Altruism in Networks

We provide the first analysis of altruism in networks. Agents are embedded in a fixed network and care about the well‐being of their network neighbors. Depending on incomes, they may provide financial support to their poorer friends. We study the Nash equilibria of the resulting game of transfers. We show that equilibria maximize a concave potential function. We establish existence, uniqueness of equilibrium consumption, and generic uniqueness of equilibrium transfers. We characterize the geometry of the network of transfers and highlight the key role played by transfer intermediaries. We then study comparative statics. A positive income shock to an individual benefits all. For small changes in incomes, agents in a component of the network of transfers act as if they were organized in an income‐pooling community. A decrease in income inequality or expansion of the altruism network may increase consumption inequality.     

Equilibria in Networks

We study a model in which two carriers choose networks to connect cities and compete for customers. We show that if carriers compete aggressively (e.g., Bertrand-like behavior), one carrier operating a single hub-spoke network is an equilibrium outcome. Competing hub-spoke networks are not an equilibrium outcome, although duopoly equilibria in nonhub networks can exist. If carriers do not compete aggressively, an equilibrium with competing hub-spoke networks exists as long as the number of cities is not too small. We provide conditions under which all equilibria consist of hub-spoke networks.     

网络图中多约束条件下的路径选择问题

本文探讨了多约束条件下的路径选择问题。本文的工作在于对多约束条件下的路径选择问题进行了规范的描述和分类,并针对各类问题讨论了典型的求解算法,同时对现有算法进行了改进,使其更适用于求解管理科学领域中的MCP问题,从而拓展了该问题的应用空间。     

面向相继故障的复杂网络上袭击策略研究

针对复杂网络遭遇随机故障和蓄意攻击引发的相继故障问题,采用网络中节点j上的初始负荷为Lj=βkjα(这里kj表示为节点j的度,α和β是可调参数),并基于崩溃节点负荷局域择优重新分配的原则,提出了一个带有可调参数的相继故障模型.通过度量网络鲁棒性的一个新的指标,即:关键阈值Tc,对比了两种袭击策略下网络上的全局相继故障现象.数值模拟得到了一些有趣而又违背直觉的结论:一方面,当模型中的可调参数α<1时,袭击网络中度最小的节点比袭击度最大的节点更易导致相继故障;而另一方面,当α=1时,两种袭击对网络的破坏几乎是相同的.此外,数值模拟结果也得到了理论解析的验证.     

Security Investment in Contagious Networks

Security of the systems is normally interdependent in such a way that security risks of one part affect other parts and threats spread through the vulnerable links in the network. So, the risks of the systems can be mitigated through investments in the security of interconnecting links. This article takes an innovative look at the problem of security investment of nodes on their vulnerable links in a given contagious network as a game‐theoretic model that can be applied to a variety of applications including information systems. In the proposed game model, each node computes its corresponding risk based on the value of its assets, vulnerabilities, and threats to determine the optimum level of security investments on its external links respecting its limited budget. Furthermore, direct and indirect nonlinear influences of a node's security investment on the risks of other nodes are considered. The existence and uniqueness of the game's Nash equilibrium in the proposed game are also proved. Further analysis of the model in a practical case revealed that taking advantage of the investment effects of other players, perfectly rational players (i.e., those who use the utility function of the proposed game model) make more cost‐effective decisions than selfish nonrational or semirational players.     

Novel Approaches for Analyzing Biological Networks

This paper proposes clique relaxations to identify clusters in biological networks. In particular, the maximum n-clique and maximum n-club problems on an arbitrary graph are introduced and their recognition versions are shown to be NP-complete. In addition, integer programming formulations are proposed and the results of sample numerical experiments performed on biological networks are reported.     

The Coexistence of Competition and Cooperation between Networks: Implications from Two Taiwanese Healthcare Networks*

The issue of coopetition, the coexistence of cooperation and competition, has recently come to the fore in the strategic management field. Previous coopetition research has focused on the intra‐organizational level, inter‐organizational level and triad level, but less attention has been paid to coopetition at the network level. The purpose of this paper is to address the coexistence of competition and cooperation between networks, and to depict how networks with different structures interact with each other. Drawing from a detailed case study of two healthcare networks in Taiwan, we demonstrate how they first initiated competition, followed by cooperation and then coopetition. From our analysis of this example of network coopetition, we develop three propositions that address the forces driving competition and cooperation and the different structures that allow competition and cooperation to coexist. We found that two organizations will compete and cooperate simultaneously when each organization has complementary but distinctly different sets of resources and when the field of competition is distinctly separate from the field of cooperation. In addition, two networks will find it easier to balance competition and cooperation when each network has compatible but distinctly different structures. We argue that the simultaneous existence of cooperation and competition is not dependent on closeness to the customer, as previously suggested in the literature, but on the balance between the forces for cooperation and for competition. We suggest from this research that networks can maintain the balance between competition and cooperation when they act using different structures. Finally, we discuss the implications of the value of competition and then coopetition at multiple levels of analysis and the implications for future research from a practical perspective.     

产业旁侧关联网络研究

研究主导部门在经济起飞中的作用时,罗斯托(Rostow)使用旁侧效应表示主导部门的变动所引起的周围一系列变化。由于缺乏可计算的方法,对旁侧效应的研究多为定性描述。本文在产业网络的基础上,根据旁侧效应的内涵提出协同型和竞争型旁侧关联的概念,构建了两类产业旁侧关联网络模型,进一步分析了四种旁侧效应。计算实例表明,产业旁侧关联网络可以描述产业部门之间的旁侧关联,表明活动过程中行为主体之间的关联关系和区域经济的结构特征,为分析旁侧效应提供了方法,也为研究关键产业、产业集群和制定区域非均衡发展战略等问题提供了定量化的依据。     

Two-Group Classification Using Neural Networks*

Artificial neural networks are new methods for classification. We investigate two important issues in building neural network models; network architecture and size of training samples. Experiments were designed and carried out on two-group classification problems to find answers to these model building questions. The first experiment deals with selection of architecture and sample size for different classification problems. Results show that choice of architecture and choice of sample size depend on the objective: to maximize the classification rate of training samples, or to maximize the generalizability of neural networks. The second experiment compares neural network models with classical models such as linear discriminant analysis and quadratic discriminant analysis, and nonparametric methods such as k-nearest-neighbor and linear programming. Results show that neural networks are comparable to, if not better than, these other methods in terms of classification rates in the training samples but not in the test samples.     

Leveraging Open Innovation Using Intermediary Networks

Open innovation, fuelled by the rise of the Internet, has made it feasible and cheaper for firms to open themselves up to a wide range of external sources of innovative ideas. The explosive growth of open innovation intermediary networks, such as InnoCentive or Linked‐in, enables the rapid pairing of firms seeking knowledge to address a wide range of business challenges (seekers) with other firms or individuals who already have relevant knowledge (solvers or knowledge brokers). These intermediary networks allow procurement departments to source codified and un‐codified knowledge from firms or individuals outside their traditional supplier networks using one‐off transactional relationships. Although sourcing ideas in this way theoretically poses problems for knowledge search and transfer, we have found that companies can draw on processes and integration mechanisms developed by procurement and design engineering to develop effective organizational learning routines. These routines are strategically vital to source new ideas through open innovation using intermediary networks and create competitive advantage.     

分布式创新中的知识网络构建

在回顾现有分布式创新概念的基础上,给出分布式创新的一般定义,并指出分布式创新知识网络的意义和网络构建障碍。依据管理支持和受益主体2个维度,划分出分布式知识网络的4种类型:个人爱好网络、专业学习网络、最佳实践网络和商机网络。基于对国内企业调研分析和国内外文献研究,提出构建分布式创新知识网络的4个重要阶段,即聚焦知识网络、创建网络背景关系、网络活动惯例化和利用网络成果。     

Domino Effect Analysis Using Bayesian Networks

A new methodology is introduced based on Bayesian network both to model domino effect propagation patterns and to estimate the domino effect probability at different levels. The flexible structure and the unique modeling techniques offered by Bayesian network make it possible to analyze domino effects through a probabilistic framework, considering synergistic effects, noisy probabilities, and common cause failures. Further, the uncertainties and the complex interactions among the domino effect components are captured using Bayesian network. The probabilities of events are updated in the light of new information, and the most probable path of the domino effect is determined on the basis of the new data gathered. This study shows how probability updating helps to update the domino effect model either qualitatively or quantitatively. The methodology is applied to a hypothetical example and also to an earlier‐studied case study. These examples accentuate the effectiveness of Bayesian network in modeling domino effects in processing facility.     

Maximizing Profits of Routing in WDM Networks

Let G = (V, E) be a ring (or chain) network representing an optical wavelength division multiplexing (WDM) network with k channels, where each edge e_j has an integer capacity c_j. A request s_i,t_i is a pair of two nodes in G. Given m requests s_i,t_i, i = 1, 2, ..., m, each with a profit value p_i, we would like to design/route a k-colorable set of paths for some (may not be all) of the m requests such that each edge e_j in G is used at most c_j times and the total profit of the set of designed paths is maximized. Here two paths cannot have the same color (channel) if they share some common edge(s).This problem arises in optical communication networks. In this paper, we present a polynomial-time algorithm to solve the problem when G is a chain. When G is a ring, however, the optimization problem is NP-hard (Wan and Liu, 1998), we present a 2-approximation algorithm based on our solution to the chain network. Similarly, some results in a bidirected chain and a bidirected ring are obtained.     

Scheduling in Switching Networks with Set-Up Delays

We consider the (preemptive bipartite scheduling problem PBS) (Crescenzi et al., On approximating a scheduling problem, Journal of Combinatorial Optimization, vol. 5, pp. 287–297, 2001) arising in switching communication systems, where each input and output port can be involved in at most one communication at the same time. Given a set of communication tasks to be communicated from the transmitters to the receivers of such a system, we aim to find a schedule minimizing the overall transmission time. To achieve this, we allow the preemption of communication tasks. However, in practice preemption comes with a cost, d, and this renders the problem NP-hard (Gopal et al., An optimal switching algorithm for multibeam satellite systems with variable bandwidth beams, IEEE Trans. Commun., vol.30, pp. 2475–2481, 1982). In this paper, we present a approximation algorithm, which is the first one for the PBS problem with approximation ratio strictly less than two. Furthermore, we propose a simple optimal polynomial time algorithm for a subclass of instances of the PBS problem.This work has been partially supported by the the European Union (FET-Working Group APPOL II), and the Greek General Secretariat of Research and Technology.     

Responsive Pricing Newsvendor Networks with Discretionary Commonality

Discretionary commonality is a form of operational flexibility used in multi‐product manufacturing environments. Consider a case where a firm produces and sells two products. Without discretionary commonality, each product is made through a unique combination of input and production capacity. With discretionary commonality, one of the inputs could be used for producing both products, and one of the production capacities could be used to process different inputs for producing one of the products. In the latter case, the manager can decide, upon the realization of uncertainty, not only the quantities for different products (outputs) but also the means of transforming inputs into outputs. The objective of this study is to understand how the firm's value, its inventory levels for inputs and capacity levels for resources are affected by the demand characteristics and market conditions. In pursuing this research, we extend Van Mieghem and Rudi ( 2002 )'s newsvendor network model to allow for the modeling of product interdependence, demand functions, random shocks, and firm's ex post pricing decision. Applying the general framework to the network with discretionary commonality, we discover that inventory and capacity management can be quite different compared to a network where commonality is non‐discretionary. Among other results, we find that as the degree of product substitution increases, the relative need for discretionary commonality increases; as the market correlation increases, while the firm's value may increase for complementary products, the discretionary common input decreases but the dedicated input increases. Numerical study shows that discretionary flexibility and responsive pricing are strategic substitutes.     

非正式创新网络结构仿真研究

非正式创新网络对于组织创新能力的提高具有重要意义,特别是我国社会具有充满"人情"味的特征,研究非正式创新网络更具有重要的现实意义.在对非正式创新网络的概念和研究现状进行分析梳理的基础之上,对非正式创新网络建立计算机仿真模型.初步研究了非正式创新网络的结构特征.发现非正式创新网络同时具有小世界以及无标度特性.     

金融网络的模型和优化

金融网络就是经济系统中资金循环,文献[1-8]研究了金融网络的模型。本文则在文献[1-8]金融网络模型的基础之上,建立了资产、负债、适度规模和价格的改进模型。这一改进模型考虑了所有经济部门的金融工具的风险、金融网络的经济资源约束、资产和负债的会计帐户约束等问题。模型的改进适用于应用。文章采用了进化规划算法,并依此进行仿真实验。     

Generalized Diameters and Rabin Numbers of Networks

Reliability and efficiency are important criteria in the design of interconnection networks. Recently, the w-wide diameter d_w(G), the (w – 1)-fault diameter D_w(G), and the w-Rabin number r_w(G) have been used to measure network reliability and efficiency. In this paper, we study d_w(G), D_w(G) and r_w(G) using the strong w-Rabin number r_w ^*(G) for 1 w k(G) and G is a circulant network G(d_n; {1, d,..., d^{n –1}}), a d-ary cube network C(d, n), a generalized hypercube GH(m_{n – 1},..., m0), a folded hypercube FH(n) or a WK-recursive network WK(d, t).     

基于交易量的供应链网络演化模型研究

将加权网络演化理论引入到供应链网络领域,在具体分析供应链网络动态演化特征、供应链网络演化影响因素和加权网络演化模型的基础上,提出了基于交易量的供应链网络演化模型,刻画了供应链网络形成和演化机理,为正确认识、管理、控制和协调供应链网络提供了新的思路,为进一步深化研究供应链网络弹性提供了理论基础.     

住房市场系统复杂网络模型研究

将系统科学和复杂网络理论相结合,建立了包含银行、房地产开发企业和购房消费者三级节点的住房市场系统复杂网络模型,刻画了住房市场系统的结构特性和动态演化特性,并通过模拟仿真上海住房市场交易变动情况,体现了住房市场的客观规律。研究提出的住房市场复杂网络模型为住房市场研究提供了新的方法,克服了以往研究模型由于数据的有限性所导致的、复杂系统过度线性化近似和动态性研究不足的问题,在此基础上开展实证研究具有重要现实意义。