口碑对不同世代消费者购买意向的影响差异研究

研究考察了口碑对青少年消费者与中年消费者购买意向的影响是否存在差异,通过实验研究法探究了口碑来源、消费者世代、产品类型三个变量对消费者购买意向的影响.实验结果显示口碑对消费者购买意向的影响会随着口碑来源、产品类型的不同而表现出显著的差别;来源于亲友的口碑对中年消费者购买意愿的影响比青少年更大,而来自意见领袖的口碑对两个群体购买意向的影响无显著差别;在购买搜寻品时,口碑对中年消费者的影响力更大,而对于体验品,口碑影响力在二者之间并无显著差异.     

基于社会网络结构的创新扩散动力机制及其仿真研究

随着社会资本的大量涌入,创新扩散逐渐受到社会网络关系的影响。在分析了创新扩散机理的基础上,构建了基于不同拓扑结构的创新扩散演化动力模型。将信息获取、领导者创新能力及机会利益作为创新扩散的动力因子。通过利用复杂网络的演化博弈仿真分析,揭示了小世界、无标度等不同网络拓扑结构下,创新技术的扩散情况。仿真结果表明:在网络结构相同的情况下,信息获取对创新扩散的影响较大;在动力因子设定相同的情况下,网络主体连接越规则,创新扩散越充分。     

基于随机Petri网的邻避冲突演化过程模型及情景仿真分析——以垃圾焚烧发电厂为例

在中国城镇化发展过程中,因某些基础设施的选址与建设而引发的“邻避冲突”时有发生,针对这一问题,对该类冲突的影响因素及其演化过程进行深入而系统的分析。通过借鉴扎根理论思想及多案例研究,对影响冲突演化过程的主要因素进行提炼与归纳,并构建冲突演化过程系统图。然后基于随机Petri网理论,对冲突演化过程进行建模,并进行情景仿真分析。结果表明,政府单边决策、意见领袖的组织策划及与设施有关的负面信息传播扩散容易引发周边居民不良的情绪反应及抵制抗议行为;政府妥协有利于事件的平息,但会使周边居民对政府形成负面经验认知、对政府产生不信任以及对风险产生过高的感知;政府无效的风险沟通行为可能会导致冲突升级,但能减少周边居民对于政府的不信任及风险感知。     

基于agent仿真的在线客户评论传播机制研究

随着互联网技术的日益发达,网民数量激增,网络口碑在顾客购买决策方面的影响效用越来越显著。在线客户评论作为一种重要的网络口碑传播方式越来越受到企业的重视。不同于以往从实证的角度对在线客户评论影响因素进行研究的文献,本文从在线客户评论的网络传播机制出发,构建在线客户评论的口碑传播模型。而后本文通过Swarm平台进行模拟仿真,主要研究了论坛作为个体在口碑传播中所起到的作用,为网络口碑的研究提供新的思路。本文研究发现在线客户评论的影响机制和因素,为企业更好的开展网络口碑营销提供借鉴。     

头雁效应——团队领导创新性工作表现对团队创新绩效影响的实证研究

团队领导创新性工作表现是一个团队对创新活动的认知,它将影响团队的创新氛围和创新绩效.基于社会认知理论,以高新技术企业的RD团队为研究对象,构建了领导创新性工作表现、团队创新氛围和团队创新绩效关系的理论模型,并应用问卷数据对理论模型进行了实证分析.结果显示:团队领导创新性工作表现有助于形成良好的创新氛围;团队创新氛围能够有效提升RD团队创新绩效;团队创新氛围在领导创新性工作表现和团队创新绩效之间起到部分中介作用.     

网络口碑对在线零售业消费者决策行为影响

从网络口碑的数量、方向、趣味性、时效性四个维度分析网络口碑对在线零售业消费者决策行为的影响.采用调查问卷的方式收集数据并进行统计分析.研究结果显示,网络口碑的数量,网络口碑的方向,网络口碑的趣味性均对消费者的决策有明显的影响,而网络口碑的时效性对消费者决策的影响程度较低.     

面向集群创新网络异质企业的知识扩散建模及仿真研究

基于合作的集群创新网络知识扩散已经成为企业实现知识创新的重要手段,而集群创新网络知识扩散的动力学过程强烈依赖于异质企业间知识扩散能力的影响,为此,本文综合考虑了企业间不同接触数量、知识吸收和传播能力、知识淘汰率等异质性因素,建立了基于传染病理论的知识扩散模型,验证了由各异质因素构成的知识扩散再生数对知识扩散均衡和扩散效果的影响,并结合仿真实验进一步得出:在知识扩散前期,集群创新网络应发挥hub节点及异质网络的优势加快知识扩散,在中后期应注意企业关系发展的均衡性及企业接触邻居的规模性;相比过于强调知识交流的广泛性,加强企业传播能力和吸收能力的培养对网络知识扩散效果的提升更具意义;随着时间演化,企业知识淘汰率也会影响网络知识扩散的收敛情况。     

自媒体时代网络推手参与下的负面网络舆论传播及治理研究——基于三方博弈视角

自媒体时代,纷繁复杂的网络信息填补着公众的碎片化时间,公众的注意力成为相关利益主体争夺的宝贵资源,网络推手应运而生,在负面网络舆论传播中有强大影响,成为治理网络舆论重要的研究对象.运用演化博弈方法构建了当事人、网络推手和监管者三方行为主体的博弈模型,对模型求解分析与数值仿真,研究各主体策略行为对负面网络舆论传播的作用机理,继而提出治理对策.通过对网络推手参与下负面舆论传播作用机理和影响因素的分析,有针对性的提出了降低负面舆论传播的监管成本、提高监管者的处罚力度、提高负面舆论传播成本、限制网络推手舆论传播收益等治理手段的具体措施.研究有助于有效治理负面网络舆论传播,净化网络空间.     

真实及虚拟社区的网购人际影响关系网络结构特征研究

真实社区及虚拟社区是消费者发布、传播、获取口碑信息的重要渠道,社区成员之间通过口碑信息交流产生购物人际影响关系,本文选取约200个真实社区和400个虚拟社区,以社区内约十万名成员的两百万条淘宝真实交易数据为基础,从社会网络的视角构建表征社区网购入际影响关系的有向有权网,并用社会网络分析法从网络内含度、网络密度、中心性、凝聚子群四方面对社区人际影响关系网络的结构特征进行研究,探索社区内网购人际交流、传播及影响的规律,为社区口碑营销提供理论基础和实践指导..     

基于集群创新合作网络的知识创新与扩散过程建模及仿真研究

基于集群创新合作网络的知识创新和知识扩散过程是集群企业实现创新的关键。为了揭示集群创新合作网络中知识增长绩效的演化规律,探讨不同网络中知识增长绩效的差异及其形成原因,论文构建了知识创新与扩散的过程模型,以东北三省新能源汽车集群创新合作网络为例,运用复杂网络理论和仿真方法进行分析。研究发现,集群创新合作网络的整体知识水平呈现先递增后递减的演化规律;知识增长的演化过程存在突变点,突变时期不同网络中企业知识水平分化的情况决定不同网络知识增长绩效的差异性;知识扩散约束条件是知识创新与扩散过程的关键;实际网络并非知识创新与扩散的最优网络,无标度网络具有知识增长的绩效优势;hub结构和适度的节点度值分布差异性有利于提升知识增长绩效。     

Failure in Complex Social Networks

A class of inhomogenously wired networks called “scale-free” networks have been shown to be more robust against failure than more homogenously connected exponential networks. The robustness of scale-free networks consists in their ability to remain connected even when failure occurs. The diffusion of information and disease across a network only requires a single contact between nodes, making network connectivity the crucial determinant of whether or not these “simple contagions” will spread. However, for “complex contagions,” such as social movements, collective behaviors, and cultural and social norms, multiple reinforcing ties are needed to support the spread of a behavior diffusion. I show that scale-free networks are much less robust than exponential networks for the spread of complex contagions, which highlights the value of more homogenously distributed social networks for the robust transmission of collective behavior.     

Diffusion dynamics in small-world networks with heterogeneous consumers

Diffusions of new products and technologies through social networks can be formalized as spreading of infectious diseases. However, while epidemiological models describe infection in terms of transmissibility, we propose a diffusion model that explicitly includes consumer decision-making affected by social influences and word-of-mouth processes. In our agent-based model consumers’ probability of adoption depends on the external marketing effort and on the internal influence that each consumer perceives in his/her personal networks. Maintaining a given marketing effort and assuming its effect on the probability of adoption as linear, we can study how social processes affect diffusion dynamics and how the speed of the diffusion depends on the network structure and on consumer heterogeneity. First, we show that the speed of diffusion changes with the degree of randomness in the network. In markets with high social influence and in which consumers have a sufficiently large local network, the speed is low in regular networks, it increases in small-world networks and, contrarily to what epidemic models suggest, it becomes very low again in random networks. Second, we show that heterogeneity helps the diffusion. Ceteris paribus and varying the degree of heterogeneity in the population of agents simulation results show that the more heterogeneous the population, the faster the speed of the diffusion. These results can contribute to the development of marketing strategies for the launch and the dissemination of new products and technologies, especially in turbulent and fashionable markets. This paper won the best student paper award at the North American Association for Computational Social and Organizational Science (NAACSOS) Conference 2005, University of Notre Dame, South Bend, Indiana, USA. Preceding versions of this paper have been presented to the Conference of the North American Association for Computational Social and Organizational Science (NAACSOS), 2005, University of Notre Dame, South Bend, USA and to the Conference of the European Social Simulation Association (ESSA), 2005, Koblenz, Germany. Sebastiano Alessio Delre received his Master Degree in Communication Science at the University of Salerno. After one year collaboration at the Institute of Science and Technologies of Cognition (ISTC, Rome, Italy), now he is a PhD student at the faculty of economics, University of Groningen, the Netherlands. His work focus on how different network structures affect market dynamics. His current application domain concerns Agent-Based Simulation Models for social and economic phenomena like innovation diffusion, fashions and turbulent market. Wander Jager is an associate professor of marketing at the University of Groningen. He studied social psychology and obtained his PhD in the behavioral and social sciences, based on a dissertation about the computer modeling of consumer behaviors in situations of common resource use. His present research is about consumer decision making, innovation diffusion, market dynamics, crowd behavior, stock-market dynamics and opinion dynamics. In his work he combines methods of computer simulation and empirical surveys. He is involved in the management committee of the European Social Simulation Association (ESSA). Marco Janssen is an assistant professor in the School of Human Evolution and Social Change and in the Department of Computer Science and Engineering at Arizona State University. He got his degrees in Operations Research and Applied Mathematics. During the last 15 years, he uses computational tools to study social phenomena, especially human-environmental interactions. His present research focuses on diffusion dynamics, institutional innovation and robustness of social-ecological systems. He combined computational studies with laboratory and field experiments, case study analysis and archeological data. He is an associate editor-in-chief of the journal Ecology and Society.     

Opinion polarization by learning from social feedback

We explore a new mechanism to explain polarization phenomena in opinion dynamics in which agents evaluate alternative views on the basis of the social feedback obtained on expressing them. High support of the favored opinion in the social environment is treated as a positive feedback which reinforces the value associated to this opinion. In connected networks of sufficiently high modularity, different groups of agents can form strong convictions of competing opinions. Linking the social feedback process to standard equilibrium concepts we analytically characterize sufficient conditions for the stability of bi-polarization. While previous models have emphasized the polarization effects of deliberative argument-based communication, our model highlights an affective experience-based route to polarization, without assumptions about negative influence or bounded confidence.     

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。     

Opinion transmission in organizations: an agent-based modeling approach

This paper builds a theoretical framework to detect the conditions under which social influence enables persistence of a shared opinion among members of an organization over time, despite membership turnover. It develops agent-based simulations of opinion evolution in an advice network, whereby opinion is defined in the broad sense of shared understandings on a matter that is relevant for an organization’s activities, and on which members have some degree of discretion. We combine a micro-level model of social influence that builds on the “relative agreement” approach of Deffuant et al. (J. Artif. Soc. Simul. 5:4, 2002), and a macro-level structure of interactions that includes a flow of joiners and leavers and allows for criteria of advice tie formation derived from, and grounded in, the empirical literature on intra-organizational networks. We provide computational evidence that persistence of opinions over time is possible in an organization with joiners and leavers, a result that depends on circumstances defined by mode of network tie formation (in particular, criteria for selection of advisors), individual attributes of agents (openness of newcomers to influence, as part of their socialization process), and time-related factors (turnover rate, which regulates the flow of entry and exit in the organization, and establishes a form of endogenous hierarchy based on length of stay). We explore the combined effects of these factors and discuss their implications.     

基于复杂网络演化博弈的企业低碳创新合作行为网络演化机理研究

针对企业低碳创新合作所面临的复杂问题,基于现实复杂网络结构特征,运用演化博弈理论研究有限理性下企业低碳创新合作行为网络演化机理,利用Matlab仿真技术探究无标度网络载体上微观因素对低碳创新合作行为的影响。研究结果表明:低碳创新利益分配、协同效益和违约惩罚对低碳创新合作行为网络演化结果的影响最为显著,网络规模越大网络演化速度越慢,网络规模越小对协同系数和利益分配系数的敏感性越强,网络规模越大对技术溢出系数和违约惩罚的敏感性越强。研究结论可以为企业低碳创新合作策略制定提供解决依据。     

不同信任环境下在线知识社区知识系统演化研究

信任作为在线知识社区中的社会影响因素,对社区中的成员进行沟通学习、知识共享有着重要的作用。不同的在线知识社区有着不同的信任环境,而信任环境的不同会影响社区中用户的学习模式和观点传播。基于此,本文提出了基于信任与Deffaunt的组合观点影响模型。信任模型主要将社区中的信任分为认知信任和情感信任,通过调节参数结构,对应不同信任环境中信任的动态演化过程。Deffaunt模型作为基本观点影响模型,模拟了不同信任环境下的在线知识社区的知识观点的演化过程。实验结果发现,信任环境的高低决定了社区中的观点是否收敛,并且社区中的群体理性人占比和信任程度都能影响观点的收敛速度。     

网络结构、采纳者偏好与创新扩散:基于采纳者决策过程的创新扩散系统动力学模型仿真分析

在对采纳者决策过程分析的基础上,将网络结构和采纳者偏好作为核心参数,构建基于采纳者决策过程的创新扩散系统动力学模型。对模型进行仿真发现,在采纳者趋同化偏好条件下,网络平均度、网络重连概率与采纳者偏好强度的变动趋势与创新扩散效率的变动趋势相同,而在采纳者差异化偏好条件下则与创新扩散效率变动趋势相反。网络平均路径长度对创新扩散的影响方向与采纳者偏好特征无关,提高网络平均路径长度会始终降低创新扩散的效率。采纳者的趋同化偏好能够放大创新扩散对网络结构变量与采纳者偏好强度变量的敏感程度,采纳者差异化偏好则会缩小创新扩散对网络结构变量与采纳者偏好强度变量的敏感程度。研究结果对于制定创新推广策略具有一定的指导意义。     

Unanimous opinions in social influence networks

In this paper, I show that persons reach unanimous opinions even when they have different initial opinions and different social influences in social influence networks. Friedkin and Johnsen introduced a model of social influence networks, and identified conditions for initially diverse opinions to converge. However, they did not examine conditions of “unanimous” convergence. Hence, I provide sufficient conditions of such unanimous consensus by focusing on three typical but conflicting social influences: the equal influence, the influence of the lowest opinion, and no influence. I show that unanimous opinions occur even when persons have antagonistic social influences such as the equal influence and the influence of the lowest opinion. I also demonstrate that the most cooperative type is the equal influence, but the most central type is the no influence.