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Interorganizational partner selection decisions are plagued with uncertainty. When making partnering decisions, firms strive to answer two questions: does the prospective partner have resources which can be used to generate value in the relationship; and will the partner be willing to actively share these resources and cooperate in good faith? Answers to these questions help reduce three types of uncertainty – partner capability uncertainty, partner competitiveness uncertainty and partner reliability uncertainty. For a relationship to benefit both partners, they have to possess complimentary resources of comparable quality, avoid explicit competition as well as be willing to engage in the cooperative behaviors within the confines of their relationship. In this paper, we examine the importance of prospective partners’ characteristics (differences in size, status and specialization) as well as their network characteristics (existence of a common partner and membership in the same clique) to the formation and longevity of their social relationships, as these characteristics reduce firms’ value generation and partner reliability uncertainty.

Boundary-spanning exploration through establishing alliances is an effective strategy to explore technologies beyond local search in innovating firms. The purpose of this paper is to argue that it is useful to make a distinction in boundary-spanning exploration between what a firm learns from its alliance partners (explorative learning from partners (ELP)) and what it learns from other organisations (explorative learning from non-partners (ELN)).

The authors contend that alliances play a role in both types of exploration. More specifically, the authors discern three types of alliances (inside ties, clique-spanning ties and outside ties) based on their role vis-à-vis existing alliance cliques. Clique members are highly embedded, and breaking out of the cliques through clique-spanning and outside alliances is crucial to improving explorative learning. Thereafter, the authors claim that clique-spanning ties and outside ties have a different effect on ELN and ELP.

The empirical analysis of the “application specific integrated circuits” industry indicates that inside ties have negligible effects on both types of explorative learning. Clique-spanning ties have a positive effect on ELP, but not on ELN. The reverse is true for outside ties. The results show that research on explorative learning should devote greater attention to the various roles alliance partners and types of alliances play in advancing technological exploration.

The literature only emphasises the learning from partners, focussing mainly on accessing their technology. In sum, alliance partners play different roles in exploration, and their network position influences the role they are able to play.

We introduce a multi-level model of the dependence of interfirm network topologies on the distribution and commonality of information in a network and the information strategies pursued by its member firms. Network topology, information properties of the network, and firm-level action within the network form dynamic, recursive, cross-level relationships – information properties in the network determine firm-level action, which in turn impacts the network topology and information properties. We derive predictions about the kinds of information strategies that firms are likely to adopt and succeed with in different information regimes, and about the kinds and short- and long-run dynamics of network topologies expected under different information regimes. Our model sheds new light on network topologies as a dependent variable that can be explained by network-level information regimes and firm-level information strategies.

The purpose of this paper is to examine the microcredit system, social networks within self-help groups (SHGs) and micro-entrepreneurial activities at the grassroots aiming at well-being, sustainability and income generation. The empirical study took place in Phnom Penh.

Focus group and in-depth interviews were employed. Two SHGs in Phnom Penh were selected for this study. The social network approach was used to distinguish the type of nodes and cliques within SHGs.

The result suggests that there exist lending and borrowing nodes and cliques. Strong ties exist within a clique and only weak ties link between cliques. Job and business information transmits well on weak ties but not entrepreneurship. This explains the failure of the process of microcredit in fostering microenterprise among very poor and low-educated borrowers.

The findings were based on a small sample from two SHGs. Further study is needed for justification of the findings.

It was original research which took place in Phnom Penh. Homogeneous lending and borrowing cliques in microcredit networks were identified. A model of hierarchical microcredit network was hypothesized to explain how some members of a SHG are able to utilize the credit in starting up their microbusinesses while others failed.

Purpose – Organizational and work studies consistently find an interrelationship between employees' relationships with coworkers to their morale, as indicated by their satisfaction and commitment levels. This same research shows organizational climate, as indicated by levels of trust and shared values and norms in the organization, strongly benefiting from satisfied and committed employees.Methodology/approach – This chapter concretizes workplace relationships using multipanel network data from 15 Indianapolis charter school teachers.Findings – With these data, network traits related to network cohesion, strong ties, and in-group identity identified as central processes undergirding affective relationships are directly tested. A feedback loop between organizational climate and employee morale, where both mutually reinforce the other, is also discussed.Implications – These findings show that affective relationships with coworkers improve employee morale and organizational climate.

Purpose – I suggest that we conceptualize labor markets as observable social networks, in which workplaces are the nodes and people moving between workplaces are the edges. The movement of people delivers the actionable information as to what the supply, demand, and going wage for labor might be. Labor market networks are hypothesized to be quite thin thus leading to substantial wage setting autonomy within workplaces, consistent with contemporary observations in both economics and sociology as to the weakness of labor market signals.Method – This paper reviews theoretical and empirical work in economics, sociology, and network science and develops a network image of labor market structure and function. Hypotheses derived from economic, sociological, and network theories are proposed to explain workplace-level wage setting.Findings – Information flow, trust in information, information variance, collusion, and status beliefs are all proposed as important network properties of labor markets. The paper outlines an observational strategy to make labor markets scientifically observable.Originality – Economists and sociologists often refer to labor markets as mechanisms setting the price of labor but rarely observe them. This paper outlines a strategy for making the invisible hand of the market scientifically observable.

The purpose of this paper is to show the role of social networks in mobilizing how actors both impact and are impacted on by their colleagues. It seeks to compare the human resource management (HRM) academic community with two other comparable communities, and to identify those groups that are seen to work closely together.

It is shown how social network analysis (SNA) can be utilized to analyse data in social networks, shedding light on the cliques and networks of people that work together over a period of time. This is based on an analysis of co‐authored papers in the field of HRM between 1990 and 2005.

It is shown how the HRM community has developed over time utilizing various SNA metrics and this community of scholars is shown to be less “dense” than comparable academic networks, being made up of several weakly‐linked subcomponents. The paper also identifies the “ego‐nets” of individuals that are indicative of different publishing strategies.

The paper's contribution lies in the application of SNA to identify how groups interact over time, and how a large network can be systematically analysed to reveal the underlying structure.

Social media platforms play a key role in information propagation and there is a need to study the same. This study aims to explore the impact of the number of close communities (represented by cliques), the size of these close communities and its impact on information virality.

This study identified 6,786 users from over 11 million tweets for analysis using sentiment mining and network science methods. Inferential analysis has also been established by introducing multiple regression analysis and path analysis.

Sentiments of content did not have a significant impact on the information virality. However, there exists a stagewise development relationship between communities of close friends, user reputation and information propagation through virality.

This paper contributes to the theory by introducing a stagewise progression model for influencers to manage and develop their social networks.

There is a gap in the existing literature on the role of the number and size of cliques on information propagation and virality. This study attempts to address this gap.

The purpose of this paper is to report the results from a study that investigated the extent to which an intervention to develop a community of library and information science (LIS) researchers – the Developing Research Excellence and Methods (DREaM) project – was successful in meeting its main objective three years after its implementation. Of particular interest are factors that support or hinder network longevity.

Data were collected by online survey/telephone and focus group. From quantitative data, a social network analysis (SNA) and network diagrams were generated. Focus group discussions were recorded and transcribed, and data from these were analysed manually.

Three years after the end of its formal funding period, DREaM endured as a loose but persistent network. Social ties were more important than work ties, and network members with the highest network centrality held roles in academic institutions. Physical proximity between members was important to the maintenance of network ties. Actor status did not appear to have a bearing on network centrality.

Discussion is limited to consideration of community development amongst core members of the network only. The “manufactured” nature of the DREaM network and unique context in which it was formed have implications for the generalisibility of the findings reported.

Social infrastructure is key to the long-term health of a network initiative. Continued ad hoc support would strengthen it further.

The findings add to understanding of factors important to the development of scholarly and learning communities. They extend contributions of earlier work that has deployed SNA techniques in LIS research and research in other fields.

The purpose of this study is to determine whether women entrepreneurs are satisfied with belonging to a women’s network, as this issue is crucial for network performance and legitimacy.

The authors tested the hypotheses on a sample of 127 French women entrepreneurs who belonged to women’s networks using multiple regression analysis.

The authors showed that these women entrepreneurs were satisfied when they developed strong ties and when cliques in the network were limited. Education had a negative effect: the higher the educational level, the less satisfaction with their networks the women reported.

The sample was small and composed only of women entrepreneurs who were members of women’s networks and not women who had left them.

The survey findings suggest ways that managers can optimize network satisfaction to keep current members while continuing to add new ones: create an environment with no cliques where members can develop strong ties. This means connecting members with similar values or status and common interests, while making sure that cliques do not develop.

To the authors’ knowledge, satisfaction with professional women’s networks has never been studied. The authors’ highlight the role of strong ties in these networks and identify the contingent effect of cliques.