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Is the sharing economy a field? Answering this question is crucial to understanding how sharing organizations look and behave, as well as how the sharing economy might develop. In this chapter, the authors applied two different field conceptions – organizational field and issue field – as a starting point for an explorative empirical analysis. To capture both field concepts, the authors collected relational data and data on organizations’ self-representations to see how organizations engaged in the debate on the sharing economy relate to each other. The observed network of organizations suggests that the sharing economy is an issue field. In addition, the core of this network shows the relational structure of an organizational field. Surprisingly, it is not an organizational field of the sharing economy. Instead, it is a field of organizations heavily engaged in proselytizing new organizational forms that will change other fields. What the authors observed is a new field configuration – the authors call it a disruptive field – that is, less inward-oriented than other fields but much more engaged in changing other fields’ structures and dynamics. With these insights, the authors contribute to institutional research on field configuration and shed light on the phenomenon of the sharing economy and its potential development.

This paper explores the emergence and coordination of synchrony in networked groups like those that develop integrated product platforms in collaborative ecosystems. While synchronized actions are an important objective for many groups, interorganizational network theory has yet to explore synchrony in depth perhaps because it does not fit the typical diffusion models this research relies upon. By adding organizationally realistic features – sparse network structure and intentional coordination – to the firefly model from theoretical biology, I take some first steps in understanding synchrony in organizational groups. Like diffusion, synchrony is more effective in denser networks, but unlike diffusion clustering decelerates synchrony’s emergence. Coordination by a few group members accelerates group-wide synchrony, and benefits the coordinating organizations with a higher likelihood that it converges to the coordinating organization’s preferred rhythm. This likelihood of convergence to an organization’s preferred rhythm – what I term synchrony performance – increases in denser networks, but is not dependent on tie strength and clustering.

The main problem addressed by this research is the current debate between the negative and positive effects of industrial clusters. This debate is a result of gaps between theoretical implications and empirical evidence in both the classical agglomeration theory and the agglomeration lifecycle theory. The purpose of this study is to propose a framework for developing an index measuring both organizational cluster involvement and organizational supply chain including the three pillars (economic, social, and environmental). Furthermore, the index acts as a quantitative predictor of the stages of the life cycle of industrial clusters. Adopting a case study methodology, the applicability of the index development framework is demonstrated. First, cross-sectional exploratory interviews are performed to locate items measuring the three pillars of organizational sustainability within Egyptian communication industry. Second, an explanatory, cross-sectional approach is applied gathering data from eight professionals related to involvement and supply chain sustainability of their organizations. Analytical hierarchical process is used for weighting and aggregating individual item metrics into two indicators (Saaty, 1980). Measuring, managing, and controlling capabilities of organization's supply chains outweighs the need to manage risks. The proposed framework aids firms within a cluster in making timely decisions about what needs addressing to improve supply chain sustainability performance. Hence, all environmental, social, and economic capabilities can be effectively monitored and controlled.

Organizations facing issues related to growth, innovation, and strategy are embracing design thinking, a problem-solving process. This study explores 40 design thinking initiatives and identifies operational practices emerge and empirical categories across various contexts. Quantitative analyses of the initiatives and qualitative interview data are used to distinguish four configurations of action analogous to races: training, emphasizing learning-by-doing; marathons, capturing personal reflection over a long project; relays, highlighting team collaboration; and sprints, reflecting fast-paced product innovation. The initiatives are differentiated as designer-led versus team-driven and, low-urgency versus high-urgency. Implications of practicing design thinking in Organization Development and Change are discussed.

An emerging stream of literature has observed that project-based organizations rely increasingly on a network of collaborations originating from the ongoing process of creating and dissolving relationships that bring new project opportunities. Project-based networks are widespread in knowledge-intensive and creative industries, such as life-science and biotechnology, nanotechnology, and software, film, and music industry. This chapter examines the structural characteristics of project-based network-ties in German biotech. We focus on the consequences of local versus international network ties for the innovative success of German biotechnology firms. The findings of our longitudinal event history analysis indicate that the most valuable learning drivers are international research alliances and centrality within the international research network. Surprisingly, we do not find any local effects: neither the density of a local research cluster, nor its diversity or age is of significance. Our results shed new light on the relevance of international linkages for firms that are engaged in project-based learning networks.

Social movement scholars use protest events as a way to quantify social movements and have most often used large, national newspapers to identify those events. This has introduced known and unknown biases into our measurement of social movements. We know that national newspapers tend to cover larger and more contentious events and organizations. Protest events are furthermore a small part of what social movements actually do. Without other readily available options to quantify social movements, however, big-N studies have continued to focus on protest events via a few large newspapers. With advances in digitized data and computational methods, we now no longer have to rely on large newspapers or focus only on protests to quantify important aspects of social movements. In this paper, we use the environmental movement as a case study, analyzing data from a wide range of local, regional, and national newspapers in the United States to quantify multiple facets of social movements. We argue that the incorporation of more data and new methods to quantify information in text has the potential to transform the way we both conceive of and measure social movements in three ways: (1) the type of focal social movement organization included, (2) the type of tactics and issues covered, and (3) the ability to go beyond protest events as the primary unit of analysis. In addition to demonstrating ways that the focus on counting protest events has introduced specific biases in the type of tactics, issues, and organizations covered in social movement research, we argue that computational methods can help us extract and count meaningful aspects of social movements well beyond event counts. In short, the infusion of new data and methods into social movements, peace, and conflict studies could lead us to a substantial shift in the way we quantify social movements, from protest events to everything that occurs outside of them.

In the context of Saudi Arabia, this chapter investigates how clustering promotes knowledge sharing and transfer in an emerging, government-directed industry cluster. It is determined that lateral actors play a key facilitating role, and formal and informal mechanisms and interpersonal links among actors support that cluster knowledge exchange. Limited social capital strength and depth and a lack of trust that prevents knowledge sharing are partially explained by the cluster's limited vertical and horizontal actors.

We reformulate regression modeling so that ideas often associated with field theory and social network analysis can be brought to bear at every stage in the computation and interpretation of regression coefficients in studies of organizations. Rather than “transcending” general linear reality, we seek to get more out of it. We formulate a dual to regression modeling based on using the variables to learn about the cases. We illustrate our ideas by applying the new approach to a database of hundreds of violent extremist organizations, focusing on understanding which groups use or pursue unconventional weapons (chemical, biological, radiological, nuclear).

This chapter aims to enrich knowledge about cluster initiatives acting as intermediaries primarily between members in a cluster or in regional context. This is a practically oriented manuscript written to contribute to refinement of existing policies by proposing recommendations based on recent empirical studies regarding funding, actors’ and activities’ content, as well as cluster initiatives’ assessment. It is proposed that public support should be balanced, targeting new as well as established, well-functioning cluster initiatives. Furthermore, regional authorities should encourage multifaceted collaboration (e.g., Triple Helix), stimulate variation in activities to maximize the benefit of cluster initiatives as well as define and communicate success factors that make it possible to evaluate cluster initiatives from a holistic perspective. These recommendations are primary aimed for regional authorities and reflect a bottom-up perspective where both logic of initiatives’ actions and their development are captured. Yet, even national authorities can make use of the recommendations in this chapter to improve governance of cluster initiatives and to determine further directions of regional policies.