Agency and structure: a social simulation of knowledge-intensive industries

Modern knowledge-intensive economies are complex social systems where intertwining factors are responsible for the shaping of emerging industries: the self-organising interaction patterns and strategies of the individual actors (an agency-oriented pattern) and the institutional frameworks of different innovation systems (a structure-oriented pattern). In this paper, we examine the relative primacy of the two patterns in the development of innovation networks, and find that both are important. In order to investigate the relative significance of strategic decision making by innovation network actors and the roles played by national institutional settings, we use an agent-based model of knowledge-intensive innovation networks, SKIN. We experiment with the simulation of different actor strategies and different access conditions to capital in order to study the resulting effects on innovation performance and size of the industry. Our analysis suggests that actors are able to compensate for structural limitations through strategic collaborations. The implications for public policy are outlined.     

知识获取视角下用户持续参与众包创新的动态控制策略

众包创新作为企业充分利用外部群体智慧以实现创新的新型开放式创新模式,其本质是企业突破组织界限,获取与整合外部网络知识以提升创新绩效。由于创新任务复杂多样、用户参与自由自愿等特征,导致在众包创新实践中用户持续参与意愿不足、创新效果不好等现象。为此,基于关系营销和知识共享相关理论,界定面向众包创新的知识承诺概念,认为知识获取视角下用户持续参与众包创新的本质是众包参与双方的知识承诺建立,进而分析众包创新中知识承诺的关键影响因素,构建用户持续参与众包创新的动态优化决策模型,通过求解和算例分析探讨最优决策结果,给出引导用户持续参与众包创新的最优控制准则。     

Structure and complexity in economic and social systems

An attempt is made to outline a theory of complexity for economics and social science purposes. A methodology is outlined that realizes complexity as an analytical category, and develops a comprehensive theory of structural forms, structural change and qualitative systems behavior based on these methods. Examples of different nature are given to support the need for such a theory of complexity.     

Coordination in Dynamic Social Networks Under Heterogeneity

People often make choices or form opinions depending on the social relations they have, but they also choose their relations depending on their preferred behavior and their opinions. Most of the existing models of coevolution of networks and individual behavior assume that actors are homogeneous. In this article, we relax this assumption in a context in which actors try to coordinate their behavior with their partners. We investigate with a game-theoretic model whether social cohesion and coordination change when interests of actors are not perfectly aligned as compared to the homogeneous case. Using analytical and simulation methods we characterize the set of stable networks and examine the consequences of heterogeneity for social optimality and segregation in emerging networks.     

Who You Know vs. What You Know: The Impact of Social Position and Knowledge on Team Performance

Organizational behavior theories generally agree that human capital is critical to teams and organizations, but little guidance exists on the extent to which such theories accurately explain the relative contributions of individual actors to overall performance. Using newly created network measures and simulations based on data obtained from a software development firm, we investigate the relative effectiveness of social network theory and resource dependency theory as predictors of individuals' contributions to team performance. Our results indicate that individual impacts on team performance are more closely associated with knowledge and task dimensions than with social network structure. Furthermore, given that knowledge may be assessed a priori, these factors provide useful guidance for structuring teams and predicting team performance.     

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。     

Something out of nothing: a Bayesian learning computational model for the social construction of value

ABSTRACT

This article develops a formalism for the social construction of value. Using a model based on Bayesian agents, it demonstrates how “something” arises out of “nothing” via the emergence of durable value conventions and shows how the developed framework can be used to investigate socially constructed valuations under a variety of circumstances. The resulting analysis clarifies why assumptions that collectives will converge upon the “intrinsic” (i.e., non-socially originating) value of an object (e.g., market efficiency) may not hold for mixed social and non-social valuation regimes, explains the dependency of socially constructed valuations on early accidents, demonstrates the effects of confident actors on constructed values, and identifies the production of time-dependent ratcheting effects from the interaction of bubbles with value conventions.     

The social impact in a high-risk community: A cellular automata model

This research examines the spread of criminal behavior and hard drug consumption using a mathematical approach called cellular automata (CA). This CA model is based on two behavioral concepts. Firstly, peer association impacts criminal involvement. Secondly, addiction can heighten criminal activity. The model incorporates four types of actors who interact in a high-risk social community and one intervention method. The actors exert a social influence on each other by encouraging or discouraging drug use and criminal behavior. The intervention method called Incapacitation has a probabilistic impact on the individuals in the model. The results identify the threshold where positive influences on a population reduce the number of high-rate offenders in the community. These results are discussed to further the knowledge about the social influences in a high-risk community and how these influences can effect decisions on offender management.     

The value of cognitive foundations for dynamic social theory

It is possible to develop models of social behavior that are predicated on detailed mechanical models of cognition. Cognitively based social models are potentially unified theoretical frameworks that can be used to explain a wide variety of social phenomena. Moreover, if a knowledge representation scheme and a knowledge acquisition scheme are specified in the underlying cognitive model then it is possible to produce a dynamic social model. The resulting social model can thus be used to predict and explain not only conditions for specific behaviors but changes in those behaviors over time.

Constructuralism is a theory of social behavior that rests on a cognitive model. The cognitive model specified has a knowledge representation scheme, knowledge acquisition procedures, and control procedures for shifting cognitive attention. The resulting social model is a dynamic model that can be used to explain both conditions for the occurrence of a behavior and social and individual changes that accrue do to a series of behaviors. The explanatory breadth of the model is illustrated by looking at predictions about a variety of social phenomena including: development of shared knowledge, identical behavior by members of the society, foreign language acquisition, clique formation, civil disobedience, and diffusion of innovative information.     

产学研合作创新方式下政府补贴策略选择

创新补贴策略是政府鼓励企业创新的一种常见政策,考虑到企业内在的吸收能力与外部不同政府补贴策略方式的存在,本文以产学研合作创新方式为基础,通过建立三阶段博弈模型,利用模型解析与仿真分析讨论吸收能力与创新投入分配比例系数对政府补贴策略选择的影响。研究结果表明:无论政府采取哪一种补贴方式,均可以有效激励企业加大创新投入规模,并且企业的吸收能力与R&D投入、产量及社会福利均呈正相关关系;但是,吸收能力对利润及政府补贴的影响受限于补贴方式和企业的创新投入分配比例系数;此外,在创新产品补贴下,创新难度系数对政府补贴额度的影响并不明显,而创新产品补贴总体优于创新投入补贴。     

Inferring social structure from continuous‐time interaction data

Relational event data, which consist of events involving pairs of actors over time, are now commonly available at the finest of temporal resolutions. Existing continuous‐time methods for modeling such data are based on point processes and directly model interaction “contagion,” whereby one interaction increases the propensity of future interactions among actors, often as dictated by some latent variable structure. In this article, we present an alternative approach to using temporal‐relational point process models for continuous‐time event data. We characterize interactions between a pair of actors as either spurious or as resulting from an underlying, persistent connection in a latent social network. We argue that consistent deviations from expected behavior, rather than solely high frequency counts, are crucial for identifying well‐established underlying social relationships. This study aims to explore these latent network structures in two contexts: one comprising of college students and another involving barn swallows.     

考虑互惠公平的创新顾客激励契约研究

基于公平偏好理论的互惠公平,从创新顾客的互惠偏好程度、激励契约类型与激励效果的关系入手,构建创新顾客参与企业创新活动的激励模型。通过模型求解和分析,探讨激励契约的外部性和互惠关系对于激励效果的影响;此外,进一步分析如何联合经济激励和心理激励,降低企业获得创新顾客高努力投入的成本;最后,通过仿真实验,验证模型分析结果。研究发现:当创新顾客之间出现互惠关系时,最优激励契约取决于创新顾客心理偏好与风险态度之间的相互作用:当创新顾客的风险规避程度较低时,最优激励契约为相对绩效契约;当创新顾客的风险规避程度较高时,最优激励契约为团队报酬契约。     

Three‐dimensional blockmodels

In the classic blockmodel formulation, a social network among members of a population with n actors and k relations (types of tie) is arrayed as k n X n matrices. Though this is a three‐dimensional data structure, it is typically reduced to a two‐way analysis. In this paper, a three‐way procedure for analyzing multigraph data is developed. Specifically, in addition to applying the rule of structural equivalence to collapse actors, it is also applied to the relations (the third dimension), and structurally equivalent sets of relations are collapsed. The result is a three‐dimensional blockmodel (image) of social structure that is a more parsimonious representation of social structure than the classic two‐dimensional blockmodel images. The three‐dimensional approach is illustrated by application to three case studies: Homan's Bank Wiring Room, Sampson's monastery, and a local economy of hospital services. The structural equivalence approach to relations is further explored by applying it to the individual‐level Liking and Antagonism relations and their compounds (of length four or less) in the Bank Wiring Room. This application demonstrates that the structural equivalence approach can be used to identify equality equations for primitive and compound relations.     

一个创新网络动态性的仿真模型

提出了一个关于创新网络动态性研究的仿真模型,模型较为全面地考察了网络的形成过程和不同的角色在创新和网络中的作用,研究结论指出:网络的形成是由于创新主体为适应创新的复杂性而寻求资源互补效应的动态相互作用的结果,中小型企业的个体在网络演化的早期和中期起了重要的作用,合作体的作用主要发挥在中后期.     

基于Half-Panel Jackknife方法的医疗制造企业创业实验机制评估

新冠肺炎疫情凸显了医疗制造业创新的重要性。文章分析企业并购衍生和营销活动对技术创新的促进作用,同时解决创新估计中固定效应的冗余参数问题。采用2010-2017年国内162家医疗装备制造上市企业的面板数据,进行多种估计偏差纠正方法的比较分析,证实Half-Panel Jackknife在双固定效应模型中能较好地控制企业数据的抽样特征与个体异质性。结果表明:高新技术企业间的并购衍生作为创新选择机制,引导全系统企业的熊彼特式“创业实验”;本地声誉和全球通道作为创新规模扩大机制对技术创新有积极影响;政府支持能显著提升创新效率,企业规模、研发投入等内部因素也具有积极贡献。显示“创业实验”对创新系统的核心功能是促进技术创新一选择创新一扩大创新规模。从而揭示了优化制度环境和激励结构以促进各行为主体创业实验的重要意义。     

Identity-based learning and segregation in social networks under different institutional environments

To study the evolution of segregation in social networks across systems embedded in different institutional environments, we develop an identity-based learning model where segregation is stochastically conditioned by the initial distribution of the actor’s attention to identity and the updating of this distribution over time. The updating process, which we call the process of mutual learning multiplier, is based on an actor’s success and failure experiences in tying with the same-subgroup and cross-subgroup actors. Results from a Monte Carlo simulation of the model show that the mutual learning multiplier produces disproportional relationships between the initial distribution of identity attention and the level of segregation in social networks. We also find that those relationships are affected by the actors’ attention to structural holes, rate of learning from experience, system size, and the identity heterogeneity of the system. Overall, the model provides insights into various dynamics of network structuration across time and space.     

An Agent-Based Model of Innovation Emergence in Organizations: Renault and Ford Through the Lens of Evolutionism

Based on evolutionist theories and project management knowledge, a connectionist model based on genetic algorithm is built to simulate innovation process in organizations. Transformation and selection produce micro dynamics to create macro behavior in the agents' population. Results clarify Darwinian Lamarckian adaptation mechanisms as their relation to environment and their interactions. Simulations show the existence of an optimal level of experimentation and selection of projects upstream the innovation process, demonstrate that the efficiency of evolutionist processes is contingent to environment complexity and allow exploring interdependencies and coexistence between two paths of evolution. The model validity is approached through similarity to admitted theory and through a comparative study of the innovation processes of two car makers (Renault and Ford).     

An approach for relating social structure to cognitive structure

There are three different reasons why non-linear functions between social macro-variables (aggregates) may arise. They can be related to three basic steps of a specific model of explanation of social phenomena, defined by Coleman: the logic of situation, the logic of selection and the logic of transition. Starting with a model of one linear difference equation, a change to three different non-linear system equations can generate stable cycles, bifurcations, and chaos. These non-linear system equations can be deduced from simple assumptions about individual or institutional social attributes. It is shown that a) non-linear individual reactions, b) different selection rules for actors having different social attributes and c) institutional constraints resulting in different transition processes are possible causes for non-linearity at the system level. Furthermore it is demonstrated that the assumption of non-linear but homogeneous reactions of all persons have a similar effect on non-linearity, like it is the case for different selection rules. However, despite of being able to show mathematically the possibility of chaos, it has to be said that chaos as a durable state of social systems is very improbable.     

ISSUE INFORMATION

Modeling social‐ecological systems is difficult due to the complexity of ecosystems and of individual and collective human behavior. Key components of the social‐ecological system are often over‐simplified or omitted. Generalized modeling is a dynamical systems approach that can overcome some of these challenges. It can rigorously analyze qualitative system dynamics such as regime shifts despite incomplete knowledge of the model's constituent processes. Here, we review generalized modeling and use a recent study on the Baltic Sea cod fishery's boom and collapse to demonstrate its application to modeling the dynamics of empirical social‐ecological systems. These empirical applications demand new methods of analysis suited to larger, more complicated generalized models. Generalized modeling is a promising tool for rapidly developing mathematically rigorous, process‐based understanding of a social‐ecological system's dynamics despite limited knowledge of the system.     

Mimetic trust and intra‐organizational network dynamics

Dynamic network models based on the homophily principle are criticized for neglecting organizational context conditions and the impact of role structures on the evolution of intra‐organizational trust networks. Using a neo‐institutional framework it is argued that individuals in competitive environments will attempt to reduce uncertainty about the trustworthiness of potential trustees by imitating the sociometric choice behavior of persons in similar network positions. Three hypotheses are developed. The positional trust hypothesis predicts that individuals tend to trust other actors who occupy a similar network position as themselves. The mimetic trust hypothesis argues that individuals trust actors who are trusted by persons in their own network position. Finally, the advisory trust hypothesis claims that individuals prefer to maintain trust relations to persons occupying a position of third party intermediary than to persons in other positions. An exploratory empirical test of the hypotheses is carried out by reanalyzing a longitudinal network study of the relationships among 25 salesmen in the furniture department of a North American retail sales store during the 1950s. Blockmodelling procedures are used to identify structural positions in the networks, and log‐linear analysis is applied to determine stability of choices within and between structural positions. The results support the mimetic trust and the advisory trust hypothesis.