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on Economics of Strategic Management |
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Issue of 2022‒06‒20
nine papers chosen by João José de Matos Ferreira Universidade da Beira Interior |
| By: | Charlotte Guillard; Ralf Martin; Pierre Mohnen; Catherine Thomas; Dennis Verhoeven |
| Abstract: | Research and development is underprovided whenever it creates knowledge spillovers that drive a wedge between its total and private economic returns. Heterogeneity in the intensity of this market failure across technological areas provides an argument to vertically target public support for R&D. This paper examines potential welfare gains of such vertical industrial policy for innovation. It develops measures of private and spillover value of patented innovations using global data on patents and their citations. Our new method identifies a large number 'Hidden Giants' - i.e. innovations scoring higher on our new spillover measure than on the traditional forward citation count measure - which are shown to be particularly prevalent among patents applied for by universities. The estimated distributions of private values by technology area are then used to parameterize a structural model of innovation. The model permits estimation of the marginal returns to technology-area-specific subsidies that reduce innovators' R&D costs. Marginal returns are high when knowledge spillovers in the technology area are valuable, when private innovation costs are low, and when private values in a technology sector are densely distributed around the private cost. The results show large variation in the marginal returns to subsidy and suggest that targeted industrial policy would have helped mitigate underprovision of R&D over the time period studied. Variation in the extent to which knowledge spillovers are internalized within countries also makes a compelling case for supranational policy coordination, especially among smaller countries. |
| Keywords: | research and development, patented innovations, decoupling, targeted industrial policy |
| Date: | 2021–11–04 |
| URL: | http://d.repec.org/n?u=RePEc:cep:cepdps:dp1813&r= |
| By: | Bratanova, Alexandra; Pham, Hien; Mason, Claire; Hajkowicz, Stefan; Naughtin, Claire; Schleiger, Emma; Sanderson, Conrad; Chen, Caron; Karimi, Sarvnaz |
| Abstract: | We demonstrate how cluster analysis underpinned by analysis of revealed technology advantage can be used to differentiate geographic regions with comparative advantage in artificial intelligence (AI). Our analysis uses novel datasets on Australian AI businesses, intellectual property patents and labour markets to explore location, concentration and intensity of AI activities across 333 geographical regions. We find that Australia's AI business and innovation activity is clustered in geographic locations with higher investment in research and development. Through cluster analysis we identify three tiers of AI capability regions that are developing across the economy: ‘AI hotspots’ (10 regions), ‘Emerging AI regions’ (85 regions) and ‘Nascent AI regions’ (238 regions). While the AI hotspots are mainly concentrated in central business district locations, there are examples when they also appear outside CBD in areas where there has been significant investment in innovation and technology hubs. Policy makers can use the results of this study to facilitate and monitor the growth of AI capability to boost economic recovery. Investors may find these results helpful to learn about the current landscape of AI business and innovation activities in Australia. |
| Keywords: | Artificial intelligence, cluster, revealed technology advantage, regional innovation, Australia |
| JEL: | O31 O33 O38 R12 |
| Date: | 2022–05–31 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:113237&r= |
| By: | Leogrande, Angelo; Costantiello, Alberto; Laureti, Lucio; Matarrese, Marco Maria |
| Abstract: | The following article investigates the determinants that lead innovative SMEs to collaborate. Data from 36 European countries is analyzed using Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled OLS, WLS and Dynamic Panel models. The analysis shows that the ability of innovative SMEs to collaborate is positively associated with the following variables: "Linkages", "Share High and Medium high-tech manufacturing", "Finance and Support", "Broadband Penetration", "Non-R&D Innovation Expenditure" and negatively to the following variables: "New Doctorate graduates", "Venture Capital", "Foreign Controlled Enterprises Share of Value Added", "Public-Private Co-Publications", "Population Size", "Private co-funding of Public R&D expenditures". A clustering with k-Means algorithm optimized by the Silhouette coefficient was then performed and four clusters were found. A network analysis was then carried out and the result shows the presence of three composite structures of links between some European countries. Furthermore, a comparison was made between eight different predictive machine learning algorithms and the result shows that the Random Forest Regression algorithm performs better and predicts a reduction in the ability of innovative SMEs to collaborate equal to an average of 4.4%. Later a further comparison is made with augmented data. The results confirm that the best predictive algorithm is Random Forest Regression, the statistical errors of the prediction decrease on average by 73.5%, and the ability of innovative SMEs to collaborate is predicted to growth by 9.2%. |
| Keywords: | Innovation, and Invention: Processes and Incentives; Management of Technological Innovation and R&D; Diffusion Processes; Open Innovation |
| JEL: | O30 O31 O32 O33 O34 |
| Date: | 2022–05–09 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:113008&r= |
| By: | Yojiro Ito (Economist, Institute for Monetary and Economic Studies (currently, Personnel and Corporate Affairs Department), Bank of Japan (E-mail: youjirou.itou@boj.or.jp)); Daisuke Miyakawa (Associate Professor, Hitotsubashi University Business School (E-mail: dmiyakawa@hub.hit-u.ac.jp)) |
| Abstract: | Studies on firm performance have found that exiting firms in Japan persistently show better performance than surviving firms, and this persistence adversely affects aggregate productivity. We use the panel data of business enterprises along with unique information on their exit modes (i.e., default, voluntary closure, and merger) to show that a large part of such a "negative exit effect" is attributed to the firms exiting through mergers. Further, we confirm that the causal effect of those mergers results in positive growth in the productivity of merging firms. Given that the size of such a positive causal effect overwhelms the negative exit effect, resource reallocation through mergers positively contributes to the aggregate growth in productivity for Japanese firms. |
| Keywords: | Productivity dynamics, Exit effects, Mergers |
| JEL: | D24 G33 G34 O47 |
| Date: | 2022–05 |
| URL: | http://d.repec.org/n?u=RePEc:ime:imedps:22-e-07&r= |
| By: | Kochetkov, Dmitry |
| Abstract: | Innovation is often perceived as an object of study in economics and management. However, the social and behavioural aspects of innovation acceptance are as important as the economics of the new product development. Based on the interdisciplinary perspective, the authors formulated their own definition of innovation for the purposes of this study. The authors consider innovation as a change in the way social action is conducted, entailing a wide range of social, economic, behavioural, and institutional changes. The variety of approaches gives rise to the need for a typology. J. Sundbo (1998) divided innovation into three groups depending on the aspect of the phenomenon: the theory of entrepreneurship; technological and social aspects; and the strategic aspect. Adopting the Sundbo conceptual framework, the authors supplemented and developed it based on the literature that appeared after 1998. The authors also added new directions at the second level of decomposition and the relationship between different aspects of innovation. In particular, attention was paid to such phenomena as open innovation, agile innovation, “helix” models, etc. Thus, the authors have developed a novel typology of innovations, which expands the theoretical knowledge in this field. |
| Date: | 2022–05–09 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:pv4zg&r= |
| By: | Audrey-Marie Moore; Edith Felix; Josh Meuth Alldredge |
| Abstract: | Our performance evaluation of the Higher Education Solutions Network (HESN) examines how USAID investments in universities, researchers, design networks, and innovators can contribute to evidence and innovation that drives international development. |
| Keywords: | Higher education, universities, innovation, USAID, country missions, development |
| URL: | http://d.repec.org/n?u=RePEc:mpr:mprres:60ad093d4e9e4f6b9acfa2c0f2651ad7&r= |
| By: | Pavel Vashchenko; Alexei Verenikin; Anna Verenikina |
| Abstract: | The article is devoted to the competitiveness analysis of Russian institutions of higher education in international and local markets. The methodology of research is based on generalized modified principal component analysis. Principal components analysis has proven its efficiency in business performance assessment. We apply a modification of this methodology to construction of an aggregate index of university performance. The whole set of principal components with weighting coefficients equal to the proportions of the corresponding explained variance are utilized as an aggregate measure of various aspects of higher education. This methodology allows to reveal the factors which exert positive or negative influence on university competitiveness. We construct a kind of objective ranking of universities in order to estimate the current situation and prospects of higher education in Russia. It is applicable for evaluation of public policy in higher education, which, by inertia, aims to promote competition rather than cooperation among universities. |
| Date: | 2022–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2205.04426&r= |
| By: | COAD Alexander; AMARAL-GARCIA Sofia (European Commission - JRC); BAUER Peter (European Commission - JRC); DOMNICK Clemens (European Commission - JRC); HARASZTOSI Peter; PAL Rozalia; TERUEL Mercedes |
| Abstract: | This paper contributes to a fast-growing literature on the impact of COVID-19 on the business economy, by focusing on how a particular group of firms - High-Growth Enterprises (HGEs) have been affected by COVID-19 across several dimensions, such as investment expectations, investment priorities, employment decisions, and their post-COVID-19 green and digital transitions. Using the EIB Investment Survey (EIBIS) and relying on descriptive statistics and basic regressions, the results suggest that COVID-19 has had a significant impact on the investment expectations of HGEs, although they continue to invest slightly more than non-HGEs. Preliminary results suggest that HGEs appear to be more optimistic than non-HGEs in a variety of dimensions, such as optimism surrounding the use of digital technologies, and willingness to invest in climate mitigation and adaptation. However, our evidence shows that the HGEs in the 2020 survey wave have still been hit hard by the COVID-19 shock, compared to HGEs in previous years, which suggests that there may be a role for policy for supporting these valuable firms. |
| Keywords: | High-Growth Enterprises, COVID-19: investment expectations, green and digital transitions |
| Date: | 2022–05 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:wpaper:202201&r= |
| By: | Thomas Sampson |
| Abstract: | Firm-to-firm relationships in global value chains create opportunities for North-South technology diffusion. This paper studies technology transfer in value chains when contracts are incomplete and in-put production technologies are imperfectly excludable. The paper introduces a new taxonomy of value chains based on whether or not the headquarters firm benefits from imitation of its supplier's technology. In inclusive value chains, where imitation is beneficial, the headquarters firm promotes technology diffusion. By contrast, in exclusive value chains headquarters seeks to limit supplier imitation. The paper analyzes how this distinction affects the returns to offshoring, the welfare effects of technical change and the social efficiency of knowledge sharing. Weaker intellectual property rights over input production technologies raise welfare when value chains are inclusive, but have the opposite effect under exclusive value chains. |
| Keywords: | technology transfer, global value chains, incomplete contracts, intellectual property rights, imitation |
| Date: | 2022–12 |
| URL: | http://d.repec.org/n?u=RePEc:cep:cepdps:dp1826&r= |