参考价格效应下报童模型的定价和库存联合策略研究

考虑带有消费者参考价格效应的具有乘项需求的价格报童模型,未满足的需求全部损失.基于平均销售的库存因子弹性定义了一类新的因子弹性-带有参考价格效应的平均销售库存因子弹性,借助此因子弹性和需求价格弹性分别分析了参考价格以及需求随机性对最优价格、订货量、最优利润以及最优服务水平的影响.最后,通过数值试验验证了结论的正确性.     

Weibull变质率和短缺量拖后的易变质物品EOQ模型

基于需求和采购价格均为时变的EOQ模型,考虑物品的变质率呈更符合现实情况的三参数Weibull分布,同时考虑短缺量拖后和资金时值对易变质物品库存管理的影响,构建了相应的EOQ模型.应用数学软件Matlab对该库存模型进行仿真计算和主要影响参数的灵敏度分析.结果表明,该模型存在最优解,且各主要影响参数对最优库存控制各有不同程度的影响,资金时值对库存总成本净现值的影响程度要甚于短缺量拖后的影响,故在制定科学的库存策略时资金时值需要更加关注.     

需求和采购价格均为时变的易变质物品EOQ模型

基于需求和采购价格均为时变的EOQ模型,进一步考虑物品的变质对库存系统的影响,建立了相应的EOQ模型,并证明了在给定条件下,计划期内的库存总成本是关于服务水平的凸函数.并应用数学软件MATLAB,对该模型进行仿真计算和主要参数的灵敏度分析,结果表明,该模型存在最优解且各主要参数对最优库存控制有不同程度的影响.     

区际救援物资中转调度的动态决策模型与算法

考虑灾害救援中灾区对应急物资的持续消耗,研究了区际多品种救援物资的动态中转调度问题.综合考虑各阶段调度费用、运输费用和库存费用总和最小化的救援物资中转调度安排和库存规划,建立了一个区际救援物资中转调度动态决策模型,并设计了一种矩阵编码的协进化遗传算法.最后通过一个算例验证了模型和算法的有效性.     

考虑变质量可折价回购与库存水平影响需求的易变质品库存模型

考虑到易变质商品在一个销售周期内会有一定数量的商品发生变质,构建了一个考虑在一个销售周期内所产生的变质数量可折价回购以及库存水平影响需求的易变质品的库存模型,而且针对销售周期内的缺货数量,模型假定采取部分延迟订购的策略。针对这一模型,给出了平均利润函数并证明了其存在最优解,然后通过算例完成了不同销售价格、不同折价回购比例和不同库存影响因子条件下的最优订货策略的确定以及其余相关参数的灵敏度分析,分析结果可对零售商的订货策略有一定的参考价值.     

库存系统中的时滞变质物品的EOQ模型

本文考虑时段性变质物品的库存问题 .给出了一订货就交货 ,不允许缺货的时滞变质物品的库存模型与最优库存策略 ,并证明了该模型不是那物品自始至终有变质性质的 EOQ模型的简单叠加 .     

替代产品的动态库存决策与控制

考虑了替代产品的动态库存决策与控制问题,建立了替代产品的多周期动态库存决策与控制模型.得到了目标函数的一些重要性质,给出了系统最优参数的求解算法,利用动态规划方法对系统的库存参数进行了优化求解.     

快速补货模式下的动态定价与库存联合策略

在供应有限的情况下,研究常规补货和快速补货下商品动态定价问题.首先,建立了动态规划模型,理论证明了最优库存策略是基于(s,S)策略下改进的基本库存策略.其次,提出了一种启发式策略求复杂系统的最优策略,启发式算法能够求出最优价格和最优库存水平.最后,数值算例研究表明,库存管理中采用快速补货提高了零售商的利润;初始库存水平越高零售商的利润越高.     

带短期价格折扣和允许两次特殊补货的库存决策模型

针对供应商提供短期价格折扣且允许零售商两次特殊补货的库存系统, 建立了以零售商库存效益最大化为目标的库存决策模型, 分析了模型的性质, 根据经济订单批量补货决策下补货时间点与折扣时段的关系, 确定了零售商在不同补货策略下的库存效益增值函数. 据此给出零售商相应的最优补货策略函数表达式, 提出了该模型的一个全局优化算法, 并通过数值算例验证了模型和算法的有效性与可行性.     

参考价格效应下Nash讨价还价公平对供应链决策的影响研究

以一制造商和一零售商构成的两级动态供应链系统为研究对象,考虑消费者参考价格效应和供应链成员具Nash讨价还价公平偏好行为,应用贝尔曼连续型动态规划理论构建了集中、分散、双方均公平和只一方具公平偏好下不同模式的微分博弈模型,讨论了供应链成员的公平行为和消费者参考价格效应对产品定价与质量决策的影响;并结合数值算例验证了所得结论并对公平程度和关键参数进行了敏感性分析.研究发现:1)在制造商具Nash讨价还价公平偏好时,供应链的决策结果会呈现出"高商誉高价格高质量"的特征,同时此模式下的品牌溢价最高.2)供应链中任意一方提高其公平关切程度都对供应链的绩效产生明显的影响.3)消费者心中参考价格的提升会促使供应链成员提升其价格和产品质量,同时会提升系统的总利润.     

Price dynamics in the European Union Emissions Trading System and evaluation of its ability to boost emission-related investment decisions

The price of permits in the European Union Emissions Trading System (EU ETS) has historically been highly sensitive and prone to jumps. We consider different stochastic processes to model the price of permits, and show that the Variance Gamma (VG) model provides the best fit for the price distribution, among a selection of infinite activity processes. Using this result as a starting point, we assess the effects of the EU ETS in delivering low-carbon investments at the firm level, by modeling a price taker electricity producer subject to the EU ETS jurisdiction. We compute, via Least Squares Monte Carlo, the value of the real option the greenhouse gas emitter has, consisting in the opportunity to switch from its current high-carbon technology to a cleaner one. We use a VG specification for carbon prices, and a mean-reverting (Brennan–Schwartz) process for the price of fuel. Moreover, we further analyze the investment decision problem, in case of a CO₂ price stabilization mechanism in the form of a price floor, by explicitly computing the expected value of the investment project by means of Fourier methods. Our results show that the introduction of the price stabilization mechanism significantly affects the timing of the investment decision, and supports emission-related investments.     

IMPACTS OF WATER SUPPLY UNCERTAINTY AND STORAGE ON EFFICIENT IRRIGATION TECHNOLOGY ADOPTION

In the framework of a stochastic dynamic programming model, the paper investigates the impact of water supply uncertainty and storage at farm level on adoption of efficient irrigation technologies under a flexible water price regime. We find that even a flexible water pricing cannot guarantee higher adoption of efficient irrigation technology in all cases. Results of the paper indicate that if a farmer invests in water storage capacity, then the value of efficient usage of water increases, and the rate of adoption of efficient irrigation technology will be higher. It establishes a complementarity relationship between investments in storage capacity and adoption of efficient irrigation technology. The relationship becomes stronger with increasing variance in water supply. In a situation without any option to store water at the farm level, we find a negative relationship between investment in efficient irrigation technology and water variability. However, numerical analysis results suggest that a risk averse farmer may invest more in efficient irrigation only if the variance in water supply is very high.     

Impact of some parameters on investments in oligopolistic electricity markets

It is seldom the case that one has the opportunity to compare investments as projected by a long-term multi-period model to what is eventually realized in practice. Further, although sensitivity analysis is of common use in any optimization setting, the impact of some parameters on strategic investments is not yet fully assessed in the context of the deregulated electricity industry. Starting with a benchmark model of the Finnish industry, we precisely explore the impact on equilibrium investments of varying such parameters as direct- and cross-price elasticities, length of the planning horizon and the depreciation rate of capacity. We run the model with different parameter values and compare the predicted equilibrium with what companies have actually done. The model is a stochastic dynamic game involving three players and played over a ten-year period.Our results show the depreciation rate and the planning horizon have a notable effect on investment levels, whereas price elasticities seem to play a lesser role. Although the model’s results are rather well aligned to total industry investments, it diverges from individual levels. This may be due to the cost parameter used and/or to the open-loop information structure adopted in the computations. In any event, these results should be of methodological and practical interest to scholars and practitioners involved in strategic investment in the electricity industry.     

Financial valuation of investments in future power generation technologies: nuclear fusion and CCS in an emissions trading system

This paper outlines a model approach for the financial valuation of future power generation technologies, such as nuclear fusion or carbon capture and storage (CCS) under an emissions trading regime. Since on imperfect markets, interdependencies between decisions inhibit the isolated valuation of an investment, we use simultaneous calculation of optimal production, sales and investment programs; these are subject to the constraints and conditions characteristic for investments in low- and zero-carbon technologies such as fusion and CCS. Duality theory allows to derive, identify and economically interpret the determinants for the price ceiling as (corrected) net present values. Sensitivity analysis shows how changes in the technical specification or environmental policies affect the maximum payable price. Particularly, tradable permits have several effects on low-carbon investments and do not always encourage CO ₂ abatement. While a zero-emissions technology like fusion always profits from a tightened emissions trading scheme, for low-carbon technology like CCS—in particular cases—this may even be counterproductive from an economic as well as an environmental point of view.     

Impact of Technology Assimilation on Investment Policy: Dynamic Optimization and Econometric Identification

The paper introduces a dynamic model of optimization of R&D intensity under the effect of technology assimilation. The model involves R&D investments, technology stock, production, and technology productivity as main variables. The model characterizes the “growth” and “decline” trends that describe the interaction between R&D investments and transformation process of production factors. The technology stock is constructed as a function of indigenous and exogenous technology stocks and their growth rates. The research focuses on the issue of a reasonable balance between the indigenous technology stock and assimilated technology flow. Econometric linearization of the technology assimilation effect is used to construct a reasonable optimal control model. The existence of the value function for the problem of the optimal economic growth on the infinite horizon is proved and the basic features of the value function are outlined. The property of strong invariance for the main proportions of the model such as technology productivity and R&D intensity is proved. The model is calibrated on the aggregate data of the Japanese automotive industry. The research was sponsored by the SIMOT Program of the Japanese Ministry of Education, Science and Technology. The second author was supported by the Russian Fund for Basic Research, Grants 05-01-00601, 05-01-08034, by the Russian Fund for Humanities, Grant RFH 05-02-02118a, and by the Program for the Sponsorship of Leading Scientific Schools, Grant NSCH-791.2003.1.     

On automorphisms of a distance-regular graph with intersection array {204, 175, 48, 1; 1, 12, 175, 204}

The research is focused on the question of proportional development in economic growth modeling. A multilevel dynamic optimization model is developed for the construction of balanced proportions for production factors and investments in a situation of changing prices. At the first level, models with production functions of different types are examined within the classical static optimization approach. It is shown that all these models possess the property of proportionality: in the solution of product maximization and cost minimization problems, production factor levels are directly proportional to each other with coefficients of proportionality depending on prices and elasticities of production functions. At the second level, proportional solutions of the first level are transferred to an economic growth model to solve the problem of dynamic optimization for the investments in production factors. Due to proportionality conditions and the homogeneity condition of degree 1 for the macroeconomic production functions, the original nonlinear dynamics is converted to a linear system of differential equations that describe the dynamics of production factors. In the conversion, all peculiarities of the nonlinear model are hidden in a time-dependent scale factor (total factor productivity) of the linear model, which is determined by proportions between prices and elasticities of the production functions. For a control problem with linear dynamics, analytic formulas are obtained for optimal development trajectories within the Pontryagin maximum principle for statements with finite and infinite horizons. It is shown that solutions of these two problems differ crucially from each other: in finite horizon problems the optimal investment strategy inevitably has the zero regime at the final stage, whereas the infinite horizon problem always has a strictly positive solution. A remarkable result of the proposed model consists in constructive analytical solutions for optimal investments in production factors, which depend on the price dynamics and other economic parameters such as elasticities of production functions, total factor productivity, and depreciation factors. This feature serves as a background for the productive fusion of optimization models for investments in production factors in the framework of a multilevel structure and provides a solid basis for constructing optimal trajectories of economic development.     

Control of ruin probabilities by discrete-time investments

The control problem of controlling ruin probabilities by investments in a financial market is studied. The insurance business is described by the usual Cramer-Lundberg-type model and the risk driver of the financial market is a compound Poisson process. Conditions for investments to be profitable are derived by means of discrete-time dynamic programming. Moreover Lundberg bounds are established for the controlled model.     

Investments in EOP-technologies and emissions trading – Results from a linear programming approach and sensitivity analysis

This paper offers a general approach to valuating investments in end-of-pipe-technologies (EOP-technologies) with special regard to an emissions trading scheme. Since investments of this kind affect production, it is necessary to derive the required payments for a financial valuation and the constraints from production theory and production planning. On this basis, it is possible to develop a valuation model. This model considers joint production, activity-level-dependent and -independent payments and specifically includes the indivisibility of the investment. Applying duality theory enables us to examine the determinants of the price ceiling for such an investment. Sensitivity analysis shows that tradable permits have several effects on an investment and do not always encourage environmentally beneficial investments – in particular cases they may even be counterproductive.     

Representative Agent Pricing of Financial Assets Based on L��vy Processes with Normal Inverse Gaussian Marginals

The aim of the paper is to test the assumption of normal inverse Gaussian returns from speculative investments. We construct an asset pricing model where price processes are pure jump processes having associated returns with marginal distributions of this particular type. The resulting model is not complete, and we employ a partial equilibrium framework with a representative agent. The model is confronted with some stylized facts, like the equity premium puzzle, and the results seem promising.     

Selection of contract suppliers under price and demand uncertainty in a dynamic market

In this paper, we consider a supply contracting problem in which the buyer firm faces non-stationary stochastic price and demand. First, we derive analytical results to compare two pure strategies: (i) periodically purchasing from the spot market; and (ii) signing a long-term contract with a single supplier. The results from the pure strategies show that the selection of suppliers can be complicated by many parameters, and is particularly affected by price uncertainty. We then develop a stochastic dynamic programming model to incorporate mixed strategies, purchasing commitments and contract cancellations. Computational results show that increases in price (demand) uncertainty favor long-term (short-term) suppliers. By examining the two-way interactions of contract factors (price, demand, purchasing bounds, learning and technology effect, salvage values and contract cancellation), both intuitive and non-intuitive managerial insights in outsourcing strategies are derived.