nep-sbm New Economics Papers
on Small Business Management
Issue of 2019‒09‒30
fourteen papers chosen by
João Carlos Correia Leitão
Universidade da Beira Interior

  1. Digitization and knowledge spillover effectiveness: Evidence from the "German Mittelstand" By Proeger, Till; Runst, Petrik
  2. Cross-country evidence on the contributions of research institutions to innovation By Caroline Paunov; Martin Borowiecki; Nevine El-Mallakh
  3. Knowledge searching strategies, testing for complementarities on the innovation behavior of the firm By Alejandro Bello-Pintado; Felipe Berrutti; Carlos Bianchi; Pablo Blanchard
  4. The Effect of High-Tech Clusters on the Productivity of Top Inventors By Moretti, Enrico
  5. Entrepreneurial Persistence beyond Survival: Measurement and Determinants By Caliendo, Marco; Goethner, Maximilian; Weißenberger, Martin
  6. Funding Emerging Ecosystems By Paige Clayton; Maryann Feldman; Benjamin Montmartin
  7. The antecedents of new R&D collaborations with different partner types: On the dynamics of past R&D collaboration and innovative performance By Rene Belderbos; Victor Gilsing; Boris Lokshin; Martin Carree; Juan Fernández Sastre
  8. What Happened to the U.S. Business Dynamism? By Ufuk Akcigit; Sina Ates
  9. Synergizing Ventures By Ufuk Akcigit; Emin Dinlersoz; Jeremy Greenwood; Veronika Penciakova
  10. New evidence on determinants of IP litigation: A market-based approach By Dirk Czarnitzki; Kristof Van Criekingen
  11. Experimentation and Startup Performance: Evidence from A/B testing By Rembrand Koning; Sharique Hasan; Aaron Chatterji
  12. Firm-level credit ratings and default in the Great Recession: Theory and evidence By Fernando Leibovici; David Wiczer
  13. Data Science in Strategy: Machine learning and text analysis in the study of firm growth By Daan Kolkman; Arjen van Witteloostuijn
  14. Corruption and firms By Colonnelli, E; Prem, M

  1. By: Proeger, Till; Runst, Petrik
    Abstract: The Knowledge Spillover Theory of Entrepreneurship (KSTE) considers determinants of knowledge diffusion as well as their impact on entrepreneurial activities and growth. Extending the KSTE, the role of incumbent firms for the broad diffusion of new knowledge has been emphasized. For those firms, the barriers to an effective flow of information are considered using the concepts of knowledge filters and absorptive capacities. Both concepts enable the derivation of institutional measures to penetrate knowledge filters and systematically increase absorptive capacities. We interpret the process of digitization as a central process of knowledge spillover in recent years and determine digitization-related knowledge filters for particular domains of firm decision-making. Using a consultant-based in-depth evaluation of 200 SMEs conducted in the context of a federal innovation program, structural drivers, firm clusters and domain-specific knowledge filters for digitization are determined. We find little evidence for structural drivers of knowledge spillover effectiveness. However, as firms are clustered according to their digitization pattern, we show that firms realize high degrees of digitization in most domains or in none, leading us to argue that domain-specific knowledge filters are weak. Rather, knowledge spillover in digitization can be considered a process with initially strong general knowledge filter and - once this filter has been penetrated - weaker subsequent domain-specific knowledge filters. Policy and managerial implications for increasing digitization-related knowledge spillovers in SMEs are discussed.
    Keywords: Digitization,Knowledge Filter,Knowledge Spillover Theory of Entrepreneurship,Small and Medium Enterprises
    JEL: D21 D82 H41 K23 L14
    Date: 2019
  2. By: Caroline Paunov (OECD); Martin Borowiecki (OECD); Nevine El-Mallakh (Université Paris 1 Panthéon-Sorbonne)
    Abstract: This paper presents preliminary evidence on the patenting activities of 21 200 research institutions - 20 091 higher education institutions (HEIs) and 1 109 public research institutes (PRIs) - for 36 OECD countries and China from 1992 to 2014. Our evidence, which builds on a database that matches research institutions to a sample of their patent applications, indicates patent applications to the European Patent Office (EPO) filed by research institutions grew faster than industry patents. Those jointly filed by industry and research institutions grew even faster. However, research institutions’ share in patent applications remains low and their ratio of patents granted to applications is below that of industry. An econometric analysis at postal code level shows that geographical proximity to research institutions is associated with higher industry patenting. Results from an instrumental variable estimation indicate that research institutions positively influence local industry patenting, including in life sciences and digital technologies.
    Keywords: China, Higher education institutions (HEIs), innovation, local knowledge spillovers, OECD countries, patents, public research institutes (PRIs), universities
    JEL: I23 O31 O34
    Date: 2019–09–24
  3. By: Alejandro Bello-Pintado (Universidad Pública de Navarra (España)); Felipe Berrutti (Universidad de la República (Uruguay). Facultad de Ciencias Económicas y de Administración. Instituto de Economí­a); Carlos Bianchi (Universidad de la República (Uruguay). Facultad de Ciencias Económicas y de Administración. Instituto de Economí­a); Pablo Blanchard (Universidad de la República (Uruguay). Facultad de Ciencias Económicas y de Administración. Instituto de Economí­a)
    Abstract: According to two basic building blocks of neo-Schumpeterian economics, firms innovation process shows idiosyncratic features related to their specific characteristics of the firm and of the environment where it acts. Moreover, firms innovation is recognized as an interactive process. Hence, due to systemic functioning, it is expected that the effect of two simultaneous external linkages will be different from the sum of their isolated effects. However, the external search for knowledge and information sources (KISs) may present constraints related to the searching costs and the cognitive distance between the firm and the KISs. This paper aims to contribute empirical evidence to revisit these theoretical building blocks by analyzing the search strategies conducted by firms. We identify three types of external KISs and analyze the effects of eight search strategies (KIS combinations) on firms innovation behavior. In addition, we test the complementarity or substitution effects of the simultaneous use of different KISs on the innovation behavior – effort and performance – of Uruguayan firms. We identify the specific effect of different KIS combinations but find no evidence of a linear relation between search scope and innovation behavior. Moreover, we find evidence of complementary effects between relatively closer and more distant KISs and substitution effects between relatively near KISs.
    Keywords: information sources, search strategy, complementarity, supermodularity
    JEL: D22 D83 L25 O32
    Date: 2019
  4. By: Moretti, Enrico (University of California, Berkeley)
    Abstract: The high-tech sector is increasingly concentrated in a small number of expensive cities, with the top ten cities in "Computer Science", "Semiconductors" and "Biology and Chemistry", accounting for 70%, 79% and 59% of inventors, respectively. Why do inventors tend to locate near other inventors in the same field, despite the higher costs? I use longitudinal data on top inventors based on the universe of US patents 1971 - 2007 to quantify the productivity advantages of Silicon-Valley style clusters and their implications for the overall production of patents in the US. I relate the number of patents produced by an inventor in a year to the size of the local cluster, defined as a city x research field x year. I first study the experience of Rochester NY, whose high-tech cluster declined due to the demise of its main employer, Kodak. Due to the growth of digital photography, Kodak employment collapsed after 1996, resulting in a 49.2% decline in the size of the Rochester high-tech cluster. I test whether the change in cluster size affected the productivity of inventors outside Kodak and the photography sector. I find that between 1996 and 2007 the productivity of non-Kodak inventors in Rochester declined by 20.6% relative to inventors in other cities, conditional on inventor fixed effects. In the second part of the paper, I turn to estimates based on all the data in the sample. I find that when an inventor moves to a larger cluster she experiences significant increases in the number of patents produced and the number of citations received. Conditional on inventor, firm, and city _ year effects, the elasticity of number of patents produced with respect to cluster size is 0.0662 (0.0138). The productivity increase follows the move and there is no evidence of pre-trends. IV estimates based on the geographical structure of firms with laboratories in multiple cities are statistically similar to OLS estimates. In the final part of the paper, I use the estimated elasticity of productivity with respect to cluster size to quantify the aggregate effects of geographical agglomeration on the overall production of patents in the US. I find macroeconomic benefits of clustering for the US as a whole. In a counterfactual scenario where the quality of U.S. inventors is held constant but their geographical location is changed so that all cities have the same number of inventors in each field, inventor productivity would increase in small clusters and decline in large clusters. On net, the overall number of patents produced in the US in a year would be 11.07% smaller.
    Keywords: agglomeration, spillovers
    JEL: J01 R00
    Date: 2019–09
  5. By: Caliendo, Marco (University of Potsdam); Goethner, Maximilian (Friedrich Schiller University); Weißenberger, Martin (University of Potsdam)
    Abstract: Entrepreneurial persistence is demonstrated by an entrepreneur's continued positive maintenance of entrepreneurial motivation and constantly-renewed active engagement in a new business venture despite counter forces or enticing alternatives. It is thus a crucial factor for entrepreneurs when pursuing and exploiting their business opportunities and to realize potential economic gains and benefits. Using rich data on a representative sample of German business founders, we investigate the determinants of entrepreneurial persistence. Next to observed survival we also construct a hybrid persistence measure capturing also the motivational dimension of persistence. We analyze the influence of individual-level (human capital and personality) and business-related characteristics on both measures as well as their relative importance. We find that the two indicators emphasize different aspects of persistence. For the survival indicator, the predictive power is concentrated in business characteristics and human capital, while for hybrid persistence, the dominant factors are business characteristics and personality. Finally, we show that results are heterogeneous across subgroups. In particular, formerly-unemployed founders do not differ in survival chances, but they are more likely to lack a high psychological commitment to their business ventures.
    Keywords: entrepreneurship, start-ups, persistence, survival
    JEL: L26 M13
    Date: 2019–09
  6. By: Paige Clayton (University of North Carolina at Chapel Hill); Maryann Feldman (University of North Carolina at Chapel Hill); Benjamin Montmartin (SKEMA Business School; Université Côte d'Azur, France)
    Abstract: Although prior research argues that location is important for firm performance, we lack an understanding of how resources accumulate in regions and how innovative ecosystems emerge and evolve over time. This paper focuses on the temporal development of an industry in a region and provides a framework for characterizing phase changes in a geographically defined entrepreneurial ecosystem. We add to the literature on entrepreneurial ecosystems by considering emergence as a temporal process and explicating finance as a mechanism that transitions between phases. Emergence is captured by the accumulation of individual entry by entrepreneurs, and punctuated by phase changes as the region accumulates resources and evolves. We use threshold regression to identify inflection points in stages of industry emergence. We then focus on the role of finance, from both public and private sources. Using a dynamic random effects probit model with regime analysis, we demonstrate interrelationships between public and private funding sources that differ over time. Finally, we estimate the relationship between the funding from various sources and firm survival within different phases using a discrete event history analysis. Our results demonstrate that public and private funding sources are complementary but with different impacts on firm survival during different phases. The results have implications for startup firms seeking funding and for policy making trying to encourage industry emergence.
    Date: 2019–09
  7. By: Rene Belderbos; Victor Gilsing; Boris Lokshin; Martin Carree; Juan Fernández Sastre
    Abstract: We examine firms’ propensity to adapt their R&D collaboration portfolio by establishing new types of R&D collaboration with different kinds of partners (suppliers, customers, competitors and universities & public research institutions). We argue that existing R&D collaboration with one of the two value chain partners (suppliers or customers) is associated with the formation of new R&D collaboration with the other value chain partner to ensure temporal alignment in innovation within the value chain. In contrast, issues related to governance and unintended knowledge spillovers suggest that ‘horizontal’ R&D collaboration with competitors only spurs R&D collaboration with other partner types if such competitor R&D collaboration has been discontinued earlier (‘delayed temporal alignment’). We posit that persistent prior R&D collaboration with institutional partners is an antecedent to the establishment of new R&D collaboration with industrial partners, and that discontinuation of a particular type of R&D collaboration is likely to lead to a restart of such R&D collaborative effort. Strong prior innovative performance is expected to increase the probability that firms establish R&D collaborations with new partner types, except for R&D collaboration with competitors, since the most innovative firms may fear leakage of proprietary knowledge to rivals. We find broad support for these predictions in a large panel of Spanish innovating firms (2004-2011). Our findings highlight that it is not just the configuration of R&D collaborations with existing partner types that predicts tie formation with new partner types, but also the intertemporal pattern of prior R&D collaboration and managerial discretion provided by past innovation success.
    Date: 2017–10
  8. By: Ufuk Akcigit (University of Chicago); Sina Ates (Federal Reserve Board)
    Abstract: In the last several decades the U.S. economy has witnessed a number of striking trends that indicate a rising market concentration and a slowdown in business dynamism. In this paper, we make an attempt to understand potential common forces behind these empirical regularities through the lens of a micro-founded general equilibrium model of endogenous firm dynamics. Importantly, the theoretical model captures the strategic behavior between competing firms, its effect on their innovation decisions, and the resulting “best vs. the rest” dynamics. We focus on four potential mechanisms that can potentially drive the observed changes and use the calibrated version of the model to assess the relative importance of these channels. One particular exercise replicates the transitional dynamics of the U.S. economy through joint moves in all four channels and decomposes the contribution of each channel to the resulting trends. Our results highlight the dominant role of a decline in the intensity of knowledge diffusion from the frontier firms to the laggard ones in explaining the observed shifts. We conclude presenting new evidence that shows an increasing concentration of innovative activity.
    Date: 2019
  9. By: Ufuk Akcigit (University of Chicago); Emin Dinlersoz (U.S. Census Bureau); Jeremy Greenwood (University of Pennsylvania); Veronika Penciakova (University of Maryland)
    Abstract: Venture capital and growth are examined both empirically and theoretically. Empirically, VC-backed startups have higher early growth rates and patenting levels than non-VC-backed ones. Venture capitalists increase a startup's likelihood of reaching the right tails of firm size and innovation distributions. Furthermore, there is positive assortative matching: better venture capitalists match with better startups, creating a synergistic effect. An endogenous growth model, where venture capitalists provide both expertise and financing to business startups, is constructed to match these facts. The degree of assortative matching and the taxation of VC-backed startups are important for growth.
    Date: 2019
  10. By: Dirk Czarnitzki; Kristof Van Criekingen
    Abstract: We contribute to the economic literature on patent litigation by taking a new perspective. In the past, scholars mostly focused on specific litigation cases at the patent level and related technological characteristics to the event of litigation. However, observing IP disputes suggests that not only technological characteristics may trigger litigation suits, but also the market positions of firms, and that firms dispute not only about single patents but often about portfolios. Consequently, this paper examines the occurrence of IP litigation cases in Belgian firms using the 2013 Community Innovation Survey with supplemental information on IP litigation and patent portfolios. The rich survey information regarding firms’ general innovation strategies enables us to introduce market-related variables such as sales with new products as well as sales based mainly on imitation and incremental innovation. Our results indicate that when controlling for firms’ IP portfolio, the composition of turnover in terms of innovations and imitations has additional explanatory power regarding litigation propensities. Firms with a high turnover from innovations are more likely to become plaintiffs in court. Contrastingly, firms with a high turnover from incremental innovation and imitation are more likely to become defendants in court, and, moreover, are more likely to negotiate settlements outside of court.
    Keywords: IP litigation, patenting, innovation, imitation
    Date: 2018–04
  11. By: Rembrand Koning; Sharique Hasan; Aaron Chatterji
    Abstract: Recent work argues that experimentation is the appropriate framework for entrepreneurial strategy. We investigate this proposition by exploiting the time-varying adoption of A/B testing technology, which has drastically reduced the cost of experimentally testing business ideas. This paper provides the first evidence of how digital experimentation affects the performance of a large sample of high-technology startups using data that tracks their growth, technology use, and product launches. We find that, despite its prominence in the business press, relatively few firms have adopted A/B testing. However, among those that do, we find increased performance on several critical dimensions, including page views and new product features. Furthermore, A/B testing is positively related to tail outcomes, with younger ventures failing faster and older firms being more likely to scale. Firms with experienced managers also derive more benefits from A/B testing. Our results inform the emerging literature on entrepreneurial strategy and how digitization and data-driven decision-making are shaping strategy.
    JEL: M13 M2
    Date: 2019–09
  12. By: Fernando Leibovici (Federal Reserve Bank of St. Louis); David Wiczer (Stony Brook University)
    Abstract: This paper studies the role of credit constraints in accounting for the dynamics of firm-level default during the Great Recession. We present novel firm-level evidence on the role of credit ratings in exit behavior during the Great Recession. Firms with low credit rating are more likely to default than firms with high credit ratings and the difference widened substantially in the Great Recession while, in contrast, default rates did not vary much by size, age, or productivity. Because credit ratings may capture the long-term solvency of firms and their access to short-term liquidity, we interpret this evidence using a model of heterogeneous firms with endogenous default and delinquency choices, where intertemporal loans are taken to pay for working capital expenditures and loan prices depend on the firms' payment history. Our findings suggest that credit constraints played an important role in accounting for the dynamics of firm-level default during the Great Recession. We investigate the extent to which credit ratings reflect imperfect information about firms, and examine their implications for the dynamics of default as well as for the design of policies during episodes of financial distress.
    Date: 2019
  13. By: Daan Kolkman (Technical University Eindhoven); Arjen van Witteloostuijn (Vrije Universiteit Amsterdam)
    Abstract: This study examines the applicability of modern Data Science techniques in the domain of Strategy. We apply novel techniques from the field of machine learning and text analysis. WE proceed in two steps. First, we compare different machine learning techniques to traditional regression methods in terms of their goodness-of-fit, using a dataset with 168,055 firms, only including basic demographic and financial information. The novel methods fare to three to four times better, with the random forest technique achieving the best goodness-of-fit. Second, based on 8,163 informative websites of Dutch SMEs, we construct four additional proxies for personality and strategy variables. Including our four text-analyzed variables adds about 2.5 per cent to the R2. Together, our pair of contributions provide evidence for the large potential of applying modern Data Science techniques in Strategy research. We reflect on the potential contribution of modern Data Science techniques from the perspective of the common critique that machine learning offers increased predictive accuracy at the expense of explanatory insight. Particularly, we will argue and illustrate why and how machine learning can be a productive element in the abductive theory-building cycle.
    JEL: L1
    Date: 2019–09–20
  14. By: Colonnelli, E; Prem, M
    Abstract: We estimate the causal real economic effects of a randomized anti- corruption crackdown on local governments in Brazil over the period 2003-2014. After anti-corruption audits, municipalities experience an increase in economic ac- tivity concentrated in sectors most dependent on government relationships. These effects spill over to nearby municipalities and are larger when the audits are covered by the media. Back-of-the-envelope estimates suggest that $1 away from corrup- tion generates more than $3 in local value added. Using administrative matched employer-employee and firm-level datasets and novel face-to-face firm surveys we argue that corruption mostly acts as a barrier to entry, and by introducing costs and distortions on local government-dependent firms. The political misallocation of resources across firms plays a seemingly secondary role, indicating that at the local level most rents are captured by politicians and public officials rather than firms.
    Keywords: Corruption, firms, audits
    JEL: D73 H83 D22
    Date: 2019–09–19

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