Agricultural Supply Chain Management Research

The objective of this chapter is twofold. First, to study how a farmer should dynamically allocate farmland between two crops when the crops have rotation benefits across growing seasons, i.e., when it is more profitable to grow a crop on rotated farmland (where the other crop was grown) than on non-rotated farmland (where the same crop was grown). Second, to develop a practically implementable heuristic allocation policy and examine its performance in comparison with other heuristic policies commonly suggested in the literature. While the chapter is based on our companion paper (Boyabatlı et al (Management Sci 65(5):2060–2076, 2019)), we characterize the optimal dynamic allocation policy in a more general setting where the rotation benefits carry through for two growing seasons. To propose a heuristic allocation policy we focus on a special case of our model where the rotation benefits carry through for one growing season, as in our companion paper. We propose a one-period lookahead policy, which we can characterize in closed form based on the optimal policy structure and examine its performance in a numerical study with models calibrated to data obtained from United States Department of Agriculture and extant resources. We show that our proposed one-period lookahead policy outperforms all other heuristic policies and provides a near-optimal performance.

In this study, we examine the relationship between crop yield and the purchasing cost of fruit and the selling price of agricultural good. We coin this relationship as “yield-dependent” cost and price. We use this relationship in determining an agricultural producer’s production planning decisions.

Our work is motivated by the applications in the olive oil industry, however, the yield-dependent cost structure can also be observed in other industries such as citrus and wine grapes. Production of olive oil is a particularly challenging business as olives grow every other year making it a riskier investment. Olive oil producers lease farm space from other growers. When the yield of olives is low because of weather and/or diseases, the firm can buy additional olives from other farmers at a cost that varies with the yield. In the same scenario, the sale price of olive oil also increases because of the limited supply. When the yield is high, the company uses some of its olives for olive oil production and the rest of the olives are sold to other oil producers. Upon deriving the olive oil, the company sells its olive oil under demand uncertainty. The paper makes several contributions. It first shows that the objective function is concave in the amount of farm space leased, leading to a unique optimal solution. Next, it determines how the total production of olive oil changes with the yield. The study proves that the optimal amount of leased farm space decreases under the presence of the flexibility pertaining to buying additional olives. Departing from earlier findings, this study shows that higher degrees of yield variance do not necessarily increase the optimal amount of leased farm space in the presence of a secondary purchasing option of olives.

Surface water, supplied through a rudimentary canal system, is the principal source of irrigation for many farming communities in the developing world. Due to the physical locations of the farms with respect to the source of water, some farmers have privileged access and get to make the primary decision on how much water to use for themselves and how much to leave for the (secondary) farmers who are further away from the source. This inequity in access can lead to a significant reduction in the productivity of the farming community as a whole, as the primary farmers tend to use more water than the socially optimal amount. To combat this inefficiency, we develop easy-to-implement, decentralized mechanisms that are rational for the farmers and enable the farming community to achieve a socially optimal utilization of water.

In this chapter we first introduce the commercial seed business in the continental USA. Subsequently, we discuss the problem formulation and solution for a firm that offers a portfolio of hybrid seed corn in the market and seeks to optimize the acreage for each hybrid. We also discuss implementation of the solution developed at the firm. As such, this chapter highlights contextual factors that make the production planning problems in the agribusiness unique and in need for customized solutions.

This chapter provides insights on the optimal procurement decisions of a commodity processing firm that sources a primary input from a quantity flexibility contract (which is characterized by a unit reservation price and a unit exercise price), to produce two outputs in fixed proportions. The firm faces uncertainties in input spot price and output demands. Our objective is twofold. First, in a single-contract setting, we investigate the role of demand correlation in the presence of fixed proportions technology and show that the firm benefits from a higher demand correlation. Second, we investigate the firm’s optimal contract selection strategy between the two available quantity flexibility contracts. Focusing on deterministic output demands, we characterize a contract index in closed form that determines the optimal contract choice. We find that a higher expected spot price always increases the reliance on the contract with the lower exercise price. However, a higher spot price variability does the same only when the expected spot price is low and the difference between the exercise prices of two contracts is sufficiently high. Otherwise, a higher spot price variability increases the reliance on the contract with the lower reservation price.

We examine the role of the yield-dependent trading cost structure on the optimal decisions regarding the selling price and production quantity for an agricultural firm that operates under supply uncertainty. The firm leases farm space, but its realized crop yield fluctuates due to weather conditions, diseases, etc. After harvest, the firm has three options: convert its crop supply to the final product, purchase additional supplies from other growers, and sell some (or all) of its crop supply in the open market without converting to the finished product. We examine the problem both from a risk-neutral and from a risk-averse perspective.

The chapter makes three sets of contributions: (1) the use of a static cost exaggerates the initial investment in the farm space and the expected profit significantly, and the actual value gained from a secondary purchase option is lower under the yield-dependent cost structure, (2) a sufficiently risk-averse firm can benefit from the presence of a fruit futures market when it does not purchase fruit futures under static costs. Thus, fruit futures can add value in the presence of yield-dependent trading costs, and (3) contrary to earlier findings, the firm does not always commit to a lower initial quantity (leased farm space) under risk aversion and it might lease a larger farm space under risk aversion.

This chapter examines the capacity investment decisions of an agricultural processing firm that produces a commodity output and a byproduct using a commodity input. We model the firm’s problem as a finite-horizon stochastic dynamic program where the firm makes one-time input processing capacity and output storage capacity investment decisions—in addition to periodic processing and inventory decisions—when facing uncertainty in both input and output spot prices as well as output yield. We characterize the optimal capacity investment portfolio in closed form. Using a model calibration based on the palm industry, we compare the performance of the optimal investment policy against capacity investment heuristics that are commonly used in practice and/or academic literature. We find that if the yield uncertainty is ignored in capacity planning, then basing capacity investment decisions on the average yield is preferable to basing them (as often occurs in practice) on the maximum yield possible. We also find that although byproduct revenue constitutes a small portion of total revenues, ignoring it during capacity planning significantly reduces the firm’s profitability.

This study examines the use of advance selling in the wine industry as a form of operational flexibility to mitigate quality rating risk. The process of making fine wine begins after the harvesting season. During this time, grapes are sorted, pressed into juice, and are left to be fermented in barrels for up to 2 years. After 6 to 8 months of barrel aging, wine experts are invited to taste the wine, and a barrel score out of 100 is assigned. This barrel score acts as an indicator of the potential quality of the wine. At this time, based on the barrel score, the winemaker must decide on two key decisions: (1) the amount of wine to be allocated for sales as futures and (2) the price of wine futures. After one more year of aging, the wine is bottled and is sent to the same set of reviewers to receive a final bottle score, which in turns influences the market price for retail. We present a prescriptive analytical model that incorporates both the uncertain bottle score assigned to the wine and the uncertain consumer valuation of wine futures. Through the analysis of the analytical model, we illustrate the effect of changing the barrel score, the winemaker’s and consumers’ risk preferences, and the degree of consumer heterogeneity, on the winemaker’s optimal decisions and profitability. In addition to the analytical model, the study presents a comprehensive numerical study to further highlights effects of barrel scores on the winemaker’s decisions. The findings from the numerical study illustrate the effectiveness of the analytical model and the potential financial impact of wine futures as tool to help winemaker mitigate quality rating risk.

This chapter features a wine distributor’s budget allocation decision between bottled wine and wine futures under weather and market uncertainty. Every May, a distributor determines its investment amount in wine futures of the recent vintage and in bottled wines of the previous vintage. In September, after observing the weather and market conditions during the growing season of the upcoming vintage, the distributor has the flexibility to adjust its initial investments. In May of the following year, the distributor finally collects revenues from these investments.

This chapter summarizes three contributions. First, empirical analysis shows that wine futures exhibit greater price volatility than the bottled wines. Second, a mathematical model, built based on the empirical insights, suggests that a wine distributor should always carry some wine futures in its portfolio. Third, financial demonstration shows that a risk-neutral distributor can improve its profits by 21% and this benefit increases in risk aversion.

We examine the impact of information provision policies on farmer welfare in developing countries where farmers lack relevant and timely information for making informed decisions regarding which crop to grow and which market to sell in. Based on our equilibrium analysis, we find the following results. When market information is offered free of charge, we show that (a) providing information is always beneficial to farmers at the individual level and (b) providing information to all farmers may not be welfare maximizing at the aggregate level. To maximize farmer welfare, it is optimal to provide information to a targeted group of farmers who are located far away from either markets. However, to overcome perceived unfairness among farmers, we show that the government should provide information to all farmers at a nominal fee so that the farmers will adopt the intended optimal provision policy willingly.

In developing countries, farmers lack information to make informed production, manufacturing/selling decisions in order to improve their earnings. To alleviate poverty, various non-governmental organizations (NGOs) and for-profit companies have developed different ways to distribute agricultural information about market price, crop advisory, and farming technique to farmers. In this chapter, we first evaluate the economic value of private and public information and then explore the government’s optimal information provision policy to enhance farmer’s welfare. Specifically, we examine the following two questions: will public agricultural market information create economic value for farmers? and what is the optimal way to disseminate the public information to help farmers? By examining the equilibrium outcomes associated with a Cournot competition game, we show that private signals do create economic value for farmers. However, this value deteriorates as the public signal becomes available (or more precise). To enhance farmers’ social welfare, it is optimal for the government to limit the number of farmers who can access to public information.

In developing economies, smallholders operate their farms by applying their own specialized knowledge and exerting costly efforts. To raise overall productivity, NGOs and governments are advocating various knowledge sharing and learning platforms for farmers to exchange a variety of farming techniques. Putting altruism aside, we examine the overall economic implications for heterogeneous farmers to share their private knowledge voluntarily with others under (implicit) competition. By analyzing a multi-person sequential game, we find that farmers with high knowledge are reluctant to share knowledge, and consequently the voluntary shared level is always lower than or equal to the “efficient” shared level that maximizes farmer welfare under coordination. This finding is motivational in developing a reward mechanism to entice farmers to elevate their knowledge shared level in a decentralized system so as to maximize farmer welfare. Upon reviewing different mechanisms, we propose a quota-based reward mechanism that can entice farmers to share knowledge voluntarily up to the efficient shared level.

Using field data, our model shows that interventions aimed at improving average yield, creating a support-price for agricultural artemisinin, and carefully managing the supply of semi-synthetic artemisinin help improve the supply of artemisinin, reducing the price fluctuations in the malaria medicine.

Governments in many developing countries often use minimum support price (MSP) as a mechanism to (i) protect farmers from fall in crop market prices and (ii) improve availability of different essential crops to consumers. Among different MSP schemes, we focus on credit-based MSPs under which a government will not take any possession of a crop; instead, it will credit farmers should the prevailing price drop below the pre-specified MSP. We examine the effectiveness of MSP in achieving the aforementioned goals by considering a market that consists of two types of farmers (with heterogeneous production costs): myopic farmers (who make their crop selection and production decisions based on recently observed market prices) and strategic farmers (who make their decisions by taking all other farmers’ decisions into consideration). By examining the strategic interactions among these farmers for the case when there are two (complementary or substitutable) crops for each farmer to select to grow, we obtain the following results. First, the total production quantity of a crop is increasing in its MSP. Second, by setting the MSP of a crop low, each individual farmer’s earning from growing that crop can be lower than the case when no MSP is offered. Third, relative to the case without MSPs, it is possible for a government to choose the MSPs carefully so as to ensure Pareto improvement of the profits of all farmers. Fourth, farmers can attain a higher surplus when government offers MSPs for complementary instead of substitutable crops.

To alleviate farmer poverty in developing economies, two common farmer subsidy schemes are either input-based that intends to reduce farmers’ input purchasing costs or output-based that aims to lower farmers’ output processing costs. By analyzing a stylized model that captures yield heterogeneity across farmers who engage in quantity competition, we find that both schemes can improve farmers’ income. However, these two schemes generate different effects. First, the input-based subsidy scheme narrows the income gap between farmers, but the output-based scheme widens this gap. Second, the output-based subsidy scheme outperforms the input-based subsidy scheme in terms of total farmer income and farmer productivity. Overall, we find that low-yield farmers prefer input-based subsidies, while high-yield farmers prefer output-based subsidies. These results continue to hold even when the farmer’s yield rate is uncertain.