This lecture, introduces you further to the social network perspective on organizations, but it elaborates how networks influence organization behavior and outcomes. And it describes ways organizations can create different network patterns and positioning. When we study the effects of networks on organizational behavior, we've used social relations and actor positioning as an independent variable shaping outcomes. We consider whether people influence one another and diffuse their motivations through their friendships. Or if being in key locations of the network have certain returns or advantages for the worker and the firm. When we consider network formation, we look at the network as an outcome or as independent variable. Here, we want to know the factors that lead persons to form relations. And in fact, there's that lead a network to assume a particular shape. And perhaps, even a pattern that you as a manager, as an analyst desire to bring about. So let's look at these using examples in the slides that follow. First, let's consider how relations influence behavior or what we call Peer Influence. The general argument of peer Influence is that people we associate with change us, they affect us. And they lead us to act in ways, we wouldn't normally act if we were out on our own. So an organization's research these studies often focus on a process of social diffusion and the adoption of organizational innovations. Some research studies whether collaborating with productive colleagues increases your productivity, so a test of whether a particular mentoring program has solid returns. But in most of these studies, researchers find that cross ties are great means to defusing attitudes and behaviors. At the end of organizational level, scholars find that the adoption of organizational innovations often flows through associations like interlocking boards of directors or alliance networks. For example, a string of papers found that the use of poison pills in corporate takeovers was an organizational innovation that spread via interlocking boards of directorates. The poison pill for those you were wondering, was a strategy that many firms would use to prevent take overs in the 1980s and 1990s. It was a way of making the firm seem like an expensive low profit gamble, whenever they were being put under a takeover. And so because of those kind of moves, they were seen as not worth taking over, so that the takeover would quickly disappear. Within the context of a single university, Craig Rawlings and I have studied how faculty productivity diffuses through collaboration networks. We found that a university could improve it's grant record by getting successful grant seekers to collaborate with novice grant seekers. Those kind of collaborations improve applications rates, success rates and the amounts awarded. The diffusion of expertise was even greater when these collaborations were repeated more than once. Thereby and ensuring that novices learn how to get grants on their own and with others in the university. So person who did not collaborate, actually struggled to win awards in comparison with their collaborative peers. So we think about this in the context of the large university in the prior lecture that where we ended up the paralecture. You could imagine how engineering faculty collaborating with those in the social and humanistic sciences or fields would benefit from those kinds of collaborations. And induce them to become more of a grant seeker or funding of doctoral research projects. In other work, the conduit of influences is not a strong tie, but a weak one. Mark Granovetter has written some seminal work on social networks. And in particular, he has made a strong case to the importance and usefulness of weak ties. In his research on job seeking, he finds that most people learn about a job and acquire it through weak ties or indirect ties. So friends of friends rather than their close friends. And he argues this is because we weak ties often bridge groups and bring people into contact with more unique information. Persons that rely purely on strong ties and cliques mostly find redundant information. So persons with weak ties have more access to new knowledge about job openings and therefore successfully acquire jobs. Strong and weak ties are often characterized as bonding and bridging forms of social capital or types of associations that bring social advantages. Strong ties and bonding capitals generate social control nd conformity as well as socialization and diffusion. While weak ties and bridging capital often extends a person's reach into pools of useful information. So strong and weak ties imply the creation of certain network configurations and network positions. And therefore, I want to turn to next, the effect of positions on outcomes. A common finding within organizations is that persons occupy certain positions within a network. And those positions afford them all kinds of advantages. For example, like the access to recognition and information. And this kind of positioning with those kind of advantages enables the acumen to be more successful in their careers, the same can be said of in organizational networks. Organizations assuming prominent or brokerage positions tend to survive, grow and have greater control and influence on the field of organizations in which they're embedded. David Krackhardt offers us a nice illustrative example of the effects of network positioning on firm behavior and firm outcomes. He describes the case of a technology firm that is the subject of a unionization effort. According to Krackhardt, the unionization effort fails because union proponents do not coopt the informal leaders of the strong tie network. I find Krackhardt case to be simple and elegant. He first describes the organizational chart of who reports to whom and he identifies the collective bargaining unit that union tries to establish. Then he goes on to show how the key union proponents are neither central to the advice network of experts, nor are they central to the friendship network of trusted relations. Here's the organizational chart and you can see the potential bargaining units circled by the dotted line. In it, I've highlighted the three leaders of the unionization effort, Hal, Ovid, and Jack. The anti-union members are outside the unit, Robin and Mel. And the key experts or advisors of work-related task are outside as well and that's Ev and Steve. Only the informal leader or the popular friend named Chris is in the union but he's not very interested as you'll see. Here's the advice network. Crackart gave the employees a survey to get this sort of information and then he entered the information in this social network software to generate the network graph. The Pro-Union leaders are highlighted in red and they are notably very peripheral to this network. The Anti-Union member are highlighted in blue, and they are notably more involved in the advice network. The lasts, the two key players are highlighted in grey and that is Ev and Steve. And from these we can see that the unionization leaders won't put a stop to the expertise network, that's for sure. The next image is of the friendship network. And again, the three Pro-Union players are highlighted in red and they're peripheral. At the center is the informal leader and popular pal, Chris. And notably, the Anti-Union members are closer to Chris and likely have greater sway over his opinions. In some, the case study uses interviews, surveys and observational records to retell the story of how unionization effort failed because the Pro-Union players were peripheral to the informal organization. They neither co-opted the experts nor the popular individuals in attempting to create a bargaining unit. Had they known to check the network and coopt Chris and his close friends, then they might have received the social support they needed to successfully unionize the firm. So David Crackart's case focuses on the effects of network positioning. What about cliques or social groups and their effects on workers? Long ago in 1939, Roethlisberger and Dickson studied a bank wiring room where workers essentially created circuit boards. There, Roethlisberger and Dickson found that friendship groups of these workers altered their rates of work output. And more of those rates so that they stay within a particular output level that work for the set of friends. Now subsequent scholars have remarked on how peer groups are clusters of strong tied individuals can be a strong force in organizations and in terms of influencing their outcomes. I see this in my own work on American high-schools and their classrooms. There, youth act with their friends in mind. In most classrooms, youth form friendship groups or cliques and those cliques lead the students to conform their behavior within them. Here's an example of one such high-school English composition class that I observed as a graduate student. It was composed as 11th and 12th grade students equally well equipped to read and comprehend the course material that concerned William Shakespeare's written works. The teacher, Sophia, liked to encourage dialogue and frequently called on students. Nonetheless, the students formed clusters of association based on gender, race and age and these groups were rank ordered within those grades. As such, there was a popular core group and a hanger-on group and this arose for each grade level. Interestingly, the 11th grade group and the core 12th grade group did not compete on the same stage. Instead, they specialized in distinct conversational arenas and topics. So, the seniors dominated the public stage of academic discussions and the juniors dominated the back stage of social discussions about parties and events around the school affairs.