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on Small Business Management |
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Issue of 2024–12–30
fifteen papers chosen by João Carlos Correia Leitão, Universidade da Beira Interior |
| By: | Ali-Yrkkö, Jyrki; Kauhanen, Antti |
| Abstract: | Abstract This study examines the impact of foreign acquisitions on innovation activities in Finnish target firms using comprehensive linked employer-employee data from 2010–2021. Unlike previous research that found negative effects on R&D expenditures and patenting, we measure innovation through the share of R&D personnel in total employment. Our main finding is that foreign acquisitions have a statistically insignificant and economically small impact on the share of R&D employees in target firms. Three years post-acquisition, the point estimate shows a 0.9 percentage point increase in R&D employee share, and we can rule out increases over 2 percentage points and decreases below 0.09 percentage points. This null effect persists across different firm sizes and industries. Our results suggest that con-cerns about foreign acquisitions substantially reducing domestic R&D activity may be overstated, at least when measured by R&D employment. |
| Keywords: | Acquisition, M&A, Research, Development, R&D, Innovation, Impact |
| JEL: | O3 L6 L64 |
| Date: | 2024–11–27 |
| URL: | https://d.repec.org/n?u=RePEc:rif:wpaper:122 |
| By: | Colin Wessendorf |
| Abstract: | Key enabling technologies (KETs) have gained attention in science and policy due to their multidisciplinary nature and their ability to link distant knowledge fields, endowing them with a central role in recombinant innovation processes. However, it remains under-researched whether KETs generally have a higher influence on innovation processes than non-KETs. This study addresses the question by using propensity score matching and regression analysis. First, a balanced dataset is created through matching KET patents to non-KET patents that stem from a comparable context. Subsequently, it is analyzed whether KET patents are associated with higher forward citation frequencies than non-KETs. The results show that KETs receive more citations on average, but it appears that this effect is driven by a few very impactful patents. The results further show that not all KETs exert a measurable impact on forward citations and highlight the heterogeneities between the individual KETs. These findings call for a more critical assessment of the KET concept and for nuanced approaches in research and policy. |
| Keywords: | Key enabling technologies, general purpose technologies, recombinant novelty, technological impact, patent citations, propensity score matching |
| JEL: | O30 O31 O33 C21 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:atv:wpaper:2403 |
| By: | Armin Schmutzler |
| Abstract: | By affecting prices and thereby market shares of green and brown firms, product innovations and process innovations influence industry emissions even when they do not directly affect the emission intensity of the innovating firm. Using a differentiated two-stage duopoly, this paper therefore analyzes the effects of environmental policy on such innovations, and it asks how these effects differ from each other and from those of environmental innovations that directly reduce the emission intensity. The paper investigates the determinants of R&D investments, showing in particular that incentives for certain types of potentially beneficial innovations may be negative. Moreover, it analyzes how suitable policies can foster green innovation. |
| Keywords: | Innovation, environmental policy, imperfect competition |
| JEL: | Q55 L13 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:zur:econwp:462 |
| By: | Mirko Draca; Max Nathan; Viet Nguyen-Tien; Juliana Oliveira-Cunha; Anna Rosso; Anna Valero |
| Abstract: | Which types of human capital influence the adoption of advanced technologies? We study the skill-biased adoption of information and communication technologies (ICT) across two waves in the UK. Specifically, we compare the 'new wave' of cloud and machine learning / AI technologies during the 2010s-pre-LLM-with the previous wave of personal computer adoption in the 1990s and early 2000s. At the area-level we see the emergence of a distinct STEM-biased adoption effect for the second wave of cloud and machine learning / AI technologies (ML/AI), alongside a general skill-biased effect. A one-standard deviation increase in the baseline share of STEM workers in areas is associated with around 0.3 of a standard deviation higher adoption of cloud and ML/AI. We find similar effects at the firm level where we are able to test for the influence of a wide range of skills. In turn, this STEM-biased adoption pattern has encouraged the concentration of these technologies, leading to more acute differences between high-tech and low-tech areas and firms. In contrast with classical technology diffusion, recent cloud and ML/AI adoption in the UK seems more likely to widen inequalities than reduce them. |
| Keywords: | Technology Diffusion, ICT, Human Capital, STEM |
| JEL: | D22 J24 O33 R11 |
| Date: | 2024–10–20 |
| URL: | https://d.repec.org/n?u=RePEc:csl:devewp:495 |
| By: | Flavio Calvino; Chiara Criscuolo; Luca Fontanelli; Lionel Nesta; Elena Verdolini |
| Abstract: | We leverage a uniquely comprehensive combination of data sources to explore the enabling role of human capital in fostering the adoption of predictive AI systems in French firms. Using a causal estimation approach, we show that ICT engineers play a key role for AI adoption by firms. Our estimates indicate that raising the current average share of ICT engineers in firms not using AI (1.66%) to the level of AI users (6.7%) would increase their probability to adopt AI by 0.81 percentage points - equivalent to an 8.43 percent growth. However, this would imply substantial investments to fill the existing gap in ICT human capital, amounting to around 450.000 additional ICT engineers. We also explore potential mechanisms, showing that the relevance of ICT engineers for predictive AI is driven by the innovative nature of its use, make-vs-buy choices, large availability of data, ICT and R&D intensity. |
| Keywords: | artificial intelligence, human capital, technological diffusion |
| Date: | 2024–11–18 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2055 |
| By: | Stefano Basilico; Alberto Marzucchi; Sandro Montresor; ; |
| Abstract: | This paper focuses on the combination of green and digital technologies at the regional level. Using patent data, we put forward an original measurement of the regional speed of green-digital (i.e. twin) combination: the temporal distance between the time at which a combination is realised for the first time in the frontier region and the time at which this same combination is accomplished in the focal region. We proceed by investigating the drivers and the technological impact related to this speed. We find that the speed of combination is enhanced by dealing with broad and diverse twin technologies. The speed at which the gap is closed, also crucially depends on the interdependencies between green and digital domains, captured by the overlap in their knowledge bases. Counterintuitively, the longer the combination paths, the faster the region combines green and digital technologies. This finding is then rationalised further looking at the policy and network characteristics. Finally, we find that the earlier the combination happens, the greater is likely to be the impact on subsequent inventions, but only for granted patents. Overall, these results are discussed in terms of policy recommendations, given the high attention placed by policymakers on the twin transition. |
| Keywords: | Twin transition; Digital technologies; Green technologies; Regional knowledge base |
| JEL: | O31 O33 R11 R12 Q55 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:egu:wpaper:2440 |
| By: | Kärnä, Anders (Financial Stability Department, Central Bank of Sweden); Myers, Samantha (Financial Stability Department, Central Bank of Sweden) |
| Abstract: | We study the effects on firms that are acquired by private equity firms in a leveraged buyout, using detailed Swedish registry data covering 1998-2022. Acquired firms see a large increase in their debt and debt related variables, but no significant change in productivity. This suggests that, on average, private equity firms target profitable firms and increase their size through the addition of leverage. |
| Keywords: | Private Equity; LBOs; Firm Performance |
| JEL: | G34 L25 |
| Date: | 2024–11–01 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:rbnkwp:0444 |
| By: | Jean-Michel Benkert, Igor Letina |
| Abstract: | We provide a model of investment in innovation that is dynamic, features multiple heterogeneous research projects of which only one potentially leads to success, and in each period, the researcher chooses the set of projects to invest in. We show that if a search for innovation starts, it optimally does not end until the innovation is found—which will be never with a strictly positive probability. |
| Keywords: | Innovation, Optimal Search, Infinite Horizon |
| JEL: | D83 O31 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:ube:dpvwib:dp2410 |
| By: | Dawid, Herbert (Center for Mathematical Economics, Bielefeld University); Riedel, Frank (Center for Mathematical Economics, Bielefeld University); Steg, Jan-Henrik (Center for Mathematical Economics, Bielefeld University); Wen, Xingang (Center for Mathematical Economics, Bielefeld University) |
| Abstract: | We study endogenous, credit-financed innovation under uncertainty in dynamic con- texts. In our model, a firm with limited cash reserves decides how much to invest in an R&D project, potentially using external financing. Investing more increases the proba- bility of a sooner innovation, but higher repayment obligations also increase bankruptcy risk if the innovation takes longer. We show that the firm reduces its investment dis- continuously if the financing cost is not favorable enough, in order to avoid the need for external financing. This insight implies that policies reducing financing costs can have discontinuous positive effects on investment, innovation rate and welfare. How- ever, policy measures increasing the effectiveness of R&D might reduce the innovation rate and welfare due to a discontinuous reduction of R&D investment. Furthermore, we find that low financing costs can lead to over-investment. The welfare loss from cash constraints is more severe for radical innovations compared to incremental ones. |
| Keywords: | Innovation, R&D investment, Cash constraints, Bankruptcy risk |
| Date: | 2024–12–09 |
| URL: | https://d.repec.org/n?u=RePEc:bie:wpaper:699 |
| By: | Steven Callander (Stanford University, Stanford Graduate School of Business); Hongyi Li (University of New South Wales, School of Economics) |
| Abstract: | Innovations bring many benefits to society, but they can also bring harm. We study the problem of a regulator deciding whether to approve an innovation where information about the impact of the innovation is held within the firms that are developing it. We show that competition for the innovation undermines the regulator’s ability to extract the information she needs to make good policy. As the number of firms increases and the expected benefit of the innovation grows, the probability that the regulator is persuaded to approve an innovation decreases. This tension between competition and communication reverses Arrow’s famous “replacement effect.” Thus, in regulated markets, more competition can lead to fewer innovations making it to market. We explore how this tension can be mitigated, but not eliminated, by political and market design. |
| Keywords: | Innovation, regulation, competition |
| JEL: | L51 O31 D82 |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:swe:wpaper:2024-07 |
| By: | Petre Caraiani (Institute for Economic Forecasting, Romanian Academy; Bucharest University of Economics Studies); Carolyn Chisadza (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Rangan Gupta (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa) |
| Abstract: | This study updates the existing literature on the adverse effects of climate change on firms' performance by providing an alternative perspective that climate change can have potential growth benefits. We examine the effects of climate shocks on firms' investments. Using a spatial autoregressive model with United States (U.S.) firm-level data from 1985 to 2019, we find that increased frequency of climate shocks is positively associated with investments for firms, with larger spillover effects on neighbouring firms. These findings remain consistent for various robustness checks which include sub-sample analysis, different outcome variables and controlling for financial characteristics of the firms. The results highlight that contrary to current evidence, climate change can create incentives for firms to increase investments in adjusting their production processes to cleaner technologies. |
| Keywords: | Climate shocks, Corporate investments, Spatial econometrics, Production network structure |
| JEL: | C31 D24 D92 Q54 |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:pre:wpaper:202448 |
| By: | Zhang Nian (Faculty of Management, Universiti Teknologi Malaysia Author-2-Name: Logaiswari Indiran Author-2-Workplace-Name: Department of Marketing and Entrepreneurship, Faculty of Management, Universiti Teknologi Malaysia, 81310, Skudai Johor, Malaysia Author-3-Name: Zuraidah Sulaiman Author-3-Workplace-Name: "Department of Marketing and Entrepreneurship, Faculty of Management, Universiti Teknologi Malaysia, 81310, Skudai Johor, Malaysia " Author-4-Name: Maria Anityasari Author-4-Workplace-Name: Department of Industrial and Systems Engineering, Institut Teknologi Sepuluh Nopember (ITS), Sukolilo Campus Surabaya Indonesia 60111 Author-5-Name: Author-5-Workplace-Name: Author-6-Name: Author-6-Workplace-Name: Author-7-Name: Author-7-Workplace-Name: Author-8-Name: Author-8-Workplace-Name:) |
| Abstract: | " Objective - This study aims to investigate whether corporate social responsibility (CSR) promotes R&D investment, whether R&D investment promotes Total Factor Productivity (TFP), and whether R&D investment plays a mediating role in the impact CSR on TFP. Methodology/Technique – Based on the hypotheses, this study constructed the structural equation model, with CSR as the independent variable, TFP as the dependent variable, and R&D as the mediating variable. The control variables are capital investment (CAP), gearing (LEV) and return on assets (ROA). The causal relationship and the heterogeneity of regional and Senior managers attributes were analyzed using SPSS software. Findings – Based on all sample data and analyzed using SPSS, it is found that CSR in the solid waste treatment industry has a positive effect on R&D investment, and R&D investment has a positive effect on TFP. Meanwhile, R&D investment plays a mediating role in the impact of CSR on enterprises' TFPs. Novelty – The novelty of this paper lies in the fact that China's solid waste treatment industry was selected as the object of analysis, and the relationship between CSR and TFP as well as the mediating effect of R&D investment in this industry were analyzed. Type of Paper - Empirical" |
| Keywords: | Corporate Social Responsibility; Research and Development; Solid Waste Treatment Industry |
| JEL: | M14 O32 Q53 |
| Date: | 2024–11–30 |
| URL: | https://d.repec.org/n?u=RePEc:gtr:gatrjs:jfbr225 |
| By: | Nadine Levratto; Mounir Amdaoud |
| Abstract: | This paper investigates how variety affects regional employment growth in France over the period 2004-2015. Starting from the seminal contribution of Frenken et al. (2007), we argue that intra-industry externalities foster employment growth. However, we don’t distinguish yet between the own effect of related variety of the region and that of its neighbourhood. Hence, we suggest that conceptual progress can be made when analysis considers the direct and indirect (neighbourhood) dimension of variety. Our empirical investigations confirm that related variety has a positive effect on employment growth. Moreover, this impact seems to be driven by the endogenous dimension of related variety in growth phase and by exogenous dimension in crisis period. We also find that the negative relationship between unrelated variety and employment growth goes only through the endogenous canal. |
| Keywords: | Related variety, unrelated variety, employment growth, neighbourhood effects, France |
| JEL: | R11 O18 D62 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:drm:wpaper:2024-34 |
| By: | Joachim Hubmer (University of Pennsylvania); Mons Chan (Queen’s University); Serdar Ozkan (Federal Reserve Bank of St. Louis, University of Toronto); Sergio Salgado (University of Pennsylvania); Guangbin Hong (University of Chicago) |
| Abstract: | Do larger firms have more productive technologies, are their technologies more scalable, or both? We use administrative data on Canadian and US firms to estimate a joint distribution of output elasticities of capital, labor, and intermediate inputs—thus, returns to scale (RTS)—along with total factor productivity (TFP). We find significant heterogeneity in RTS across firms within industries. Furthermore, larger firms operate technologies with higher RTS, whereas the largest firms do not exhibit the highest TFP. Higher RTS for large firms are entirely driven by higher intermediate input elasticities. Descriptively, these align with higher intermediate input revenue shares. We also show that high-RTS firms grow faster, pay higher wages, and are owned by wealthier households. We then incorporate RTS heterogeneity into the workhorse model of endogenous entrepreneurship that matches the observed heterogeneity in TFP and RTS. We find that the efficiency losses from financial frictions are more than twice as large compared to a conventional calibration that attributes all heterogeneity to TFP and assumes a common RTS parameter. |
| Keywords: | Production function heterogeneity, returns to scale, misallocation |
| JEL: | E22 L11 L25 |
| Date: | 2024–11–21 |
| URL: | https://d.repec.org/n?u=RePEc:pen:papers:24-036 |
| By: | MOTOHASHI Kazuyuki; KIM Young Gak |
| Abstract: | With the development of new AI technologies such as generative AI, the use of AI in business is progressing in companies. However, it is said that few companies are achieving concrete business advantages from AI. In order to fully realize the potential benefits of AI implementation, companies require complementary management resources such as skilled human resources implementation and data utilization, in addition to organizational changes through digital transformation (DX), but the lack of company-wide AI utilization strategies is thought to be the cause of insufficient investment in these resources. With this problem in mind, the Research Institute of Economy, Trade and Industry conducted the "Survey on AI and Data Utilization" from January to March 2024. Here, using the results of this survey (a postal survey of 5, 000 companies, responses were obtained from 650 companies: response rate 13%), we will present the results of an analysis using descriptive statistics focusing on the management resources that are necessary to achieve concrete organizational benefits of AI implementation. The results revealed that companies that have introduced AI are relatively young companies, and that the adoption rate is not necessarily high among large companies. In terms of the skills required for data utilization personnel, companies that have introduced AI tend to place more emphasis on knowledge of their business domain, while companies that have not introduced AI tend to be more focused on information processing and programming skills. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:eti:rpdpjp:24010 |