Effective irrigation management is critical for future food supplies and the prosperity of producers engaged in irrigation production. Through a deficit irrigation field experiment, we determine the financial impact on producers caused by changing irrigation costs, corn prices, extreme weather events, and restricting irrigation levels. Results suggest that the optimal economic strategy within our constrained optimization model is to fully irrigate, with the economic impact highly dependent on commodity prices, restriction level, and irrigation costs. The greatest economic losses caused by irrigation restrictions come from decreases in yield. Some simulations resulted in negative profits, indicating that a switch to alternative crops requiring less irrigation may be warranted.

We consider a two-stage service system with two types of servers, namely subordinates who perform the first-stage service and supervisors who have their own responsibilities in addition to collaborating with the subordinates on the second-stage service. Rewards are earned when first- or second-stage service is completed and when supervisors finish one of their own responsibilities. Costs are incurred when impatient customers abandon without completing the second-stage service. Our problem is to determine how the supervisors should distribute their time between their joint work with the subordinates and their own responsibilities. Under the assumptions that service times at both stages are exponentially distributed and that the customers waiting for second-stage service abandon after an exponential amount of time, we prove that one of two policies will maximize the long-run average profit. Namely, it is optimal for supervisors to start collaborating with subordinates either when subordinates can no longer serve new customers or as soon as there is a customer ready for second-stage service. Furthermore, we show that the optimality condition is a simple threshold on the system parameters. We conclude by proving that pooling supervisors (and their associated subordinates) improves system performance, but with limited returns as more supervisors are pooled.

PALWEED:WHEAT is a bioeconomic decision model for determining profit-maximizing postemergence herbicide treatments for winter wheat in the Washington–Idaho Palouse region. PALWEED:WHEAT performed relatively well economically in 2 yr of on-farm field tests. However, the model was less sensitive than desired in prescribing postemergence broadleaved herbicides in the presence of high densities of broadleaved weed seedlings. Therefore, PALWEED:WHEAT was revised in response to the field testing. This paper compares the revised model's agronomic and economic performance to the original model in computer simulations. The revised model, PALWEED:WHEAT II, differs from the original model in several respects: (1) exponential functions replace linear functions in predicting weed survival, (2) preplant application of a nonselective herbicide is entered as an exogenous binary variable, (3) separate indices of broadleaved and grass competition are substituted for an aggregate weed competition index in the wheat yield function, (4) hyperbolic replaces logistic functional representation of weed damage to wheat yield, and (5) separate models are estimated for winter wheat after spring dry pea and for winter wheat in all examined crop rotation positions. In simulations including a variety of agronomic and economic conditions, PALWEED:WHEAT II recommended postemergence herbicide types and rates that consistently complied with agronomic and economic theory. Furthermore, the revised model, especially when estimated from the relevant wheat after pea data set, was markedly more balanced in recommending both broadleaved and grass herbicides in response to observed densities of both weed groups. The substantial change in herbicide recommendations in response to changes in model functional specifications following field testing confirms the importance of field testing and revision of bioeconomic decision models.

Transfer spending among English Premier League clubs has increased drastically since the inception of the league, often funded by extremely wealthy owners who began purchasing majority stakes in clubs. Using data from the Deloitte Annual Review of Football Finance, we allow for different tiers of football clubs representing the haves and the have nots as well as a comparison between the first and second decades of the Premier League. Our finding that heightened spending has improved on-field performance only at the expense of hurting profitability is in line with win maximisation surmounting profit maximisation in today's Premier League.

This research examines the predictability of a profit maximization model, an expected value-variance utility maximization (E-V) model, and two versions of the target-MOTAD model for modeling risky agricultural production decisions. Model solutions were translated into expected value and variance of farm income for analysis. Direct comparison and chi-square analysis of actual and predicted expected income distributions were used in the analyses. It was concluded that the utility maximization and cash-cost target-MOTAD models predicted distributions of farm income better than the variable-cost target-MOTAD and profit maximization models.

The objective of this research is to identify and quantify the motivations for organic grain farming in the United States. Survey data of US organic grain producers were used in regression models to find the statistical determinants of three motivations for organic grain production, including profit maximization, environmental stewardship, and an organic lifestyle. Results provide evidence that many organic grain producers had more than a single motivation and that younger farmers are more likely to be motivated by environmental and lifestyle goals than older farmers. Organic grain producers exhibited a diversity of motivations, including profit and stewardship.

Different theories have been posited that try to explain the decision-making process of smallholders especially regarding the adoption of new technologies or new agricultural techniques. The objective of this paper is to review and re-assess the dominant household production theories to explain the decision making of smallholders practicing conservation agriculture (CA) in the southern, eastern, and central provinces of Zambia. It also discusses the potential role of CA toward economic development. It finds that the CA smallholders studied did not aim to maximize profits but tried to secure household consumption from their own production before any other considerations in risky and uncertain environments. Their response to economic incentives was contingent on minimizing risks associated with securing a minimum level of livelihood and investing into local forms of insurance. This paper concludes that the ability for CA to contribute to rural livelihoods and economic development would depend on how adequately the factors that hinder smallholder agricultural development in general are addressed.

Herbicide-resistant (HR) rice technology is a potential tool for control of red rice in commercial rice production. Using an ex ante mathematical programming framework, this research presents an empirical analysis of HR rice technology adoption under uncertainty. The analysis accounts for stochastic germination of red rice and sheath blight to model a profit maximization problem of crop rotation among HR rice, regular rice, and soybeans. The results demonstrate that risk attitudes and technology efficiency determine adoption rates and optimal rotation patterns.