Biology remains the most extensive and complex information network on the planet. This chapter examines the nature of biological networks, including their inherent stability and risks to their resilience. After a general introduction exploring networks and biological systems, this chapter reviews (1) the evolution of biological networks; (2) principles that govern biological networks; and (3) measures of stability, productivity, and efficiency in biological networks. The authors use examples from food (energy) transfer in rainforests and coral reefs, as well as the creation of a biological network through colonization in Darwin’s Finches of the Galapagos Islands. Research shows that while large biological networks are inherently unstable, some are more stable than others.

Although networks in key business areas such as communications, supply chains, R&D, and sales are designed to improve the flow of information, people, or goods, they can also be used to improve the “peripheral vision” of the organization. In this chapter, the authors examine how networks can be used by organizations to scan, sense, and adapt to new and important signals from the organization’s strategic environment beyond its core focus. The first part of the chapter emphasizes the importance of peripheral vision in helping organizations not being blindsided by threats while seeing new opportunities sooner. The authors examine some key obstacles to using networks to better mine the periphery for early insight. They then explore how extended networks can help the organization be a responsive open system adapting faster to changes in the environment. They examine to what extent network constructs such as centrality, hierarchy, self-healing, distributed intelligence, multihoming, and latency can be used to improve organizational networks for scanning the periphery. The last section explores some of the leadership challenges associated with using networks to detect weak signals sooner.

As terrorist organizations such as Al-Qaeda have been transformed from hierarchical organizations to more fluid networks, countering terrorism requires an understanding of networks. These networks evolve rapidly in response to actions to thwart them, leading to an ongoing struggle of terrorist and antiterrorist networks. In this chapter, Boaz Ganor examines the evolving threat of terrorist networks and network-based responses. As he notes, “it takes a network to beat a network.” He also examines direct and indirect implications for business organizations.

Artificial intelligence (AI) offers computational methodologies for modeling systems, which can be valuable in understanding networks. In this chapter, the author examines several types of applications of these methods in exploring how the behavior of individual agents leads to outcomes across networks. For example, he considers how one system, based on a Prisoner’s Dilemma that provides a higher payoff for players who don’t cooperate, can result in a surprising outcome in which cooperation dominates after many rounds of play. He also considers agent-based models--including turtles in a pond, showing discrimination effects; and sugar and spice trading, showing interactions through trading. Finally, he explores applications to ant colony optimization and swarming optimization of flocks of birds or schools of fish. He concludes that computational models offer important insights into networks, and the procedures used in modeling have a significant impact. The discussion also demonstrates that “networks matter,” affecting outcomes in sometimes unpredictable ways.

What can we learn about networks from ants, honeybees, and other animals with evolved social structures? The impact of information and communications strategies on network dynamics did not arrive with the emergence of computers, cell phones, and the Internet. This chapter describes communication networks selected from among many that have been studied in communities of nonhuman organisms. It explores the extent to which communication linkages have controlled the development of those networks. In some of those networks, developmental histories are manifest as evolved body plans and gender roles not represented in human communities. Many of those networks are founded on efficient exchange of information via pathways of which humans are almost fully oblivious.

This chapter provides an overview of social networks, the basic discipline from which ideas and terminology are drawn when characterizing popular phenomena such as “social networking” Internet sites like Facebook. The authors offer the reader a flavor of the theoretical and empirical research conducted by social network scholars since the 1930s. They explore how researchers have used social networks to generate and test economic, sociological, and organizational theories. They also examine broad insights from this research, as well as management implications in areas such as advertising, brands, loyalty, authenticity, and segmentation. The overriding message is that as power shifts from firms to social networks, companies have less control over their own destinies and need to pay more attention to networks.

Global networks of firms are rapidly replacing top-down, hierarchical organizations. Such networks, thanks to information technology and global communications systems, can respond to changes in international demand faster and more flexibly than rigid corporate organizations of the past. But by drawing together diverse cultures and individuals, these networks present new challenges to leaders. Traditional styles of leadership are not enough for this emerging environment. The kind of leadership style that leads to efficient execution in these global networks is different from the “do it and do it now” approach that might work in hierarchical organizations. Based on the author’s experience in the leading global accounting firm Touche Ross, serving as dean of the Wharton School, and heading his own corporate investment firm, this chapter discusses leadership in a networked, global environment.