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This chapter discusses the empirical application of a class of strategic network formation models, using the approach to identification introduced by de Paula, Richards-Shubik, and Tamer (2018). The author emphasizes the interplay between model specification and computational complexity, and suggests tactics to make empirically realistic models become tractable. Two detailed examples, on friendship networks and coauthorship networks, are used to illustrate these issues and to demonstrate the performance of the approach with both simulation and empirical evidence. Also, the author presents extensions to the estimation method, which expand the potential range of applications, and which provide statistical inference with minimal computational burden.

This article canvasses the components that go to define the concept of governance and develops a framework to provide a coherent explanation of the dynamics of governance and the relationship between its many modes. To illustrate the validity of the governance framework, the paper focuses on the three primary patterns of governance as found in the “real” world; namely markets, hierarchies and networks. The impact of public management reforms of the past two decades is analysed in terms of these patterns of governance and a couple of specific reforms are looked at more closely. Through such discussion, it is possible to gain an appreciation of how the proposed JEWAL synthesis framework can help explain the dynamics of governance both at the level of society and at the level of groups or organizations. Finally, it is demonstrated how the framework is also applicable to governance of the individual’s personal life.

The study seeks to classify retailer‐driven clothing supply networks to provide new insights on their structure and operation and examine whether or not differences are evident in the types of networks operated by different types of retailer.

A large‐scale empirical investigation is conducted of 73 supply networks operating with 26 Sri Lankan apparel manufacturers, representing 39 major retailers. In‐depth interviews and survey methods are used, representing qualitative and quantitative approaches, respectively.

Six primary types of clothing supply network are identified. A strong association is shown between retailer type and network type, specifically for networks operated by established brand retailers and by value players such as supermarket retailers. The typical attributes of the supply networks of each type of retailer are compared.

Although the empirical study is large, it is limited to supply networks with prime manufacturing partners located in Sri Lanka. The country is important in global clothing production, serving many prominent global retailers. Studying and comparing supply networks anchored in other regions will provide a valuable comparison with the findings here.

The study has implications for clothing retailers in analyzing, managing and developing their networks. For manufacturers, it provides insights to understand the network structures operated by different types of retailer for different classes of garment. The study also offers insights for policy makers in clothing producing regions.

A new empirically based classification is presented for clothing supply networks. The diversity in network types has not previously been shown. The comparison of networks of established brand retailers and value players provides empirical evidence of differences not reported previously. The findings enrich both the theoretical and empirical bases for sector‐specific supply network studies.

The purpose of this paper is to attempt to calculate the trust degree between two enterprises in an industrial network using grey correlation degree algorithm for exploring characteristics of community structure and evolution rules of cluster cooperation networks in axle‐type and satellite‐type clusters.

Starting from analysis of trust formation mechanism of inter‐enterprise in industrial networks, adjacency of inter‐enterprise relationship, their information acquisition ability, their influence power in network and their past interaction experience are chosen as influencing factors of the trust between two enterprises. Grey correlation degree algorithm was chosen to calculate the trust degree between two enterprises in an industrial network. According to the rules of dynamic adjustment of trust degree originated from thoughts of the prisoners' dilemma model, computer simulation is applied to explore characteristics of community structure and evolution rules of cluster cooperation network in axle‐type and satellite‐type clusters.

With the dynamic adjustment of enterprises' trust degree, the network density of axle‐type and satellite‐type cluster networks was decreasing as the cluster scale was enlarging, and eventually tended to be stable; community structure was emerged in axle‐type and satellite‐type industrial clusters as the cluster scale was enlarging; community characteristics were obviously stronger in axle‐type cluster networks than in satellite‐type; communities were overlapped in axle‐type cluster networks, that is, bridge nodes emerged between communities.

This paper is the first to apply the grey correlation degree algorithm to calculate the trust degree between two enterprises in cluster networks for designing the rules of dynamic adjustment of trust degree.

Describes how the huge problems of managing a large telecommunications network have been addressed in the development of a proprietary system called NETWORKS. Discusses the user′s mental model. Describes a network object model. Presents examples of how object‐oriented graphics can be applied to network management tasks.

This paper aims at investigating the multifaceted nature of innovation networks by focusing on two research questions: Do cluster actors exchange only one type of innovation-related knowledge? Do cluster actors play different roles in innovation-related knowledge exchange?

This paper builds on data collected at the firm level in an Italian aerospace cluster, that is a technology-intensive industry where innovation is at the base of local competitiveness. A questionnaire was used to collect both attribute data and relational data concerning collaboration and the flows of knowledge in innovation networks. The authors distinguished among three types of knowledge (technological, managerial and market knowledge) and five types of brokerage roles (coordinator, gatekeeper, liaison, representative and consultant). Data analysis relied on social network analysis techniques and software.

Concerning the first research question, the findings show that different types of knowledge flow in different ways in innovation networks. The different types of knowledge are unevenly exchanged. The exchange of technological knowledge is open to everyone in the cluster. The exchange of market and managerial knowledge is selective. Concerning the second research question, the authors suggest that different types of cluster actors (large firms, small- and medium-sized enterprises, research centers and universities and institutions for collaboration) do play different roles in innovation networks, especially with reference to the three types of knowledge considered in this study.

The present paper has some limitations. First of all, the analysis focuses on just one cluster (one industry in one specific location), cross- and comparative analyses with other clusters may illuminate the findings better, eliminating industry and geographical biases. Second, the paper focuses only on innovation-related knowledge exchanges within the cluster and not across it.

The results have practical implications both for policy makers and for managers. First, this research stresses how innovation often originates from a combination of different knowledge types acquired through the collaboration with heterogeneous cluster actors. Further, the analysis of brokerage roles in innovation-driven collaborations may help policy makers in designing programs for knowledge-transfer partnerships among the various actors of a cluster.

The paper suggests a clear need of developing professional figures capable of operating at the interface of different knowledge domains.

The data illuminate several aspects of how innovation takes place in a cluster opening up intriguing aspects that have been overlooked by extant literature. The authors believe that this may trigger several lines of further research on the topic.

The purpose of the study is to empirically analyze how various types of foreign networks influence the internationalization performance of Korean small and medium enterprises (SMEs). The specific aim is to investigate the impact of each network type (family and friends, clients (buyers, vendors, etc.), potential buyers contacted through an Internet search for export, acquaintances from trade shows and fairs and acquaintances from government organizations) on internationalization performance outcomes, such as financial performance, financial performance satisfaction and strategic performance.

To identify influential foreign networks, multiple regression analysis was conducted. The sample consisted of 484 exporting Korean SMEs.

The results emphasized the role of business networks with clients in enhancing financial performance, financial performance satisfaction and strategic performance of Korean SMEs in international markets.

The research contributes to the expansion of SME internationalization literature by identifying various types of foreign networks used in international markets and revealing their differential roles on the internationalization performance of Korean SMEs.

The purpose of this paper is to integrate scholarship on personality, mentoring, developmental relationships, and social networks in delineating how employees with particular personality characteristics are more or less likely to be involved in four types of developmental networks.

The paper reviews scholarship on personality characteristics and developmental relationships to identify a set of distinct personality characteristics proposed to be related to employees' tendencies to develop four types of developmental networks. These network types are defined based on high or low relationship strength and high or low relationship diversity in employee ties with others. We develop propositions delineating the nature of expected relationships of these personality characteristics with developmental network types.

The paper identifies five personality characteristics – interdependent/independent self‐construal, core self‐evaluations, openness to experience, conscientiousness, and extroversion/introversions – and explained how each should be related to employees' tendencies to develop the four types of developmental networks. These networks have been described as opportunistic, entrepreneurial, receptive, and traditional developmental networks, based upon the strength and the diversity of network relationships.

The paper suggests that personality variables are potentially valuable for understanding how individuals develop particular types of developmental relationships, an area that deserves more research attention. It is noted that developmental relationships have been shown to be related to both employees' objective career outcomes such as promotions and salary progress, and subjective outcomes such as career and job satisfaction.

The purpose of this paper is to suggest that business group (BG) networks act as conduits for diffusion of information and resources pertaining to internationalization. It considers three types of BG networks arising from three different types of ties- director interlock, direct equity, and indirect equity. In particular, it examines the effects of cohesiveness of these BG networks on the diffusion of internationalization within a BG.

Drawing on social network perspective, it is hypothesized that, for each type of network, cohesiveness enhances within-BG similarity of the extent of internationalization. An empirical investigation is conducted on a sample of 55 Indian BGs for the period 2009-2013.

Results support all the three hypotheses, suggesting that higher level of cohesiveness leads to higher level of within-BG similarity of the extent of internationalization, for all three network types.

Findings of this study contribute to the BG literature by examining the effects of BG network cohesiveness on the diffusion of internationalization within a BG, for three types of BG networks.

The purpose of this paper is to bring clarity to the concept of social capital in the value creation in firms from the knowledge management perspective. To discuss the social characteristics of different types of knowledge.

Based on a review of the literature, it is argued that different types of knowledge have the distinctive logic of value creation and social capital. Social capital is seen as a network of individuals with shared norms, beliefs and trust.

The social network structure for explicit knowledge is centralized and maintained by clearly defined rules, beliefs in high quality and trust in organizational hierarchy. The social network structure for tacit knowledge is distributed and maintained by the norms of reciprocity, beliefs in lifelong learning and an incremental trust. Finally, the social network structure for emergent, potential knowledge is decentralized and maintained by liberal norms, beliefs in innovativeness and an enabling type of trust.

This paper helps to understand the role of social capital in the value creation of a firm and the connections between different types of knowledge and their corresponding types of social characteristics.

This paper presents a holistic approach to explicit, tacit and potential types of knowledge and the argument that all are needed. It is stated that these three types of knowledge form a basis for three management systems of firms.