Technology entrepreneurship is key to economic development. New technology ventures (NTVs) can have positive effects on employment and could rejuvenate industries with disruptive technologies. However, NTVs have a limited survival rate. In our most recent empirical study of 11,259 NTVs established between 1991 and 2000 in the United States, we found that after four years only 36 percent, or 4,062, of companies with more than five full-time employees, had survived. After five years, the survival rate fell to 21.9 percent, leaving only 2,471 firms still in operation with more than five full-time employees. Thus, it is important to examine how new technology ventures can better survive. In the academic literature, a number of studies focus on success factors for NTVs. Unfortunately, empirical results are often controversial and fragmented. To get a more integrated picture of what factors lead to the success or failure of new technology ventures, we conducted a meta-analysis to examine the success factors in NTVs. We culled the academic literature to collect data from existing empirical studies. Using Pearson correlations as effect size statistics, we conducted a meta-analysis to analyze the findings of 31 studies and identified the 24 most widely researched success factors for NTVs. After correcting for artifacts and sample size effects, we found that among the 24 possible success factors identified in the literature, 8 are homogeneous significant success factors for NTVs (i.e., they are homogeneous positive significant metafactors that are correlated to venture performance): (1) supply chain integration; (2) market scope; (3) firm age; (4) size of founding team; (5) financial resources; (6) founders' marketing experience; (7) founders' industry experience; and (8) existence of patent protection. Of the original 24 success factors, 5 were not significant: (1) founders' research and development (R&D) experience; (2) founders' experience with startups; (3) environmental dynamism; (4) environmental heterogeneity; and (5) competition intensity. The remaining 11 success factors are heterogeneous. For those heterogeneous success factors, we conducted a moderator analysis. Of this set, three appeared to be success factors, and two were failure factors for subgroups within the NTVs' population. To facilitate the development of a body of knowledge in technology entrepreneurship, this study also identifies high-quality measurement scales for future research. The article concludes with future research directions.
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This study addresses the question of how established organizations develop new business models over time, using a process research approach to trace how four business model innovation trajectories unfold. With organizational learning as analytical lens, we discern two process patterns: “drifting” starts with an emphasis on experiential learning and shifts later to cognitive search; “leaping,” in contrast, starts with an emphasis on cognitive search and shifts later to experiential learning. Both drifting and leaping can result in radical business model innovations, while their occurrence depends on whether a new business model takes off from an existing model and when it goes into operation. We discuss the implications of these findings for theory on business models and organizational learning.
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