A study on the effect of yield uncertainty in price-setting newsvendor models with additive-multiplicative demand

Random yield and uncertain demand usually both exist in many industries, such as the semiconductor industry. In this paper, the price-setting newsvendor model is studied which involves a single manufacturer and a single retailer with random yield and uncertain demand respectively. Under the condition of additive-multiplicative demand, we investigate the varying effects of random yield on the optimal price, order quantity, and expected profit in two situations with different cost structures. The first case is an in-house production case where the firm pays for the raw material quantity it has ordered, and the second one is a procurement case where the firm pays for the real product quantity it receives only. By using the theory of stochastic comparisons, we find that a less variable and a stochastically larger yield rate both lead to a lower optimal price and a higher expected profit for the in-house production case. Moreover, a less variable yield rate also results in a lower optimal price and a higher profit for the procurement case, but this is not true for a stochastically larger yield rate. Numerical examples illustrate that the effect of yield randomness on the optimal order quantity is not general.     

规模效应下产品具有可替代性的竞争企业的外包决策

针对产品具有一定替代性的两个竞争企业(分别为企业1和企业2)和存在规模效应的上游供应商的外包决策问题, 构建了企业1 外包前后各方的利润模型,求解了下游企业的外包和自产的最优策略以及供应商的最佳批发价格,分析了企业1 的外包策略对企业2 和供应商的外包决策的影响,比较了产品替代性对外包前后各决策变量的影响。研究发现:当企业的单位生产成本高于外包成本时,企业也可能选择自产;而当企业的单位生产成本低于外包成本时,企业也可能选择产品外包。并对模型进行进一步的拓展,比较了下游企业作顺序和同时外包决策两种情景的异同。     

Anticipated responses: The positive side of elicited reactions to competitive action

This study advances the action-oriented perspective on strategy dynamics. Strategy research suggests that a firm’s profit will decrease when facing rival responses, yet anecdotal evidence indicates that countermoves may enhance its performance. What is the interaction effect of simultaneous negative- and positive-side competitive responses on organisational performance? We propose that the answer depends not only on the actor’s characteristics but also the action’s characteristics. Grounded in empirical facts, our formal model of competitive dynamics examines the possibility of anticipated responses that are deliberately elicited by the attacking firm. We show that against attentive rivals, a firm with high attention and low aggressiveness can utilise visible actions to achieve its strategic intention and deployment. Our study offers significant implications for theory and practice.     

Competitive facility location on decentralized supply chains

This paper addresses a novel competitive facility location problem about a firm that intends to enter an existing decentralized supply chain comprised of three tiers of players with competition: manufacturers, retailers and consumers. It first proposes a variational inequality for the supply chain network equilibrium model with production capacity constraints, and then employs the logarithmic-quadratic proximal prediction–correction method as a solution algorithm. Based on this model, this paper develops a generic mathematical program with equilibrium constraints for the competitive facility location problem, which can simultaneously determine facility locations of the entering firm and the production levels of these facilities so as to optimize an objective. Subsequently, a hybrid genetic algorithm that incorporates with the logarithmic-quadratic proximal prediction–correction method is developed for solving the proposed mathematical program with an equilibrium constraint. Finally, this paper carries out some numerical examples to evaluate proposed models and solution algorithms.     

Chapter 9 Moving frontier analysis: An application of Data Envelopment Analysis for competitive analysis of a high-technology manufacturing plant

Competitive analysis of plants is fundamental to enhancing the competitiveness of manufacturing firms. Moving Frontier Analysis (MFA), proposed in this paper, is a new application of Data Envelopment Analysis (DEA) to conduct competitive analysis of a high-technology manufacturing plant. The development and application of MFA was done in collaboration with the management of a US merchant semiconductor manufacturing firm. A wafer fabrication plant of the firm served as the research site for this study. MFA provides a means to determine (i) the gap between a plant's best performance and the best of competition, and (ii) whether or not it will be possible to close this performance gap, and if so, the time it will take to do so. From an implementation standpoint, competitive analysis using MFA can be conducted even if (i) accurate and detailed data on comparable plants of competitor companies are not available, and (ii) the operations of competitors' plants are dynamically changing. An application of MFA for conducting competitive analysis of the wafer fabrication plant is presented. This application illustrates how MFA makes it possible to estimate (i) the unit cost of production for the best of competitors' plants using aggregate operational information on industry best practices, and (ii) the time it will take for the plant's unit cost of production to catch up with the best of competition using the technologies in operation.     

A convergent optimization algorithm with application to monopolistic firms

We consider a monopolistic firm which auctions each business period's production at the end of the period, and wishes to maximize a discounted sum of its profits over all periods. Considering the simpler problem of determining the production which maximizes single period profit, we find that an algorithm based on using linear approximations to the firm's (unknown) average contribution margin function generates production sequences globally convergent to this production under conditions reasonably likely to hold in practice. An essentially heuristic argument then leads us to conjecture that this algorithm should be competitive with others available when applied to the original problem, and we present numerical results bearing out this conjecture.     

Competitive production scheduling: A two-firm,noncooperative finite dynamic game

In this paper, we study the production scheduling problem in a competitive environment. Two firms produce the same product and compete in a market. The demand is random and so is the production capacity of each firm, due to random breakdowns. We consider a finite planning horizon. The scheduling problem is formulated as a finite dynamic game. Algorithms are developed to determine the security, hazard, and Nash policies. Numerical examples are discussed. A single-firm optimization model is also analyzed and it is observed that the production control policy from the single-firm optimization model may not perform well in a competitive environment.     

The effect of supply uncertainty in price-setting newsvendor models

We consider a price-setting newsvendor model in which a firm needs to make joint inventory and pricing decisions before the selling season. The supply process is uncertain such that the received quantity is the product of the order quantity and a random yield rate. Two cost structures are investigated, the in-house production case in which the firm pays for the input quantity and the procurement case in which the firm pays for the quantity received only. Our objective is to investigate the effect of yield randomness on optimal decisions and expected profit. By using the theory of stochastic comparisons, we find that under both cost structures, a less variable yield rate leads to a lower optimal price and a higher expected profit. Moreover, we show that in the in-house production case, a stochastically larger yield rate also results in a lower optimal price and a higher profit, but this is not true in the procurement case. Examples show that the effect of supply uncertainty on optimal order quantity is not universal.     

Upper bounds for objective functions of discrete competitive facility location problems

Under study is the problem of locating facilities when two competing companies successively open their facilities. Each client chooses an open facility according to his own preferences and return interests to the leader firm or to the follower firm. The problem is to locate the leader firm so as to realize the maximum profit (gain) subject to the responses of the follower company and the available preferences of clients. We give some formulations of the problems under consideration in the form of two-level integer linear programming problems and, equivalently, as pseudo-Boolean two-level programming problems. We suggest a method of constructing some upper bounds for the objective functions of the competitive facility location problems. Our algorithm consists in constructing an auxiliary pseudo-Boolean function, which we call an estimation function, and finding the minimum value of this function. For the special case of the competitive facility location problems on paths, we give polynomial-time algorithms for finding optimal solutions. Some results of computational experiments allow us to estimate the accuracy of calculating the upper bounds for the competitive location problems on paths.     

Nash implementation of competitive equilibria in the job-matching market

This paper studies Nash implementation in the job-matching market where each worker works for only one firm and a firm hires as many workers as it wishes. We show that the competitive equilibrium correspondence (CEC) is the smallest Nash implementable correspondence satisfying individual rationality and Pareto indifference. Furthermore, the CEC is the minimal monotonic extension of the worker-optimal and firm-optimal subcorrespondences. We offer two “good” mechanisms that implement this correspondence in Nash equilibrium.     

The dynamics of price, quality and productivity improvement decisions

Although quality has received significant attention during the last decades and its economic benefits are beyond any doubt, lots of questions have remained unanswered as to how much, when, and in what to invest to maintain sustainable competitive advantage. A model is introduced here to guide a firm in addressing these questions. The firm produces a single product and operates in a market where monopolistic competition is effective. Demand for the product in the industry depends on both price and performance quality. Increasing productivity knowledge decreases unit production cost, but demand for the company’s product decreases over time, as competitors will be able to offer products with similar performance. Productivity and quality knowledge can be developed through induced and autonomous learning in order to strengthen company position. The paper provides an optimal control formulation of the problem and develops necessary conditions for optimality and characterizes the dynamics of optimal price, quality and investment decisions.     

Coordinating pricing and production decisions in the presence of price competition

In this paper we study the effects of coordinating pricing and production decisions on the improvement of a firm’s position in a price-competitive environment. Assuming duopolistic market conditions, we use game-theoretic concepts and models to analyze two scenarios. A firm’s marketing and production departments may vertically coordinate their pricing and production quantity decisions and the two firms may horizontally compete for price-sensitive random demand. The two scenarios include (i) no coordination and (ii) coordination in both firms. We show that by coordinating their pricing and production decisions, competing firms can increase their profitability—especially when conditions are unfavourable (i.e., with smaller market sizes, higher unit costs and lower unit revenues). While it may be intuitive to expect that coordination will outperform non-coordination, our models provide a means for formalizing and quantifying the differences between the two policies.     

The construction of a comprehensive model for production strategy evaluation

To acquire reasonable profits and to be competitive in the globalize market, more and more firms today have exploited various kinds of production strategies, such as outsourcing, joint venture, or some kind of strategic alliance. Since every production strategy has its benefits and costs and may bring a firm different opportunities and risks, which kind of production strategy is the most suitable for a firm to carry out is a difficult and complicated decision with a high degree of uncertainty. Therefore, this research proposes a comprehensive production strategy evaluation model that can facilitate such a decision making for a firm. The factors that should be considered for devising a production strategy are listed for the benefits, opportunities, costs and risks (BOCR) merits first, and fuzzy Delphi method is applied next to select the most important factors under each merit. A network with BOCR merits is constructed to incorporate the selected factors, and fuzzy analytic network process is then applied to consider the interdependence and feedback inside the network. The proposed model can effectively aid decision making on which kind of production strategy should be adopted by a firm. A case of a printed circuit board manufacturer is presented for the illustration of the proposed model.     

新成员的加入对供应商网络效率的影响分析

不断有企业进入或者退出供应商网络,网络中企业的效用和网络效率都会受到影响.本文把关系收益和竞争系数结合起来,构建了新的效用函数.并通过效用的比较分析,竞争系数对称时,新企业的加入会使网络效率增加的结论,并进一步给出了进入企业选择与中心企业或者与边缘企业建立关系所应满足的条件;而竞争系数不对称时,网络效率可能会降低.     

On Robust stability of singular systems with random abrupt changes

This paper deals with the class of continuous-time singular linear systems with Markovian switching. Sufficient conditions on stochastic stability and robust stochastic stability are developed in the LMI setting. The developed sufficient conditions are used to check if either the nominal or the uncertain systems are regular, impulse-free and stochastically stable or robust stochastically stable.     

Politics,strong institution and competitive advantage: an examination of organizational aspiration for competition

This study seeks to elucidate the interplay of interfirm rivalry and aspiration formation. Organizational aspiration serves as a categorical judgment over a desirable level of organizational performance. While aspiration as a driver of collective decision-making inside the firm is well recognized, our understanding is still limited as to the competitive consequence of aspiration-induced actions. From a computational model of aspiration-induced R&D, where competition is biased towards the status quo, this study suggests that although radical innovation calls for flexibility and diversity inside the firm, aspiration-induced action favors consensus such as a firm with machine bureaucracy either (1) in a market where a majority of consumers are unable to discern a small quality improvement, i.e., demand difficult to satisfy or (2) in a market where competitive advantage dissipates quickly, i.e., an unstable environment. In particular, this study shows that: (1) the level of organizational aspiration has little to do with the sustainability of competitive advantage; (2) aspiration strength—i.e., the extent of consensus among decision makers of the firm as to a legitimate level of organizational aspiration—interacts with the change in competitive advantage. The leading firm is likely to lose its competitive advantage when a follower has a stronger aspiration than the leader in a market whose demand is difficult to satisfy; and (3) the effect of aspiration strength on the sustainability of competitive advantage increases whenever organizational assets depreciate over time.     

Dynamics of spatial heterogeneity in a landfill with interacting phase densities – a stochastic analysis

A landfill represents a complex and dynamically evolving structure that can be stochastically perturbed by exogenous factors. Both thermodynamic (equilibrium) and time varying (non-steady state) properties of a landfill are affected by spatially heterogenous and nonlinear sub-processes that combine with constraining initial and boundary conditions arising from the associated surroundings. While multiple approaches have been made to model landfill statistics by incorporating spatially dependent parameters on the one hand (data based approach) and continuum dynamical mass-balance equations on the other (equation based modelling), practically no attempt has been made to amalgamate these two approaches while also incorporating inherent stochastically induced fluctuations affecting the process overall. In this article, we will implement a minimalist scheme of modelling the time evolution of a realistic three dimensional landfill through a reaction–diffusion based approach, focusing on the coupled interactions of four key variables – solid mass density, hydrolysed mass density, acetogenic mass density and methanogenic mass density, that themselves are stochastically affected by fluctuations, coupled with diffusive relaxation of the individual densities, in ambient surroundings. Our results indicate that close to the linearly stable limit, the large time steady state properties, arising out of a series of complex coupled interactions between the stochastically driven variables, are scarcely affected by the biochemical growth–decay statistics. Our results clearly show that an equilibrium landfill structure is primarily determined by the solid and hydrolysed mass densities only rendering the other variables as statistically “irrelevant” in this (large time) asymptotic limit. The other major implication of incorporation of stochasticity in the landfill evolution dynamics is in the hugely reduced production times of the plants that are now approximately 20–30 years instead of the previous deterministic model predictions of 50 years and above. The predictions from this stochastic model are in conformity with available experimental observations.     

A non-stationary periodic review production–inventory model with uncertain production capacity and uncertain demand

In this paper we consider a nonstationary periodic review dynamic production–inventory model with uncertain production capacity and uncertain demand. The maximum production capacity varies stochastically. It is known that order up-to (or base-stock, critical number) policies are optimal for both finite horizon problems and infinite horizon problems. We obtain upper and lower bounds of the optimal order up-to levels, and show that for an infinite horizon problem the upper and the lower bounds of the optimal order up-to levels for the finite horizon counterparts converge as the planning horizons considered get longer. Furthermore, under mild conditions the differences between the upper and the lower bounds converge exponentially to zero.     

EMISSION PERMITS UNDER MONOPOLY

This paper studies the regulation of pollution emissions when one polluting firm is a monopolist in its output market and other polluting firms are competitive in their output markets. It is shown that an emissions permit system can generally support a second-best allocation when the monopolistic firm has market power in the emission permit market. The second-best permit regulation specifies a permit endowment for the monopolist such that the monopolist is a net supplier of permits in the equilibrium. Extensions to cases of multiple monopoly, monopsony, and oligopoly are discussed.     

Dynamic investment strategies with demand-side and cost-side risks

Investments in cost reductions are critical for the long run success of companies that operate in dynamic and stochastic market environments. This paper studies optimal investment in cost reductions as a real option under the assumption that a single firm faces two different sources of risk, stochastic demand and input prices. We derive optimal investment strategies for a monopoly as well as a firm in a perfectly competitive market and show that in case of high marginal costs, cost reductions take place earlier in competitive than in monopoly markets. While the existence of an option to invest in cost reductions increases firm value it also increases a firm’s systematic risk. Risk can be smaller in a monopolistic than in a competitive industry.