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Blockmodeling is viewed often as a data reduction method. However, this is a simplistic view of the class of methods designed to uncover social structures, identify subgroups, and reveal emergent roles. Worse, this view misses the richness of the method as a tool for uncovering novel human resource management (HRM) insights. Here, we provide a brief overview of some essentials of blockmodeling and discuss research questions that can be addressed using this approach in applied HRM settings. Finally, we offer an empirical example to illustrate blockmodeling and the types of information that can be gleaned from its implementation.

The paper aims to examine Karl Polanyi's view of market evolution in the context of the emergence of a national grain market in China's transition economy.

The dataset used includes information about inter‐provincial grain trade on China's grain market from November 1999 to October 2000. A priori blockmodelling method is used for hypothesis testing.

This paper finds that a partially integrated national grain market had emerged at the beginning of the twenty‐first century in China in spite of local protectionism. Additionally, the emergence of this market is found to be partly a result of the reform‐oriented state's attempt to create national wholesale grain markets.

The findings of the paper might have implications for market development in both China and other transition economies.

Economic agents in systems (individuals, firms, government organizations, etc.) engage in a wide range of cooperative activities that may be mapped as networks. This paper aims at determining whether alliances embedded in such networks show higher densities of interaction between agents than other network subsets.

This paper uses the blockmodeling technique on a unique sample of armed forces that have engaged in repeated cooperative behaviour over a decade.

This study finds that the alliance in the sample does exhibit a significantly higher density of interaction than the rest of the network.

Using blockmodeling may be necessary, but not sufficient, to ascertain the presence of undisclosed alliances in networks.

This work is useful for the detection of potential or actual collusive behaviour in the form of higher densities of interactions between agents in systems.

Blockmodeling, as a technique, and agents like armed forces, as a sample, are uncommon occurrences in the contemporary cybernetics and general systems literature. This paper provides novel insights to research on collaborative behaviour.

In this paper, I demonstrate an alternative explanation to the development of the American electricity industry. I propose a social embeddedness approach (Granovetter, 1985, 1992) to interpret why the American electricity industry appears the way it does today, and start by addressing the following questions: Why is the generating dynamo located in well‐connected central stations rather than in isolated stations? Why does not every manufacturing firm, hospital, school, or even household operate its own generating equipment? Why do we use incandescent lamps rather than arc lamps or gas lamps for lighting? At the end of the nineteenth century, the first era of the electricity industry, all these technical as well as organizational forms were indeed possible alternatives. The centralized systems we see today comprise integrated, urban, central station firms which produce and sell electricity to users within a monopolized territory. Yet there were visions of a more decentralized electricity industry. For instance, a geographically decentralized system might have dispersed small systems based around an isolated or neighborhood generating dynamo; or a functionally decentralized system which included firms solely generating and transmitting the power, and selling the power to locally‐owned distribution firms (McGuire, Granovetter, and Schwartz, forthcoming). Similarly, the incandescent lamp was not the only illuminating device available at that time. The arc lamp was more suitable for large‐space lighting than incandescent lamps; and the second‐generation gas lamp ‐ Welsbach mantle lamp ‐ was much cheaper than the incandescent electric light and nearly as good in quality (Passer, 1953:196–197).

This study aims at analyzing the features of knowledge flow and the role-specific nodes in knowledge networks among individuals and business units of six organizations in different industries, and suggesting prescriptions to prevent the organizational knowledge sclerosis.

This research conducts multiple case studies on the organizational knowledge paths of six companies in the multiple industries through social network analysis (SNA) tool developed by the authors of this paper.

This study provides four major findings which shed a new light on how to comprehend the features of knowledge flow and the role-specific nodes in knowledge networks in organizations: the within-business unit knowledge flows are more dominant over the inter-business units knowledge flow; the downward knowledge flows are dominant over the horizontal and upward knowledge flows in the management levels; distributions of knowledge owners and providers are like L-shape and the gap between knowledge owing and providing expands as the management levels go up; and the top 20 percent people in an organization dominate over a large portion of the knowledge brokerage activities.

Cultural difference issue might arise because data collection was limited to Korean organizations. Therefore, the findings from this study needs to be cautiously interpreted considering the cultural difference/deeper understanding of the organizational knowledge paths through social network lens can make it possible for more context-specific KM strategies (e.g. suitable for a specific functional unit, management level, or industry type) to be identified and implemented.

Managers can have a solid grasp about knowledge flows and knowledge node roles in their organization through social network analysis in order to facilitate the knowledge transfer and eliminate the knowledge link lapse in organizations.

This study could be a stepping stone for further empirical research since it expanded the level of organizational knowledge network analysis from individual and team to inter-unit and inter-management level through the block modeling analysis of knowledge network.

This commentary addresses the problem of interfirm network formation from the perspective of multiple types of relationship content and of network structure. The approach builds on Burt’s (1980) typology of network structures and on a range of empirical studies on interorganizational networks. The chapter by Moldoveneau, Baum and Rowley on network evolution from an information-sharing perspective captures part of this research domain. The challenges posed by network evolution research are discussed in the broader light of multilevel analysis.

Network analysis is a well consolidated research area in several disciplines. Within management and organizational studies, network scholars consolidated a set of research practices that allowed ease of data collection, high inter case comparability, establishment of nomological laws and commitment to social capital motivation. This paper aims to elicit the criticism it has received and highlight the unsettled lacunae.

This paper sheds light on Network Analysis’s breakthroughs, while showing how its scholars innovated by responding to critics, and identifying outstanding debates.

The paper identifies and discusses three streams of criticism that are still outstanding: the role of human agency, the meaning of social ties and the treatment of temporality.

This paper brings to fore current debates within the Network Analysis community, highlighting areas where future studies might contribute.

Research on organizational innovation remains relatively scarce, particularly with respect to social structures and processes. In contrast to product innovation, organizational innovation relies more on informal processes and relationships among members of the organization than on formal processes. The purpose of this paper is to contribute to the understanding of these processes at the micro level.

Building on a process model of organizational innovation, the authors study the case of a dermatology department of a large hospital in France and conceptualize organizational innovation as the outcome of a social system represented by networks of relationships, professional identities and formal structures.

The findings suggest that informal networks support the early phase of the invention and development of organizational innovation. However, the later phases depend more on the formal structure. A mismatch between professional identities and formal roles and positions can prevent the institutionalization and legitimation of organizational innovation in the final phases of the innovation process.

The study is limited to one case, a department in a French hospital. The authors call for future research to study different industry/country contexts.

Professional organizations such as hospitals should encourage better interactions between actors of different professional identities to support the development and implementation of organizational innovation. Reducing the perceived hierarchy of different professional identities may also be useful.

This study is the first to investigate micro-level processes in organizational innovation by combining the concept of professional identity and network analysis.