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Focusing on interorganizational networks, analysed with reference to the Italian environmental movement in the 1980s, this chapter challenges the assumption that social movements be necessarily decentralized and anti‐hierarchical. The position of different organizations within the environmental movement network is assessed in the light of two criteria , namely network centrality and brokerage. These measures reflect two different types of movement influence, based on the capacity to attract support for specific initiatives (centrality) and the capacity to connect sectors of a movement who hold different stances and worldviews (brokerage). These measures are differently correlated with external indicators of leadership like access to institutions and the media. The chapter also discusses the conditions under which centrality and brokerage positions tend to be occupied by the same actors or by different actors.

This chapter focuses on a major force in the economy, and one that is key to the capitalist system: securities markets and the brokerage industry. Although Nasdaq online securities market was one of the first movers in electronic markets, when Electronic Communications Networks (ECNs) came along and siphoned a considerable amount of trade away, Nasdaq, with its very survival in question, took a long time to respond to the threat. The chapter relates the story of how organizational factors made it difficult for the most successful broker, Merrill Lynch, to respond with a new price structure for trading stocks when electronic brokerages like Schwab and e-Trade came along. These examples illustrate a winner’s curse that comes from complacency and the psychological and organizational factors that often prevent a winner from responding to new events and challenges.

This chapter describes the presence, structure, and form of the banking, insurance, and brokerage industries in the United States. It describes the evolution of these industries over the past half century including their size, how they made money, and their activities. Also described is how the government regulated their activities and how this affected their use of information technology. The case for how these industries evolved into a new digital style of operation is articulated.

This chapter describes the history of how the brokerage industry evolved since the 1950s, and what information technology applications it embraced. It then describes the extent of IT use and its effects on the work, structure, and services in this industry.

The first part of this chapter discusses the institutional response of the London Stock Exchange to the long‐expected outbreak of the Second World War––a response that, unlike that to the First World War, had been planned. The various aspects discussed include the planning and operation of the agreements made between the Exchange and the Treasury and the Bank of England (which ceded ultimate power to the Treasury, and ultimately led to a post‐war compromise on the relative power of the government and Exchange over the securities market) and plans to physically relocate to the Denham film studios (subsequently abandoned). The rest of the chapter discusses the effects of the war on membership and the new rules on rebates, and competition––aspects covered include North American brokerage houses in London, foreign business, the market for domestic securities, provincial stock exchanges, country jobbing, the Stock Exchange ban on account trading, Treasury refusal to give permission for markets in various issues, and securities values.

This chapter look at the decline of the London Stock Exchange during the 1950s. The first part discusses the ways that the Stock Exchange raised money to enable it to survive in the early 1950s, relations between it and the government (which were conducted informally through confidential exchanges between the Governor of the Bank of England and the Chairman of the Stock Exchange), the restoration of option dealing, and the use of the Stock Exchange by the government to police activities regarding securities. The second part discusses the policing of the members of the Stock Exchange, and the third discusses the growing competition from the provincial stock exchanges, closer integration with the London‐based North American brokerage houses, and the Stock Exchange's lack of concern with international business. The last section looks at money and capital (securities) markets in the face of the decline of the Stock Exchange over the 1950s.

The financial services industry has been changing so fast and growing so complex that broker-dealers and investment advisers, which are subject to different regulations, are no longer easy to distinguish from one another. Since the 1990s, market demands have introduced new business practices and firms have taken many different forms, making it harder for investors to distinguish these traditional distinctions. Given such complexity, it is not surprising that typical investors are confused about the nature of the services their financial professional offers. Many of those surveyed, as well as focus group participants, did not understand the key distinctions between investment advisers and broker-dealers: their duties, the titles they use, the services they offer, or the fees they charge. They attributed part of their confusion to the dozens of titles used in the field, including generic titles such as financial advisor and financial consultant, as well as advertisements that claim “we do it all.”

What is at stake with the study of agenting is more than just bringing out of the shadows formerly invisible participants in the manufacture of popular culture. There are lessons to learn from this case study for understanding other types of activity and social worlds, and first of all other art and entertainment industries. Beyond the sole creative worlds, studying “talent agenting” also has an important analytic impact because it sheds light on the crucial role of intermediation and brokerage in highly specialized, differentiated societies. At a more structural level, what this book unveils of Hollywood may be useful for exploring power and action in other social worlds that are also experienced by the participants as relationship-driven all the while being highly institutionalized and organizationally structured spaces.

This chapter deals with a neglected feature of financial markets: the role of status groups and prestige. It shows how in the eighteenth century, stock brokers lacked prestige and legitimacy. At the turn of the nineteenth century, a process of socio-institutional enclosure began, which restricts access to brokerage activities and to transactions. Against the lack of a legal frame reinforcing financial transactions, prestige appeared as a means of building trust and legitimacy for stock exchange activities. Along with transaction rituals, rules of good social behavior, the dynastic transmission of brokerage privileges, social hierarchies, and the restricted access of outsiders to brokerage activities, another feature of social prestige emerged now on both sides of the Atlantic: the transformation of some brokers into “serious” authors, keen to straighten the public image of stock exchanges and of investment activities. Social closure should not be understood exclusively as professionalization, since it includes the opposite of the former: namely reaching out into society at large through inventing new activities such as writing.

This chapter reviews findings in various fields that may provide the basis for the development of theories of foraging by social groups. The power of cooperation is related to the amount of diversity of the information foragers. Greater diversity leads to greater returns for the group and the individual. This is related to the notion that brokerage (diverse social contacts) provides social capital, and there is evidence which suggests that brokers in the flow of information are more likely to be sources of innovative discoveries. Although there are benefits to co-operation, those benefits trade against interference effects that ultimately seem to limit the size of groups. In addition, because of the diversity of individuals and because of the way people associate with like-minded people, information is typically likely to flow to small finite-sized groups. The chapter presents mathematical models that capture the basic elements of these results.

This chapter addresses social network structure and process to explain how brokerage functions to get new things done. First, innovative action is described as often unfolding in triads through brokerage. Second, the chapter explains how network structure sets the context for action, emphasizing the distinction between open and closed social network structures. Third, the chapter distinguishes between brokerage as action and brokerage as structure. Fourth, the chapter considers the brokerage process, first by defining it and then by proposing three fundamental brokerage orientations or behaviors: conduit, tertius gaudens, and tertius iungens. Finally, the chapter revisits Fligstein’s idea of social skill, or the ability to induce cooperation, to argue that inducing cooperation to get new things done is achieved by strategically combining the three brokerage orientations toward action.

This chapter illustrates the BKAP model with an extended ethnographic case to show how network and knowledge processes interact to produce routine-based innovative action over time. The chapter first provides relevant context for the automotive design process, after which the author walks through the extended case in three phases of activity and analysis: the first phase involves disruption of the existing design routine and the initial challenges experienced by the manual shifter “crunch team” in its efforts to respond to that disruption; the second and third phases contrast two pairs of actors (two engineers and two sets of designers) who attempt to mobilize support for innovation. In both phase two and phase three, successful innovation advocates mobilized action through brokerage and knowledge articulation to get new things done.

This chapter illustrates the BKAP model through an extended ethnographic case to show how network and knowledge processes interact to produce project-based innovation. An ethnographic case study in the same automotive setting found in Chapter 4 illustrates the emergence of creative projects launched in pursuit of innovation. Specifically, this chapter depicts how an automobile manufacturer’s prototype parts purchasing routine contrasts with two creative projects undertaken to redesign it. The chapter elaborates how trajectory strategy, consisting of the trajectory projection and scheme, and trajectory management, consisting of knowledge articulation, brokerage activity, and an additional category emerging from the author’s field data—contingency management—impact the two projects’ adoption. To lay the groundwork for how the two creative projects emerged, the author describes the “cowboy culture” presented in the Introduction, a culture imprinted within NewCar that gave rise to behaviors through which creative projects were pursued.

The Introduction provides an overview of the book’s action model. Actors engage in specific social processes to mobilize networks and knowledge to drive both organizational innovation and growth, and many other efforts to get new things done. Innovation takes both more-routine and nonroutine forms, and a particular form of nonroutine action, the creative project, is emphasized as an undertheorized source of innovation in the modern world. Innovation, at the individual level, has four key explanatory variables: (1) brokerage network structure; (2) brokerage process—the action by which a strategic actor leverages his or her network; (3) the strategic actor’s stock of knowledge, whether rooted in experience or education; and (4) the strategic actor’s knowledge articulation skill with which he or she communicates that knowledge for the purposes of engaging or enlisting others. The BKAP model (Brokerage, Knowledge Articulation, Projects) is introduced.

This chapter focuses on Mark Barton, a day trader who, after killing his wife, his eight-year-old daughter, and his twelve-year-old son with a hammer in July 1999, proceeded to shoot nine people at two different brokerage houses before shooting himself. His murderous “rampage” was attributed by the press to his newfound habit of day trading. In a letter of confession left at the family scene, Barton represents his violence as a legitimate expression not only of hatred but of devotion. As Barton has it, he murdered his children in an entirely different spirit, and with a different motive, than he murdered his fellow traders at the brokerage firms. The latter were those who deserved to die because they “greedily sought [his] destruction.”

In social network analysis, centrality measures are used to translate empirical and common sense observations of social behaviour into mathematical expressions. In order to assess how well an algorithm performs in conditions of imperfect data, researchers typically first select either a random or a realworld network, compute a variety of centrality measures, and declare these values to be their point of reference. In a second step, they manipulate these referential networks by adding or removing nodes or ties, again either randomly or following a set of rules. They then compare the centrality measures of the referential network to the ones gathered from the manipulated network. Borgatti et al. (2006) used this approach on a large number of randomly generated networks and found that as long as manipulations were minor (c.10 per cent), results remained reasonably similar to the referential networks’ measures. This approach helps to shed light on the impact of false and missing data on centrality computations, and also helps us to assess the ability of these algorithms to describe social reality (as we reconstruct it) itself. It is surprising that the effectiveness of centrality measures to accurately describe notoriously vague concepts such as ‘power’ or ‘influence’ has not been used alongside empirical observations more often (similarly: Zemljič and Hlebec 2005: 74). In this chapter, I will compare the performance of common centrality measures with the results of an in-depth reconstruction of six historical networks: in this case, support networks for persecuted Jews during the Second World War. Data were extracted from historical narratives, contemporary and retrospective autobiographical reports, interviews, applications for remuneration, and police interrogations. These sources provide a high level of detailed contextual information about the respective ties and actions they represent. It has now become common knowledge that a small minority of Jews managed to survive the Holocaust in hiding and with support from a small and diverse group of helpers. Soon after the end of the Second World War, historians, sociologists, (social) psychologists, and scholars from many other disciplines began to analyse stories of help and survival and found several answers to what seemed to be the key question: ‘Why did helpers decide to help?’

Chapter 1 examines the development of retail trading from the 1960s until our days, paying special attention both to the technological developments that marked the transition to electronic trading in the mid to late 1990s and to the place of retail brokerages within the institutional structure of financial markets. The focus is on the United States and the United Kingdom. Three kinds of processes are investigated close up: the evolution and diversification of retail brokerages in relationship to trading technologies; regulatory regimes and changes in these regimes; the evolution of the client structure of retail brokerages in relationship to online trading. In the 1980s retail brokerages adopted technological innovations meant to increase the frequency with which their customer base was trading. This trend continued in the 1990s, when online platforms for retail traders emerged. The creation of financial products tailored to retail traders and to more frequent trading was accompanied by a regulatory regime that also encouraged trading frequently (e.g., via a favorable taxation regime and high leverage). Between 2000 and 2010, the demographic structure of retail trading populations began to shift toward younger age groups, while income spreads grew larger.

This chapter illustrates how epinets ground the analysis of social network phenomena. Logical and epistemic pre-conditions for co-mobilization and coordination – important capabilities of social networks – are rendered precise and examined empirically. The epistemic properties of pivotal agents (‘coordinators’ and ‘mobilizers’) and propositions (‘coordinata’) at the epistemic core of coordination and co-mobilization processes are described. The epistemic properties of ‘brokerage’ and epistemic operations embedded in brokers are also brought into relief by the use of epinets. The epistemic approach is further extended to the analysis of status to make more precise distinctions among levels of knownness and fame of connected agents.