网络博弈视角下的中国汽车企业对抗互动研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
多市场接触和策略互动是现代企业竞争的两大突出特点。在多市场接触明显的产业里,企业之间的竞争可以被视为是嵌入在以市场接触为纽带的企业网络上的对抗互动过程。因此,很有必要从企业网络和策略互动的角度来研究企业之间的竞争。本文运用网络博弈理论,结合复杂网络分析方法,对中国汽车企业的对抗互动做了细致而深入的理论研究。
     首先,建立了企业对抗互动的网络博弈分析框架和模型:(1)构建了一般性的企业对抗互动无限重复博弈网络模型。(2)从多个视角定义了博弈中的企业策略,包括触发策略如针锋相对策略和冷酷策略等,非一致性和一致性策略,以及察觉-动机-能力视角下的随机惩罚触发策略。(3)以产品差异化的古诺模型为基础,建立了三个具有明确产业含义的企业对抗互动无限重复网络博弈模型,它们分别是价格战网络博弈模型、品牌竞争网络博弈模型和产能扩张竞争网络博弈模型。
     接下来,利用价格战、品牌竞争和产能扩张竞争的网络博弈模型对中国汽车企业的对抗互动展开理论分析。先是利用2000年到2006年的产品产量数据,每年建立一个企业-产品加权二分网络,并依据这7个二分网络设计了上述三类企业对抗互动的仿真模型,具体工作包括:估计产品市场规模和企业生产成本,设定仿真参数、控制变量、初始状态、仿真过程和输出变量。然后进行仿真并对仿真结果进行分析,总结中国汽车企业对抗互动的特点,得到以下主要发现:(1)企业采取一致性策略能够有效抑制品牌竞争的发生,同时会促进价格战和品牌竞争的扩散,但对价格战的发生以及产能扩张竞争的发生和扩散没有明显的影响。(2)企业对反击的预期的提高,能够显著地抑制价格战和产能扩张竞争的发生,但对品牌竞争的发生和三种对抗互动的扩散没有明显的影响。(3)不同年份的企业-产品二分网络对品牌竞争的影响非常大,对价格战也有一定的影响,对产能扩张竞争的影响却很小。
     最后,研究了企业-产品二分网络的拓扑结构对中国汽车企业价格战和品牌竞争的影响,得到如下发现:(1)一个企业在价格战中发动对抗行动的倾向,与它的平均最短路和聚集系数呈负相关关系,但与它的节点权没有明显的相关关系;不同地,一个企业在品牌竞争中发动对抗行动的倾向,与它的节点权和聚集系数呈正相关关系,但与它的平均最短路呈负相关关系。(2)从2000年到2006年,企业-产品二分网络的平均最短路越来越小,聚集系数越来越大,节点权分布的幂指数越来越小。上述的拓扑指标变化规律,很好地解释了中国汽车企业对抗互动的演变特点。(3)汽车企业-产品二分网络具有明显的社团结构,并且企业对抗互动主要发生在网络社团的内部,有时也会在联系比较密切的社团之间互相扩散。
     本文的创新主要体现四个方面。第一,运用网络博弈理论研究企业对抗互动,提出了基于企业-市场二分网络的无限重复网络博弈一般性模型和分析框架,为企业对抗互动提供了新视角和新思路。第二,引入产品差异化的古诺竞争模型建立价格战、品牌竞争和产能扩张竞争的网络博弈模型,为这三类企业对抗互动提供了很好的理论分析工具。第三,将复杂网络分析和网络博弈仿真结合起来探讨网络拓扑结构对企业对抗互动的影响,是一个较成功的尝试,为同类研究提供了较好的方法论借鉴和参考。第四,揭示了中国汽车企业价格战、品牌竞争和产能扩张竞争的对抗互动特点及其演变规律,有助于增进人们对中国汽车企业对抗互动的理解。
Multi-market contact and strategy interaction are two prominent characteristics of competition between modern firms. In an industry with obvious multi-market contact, the competition between firms can be viewed as a process of inter-firm rivalry on the firm network linked by market contact. Hence it is of necessity to study the competition between firms from the perspective of firm network and of strategy interaction. The present paper tries to offer a meticulous and profound theoretical analysis on the inter-firm rivalry in China automobile industry by applying the network game theory and incorporating complex network analysis method.
     The paper begins with the construction of a grneral network game analysis framework and some specific models of inter-firm rivalry: (1) constructing a general infinite repeated network game model for inter-firm rivalry; (2) defining from multiple perspectives the strategies of firms in the game, including trigger strategy (such as tit-for-tat and grim strategy), inconsistent and consistent strategy, and random punishment trigger strategy from the perspective of Awareness-Motivation-Capability; (3) constructing three infinite repeated network game model with specifically-defined rivalry action for the inter-firm rivalry based on differentiated product Cournot model, namely: price war network game model, brand competition network game model and capacity expansion competition network game model.
     Then, the paper carry out a theoretical analysis of inter-firm rivalry between China automobile firms based on the price war, brand competition and capacity expansion competition network game model. Initially, 7 firm-product weighted bipartite networks are constructed, in which the edge weight are the corresponding annual output from 2000 to 2006, respectively. Thereafter, simulation models of inter-firm rivalry according to the bipartite networks above are designed, including estimatation of product market size, production cost of firms and setting of simulation parameter, control variables, initial state, simulation proccess and output variables. The analysis of simulation results show that: (1) the consistent strategies can effectively inhibit the occurrence of brand competition but will enhance the diffusion of price war and of brand competition; whereas they have no significant impact on the occurrence of price war or on the occurrence and diffusion of capacity expansion competition; (2) the enhancement of enterprises’expectation for counterattack can effectively inhibit the occurrence of price war and capacity expansion competition, but has no significant impact on the occurrence of brand competition or the diffusion of all categories of inter-firm rivalry; (3) firm-product bipartite network exerts a tremendous impact on brand competition, whereas the impact is moderate on price war and insignificant on capacity expansion competition.
     Finally, The paper anylyzes the relationship between the topology structure of firm-product bipartite networks and the price war and brand competition of China automobile firms, while reveals the following discoveries: (1) the tendency of firms in launching rivalry action in price wars is in negative correlation with its average shortest path and clustering coefficient but not significantly related to its node weight. In contrast, the tendency of firms to initiate rivalry action in brand competition is in positive correlation with its node weight and clustering coefficient but in negative correlation with its average shortest path. (2) From 2000 to 2006, the average shortest path of firm-product bipartite network is increasingly smaller and the clustering coefficient is getting larger whereas the power exponent of node weight distribution is getting smaller. Such variation of the typology indexes offers a reasonable explanation for the evolutionary features of China automobile firms in real-life inter-firm rivalry. (3) Firm-product bipartite networks in the Chinese automobile industry has distinct community structure whereas the inter-firm rivalry of enterprises mainly takes place inside network community, but also spreads among closely interconnected communities.
     The innovation of the present paper is chiefly embodied in the following aspects: (1) it applies the network game theory to study the inter-firm rivalry to put forward a general model and analysis framework of infinite repeated network game based on firm-product bipartite network, which offers a new perspective and new idea for the research of inter-firm rivalry. (2) It introduces Cournot competition model of production differentiation to construct a network game model of price war, brand competition and capacity expansion competition, thus offering an effective tool of theoretical analysis on inter-firm rivalry. (3) it discusses the impact of network typology on inter-firm rivalry by combining complex network analysis and network game simulation; this has been a successful attempt which will in turn provides methodological reference for similar research. (4) it reveals the features and evolutionary features of inter-firm rivalry of China automobile firms in price war, brand competition and capacity expansion competition, hence facilitating our understanding of the inter-firm rivalry between China automobile firms.
引文
[1] Abramson G., Kuperman M. Social games in a social network[J]. Phys. Rev. E, 2001, 63: 030901.
    [2] Albert R., Barabási A.L. Statistical mechanics of complex networks[J]. Rev. Mod. Phys. 2002, 74: 47-97.
    [3] Almaas E., Kovacs B., Vicsek T., et al. Global organization of metabolic fluxes in the bacterium Escherichia coli[J]. Nature 2004, 427: 839-843.
    [4] Ballester, C., Calvo-Armengol, A., Zenou, Y. Who's who in networks wanted: the key player [J]. Econometrica, 2006, 74(5): 1403-1417.
    [5] Barabási A. L., Albert R. Emergence of scaling in random networks[J]. Science. 1999, 286: 509-512.
    [6] Baranes, E., Mirabel, F., Poudou, J.C. Collusion sustainability with multimarket contacts: revisiting HHI tests [A], working paper, 2009.
    [7] Barber, M. J. Modularity and community detection in bipartite networks [J]. Physical Review E, 2007, 76: 066102.
    [8] Barnett, Steven, W. Benefit-Cost Analysis of Preschool Education: Findings from a 25-Year Follow-Up[J]. American Journal of Orthopsychiatry, 1993, 63(4): 500-508.
    [9] Barrai A., Barthelemy M., Vespignani A. Weighted evolving networks: coupling topology and weight dynamics[J]. Phys. Rev. Letts. 2004, 92: 228701
    [10] Baum J.A.C., Korn H.J. Dynamics of dyadic competitive interaction[J]. Strategic Management Journal, 1999, 20: 251–278.
    [11] Baum, A.C., Korn, H.J. Competitive Dynamics of Interfirm Rivalry [J]. The Academy of Management Journal, 1996, 39(2): 255-291
    [12] Belleflamme, P., Bloch, F. Sustainable collusion on separate markets[J]. Economics Letters, 2008, 99: 384-386.
    [13] Bernheim B.D., Whinston M.D. Multimarket contact and collusive behavior [J]. RAND Journal of Economics, 1990, 21(1): 1-26.
    [14] Bertrand, J. Révue de la Théorie Mathématique de la Richesse Sociate et des Recherchessur les Principles Mathématiques de ta Théorie des Richesses. Journat des Savants, 1883: 499-508.
    [15] Boeker W., Goodstein, J., Stephan, J., et al. Competition in a Multimarket Environment: The Case of Market Exit[J]. Organization Science, 1997, 8(2): 126-142.
    [16] Boulding, W., Christen, M. Idea—First-mover disadvantage[J]. Harvard Business Review, 2001, 79(9): 20–21.
    [17] Bowley, A. The mathematical groundwork of economics[M]. Oxford University Press, Oxford, 1924.
    [18] Bramoulle, Y., Kranton R. Public Goods in Networks [J]. Journal of Economic Theroy, 2007, 135: 478-494.
    [19] Carayol, N; and Roux, P. Self-organizing innovation networks: when do small worlds emerge? [J]. European Journal of Economic and Social Systems, 2005, 18(2): 307-332.
    [20] Caves, R. E. Economic analysis and the quest for competitive advantage[C]. Papers and Proceedings the 96th Annual Meeting of the American Economic Association, 1984, 74(2): 127-132.
    [21] Chen M.J, Venkataramana S., Sylvia S.B., et al.The Role of Irreversibilities in Competitive Interaction: Behavioral Considerations from Organization Theory[J]. Managerial and decision economics, 2002, 23: 187-207
    [22] Chen M.J. Competitor analysis and interfirm rivalry: toward a theoretical integration[J]. Academy of Management Review. 1996, 21(1): 100-134.
    [23] Chen M.J., MacMillan I.C. Nonresponse and Delayed Response to Competitive Moves: The Role of Competitor Dependence and Action Irreversihilily[J]. Academy of MananemenL Journal, 1992, 35: 539-70.
    [24] Chen MJ, Su KH, Tsai W. Competitive tension: the awareness-motivation-capability perspective[J]. Academy of Management Journal, 2007, 50(1): 101–118.
    [25] Chen, M.J., Hambrick, D.C. Speed, Stealth, and Selective Attack: How Small Firm Differ from Large Finns in Competitive Behavior[J]. Academy of Management Journal, 1995, 38(2): 453-482.
    [26] Chen, Z., Ross, T. Markets linked by rising marginal costs: implications for multimarket contact, recoupment, and retaliatory entry[J]. Review of Industrial Organization, 2007, 31(1):1-21.
    [27] Clauset A., Newman M. E. J., Moore C. Finding community structure in very large networks. Phys. Rev. E, 2004, 70:066111.
    [28] Coccorese, P., Pellecchia, A. Multimarket Contact and Profitability in Banking: Evidence from Italy[J]. J Finance Serv Res, 2009, 35:245-271
    [29] D’Aveni R. A. Competitive pressure systems mapping and managing multimarket contact [J]. MIT Sloan Management Review, 2002, 44(1): 39-49.
    [30] D’Aveni R.A. Hypercompetition: Managing The Dynamics of Strategic Maneuvering[M]. New York: Free Press.1994.
    [31] Dixit, A.K. A Model of Duopoly Suggesting a Theory of Entry Barriers [J]. Betl Joumal of Economics 1979 10: 20-32.
    [32] Edwards C D. Conglomerate Bigness as a Source of Power[C]//Business Concentration and Price Policy. Princeton, NJ: Princeton University Press, 1955: 331–352.
    [33] Erdos, P., Renyi A. On the Evolution of Random Graphs[J]. Publication of theMathematical Institute of the Hungarian Academy of Sciences, 1960, 5:17-61.
    [34] Eric W., Berend W. Explaining Competitors' Reactions to New Product Introductions: The Roles of Event Characteristics, Managerial Interpretation, and Competitive Context[J]. Marketing Letters, 2000, 11(1): 67-79
    [35] Evans,W.N., Kessides, I.M.Living by the‘Golden Rule’: Multimarket Contact in the U.S.Airline Industry [J]. The Quarterly Journal of Economics, 1994, 109(2): 341-366.
    [36] Fan Y., Li M.H., Chen J., et al. Network of econophysicsts: a weighted network to investigate the developmeat of econophysics[J]. Int. J. of Mod. Phys. H, 2004, 18: 25052S12
    [37] Fan Y., Li M.H., Zhang P., et al. Accuracy and Precision of Methods for Community Identification in Weighted Networks[J], Physica A, 2007, 377: 363-372
    [38] Feinberg R.M.‘Sales-at-risk’: a test of the mutual forbearance theory of Conglomerate behavior [J]. J Bus, 1985, 58:225–241.
    [39] Fenner T., Levene M., Loizou G. A model for collaboration networks giving rise to a power-law distribution with an exponential cutoff[J]. Social Networks, 2007, 29: 70-80
    [40] Ferrier W.J. Navigating the competitive landscape: The drivers and consequences of competitive aggressiveness[J]. Academy of Management Journal, 2001, 44: 858-877
    [41] Francisco J., Más-Ruiz Juan L., Nicolau-Gonzálbez, et al. Asymmetric rivalry between strategic groups: response, speed of response and exante VS expost competitive interaction in the spanish bank deposit market[J]. Strategic Management Journal, 2005, 26: 713–745
    [42] Franke J., Ozturk T. Conflict networks [A], Ruhr Economic Papers, 2009, No. 116.
    [43] Fuentelsaz, L., Gomez J. Multipoint Competition,Strategic Similarity and Entry into Geographic Markets [J]. Strategic Management Journal, 2006, 27: 477-499.
    [44] Furusawa, T, and Konishi, H. Free trade networks [J]. Journal of International Economics, 2007, 72(2): 310-335.
    [45] Gatignon, Hubert, David Reibstein. Creative Strategies for responding to Competitive Actions[J]. Wharton on Dynamic Competitive Strategy, 1997: 237-255
    [46] Gibson, Kleinberg. Raghavan. Inferring Web Communities from Link Topology[J]. Proceedings of the ninth ACM conference on Hypertext and hypermedia, 1998: 225-234
    [47] Gimeno J., Woo C.Y. Hypercompetition in a Multimarket Environment: The Role of Strategic Similarity and Multimarket Contact in Competitive De-Escalation[J]. Organization Science, 1996, 7(3): 322-341
    [48] Gimeno, J., Woo, C.Y. Multimarket Contact, Economies of Scope, and Firm Performance[J]. The Academy of Management Journal, 1999, 42(3): 239-259.
    [49] Girvan M., Newman M. E. J. Community structure in social and biological networks. Proc Natl. Acad. Sci. 2001, 99: 7821-7826.
    [50] Gleiser P, Danon L. Community structure in Jazz [J]. Advances in Complex System, 2003, 6: 565-573
    [51] Goyal, S, and Joshi, S. Bilateralism and free trade [J]. International Economic Review, 2006, 47(3): 749-778.
    [52] Goyal, S, and Joshi, S. Networks of collaboration in oligopoly [J], Games and Economicbehavior, 2003, 43(1): 57-85.
    [53] Goyal, S., Moraga-Gonzalez. R&D Networks [J]. RAND Journal of Economics, 2001, 32(4): 686-707.
    [54] Granovetter, M. The strength of weak ties[J]. American Journal of Sociology, 1973, 78(6): 1360-1380.
    [55] Greve, H.R. Multimarket contact and sales growth: evidence from insurance [J]. Strategic Management Journal, 2008, 29: 229-249.
    [56] Grimm C.M., Smith K.G. Strategy as action: Industry rivalry and coordination[M]. Cincinnati: Souty-Western College Publishing. 1997
    [57] Guillaume J., Latapy M. Bipartite graphs as models of complex networks[J]. Physica A, 2006, 371: 795–813
    [58] Güler, Ergün. Human Sexual Contact Network as a Bipartite Graph[J]. PHYSICA A, 2002, 308: 483-488
    [59] Hackner, J., 2000. A note on price and quantity competition in differentiated oligopolies[J]. Journal of Economic Theory, 2000 93: 233–239.
    [60] Han D.D., Qian J.H., Liu J.G. Network Topology of the Austrean Airline Flights[J], arXiv:physics/0703193, 2007
    [61] Hannan, M. T., and Freeman, J. Organizational ecology[M]. Cambridge, MA: Harvard University Press, 1989.
    [62] Hauert, C., Doebeli, M. Spatial Structure of often inhibits the evolution of cooperation in the snowdrift game [J]. Nature, 2004, 428: 643-646.
    [63] Haveman, H.A., Nonnemaker, L. Competition in multiple geographic markets: theimpact on growth and market entry [J]. Administrative Science Quarterly, 2000, 45: 232-267.
    [64] Heggestad, A.and Rhoades, S. MutliMarket Interdependence and Local Market Competition in Banking[J]. The Review of Economics and Statistics, 178 60(4): 523-532.
    [65] Holme P., Liljeros F., Edling C.R., et al. On network bipartivity[J]. Phys. Rev. E 2003, 68: 056107
    [66] Hopkins H.D. The response strategies of dominant U.S. firms to Japanese challengers[J].Journal of Management, 2003, 29: 5–25
    [67] Jackson, M O, and Wolinsky, S. A strategic model of social and economics network [J]. Journal of Economic Theory, 1996, 71(1): 44-74.
    [68] Jackson, M O. A Survey of Models of Network Formation: Stability and Efficiency, in Group Formation in Economics; Networks, Clubs and Coalitions[M], edited by Gabrielle Demange and Myrna Wooders, Cambridge University Press: Cambridge U.K., 2004.
    [69] Jacobson, R. 1992. The "Austrian" school of strategy[J]. Academy of Management Review, 17: 782-807.
    [70] Jean L.G., Matthieu L. Bipartite structure of all complex networks[J]. Information Processing Letters, 2004, 90(5): 215–221.
    [71] Johnson, S.C. Hierarchical clustering schemes, Psychometrika 32(3) (1967) 241-254.
    [72] Karnani, A., Wernerfelt, B. Multiple Point Competition [J]. Strategic Management Journal, 1985, 6(1): 87-96.
    [73] Kernighan B. W. and S. Lin, An efficient heuristic procedure for partitioning graphs[J]. Bell System Technical Journal 49, 291–307 (1970).
    [74] Ketchen DJ, Snow CC, Hoover VL. Research on competitive dynamics: recent accomplishments and future challenges[J]. Journal of Management, 2004, 30: 779–804.
    [75] Kobayashi, H., Ohta K., Multimarket contact in continuous-time games [J]. Economics Letters, 2008, 101: 4-5.
    [76] Kranton, R. and Minehart, D. A Theory of Buyer-Seller Networks [J]. The American Economic Review, 2001, 91(3): 485-508.
    [77] Lambiotte R., Ausloos M. Uncovering collective listening habits and music genres in bipartite networks[J]. PHYSICAL REVIEW E 2005, 72: 066107
    [78] Li M.H, Fan Y., Chen J., et al. Weighted networks of scientific communication: the measurement and topological role of weight[J]. Physica A, 2005, 350, 643-656
    [79] Li, W., Cai, X. Statistical analysis of airport network of China[J]. Phys. Rev. E, 2004, 69: 046106
    [80] Li, X., Liu, B., Philip S., et al. Mining Community Structure of Named Entities from WebPages and Blogs, AAAI-CAAW 2006
    [81] Lieberman, M. B., Montgomery, D. B. First-mover advantages [J]. Strategic Management Journal, 1988, 9: 41-58.
    [82] M. Fiedler, Algebraic connectivity of graphs. Czech. Math. J. 1973, 23: 298–305.
    [83] MacMillan, I. C. Seizing competitive initiative[J]. Journal of Business Strategy, 1982, 2(4): 43-57
    [84] MacMillan, McCafferty, and Van Wijk, competitor’s response to easily imitated new products—exploring commercial banking product introductions [J]. Strategic Management Journal 1985, 6: 75-86.
    [85] Matsushima H. Multimarket contact, imperfect monitoring, and implicit collusion, Journal of Economic Theory, 2001 98(1): 158-178.
    [86] Miller D., Chen, M.J. The Causes and Consequences of Competitive Inertia[J]. Administrative Science Quarterly, 1994, 39:1-23
    [87] Minzberg H., Ahlstrand B., Lampel J. Strategy Safari: a guided tour through the wilds of strategic management[M]. The Free Press.1998: 185-192
    [88] Newman M E J, Girvan M .Finding and evaluating community structure in network[J]. Physical Review E, 2004a, 69:026113
    [89] Newman M E J. Analysis of weighted networks[J]. Phys. Rev. E 2004c, 70: 056131
    [90] Newman M. E. J. Fast algorithm for detecting community structure in networks [J]. Phys. Rev. E, 2004b, 69: 066133
    [91] Newman M.E.J. Scientific collaboration networks I: Network construction and fundamental results[J]. Phys Rev. E, 2001b, 64, 016131
    [92] Newman M.E.J. Scientific collaboration networks II: Shortest paths, weighted networks, and centrality [J]. Phys. Rev. E, 2001a, 64: 016132
    [93] Newman M.E.J. The structure of scientific collaboration networks[J]. Proceeding of the National Academy of Sciences, USA, 2001a, 98: 404-409
    [94] Nowak, M.A., and May, R.M. Evolutionary games and spatial chaos. Nature 359, 1992: 826–829.
    [95] Nowak, M.A., May, R.M. The spatial dilemmas of evolution [J], International Journal of Bifurcation and Chaos, 1993, 3(1): 35-78.
    [96] Ohkubo J., Tanaka K., Horiguchi T. Generation of complex bipartite graphs by using a preferential rewiring process[J]. PHYSICAL REVIEW E, 2005, 72: 036120, 1-10
    [97] Onnela J.P., Saramaki J., Hyvonen J., et al. Analysis of a large-scale weighted network of one-to-one human communication[J]. New J. Phys, 2007, 179(9): 0702158
    [98] Ou R.Q, Yang J.M., Chang J, et al. On Heterogeneity of Complex Networks in the Real World[C]. MCDM, 2009, 213-219.
    [99] Ou, R.Q., Yao C.Z., Y J.M, et al. Social Network and Agency Activity: Wage, Efficiency and Market Mechanism [C]. International Conference on Management Science & Engineering September, 2008, 1797-1802
    [100] Palla G., Derenyi I., Farkas I., Vicsek T. Uncovering the overlapping community structure of complex networks in nature and society [J]. Nature, 2005, 435(7043): 814-818
    [101] Pastor-Satorras R., Vespignani A. Evolution and structure of the Internet: a statistical physics approach[M]. Cambridge, England: Cambridge university press, 2004
    [102] Porter M.E. Competitive Strategy: techniques for analyzing industries and competitors[M]. Free Press, New York. 1980: 247-254
    [103] R Jesus, M Schwartz, S Lehmann, Bipartite networks of Wikipedia's articles and authors: a meso-level approach[C]. Proceedings of the 5th International Symposium on Wikis and Open Collaboration 2009
    [104] Radicchi F., Castellano C., Cecconi F., Loreto V., Parisi D. Defining and identifying communities in networks[J]. Proc. Natl. Acad. Sci., 2004, 101:373-380.
    [105] Ramasco J.J., Dorogavtsev S.N., P-Satorras R. Self-organization of collaboration networks[J]. Physical Review E, 2004, 70: 036106
    [106] Rees, A. Information networks in labor markets[J]. The American Economic Review, 1966, 56: 559-566.
    [107] Rhoades, S.A., Heggestad, A. Multimarket Interdependence and Performance in Banking: Two Tests [J]. Antitrust Bulletin, 1985, 30: 975-995.
    [108] Robins, G., Alexander, M., Small worlds among interlocking directors: network structure and distance in bipartite graphs [J]. Computational & Mathematical Organization Theory, 2004, 10 (1): 69–94.
    [109] Rong, Z.H., Li, X., Wang X.F. Roles of mixing patterns in cooperation on a scale-free networked game. Phys Rev E, 2007, 76:027101.
    [110] Santos, F.C., Pacheca, J.M. Scale-free networks provide a unifying framework for the emergence of cooperation [J]. Phys Rev Lett, 2005, 95: 098104.
    [111] Santos, F.C., Pacheca, J.M., Lenaerts, T Evolutionary dynamics of social dilemmas in structured heterogeneous populations [J]. Proc Natl Acad Sci USA, 2006, 103(9): 3940-3494.
    [112] Santos, F.C., Rodrigues, J.F., Pacheca, J.M. Graph topology plays a determinant role in the evolution of cooperation [J]. Proc Royal Soc London B, 2006, 273: 51-55.
    [113] Schilling M A, Phelps C C, Interfirm Collaboration Networks: The Impact of Large-Scale Network Structure on Firm Innovation[J]. Management Science, 2007 53(7): 1113-1126.
    [114] Scott, J.T. Multimarket contact and economic performance review of economics and statistics [J], LXIV, 1982: 368-75.
    [115] Singh, N., and Vives, X. Price and quantity competition in a differentiated duopoly[J]. Rand Journal of Economics 1984 15(4): 546-554
    [116] Smith K., Grimm C., Gannon M. Dynamics of Competitive Strategy [M]. Newbury Park, California: Sage Publications, 1992.
    [117] Smith K.G., Ferrier W.J., Ndofor H. Competitive dynamics research: critique and future directions[C]. In Handbook of Strategic Management, M. Hitt, R. E. Freeman, &J. Harrison, London: Blackwell Publishers, 2001
    [118] Spence, A.M. Entry, investment, and oligopolistic pricing[J]. The Bell Journal of Economics, 1977 8(2):534-544.
    [119] Stephan, J., Murmann, J.P., Boeker, W., et al. Bringing Managers into Theories of Multimarket Competition: CEOs and the Determinants of Market Entry [J]. OrganizationScience, 2003, 14(4): 403-421.
    [120] Strickland, S., Smith, K.K., Marotti, K.R. Hormonal induction of differentiation in teratocarcinoma stem cells: Generation of parietal endoderm by retinoic acid and dibutyryl cAMP[J]. Cell, 1980, 21: 347-355.
    [121] Szabo, G., Hauert, C. Phase transitions and volunteering in spatial public goods games, Phys Rev lett, 2002, 89: 118101.
    [122] Szabo, G., Toke C. Evolutionary Prisoner’s dilemma on a square lattice [J]. Phys Rev E, 1998, 58: 69-73.
    [123] Szabo, G., Vukov, J., Szolnoki, A. Phase diagrams for an evolutionary prisoner’s dilemma game on two-dimensional lattices [J]. Phys Rev E, 2005, 72: 047107
    [124] Tambayong, L. Dynamics of network formation processes in the co-author model [J]. Journal of Artificial Societies and Social Simulation, 2007, 10(32).
    [125] Tang C L, Wang W X, Wu X, Wang BH. Effect of average degree on cooperation in networked evolutionary game[J]. Eru Phys J B, 2006, 53: 411-415.
    [126] Teece D.J., Pisano G., Shuen A. Dynamic Capabilities and Strategic Management Foss[J]. Resource Firms and Strategies, 1997: 268-285
    [127] Tomassini M, Luthi L, GIacobini M. Hawks and doves on small-world network[J]. Phys Rev E, 2006, 73: 016132.
    [128] Vedel, S.E. Greating first-mover advantages in nature-based recreational goods [J]. Small-scale Forestry 2010, 9: 21-39.
    [129] Verspagen B, Duysters G. The SmallWorlds of Strategic Technology Alliances[J]. Technovation, 2004, 24(7):563–571.
    [130] Vukov, J., Szabo, G., Szolnoki, A. Cooperation in the noisy case: Prisoner’s dilemma game on tow types of regular random graphs [J]. Phys Rev E, 2006, 73: 067103.
    [131] Wang D.H, Zhou L., Di Z.R. Bipartite producer–consumer networks and the size distribution of firms[J]. Physica A, 2006, 363: 359–366
    [132] Wang, P., and Watts, A. Formation of buyer-seller trade networks in a quality-differentiated product market[J]. Canadian Journal of Economics, 2006, 39(3):971-1004.
    [133] Wang, W.X., Ren, J., Chen, G., et al. Memory-based snowdrift game on networks[J]. Phys Rev E, 2006, 74: 056113.
    [134] Watts, D. J., Strogatz, S. H. Collective dynamics of `small-world networks [J]. Nature, 1998, 393: 440-442.
    [135] Wu, Z.X., Wang, Y.H., Cooperation enhanced by the difference between interaction and learning neighborhoods for evolutionary spatial prisoner’s dilemma games [J]. Phys Rev E, 2007 75: 041114.
    [136] Wu, Z.X., Xu, X.J., Chen, Y., et al. Spatial prisoner’s dilemma game with volunteering in Newman-Watts small-world networks [J]. Phys Rev E, 2005, 71: 036107.
    [137] Wu, Z.X., Xu, X.J., Huang Z.G. et al. Evolutionary Prisoner’s dilemma game with dynamic preferential selection [J]. Phys Rev E, 2006, 74:021107.
    [138] Xianyu, B., Yang, J.M. Evolutionary ultimatum game on complex networks under incomplete information [J]. Physica A, 2010, 389: 1115-1123.
    [139] Yang J. M., Lu L. P., Xie W. D., Chen G. R., Zhuang D. On competitive relationship networks: a new method for industrial competition analysis [J]. Physica A, 2007, 382: 704-714.
    [140] Yang J.M., Huang X.Z., Zhuang D., et al. The Complex Network Analysis of Competitive Relationships between Manufacturers in Foshan Ceramic Industry Cluster[C]. Proceedings of 2006 International conference on Management Science & Engineering(13th), 2006, 2(10): 1020-1023
    [141] Yang J.M., Wang W.J., Chen G.R. A two-level complex network model and its application [J]. Physica A, 2009, 388(12): 2435-2449.
    [142] Yang J.M., Zhuang D., Xu X. The complex network analysis on service channels of a bank and its management utility[J]. Dynamics of Continuous, Discrete and Impulsive Systems B, 2008, 15: 179-193.
    [143] Yook S.H., Jeong H., Barabasi A.L., et al. Weighted evolving networks[J]. Phys. Rev. Lett., 2001: 865835
    [144] Zhang P.P., Chen K., He Y., et al. Model and empirical study on some collaboration networks[J]. Physica A, 2006, 360: 599-616
    [145] Zheng D., Trimper S., Zheng B., et al. Weighted scale-free networks with stochastic weigh assignments[J]. Phys. Rev. E, 2003, 67: 040102
    [146] Zhuang D., Yang J.M. Simulation of Rivalry Spread Effect over the Competitive Pressure Network[C], Pro. IEEE, SMC, 2008
    [147] Zhuang D., Yang J.M., Pan X.D., et al. The bipartite network based growth mechanisms of complex company competitive relationship networks(C). Proceedings of 2006 IEEE Asia-Pacific Conference on Services Computing. 2006.12: 247-252.
    [148]傅林华,郭建峰,朱建阳.图书馆图书借阅系统与单标度二元网络模型[J].情报学报, 2004, 23: 571-575
    [149]干春晖,戴榕,李素荣.我国轿车工业的产业组织分析[J].中国工业经济,2002, 8: 15-22.
    [150]郭雷,许晓鸣,史定华,等.复杂网络[M].上海,上海科技教育出版社, 2006.
    [151]胡鲜,杨建梅,李得荣.广东软件企业竞争关系的复杂网络演变分析[J].软科学,2008. 6.
    [152]胡鲜.发展企业的“动态能力”[J].通信企业管理, 2003, 10: 44-45
    [153]胡鲜.基于复杂网络的中国汽车零部件企业竞争关系结构及行为研究[D].华南理工大学工商管理学院, 2008.
    [154]黄玮强,庄新田,姚爽.企业创新网络的自组织演化模型[J].科学学研究, 2009, 27(5): 793-800.
    [155]刘慧,李增扬,陆君安.局域演化的加权网络模型[J].复杂系统与复杂性科学, 2006, 1(3): 36-43.
    [156]马丁.史东辉(译).高级产业经济学[M].上海财经大学出版社,上海, 2003.
    [157]施中华.中国轿车产业组织演化研究[D].复旦大学管理学院,上海, 2006.
    [158]汪小帆,李翔,陈关荣.复杂网络:理论及其应用[M].北京:清华大学出版社, 2006
    [159]谢洪明,蓝海林,叶广宇,等.动态竞争:中国主要彩电企业的实证研究[J] .管理世界, 2003, 4: 77-86.
    [160]杨建梅,陆履平,谢王丹.广州软件企业竞争关系的复杂网络分析[A].第二届全国复杂动态网络学术论坛论文集[C]. 2005: 616-619.
    [161]杨建梅.企业间竞争关系与对抗行动的二层复杂网络分析思路[A]. 2006全国复杂网络会议论文集[C], 2006: 232-233.
    [162]袁娟,张宁.家电企业竞争网络的拓扑结构分析.上海理工大学学报, 2007, 9(1): 37-41.
    [163]张培培,何阅,周涛,等.一个描述合作网络顶点度分布的模型[J].物理学报, 2006, 55(1): 60-67
    [164]植草益.产业组织论[M].中国人民大学出版社,北京, 1988.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700