Game analysis of technology innovation alliance stability based on knowledge transfer

Under incomplete information, a game model is used to investigate the influence of ownership level and learning ability on the stability of technology innovation alliance from the perspective of knowledge transfer. The decision-making processes of involved parties are divided into two stages in the model. In the first stage, the firm possessing advanced technology decides on the level of knowledge it transfers to its alliance partner. In the second stage, the decision of the parties on whether to maintain or terminate the alliance is based on two factors: the level of knowledge learned and profits gained. The outcomes of the Cournot–Nash equilibrium in the model can reveal when the parties decide to maintain or terminate the alliance. The model explores the status of alliance stability under different ownership levels and learning abilities to provide theoretical support for the selection of optimal dynamic competitive-cooperative relationship and managerial flexibility.     

The impact of product recall on advertising decisions and firm profit while envisioning crisis or being hazard myopic

The occurrence of a product recall can have a disastrous effect on the firm responsible for the recall. Any major recall by a firm can negatively affect the goodwill of the firm. Consequently, the firm incurs a substantial indirect cost due to decline in sales and loss in profit. Moreover, a competitor’s opportunistic reaction can intensify the recalling firm’s damages. Strategic use of advertising recovers lost goodwill and mitigates the damages made by a product recall. In this paper, using a goodwill based model under a differential game framework, we analyze the equilibrium strategies of two competing manufacturers when either one firm or both can issue a product recall at a random time, and investigate (i) the firms’ equilibrium advertising strategies (ii) analyze the impact of the recall on a firm’s profit (iii) introduce and investigate the effect of “hazard myopia” (a firm’s inability to foresee the crisis likelihood) on a firm’s advertising decisions and profit. Our study finds that the equilibrium advertising strategies of competing firms depend on the impact and likelihood of the recall. Notably, we find that when both the firms are focal firms without the prior knowledge of who will recall first in a planning horizon, adjusting optimal advertising at an appropriate time is essential. Surprisingly, a product-recall with a minor impact can increase the focal firm’s long-term expected profit. On the other hand, hazard myopia can be profitable if the long-term effect of the recall is small. Our findings suggest that advertising levels of firms should differ in pre-recall and post-recall regimes depending on the impact and likelihood of the recall.     

On the statistical origins of the learning curve

This paper presents a statistical rationale for the existence of the learning curve phenomenon. We consider a firm which allocates a fixed amount of input into several activities under uncertainty concerning the values of the parameters of the production function. It is shown, under fairly reasonable assumptions, that if the firm learns about the parameters of the production function from previous observations of allocations and outputs, then a learning curve phenomenon will emerge. This result occurs since the estimates of the parameters become more precise over time, and thus the allocation of the production factor into the various activities becomes more efficient (i.e. closer to the optimum allocation that would have been determined if the parameters were known with certainty). Output, therefore, increases and inputs per unit of output decrease as a function of time (and cumulative output), and a learning curve emerges.‘Plateauing’ of the learning curve is discussed, as are the conditions sufficient for the existence of this phenomenon, for which the model presented herein is offered as a possible explanation.     

Existence and uniqueness of optimal dynamic pricing and advertising controls without concavity

We consider a pricing and advertising dynamic-optimization problem where the goodwill dynamics evolve à la Nerlove–Arrow. The firm maximizes its profit over a finite-planning horizon corresponding to the product’s lifespan, and it turns out that the Hamiltonian is non-concave. We show the existence and uniqueness of an optimal solution under some mild conditions.     

市场机制和政府调控下产学研联盟稳定性研究

为了促进产学研联盟的稳定发展,针对我国产学研联盟短期化行为严重问题,基于演化博弈理论从市场机制和政府调控两方面构建企业和学研机构联盟行为选择的决策模型,以及通过复制动态方程对策略选择进行稳定性分析,同时运用Matlab 7.0软件模拟仿真在不同程度的市场机制和政府调控下企业和学研机构在联盟创新中的演化行为。通过市场机制和政府调控两方面的深入剖析,对我国产学研联盟的稳定发展具有重要的理论指导意义。     

突破性创新研发联盟最优伙伴组合方案研究

突破性创新研发联盟的研究已成为国内外学术界共同关注的重大课题,而伙伴选择是研发联盟中一个十分重要的问题,伙伴挑选的成功与否直接关系到研发联盟的合作效果和成败.在分析Bernardo方法缺陷的基础上,提出改进的Bernardo方法,进而建立具有资源约束的伙伴选择的改进Bernardo模型,并将其应用到突破性创新研发联盟最优伙伴的选择中,不仅可以求得资源约束下候选伙伴的优劣排序,还能求得参与研发联盟的最优伙伴数量和最优伙伴组合方案.     

Planning the supply of rewards with cooperative promotion considerations in coalition loyalty programmes management

Coalition loyalty programmes (CLPs) are owned and operated as for-profit enterprises. We consider the ordering decisions of rewards that arise in this context, under a general setting in which not only is the demand for rewards uncertain, but also the CLP firm offers bonus points, a very common cooperative promotion mechanism used in loyalty programmes. The rewards are acquired either at a wholesale ‘discounted’ cost or at a wholesale ‘non-discounted’ cost by the CLP firm from its multiple commercial partners and supplied to customers seeking to redeem their accumulated ‘reward points’, subject to commercial partners’ capacities for offering rewards, the firm’s overall budget for purchasing rewards, and its control policy on points liability. We formulate the problem as a stochastic linear programme with recourse and solve it using a sampling-based heuristic solution procedure previously discussed in the literature. We report on the managerial applicability of our model in dealing with the redemption budget spending resulting from changes in demand variability, changes in the redemption budget, and the control of liability levels within a reasonable range.     

On optimal bidding and inventory control in sequential procurement auctions: the multi period case

We consider the problem of a firm that in each cycle of a planning horizon builds inventory of identical items that it acquires by participating in auctions in order to satisfy its own market demand. The firm’s objective is to have a procurement strategy that maximizes the expected present value of the profit for an infinite planning horizon of identical cycles. We formulate this problem as a Markov decision process. We establish monotonicity properties of the value function and of the optimal bidding rule.     

Dynamic switching times from season to single tickets in sports and entertainment

Revenue management can be used in many industries where there is a limited, perishable capacity and the market can be segmented. In this paper we focus on the sales of event tickets in the Sports and Entertainment industries, where tickets are sold exclusively as season tickets initially or as single events later in the selling horizon. We specifically study the optimal time to switch between these market segments dynamically as a function of the state of the system. Under Poisson demand processes, we find the optimal switching time is a set of time thresholds that depends on the remaining inventory and time left in the horizon. We use numerical experiments to show that significant profit improvements can be obtained by dynamically deciding the optimal switch time over the case when the date is announced in advance. We also study an extension where ??early switch to a low-demand event?? is allowed.     

Optimal pricing and inventory policies with reliable and random-yield suppliers: characterization and comparison

In this paper, we study the joint pricing and inventory replenishment problem for a periodic-review inventory system with random demand and dual suppliers, one of the suppliers is reliable but more expensive, the other supplier is less expensive but is unreliable with random yield. We characterize the firm’s optimal policies that simultaneously determine the optimal ordering and pricing decisions in each period over a finite planning horizon, and investigate the impacts of supply source diversification and supplier reliability on the firm and on its customers. We show that having source diversification or higher reliability of suppliers not only increases the firm’s expected profit, but also results in a lower optimal selling price, thus they benefit both the firm and its customers.     

Using an Iterated Prisoner's Dilemma with Exit Option to Study Alliance Behavior: Results of a Tournament and Simulation

Nearly half of all strategic alliances fail (Park and Russo, 1996; Dyer et al., 2001), often because of opportunistic behavior by one party or the other. We use a tournament and simulation to study strategies in an iterated prisoner's dilemma game with exit option to shed light on how a firm should react to an opportunistic partner. Our results indicate that a firm should give an alliance partner a second chance following an opportunistic act but that subsequent behavior should be contingent on the value of the next best opportunity outside the alliance. Firms should be more forgiving if the potential benefits from the alliance exceed other opportunities. The strategies were also found to be robust across a wide range of game lengths. The implications of these results for alliance strategies are discussed. Steven E. Phelan received his PhD in economics from La Trobe University (Australia) in 1998. Following five years at the University of Texas at Dallas, he joined the faculty of the University of Nevada Las Vegas in 2003. Dr. Phelan's research interests include competitive dynamics, organizational efficiency, acquisition and alliance performance, and entrepreneurial competence. His methods of choice to study these phenomena include agent-based modelling, experimental game theory, and event studies. Prior to joining academia, Dr. Phelan held executive positions in the telecommunications and airline industries and was a principal partner in Bridges Management Group, a consultancy specializing in strategic investment decisions. Richard J. Arend is a graduate of the University of British Columbia's doctoral program in Policy Analysis and Strategy. He is on the Management faculty of the University of Nevada, Las Vegas, arriving most recently from the Management faculty of New York University's Stern School of Business. Dr. Arend's interests lie in the analysis of unusual modes of firm value creation and destruction, where he has published in several top journals. He is a professional engineer with work and consulting experience in aerospace and computing. Darryl A. Seale joined the faculty of UNLV in 1999, following three years at Kent State University and the University of Alabama in Huntsville. Prior to Alabama, he completed his Ph.D. and M.S. degrees in Business Administration at the University of Arizona, his M.B.A. from Penn State University, and spent over ten years in management and market planning positions in the health care industry. Professor Seale's research interests include strategic decision making, bargaining and negotiation, and behavioral game theory. His research has been funded by the National Science Foundation and has been published in top-tier journals including Management Science, OBHDP, Games and Economic Behavior, and Strategic Management Journal. His teaching interests include business policy/strategy, managerial decision making, and bargaining and negotiation.     

Continuous learning methods in two-buyer pricing problem

This paper presents continuous learning methods in a monopoly pricing problem where the firm has uncertainty about the buyers’ preferences. The firm designs a menu of quality-price bundles and adjusts them using only local information about the buyers’ preferences. The learning methods define different paths, and we compare how much profit the firm makes on these paths, how long it takes to learn the optimal tariff, and how the buyers’ utilities change during the learning period. We also present a way to compute the optimal path in terms of discounted profit with dynamic programming and complete information. Numerical examples show that the optimal path may involve jumps where the buyer types switch from one bundle to another, and this is a property which is difficult to include in the learning methods. The learning methods have, however, the benefit that they can be generalized to pricing problems with many buyers types and qualities.     

超竞争环境下企业困境并购定价与时机选择的期权博弈分析

基于期权博弈理论,以超竞争环境为研究背景,在多个主并企业合作的情形下,建立目标企业存在财务困境的并购模型,得出主并方的最优并购时机;并进行数值模拟分析,重点分析了代表超竞争特点的三个变量(竞争强度、竞争不确定性、企业价值损失因子)、主并企业联盟中参与者的重要程度及联盟中发生机会主义的概率、企业困境因子这六个变量对并购阈值的影响。     

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.     

Choosing best alliance partners and allocating optimal alliance resources using the fuzzy multi-objective dummy programming model

Synergy effects are the motives to enter into strategic alliances; however due to lack of adequate preparation or planning, these alliances often fail. It is of no doubt that a successful strategic alliance depends on choosing the correct alliance partners and appropriate resource allocation. In this paper, the fuzzy multi-objective dummy programming model is proposed to overcome the above-mentioned problems. Two types of strategic alliances, joint ventures and mergers and acquisitions (M&A), are demonstrated to choose the best alliance partners and allocate the optimal alliance resources in a numerical example. Based on the results, our method can provide the optimal alliance cluster and satisfaction in strategic alliances.     

Forecast Accuracy: The Financial Benefits to a Small Airline

This paper assesses possible gains to be made from increasing forecast accuracy. It examines the financial return from improving passenger revenue forecasts for a small airline, both in theory assuming ‘optimal’ cash management and in practice using policies currently in operation in the firm. It concludes that the gains are unlikely to outweigh the costs, that greater returns are likely to be available through better cash management and that the nature of forecast errors must be considered along with their size.     

A process of students and their instructor developing a final closed-book mathematics exam

This article describes a study, from a Canadian technical institute's upgrading mathematics course, where students played a role in developing the final closed-book exam that they sat. The study involved a process where students developed practice exams and solutions keys, students sat each other's practice exams, students evaluated classmates' solutions to the practice exams, and finally the instructor used questions from the practice exams to develop the ‘live’ final exam. Phenomenography is used to analyse interview data and report students' experiences. Through the results, claims are made that students experienced deep approaches to learning and worked as partners in learning, teaching and assessment during the process of developing the final exam with their instructor.     

服务水平约束下动态定价与库存管理

本文研究服务水平约束下的动态定价与库存管理问题。企业在有限期内销售某种产品,产品的需求为随机需求,且期望需求依赖于产品价格。在每一期期初,企业需要在满足服务水平约束的条件下同时决定订货量和产品价格。本文首先构建了动态定价和订购联合决策的随机动态规划模型,并证明了最优解的存在性。进一步,通过对最优解的结构进行刻画,将原问题的求解转化为若干子问题的求解,降低了问题求解的难度。通过对最优解的分析发现,当期初库存增大时,产品最优价格降低。通过分析目标服务水平对利润的影响,证明了服务水平与利润之间存在权衡,实现高的服务水平需要承受利润损失。数值模拟表明,相对于传统的静态定价策略,采用动态定价策略可以降低追求服务水平所带来的利润损失,验证了动态定价策略的有效性。     

Optimal gainshare/painshare in alliance projects

Alliances are popularly used in delivering infrastructure. However, discussion is ongoing as to what is the optimal gainshare/painshare arrangement. This paper derives a result for the optimal gainshare/painshare between risk-averse parties, where the level of aversion may range from very large to being risk neutral. The derivation is based on solving an optimization problem using concepts from agency theory. The influence of the parties’ level of risk aversion and outcome uncertainty is examined. Practitioners were engaged in a designed exercise in order to validate the approach and propositions. The paper shows that: (i) the optimal gainshare/painshare arrangement in alliances is linear in the project outcome; (ii) the optimal gain/pain share to the contractor should decrease with increasing contractor level of risk aversion and/or decreasing owner level of risk aversion; and (iii) the outcome uncertainty has no influence on the optimal gainshare/painshare. The paper provides those who write alliance contracts with recommendations on gainshare/painshare. This study casts new light on establishing optimal alliance arrangements in the construction industry.