A learning curve model with knowledge depreciation

Empirical studies in several industries have verified that unit costs decline as organizations gain experience or knowledge in production, which is referred to as the learning curve effect. In the past two decades, there has also been analytical work on the relationship between a firm's learning curve effects and its pricing and output decisions. Learning rates differ significantly across firms in the same industry and recent empirical evidence has shown that knowledge depreciation may be an important reason for these differences. We propose and analyze a learning curve model with knowledge depreciation and provide several new insights. First, we show that there exists a steady state where knowledge level and unit cost remain constant over time and there exists an optimal path to this steady state. Many empirical researchers have observed this ‘plateau’ phenomenon, whereby unit costs decline but reach saturation after some time. While this has been traditionally modeled exogenously in the learning curve literature by assuming that cost reduction stops at some level of knowledge through a convex, decreasing unit cost function, we provide an alternative endogenous explanation. We are also able to show that, unlike in the model without knowledge depreciation, the production rate along the optimal path to the steady state may decrease over time. Also, the knowledge level along the optimal path may actually decline over time. Finally, we show that the optimal production rate decreases at higher interest rates and increases at higher knowledge depreciation rates. In turn, this implies that a high interest rate environment discourages firms from achieving high knowledge levels and results in higher prices. On the other hand, higher knowledge depreciation rates result in higher production rates and lower prices.     

Output learning and duality in joint production programs

Summary Output learning is incorporated into a short-run static cost-minimizing model of the multiproduct, multifactor firm which employs a fixed-coefficients technology. The firm's output processes or activities are ultimately specified as functions of the activity variables themselves, thus rentering a generalization to a concave program. A Lagrange dual formulation is then used to obtain the indirect cost objective. Given that this optimal cost function is differentiable and satisfies a regularity condition, its price derivatives serve as input demand functions while its derivatives with respect to the minimum output requirements yield a set of (implicit) marginal costs or dual variables.     

规模报酬递增、要素供给结构与经济增长研究

要素供给结构是要素在生产活动中配置产生的直接结果。理论分析表明在规模报酬递增生产函数前提假设下,物质资本、人力资本供给结构与均衡产出正相关,产出是二者供给结构变量的增函数。对中国经济增长的实证分析表明建国后特别是改革开放以来,以物质资本扩张为主要特征的要素供给结构对产出的增长产生了较大的推动作用,但长期来看,相对于巨大的物质资本积累而言,中国人力资本的积累太少,要素间配置效率开始恶化,这将制约中国的长期经济增长。增加人力资本投资并优化人力资本和物质资本投资结构是解决这一问题的主要途径。     

Global facility network design in the presence of competition

We study the facility network design problem for a global firm that is a monopolist seller in its domestic market but faces local competition in its foreign market. The global firm produces in the face of demand and exchange rate uncertainty but can postpone localization and distribution of the output until after uncertainties are resolved. The competitor in the foreign market, however, enjoys the flexibility of postponing all production activities until after uncertainties are resolved. The two firms engage in an ex-post Cournot competition in the foreign market. We consider three potential network configurations for the global firm. Under a linear demand function, we provide the necessary and sufficient condition that one of the three networks is the global firm’s optimal choice, and explore how the presence of foreign competition affects the sensitivity of the global firm’s design to various cost parameters and market uncertainties.     

Estimating output gains by means of Luenberger efficiency measures

In this paper we propose a new measure of input allocative efficiency that we estimate using directional distance functions. Our new measure compares the gain in output if a firm reduces technical inefficiency for the direct production possibility set and the gain in output if the firm reduces technical inefficiency for the indirect production possibility set. Because the directional distance function uses a translated origin, the gain in output from an optimal reallocation of inputs can be estimated for non-radial expansions in output. We estimate efficiency for Japanese banks during 1992–1999. The gains in outputs from reducing allocative inefficiency by reallocating inputs are greater than the gains in outputs that can be attained by reducing technical inefficiency.     

Learning curve parameter estimation beyond traditional statistics

Due to decreasing order quantities, increasing product variety and fluctuating production orders, manufacturing companies have been encountering an increased occurrence of repetitive learning-forgetting phenomenon. In this paper, deterministic methods for the learning curve parameter estimation from the limited production data available from the unstable production environment are studied. Two main learning curve models: cumulative average (Wright) and unit (Crawford) were considered and several different mathematically proven methods were proposed for the parameter estimation. The calculation results illustrated that learning curve parameters can be unequivocally estimated from the limited production data (single random sample) by using deterministic methods for both of the learning curve models, although more accurate estimation was provided by the cumulative average model based methods. Newly proposed methods enable sufficiently accurate parameter estimation from the limited production data where traditional statistical parameter estimation methods cannot be applied.     

The Nash solution of a maintenance-production differential game

A simple two-person nonzero-sum differential game between the maintenance crew of a firm and the production department of the same firm is considered. It is assumed that preventive maintenance decelerates the decrease in quality of a machine, whereas the production activities set by the firm reduces the quality of the machine. Due to the special structure of the game a system of two differential equations for the non-cooperative Nash solution trajectories can be derived. This provides a possibility to obtain qualitative insights into the structure of the solution paths by phase diagram methods without solving the necessary optimality conditions explicitly.For small salvage values of the machine, it is shown that the optimal maintenance expenditures decrease over time whereas the optimal production rate increases monotonically.Moreover, another interpretation of the differential game analyzed is given as a conflict situation between a firm polluting the environment by producing an output and a governmental agency cleaning up the pollution.     

Decomposing technical inefficiency using the principle of least action

In for-profit organizations, profit efficiency decomposition is considered important since estimates on profit drivers are of practical use to managers in their decision making. Profit efficiency is traditionally due to two sources – technical efficiency and allocative efficiency. The contribution of this paper is a novel decomposition of technical efficiency that could be more practical to use if the firm under evaluation really wants to achieve technical efficiency as soon as possible. For this purpose, we show how a new version of the Measure of Inefficiency Proportions (MIP), which seeks the minimization of the total technical effort by the assessed firm, is a lower bound of the value of technical inefficiency associated with the directional distance function. The targets provided by the new MIP could be beneficial for firms since it specifies how firms may become technically efficient simply by decreasing one input or increasing one output, suggesting that each firm should focus its effort on a specific dimension (input or output). This approach is operationalized in a data envelopment analysis framework and applied to a dataset of airlines.     

学习时间的数学模型与概率分布

根据长期教学经验总结建立出学习量与时间的关系曲线.通过曲线讨论了学习知识过程中所获知识量的时间分配和关键时间点,对学习者或教育者提出在自学或教学中关键时间点起的作用.后将学习曲线引入到概率理论分析,提出学习时间分布和密度函数观点,从而运用概率理论研究学习与时间的关系.     

Managing capacity flexibility in make-to-order production environments

This paper addresses the problem of managing flexible production capacity in a make-to-order (MTO) manufacturing environment. We present a multi-period capacity management model where we distinguish between process flexibility (the ability to produce multiple products on multiple production lines) and operational flexibility (the ability to dynamically change capacity allocations among different product families over time). For operational flexibility, we consider two polices: a fixed allocation policy where the capacity allocations are fixed throughout the planning horizon and a dynamic allocation policy where the capacity allocations change from period to period. The former approach is modeled as a single-stage stochastic program and solved using a cutting-plane method. The latter approach is modeled as a multi-stage stochastic program and a sampling-based decomposition method is presented to identify a feasible policy and assess the quality of that policy. A computational experiment quantifies the benefits of operational flexibility and demonstrates that it is most beneficial when the demand and capacity are well-balanced and the demand variability is high. Additionally, our results reveal that myopic operating policies may lead a firm to adopt more process flexibility and form denser flexibility configuration chains. That is, process flexibility may be over-valued in the literature since it is assumed that a firm will operate optimally after the process flexibility decision. We also show that the value of process flexibility increases with the number of periods in the planning horizon if an optimal operating policy is employed. This result is reversed if a myopic allocation policy is adopted instead.     

Single-machine group scheduling problems with deteriorated and learning effect

In many realistic situation, a job processed later consumes more time than the same job when it is processed earlier, this phenomenon is known as deteriorated effect. The skills of workers continuously improve when repeating the same or similar tasks, this phenomenon is as the “learning effect” in the literature. However, most studies considering the deteriorated and learning effect ignore the fact that production efficiency can be increased by grouping various parts and products with similar designs and/or production processes. This phenomenon is known “group technology” in the literature. In this paper, we propose a new group scheduling with deteriorated and learning model where the learning effect not only depends on job position, but also depends on the group position; the deteriorated effect depends on its starting time of the job. We then show that the single-machine makespan and the total completion time problems remain polynomial optimal solvable under the proposed model. In addition, we show the maximum lateness have a polynomial optimal solution under certain agreeable restriction.     

Optimal strategies for general price-quality decision models of new products with learning production costs

The question of product quality permeates every level of business and is becoming crucial for the survival of modern manufacturing firms in automotive and high-tech industries. In this paper, we deal with the optimal price and quality policies for the introduction of a new product. On the supply side, the firm wants to determine the unit price and quality level over time given that unit cost declines along a learning curve, and increases if quality is made greater. On the demand side, dynamic demand is related to price and quality, as well as to cumulative sales (which represent diffusion and saturation effects). We will model this problem in a general framework that includes several previous results as special cases.By applying the maximum principle, we will derive the optimal price and quality policies and discover the interactions between these two major strategic marketing instruments, and the diffusion process. Several fundamental theoretical results will be established for the model. Under certain specified conditions higher prices do imply higher quality, and under other conditions the optimal price declines over time while the product quality improves. To illustrate these results, the theoretical results are applied to two specific-cases: the first one is a simple nonseparable demand growth function in price and quality, the other is a separable demand function of price and quality.     

On the robustness of the bowl phenomenon

The bowl phenomenon provides a way of increasing the throughput of some production line systems with variable processing times by purposely unbalancing the line in a certain manner. However, achieving this increase in throughput depends on correctly identifying the values of the system parameters to estimate the optimal amount of unbalance and then actually being able to assign work to stations according to the optimal bowl allocation. In this paper we study the robustness of the bowl phenomenon by examining the effect of inaccurately estimating the optimal amount of unbalance and the effect of deviating from the optimal bowl allocation. Our results show that the bowl phenomenon is relatively robust in the sense that fairly large errors (even 50%) in the amount of unbalance still provide most of the potential improvement in throughput over a perfectly balanced line. Moreover, the throughput still exceeds that of a perfectly balanced line in most cases even when the work allocation to each station deviates from the optimal bowl allocation by as much as 10%. We also address the question of whether the optimal bowl allocation or the balanced line provides a more robust ‘target’ when assigning work to stations. When the deviations from these two targets are of the same magnitude, we found that the optimal bowl allocation target yields the larger throughput in most cases, where the average difference between their throughputs is roughly the same as the difference between the optimal throughput and the throughput of a balanced line. Furthermore, for the same magnitude of deviation, the throughput depends more heavily on the direction of the deviation from the balanced line than that from the optimal bowl allocation, so that the risk of a substantially reduced throughput is much larger when using the balanced line as the target. Therefore, the optimal bowl allocation provides a much more robust target than the balanced line.     

最优绩效分配的多目标优化方法

如何体现某种程度的激励并兼顾公平性是绩效分配问题研究的关键之一. 基于考核对象的个体差异性, 对考核对象进行分类处理, 通过引入以体现激励程度的控制参数和所有考核对象的基础工作量为变量的分值转化函数与满意度函数, 建立以所有考核对象的总体满意度的最大化和考核对象的满意度尽可能均衡为目标的多目标优化模型. 进而利用多目标优化模型的epsilon-约束标量化方法证明了弱有效解的存在性. 作为其应用, 研究了某高校教师的最优绩效分配问题.     

内扰动与属性合取扩展规律挖掘-发现

扰动的存在使得系统标准输出规律变成非标准输出规律的现象等价于在扰动存在的条件下,非标准输出规律被挖掘-发现;利用函数P-集合模型与它的动态特征给出这个现象的理论研究.主要结果:给出函数P-集合的结构与规律扰动,扰动恢复概念;给出扰动度量;利用这些概念,给出内扰动与属性合取扩展定理;属性合取扩展与内扰动规律挖掘定理,内扰动与规律挖掘辨识定理,内扰动与规律挖掘属性不变性定理.     

Optimal Solutions in an Allocation Process for a Continuum of Traders

We prove an existence theorem in an allocation process for a continuum of traders in the absence of the convexity assumption on the cost function and under the presence of some economic parameters.     

Time inconsistency and learning in bargaining games

This paper studies an alternating-offers bargaining game between possibly time-inconsistent players. The time inconsistency is modeled by quasi-hyperbolic discounting and the “naive backwards induction” solution concept is used in order to obtain the results. Both naive agents who remain naive and those who learn about their own preferences are considered. Offers of the players who are naive or partially naive are never accepted by any type of player in either no learning or gradual learning cases. The game between a naive or partially naive player who never learns and a time-consistent agent ends in an immediate agreement if the time-consistent agent is the proposer. A one period delay occurs if the time-consistent agent is the responder. The more naive the player is, the higher the share received. In addition, two naive agents who never learn disagree perpetually. When naive and partially naive agents play against exponential or sophisticated agents and they are able to learn their types over time, there exists a critical date before which there is no agreement. Therefore, the existence of time-inconsistent players who can learn their types as they play the game can be a new explanation for delays in bargaining. The relationship among the degree of naivete, impatience level and bargaining delay is also characterized. Specifically, for sufficiently high discount factors, agreement is always delayed. On the other hand, if the naive agent has sufficiently firm initial beliefs (slow learning or high degree of naivete), agents agree immediately.     

Learning horizon and optimal alliance formation

We develop a theoretical Bayesian learning model to examine how a firm’s learning horizon, defined as the maximum distance in a network of alliances across which the firm learns from other firms, conditions its optimal number of direct alliance partners under technological uncertainty. We compare theoretical optima for a ‘close’ learning horizon, where a firm learns only from direct alliance partners, and a ‘distant’ learning horizon, where a firm learns both from direct and indirect alliance partners. Our theory implies that in high tech industries, a distant learning horizon allows a firm to substitute indirect for direct partners, while in low tech industries indirect partners complement direct partners. Moreover, in high tech industries, optimal alliance formation is less sensitive to changes in structural model parameters when a firm’s learning horizon is distant rather than close. Our contribution lies in offering a formal theory of the role of indirect partners in optimal alliance portfolio design that generates normative propositions amenable to future empirical refutation.     

Global indeterminacy of the equilibrium in the Chamley model of endogenous growth in the vicinity of a Bogdanov–Takens bifurcation

This paper studies the dynamics implied by the Chamley (1993) model, a variant of the two-sector model with an implicit characterization of the learning function. We first show that under some “regularity” conditions regarding the learning function, the model has (a) one steady state, (b) no steady states or (c) two steady states (one saddle and one non-saddle). Moreover, via the Bogdanov–Takens theorem, we prove that for critical regions of the parameters space, the dynamics undergoes a particular global phenomenon, namely the homoclinic bifurcation. Because these findings imply the existence of a continuum of equilibrium trajectories, all departing from the same initial value of the predetermined variable, the model exhibits global indeterminacy.     

Impact of equity and equality on stability and collusion in a decentralized network

We consider a firm that procures a product from a regular supplier whose production is subject to both supply disruption and random yield risks and a backup supplier whose production capacity requires reservation in advance. Under both deterministic and stochastic demand, we study the impact of the two types of supply risks on the firm’s optimal procurement decisions and the importance of correctly identifying the source of supply risks. We find that if the overall supply risk is unchanged but its main source shifts from random yield to supply disruption, the firm should order more from the regular supplier and reserve less capacity from the backup supplier. Ignoring the existence of supply disruption leads to under-utilization of the regular supplier and over-utilization of the backup supplier. Moreover, we examine the option value of the reserved capacity that is affected by the uncertainty of customer demand. We find that the option value increases/decreases in demand uncertainty if the reservation capacity is exercised after/before demand is realized.