Entry into New Niches: The Effects of Firm Age and the Expansion of Technological Capabilities on Innovative Output and Impact

We provide evidence that young firms systematically differ from older firms in their innovative output when they enter ‘new to the firm’ technological niches. We analyze data from 128 biotechnology firms since their inception and track these firms over time. Our analyses reveal that the organizational age at which the firm branches into new technological niches significantly influences its innovative activity. We refine the focus of the extant literature by separately examining the effects of branching on the quantity of innovative output, and the impact that this output has on the technology domain. Subsequent to branching into new niches, we find that older firms have a higher quantity of output than their younger counterparts; whereas young firms tend to outpace their older rivals with higher impact. The implications of these findings for the literature on dynamic capabilities and entrepreneurship are discussed. Entry into New Niches 3 How does the timing of capability development matter? We examine whether the benefits that accrue to expanding technological capabilities are contingent upon firm age. We draw on the organizational aging and dynamic capability literatures to study how the expansion of a firm’s capabilities by entering ‘new to the firm’ technological niches, termed as branching, at different points in the firm’s age would vary in its influence on subsequent innovative activity. Though commonly assumed that startups create breakthrough inventions, some contrarian evidence suggests that mature incumbents also generate such discoveries (Dushnitsky and Lenox, 2005; Phene et al., 2006). In a study of large chemical firms, Ahuja and Lampert (2001) proffer evidence to suggest that mature incumbents overcome pathologies of aging by branching into new domains and by recombining new with old knowledge. Other researchers have investigated the temporal and structural effects of recombining new with old knowledge on innovative output (Nerkar, 2003; Rosenkopf and Nerkar, 2001; Rothaermel and Boeker, 2008; Yayavaram and Ahuja, 2008). We contribute to this conversation by examining the role of entry into novel technology areas, i.e. branching, and how the effects of branching on innovative activity vary with firm age. To examine whether the pattern of optimal technological expansion is conditional on firm age, we study innovative output of biotechnology firms from their inception over a twenty year period. This sample allows us to investigate the underlying conditions when firms optimize their output and impact by managing entry into new technological niches. The study engages the literature on capability development, especially in young firms. The entry into new niches corresponds with the expansion of a firm’s technological capabilities to drive innovation within and across these technological domains. We also refine the focus of the extant literature by Entry into New Niches 4 separately examining the effects of branching on the quantity of innovative output and the impact that the output has on the technology domain. Branching, Recombination, and Innovation Scholars have posited that new knowledge is created by unique recombination of existing knowledge repositories (Basalla, 1988; Henderson and Cockburn, 1994; Schumpeter, 1939). Though inventors can possibly combine any prevalent technological components, what actually gets combined is constrained by the localness of their search and the social construction on what components can be gainfully combined. Branching into a ‘new to the firm’ technology domain increases the stock of opportunities to which the firm has access (Fleming, 2001; Fleming and Sorenson, 2004). The knowledge components that the firm acquires in the new domain can then be recombined with its existing knowledge to introduce heterogeneity that facilitates problem solving (Amabile, 1988; George, Kotha and Zheng, 2008). The variety in problem solving approaches increases the likelihood that solutions can be found for technological bottlenecks. Recombination can also enhance the impact of the innovation on the technology domain itself. Indeed, it has been argued that breakthroughs result from recombining non-obvious technology components (Basalla, 1988). Hence, when a firm branches, it could combine new knowledge with its existing knowledge to yield radical innovation (Ahuja and Lampert, 2001; Katila and Ahuja, 2002) that can potentially influence both domains (Ethiraj and Puranam, 2004). Though searching widely for technology solutions has positive implications, extensive experimentation without deep understanding of the causal relationships between components may prove counterproductive (George et al., 2008; Lee et al., 2004; Yayavaram and Ahuja, 2008). Entering multiple new technological niches simultaneously necessitates experimentation to understand the technology domains and their underlying science. Excessive experimentation Entry into New Niches 5 can hurt output and quality by reducing reliability (March, 1991). To create impact, firms will need to develop a deeper understanding of the new technical field that they enter in order to build on existing knowledge. When firms concurrently enter multiple domains, it becomes difficult to absorb knowledge (Cohen and Levinthal, 1990), likely reducing novelty and impact because they fail to invest in maximizing contributions to the multiple technological fields that they enter. Assimilating knowledge is time-consuming and expensive; a luxury ill-afforded by firms that are resource constrained because processing knowledge for multiple domains likely increases the coordination cost multifold. Consequently, we expect a curvilinear relationship between branching and innovative output and its impact on the technology field, such that moderate branching is better than low or high branching for the count of innovative output and its impact on the technology field. Hypothesis 1a: The relationship between the number of entries into new technological niches (branching) and the quantity of innovative output is curvilinear (inverted Ushaped) such that moderate branching yields optimal outcomes. Hypothesis 1b: The relationship between the number of entries into new technological niches (branching) and the technological impact of the innovative output is curvilinear (inverted U-shaped) such that moderate branching yields optimal outcomes. Branching, Firm Age, and Innovation We posit that the relative benefit that accrues to the firm’s branching activity systematically differs by the age at which the firm undertakes this capability expansion. The causal mechanisms that underlie the differences in effects of branching by firm age can be traced to the tension that arises from efficiencies in learning from cumulative output versus the rigidities that occur with senescence (Argote, 1999; Barron, West and Hannan, 1994). Scholars have argued that a firm’s competence to increase production output improves with age because the firm benefits from well-embedded, robust routines derived from prior operating experiences Entry into New Niches 6 (Nelson and Winter, 1982). Similarly, Cohen and Levinthal (1990) found that accumulation of knowledge enhances a firm’s ability to acquire, assimilate and exploit information to generate further innovations. In addition, a firm’s resource endowment, especially its slack resources, may positively influence innovative output (Nohria and Gulati, 1996) and encourage it to explore new areas for growth (Penrose, 1959). When a firm branches into a new technological niche, the slack allows it to divert free resources towards integrating new knowledge with existing knowledge repositories to increase innovative output. Also, the presence of an infrastructure to innovate such as research laboratories and scientific human capital, increase the potential for a firm to absorb information (Zucker, Darby and Brewer, 1998). Since older firms are more likely to have accumulated experience and slack resources (Penrose, 1959), we expect that they stand to benefit more from branching into new niches than younger firms. Also, older firms are likely to have routinized search strategies which further improve innovative output (Nelson and Winter, 1982; Ronsenkopf and Nerkar, 2001). On the contrary, younger firms suffer from severe resource constraints and lack the efficiency-enhancing experience (George, 2005; Stinchcombe, 1965). Collectively, these arguments suggest that older firms are likely to yield higher innovative output than younger firms when they branch into new niches. Hypothesis 2a: The number of entries into new technological niches (branching) is more positively related to innovative output for older firms than for younger firms. Whereas resource and experience arguments favor older firms and their innovative output, the impact of such output on the technological domain is likely driven by a different causal dynamic. First, in older firms, as experience in a technology accumulates, the cognitive maps of scientists and managers become increasingly rigid where paradigmatic solutions are likely to further confound problems (March, 1991). In examining letters to shareholders of the 15 Entry into New Niches 7 largest pharmaceutical firms, Kaplan, Murray and Henderson (2003) found that the mental models of senior management are partially responsible for the difficulties these firms faced when responding to technological discontinuities. Others argue that older firms possess informationprocessing routines that encourage innovation in their existing technology trajectories rather than in new technological fields (Henderson, 1993; Nerkar, 2003). Older firms are also likely to be constrained by ossified routines and structures that hinder exploration (Nelson & Winter, 1982). Because heterogeneity in problem solving techniques is an important source of novel solutions (Amabile, 1988), rigid mental models and deeply embedded routines serve to natural