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The purpose of this chapter is to describe the rationale for and structure of organizational networks in support of traffic safety programming. It outlines the operational considerations and approaches important to both understanding network-based partnerships and improving their functionality. The chapter draws on conceptual and empirical studies of organizational networks in order to enhance the effectiveness of networks and integrate network-based approaches with the cultural orientation already present in traffic safety research and practice.

This chapter proceeds from the premise that, increasingly, efforts to impact traffic safety behaviors will be interconnected with other concerns, and that traffic safety initiatives will require engagement with organizations focused on concerns other than traffic safety. The implication of the ideas examined in this chapter is that traffic safety agencies will need to focus not just on traffic-related behaviors, but also on the strategic and operational coordination with other organizations. Doing so has the potential to create synergies that would be unachievable if agencies operation in isolation.

Past studies suggest that full-time maternal employment may be negatively related to children’s cognitive development. Most studies measure maternal employment at one time point, while mothers’ work hours may not be stable during early childrearing years. Using data from the 2001 Early Childhood Longitudinal Study – Birth Cohort (N ≈ 6,500), the authors examine stability in mothers’ work hours across four waves when children are 9 and 24 months old, in preschool, and in kindergarten, mothers’ background characteristics associated to it, and its link to child cognitive development. Results show that the majority of mothers change work hours across the four waves. Analysis using multinomial logistic regression models suggests that mothers’ older age, fewer children, and higher household income are related to working full time at all four waves compared to varying work hours across the waves; more children and less than high school completion are related to staying home at all four waves; and mothers’ older age, being White, no change in partnership status, and holding a college degree are related to working part time at all four waves. Compared to mothers’ changing work hours, mothers’ stable work hours, full time or part time, at all four waves is related to children’s better reading, math, and cognitive scores in kindergarten, whereas mothers’ staying home at all four waves is negatively related to these scores. These associations disappear when background characteristics are controlled for in ordinary least squares regression models. These findings underscore the role of background characteristics in shaping both mothers’ stable employment and children’s cognitive development.

This study aims to examine the relationship between Achievement Motivation (AM), Smart Work (SW), and human resources (HR) performance. It questions how moral global leadership (MGL) could moderate the relationship between AM, SW, and HR performance. A theoretical model was developed and tested on sample data representing 219 employees, educators, and educational staff of Islamic Higher education (IHE). The data were collected through surveys and applied to structural equation modeling using SEM-PLS. This study found that AM and SW significantly affect HR performance. While MGL substantially moderates the relationship between AM, SW, and HR performance. This study contributes to the literature on MGL, AM, and SW in creating HR performance that has yet to be studied so far. This study offers the concept of MGL, which plays a central role in moderating the relationship between AM, SW, and HR performance.

To resolve an inherent dilemma in extant research on geographically dispersed research and development (R&D), this study explores interdependencies between formal and informal network structures. Firms that seek to benefit from the decentralization associated with disperse R&D must align it with an informal structure that enhances organizational members’ motivation to share and assimilate their unique knowledge and skills. On the basis of an investigation among 424 US biotechnology firms between 1973 and 2003, this study reveals the moderating effect of the firm’s informal social structure on the effect that geographically dispersed R&D personnel have on the exploration of new technological opportunities. Specifically, the higher the social network density among R&D members, the more likely geographic disparity is to affect exploration; however, this likelihood decreases with an increase in power asymmetries. These results offer insights into the conditions in which the appropriate management of geographically dispersed R&D varies.

This paper draws upon the idea that an organisation can be understood as an open system embedded in a larger social system. We propose that geographical proximity is a key determinant of the porous boundaries of organisations. Proximity produces repeated, trusting and long-term perspective relationships. Consequently, clustered firms (i.e. in an industrial district) develop relevant relations and interactions within this social system. Firms acquire new resources and capabilities using external endowments. In an industrial district, firms benefit from a common reputation, from an intense exchange and combination of resources, and the presence of different local institutions. As a result, firms in the industrial district may improve innovation and net-value creation capacities, which explain the competitive superiority of these firms. Our study draws on an empirical study involving a sample of 350 Spanish industrial firms in which we compared district and non-district member firms. Findings suggest relevant conclusions with respect to our theoretical propositions.

The purpose of this chapter is to provide a comprehensive analysis of how sentiments may be a part of, or adjacent to, status generalization. We demonstrate why this problem is so difficult to solve definitively, as many resolutions may exist. Sentiments may present the properties of graded status characteristics but may also be disrupted by processes of the self. Sentiments may have status properties enacted within dyadic interactions. However, sentiments may also be status elements during triadic constellations of actors. Finally, we discuss current research that is underway to provide more empirical evidence to offer confirmation or disconfirmation for some of our proposed models.

We provide a synthesis of literatures, including pieces from group processes, neuroscience, psychology, and network scholarship, to address the relation between sentiment and status processes. Accordingly, this is a conceptual chapter.

We attempt to motivate future research by exploring the many complications of examining these issues.

Understanding how social inequalities may emerge during group interaction allows researchers to address their deleterious effects. Positive sentiments (in other words, “liking”) should bring actors closer together to complete tasks successfully. Ironically, when paired with negative sentiments within task groups, inequalities in group opportunities may result. To address these social inequalities, a thorough understanding of how they develop is necessary, so that efficacious interventions can be adopted.

This deep dive into the relation between sentiment and status processes joins the 25-year quest to understand the issues surrounding this relationship.

Social enterprises (SEs), part of the third sector, are hybrid organizations combining the pursuit of social scopes with commercial business solutions. In seeking for social value, they pair for-profit and non-profit features, thereby compensating for shortcomings of both the public sector and the commercial market. Therefore, the performance management of such organizations assumes a crucial relevance. Among the available tools, the balanced scorecard (BSC) aims to capture performance multidimensionality, at the same time fostering legitimacy towards stakeholders.

In general terms, the BSC has the limit to follow a linear and static logic of construction and functioning. For this reason, scholars combine it with system dynamics (SD) to create dynamic balanced scorecards (DBSCs). However, literature seems to devote scarce attention to the adoption of such analytic tools in the third sector, particularly in SEs. This chapter wants to contribute to bridging this gap by proposing a tailored application in the context of a social cooperative, active in the clothing recycle and in the re-integration of disadvantaged social categories. By referring to previous literature about DBSC, two modelling strategies are identified: the BSC-driven and the SD-driven. The latter, based on inductive reasoning, is the one privileged for the study because of its wider flexibility. The modelling outputs consider different perspectives than the ones within traditional BSCs, contain elements of circular causality and show how financial and non-financial performances interplay and co-determine each other. Insights from the proposed model can be useful to support both decision-making and stakeholder engagement.

The Mediterranean has long been celebrated for the richness, diversity, and historical depth of its cultural heritage. However, in recent years heritage and heritage practice could be said to have become a new mode of production in the region (Bianchi, 2005). There are a number of reasons for this; one has to do with the stagnation of the Mediterranean's traditional “sun, sea, and sand” tourism. As a result of this tour operators and national governments have started to push the packaging of “culture” and “heritage” for a more diversified “up-market” product to attract higher-spending tourists to the region's cities and rural hinterland. Another factor is the restructuring and liberalization of the regional economy since the closing decades of the 20th century. There has seen a shift from agriculture to services as the dominant economic sector in this region and the concomitant discovery of culture has become an economic asset for investors seeking an outlet for global capital flows (Bianchi, 2005; Daher, 2007; Nogués-Pedregal, 2002). The European Union (EU) has had an important role to play in these processes, both in driving the region's neoliberal market reforms, and in promoting the establishment of its cultural heritage economy. Cultural heritage has become a priority area in EU Mediterranean policy, with millions of euros earmarked for heritage related projects. This takes the form both of loans to private investors from the European Development Bank, and of grants for public sector cultural heritage initiatives, for example, through its Euromed Heritage programs, the fourth phase of which is underway at the time of writing (Bianchi, 2005; Euromed Heritage, n.d.).

We survey and organize over fifty years of theoretical research on status and expectation state processes. After defining some key terms in this theoretical approach, we briefly describe theories and branches in the program.

We also focus on a few theories that illustrate distinct patterns of theory growth, using them to show the variety of ways in which the research program has grown.

The program structure developed from a single set of theories on development and maintenance of group inequality in the 1960s to six interrelated branches by 1988. Between 1988 and today, the overall structure has grown to total 19 different branches. We briefly describe each branch, identifying over 200 resources for the further study of these branches.

Although the various branches share key concepts and processes, they have been developed by different researchers, in a variety of settings from laboratories to schools to business organizations. Second, we outline some important issues for further research in some of the branches. Third, we emphasize the value of developing new research methods for testing and applying the theories.

These theories have been used to explain phenomena of gender, racial, and ethnic inequality among others, and for understanding some cases of personality attributions, deviance and control processes, and application of double standards in hiring.

Status and expectation state processes often operate to produce invidious social inequalities. Understanding these processes can enable social scientists to devise more effective interventions to reduce these inequalities.

Status and expectation state processes occupy a significant segment of research into group processes. This chapter provides an authoritative overview of ideas in the program, what is known, and what remains to be discovered.

We compare methods to measure comovement in business cycle data using multi-level dynamic factor models. To do so, we employ a Monte Carlo procedure to evaluate model performance for different specifications of factor models across three different estimation procedures. We consider three general factor model specifications used in applied work. The first is a single-factor model, the second a two-level factor model, and the third a three-level factor model. Our estimation procedures are the Bayesian approach of Otrok and Whiteman (1998), the Bayesian state-space approach of Kim and Nelson (1998) and a frequentist principal components approach. The latter serves as a benchmark to measure any potential gains from the more computationally intensive Bayesian procedures. We then apply the three methods to a novel new dataset on house prices in advanced and emerging markets from Cesa-Bianchi, Cespedes, and Rebucci (2015) and interpret the empirical results in light of the Monte Carlo results.