An analysis of interorganizational resource sharing decisions in collaborative knowledge creation

Collaborative relationships between organizations for knowledge creation have received considerable attention in recent literature. For any collaborative endeavor to succeed, adequate allocation and sharing of resources is important. We explored the conditions of resource sharing in which organizations are motivated to collaborate for knowledge creation, as well as the conditions required for the collaboration to continue. Using the game theoretic framework, we modeled the collaboration for knowledge creation as a Stackelberg leader–follower game. Specifically, we modeled two scenarios, the first in which organizations expend current efforts only, and the second in which organizations have made relevant prior efforts. The equilibrium values of current efforts in knowledge creation, the leader organization’s resource participation rate, and the total expected system gain in both of these scenarios were determined. Both within scenario and cross-scenario analyses were conducted. It is important to maintain an optimal ratio between the leader’s and follower’s marginal gains for the formation and continuation of the collaboration.     

智能家居创意空间系统知识协同行为的博弈分析

为明确智能家居创意空间系统知识协同行为实质,在研究其知识协同网络构成的基础上,考虑不同主体间协同行为的无限次重复博弈,构建知识协同行为的一般博弈模型,并利用演化博弈理论分别建立对称与非对称合作博弈模型,对系统中知识协同行为的演化过程进一步分析。研究表明,该系统运营知识资源的能力、激励强度以及协同主体知识协同运作获得的附加利益、合作次数是影响知识协同行为的关键因素;知识协同带来的纯收益与付出的初始成本是影响知识协同行为演化的重要参数。     

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 bargaining and leader–follower models in water allocation: Application to the Zarrinehrud River basin,Iran

Mathematical models for conflict resolution are very important in integrated water resources and environmental management. This study proposes a new methodology to resolve conflicts among different water users and water suppliers while considering environmental requirements and the system’s constraints. A two-level leader–follower model is applied to maximize the net benefit with the Iran Water Resources Management Company as the leader and agricultural, domestic, and industrial users as followers subject to the system’s constraints. As a comparison, the Nash bargaining solution is also used to find a solution when simultaneous moves are assumed by the participants. The suggested method is then applied to the real case of the Zarrinehrud River basin that is one of the areas facing water shortages in Iran. For the actual optimization, Genetic Algorithm is used in order to avoid local optimum. As the contribution of this study, the results show that benefits for the leader in the leader–follower model increased in comparison with the Nash bargaining solutions.     

A two-level evolutionary algorithm for solving the facility location and design (1|1)-centroid problem on the plane with variable demand

In this work, the problem of a company or chain (the leader) that considers the reaction of a competitor chain (the follower) is studied. In particular, the leader wants to set up a single new facility in a planar market where similar facilities of the follower, and possibly of its own chain, are already present. The follower will react by locating another single facility after the leader locates its own facility. Both the location and the quality (representing design, quality of products, prices, etc.) of the new leader’s facility have to be found. The aim is to maximize the profit obtained by the leader considering the future follower’s entry. The demand is supposed to be concentrated at n demand points. Each demand point splits its buying power among the facilities proportionally to the attraction it feels for them. The attraction of a demand point for a facility depends on both the location and the quality of the facility. Usually, the demand is considered in the literature to be fixed or constant regardless the conditions of the market. In this paper, the demand varies depending on the attraction for the facilities. Taking variable demand into consideration makes the model more realistic. However, it increases the complexity of the problem and, therefore, the computational effort needed to solve it. Three heuristic methods are proposed to cope with this hard-to-solve global optimization problem, namely, a grid search procedure, a multistart algorithm and a two-level evolutionary algorithm. The computational studies show that the evolutionary algorithm is both the most robust algorithm and the one that provides the best results.     

竞争性企业技术联盟的知识共享效应研究

通过三阶段博弈模型分析竞争性企业技术联盟知识共享效应,结果表明:知识共享的程度是随着竞争性企业技术联盟规模的扩大而增加的.因为随着技术联盟规模的扩大,知识共享的规模收益会逐渐上升,从而减少了由于知识溢出而带来的损失.因此,在企业技术联盟内部构建一个能够有效地吸收、保持和共享知识的机制对于提高技术联盟的绩效具有积极的作用.     

Innovation and learning performance implications of free revealing and knowledge brokering in competing communities: insights from the Netflix Prize challenge

Firms increasingly use open competitions to extend their innovation process and access new diverse knowledge. The Netflix Prize case we study in this paper is a multi-stage repeat-submission open competition involving the creation of new knowledge from across knowledge domains, a process which benefits from knowledge sharing across competing communities. The extant literature says little about the effects of different types and levels of knowledge sharing behavior on the learning and innovation outcomes of such a competitive system, or what the performance boundaries may be for the system as a result of such differences. Our research explores those boundaries unveiling important tradeoffs involving free revealing behavior—defined as voluntarily giving away codified knowledge and making it into a ‘public good’—and knowledge brokering behavior—defined as using knowledge from one domain to innovate in another—on the learning performance of competing communities. The results, analyzing the system-level average and volatility of learning outcomes, lead to three conclusions: (i) greater knowledge sharing, as portrayed by greater free revealing and knowledge brokering, helps achieve better average learning for the system as a whole, however, (ii) achieving the best overall outcome possible from the system actually requires controlling the amount of knowledge brokering activity in the system. The results further suggest that (iii) it should not be possible to simultaneously achieve both the best overall outcome from the system and the best average learning for the system. The tradeoffs that ensue from these findings have important implications for innovation policy and management. This research contributes to practice by showing how it is possible to achieve different learning performance outcomes by managing the types and levels of knowledge sharing in open competitive systems.     

基于动机的联合风险投资收益分配契约设计(A2016-0158)

从联合风险投资的领导者采取联合投资的动机出发,考虑分配给跟随者的收益份额是否能达到目的,运用优化理论建立了联合投资双方的收益分配模型,提出了联合风险投资机构之间的收益分配契约设计的一种可供参考的方法,并用实例说明了模型方法的应用。研究还表明,潜在的市场竞争可能对领导者造成的损失越大,领导者越愿意给予跟随者更多的收益份额;当项目质量信息的不确定性越高,单独投资将存在较大风险的时候,为了获得项目质量信息的补充,也使得领导者愿意给予跟随者更多的收益份额。     

预期更新技术出现时新技术采用中经营成本对投资策略的影响

The adoption of new technologies often represents acrucial component of firms' investment decisions.This paper studies a dynamic duopoly model in which two firms compete in adoption of current technology with afurther new technology anticipated.Here it is assumed that the operating costs are not zero which has more explanatory power of the real world.There exist three kinds of equilibria that may occur in adoption of current technology,which mainly depends on the level of operating costs and the first-move advantage.It shows that the faster technological substitution or innovation encourages the leader to invest earlier while induces the follower to invest later.Furthermore,like the investment costs,with the increase of operating costs the follower tends to invest later while the leader tends to invest earlier,the investment thresholds are more sensitive to the change of operating costs than that of investment costs.     

IMPACT OF OPERATING COSTS ON INVESTMENT STRATEGIES IN NEW TECHNOLOGY ADOPTION WITH A FURTHER NEW TECHNOLOGY ANTICIPATED

The adoption of new technologies often represents a crucial component of firms＇ investment decisions. This paper studies a dynamic duopoly model in which two firms compete in adoption of current technology with a further new technology anticipated. Here it is assumed that the operating costs are not zero which has more explanatory power of the real world. There exist three kinds of equilibria that may occur in adoption of current technology, which mainly depends on the level of operating costs and the first-move advantage. It shows that the faster technological substitution or innovation encourages the leader to invest earlier while induces the follower to invest later. Furthermore,like the investment costs,with the increase of operating costs the follower tends to invest later while the leader tends to invest earlier ,the investment thresholds are more sensitive to the change of operating costs than that of investment costs.     

Controlled predatory pricing in a multiperiod Stackelberg game: an MPEC approach

We analyze a multiperiod oligopolistic market where each period is a Stackelberg game between a leader firm and multiple follower firms. The leader chooses his production level first, taking into account the reaction of the followers. Then, the follower firms decide their production levels after observing the leader’s decision. The difference between the proposed model and other models discussed in literature is that the leader firm has the power to force the follower firms out of business by preventing them from achieving a target sales level in a given time period. The leader firm has an incentive to lower the market prices possibly lower than the Stackelberg equilibrium in order to push the followers to sell less and eventually go out of business. Intentionally lowering the market prices to force competitors to fail is known as predatory pricing, and is illegal under antitrust laws since it negatively affects consumer welfare. In this work, we show that there exists a predatory pricing strategy where the market price is above the average cost and consumer welfare is preserved. We develop a mixed integer nonlinear problem (MINLP) that models the multiperiod Stackelberg game. The MINLP problem is transformed to a mixed integer linear problem (MILP) by using binary variables and piecewise linearization. A cutting plane algorithm is used to solve the resulting MILP. The results show that firms can engage in predatory pricing even if the average market price is forced to remain higher than the average cost. Furthermore, we show that in order to protect the consumers, antitrust laws can control predatory pricing by setting rules on consumer welfare.     

A Stackelberg equilibrium for a missile procurement problem

This paper deals with a procurement problem of missiles involving the efficient assignment of the missiles to some targets. Within a fixed amount of budget, a leader purchases several types of missiles, by which he aims to damage as much value as possible a follower hides into some facilities later. The effectiveness of the missile depends on the type of missile and facility. A payoff of the game is the expected amount of destroyed value. The problem is generalized as a two-person zero-sum game of distributing discrete resources with a leader and a follower. Our problem is to derive a Stackelberg equilibrium for the game. This type of game has an abundance of applications. The problem is first formulated into an integer programming problem with a non-separable objective function of variables and it is further equivalently transformed into a maximin integer knapsack problem. We propose three exacts methods and an approximation method for an optimal solution.     

协同创新视角下产学研合作行为决策机制研究

产学研合作是科技与经济结合的有效形式,协同创新理论对产学研合作提出了更高的要求。从协同创新视角出发,利用基于有限理性的演化博弈理论构建了企业与学研机构间的协同合作决策博弈模型,并对策略选择进行稳定性分析。理论研究和数值仿真结果表明:当企业和学研机构在协同合作中获得的经济收益净值大于其选择中途放弃获得的经济收益时,双方才会全部选择协同合作策略;产学研协同合作总收益、收益分配系数、赔偿系数和协同合作成本对企业和学研机构的决策结果有显著的影响,但作用机制有所不同;政府对产学研协同合作的资助和惩罚机制对企业和学研机构选择协同合作策略有促进的作用,但应将资助和惩罚力度控制在一定范围内发挥其最大激励效用。     

Mesoscopic supply chain simulation

This paper reviews and compares existing approaches for supply chain modeling and simulation and applies the mesoscopic modeling and simulation approach using the simulation software MesoSim, an own development. A simplified real-world supply chain example is modeled with discrete event, mesoscopic and system dynamics simulation. The objective of the study is to compare the process of model creation and its validity using each approach. The study examines advantages of the mesoscopic approach for the simulation. Major benefits of the mesoscopic approach are that modeling efforts are balanced with the necessary level of detail and facilitate quick and simple model creation and simulation.     

Empirically assessing and modeling spillover effects from operational risk events in the insurance industry

The aim of this paper is to propose the first mathematical model for spillover effects caused by operational losses and to calibrate it based on an extensive empirical study of spillover effects and their influencing factors in the US and European banking and insurance industry. Our event study shows significant spillover effects due to operational losses, whereby a higher number of firms faces contagion effects than competitive effects. A regression analysis further reveals that spillover effects are rather information-based than pure, as event and firm characteristics have a significant impact, specifically external fraud, the return on equity of the announcing firm and the similarity between the announcing and the non-announcing firm in terms of size. Based on the empirical findings, we fit a distribution and model spillover effects and underlying operational losses to assess respective risk measures by means of a simulation analysis. The results show that spillover risk can be considerable for non-announcing firms as well as from a portfolio view, which has important risk management implications.     

Estimating parameters of proportional hazards model based on expert knowledge and statistical data

Proportional hazards model (PHM) is a convenient statistical tool that can be successfully applied in industrial problems, such as in accelerated life testing and condition-based maintenance, or in biomedical sciences. Estimation of PHM requires lifetime data, as well as condition monitoring data, which often is incomplete or missing, and necessitates the use of expert knowledge to compensate for it. This paper describes the methodology for elicitation of expert's beliefs and experience necessary to estimate the parameters of a PHM with time-dependent covariates. The paper gives a background of PHM and review of the literature related to the knowledge elicitation problem and gives a foundation for the proposed methodology. The knowledge elicitation process is based on case analyses and comparisons. This method results in a set of inequalities, which in turn define a feasible space for the parameters of the PHM. By sampling from the feasible space an empirical prior distribution of the parameters can be estimated. Then, using Bayes rule and statistical data the posterior distribution can be obtained. This technique can also provide reliable outcomes when no statistical data are available. The technique has been tested several times in laboratory experiments and in a real industrial case and has shown promising results.     

基于QoS协同关联的改进Skyline制造服务组合优化方法

服务社会网络环境下,云制造服务通过与其他参与同一任务的服务共享与竞争物理设备、信息、知识等资源形成协同效应,对双方实际执行效果具有重要影响,导致出现QoS偏离现象,现有服务选择模型难以适应这一情景。根据服务协同网络特点,本文提出基于QoS协同关联的制造服务组合方法。运用QoS协同关联和协同系数表达资源共享、冲突对QoS的影响程度,构建了新的服务选择优化模型。基于创新Skyline服务对概念,改善了Skyline算法在QoS协同关联条件下的搜索效率和结果,通过智能汽车制造仿真实验,验证了本文模型和算法的有效性。     

多阶段并发的协同物流网络任务-资源集成调配模型

协同物流网络作为动态开放的网络需要整合多种资源,以完成多项并行的物流任务。为此,本文从物流服务集成商的角度,研究了带时间窗和资源约束的任务—资源集成调配问题。通过将物流任务分解为不同阶段,构造多阶段并发的协同物流网络任务—资源集成调配模型,并采用遗传算法对模型进行求解,以从候选资源集合中为任务阶段匹配合适的资源。算例结果表明,该模型能够有效实现N-N的任务-资源集成调配,使得协同物流网络的整体效益达到最优。     

市场导向、多主体协同与创新扩散:基于复杂网络的动态仿真

市场导向与多主体协同关系密切,是提升创新扩散效率的主要驱动要素。本文首先从协同关系和创新收益两个层面,构建空间结构和有效预期的演化机制,生成复杂网络模型,对多主体协同的创新扩散过程进行动态仿真。其次通过细化市场导向理论在用户需求、竞争驱动和职能协同等不同维度的作用路径,深入分析了市场导向对多主体协同的影响机制。研究表明:(1)市场导向对多主体协同的影响与网络结构动态特征具有高度相关性;(2)少量的用户需求与竞争驱动导向对多主体协同的效益提升最为显著,职能协同导向的影响则呈现周期性“倒U型”波动特征;(3)用户需求导向对多主体协同的创新收益驱动效应最明显,竞争驱动导向的推动效果次之。     

Stackelberg博弈均衡点的存在性及通有存在性

针对具有一个领导者和一个跟随者的Stackelberg博弈模型,考虑两种情况:(i)没有凸性条件；(ii)没有凸性条件且减弱连续性.并利用非线性分析方法,证明了在这两种情况下的Stackelberg博弈均衡点的存在性及通有存在性的结论,这些结论改进了Basar T,Olsder G J的结论[1].