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

Dynamic pricing and inventory control of online retail of fresh agricultural products with forward purchase behavior

In this paper we formulate and analyze a novel model on a retailer’s inventory and pricing decisions for fresh agricultural products with consumers’ forward consuming behavior under online channel. We consider a dynamic stochastic setting, where every period consists of two stages, discounting pricing stage and regular sale stage. At the beginning of the period, the retailer decides how much new fresh agricultural products to order and sets discount price for leftover inventories from the previous period which will be disposed otherwise, and determines regular price for fresh products on the second stage, respectively. Since forward purchase consumers may buy the products during discount pricing stage, which may cannibalize future sales at regular price, the retailer needs to make a trade-off decision between regular price and discounting price. We bring forward a dynamic optimization model and use nonlinear programming method of Karush Kuhn Tucker condition to obtain the optimal dynamic strategy, which is comparatively analyzed to dominate the related static strategy. We also show that consumers forward buying behavior will negatively influence the retailer’s profit. When the price is set too low in regular or discounting sales, the profit will show an up-down trend if the inventory exceeds a certain threshold. Meanwhile, when fresh goods returns are allowed and resold in the secondary stage, the retailer’s profit will increase. We finally conduct numerical studies to further characterize the optimal policy, and to evaluate the loss of efficiency under static policies when compared to the optimal dynamic policy

Does Discounting Work in the Lodging Industry?

The central intent of this econometric case study analysis is to examine the relationship between discounting room rates and hotel financial performance. The study provides a theoretical framework that investigates the fundamentals of discounting and empirically assesses the efficacy of the discounting process in the lodging industry. The study adopts an error correction model to properly account for the dynamics of the industry. The results indicate that the variables may be modeled as an integrated process and which are linked in the long run and also possess a short-term relationship. The research findings suggest that discounting works both in the short term and the long term only if the discount rate exhibits serial correlation or nonstationary tendencies

The Value of Demand Information in Omni-Channel Grocery Retailing

As e-commerce reaches one of the last strongholds of traditional fulfillment, how can grocers leverage the omni-channel trend and stay competitive in today’s changing market landscape? To improve operating outcomes and address food waste concerns, this study investigates various scenarios in which the grocery retailer accepts online orders in advance. We examine the value of advance demand information through a Markov Decision Process-based model, in terms of changes to expected profits, outdating, freshness, and several inventory and service performance metrics. Our results indicate that when the demand lead time is longer than the replenishment lead time, close to 20% safety stock reduction on average can be achieved, leading to a 15% decrease in product deterioration and 26% less outdating. In some cases, we also find that it is possible to profitably offer discounted prices in exchange for the customer’s future demand information

Supply chain finance for ameliorating and deteriorating products: a systematic literature review

Ameliorating and deteriorating products, or, more generally, items that change value over time, present a high sensitiveness to the surrounding environment (e.g., temperature, humidity, and light intensity). For this reason, they should be properly stored along the supply chain to guarantee the desired quality to the consumers. Specifically, ameliorating items face an increase in value if there are stored for longer periods, which can lead to higher selling price. At the same time, the costumers’ demand is sensitive to the price (i.e., the higher the selling price the lower the final demand), sensitiveness that is related to the quality of the products (i.e., lower sensitiveness for high-quality products). On the contrary, deteriorating items lose quality and value over time which result in revenue losses due to lost sales or reduced selling price. Since these products need to be properly stored (i.e., usually in temperature- and humidity-controlled warehouses) the holding costs, which comprise also the energy costs, may be particularly relevant impacting on the economic, environmental, and social sustainability of the supply chain. Furthermore, due to the recent economic crisis, companies (especially, small and medium enterprises) face payment difficulties of customers and high volatility of resources prices. This increases the risk of insolvency and on the other hand the financing needs. In this context, supply chain finance emerged as a mean for efficiency by coordinating the financial flow and providing a set of financial schemes aiming at optimizing accounts payable and receivable along the supply chain. The aim of the present study is thus to investigate through a systematic literature review the two main themes presented (i.e., inventory management models for products that change value over time, and financial techniques and strategies to support companies in inventory management) to understand if any financial technique has been studied for supporting the management of this class of products and to verify the existing literature gap

Agent based mobile negotiation for personalized pricing of last minute theatre tickets

This is the post-print version of the final paper published in Expert Systems with Applications. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2012 Elsevier B.V.This paper proposes an agent based mobile negotiation framework for personalized pricing of last minutes theatre tickets whose values are dependent on the time remaining to the performance and the locations of potential customers. In particular, case based reasoning and fuzzy cognitive map techniques are adopted in the negotiation framework to identify the best initial offer zone and adopt multi criteria decision in the scoring function to evaluate offers. The proposed framework is tested via a computer simulation in which personalized pricing policy shows higher market performance than other policies therefore the validity of the proposed negotiation framework.The Ministry of Education, Science and Technology (Korea

Efficient inventory control for imperfect quality items

In this paper, we present a general EOQ model for items that are subject to inspection for imperfect quality. Each lot that is delivered to the sorting facility undertakes a 100 per cent screening and the percentage of defective items per lot reduces according to a learning curve. The generality of the model is viewed as important both from an academic and practitioner perspective. The mathematical formulation considers arbitrary functions of time that allow the decision maker to assess the consequences of a diverse range of strategies by employing a single inventory model. A rigorous methodology is utilised to show that the solution is a unique and global optimal and a general step-by-step solution procedure is presented for continuous intra-cycle periodic review applications. The value of the temperature history and flow time through the supply chain is also used to determine an efficient policy. Furthermore, coordination mechanisms that may affect the supplier and the retailer are explored to improve inventory control at both echelons. The paper provides illustrative examples that demonstrate the application of the theoretical model in different settings and lead to the generation of interesting managerial insights

A Nested Logit Model of Strategic Promotion

Retailers use sales "price promotions" for a number of potential reasons. There is relatively little research, however, on their strategic role among frequently consumed perishable products. Using a two-stage, nested logit model of retail equilibrium, we show that promotion will be most effective (ie. increase store-level sales) if products are highly differentiated, but stores are relatively similar. To test this hypothesis, we an oligopolistic model of promotion rivalry with category-level scanner data from the four largest supermarket retailers in a major U.S. metropolitan market. The results show that promotion has a greater impact on store share than product share, because the elasticity of substitution among stores is larger than the elasticity of substitution among products. Consequently, promotion has its greatest value in driving demand for differentiated products among stores that are similar. This finding supports the observed trend toward premium private label products being offered by supermarket retailers.Research Methods/ Statistical Methods,

A MULTI-ITEM INVENTORY MODEL WITH VARIOUS DEMAND FUNCTIONS CONSIDERING DETERIORATION AND PARTIAL BACKLOGGING

Inventory management is an important thing to be considered in order to run the activities of a company smoothly. By considering deterioration factor, partial backlogging policy and different type of demand functions, we develop a mathematical model for multi-item inventory system. In this paper, three inventory models with constant deterioration, partial backlogging, with various demand functions are developed.  We consider inventory-dependent demand, time-dependent demand and exponential demand function in each model.  In addition, we also consider the replenishment policies for those three items, viz. individual replenishment, joint replenishment and combination both individual and joint replenishments. Sensitivity analysis of the models is also performed, and we found that the ordering cost greatly affects the total inventory cost when comparing the available replenishment policies