Negative Ties in Organizational Networks

An employee retention model using organizational network analysis for voluntary turnover

Contemporary research of employee social network analysis has grown far beyond the conventional wisdom of network and turnover theory; however, what is missing is a comprehensive review highlighting new perspectives and network constructs from a retention viewpoint. Since turnover is a concurrent component of retention, the analysis of the factors of quit propensity can result in a pre-emptive strategy for retention. This paper aims to capture the current state of the field and proposes a conceptual model for retention by exploring network position, centrality measures, network type, and the snowball effect. We identified 30 papers exploring voluntary turnover in social network constructs. Findings show that central network position is not always associated with negative turnover. Eigenvector, structural holes, and K-shell also prove to be a strong predictor of turnover. The snowball turnover of employees in similar network positions is pronounced in scenarios where employee sentiment is negative with poor group efficacy, entrepreneurship, and group values. This paper focuses on several themes to coalesce different determinants of an organizational network to demonstrate how social network theory has evolved to predict employee turnover. The resulting conceptual model suggests how to identify star performers and propose retention strategies.

Promoters versus Adversaries of Change: Agent-Based Modeling of Organizational Conflict in Co-Evolving Networks

The social adoption of change is usually hard because in reality, forces opposing the social adoption of change manifest. This situation of organizational conflict corresponds to the case where two competing groups of influential agents (“promoters” versus “adversaries” of change) operate concurrently within the same organizational network. We model and explore the co-evolution of interpersonal ties and attitudes in the presence of conflict, taking into account explicitly the microscopic “agent-to-agent” interactions. In this perspective, we propose a new ties-attitudes co-evolution model where the diffusion of attitudes depends on the weights and the evolution of weights is formulated as a “learning mechanism” (weight updates depend on the previous values of both weights and attitudes). As a result, the co-evolution is intrinsic/endogenous. We simulate representative scenarios of conflict in 4 real organizational networks. In order to formulate structural balance in directed networks, we extended Heider’s definition of balance considering directed triangles. The evolution of balance involves two stages: first, negative links pop up disorderly and destroy balance, but after some time, as new negative links are formed, a “new” balance is re-established. This “new” balance is emerging concurrently with the polarization of attitudes or domination of one attitude. Moreover, same-minded agents are positively linked and different-minded agents are negatively-linked. This macroscopic self-organization of the system is due only to agent-to-agent interactions, involving feedbacks on weight updates at the local microscopic level.

The effect of social network ties on performance: a moderated mediation model

Purpose

The purpose of this paper is to adapt the job demands–resources perspective to extend social network literature by examining the effectiveness of psychological (work engagement and emotional exhaustion) and instrumental (access to benefits) mechanisms as mediators of the relationship between employees’ centrality in positive and negative ties networks and job performance.

Design/methodology/approach

The survey data were collected from 103 employees working at a public bank in three stages.

Findings

The study results supported the hypotheses that an individual’s centrality in a negative network increases his/her experience of emotional exhaustion, while individual centrality in a positive network increases his/her work engagement. In addition, the findings showed that centrality in positive networks will be more predictive of work engagement when negative ties centrality increases, and the relationship between centrality in the negative network and emotional exhaustion is weaker when centrality in the positive network is higher.

Originality/value

The study extends out to the social ledger model (Labianca and Brass, 2006) by examining the dual pathways of effects of positive and negative ties in predicting employee outcomes. In addition, the authors’ model enriches the understanding of the nature of social network ties more broadly by suggesting that its effects in the workplace can extend beyond psychological effects to include instrumental impact.

Structural balance emerges and explains performance in risky decision-making

Polarization affects many forms of social organization. A key issue focuses on which affective relationships are prone to change and how their change relates to performance. In this study, we analyze a financial institutional over a two-year period that employed 66 day traders, focusing on links between changes in affective relations and trading performance. Traders’ affective relations were inferred from their IMs (>2 million messages) and trading performance was measured from profit and loss statements (>1 million trades). Here, we find that triads of relationships, the building blocks of larger social structures, have a propensity towards affective balance, but one unbalanced configuration resists change. Further, balance is positively related to performance. Traders with balanced networks have the “hot hand”, showing streaks of high performance. Research implications focus on how changes in polarization relate to performance and polarized states can depolarize.

How do socially polarized systems change and how does a change in polarization relate to performance? Using instant messaging data and performance records from day traders, the authors find that certain relations are prone to balance and that balance is associated with better trading decisions.

Urban occupational structures as information networks: The effect on network density of increasing number of occupations

Urban economies are composed of diverse activities, embodied in labor occupations, which depend on one another to produce goods and services. Yet little is known about how the nature and intensity of these interdependences change as cities increase in population size and economic complexity. Understanding the relationship between occupational interdependencies and the number of occupations defining an urban economy is relevant because interdependence within a networked system has implications for system resilience and for how easily can the structure of the network be modified. Here, we represent the interdependencies among occupations in a city as a non-spatial information network, where the strengths of interdependence between pairs of occupations determine the strengths of the links in the network. Using those quantified link strengths we calculate a single metric of interdependence–or connectedness–which is equivalent to the density of a city’s weighted occupational network. We then examine urban systems in six industrialized countries, analyzing how the density of urban occupational networks changes with network size, measured as the number of unique occupations present in an urban workforce. We find that in all six countries, density, or economic interdependence, increases superlinearly with the number of distinct occupations. Because connections among occupations represent flows of information, we provide evidence that connectivity scales superlinearly with network size in information networks.

A Two-Wave Study of Self-Monitoring Personality, Social Network Churn, and In-Degree Centrality in Close Friendship and General Socializing Networks

We examine the role of self-monitoring personality in shaping network change in two important types of social relationships. In a two-wave social network study, we find that individuals with higher levels of self-monitoring derive persistent personality-linked in-degree centrality benefits in the general socializing network but have fading benefits over time in the close friendship network. Simultaneous examination of the formation and dissolution of relationships over time (network churn) reveals that this pattern of network change is shaped by differential reactions of relationship partners to individuals based upon level of self-monitoring in the two network types. Overall, by incorporating the dynamic reactions of relationship partners, the findings contribute to the understanding of the complex relationship between personality and social network development.