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The chapter presents a theoretical framework that deals with the basic question of how networks and industries coevolve. We draw upon the structural and relational perspectives of networks to theorize about changes occurring in interfirm networks over time and the coevolutionary linkage of these changes to the industry life cycle. We further extend the widely accepted industry life cycle model by claiming that industry-specific evolutionary patterns impact the structure of the network’s relations, which in turn lead to diversification in the sources of innovation and to variation in the patterns of industrial evolution.

There is a growing need for measures assessing technological changes in systemic contexts as business ecosystems replace standalone products. In these ecosystem contexts, organizations are required to manage their innovation processes in increasingly networked and complex environments. In this paper, we introduce the technology and ecosystem clockspeed measures that can be used to assess the temporal nature of technological changes in a business ecosystem. We analyze systemic changes in the personal computer (PC) ecosystem, explicitly focusing on subindustries central to the delivery of PC gaming value to the end user. Our results show that the time-based intensity of technological competition in intertwined subindustries of a business ecosystem may follow various trajectories during the evolution of the ecosystem. Hence, the technology and ecosystem clockspeed measures are able to pinpoint alternating dynamics in technological changes among the subindustries in the business ecosystem. We subsequently discuss organizational considerations and theoretical implications of the proposed measures.

We examine the evolution of vertical specialization in three industries: chemicals, computers, and semiconductors. Vertical specialization is the restructuring of industry-wide value chains, such that different stages are controlled by different firms, rather than being vertically integrated within the boundaries of individual firms. In some cases, vertical specialization may span international boundaries and is associated with complex international production networks. After decades of vertical specialization, firms in the chemical industry are re-integrating stages of the value chain. By contrast, the semiconductor and computer industries have experienced significant vertical specialization during the past ten years. We examine how and why these contrasting trends in vertical specialization have co-evolved with industry maturation and decline, and underscore the importance and role of both industry factors and business strategies necessary for industries to become more specialized. We also consider the effects of vertical specialization on the sources of innovation and the geographic redistribution of production and other activities. We conclude that the evolution of vertical specialization in these three industries has both reflected and influenced the strategies of leading firms, while also displays industry-specific characteristics that are rooted in different technological and market characteristics.

Purpose – This chapter is intended to encourage comparative-historical research in strategy by articulating a framework for the study of industry and firm evolution.

Design/methodology/approach – Strategy research at its core tries to explain sustained performance differences among firms. This chapter argues that one, out of the many ways to create a productive marriage between strategy research and historical scholarship, is to carry out historically informed comparative studies of how firms and industries gain and lose their competitive position. While much of current strategy research adopts a large N hypothesis testing mode with the implicit assumption that one discovers generalization just like a Newtonian law such as F=m×a that applies across all space and time, an historically grounded methodology starts from the opposite direction. It assumes that a process or event may be idiosyncratic and therefore seeks to establish with detailed evidence that a 2nd (and later 3rd, 4th, … nth) process or event is indeed similar before generalizing across observations.

Findings/originality/value – The chapter argues that the field of strategy would benefit from allocating more effort on building causal generalizations inductively from well-researched case studies, seeking to establish the boundary conditions of emerging generalizations. It articulates a comparative research program that outlines such an approach for the arena of industry and firm evolution studies.

This chapter describes and applies concepts informed by the behavioral theories of the firm to investigate the macrocosmic dynamisms as embodied in China's travel agency policy changes. Through a focused thick description, the study reviews the evolution of China's travel agency regulations since its reform and opening up era and subsequently discusses the impacts and implications of the recent changes in China's travel agency regulations on the regional tourism. By reviewing the evolution of China's travel agency regulations and discussing the impacts of the recent changes in the 2009 Travel Agency Act on the regional tourism, this chapter demonstrates that (1) the government has undergone a learning process to integrate both internal and external evolution factors in regulating its travel agencies’ behaviors; (2) the government–firm relationship behaviors remain the center in the evolution of China's travel agency policies; and (3) the 2009 Travel Agency Act would act as a shock factor initiated by the government to change the routines in firm behaviors, and subsequently the population ecology in both China's and the regional tourism industry.

The purpose of this paper is to provide a link between entrepreneurial activity on the one hand, and industry evolution and economic growth on the other. The role that entrepreneurship plays in innovative activity is explained. The link between entrepreneurship and industry evolution through the spillover of knowledge in generating entrepreneurial activity is analyzed. This implies that the relationship between entrepreneurship and growth is identified. In particular, this paper finds that entrepreneurship generates a positive pulse in the evolution of industries in such a way that fosters economic growth.

Although a growing body of literature that we will discuss later in the paper gives evidence of changing perspectives on entrepreneurship – perspectives that reveal increasing emphasis on the collectivity – two troubling themes persist: (1) the “myth of the lonely only entrepreneur,” and (2) the supply versus demand perspectives on mass entrepreneurial activity. In the sections that follow, we briefly describe these perspectives and argue that they have long since overstayed their welcome.

We investigate product innovation by a cohort of entrants who use technology that eventually suffers disruption. We concentrate on two types of entrants – those with and those without relevant prior experience in the disrupted technology. Using the industrial robotics industry as the context of our study, we explore product innovation using disrupted technology during two time periods: the first prior to sales takeoff of the disruptive products and the second subsequent to takeoff. We find that the two types of entrants did not differ in product innovation prior to takeoff, but firms with prior experience in the disrupted technology manufactured more innovative products subsequent to the sales takeoff of disruptive products. Our research underscores that the boundary conditions of the utility of prior experience is more nuanced than that which literature suggests – it affects product innovation only in the post-sales takeoff period when the demand uncertainties are relatively low. Our findings also suggest that the boundary conditions of Christensen’s thesis are narrower than predicted by prior literature.

Syndicated investments in startups within a particular industry follow an evolutionary path consistent with models of industry growth and evolution. Some industries spend a long time gestating, while others grow and mature quickly. Entry into ecommerce industry segments has both characteristics. What spurred the sector's slow emergence and subsequent quick rise? One obvious answer is the development of the Internet in the mid-1990s. However, a competing possibility is that the diffusion pattern resembles an epidemic among venture capital firms. This chapter examines how the existing structure of the VC syndication network in the US enabled such an epidemic. Consistent with existing theory on the spread of a disease in a small world, this study argues that the incidence of investments in ecommerce startups was a function of prior investments located on shortcuts in the network. The time frame is 1980 to just before the NASDAQ boom in 1999.

The central organizing principle for this volume – the industry life cycle model – is so widely accepted and its basic premises so taken for granted that it has become conventional wisdom in business. Executives in a range of industries use the model to guide their thinking about when and how to invest in various industries. Diversification decisions, for example, are often made on the basis of life cycle logic, especially as large, established companies seek high-growth opportunities for investment.