better and faster than previously known methods, especially when the average demand and the degree of substitutability amongst products are high.
Author: Alys Jiaxin Liang
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
We consider a deterministic (fluid) multi-period assortment and inventory planning problem under the Multinomial Logit (MNL) choice model with dynamic (stockout-based) substitution, customer returns with a general return time distribution, and a cumulative capacity (storage) constraint for all products. Specifically, there is a one-time inventory decision at the beginning of the selling horizon and a customer who makes a purchase in the current period is allowed to return the purchase at a future period. The returned item will be inspected and, if it passes the inspection, it will be restocked and becomes available again for sale in the next period. The objective of the firm is to identify the initial inventories of the products that maximize the total profit throughout the horizon. Due to the dynamics created by the dynamic substitution and customer returns, this is a technically challenging problem to solve. Unlike in the setting without returns where a product will no longer be available throughout the remaining periods after it stocks out, in the presence of returns, a product could again be available due to restocked returns and may even stock out again, and this cycle might continue for several times depending on the availability of other products. We focus on the fluid version of this problem and develop a linear program (LP)-based approach to exactly solve this problem. If the LP has a unique optimal solution, then this solution is also an optimal solution to our problem. If, however, the LP does not have a unique optimal solution, an arbitrary optimal solution of the LP may not be feasible for our problem. To deal with this scenario, we develop an algorithm using which, given any optimal LP solution, we can construct an alternative optimal LP solution that is also optimal for our problem. The algorithm uses both primal and dual LP solutions together with exploiting some key structural properties of the problem. We visualize our approach using illustrative examples.
Author: Narendra Agrawal
Publisher: Springer
ISBN: 1489975624
Category : Business & Economics
Languages : en
Pages : 454
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Book Description
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.
Author: Omar El Housni
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
We study a joint assortment and inventory optimization problem faced by an online retailer who needs to decide on both the assortment along with the inventories of a set of N substitutable products before the start of the selling season to maximize the expected profit. The problem raises both algorithmic and modeling challenges. One of the main challenges is to tractably model dynamic stock-out based substitution where a customer may substitute to the most preferred product that is available if their first choice is not offered or stocked-out. We first consider the joint assortment and inventory optimization problem for a Markov Chain choice model and present a near-optimal algorithm for the problem. Our results significantly improve over the results in Gallego and Kim (2020) where the regret can be linear in T (where T is the number of customers) in the worst case.We build upon their approach and give an algorithm with regret Õ( sqrt{NT}) with respect to an LP upper bound. Our algorithm achieves a good balance between expected revenue and inventory costs by identifying a subset of products that can pool demand from the universe of substitutable products without significantly cannibalizing the revenue in the presence of dynamic substitution behavior of customers. We also present a multi-step choice model that captures the complex choice process in an online retail setting characterized by a large universe of products and a heavy-tailed distribution of mean demands. Our model captures different steps of the choice process including search, formation of a consideration set and eventual purchase. We conduct computational experiments that show that our algorithm empirically outperforms previous approaches both on synthetic and realistic instances.
Author: Sabine Rättig
Publisher:
ISBN:
Category :
Languages : en
Pages : 128
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Book Description
