Why might firms be regarded as astutely managed at one point, yet subsequently lose their positions of industry leadership when faced with technological change? We present a model, grounded in a study of the world disk drive industry, that charts the process through which the demands of a firm's customers shape the allocation of resources in technological innovation—a model that links theories of resource dependence and resource allocation. We show that established firms led the industry in developing technologies of every sort—even radical ones—whenever the technologies addressed existing customers' needs. The same firms failed to develop simpler technologies that initially were only useful in emerging markets, because impetus coalesces behind, and resources are allocated to, programs targeting powerful customers. Projects targeted at technologies for which no customers yet exist languish for lack of impetus and resources. Because the rate of technical progress can exceed the performance demanded in a market, technologies which initially can only be used in emerging markets later can invade mainstream ones, carrying entrant firms to victory over established companies.

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T he easiest way to respond to the critiques and complements the other authors in this issue have written about the model of disruption would simply be to address them head on-to accept some as useful additions or corrections and to suggest that others are ill-founded. Because this special issue of JPIM represents a unique opportunity to examine the process of theory-building as it unfolds, however, this article is structured in a way that addresses the other scholars' suggestions in the context of a model of the process by which theory is built and improved. My hope in doing so is that this issue might not just be an examination of this particular theory of disruptive innovation but that it might also constitute a case study about theory-building itself-a study that can help scholars of management in different fields to conceptualize how the theory-building process is or is not at work in their domain-and how they might help the process work better. A Model of the Theory-Building ProcessSome years ago in a doctoral seminar my students and I examined how communities of researchers in a variety of disciplines had cumulatively built bodies of understanding. Seeing some stunning commonalities in the processes these scholars had followed, we synthesized a model of the process of theory building (for a summary, see Carlile and Christensen, 2005). My students and I found this model extremely useful as we designed our own research, positioned our work within streams of prior researchers' efforts, and evaluated the reliability and validity of various papers. The present article recounts the development of the theory of disruption within the context of this model of what theory is and how it is built. It also suggests how the comments of the other authors in the current issue of JPIM might contribute to the improvement of this body of theory. In this way, I hope that both the content of this theory and the process by which it is being built might become clearer.Our model asserts that theory is built in two major stages: the descriptive stage and the normative stage. Within each of these stages, theory builders proceed through three steps. The theory-building process iterates through these three steps again and again. In the past, management researchers have quite carelessly applied the term theory to research activities pertaining to only one of these steps. Terms such as utility theory in economics and contingency theory in organization design, for example, actually refer only to an individual step in the theory-building process in their respective fields. It is more useful to think of the term theory as a body of understanding researchers build cumulatively as they iterate through each of the three steps in the descriptive and normative stages. This should be abundantly clear as we examine the theory of disruption. It already has evolved considerably as a growing group of scholars, including those whose work is published herein, have worked to refine it. Among the most notable improvements to date haveThe descriptive st...

The concept of disruptive innovation has gained considerable currency among practitioners despite widespread misunderstanding of its core principles. Similarly, foundational research on disruption has elicited frequent citation and vibrant debate in academic circles, but subsequent empirical research has rarely engaged with its key theoretical arguments. This inconsistent reception warrants a thoughtful evaluation of research on disruptive innovation within management and strategy. We trace the theory's intellectual history, noting how its core principles have been clarified by anomaly-seeking research. We also trace the theory's evolution from a technology-change framework-essentially descriptive and relatively limited in scope-to a more broadly explanatory causal theory of innovation and competitive response. This assessment reveals that our understanding of the phenomenon of disruption has changed as the theory has developed. To reinvigorate academic interest in disruptive innovation, we propose several underexplored topics-response strategies, performance trajectories, and innovation metrics-to guide future research.

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Disruptive innovation has brought affordability and convenience to customers in a variety of industries. However, health care remains expensive and inaccessible to many because of the lack of business-model innovation. This paper explains the theory of disruptive innovation and describes how disruptive technologies must be matched with innovative business models. The authors present a framework for categorizing and developing business models in health care, followed by a discussion of some of the reasons why disruptive innovation in health care delivery has been slow.

This study traces the origins of innovative strategies by examining the attributes of 'innovative entrepreneurs.' In an inductive grounded theory study of innovative entrepreneurs, we develop a theory that innovative entrepreneurs differ from executives on four behavioral patterns through which they acquire information: (1) questioning; (2) observing; (3) experimenting; and (4) idea networking. We develop operational measures of each of these behaviors and fi nd signifi cant differences between innovative entrepreneurs and executives in a large sample survey of 72 successful and unsuccessful innovative entrepreneurs and 310 executives. Drawing on network theory, we develop a theory of entrepreneurial opportunity recognition that explains why these behaviors increase the probability of generating an idea for an innovative venture. We contend that one's ability to generate novel ideas for innovative new businesses is a function of one's behaviors that trigger cognitive processes to produce novel business ideas.We also posit that innovative entrepreneurs are less susceptible to the status quo bias and engage in these information-seeking behaviors with a motivation to change the status quo.

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