A retail category management model integrating shelf space and inventory levels

A retail category management model that considers the interplay of optimal product assortment decisions, space allocation and inventory quantities is presented in this paper. Specifically, the proposed model maximizes the total net profit in terms of decision variables expressing product assortment, shelf space allocation and common review period. The model takes into consideration several constraints such as the available shelf space, backroom inventory space, retailer's financial resources, and estimates of rate of demand for products based on shelf space allocation and competing products. The review period can take any values greater than zero. Results of the proposed model were compared withthe results of the current industry practice for randomly generated product assortments of size six, ten and fourteen. The model also outperformed the literature benchmark. The paper demonstrates that the optimal common review period is flexible enough to accommodate the administrative restrictions of delivery schedules for products, without significantly deviating from the optimal solution

USES OF SCANNER INFORMATION FOR FOOD INDUSTRY EXECUTIVES

Agribusiness,

From supply chains to demand networks. Agents in retailing: the electrical bazaar

A paradigm shift is taking place in logistics. The focus is changing from operational effectiveness to adaptation. Supply Chains will develop into networks that will adapt to consumer demand in almost real time. Time to market, capacity of adaptation and enrichment of customer experience seem to be the key elements of this new paradigm. In this environment emerging technologies like RFID (Radio Frequency ID), Intelligent Products and the Internet, are triggering a reconsideration of methods, procedures and goals. We present a Multiagent System framework specialized in retail that addresses these changes with the use of rational agents and takes advantages of the new market opportunities. Like in an old bazaar, agents able to learn, cooperate, take advantage of gossip and distinguish between collaborators and competitors, have the ability to adapt, learn and react to a changing environment better than any other structure. Keywords: Supply Chains, Distributed Artificial Intelligence, Multiagent System.Postprint (published version

The Future of Retail Operations

Retailing consists of all the activities associated with the selling of goods to the final consumer. In this article, we review the research on retail operations published in Manufacturing & Service Operations Research (M&SOM) since 1999. We then discuss the current retail landscape and the new research directions it offers, in which M&SOM can play a prominent role

Competing for shelf space

This paper studies competition for shelf space in a multi-supplier retail point. We consider a retailer that seeks to allocate her shelf space to maximize her profit. Because products associated with larger profit margin are granted more shelf space, suppliers can offer the retailer financial incentives to obtain larger space allocations. We analyze the competitive dynamics arising from the scarcity of space, and show existence and uniqueness of equilibrium. We then demonstrate that the inefficiencies from decentralizing decision-making are limited to 6% with wholesale-price contracts, and that full coordination can be achieved with pay-to-stay fee contracts. We finally investigate how competition is distorted under the practice of category management.Game theory; Supply chain competition; Price of Anarchy; Pricing; Supply contracts;

Minimizing food waste in grocery store operations: literature review and research agenda

Research on grocery waste in food retailing has recently attracted particular interest. Investigations in this area are relevant to address the problems of wasted resources and ethical concerns, as well as economic aspects from the retailer’s perspective. Reasons for food waste in retail are already well-studied empirically, and based on this, proposals for reduction are discussed. However, comprehensive approaches for preventing food waste in store operations using analytics and modeling methods are scarce. No work has yet systematized related research in this domain. As a result, there is neither any up-to-date literature review nor any agenda for future research. We contribute with the first structured literature review of analytics and modeling methods dealing with food waste prevention in retail store operations. This work identifies cross-cutting store-related planning areas to mitigate food waste, namely (1) assortment and shelf space planning, (2) replenishment policies, and (3) dynamic pricing policies. We introduce a common classification scheme of literature with regard to the depth of food waste integration and the characteristics of these planning problems. This builds our foundation to review analytics and modeling approaches. Current literature considers food waste mainly as a side effect in costing and often ignores product age dependent demand by customers. Furthermore, approaches are not integrated across planning areas. Future lines of research point to the most promising open questions in this field

Demand Estimation at Manufacturer-Retailer Duo: A Macro-Micro Approach

This dissertation is divided into two phases. The main objective of this phase is to use Bayesian MCMC technique, to attain (1) estimates, (2) predictions and (3) posterior probability of sales greater than certain amount for sampled regions and any random region selected from the population or sample. These regions are served by a single product manufacturer who is considered to be similar to newsvendor. The optimal estimates, predictions and posterior probabilities are obtained in presence of advertising expenditure set by the manufacturer, past historical sales data that contains both censored and exact observations and finally stochastic regional effects that cannot be quantified but are believed to strongly influence future demand. Knowledge of these optimal values is useful in eliminating stock-out and excess inventory holding situations while increasing the profitability across the entire supply chain. Subsequently, the second phase, examines the impact of Cournot and Stackelberg games in a supply-chain on shelf space allocation and pricing decisions. In particular, we consider two scenarios: (1) two manufacturers competing for shelf space allocation at a single retailer, and (2) two manufacturers competing for shelf space allocation at two competing retailers, whose pricing decisions influence their demand which in turn influences their shelf-space allocation. We obtain the optimal pricing and shelf-space allocation in these two scenarios by optimizing the profit functions for each of the players in the game. Our numerical results indicate that (1) Cournot games to be the most profitable along the whole supply chain whereas Stackelberg games and mixed games turn out to be least profitable, and (2) higher the shelf space elasticity, lower the wholesale price of the product; conversely, lower the retail price of the product, greater the shelf space allocated for that product

A Roadmap to Reduce U.S. Food Waste by 20 Percent

The magnitude of the food waste problem is difficult to comprehend. The U.S. spends $218 billion a year -- 1.3% of GDP -- growing, processing, transporting, and disposing of food that is never eaten. The causes of food waste are diverse, ranging from crops that never get harvested, to food left on overfilled plates, to near-expired milk and stale bread. ReFED is a coalition of over 30 business, nonprofit, foundation, and government leaders committed to building a different future, where food waste prevention, recovery, and recycling are recognized as an untapped opportunity to create jobs, alleviate hunger, and protect the environment -- all while stimulating a new multi-billion dollar market opportunity. ReFED developed A Roadmap to Reduce U.S. Food Waste as a data-driven guide to collectively take action to reduce food waste at scale nationwide.This Roadmap report is a guide and a call to action for us to work together to solve this problem. Businesses can save money for themselves and their customers. Policymakers can unleash a new wave of local job creation. Foundations can take a major step in addressing environmental issues and hunger. And innovators across all sectors can launch new products, services, and business models. There will be no losers, only winners, as food finds its way to its highest and best use

Item-level RFID for enhancement of customer shopping experience in apparel retail

In the customer-oriented apparel retail industry, providing satisfactory shopping experience for customers is a vital differentiator. However, traditional stores generally cannot fully satisfy customer needs because of difficulties in locating target products, out-of-stocks, a lack of professional assistance for product selection, and long waiting for payments. Therefore, this paper proposes an item-level RFID-enabled retail store management system for relatively high-end apparel products to provide customers with more leisure, interaction for product information, and automatic apparel collocation to promote sales during shopping. In this system, RFID hardware devices are installed to capture customer shopping behaviour and preferences, which would be especially useful for business decision-making and proactive individual marketing to enhance retail business. Intelligent fuzzy screening algorithms are then developed to promote apparel collocation based on the customer preferences, the design features of products, and the sales history accumulated in the database. It is expected that the proposed system, when fully implemented, can help promote retail business by enriching customers with intelligent and personalized services, and thus enhance the overall shopping experience. © 2015 Elsevier B.V.postprin