Problem definition: It is estimated that one third of the food produced worldwide is wasted. This has been recognized as a critical problem by the United Nations, the U.S. Environmental Protection Agency, the European Union, and industry groups because of its implications for the environment, conservation of resources, and global hunger. Academic/practical relevance: The problem of food waste represents a significant research opportunity for the Operations Management (OM) community because it is closely connected with OM topics and methodologies in supply chain technology and management, incentives and coordination, business model innovation, and behavioral operations. Research in food waste can lead to novel academic contributions and have meaningful impact on practice. Methodology: Using the academic literature, industry literature, and interviews with managers, this article describes the problem of food waste, identifies its root causes and implications, argues for the importance of research in this area in OM, and develops a research agenda for OM scholars to contribute to the theory and practice of food waste reduction. Results: The agenda is organized around five themes: 1) supply chain technology, 2) supply chain logistics, 3) incentives and coordination in the supply chain, 4) business model innovation, and 5) behavioral operations. Managerial implications: This article aims to stimulate research on food waste in our field.
P roduct expiration is an important problem in the consumer-packaged-goods industry eroding profits and generating substantial waste. We propose that shelf space selection can be an operational lever to control expiration of perishable inventory. To this end, we first explain the conditions under which shelf space impacts expiration then develop a method to determine the appropriate level of shelf space which incorporates this impact. We formulate a shelf space selection problem for a single product using an infinite horizon Markov chain model. For the special case where demand is constant across periods, we find closed-form expressions for the average net profit, order levels, and expiration levels as a function of the product's shelf space under different shelf rotation assumptions. We show that when inventory is not rotated, expiration increases quickly when shelf space exceeds the demand per period. In contrast, when inventory is rotated, the increase occurs when shelf space is larger than the product demand throughout its shelf life. Since computing the optimum shelf space is computationally-challenging for large shelf life values, we approximate the net profit function leveraging the constant demand analysis. Our approximation method is easy to implement and performs well with a median optimality gap of 0.41% across 160 scenarios. We compare our method with two alternative heuristics and find that it performs better. As a byproduct of this approximation, we develop several managerial insights for the shelf space decision at the tactical level. In addition, we extend our analysis to consider shelf space-dependent demand.
Problem definition: Our research is motivated by the product expiration problem in consumer packaged goods retailing, which creates substantial landfill waste and drains firm profits. We analyze shipment policies (i.e., the rules to determine the quantity and age composition of inventory to ship from a warehouse to a retail location) and their impact on profits and waste. Academic/practical relevance: The same firm often bears the cost of expiration at the warehouse and the retail store, which is why the problem necessitates a supply chain perspective. The ship oldest first (SOF) policy (commonly referred to as first in, first out) is advocated by industry experts to manage product shelf lives. Although its optimality in a single location is well established in the literature, it has not been studied in the context of a two-stage supply chain. Methodology: We conduct empirical analysis on a real-life data set to motivate the relevance of our problem. Then, we formulate an infinite horizon dynamic programming problem with stochastic demand for which we obtain analytical and numerical results. Results: The SOF policy is found to always minimize waste at the warehouse and total waste (warehouse and retail level combined) and under certain practically unlikely conditions, to maximize profits. However, in most practical applications, it is suboptimal, and the optimal policy is shown to have a complex structure. We analyze deterministic and myopic versions of our problem in order to generate insights on the trade-off between the issuing cost and the expiration cost. Then, we develop heuristic policies based on the myopic analysis of the problem, which are shown to perform well in terms of profits, waste, and product freshness; in our numerical analysis, the best such heuristic yields a median optimality gap of 9.5% versus 21% for SOF, pantry life of 69% versus 56% for SOF, and retail waste of 4% versus 10% for SOF. Managerial implications: The SOF policy is shown to generate high waste at the retail store, where waste is more likely to be disposed of at landfills as opposed to being donated; therefore, it may have an adverse impact on the environment. Our results also show that it is not effective at managing shelf lives in the supply chain, contrary to what practitioners argue, as evidenced by poor pantry life leading to excessive waste at the household level. Our analysis also questions the value of flow-through stocking systems to facilitate SOF as we show that firms can gain much more from improving their issuing policies.
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