Explore the vast range of titles available.

This research was aimed to estimate the long-run cost and supply functions and to calculate the optimum profit-maximizing level of production, optimum capacity for broiler projects. The preliminary data were obtained by questionnaires that were distributed to project owners in Qadisiyah, Babil and Wasit governorates. A total of 80 projects amounted for 15% of the total projects in these governorates were included. The results indicated that the optimal profit-maximizing and actual production were 25,337, 34,737, and 21.25 tons respectively. The optimum production capacity was 9.9 thousand birds, while the actual capacity was 8.3 thousand chicken The cost elasticities were 0.936, 1.0 and 1.23 at the actual, optimal and profit maximizing production, respectively. The supply function had low elasticity indicating that the producers face great difficulty in controlling production in case of price changes. From these results, it can be concluded that government support is required for productive inputs, facilitating loans, preventing poultry importing, and adoption of strategic policy for the agricultural sector in general and poultry production in particular.

We consider a day-ahead electricity market that consists of multiple competing renewable firms (e.g., wind generators) and conventional firms (e.g., coal-fired power plants) in a discrete-time setting. The market is run in every period, and all firms submit their price-contingent production schedules in every day-ahead market. Following the clearance of a day-ahead market, in the next period, each (renewable) firm chooses its production quantity (after observing its available supply). If a firm produces less than its cleared day-ahead commitment, the firm pays an undersupply penalty in proportion to its underproduction. We explicitly characterize firms’ equilibrium strategies by introducing and analyzing a supply function competition model. The purpose of an undersupply penalty is to improve reliability by motivating each firm to commit to quantities it can produce in the following day. We prove that in equilibrium, imposing or increasing a market-based undersupply penalty rate in a period can result in a strictly larger renewable energy commitment at all prices in the associated day-ahead market, and can lead to lower equilibrium reliability in all periods with probability 1. We also show in an extension that firms with diversified technologies result in lower equilibrium reliability than single-technology firms in all periods with probability 1. The electronic companion is available at https://doi.org/10.1287/mnsc.2017.2961 . This paper was accepted by Serguei Netessine, operations management.

The central issue in supply chain management is to match supply with demand, and the heart of a planning model is the modeling of supply and demand functions. To allow for analytical tractability, the existing literature often assumes almost surely linear supply and demand functions, which greatly limits the applicability of the models. The goal of this paper is to provide a unified approach to analyze general random supply and demand functions. By transforming the problem into one defined on a higher dimension, we show that many of the seemingly highly nonlinear supply and demand functions (in the almost sure sense) are linear in the stochastic sense. With this new notion of linearity, called stochastic linearity in midpoint , our ability to analyze supply chain problems is much enhanced. We are able to prove the concavity of the profit function in the transformed supply and demand decisions for a general class of supply and demand functions that include, but are not restricted to, the ones studied in the existing literature. Thus, many of the challenging problems now become tractable. Moreover, we characterize a set of easy-to-verify conditions for stochastic linearity in midpoint. The online appendix is available at https://doi.org/10.1287/opre.2017.1648 .

The work is devoted to the modeling of the behavior of the tourism market in the conditions of a supply random lag, distributed according to normal and uniform distribution laws. The behavior of dependences on the tourist market of supply and demand on the price is considered. The modeling of the behavior of the tourism market was carried out using a market dynamic model in the plane of variables “supply – price – demand” taking into account the interests of different groups of consumers, primarily from the point of view of pricing. The delay between changes in supply and demand volumes is taken into account using a Cobweb model. To test this method, information was collected on family expenses when traveling abroad (outbound tourism, tourist vacations lasting 7-15 days) by surveying the employees of 38 travel organizations as of 2021. Three segments of the tourism market are identified: low ($2000 − 4000), medium ($4000 − 12000), and VIP-segment ($12,000 − 20,000). The analysis of the modeling results showed that the behavior of tourists of different segments can significantly influence the market dynamics. The use of a Cobweb model allowed for determining the level of stability of tourist behavior and assessing the possibility of consumer migration from one segment to another. Sensitivity to price changes and response to new offers from different segments can be different, which is important for determining pricing strategies, marketing, and the development of new tourism products.

Energy efficiency may be an inexpensive way to meet future demand and reduce greenhouse gas emissions, yet little work has been attempted to estimate annual energy efficiency supply functions for electricity planning. The main advantage of using a supply function is that energy efficiency adoption can change as demand changes. Models such as Duke University’s Dynamic Integrated Economy/Energy/Emissions Model (DIEM) have had to rely on simplistic or fixed estimates of future energy efficiency from the literature rather than on estimates from energy efficiency supply curves. This paper attempts to develop a realistic energy efficiency supply curve and to improve on the current energy efficiency modeling. It suggests an alternative approach based on saved-energy cost data from program administrators and explains the methodologies employed to create the supply curve. It illustrates this approach with results from DIEM for various electricity demand scenarios. The analysis suggests that an additional 5–9% of energy efficiency is deployed for every 10% increase in the cost of electricity. Therefore, DIEM “invested” in energy efficiency up to an inelastic point on the energy efficiency supply curve. By contrast, the U.S. Environmental Protection Agency’s energy efficiency approach assumes that realized energy efficiency is fixed, and has no elasticity, regardless of changes to marginal costs or constraints that affect emissions or economics.

As multisourcing becomes a widely adopted strategy in dynamic procurement planning, firms inevitably source from suppliers with dependent material flows, and such supply dependence, created by common second-tier suppliers or a common economic environment, is often positive. We show that firms can experience significant profit loss when implementing a policy computed based on a model that ignores the dependence among suppliers’ stochastic material flows. The profit loss is particularly significant when a firm earns a low margin or faces an unreliable and fragmented supplier base. Analysis of the firm’s dynamic multisourcing strategy under dependent supply uncertainties, however, is challenging. By expanding the space of ordering decision to a class of contingency policies, we identify conditions under which the dynamic planning model has a concave transformation. This approach allows us to characterize the optimal procurement policy. Moreover, our analysis suggests that the firm may order more from a less reliable supplier than from a more reliable one who charges the same procurement cost. The order allocation to the less reliable supplier can be even larger when the capacities are more dependent. Though the analysis of our base model is conducted for dependent supply capacities that are independent across periods, we show that the results can be generalized to Markov-modulated supplies or general supply functions that are stochastically linear in midpoint. This paper was accepted by Noah Gans, stochastic models and simulation.

We consider demand function competition with a finite number of agents and private information. We show that any degree of market power can arise in the unique equilibrium under an information structure that is arbitrarily close to complete information. Regardless of the number of agents and the correlation of payoff shocks, market power may be arbitrarily close to zero (the competitive outcome) or arbitrarily large (so there is no trade). By contrast, price volatility is always lower than the variance of the aggregate shock across all information structures. Alternative trading mechanisms lead to very distinct bounds as a comparison with Cournot competition establishes.

We consider a model where a finite number of producers compete to meet an infinitely divisible but inelastic demand for a product. Each firm is characterized by a production cost that is convex in the output produced, and firms act as profit maximizers. We consider a uniform price market design that uses supply function bidding : firms declare the amount they would supply at any positive price, and a single price is chosen to clear the market. We are interested in evaluating the impact of price-anticipating behavior both on the allocative efficiency of the market and on the prices seen at equilibrium. We show that by restricting the strategy space of the firms to parameterized supply functions, we can provide upper bounds on both the inflation of aggregate cost at the Nash equilibrium relative to the socially optimal level, as well as the markup of the Nash equilibrium price above the competitive level: as long as N > 2 firms are competing, these quantities are both upper bounded by 1 + 1/( N − 2). This result holds even in the presence of asymmetric cost structure across firms. We also discuss several extensions, generalizations, and related issues.

The Zhangcheng District is critically responsible for protecting water resources, preserving sand sources, and improving the ecological environment in Beijing. Quantitative evaluation and research on the ecosystem water supply services in this area are beneficial for developing conservation planning and establishing ecological compensation mechanisms in water conservation areas. In this paper, based on the land use, meteorological, soil, and field observation data of the research area, the InVEST water yield model is used to estimate the water supply of the ecosystem in the Zhangcheng District. The model quantitatively analyzes the spatiotemporal distribution characteristics of water supply services in the basin and the influence of different topographic factors. The results show that the average supply of ecosystem water in the Zhangcheng District is approximately 45 mm, and there is a degree of spatial heterogeneity. The total water supply in the Zhangcheng District is relatively small. The water resource supply in the southwest is relatively small, the rainfall in mountainous forest areas in the southeast is high, its water supply is higher, and the supply of forest land water is relatively high. The high-value areas are mainly distributed at 1500 to 3500 m and 15°~40°; the water supply on the sunny slope is greater than that on the shady slope. With the increase in altitude and slope, the water supply in the basin tends to increase first and then decrease.

With the reform of electricity markets, demand response (DR) plays an important role in providing flexibility to the markets. Block bidding market is a new market mode, which is based on the concept of “the same quality, the same price”. The mechanism has great effects in reducing start-stop related costs. In this paper, we propose a double-sided non-cooperative game model in block bidding markets with a DR program. The model combines the advantages of block bidding and the simplicity of hourly bidding. In the model, one side is the non-cooperative game of supply-side power firms, and we propose a novel supply function bidding model based on block duration and load capacity to maximize each firm’s profit. The other side is the demand-side different types of customers, and we propose a DR model that combines hourly-various prices with the block bidding mechanism to maximize each customer’s payoff. The overall market optimization problem is solved by a distributed iterative algorithm, which has great convergence performance. We verify the proposed model on real data, and the results show that the demand load curve becomes flattened with DR, and the total generation costs decrease while the social welfare is significantly improved.