Yield Uncertainty Research Articles

Uncertainty in climate change impact studies for irrigated maize cropping systems in southern Spain

This study investigates the main drivers of uncertainties in simulated irrigated maize yield under historical conditions as well as scenarios of increased temperatures and altered irrigation water availability. Using APSIM, MONICA, and SIMPLACE crop models, we quantified the relative contributions of three irrigation water allocation strategies, three sowing dates, and three maize cultivars to the uncertainty in simulated yields. The water allocation strategies were derived from historical records of farmer’s allocation patterns in drip-irrigation scheme of the Genil-Cabra region, Spain (2014–2017). By considering combinations of allocation strategies, the adjusted R2 values (showing the degree of agreement between simulated and observed yields) increased by 29% compared to unrealistic assumptions of considering only near optimal or deficit irrigation scheduling. The factor decomposition analysis based on historic climate showed that irrigation strategies was the main driver of uncertainty in simulated yields (66%). However, under temperature increase scenarios, the contribution of crop model and cultivar choice to uncertainty in simulated yields were as important as irrigation strategy. This was partially due to different model structure in processes related to the temperature responses. Our study calls for including information on irrigation strategies conducted by farmers to reduce the uncertainty in simulated yields at field scale.

Retailer's make-or-buy decision for remanufactured products under in-house yield uncertainty

Remanufacturing is a sustainable practice, as it can save resources and alleviate environmental pollution. However, the production process can be subject to yield uncertainty if the manufacturer has limited remanufacturing capability. This study considers a retailer that sells both new and remanufactured products simultaneously. The retailer can either produce the remanufactured product in-house under yield uncertainty (Scenario I), or remove this uncertainty by relying on a third-party remanufacturer (Scenario O). We investigate the retailer's make-or-buy decision under in-store competition (between new and remanufactured products) and find that, remarkably, consumers’ high valuation of the remanufactured product induces the retailer to order an increased quantity of new products in both Scenarios O and I. In addition, we find that the retailer can obtain a higher profit in Scenario O because the new product supplier will strategically lower the wholesale price owing to the intensified supply competition, which could also benefit the new product supplier and, hence, achieve a win–win situation.

Integrated spatially explicit landscape and cellulosic biofuel supply chain optimization under biomass yield uncertainty

This paper proposes an integrated stochastic mixed-integer linear programming model for biofuel supply chain and landscape design optimization that considers the interactions between uncertainty in biomass yield, spatially explicit feedstock availability, supply chain configuration, operational decisions, and the system's environmental impact. By modeling crop establishment and fertilization as strategic decisions made before the realization of uncertainty, model solutions identify integrated supply chain configurations better suited to mitigate uncertain biomass yields. Importantly, the paper presents an approach for gathering and processing the large amount of necessary real-world data, including an accurate accounting of soil carbon sequestration. A case study located in Michigan, USA, demonstrating the capabilities of the integrated model with realistic data, is presented. Results at a variety of harvesting site resolutions and number of uncertainty scenarios, show that large-scale instances, at fine spatial resolutions, identify attractive environmental solutions and that solving the stochastic problem leads to an economic benefit.

Optimum operational schedule and accounts receivable financing in a production supply chain considering hierarchical industrial status and uncertain yield

Consider a production supply chain system, in which a small- and medium-sized enterprise (SME) supplies products to and has accounts receivable (AR) from a core enterprise (CE), and the SME collateralizes the AR to a commercial bank (CB) for a loan to make production. We address and model hierarchical industrial status of the SME, CE, and CB and the uncertainties in SME's production yield and market demand. The production decisions on the order quantity of the CE and the production quantity of the SME are determined through a Stackelberg game, and the AR loan contract that specifies the loan quota and interest rate is determined by the CB by means of optimizing its expected profit while satisfying the requirements from the SME. We derive the analytical optimal conditions for these decisions and demonstrate the effects of the market value of AR, upper bound of loan interest rate, production yield uncertainty, and market demand uncertainty on the operational decisions and the AR loan contract through sensitivity analysis. The analytical approach and results and numerical findings provide decision tools and advice for production schedules and loan application of the SME as well as suggestions for intervention of macro regulations.

Production and green technology investment strategy for contract-farming supply chain under yield insurance

We consider a contract-farming supply chain with multiple farmers and an agro-dealer, where farmers are risk-averse and they invest in green technologies. To hedge the risk of yield uncertainty, farmers can purchase agricultural yield insurance. We build a Stackelberg game model to investigate the optimal decisions of farmers and the agro-dealer. The results show that agricultural competition, yield uncertainty, and farmers’ risk aversion have negative impacts on the farm size and the agrochemical reduction technology input, while the yield insurance has positive impacts. We also show that, for farmers with low initial agrochemical input, yield insurance can reduce the agrochemical inputs per acre, and the total agrochemical inputs despite that the farm size increases. Therefore, yield insurance can reduce agricultural pollution emissions. Despite the result of higher social welfare, more agricultural competition generates higher agricultural pollution emissions because farmers would have no incentive to invest more in green technologies. Furthermore, yield insurance enhances the social welfare if the environmental damage of agrochemicals is low. However, when the environmental damage of agrochemicals is high, the social welfare decreases under the yield insurance.

The Interaction between Dual Sourcing and Blockchain Adoption under Yield Uncertainty

An unprecedented global crisis caused by the COVID-19 pandemic has revealed multiple challenges for operation management. One of them is yield uncertainty. In this paper, we examine the effect of the dual sourcing strategy and blockchain adoption on the performance of supply chain members in the presence of yield uncertainty. We develop a stylish model in which a decentralized supply chain consists of a downstream firm and the supplier and a centralized supply chain are competing. The downstream firm faced with yield uncertainty decides whether to procure from the competitor and decided whether to adopt blockchain to enhance the information quality about yield rate. Our results show that the dual sourcing strategy is a dominant strategy and the decision-maker benefits from the blockchain adoption if the volatility level of the yield rate is low.

Planning rice cultivation in a large plot agricultural system

This research aimed to study the approach of the community toward the decision to grow rice and economic crops, including appropriate resource allocation for use on a farm under a large plot agricultural system. The study areas were in Phan district, Chiang Rai province, Thailand, and the data were collected from a sampling of 400 field agriculturalists. The method used was to develop a mathematical model for growing crops with multi-objectives and in multi-periods, together with an agriculturist representative and experts in multiple-criteria decision-making (MCDM). This was to prioritize the importance of alternative crops and find the appropriate allocation of the resources to achieve the targeted goal. The results showed that agriculturists prioritized most toward the criteria for growing Japanese rice with a weight of 0.179 Kg., followed by transplanted rice, transplanted glutinous rice, garlic, sown paddy rice, and sown glutinous paddy rice, respectively. The study’s results also showed that the price fluctuation of the crop products resulted in more use of land and labor in order to increase the production to compensate for the low price, and this also resulted in the higher opportunity cost of growing transplanted rice. Therefore, growing transplanted rice during in season planting was considered the most effective way, while during the off season, either garlic or Japanese rice could be grown. A collective pattern for planning for using resources together in large plot agricultural areas, together with a clear marketing target would bring about effective use of the resources and reduce the risk in revenue from the fluctuation in prices and uncertainty of yields from drought. Moreover, technology development to solve the problem of the lack of labor would be deemed an important approach toward the enhancement of the competitiveness of agriculturists in the future as well.

Green Credit and Sharing Contract-Driven Financing Strategies in a Low-Carbon Supply Chain with Yield Uncertainty

Green Credit and Sharing Contract-Driven Financing Strategies in a Low-Carbon Supply Chain with Yield Uncertainty

Coordinating a Three‐Level Fresh Agricultural Product Supply Chain considering Option Contract under Spot Price Uncertainty

We consider a three‐level fresh agricultural product supply chain consisting of a producer, a supplier, and a retailer, where the producer plants the initial fresh agricultural products with yield uncertainty, the supplier is the leader of the supply chain and the designer of the contracts, and the retailer sells processed products with random demand and spot price. This paper discusses coordination mechanism of wholesale price contracts or option contracts between the supplier and the retailer and wholesale price contracts between the supplier and the producer. Based on this, we not only explore the conditions for supply chain full coordination and Pareto improvement but also analyze the effect of the retailer’s spot market volatility by comparing two scenarios of the retailer with or without a random spot market. Results show that the wholesale price contract cannot coordinate the supply chain regardless of whether the retailer has a random spot market or not. The supply chain can be simultaneously fully coordinated and achieve Pareto improvement by setting reasonable option contract parameters, but the conditions for coordination are rigorous. When the expected value of reduction from the retailer’s spot market in unit shortage loss cost is greater, the total profit of supply chain will increase. Numerical analysis shows that the option exercise price must be set higher when the retailer has a spot market to achieve Pareto improvement. The loss rate in distribution process and other volatility risks will also affect the coordination of the agricultural supply chain.

Comparison of Conservation Incentives under Long-Run Yield Uncertainty and Farmer Risk Aversion

Comparison of Conservation Incentives under Long-Run Yield Uncertainty and Farmer Risk Aversion

Decision Model of Contract‐Farming Supply Chain Considering Producer’s Fairness Concerns under Random Yield

Supply chain management is critical for addressing uncertainties caused by random demand and production yield. In this study, a random yield supply chain, in which the production process of fresh agricultural products is easily affected by factors, such as weather, soil, or plant diseases and insect pests, was considered. Therefore, the actual output is typically less than the planned output. A model in which the producer faces yield uncertainty was considered, and the influence of the producer’s fairness concerns on the planned output of the contract‐farming supply chain was considered. Methods to motivate the producer to increase planned output through reasonable contracts were investigated. The results revealed that the producer’s fairness concern considerably influences the optimal expected profit. In the case of the random output, the planned output and maximum expected profits reduce when the farmer exhibits fairness concerns. As the degree of the producer’s fairness concern increases, the planned output and expected profit gradually decrease The cost‐sharing contract can effectively encourage the producer to increase his planned output and expected utility. Finally, the results were verified numerically.

A decision model for stochastic optimization of seasonal irrigation-water allocation

Optimal water allocation on a seasonal basis is generally a decision taken with uncertainty regarding seasonal crop needs (unknown yield, precipitation and other environmental factors). Decision criteria, such as “irrigating for the good years of production” and "applying a little extra water just in case it is needed by the plant", are consistent with the rational behaviour of stochastic profit maximization. The motivation behind an increase in water allocation (acquiring water rights or reserving water for certain crops) is that of self-protection: it is better to maintain an extra allocation of water than to face potential yield losses due to water constraints on production in those years when potential yields exceed average levels. The stochastic optimization model presented herein is applied to maize in Spain showing that in current economic and technical conditions, the optimal stochastic water allocation under yield uncertainty is 10% higher than the irrigation dose required under certainty (historical average yield), which leads to an 8% higher expected profit than that obtained for an average-yield water application.

Optimal Green Operation and Information Leakage Decisions under Government Subsidy and Supply Uncertainty

This study investigated optimal green operation and information leakage decisions in a green supply chain system. The system consists of one supplier, one leader retailer 1, one follower retailer 2, and the government. In this system, the government subsidizes each retailer based on the selling price of the product. The supplier is subject to a yield uncertainty process. The suppler decides whether to leak leader retailer 1′s order quantity to follower retailer 2 or not. In this study, we first built a Stackelberg game to address the equilibrium green operation decisions, when the supplier has and has not information leakage behavior, respectively. Subsequently, we identify the supplier’s information leakage equilibrium and how such behavior affects retailers’ ex ante profits, consumer surplus, and social welfare through a numerical study. Interestingly, we obtained the following results: (1) Supplier leaks are the unique equilibrium of the supplier. The product’s green degree and wholesale price at supplier’s equilibrium are higher under information leakage than under no information leakage. (2) The supplier’s information leakage behavior is good for leader retailer 1 and bad for follower retailer 2. (3) Information leakage behavior increases both consumer surplus and social welfare under certain conditions. (4) In general, key system parameters (e.g., the subsidy rate, supply uncertainty, supply correlation, and forecast accuracies) positively correlate with consumer surplus and social welfare in the same direction, while they affect retailer 1′s and retailer 2′s ex ante profit in the opposite direction. These findings provide useful insights for businesses to manage demand forecast information and make decisions on the green level of the product in green supply chain management.

Input Quantity Decision and Coordination Mechanism with Two Production Chances and Yield Uncertainty

Conducting a second production run can improve the company’s capability of meeting the market demand. Few works examine optimal input quantity decisions under the mode with two production chances considering demand and yield uncertainty. We propose a vendor-managed inventory (VMI) supply chain with one supplier and one retailer. The supplier has two production chances and faces yield uncertainty in each production run. It is necessary for the supplier to make trade-offs between the cost and benefit of the second production run, then decide whether to conduct the second production run. We investigate the supplier’s optimal input quantity decision in each production run and obtain the supply chain members’ expected profits. As a comparison, the mode with one production chance is also developed. We find that two production chances can help improve the performance of the supply chain under yield uncertainty. A revenue-sharing contract is introduced to coordinate the supply chain with two production chances, and efficient profit allocation is achieved through adjusting the revenue-sharing ratio and the wholesale price. An extension is conducted for a sensitivity analysis of unit punishment cost on the supplier’s input quantity decisions.

Assessing parametric and nitrogen fertilizer input uncertainties in the ORYZA_V3 model predictions

AbstractThe ORYZA_V3 model is widely used for simulating paddy rice (Oryza sativa L.) growth. However, few studies have assessed the uncertainties in the ORYZA_V3 model predictions. This study examined the effects of uncertainties in crop parameters and input nitrogen (N) fertilizer rates on four growth variable predictions using the Markov Chain Monte Carlo and Monte Carlo methods. The results showed: (a) This model generated accurate predictions of the yield and aboveground biomass (AGB) at harvesting and leaf N concentration (FNLV) at the early (FNLVE) and middle (FNLVM) development stages but poor predictions of the FNLV at the late development stage (FNLVL) and leaf area index (LAI) at tillering, stem elongation, and panicle initiation development stages. (b) Parametric uncertainty had a significant effect on FNLVE and FNLVM predictions but had a negligible effect on LAI predictions at the three development stages. (c) Different input N fertilizer rates produced different degrees of parametric uncertainty in yield, AGB, FNLVM, and FNLVL predictions. (d) Incorporating the uncertainty in the input N rates increased the predictive variance of the variables. The average magnitude of increase was 69.45% for yield; 9.73% for AGB; 0.43% for LAI; and 0, 101.71, and 146.91% for FNLVE, FNLVM, and FNLVL, respectively. However, the mean values of the prediction distributions varied slightly after incorporating the uncertain input N rates. This study demonstrated the importance of the input N rates for simulating the yield, AGB, FNLVM, and FNLVL. The ORYZA_V3 model can be used to determine the impacts of N on rice growth.

Price negotiation and coordination in outsourcing supply chain under yield and demand uncertainties

This paper considers the issues of pricing, lot-sizing decisions and coordination in a supply chain consisting of one original equipment manufacturer (OEM) and one contract manufacturer (CM). A Bayesian game accounting for asymmetric information is established to optimize the CM’s outsourcing price and the OEM’s selling price. A Stackelberg game incorporating yield and demand uncertainties is subsequently modelled to optimize the CM’s production quantity and the OEM’s order quantity. Finally, a shortage penalty with surplus purchase contract is proposed to coordinate the supply chain. It is found that the optimal outsourcing price is either the lower limit or the stationary point of the common price domain, while the optimal selling price is the upper limit. Whether the CM adopts a conservative or an aggressive production strategy depends on the threshold of the outsourcing price. Moreover, the coordination contract offers great flexibility in parameter selection. By setting the order quantity, penalty price and surplus purchase price properly, the supply chain can realize a win-win situation.

Modeling the Korean Crop Market under the Yield Uncertainty Using the Stochastic Approach

This study introduces a stochastic agricultural policy model to generate stochastic projection under uncertainty. To do that, we extract an uncertainty from the residual in the yield functions for rice, wheat, corn, soybean, and barley to consider the uncertainty of climate conditions. A copula function is used to reflect a correlation among variables. We then utilize a Monte Carlo simulation approach to generate 500 random draws representing residuals for the yield of individual crop in the future. We impose random draws into the stochastic model built based on the crop model in KREI-KASMO. Our stochastic projections show the possible range of prices that a deterministic model does not generate. These ranges imply that the possible range of prices under the uncertainty of climate conditions in the Korean crop market. Our study finds that the actual price of rice is out of the projected range, but soybean price is within the range of stochastic price projection. Our study provides the necessity of stochastic agricultural policy model and helps policy makers and market analysts who consider a future market.

The Value and Cost of Crop Minimum Support Price: Farmer and Consumer Welfare and Implementation Cost

In many developing countries, crop minimum support price (MSP) is a subsidy scheme to (i) improve farmer welfare by safeguarding farmers’ incomes against vagaries in crop price and (ii) improve consumer surplus by ensuring sufficient crop production. Among different mechanisms to operationalize an MSP scheme, we focus on credit-based MSPs under which the government credits farmers should the prevailing market price be below the prespecified MSP. By accounting for the implementation cost of the MSP, we examine the effectiveness of the MSP in terms of net benefit (i.e., farmer’s surplus minus the implementation cost) and net social value (i.e., sum of farmer’s and consumer’s surpluses minus the implementation cost) in a market that consists of risk-averse farmers with heterogeneous production costs. Also, farmers face two types of uncertainties: (1) market and (2) production yield uncertainty. We find that a credit-based MSP can induce crop production, which is intuitive. However, we find some more interesting results: (i) offering a higher MSP may not improve farmer’s surplus, (ii) the net benefit of an MSP can be negative—the cost of offering an MSP can exceed the farmer’s surplus, and (iii) there exists an MSP that maximizes the net social value. We extend our single-crop model to the case of two crops to capture the intercrop MSP interaction. We show that when one crop is more rewarding but riskier than the other crop, then it is sufficient to offer an appropriate MSP for one of the two crops while offering no MSP to the other crop. This paper was accepted by Vishal Gaur, operations management.

Make-to-order supply chain coordination through option contract with random yields and overconfidence

This paper investigates a two-echelon supply chain with a supplier and a manufacturer with yield uncertainty. We assume that the manufacturer is overconfident about its yield and examine how this could impact on the performance for each company and the supply chain. We propose option contracts to be used to coordinate the ordering and production across the supply chain. A wholesale price contract without overconfidence (i.e., with complete rationality) about the manufacturer's yield is first developed as a benchmark. Based on that, we analyze the impact of overconfidence on the decisions and the expected profits for each player in the supply chain under the wholesale price contract. This setting is then applied to the case of option contracts. We derive analytical results on the decisions and the expected profits, and propose conditions for the option price and the option execution price to achieve supply chain coordination. Overall we find that overconfidence has an adverse impact on the performance of both companies. Their expected profits will decline as the level of overconfidence goes up. Option contracts can improve the performance for both companies but cannot completely eliminate the impact of overconfidence. This paper therefore could be used to guide the coordination and cooperation of companies along a supply chain when there exists yield uncertainty and overconfidence. Our propositions are validated through numerical experiments on a hypothetical case and supported by extensive parameter sensitivity analyses.

An Economic Analysis of Agricultural Support Prices in Developing Economies

The goals of the guaranteed support price (GSP) scheme, adopted by several developing countries to support their farmers and the underprivileged population, are threefold: (a) as a supply‐side incentive, to ensure high output from the farmers, (b) as a demand‐side provisioning tool, to subsidize the consumption needs of the poor, and (c) to maintain an adequate amount of foodgrains as reserve stock, to mitigate the adverse effects of yield uncertainty (food security). We offer analytically supported insights on the fundamental aspects of this scheme by analyzing a Stackelberg game between a homogenous population of small farmers and a social planner. We model the strategic behavior of the farmers and the consuming population (Above‐ and Below‐Poverty‐Line consumers), and compare the equilibrium outcome with that under the direct benefit transfer (DBT) scheme, where the social planner simply distributes the budget among the BPL consumers. The comparison of the social planner's surplus depends on the marginal value from maintaining a reserve stock (i.e., the significance of food security). If this value is high, then the surplus under the GSP scheme strictly dominates that under DBT; otherwise, the surplus is identical. The comparison of the production by the farmers depends on two economic forces—the poorness of the BPL consumers and yield uncertainty. If the poorness is extreme, then the two schemes lead to identical production. If yield uncertainty is dominant, then DBT is ineffective in improving production while the GSP scheme can induce a strictly higher production by strategically choosing the reserve stock.