Economics of Innovation and New Technology最新文献

{"title":"Mitigating the labor displacing effects of automation through a robot tax: evidence from a survey experiment","authors":"Emanuela Carbonara, Chiara N. Focacci, Enrico Santarelli","doi":"10.1080/10438599.2023.2293031","DOIUrl":"https://doi.org/10.1080/10438599.2023.2293031","url":null,"abstract":"We examine how taxation might influence the relationship between automation and employment dynamics. The results obtained through a survey experiment with 2,000 entrepreneurs residing in the U.S. s...","PeriodicalId":51485,"journal":{"name":"Economics of Innovation and New Technology","volume":"1 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138681218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Are temporary hires good or bad for innovation? The Italian evidence","authors":"Stefano Dughera, Francesco Quatraro, Andrea Ricci, Claudia Vittori","doi":"10.1080/10438599.2023.2287443","DOIUrl":"https://doi.org/10.1080/10438599.2023.2287443","url":null,"abstract":"This paper investigates the relationship between temporary workers and innovation. We model a firm’s choice concerning: (i) the mix of temporary and permanent workers; (ii) the optimal level of tra...","PeriodicalId":51485,"journal":{"name":"Economics of Innovation and New Technology","volume":"459 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138496224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of ultra-fast broadband on labor income: an event study approach","authors":"Laura Abrardi, Carlo Cambini, Lorien Sabatino","doi":"10.1080/10438599.2023.2275211","DOIUrl":"https://doi.org/10.1080/10438599.2023.2275211","url":null,"abstract":"ABSTRACTWe investigate the impact of ultra-fast broadband connections on labor income and employment. We use panel data for Italian municipalities for the period 2012–2019 and we exploit the staggered roll-out of ultra-fast broadband started in 2015. Through an event study approach, we find evidence of endogeneity between ultra-fast broadband roll-out and labor market outcomes. To identify causal relationships, we use income from pensions to implement the estimator developed by [Freyaldenhoven, S., C. Hansen, and J. M. Shapiro. 2019. “Pre-Event Trends in the Panel Event-Study Design.” American Economic Review 109 (9): 3307–3338. https://doi.org/10.1257/aer.20180609.]. We find that access to ultra-fast broadband increases the income of the self-employed by 1.3% but has no impact on workers. Such an effect is mostly driven by a rise in self-employed workers, which is concentrated in urban areas, and in municipalities at the top and bottom quartiles of labor income.KEYWORDS: Ultra-fast broadbandfiber-based networkslabor incomeself-employed workersJEL CODES: L96D24D22 AcknowledgmentsWe would like to thank the Editor, three anonymous Referees, as well as Fabio Landini, Giovanni Cerulli and the participants to the SIE 2022 (Torino) and SIEPI 2022 (L'Aquila) for useful comments and suggestions to previous versions of the paper. We are grateful to Mario Mirabelli (TIM-LAB) and Francesco Nonno (OpenFiber) for providing us with access to and guidance on the broadband data used in this paper. The views expressed herein represent those of the authors and do not reflect in any case the opinions of the companies and institutions that provided the data and funding.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 Indeed, starting in 2018, the Italian government has increased the financial resources from 0.5 to 7 billion Euros for UBB. In 2021, the Italian Government has decided to use part of the Next Generation EU funds to finalize the deployment of UBB infrastructure throughout the country, with around 3.6 billion Euros of public expenditure.2 The two papers also differ in the UBB variable used. While we consider a dummy variable describing the availability of a UBB access in a municipality in a given year, Abrardi and Sabatino (Citation2023) use the number of years since UBB was introduced in a given municipality.3 Higher broadband speed levels may also affect property prices (Ahlfeldt, Koutroumpis, and Valletti Citation2017) and firms' location decisions (Canzian, Poy, and Schüller Citation2019; Duvivier Citation2019).4 The Digital Agenda for Europe specifies the goals in terms of network coverage and service adoption for the whole European population. See https://www.europarl.europa.eu/factsheets/en/sheet/64/digital-agenda-for-europe for more.5 https://www.agcom.it/documents/10179/1571667/Documento+generico+08-11-2014+1415441917492/d34cc914-c150-4fd7-a383-a0c39c9d7670?version=1.16 Before 2015 only a few large cities","PeriodicalId":51485,"journal":{"name":"Economics of Innovation and New Technology","volume":"4 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135972837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Innovation-driven economic growth under global turbulence: how countries strengthen innovation systems to deal with threats","authors":"Valeriya Vlasova, Anastasia Saprykina","doi":"10.1080/10438599.2023.2276318","DOIUrl":"https://doi.org/10.1080/10438599.2023.2276318","url":null,"abstract":"ABSTRACTThe role of innovation as a major force of economic growth is not to doubt. Despite this, geopolitical challenges in recent years pose difficulties for countries, especially for those who struggle with lower GDP per-capita, to enhance innovative performance and grow. Building upon the national innovation system concept and using the methodological framework of country-level composite innovation indexes, this paper aims to explore features of innovation systems inherent in lagging economies and their relevance for economic growth. The analysis, based on a panel dataset comprising the Global Innovation Index elementary indicators on 76 countries during 2015–2021, demonstrates the lower initial state, but faster development of innovation system components in lagging economies. Crucial to their growth is the external validation of national innovation efforts, proxied by international trade and foreign investment indicators. In addition, a sustainable economic growth requires balanced and synergetic development of all components and functions. Therefore, bottom-up approaches are needed to sustain further growth of lagging economies, starting with the provision of effective resource allocation, knowledge creation and its diffusion.KEYWORDS: national innovation systemeconomic growthglobal innovation indexcross-country analysislagging economiesSUBJECT CLASSIFICATION CODES: O11O36O47O57P51 AcknowledgementsWe thank the editor and anonymous reviewers for their helpful comments. We also express our gratitude to Dr. Vitaliy Roud (Zagreb School of Economics and Management) for his valuable suggestions on the initial stage of the study.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 The World Bank Income Group Classification is yearly revised, which makes it impossible to use the division for the longitudinal analysis. Hence, the authors used alternative approach to classify the countries, applied for e.g. in (Fagerberg, Srholec, and Knell Citation2007).2 The choice of sample median as a threshold to classify countries is dictated by the presence of some outliers in the data that would produce a less balanced sample, in case the sample average was used.3 The ‘oblique' rotation type is preferred over orthogonal rotations such as ‘varimax normalized' rotation, since the latter assumes that the underlying factors are close to be completely uncorrelated, which is a too strong assumption (Fabrigar et al. Citation1999). The scree plot analysis was further conducted in order to define the resulting number of principal components to be retained.4 The model considers both the initial value for the period and the growth rate of the corresponding NIS componentsAdditional informationFundingThe article was prepared within the framework of the Basic Research Program of the HSE University.","PeriodicalId":51485,"journal":{"name":"Economics of Innovation and New Technology","volume":"8 22","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135973404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The unequal implications of Industry 4.0 adoption: evidence on productivity growth and convergence across Europe","authors":"Fabio Lamperti, Katiuscia Lavoratori, Davide Castellani","doi":"10.1080/10438599.2023.2269089","DOIUrl":"https://doi.org/10.1080/10438599.2023.2269089","url":null,"abstract":"ABSTRACTDo new manufacturing technologies of the Industry 4.0 (I4.0) boost TFP growth? By adopting a distance-to-frontier framework, this paper explores whether the adoption of (advanced) digital technologies affect the sectoral TFP growth rates across manufacturing industries of 14 European countries, during the period 2009–2019. We rely on a novel measure of adoption of I4.0 technologies (namely, advanced industrial robots, additive manufacturing and industrial internet of things), exploiting highly detailed (8-digit level) information on imports of capital goods embodying such technologies. Our results suggest that adopting new digital manufacturing technologies of the I4.0 brings quantitatively important and statistically significant contributions to sectoral TFP growth rates, although these are mostly concentrated in countries close to the technology frontier. In turn, these technologies seem to have hampered the process of convergence between European technological leaders and laggards over the last decade.KEYWORDS: Industry 4.0fourth industrial revolutiontechnology diffusiontotal factor productivity (TFP)technological convergenceJEL CLASSIFICATION: O11O33O47 AcknowledgementsWe thank the Editor and two anonymous reviewers for their most constructive and helpful suggestions. The authors are especially grateful to Marco Grazzi and to Eduardo Ibarra-Olivo for their valuable comments and suggestions, and to the participants of the Italian Trade Study Group meeting (Ancona, November 2020) and of the seminar at the Economics Department (University of Perugia, May 2021) for their comments on earlier versions of this paper.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 Their disruptive potential results from their potential for a widespread application across every manufacturing industry due to their ‘versatility and complementarity’ (Eurofound Citation2018, 3). Furthermore, while we already acknowledged the impact I4.0 technologies have on manufacturing operations – e.g. higher operational flexibility, higher production efficiency and quality, lower set-up costs and integration along the value chain, resulting in higher productivity and better performance overall (see also Skilton and Hovsepian Citation2017; Eurofound Citation2018) – additional high-level impact resides in the world of work and, in general, the entire society. On the one hand, a general concern around the ‘risks of new monopolies, mass redundancies, spying on workers, and the extension of precarious digital work’ (Davies Citation2015, 9) emerges. On the other hand, this transformation calls for a policy debate on the upcoming changes in the task content and occupational profiles of manufacturing employment (Frey and Osborne Citation2017; Eurofound Citation2018).2 In this work, we focus on studies addressing the implications of ‘physical’ I4.0 technology adoption. We stress the difference between ‘physical’ (i.e. capital embodied) and ‘di","PeriodicalId":51485,"journal":{"name":"Economics of Innovation and New Technology","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135858968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How do local government fiscal revenue targets affect green technology innovation in China?","authors":"Jingxia Chai, Yu Hao, Haitao Wu, Yunke Yu, Nan Hu","doi":"10.1080/10438599.2023.2267447","DOIUrl":"https://doi.org/10.1080/10438599.2023.2267447","url":null,"abstract":"ABSTRACTThe process of economic development in China cannot be separated from the ‘shadow’ of government target intervention. Under the Chinese system of fiscal decentralization, constraints created by local government fiscal revenue targets (CCFRTs) will have a series of influence on development economically and socially. Based on the fiscal revenue target data revealed in the government work reports of 281 prefecture-level cities in China from 2006 to 2019, this paper explores the influence of CCFRTs on green technology innovation (GTI). The findings are as follows: first, CCFRTs significantly inhibits GTI. Second, Spatial Durbin model analysis shows that CCFRTs has significant negative spatial spillover effect on GTI. Third, CCFRTs can affect GTI through the optimization of industrial structure, the level of human capital, and the degree of opening-up, technological progress and economic growth. Fourth, CCFRTs has an obvious threshold effect on GTI. Finally, the influence of CCFRTs on GTI has regional heterogeneity in central, eastern and western China. In the western and central regions, CCFRTs significantly restrains GTI significantly, while in the eastern region, CCFRTs significantly promotes GTI.KEYWORDS: Constraints created by local government fiscal revenue targetsgreen technology innovationinfluence mechanismspatial effect AcknowledgmentsThe authors acknowledge financial support from the Special Fund for Joint Development Program of the Beijing Municipal Commission of Education. The usual disclaimer applies. The usual disclaimer applies.Data availability statementThe data are available upon reasonable request.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 https://www.gov.cn/zhuanti/19thcpc/ (accessed on 6 December 2022).2 http://zhs.mofcom.gov.cn/article/zt_shisiwu/subjectcc/202107/20210703175933.shtml. (accessed on 6 December 2022).3 China operates under a unitary state system characterized by a hierarchical structure of state administration, encompassing five distinct levels: the central government, provincial authorities, municipal entities, county administrations, and township governance. According to China's current system, the national and provincial governments grant prefecture-level governments the authority to set their own fiscal revenue targets. Therefore, each prefecture-level city has its own autonomy in the formulation of fiscal revenue targets, and there is no centralized state intervention. This paper mainly selects fiscal revenue target data at the municipal level for analysis.4 The ‘yardstick effect’ refers to the basis for the assessment and promotion of officials in China's government structure, the possibility of promotion of local governments is getting smaller and smaller under the pyramid-type sector structure. In order to better win the trust and recognition of the superior government and gain promotion, there is a ‘contest’ between governments at the same level. There","PeriodicalId":51485,"journal":{"name":"Economics of Innovation and New Technology","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136211184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Innovation, asymmetric information and the capital structure of new firms","authors":"Jonathan Taglialatela, Andrea Mina","doi":"10.1080/10438599.2023.2265821","DOIUrl":"https://doi.org/10.1080/10438599.2023.2265821","url":null,"abstract":"ABSTRACTStart-ups are essential contributors to economic development, but they often face several barriers to growth, including access to finance. We study their capital structure in their early years of operation through the lens of Pecking Order Theory, exploring how the pursuit of innovation influences firms’ reliance on different types of finance. Panel analyses of 8273 German start-ups show that innovation activities are relevant predict start-ups’ revealed preferences for finance. Effects on the type and order of financing sources depend on the degree of information asymmetries specific to research and development activities, human capital endowments, and the market introduction of new products and processes. New firms focused on research and development activities and with better human capital are less likely to receive informationally complex finance such as debt and will rely relatively more on owner and equity finance. Mixed evidence is found, instead, on the role of new products or processes. Our results suggest that the traditional pecking order theory does not hold for new firms, implying that owner and external equity play a much more prominent role for such firms. Then, managers and entrepreneurs should consider specific sources of finance and financial instruments in light of their innovative activities.KEYWORDS: Innovationinformation asymmetriesstart-uppecking orderentrepreneurial financeJEL CODES: G32O16O30 Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 For a broader discussion on the relationship between Schumpeterian innovation and firm financial constraints see Hajivassiliou and Savignac (Citation2008), Hottenrott and Peters (Citation2012) and Lahr and Mina (Citation2021).2 Following this perspective, several contributions have explored the effect of innovation on investment selection behaviours in venture capital markets (Audretsch, Bönte, and Mahagaonkar Citation2012; Baum and Silverman Citation2004; Conti, Thursby, and Thursby Citation2013; Conti, Thursby, and Rothaermel Citation2013; Häussler, Harhoff, and Müller Citation2012; Hsu and Ziedonis Citation2013; Mann and Sager Citation2007; Lahr and Mina Citation2016).3 Before 2014 this database was known as KfW/ZEW Start-up Panel.4 The first two years of data (i.e., 2005-2006) only contain information about the firm’s cost, investments and revenues and exclude information on innovation. Therefore, they cannot serve the purpose of this study.5 We stress that our data indicate the types of financing obtained by firms, but contain no information on whether firms have applied for other types of finance and were rejected. In other words, without observation of finance-seeking behaviours, we can only observe the “revealed preferences” of firms.6 The results of simple Logit models are available upon request. All the statistical tests confirmed the better fit of all panel specifications.","PeriodicalId":51485,"journal":{"name":"Economics of Innovation and New Technology","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136354169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of technological change on growth trajectory of India: a multivariate-BVAR analysis","authors":"Debasis Rooj, Rituparna Kaushik","doi":"10.1080/10438599.2023.2267994","DOIUrl":"https://doi.org/10.1080/10438599.2023.2267994","url":null,"abstract":"ABSTRACTThis paper examines the impact of technological change on Indian economic growth using the Bayesian Vector Auto-Regressive (BVAR) methodology. We use a comprehensive annual time series dataset covering the period of 1980 to 2019 on real economic activity, gross fixed capital formation, and employment. Technological innovation is measured by the number of patents filed by resident Indians. Technological innovation positively impacts both economic growth and gross fixed capital formation. Our findings indicate that increasing the number of patents leads to higher investment, which drives India's economic growth. However, our results also point towards the possible negative influence of technological innovation on the aggregate employment scenario in India. Our main findings are robust to alternative identification strategies and variable transformation. The asymmetric analysis also corroborates the positive influence of patents on driving investment and economic growth in India.KEYWORDS: Economic growthtechnological changepatentsBayesian VARJEL CLASSIFICATION: E44E31 AcknowledgmentWe thank the Managing Editor, Prof. Cristiano Antonelli, for providing invaluable suggestions in helping us improve the manuscript. We also thank three anonymous reviewers of our manuscript for their detailed comments and suggestions. We also thank Dr. Reshmi Sengupta, Dr. Nilanjan Banik, and Dr. Arnab Chakrabarti for their suggestions and comments in improving certain sections of the paper.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 Antonelli and Scellato provide comprehensive discussions on the idea of \"Innovation.\"2 Although the data is available until 2020, we restrict our sample to 2019 and exclude 2020 to avoid the problem that can arise due to the COVID-19 pandemic.3 Normal-Wishart prior constraints λ2 to the value of 1. We have estimated the baseline model with different set values for the hyperparameters. The finding suggests that IRFs are not qualitatively different due to changes in the values of the hyperparameters. However, for some choices, the confidence intervals become wider or narrower, and these are only indicative of the shape of the posterior distribution and have no statistical significance. Therefore, we can conclude that the findings from these specifications are robust to choices of different hyperparameter values for the priors.4 We have considered slightly lower values of the AR(1) parameter, such as 0.9 and 0.8, but it has a negligible impact on the results.5 The DIC value for our baseline model is -969.84.6 BVAR estimation is conducted by employing the BEAR toolbox in MATLAB developed by Dieppe et al. (Citation2016)7 Sims and Zha (Citation1999) assert that the traditional frequentist error bands may be misleading as they mix parameter location information with model fit information. The authors propose using likelihood-based bands and argue that 68% interval bands provide a more precise es","PeriodicalId":51485,"journal":{"name":"Economics of Innovation and New Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136352432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Firm survival and innovation: direct and indirect effects of knowledge for SMEs","authors":"Sergio Destefanis, Ornella Wanda Maietta, Fernanda Mazzotta, Lavinia Parisi","doi":"10.1080/10438599.2023.2263371","DOIUrl":"https://doi.org/10.1080/10438599.2023.2263371","url":null,"abstract":"ABSTRACTThis paper explores the effects of innovation on firm survival by using data from a representative survey of small and medium manufacturing firms in the province of Salerno, Italy. We innovate upon the literature by (a) comparing the impact of different sources of internal and external knowledge (including universities) on the probability of firm survival; (b) assessing the mediating impact of the human capital of workers and entrepreneurs on learning from these knowledge sources. Finally, we measure the impact of different types of innovation on firm survival. Our evidence upholds the link between innovation and firm survival, particularly for product and organisational innovation. Results regarding the impact of different sources of knowledge highlight the roles of employee training, the human capital of entrepreneurs and workers and the productivity of university departments providing relevant knowledge. Other elements of external knowledge, such as proximity to the University of Salerno or being in the city of Salerno, are significant facilitators of survival only if mediated through high levels of the human capital of entrepreneurs and workers.KEYWORDS: Internal and external knowledge; absorptive capacitySMEsuniversity collaborationhuman capitalJEL CLASSIFICATIONS: L20O3D22I2 Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 There is a common presumption that firm survival is ‘good’. However the literature on firm exit emphasises the distinction between voluntary entrepreneurial closure and failure (Bates Citation2005; Coad Citation2014; DeTienne, McKelvie, and Chandler Citation2015; Headd Citation2003; Khelil Citation2016; Wennberg, Delmar, and McKelvie Citation2016).2 Hyytinen, Pajarinen, and Rouvinen (Citation2015) and Fernandes and Paunov (Citation2015) also apply probit models to the study of innovation and survival. Their analyses, however, do not allow for the joint determination of innovation and survival and hence do not yield estimates of the direct and indirect effects of innovation on survival.3 It is worth noting that in 2016, 93% of EU manufacturing firms had fewer than ten employees (Muller et al. Citation2017).4 Note however that Trushin and Ugur (Citation2021) find that firms in hazardous environments can mitigate the detrimental effects of these environments on survival through R&D expenditure.5 Interestingly, Holl, Peters, and Rammer (Citation2023) report a similar spatial range for German manufacturing firms in a related context (the impact of patents on innovation persistence).6 This finding is consistent with the theoretical model of Desmet and Parente (Citation2012), where a large firm size is essential for the introduction of effective cost-saving technologies.7 The survey was conducted by the Centre for Economic and Labour Policy Evaluation at the University of Salerno and funded by the Sichelgaita Foundation in Salerno.8 LMAs, akin to British travel to work areas, are","PeriodicalId":51485,"journal":{"name":"Economics of Innovation and New Technology","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135093685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Can the development of digital finance stimulate enterprise innovation? Empirical evidence from China","authors":"Kai Zhao, Haonan Shan, Zeping Chen, Wanshu Wu","doi":"10.1080/10438599.2023.2266376","DOIUrl":"https://doi.org/10.1080/10438599.2023.2266376","url":null,"abstract":"ABSTRACTBased on the data of China A-share listed enterprises, this paper examines the actual effect and mechanism of the development of digital finance on different innovation behaviors of enterprises, by using the panel data model and regression-based mediation analysis. It is found that the development of digital finance not only promotes the R&D investment of enterprises but also improves the quantity and quality of enterprise innovation output. The incentive effect of digital finance on enterprise R&D investment is stronger than that on innovation output, while the incentive effect of digital finance on enterprise breakthrough innovation is stronger than that of incremental innovation. Both the ‘broadening’ and the ‘deepening’ of digital finance have a significant positive effect on enterprise innovation, while the ‘digitalization degree’ of digital finance has no significant effect on enterprise innovation, and even may hinder the improvement of innovation quality. The incentive effect of digital finance on the innovation output of state-owned enterprises is reflected in ‘quantity’, while the incentive effect on innovation of non-state-owned enterprises is reflected in ‘quality’. Digital finance can stimulate enterprise innovation by easing the financing constraints of enterprises, optimizing the government subsidy system, and improving the business environment.KEYWORDS: Digital financeenterprise innovationinnovation qualitybusiness environmentgovernment subsidies Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by Shandong Provincial Natural Science Foundation [Grant Number ZR2023MG075]; National Planning Office of Philosophy and Social Sciences of China [Grant Number 20FJYB017].","PeriodicalId":51485,"journal":{"name":"Economics of Innovation and New Technology","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134975509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}