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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.

What makes firms innovate their business models? Why do they engage in innovating how they create, deliver, and capture value? And how does such innovation translate into innovation performance? Despite the importance of business model innovation for achieving competitive advantage, existing evidence seems to be confined to firm-level antecedents and pays little attention to the impact of industry structure. This study investigates how different stages of an industry’s life cycle and levels of industry competition affect firms’ business model innovation, and how such innovation translates into innovation performance. Based on a cross-industry sample of 1,242 Austrian firms, we introduce a unique measure for the degree of innovation in a firm’s business model. The results indicate that the degree of business model innovation is highest toward the beginning of an industry life cycle, that is, in the emergent stage. Competitive industry pressures turn out to be negatively related to the degree of business model innovation. Moreover, we find that the degree of a firm’s business model innovation, conditional on it having introduced a new product or process recently, positively influences innovation performance. Our findings contribute to the ongoing dialog on the role of industry structure in business model innovation, and provide implications for the management of business model innovation.

As an answer for the limited growth potentials of diversification and internationalization, services became increasingly important for industrial firms in recent years. Based on existing and established business concepts, companies explore new segments in their traditional value chains beyond traditional market penetration strategies: they pursue service transition strategies to open up new sources for growth, even in markets that do not promise great expansion potential. Our paper addresses the issue of economies of scope of service transition. In this context, we first explore the question, to what extent the insights about product diversification strategies from physical goods sectors can be transferred to the service sector. Using competence-based considerations on diversification we focus on dynamic economies of scope, whose central idea is exploration and development of new resources rather than the static exploitation of existing ones. Furthermore, we integrate the largely neglected issue of how the phenomenon of service diversification depends on the industry's life cycle stage. In a small empirical study of the German mechanical engineering industry we demonstrate that diversification steps into services require a shift in the resource and competence base of firms. Using a dynamic perspective, we construct a conceptual framework for analyzing and explaining the advantages of service transition strategies. The developed model describes a service diversification trajectory and points out that the establishment of a profitable service business requires the exploration and development of competences and adequate organizational structures.

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.

New industries are created from the pioneering activities of a few firms. These firms generally face great uncertainty and risk, but also stand to benefit from early mover advantages due to the preemption of resources. Based on an empirical analysis of a diverse set of consumer and industrial innovations introduced in the U.S. over the past 100 years, we find that entrants during the pre-firm take-off stage (termed Creators) have higher survival rates than later entrants that enter between the firm and sales take-off (termed Anticipators), and both of these entrant types have higher survival rates than firms that enter after the sales take-off (termed Followers). Notably, survival rates for Creators and Anticipators do not depend on entry time within the cohort group, i.e. what matters is whether an entrant enters before or after the take-off, not whether it entered first in its cohort. Our results indicate that there is no real option value in waiting when one considers survival as a performance measure, which bodes well for firms interested in creating new industries.

This article considers the relationship between consumers’ valuation of performance improvements and technology development over the technology life cycle. Presenting a demand-based perspective, it explores how the character of life cycle maturity, the nature of competitive threats, and firms’ innovation incentives all change when consumer demand for performance matures in advance of a technology’s performance trajectories. It characterizes demand maturity by introducing the idea of a demand S curve as a complement to the traditional technology S curve. In doing so, it offers a new lens for assessing firms’ prospects of achieving superior performance through the commercialization of new technologies.

This chapter employs institutional theory and the demand-side approach to discuss the entry of new companies into industries. Theory and empirical evidence provides support for the hypothesis that the industry stage of development is the primary factor that determines whether a company should use innovation or imitation as an entry wedge. The evidence suggests that innovation is most often used successfully during the introduction and decline stages of industry development. Imitation is most often used successfully during the growth stage of industry development. During the mature phase both innovation and imitation are used, but usually with limited success.