The Benefits and Pitfalls of Social Capital: Empirical Evidence from Two Organizations in the United Kingdom *

Recently, there has been a shift in the way management scholars view the firm, from traditional models that are based on ideas of opportunism and market failure to newer knowledge‐based theories that argue for a more socialized perspective. One of the key components of these theories is the notion of social capital. Social capital is the set of resources that accrue to an individual or group by virtue of their social connections. As such, it is a resource that is jointly owned. Most recent research adopts a more‐is‐better approach to social capital, suggesting that individuals with larger quantity of ties derive more positive benefits. However in this paper, we argue that using social capital has both benefits and drawbacks for organizations, and that these positive and negative aspects of social capital occur simultaneously. To substantiate our claim, we use data collected from sets of interviews with senior and middle managers in two organizations in the United Kingdom. Our findings indicate that while social capital has many beneficial effects with respect to information access and retrieval, community building, and underlying group norms, there are also a number of less‐beneficial aspects, which are under‐explored in the current empirical literature. Furthermore, we suggest that organizations must develop an understanding of the bridging and bonding elements of social capital, as these are critical for its implementation. Implications of the research findings and future research directions are discussed.     

Psychosocial safety climate as an antecedent of work characteristics and psychological strain: A multilevel model

Abstract

Psychosocial safety climate (PSC) refers to a specific organizational climate for the psychological health of workers. It is largely determined by management and at low levels is proposed as a latent pathogen for psychosocial risk factors and psychological strain. Using an extended Job Demands-Control-Support framework, we predicted the (24 month) cross-level effects of PSC on psychological strain via work conditions. We used a novel design whereby data from two unrelated samples of nurses working in remote areas were used across time (N=202, Time 1; N=163, Time 2), matched at the work unit level (N= 48). Using hierarchical linear modelling we found that unit PSC assessed by nurses predicted work conditions (workload, control, supervisor support) and psychological strain in different nurses in the same work unit 24 months later. There was evidence that the between-group relationship between unit PSC and psychological strain was mediated via Time 2 work conditions (workload, job control) as well as Time 1 emotional demands. The results support a multilevel work stress model with PSC as a plausible primary cause, or “cause of the causes”, of work-related strain. The study adds to the literature that identifies organizational contextual factors as origins of the work stress process.     

Masquerading in the U.S. Capital Markets: The Dark Side of Maintaining an Institution

This article examines the work of professional service firms (PSFs) in their relationships with public corporations; work that is designed to ensure that investors and potential investors have information that will enable them to participate in the capital markets. Using an institutional theory lens, we view these efforts by PSFs as institutional maintenance work and specifically analyze their work related to policing (i.e., rating), enabling (i.e., tutoring), and embedding and routinizing (i.e., collaborating) that helps to support the capital market as a core institution in society. We illustrate how there is a “dark” side to each of these forms of institutional work that exists because of ongoing conflicts of interest within and between their work practices. This dark side has the unintended consequence of producing often biased information or information unavailable to many. When a crisis brings this bias to light, some repair is introduced but often not enough to alleviate the distortion. Our contribution is, therefore, to shed light on the dark side of institutional maintenance work and to explore why repair is increasingly necessary, but often only partially effective.     

Model Selection When a Key Parameter is Constrained to be in an Interval

This article considers model selection procedures based on choosing the model with the largest maximized log-likelihood minus a penalty, when key parameters are restricted to be in a closed interval. Its main emphasis is how these penalties might be chosen in small samples to give good properties of the resultant procedure. We illustrate two model selection problems in the context of Box–Cox transformations and their application to the linear regression model. Simulation results for both problems indicate that the new procedure clearly dominates existing procedures in terms of having higher probabilities of correctly selecting the true model.