1,721,157 research outputs found
Waiting for the Payday? The market for startups and the timing of entrepreneurial exit
No full textMost technology startups are set up for exit through acquisition by large corporations. In choosing when to sell, startups face a trade-off. Early acquisition reduces execution errors, but later acquisition both improves the likelihood of finding a better match and benefits from increased buyer competition. Startups’ exit strategies vary considerably: Some startups aim to sell early; others remain in stealth mode by developing the invention for a late sale. We develop an analytical model to study the timing of the exit strategy. We find that startups with more capable founding teams commit to a late exit, whereas those with less capable founding teams commit to an early exit. Finally, startups with founding teams of intermediate capabilities remain flexible: They seek early offers but eventually sell late. If trying the early market is so costly that startups have to make a mutually exclusive choice between an early and late sale, startups sell inefficiently late. Instead, if they can collect early offers at no cost before deciding on the timing of sale, there are too many early acquisitions
The missing middle: value capture in the market for startups
Full text linkWe argue that innovations that involve both upstream (technological) and downstream (commercialization) challenges are disadvantaged in a startup-based innovation system where startups develop inventions, while incumbents acquire startups. We propose an analytical model in which startups are more efficient at solving technological challenges and incumbents are more efficient at solving commercialization challenges, and where uncertainty about the best acquirer prevents complete contracts. We find that when both technological and commercialization challenges are present, as commonly observed in deep tech innovations, startups are able to capture a smaller fraction of the value created. This introduces a bias in the direction of innovation as projects that are primarily characterized by one type of challenge are more attractive investments compared to projects, equally or more valuable, which face both challenges. We discuss the implications of our model for startup strategies, empirical research and deep tech innovation policies
The market for technology
No full textThis chapter discusses several aspects of the nature, formation and growth of technology markets
Markets for Technology
No full textTrade in disembodied technology – the market for technology – has become common, giving firms more strategic options as they can buy, sell and use their technologies internally. At the industry level, this encourages a division of innovative labour between firms with a comparative advantage in the generation of innovation and those better at the development and commercialization of innovations. Technology trade depends upon institutions, demand conditions and the internal organization of firms. Whether markets for technology will thrive is unclear, as is whether strategic patenting will affect their development
Lipid-protein interactions with cardiac phospholamban studied by spin-label electron spin resonance
No full textPhospholamban is a cardiac regulatory protein that, in its monomeric form, inhibits the Ca2+-ATPase. Lipid-protein interactions with a synthetic variant of phospholamban, in which all cysteine residues are replaced with alanine, have been studied by spin-label electron spin resonance (ESR) in different lipid host membranes. Both the stoichiometry and selectivity of lipid interactions were determined from the two-component ESR spectra of phospholipid species spin-labeled on the 14 C atom of the sn-2 chain. The lipid stoichiometry is determined by the oligomeric state of the protein and the selectivity by the membrane disposition of the positively charged residues in the N-terminal section of the protein. In dimyristoylphosphatidylcholine (DMPC) membranes, the stoichiometry (Nb) is 7 lipids/monomer for the full-length protein and 4 for the transmembrane section (residues 26-52). These stoichiometries correspond to the dimeric and pentameric forms, respectively. In palmitoyloleoylphosphatidylcholine, Nb = 4 for both the whole protein and the transmembrane peptide. In negatively charged membranes of dimyristoylphosphatidylglycerol (DMPG), the lipid stoichiometry is Nb = 10-11 per monomer for both the full-length protein and the transmembrane peptide. This stoichiometry corresponds to monomeric dispersion of the protein in the negatively charged lipid. The sequence of lipid selectivity is as follows: stearic acid > phosphatidic acid > phosphatidylserine = phosphatidylglycerol = phosphatidylcholine > phosphatidylethanolamine for both the full-length protein and the transmembrane peptide in DMPC. Absolute selectivities are, however, lower for the transmembrane peptide. A similar pattern of lipid selectivity is obtained in DMPG, but the absolute selectivities are reduced considerably. The results are discussed in terms of the integration of the regulatory species in the lipid membrane
The Management, Organization, and Geography of Novel Innovation
No full textThis dissertation develops new theory and evidence on the antecedents and consequences of innovation for firms, and includes three empirical studies focusing on various facets of the management, organization, and geography of novel innovation.Chapter 1 examines the role of relationships in mitigating change to firm boundaries for new firms entering the medical device industry, focusing in part on how the timing of novel innovation influences whether firms integrate their sales function. Using a new dataset on more than 1,600 new medical device manufacturers that documents both their full product portfolios and sales governance modes over time, this paper finds evidence that relationships develop and influence sales governance choices only when they cross firm boundaries. Further, launching a novel innovation has a nuanced relationship with integration: early in a firm's life, it increases the likelihood of sales integration, but this relationship diminishes over time. This research offers new insights into the limits of relational governance, and contributes to our understanding of the nuanced impact of novel innovation on firm boundaries.Chapter 2 examines the “dual role” of local inventive activity in firm innovation. On one hand, a vibrant, local research community provides inputs into internal research and development activities: the seeds of internal invention. On the other, external inventive activity provides inventions which can substitute for internally generated inventions: the fruit. Furthermore, inventive activities also provide fertile ground for imitation. This paper develops a simple model of how geographically proximate inventive activity—or clusters—affect firms' innovation choices. Firm invention capability importantly conditions the value to a firm of local innovation-related inputs. The paper employs a recent survey of product innovation and the “division of innovative labor” among nearly 5,000 US manufacturing firms. Absent a direct measure, invention capability is treated as a latent, unobserved variable, and a latent class multinomial model is used to infer its value. Consistent with the model's predictions, more inventive firms make use of the richer soil whereas less inventive firms pick the fruit. Further, more capable firms make use of higher value external sources in clusters. This research expands our understanding of how location shapes both who innovates and how they innovate, and provides a novel method for identifying latent capability.Chapter 3 examines how the novelty of a startup's invention conditions its likelihood of venture capital (VC) financing. In it, I argue novelty increases uncertainty about commercial viability, thus requiring startups to search more extensively to find willing VCs to fund them. Two factors lower the cost of search: prior startup experience and a thick VC market. Because these factors make extensive search cheaper, novel startups will disproportionately benefit from experience and cluster location. To test this, I build a hand-collected dataset of 4,700 patenting US medical device startups, and follow them from “birth” (first patent), to VC investment (if any), to eventual success or failure. While novelty has no impact on funding or success on average, firms with novel technologies who also have a lower cost of finding and attracting potential partners are much more successful than those with more incremental technologies. Further, thick markets are less useful for firms pursuing novel technologies if they lack prior startup experience, and experienced founders are not especially advantaged in thin markets. Advancing theories of innovation and entrepreneurship, this study highlights when, where, and for whom novelty pays.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Essays on Firm Innovation in Dynamic Product Markets: Examining Competitive Interactions During Technological Commercialization
No full textHow can firms gain competitive advantage from available technologies is a key question in strategy. In my dissertation, I develop new theory and provide evidence to show that a firm’s focus in selective technological areas may play a central role of creating competitive advantage in industries with rapid product turnover. Firms commit limited resources when selecting which technologies to develop, affecting the composition of their product portfolios and allowing some firms to subsequently capture greater value relative to others. I examine how firm attention to technologies within an industry affect their ability to swiftly incorporate them into products (essay 1); establish a theoretical foundation for firm-to-firm matching in the market for alliances (essay 2); develop an econometric methodology based on the insights from a firm-to-firm matching market (essay 3); and investigate how common technological interests attract partners in the market for interfirm collaboration (essay 4). Across four essays, I find that competitive advantage varies with the firm’s technological composition, its current focal area of technological development, and the collection of potential alliance partners. These findings contribute to understanding conditions under which a firm captures value from the component technologies scattered across its industry, and the key tradeoffs associated with allocating its technological focus.</p
Essays on Corporate Investment in Scientific Research
No full textIn light of a reduction in corporate scientific research in recent decades, my dissertation examines the mechanisms that drive corporate investment in scientific research. More specifically, I explore the relationship between scientific research and its use in invention, how it is organized within the firm, and its aggregated effect on firm-level outcomes, within large firms in the U.S.. To answer my research questions, I construct a novel dataset that traces above 4,000 U.S. publicly traded firms’ investment in science and invention for 35 years (1980-2015). The second chapter of the dissertation provides an overview of the dataset and presents its advantages over previous data. The third chapter of the dissertation examines how the production of scientific research by U.S. corporations is related to its use in invention by the focal firm and to spillovers captured by rivals’ inventions. The fourth chapter further looks at the heterogeneity in firms’ investment in science by examining how the within-firm organization of scientific discovery and invention conditions research output. The findings from chapter three and chapter four suggest that as spillovers of science to rivals increase, and the greater the connectedness between research and invention practices within the firm, the less likely firms are to invest in internal scientific research.</p
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