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Research, Innovation and Productivity: An Econometric Analysis at the Firm Level
... Building upon the seminal work of Cohen and Levinthal (1990), this paper focuses on the firm's capacity to acquire and utilize information from diverse sources as a critical determinant of innovation. Recognizing the importance of addressing endogeneity concerns, our approach draws inspiration from the work by Crepon, Duguet, and Mairesse (1998). ...
... Numerous studies have focused on investigating innovation performance and its determinants. Crepon, Duguet, and Mairesse (1998) developed a model that established a framework for exploring the causation of innovation output and productivity growth by linking innovation survey variables. Building on this model, subsequent research has further examined the relationship between innovation survey variables and innovation output. ...
... Several studies have addressed the endogeneity of R&D investment on innovation outputs using various econometric approaches. Crepon, Duguet, and Mairesse (1998) conducted an analysis at the firm level, focusing on French manufacturing firms. Their study employed a system of simultaneous equations to examine the interplay between productivity, innovation, and R&D. ...
sing the Chilean Innovation Survey for 2019-2020, this work studies the effects of different knowledge sources on a range of innovation outputs. Findings reveal distinct impacts of sourcing information from competitors, customers, and government agencies on product, process, marketing, organizational, and social innovation outputs. Information from customers has a positive effect on overall innovation. Social innovation is positively influenced by information sourced from government agencies. These findings contribute to the understanding of how different knowledge sources shape innovation outputs on developing countries. They provide valuable insights for firms, policymakers, and researchers seeking to enhance innovation capabilities and inform evidence-based policies.
... We measure innovation using patent applications. Following Crepon et al. (1998), we assume the patent equation as a heterogenous count data process with an expectation # Ã it conditional on firms' performance captured through firms' productivity and other explanatory variables. ...
... Following the conceptual framework in the preceding section and prior literature (Crepon et al., 1998;Zachariadis, 2003;Cainelli et al., 2006), the empirical specification, which measures the role of productivity on the innovative performance of the firms, is given as follows: ...
... 11. Cainelli (2006) and Fang et al. (2020) instrumented firms' performance using using sales data for their study of the Italy and Chinese firms. Crepon et al., 1998Crepon et al., 1986Crepon et al., -1990 French, The ratio of the compensation paid to employees to the number of employees of firm i during period t. ...
Purpose
This paper aims to explore whether firms’ performance determines innovation using a sample of Indian manufacturing firms. The impact of innovation on firms’ performance across specific countries has been discussed in the literature. However, the effect of firms’ performance on innovation output, especially for a developing country like India, remains an open question. Against this backdrop, this paper investigates whether firms’ performance determines innovation in Indian manufacturing firms.
Design/methodology/approach
The authors use patent filing information to instrument innovation and total factor productivity to instrument firms’ performance. The patent data are collected from the Patent Search and Analysis Software database and firm-level data from the Centre for Monitoring Indian Economy’s Prowess database. The study uses a sample of 309 Indian manufacturing firms from 2005 to 2021. Given the count nature of the data set used in this study coupled with over-dispersion issues, the authors have used the negative binomial regression to estimate the empirical specification of the models. There could be a possible problem of endogeneity due to the contemporary nature of innovation and firms’ performance. Therefore, to address the possible issues of endogeneity in the model, the authors have used the Generalized Method of Moments (GMM) estimators for more robustness checks of the empirical results.
Findings
The empirical results exhibit a positive and significant impact of firms’ performance on the innovation output, validating that firms’ performance determines innovation in Indian manufacturing firms. The posterior estimation results using GMM estimation also corroborate that firms’ productivity is a determining factor for the innovation output of Indian manufacturing firms. Furthermore, empirical results exhibit that the ex ante innovativeness of the firms substantially affects the current innovation. This validates that the firms’ prior experience, learning by doing and past innovative efforts are more likely to precipitate more innovation in the current period.
Originality/value
This paper’s main contribution is empirically estimating whether firms’ performance determines innovation, which is hardly discussed in the existing innovation literature, specifically using Indian manufacturing industries. Further, it adds to the existing literature in two other prominent ways. First, this paper investigates whether firms require ex ante expertise to innovate or if a firm starting from scratch can innovate significantly without any hindrances. Second, it enriches the literature by instrumenting innovation in output terms with the patent application against input measures of innovation, such as research and development expenditures, acquisition of machinery and equipment, while discussing the relationship between firms’ performance and innovation, specifically in the context of a developing economy like India.
... This study contributes to the existing literature by using more recent and comprehensive data on BIGS programs which presents a notable advantage from a methodological standpoint compared with other studies relying on survey data. Additionally, to account for the interdependency between employment, revenue and profit as financial measures of firm performance, the study adopted the CDM (Crépon et al., 1998) model for analyzing the firm innovation process, which has been extensively employed in previous research (e.g., Bérubé & Mohnen, 2009;Crépon et al., 1998;Dagenais et al., 2004;Fedyunina & Radosevic, 2022). ...
... This study contributes to the existing literature by using more recent and comprehensive data on BIGS programs which presents a notable advantage from a methodological standpoint compared with other studies relying on survey data. Additionally, to account for the interdependency between employment, revenue and profit as financial measures of firm performance, the study adopted the CDM (Crépon et al., 1998) model for analyzing the firm innovation process, which has been extensively employed in previous research (e.g., Bérubé & Mohnen, 2009;Crépon et al., 1998;Dagenais et al., 2004;Fedyunina & Radosevic, 2022). ...
... The studies in the first stream (e.g., David et al., 2000;De Fuentes et al., 2021) investigate the impact of innovation programs on firm-level innovation and growth using the treatment effect approach in their empirical analysis, comparing the performance of funding recipients with the performance of firms that did not receive funding. By contrast, those in the second stream (e.g., Crépon et al., 1998;Hall & Van Reenen, 2000;Le, 2020;Lööf et al., 2017;Mairesse et al., 2005) use the CDM model proposed by Crépon et al. (1998), which explores determinants of firms' innovation processes without considering the government support received by these firms. ...
This study examined the impact of federal business innovation and growth support (BIGS) programs on firm financial performance measured using revenue, profit and employment metrics. Using Statistics Canada’s Business Linkable File Environment data, the study observed the effects of BIGS on exporting versus non-exporting firms and Canadian- versus U.S.-owned firms from 2015 to 2020. Unlike previous studies that relied mainly on survey data, one significant aspect of this research was the use of a new dataset, enabling panel data structures and models to be employed. To assess the impact of BIGS and research and development spending on three interrelated measures of firm financial performance, the CDM (Crépon et al., 1998) framework was adopted.
... In an environment driven by the acceleration of technological change, economic demands imposed by markets, and social demands formed by value systems, innovation is seen as an element of maintaining the competitiveness of firms (Aghion et al., 2005;Chang et al., 2024;Jordão & Novas, 2024;Rahimzadeh & Jafarpour Ghalehteimouri, 2024;Tchamyou, 2017), productivity growth (Blundell et al., 1999;Hall et al., 2008;Wolf, 2006), wealth creation (Mohnen, 2019), and economic growth (Ahmad & Zheng, 2023;Boubakary & Moskolaï, 2021;Krugman, 1990;Qin et al., 2024). This innovation on its technological and nontechnological aspects would aim at a new or significantly improved production, a new method of organization and marketing, allowing firms to adapt quickly to the pace of change in the economic environment Crépon et al., 1998;Guellec & Ralle, 1993;Mairesse et al., 2005;Parisi et al., 2006;Tayebeh et al., 2023). Classifying innovations as technological and nontechnological, many studies question the relationship between the latter or nontechnological dimension (Battisti & Stoneman, 2010;Flikkema et al., 2007;González-Blanco et al., 2019;Mothe & Nguyen-Thi, 2012;Tether & Tajar, 2008). ...
... The managerial capacity is a built variable. It creates a fertile environment for the development of different types of innovations that are vital for a company to achieve better performance (Chudnovsky et al., 2006;Miguel-Benavente, 2006;Crépon et al., 1998). Although we attempt to construct a measure of managerial capability by including variables related to personnel management, financial management, management of relationships with other stakeholders in the firm, and ethics management, we recognize that other unobserved factors may be present. ...
The motivation for this study builds on the rapid changes in the business environment that have led companies to include innovation as one of the strategies for productivity growth, competitiveness, and sustainability. The objective of this work is to analyze the interaction and complementarity between technological innovation practices and non-technological innovation used by companies. The methodology used by the paper is a Bivariate Probit model applied to micro-data from 1897 firms in Cameroon, Côte d’Ivoire, and Senegal. The effect of the adoption of a technological innovation on a non-technological innovation practice is estimated by conditional probabilities using two-dimensional normal distributions. The results show strong significant correlations between the various innovation practices within the firm with important complementarity effects between them. This complementarity is the proof that the adoption of a technological innovation practice leads to the initiation of another non-technological innovative activity and vice versa for a better performance of the firm’s activities. These complementarity effects between the different types of innovations are heterogeneous according to the sector of activity, which suggests that innovation policies should be specific to each sector. The originality of the study is premised on the use of both technological and non-technological dimensions of innovation in the assessment of how innovations affect manufacturing and service firms in Africa.
... A novelty with respect to its predecessor Horizon 2020, is the creation of the European Innovation Council, which specifically supports breakthrough and disruptive innovations with high growth potential that may be too risky for private investors. 1 There are numerous historical case studies and empirical studies that find evidence of different positive effects of investing in R&D (see for example Aghion et al., 2017;Añón, 2007;Crépon et al., 1998;Gupta, 2020;Griliches, 1998;Roper & Turner, 2020). However, all these positive effects come up against the problem that the idiosyncrasy of the R&D investments limits the access to the necessary funds to carry out the innovation project, i.e. it can give rise to financial constraints (Czarnitzki & Binz, 2008;Hall, 2002;Mohnen et al., 2008). ...
... However, registering patents does not seem to have any significant correlation with the probability of starting to perform R&D. Our estimates also suggest that Crépon et al. (1998), find that firm productivity is positively correlated with higher innovation. ...
This study performs a comprehensive analysis of the importance of the financial constraints on: general firms’ decisions to perform R&D, R&D intensity, firms’ decision to start performing R&D, and R&D persistence. Different dimensions such as profitability, liquidity, total assets, solvency, repaying ability and the cost of the external financing are summarized in a synthetic index to build our financial constraints variable. We estimate our models using firm-level data of Spanish manufacturing drawn from the Survey of Business Strategies, for the period 1992-2016. We find that financial health is associated with the likelihood of performing R&D. Besides, we differentiate how financial health may influence both the decision to start R&D activities and the decision to continue them. Our results suggest that financial health is relevant in SMEs' decisions to start R&D activities and persist in them. In contrast, for large firms, financial constraints seem to be relevant only for the decision to continue engaged in R&D activities. These findings highlight the importance of analyzing separately the role of financial constraints in different stages of R&D decisions.
... Los aportes teóricos iniciales propuestos por Schumpeter (1942); han sido aplicados a nivel empírico por Griliches (1979) o Crépon et al. (1998) a través de los modelos CDM; y por otros autores como Máñez et al. (2011) o Demmel et al. (2017. Esta relación también ha sido explorada a nivel macroeconómico basándose en el modelo del cambio técnico residual a la Solow (Bilbao-Osorio y Rodríguez-Pose, 2004;Gordon, 2012;Verspagen, 2006, entre otros). ...
... Los estudios empíricos en estos tópicos para Colombia son escasos (Sanchis-Llopis et al., 2024). Sin embargo, se han realizado investigaciones centradas en la hipótesis API, siguiendo a Griliches (1979), y más específicamente a Crépon et al. (1998). En este sentido, Arbeláez y Parra (2011) muestran que la producción de bienes y servicios nuevos para la empresa y para el mercado interno, mejora las ventas por trabajador, y la innovación en producto impulsa tanto las ventas como la PTF. ...
Este documento explora la hipótesis de autoselección por innovaciones en la industria manufacturera caucana. Esto es, la incidencia de la productividad total de los factores (PTF) en la introducción de innovaciones y no la causalidad contraria, es decir, la hipótesis de aprendizaje por innovaciones. Inicialmente, se estima la PTF a través de un proceso bietápico, incluyendo un proceso markoviano endógeno, para posteriormente implementar un modelo probit dinámico, con datos panel que introduce el patrón de la experiencia exportadora, al igual que trata el problema de las condiciones iniciales, con el fin de evitar problemas de endogeneidad. La información se obtiene del Departamento Administrativo Nacional de Estadística (DANE), específicamente de la encuesta anual manufacturera (EAM); de la encuesta de innovación y desarrollo tecnológico (EDIT) y de la encuesta anual TIC (EAM-TIC), en el periodo 2023-2018; con lo cual se obtiene un panel que consta de 435 observaciones repartidas en 92 empresas. Para comparar los resultados se estima también el modelo para la región, conformada por Bogotá, Antioquia y Valle (BAV); al igual que para Colombia. Los principales resultados señalan una evidencia tenue y discrecional del proceso de autoselección por innovaciones en el departamento del Cauca, al igual que en la región BAV y en Colombia, ya que sus impactos son bajos y dependen del tipo de innovación analizado.
... Organizations have devoted a substantial amount of¯nancial e®ort to research with the aim of ameliorating their technologies and positions in the market. Thus, R&D has become a crucial component of companies' growth strategy, as it permits them to innovate, reinforce their competitive advantage, and increase their earnings [Cr epon et al. (1998); Morris (2018)]. Being *Corresponding author. ...
... Employing the Chilean innovation survey panel, Guzman et al. [2024] highlighted the importance of R&D spending in innovation. Extending the Crepon-Duguet-Mairesse model [Cr epon et al. (1998)], they also fund that skilled employees positively a®ect organizational innovation strategies, and that the choice of the innovation design is relevant for¯rm's productivity. Bustamante Izquierdo [2024], investigated on the impact of innovation on employment. ...
This study uses an extensive sample of company data referring to seven Latin American countries to analyze the potential influence of simultaneity and heterogeneity in determining decisions to commit to R&D and innovation outputs. First, the analysis focuses on the decisions about spending on in-house and external research. Second, the outcomes of three different innovations: process, product, and organizational. Choices were considered simultaneously by employing a multivariate probit estimation model. In so doing, the enquiry considered the possible systematic interdependencies among the decisions. The results indicate that the two R&D decisions are interdependent. However, a different picture emerged in relation to innovation outputs, in which the correlations coefficients were small with unexpected signs. This may indicate a structural weakness of the technological production system in Latin America, wherein the synergies, complementarities, and complex relationships usually involved in the process of innovation are not fully developed.
... However, other scholars using principal component analyses have revealed that digital technology has minimal impacts on innovation performance [5]. Regarding organizational conditions, researchers have primarily used traditional linear regression analysis methods to study the single net effects of various factors, such as human capital levels, the top management team's heterogeneity, entrepreneurship, internal control levels, and enterprises' dynamic capabilities on the generation and transformation of technological innovation outcomes [8][9][10][11][12][13][14][15]. Ge noted that dynamic capabilities positively affect product, process, and collaborative innovation performance [8]. ...
... Zhang et al. observed that the top management team's heterogeneity positively moderated digital transformations' impacts on enterprises' innovation [13]. Crépon et al. emphasized the significance of innovation management, particularly in developing a high-quality talent team, which is crucial for enterprises to promote technological innovation and maintain competitive advantage, and offers a useful reference for strategic emerging enterprises to enhance their innovation performance [14]. When examining external environmental conditions on enterprises' innovation, existing research has focused on the linear relationships between factors such as government subsidies, regional innovation policies, tax incentives, the business environment, market competition, and innovation performance [16][17][18][19][20][21][22]. ...
As vehicles for implementing innovation-driven strategies, the strategic emerging industries are crucial for enhancing national competitiveness and sustainable development. Improving innovation performance in these industries has been a central focus of academic research. Notably, existing studies have primarily analyzed the net effects from a single perspective. This study examined 261 strategic emerging Chinese enterprises listed on the A-share market. Utilizing the Technology–Organization–Environment framework and fuzzy set qualitative comparative analysis, this study explores the impact paths and mechanisms of the coupling configurations of technology, organization, and environment to enhance enterprises’ innovation performance from a configuration perspective. We discovered that, first, no single antecedent condition is necessary to achieve high enterprise innovation performance. However, increasing the level of digital transformation and intensity of innovation investments universally results in high innovation performance. Second, the technological, organizational, and environmental conditions exhibit “multiple concurrency”, forming diverse configurations that drive enterprise innovation performance; hence, the driving paths of enterprise innovation performance are varied. Third, four schemes exist for achieving high innovation performance in strategic emerging enterprises: environment-driven under technological dominance, technology–organization driven type, organization-driven under technological–environmental dominance, and technology–organization–environment co-driven type. Exploring the synergistic paths driving innovation performance from a configuration perspective enhances our understanding of the complex interactions among multiple factors in improving such performance. This provides significant theoretical and practical implications for enterprises aiming to improve their innovation performance.
... Given that returns from low-risk projects are taxed at a lower rate compared to those from riskier endeavors, firms encounter a productivity threshold when deciding to engage in high-uncertainty activities such as innovation and exporting. Although firms invest in R&D to boost future productivity (Arora et al., 2017;Crépon et al., 1998), within our framework, they must already demonstrate superior performance to manage the initial sunk costs of R&D investment. To ensure the robustness of our findings, the econometric analysis meticulously controls for feedback effects in the relationship between productivity and R&D investment, ensuring that our results reflect genuine causal relationships rather than mere correlations. ...
... These gains, in turn, enhance future profitability and consequently increase corporate tax liabilities. Romero-Jordán et al. (2020) suggest that this relationship highlights how innovation and exporting not only bolster firm performance-a finding well-supported in the literature (Bloom et al., 2016;Crépon et al., 1998;De Loecker, 2007)-but also elevate productivity, leading to higher tax obligations. To account for possible future feedback effects, we instrument EATR ict−1 , TFP ict−1 and EATR ict−1 × TFP ict−1 with their own lags in period t − 2. Additional set of instruments are also considered in our sensitivity analysis. ...
The paper presents a unified framework for analyzing the impact of corporate taxation on R&D and exporting, considering firm productivity heterogeneity and sunk costs. We empirically examine three hypotheses using data from 7819 European firms spanning 2001-2014. We propose that: (a) an increase in corporate tax reduces the likelihood of innovation,(b) an increase in corporate tax reduces the likelihood of exporting, and (c) firms that innovate are more likely to enter foreign markets. On average, a high Effective Average Tax Rate (EATR) lowers the probability of investing in R&D and exporting by 2.3% and 1.41%, respectively. For firms with low Total Factor Productivity (TFP), the adverse effect of taxation on R&D investment ranges from 3.71% in our baseline analysis to 12.9% in our sensitivity analysis. Interestingly, while EATR positively influences the export decisions of high-TFP firms, a higher EATR can reduce the export probability by up to 25.5% for firms at the lower end of the TFP distribution. Our findings demonstrate a causal relationship between firm heterogeneity and their capacity to mitigate the distortions caused by higher taxes. From a policy perspective, our results suggest that fostering innovation is essential for firms aiming to expand into international markets.
... In particular, this paper focuses on the extent to which initial levels of firm productivity can be seen as a predictor of SME-university collaboration and any subsequent changes in productivity post-collaboration. In terms of the former, there exists substantial evidence of a positive relationship between productivity and innovation within SMEs (Crepon, Duguet and Mairesse, 1998;Griffith et al., 2006;Hall, Lotti and Mairesse, 2009;Hall, 2011;Saunila, 2014;Baumann and Kritikos, 2016); therefore, SMEs that are more productive are, typically, more innovative. As pursuing an innovation is the key reason for university collaborations (Mindruta, 2013;Mindruta, Moeen and Agarwal, 2016), this outcome suggests that the SMEs engaging in collaborative links with universities are likely to be more productive overall. ...
... The evidence of a positive relationship between productivity and innovation within SMEs has established that more productive firms are more innovative (Crepon, Duguet and Mairesse, 1998;Griffith et al., 2006;Hall, Lotti and Mairesse, 2009;Hall, 2011;Saunila, 2014;Baumann and Kritikos, 2016). Furthermore, there is evidence that higher levels of open innovation also have a positive effect on firm productivity (Greco et al., 2021). ...
Purpose
As little is known about the productivity levels of small and medium-sized enterprises (SMEs) engaging with universities and the relative changes in productivity of SMEs subsequent to these collaborations, the paper examines the following questions: (1) Does the relative productivity of SMEs engaging in university collaboration differ from those that do not? (2) Are subsequent changes in firm productivity following university collaboration related to their initial levels of productivity?
Design/methodology/approach
The paper utilises data on 254 SMEs from the Longitudinal Small Business Survey and uses two statistical techniques: First, bivariate tests of difference were used to inspect the relationships between productivity levels and whether the firm collaborated with a university to introduce its innovation. Second, ordinary least squares regressions were used to test whether the future productivity of SMEs that collaborated with universities was related to their initial productivity levels.
Findings
The analysis reveals that SME–university collaboration is unrelated to starting productivity. Furthermore, the analysis suggests a nonlinear relationship exists between the starting productivity of SMEs and their subsequent productivity following a university collaboration. Therefore, higher levels of subsequent productivity are observed among those SMEs where starting productivity was either relatively low or high, suggesting that collaborations have a transformative effect on SMEs with relatively lower initial levels of productivity and a maintenance effect for SMEs with relatively higher levels of initial productivity.
Practical implications
Given the fact that the extant literature also suggests that, overall, university collaboration is beneficial, policymakers should strive to encourage greater levels of collaboration involving SMEs. In light of the evidence that SME–university collaborations can transform less productive firms, it appears unjustified for practitioners and policymakers to only consider stronger-performing firms to be included in such programmes.
Originality/value
The study contributes new theoretical and practical knowledge to the understanding of the role of firm productivity in predicting the proclivity of firms to collaborate with universities. Furthermore, as few studies have examined the impact of these collaborations on the subsequent productivity of firms that collaborate with universities, this paper fills an existing gap in the literature.
... This study presented a structural innovation model considering R&D expenditures and productivity measures (Hall et al., 2009: 13). Another remarkable study in this cluster is the study of Cohen & Levinthal (1990). The unit of analysis of this study is the final level. ...
... 57 citations,Lööf (2006) 47 citations,Crespi (2012) 45 citations, Parisi (2006) 43 citations, Hall (2009) 43 citations, Levinsohn (2003 43 citations, Mohnen (2013) ) 42 citations,Romer (1990) 40 citations, Olley (1996 37 citations,Cohen (1990) 36 citations, Chudnovsky (2006) 33 citations,Cohen (1989) 33 citations, Solov (1957) 33 citations, Porter (1995 32 citations, Aghion (1992) 31 citations, Benavente (2006) 28 citations, Aghion ( 2005) 28 citations, Heckman (1979) 27 citations were received. ...
Purpose: This study aims to reveal research trends by revealing the evaluation in this field by making a holistic analysis of academic studies that have examined the concepts of innovation and productivity in the last five decades. This analysis aims to reveal the general structure of academic studies that deal with the concepts of innovation and productivity. Methodology: Articles searched in the ‘‘Social Science Citation Index (SSCI)’’, ‘‘Science Citation Index Expanded (SCI-EXPANDED)’’ and ‘‘Emerging Sources Citation Index (ESCI)’’ in the ‘‘Web of Science (WoS)’’ database, researching innovation and productivity together between 1980-2023. It was analysed and mapped using the VOSviewer 1.6.19 software and manual methods. Co-occurrence Keyword Analysis, Document Co-citation Analysis and manual analysis methods were used in the mapping. Findings: This study reveals how research in innovation and productivity has developed over the last five decades and what trends it has. It has been determined that the most published areas are Economy, Management and Business. The most frequently used keywords were found to be "innovation", "productivity", "research-and-development", "growth", "performance" and "impact". The most published topics on a cluster basis are "impact", "innovation and productivity", "growth", "research and development" and "performance", respectively. In the document co-citation analysis, it was determined that the publication in which all publications were linked included the study titled "Research, Innovation and Productivity: an econometric analysis at the firm level", published by Crépon et al. (1998). This information can be a valuable resource for future research and policy-making and can be used to drive innovation and productivity progress. Originality: While the study is the first and only content analysis to reveal the combined trends in this field by examining the "innovation and productivity" studies together, it is thought that the results obtained can guide researchers and professionals.
... The methodology used, inspired by Crepon, Duguet, and Mairesse (1998) is formalized in a multistage model in which, on the one hand, the TFP is calculated following the Levinsohn and Petrin's (2003) estimator, and in parallel, the innovation variable, contained in the database used, is endogenized in order to incorporate a continuous variable that allows weighting the relative importance of the innovation carried out, and finally the effects of this innovation on the TFP are analyzed. The results led to three main conclusions. ...
... Other studies follow Crepon, Duguet, and Mairesse (1998) to measure knowledge capital and include it in the production function (Aiello et al., 2020;Masso and Vahter, 2008;Ugur and Vivarelli, 2021). In general, the ability to innovate helps companies to improve its products and services, and thus meet market demands and allocate resources more efficiently. ...
Empirical research has confirmed a mostly positive relationship between innovation and performance, but more work is needed to establish whether this relationship is homogeneous or whether it depends on other variables, such as ownership model (family/non-family) and who manages the company (owner/non-owner). This paper studies differences in the impact of innovation on productivity between family firms, owner-managed or professionalized, and non-family firms, also subdivided, for the first time in the academic literature, between owner-managed and non-owner-managed firms. A multistage model is used, controlling for endogeneity and selection bias issues. The results yielded by a large panel dataset of Spanish manufacturing firms suggest differences in the ability to benefit from innovation. These results confirm that, in non-professionalized firms, family ownership reduces the positive effect of innovation on productivity, while in professionalized firms, there are no significant differences between the family and non-family ownership model.
... For example, Crépon et al. (1998) used a longitudinal data set of French firms from 1984 to 1990 and employed the control function approach to estimate the causal effect of R&D on firm-level productivity. Griffith et al. (2006) analysed the relationship between innovation and productivity in four European countries using firm-level data from the innovation surveys for the period of 1996-2000. ...
... It is likely that our estimations with excluded instrumental variables are subject to the problem of weak instruments, which is a limitation of this study. To address this concern, we employ a structural model of R&D, innovation and firm performance, following the approach of Crépon et al. (1998). In this model, R&D is a linear function of the number of full-time permanent employees, competition and FC, while product and process innovations are linear functions of R&D, the number of full-time permanent employees, competition and FC. ...
Alongside rapid economic growth, the Chinese economy has witnessed a notable increase in research and development (R&D) expenditure, escalating from 0.56 per cent of GDP in 1996 to 2.43 per cent in 2021. Recognising the significance of innovation in economic growth, this article utilises unique firm-level data from China for the year 2012 to investigate the influence of R&D, product innovation and process innovation on firm productivity. The findings suggest that R&D positively affects the performance of Chinese firms, as measured by either firm sales or sales per permanent full-time employee. Moreover, product innovation may have a detrimental impact on firm performance, whereas the impact of process innovation lacks robustness.
JEL: D22, N65, O32
... 3.3. Proxying for true productivity by the innovativeness of the product is consistent with Crepon et al. (1998) and Hall (2011: 14) who concluded that: "innovative sales are associated with revenue productivity, and that the association is stronger for higher technology sectors". 11 We will compare the size of the estimated elasticities between Hypotheses 1 and 2 to infer what demand elasticity seems most plausible empirically. ...
Plain English Summary
New study uncovers trade-offs in venture creation. Want to be innovative? It could increase time to breakeven. Need revenue fast? Innovation takes a hit. However, founder resources tip the scales for startups. #entrepreneurship #innovation #startupsuccess. This study examines how new businesses deal with uncertainty, focusing on the tradeoff between how quickly they become profitable (speed-to-breakeven) and how much revenue they generate when they do. We analyze data from 331 information and communication technology (ICT) ventures to understand these tradeoffs better, considering factors like financial resources and labor inputs. We find that more innovative ventures, which tend to be more uncertain, often take longer to reach profitability and may earn less when they do. Moreover, regardless of their level of innovation, all new ventures face a tradeoff between speed-to-breakeven and revenue. The study highlights that unique resources, such as founder equity and founder labor, help businesses overcome challenges in the venture creation process. It helps to understand why some ventures are more efficient than others in the early stage of creating new businesses.
... The knowledge generation function aims to assess the determinants of knowledge as an output (Griliches, 1979), while the technology production function analyses the role of knowledge as an additional factor input in the production of other goods. The two equations, together, enable us to analyse the dual role of technological knowledge as an input and output (Antonelli & Colombelli, 2023;Crépon et al., 1998). ...
The paper discusses the knowledge cost approach as a comprehensive framework to account for endogenous technological change and test it to explain productivity differences across European regions. The assessment of the limited transferability of knowledge and the appreciation of the intentional efforts required to use knowledge spillovers question the assumptions of automatic, spontaneous, homogenous, symmetric and universal effects of knowledge spillovers conjectured by the New Growth Theory. The knowledge cost approach, instead, stresses the localized, idiosyncratic and contextual effects of knowledge spillovers that are strong -only- in high-quality innovation systems. If the access and absorption of knowledge in high-quality innovation systems is cheaper, the cost of knowledge falls below equilibrium levels and its use in the technology production function contributes to higher total factor productivity growth rates. Using a sample of 192 European regions for which we estimate productivity growth for the period from 2005 to 2020, we confirm that regions with lower knowledge costs exhibit higher Total Factor Productivity growth rates.
... The framework is based on the CDM (Crépon et al., 1998) system of equations, which has become a funding stone of the economics of innovation and knowledge. The CDM approach unveils the sequential structure of the determinants and effects of the innovation process. ...
This paper presents and frames the results of the recent book The creative response: knowledge and innovation by Antonelli and Colombelli (2023). The book combines the advances of the economics of knowledge and innovation, implementing the Schumpeterian notion of creative response to understand the determinants and the effects of the rate and direction of technological and organizational change and its variance across time and space, firms and industries. The notion of creative response, introduced by Joseph Schumpeter in the essay “The creative response in economic history” published in 1947 by The Journal of Economic History , can be regarded as the synthesis of his life-long work on innovation. It provides an inclusive framework that enables to highlight the crucial role of knowledge in assessing the rate and direction of technological change and to clarify that no innovation is possible without the generation of new knowledge, while the generation of new knowledge augments the chances of innovation but does not yield automatically the introduction of innovation. Firms thus are faced with a number of strategic decisions to make the creative response possible. The position paper elaborates the analytical core of the notion of creative response and articulates its implications for economic policy and strategic management.
... In order to analyse the relationship between the innovation activity and the probability of becoming a HGF, we apply a bivariate probit procedure. Our approach is based on the model labelled as CDM model (Crépon, et al., 1998) where a firm's innovation effort has an impact on the capacity to innovate. And finally the innovation effort will have an impact on the firm performance measured in productivity. ...
This paper analyses the effect of innovation on a high-growth firm (HGF). The micro-data belongs to the Community Innovation Survey 2008 provided by Eurostat covering the period 2006-2008 for 15 European countries. We classify the EU countries in two groups according to the share of business R&D on GDP: leader countries (Germany, Slovenia, Czech Republic, Norway, Portugal, Spain and Italy) and laggard countries (Estonia, Hungary, Slovakia, Lithuania, Romania, Bulgaria, Latvia and Cyprus). Firms in leader countries are more prone to invest in R&D but the presence of HGFs is more moderated than firms in laggard countries. Our main results show that the drivers to innovate and become a HGF differ across European countries. In leader countries, the HGF firms presence is related to R+D inversions and innovation, whereas in laggard countries depend directly on the size of the firm, as well as the turbulence rate in the economy as a whole. All in all, our results show light on the different entrepreneurial ecosystems of the European Union member countries.
... Labor productivity is positively impacted by process innovation as well, although this impact is greater when process innovation is combined with product innovation. Crepon et al. (1998) also concluded the same results about R&D with the demand pull and technology push indicators. ...
The paper examines the impact of different types of innovations—such as process, product, and R&D—on labor productivity and employment across several African nations. Utilizing data from the World Bank Enterprise Survey, the study constructs pseudo-panel data based on legal status, firm size, and industry type and employs the propensity score matching and the dose–response model to explore the relationship between innovation and labor market outcomes. The descriptive analysis indicates that 2,673 firms are engaged in at least one of the innovation activities, and 250 firms do not have any innovation activities. The propensity score matching finds that the overall combined effect of all types of innovation is statistically significant and has a positive effect on the employment of non-production workers and skilled workers, but it harms their productivity. Not only this, but it has also a negative impact on the productivity of permanent, and unskilled workers. The only positive impact goes to the productivity of production workers. Except for skilled labor, no segments of the labor force have been impacted by product innovation, but it has statistically significant influences on the productivity of all types of workers, still, production workers received a positive influence. It also finds that process innovation positively influences the productivity of production workers and the employment of skilled, non-production, and production workers. On the other hand, permanent, non-production, and skilled employees respond negatively to process innovation. Regarding R&D innovation, except for production workers, all are negatively impacted and statistically significant. On employment creation, R&D has also a positive and statistically significant impact on employment except for permanent employees. On top of this, the findings of the dose–response function are also in line with the propensity score matching method except for the combined effect of innovation on production workers. In other words, the intensity has a declining dose effect while innovation has a growing effect by the propensity score method for production workers. Additionally, the dose–response function shows a strong positive correlation between the intensity of innovation and skilled workers with various trends as well as permanent employees. The effect is initially diminishing for unskilled workers and non-production workers, but it gradually increases over time. In general, the finding challenges the assumption that innovation uniformly improves productivity, instead revealing a more complex dynamic where job creation comes at the cost of lower productivity in certain labor segments.
... The researchers have been interested in several dimensions and relationships. Firstly, the bulk of the literature investigated the impact of these type of services on growth rate of employment, valued added, and productivity (Kox & Rubalcaba, 2007a, 2007b, while other studies were supporting the relationship between KIBS innovation and economic growth, especially in the manufacturing sector (Cainelli et al., 2006;Crepon et al., 1998;Evangelista, 1999;Griliches, 1995Griliches, , 1998Klomp & van Leeuwen, 1999;Krempet et al., 2004;Loof & Heshmati, 2001). Another line of research has considered the different innovation behaviours between KIBS and manufacturing, considering several innovation variables related to R&D (Teixeira & Santos, 2016). ...
This paper evaluates how features related to localization economies, innovation, and information and communications technology(ICT), influence the location of knowledge-intensive business services (KIBS) and the emergence of new specialization in KIBS acrossNUTS3 regions in Italy over the period 2007–2020. We adopt a Spatial Durbin Model (SDM), which shows a strong presence of interregional positive spatial spillover effects from neighbors’ NUTS3 regions. Common drivers, such as location in capital cities,input–output linkages between KIBS and manufacturing, innovation and ICT are confirmed to be key drivers of KIBS location.However, turning to the analysis of factors triggering
new specialization across the KIBS sectors, a prominent role for urbanization economies and ICT emerges. Our findings seem to suggest that the access to new KIBS specialization is concentrated in territories with higher urbanization and ICT, emphasizing the relevance of urban agglomeration economies more than specialization economies for achieving better KIBS performances, and hinting at the relevance of ICT development to support the new knowledge economy.The policy implications point to the relevance of appropriate tools with which to face the strong intensity of the North–South divide and the capital-periphery gaps in KIBS location and to achieve better performances, particularly in the technology-based KIBS (T-KIBS).
... The CDM was originally created byCrepon et al. (1998). . ...
Due to constrained resources, small and medium-sized enterprises (SMEs) often have a low capacity to innovate. While research has focused chiefly on empowering SMEs' innovation through tangible factors, this paper explores the contribution of intangible factors towards innovation under frugality conditions. We address this gap using data collected from Indonesian SME automobile component manufacturers. We employ the expanded CDM (Crepon Duguet Mairesse) model that divides innovation into three stages: effort, output, and productivity. The findings showed that in addition to common tangible factors, intangible factors contribute to all stages of innovation, though tangible factors appear to exert greater influence. The direct impact of product innovation on firm performance is moderated by tangible factors, whereas the indirect impact is moderated by intangible factors. By examining how intangible and tangible factors simultaneously empower SMEs’ innovation and hence firms’ performance, we significantly contribute to advancing the theory of frugal innovation, the competition and strategy theory, and the extended resource-based view (ERBV).
... We thus adopt a richer conceptual framework where the technological transformation is a relationship, embedded in the production process, between inputs in which firms invest to increase their stock of productive knowledge and innovation outputs. This approach generally considers investments in R&D (Crépon, Duguet, and Mairesse 1998). However, Information and Communication Technologies (ICTs) and their digital advances have also been included in this relationship in a number of studies (Bartelsman, van Leeuwen, and Polder 2017;Mohnen, Polder, and Van Leeuwen 2019;Nicoletti, von Rueden, and Andrews 2020;Polder et al. 2010;Venturini 2015). ...
We investigate the links between the technological transformation of firms and employee control over working time. We conduct EU-wide analysis at the meso-level by relating information from the European Company Survey 2019 (Eurofound and Cedefop) with the Labour Force Survey ad hoc module 2019 (Eurostat). This dataset allows analysing the technological transformation of firms as a relationship between three types of investments (in R&D, digital technologies and learning capacity of the organisation) that spur innovation outputs. We then study the consequences of the technological transformation on the spread of unfavourable working time arrangements, distinguishing between individual and organisation-oriented arrangements. Our model considers the direct effects of investments in Digital technologies adoption and use and Learning capacity of the organisation and the mediating role of firms’ innovation strategies. Results indicate that the Learning capacity of the organisation is directly associated with more individual-oriented working time flexibility, but entails higher organisation-oriented working time flexibility. The effect of Digital technologies adoption and use depends instead on firms’ innovation strategy: product innovation leads to more employee control over working time, while marketing innovation has the opposite outcome. Process and organisational innovations yield mixed consequences buffering employees from organisation-oriented working time flexibility in more time-constrained work environments.
... For research on innovation, we show the relevance of considering a two-part model when modelling innovation sales relative to total sales. While some theoretical frameworks, such as those proposed by Crepon et al. (1998) and Ramalho et al. (2011), offer insights, there is a concurrent need for empirical models adept at accurately handling this distinct type of innovation output. We develop a suitable two-part framework that can handle the kind of data arising when analysing innovation sales and thereby hope to contribute to improving the statistical practices used to estimate innovation to improve the trustworthiness of results. ...
In empirical studies, firms’ innovation is often measured as the proportion of sales that can be attributed to new products or services. In a review of 20 years of research on innovation, we find this variable to be used in 141 studies providing a useful common ground to compare and contrast findings. We argue that two-part models are attractive when modelling innovation as they separate the decision to innovate from the amount of sales generated by innovation. Our review shows that only a minority of studies employ two-part models, most often in sub-optimal ways. We develop a two-part modelling framework that is suitable for innovation research and different from the conventional methods prevalent in econometrics. Furthermore, we provide a worked example of how it can be implemented. This paper contributes new knowledge about two-part models for innovation research and hopes to lay the ground for new theorising in the future.
... These innovation output activities are indicators of the outcome of the innovation process or results of R&D investment like training, technology adoption, and sales of new products new to the market or the firm. Crépon et al. [1998] introduced a new structural model that links innovation input (mostly R&D), innovation output, and productivity which provides insights into how these elements interact to drive firm performance. The Crépon-Duguet-Mairesse (CDM) model is a multistage econometric framework that sequentially links a firm's R&D investment to innovation output, and subsequently connects innovation output to productivity growth. ...
This paper explores the relationship between industrial policy, innovation, and productivity in the Philippines. It argues that strategic industrial policies can promote innovation by incentivizing market-oriented research and development and commercialization, developing necessary innovation infrastructure, and fostering a skilled workforce equipped to work with new technologies and adapt to changing market demands. The paper also focuses on the importance of connecting innovation and entrepreneurship ecosystems, highlighting the challenges facing the Philippines in this area. It specifically analyzes the country’s startup ecosystem and recommends the establishment of Regional Inclusive Innovation Centers (RIICs) to facilitate collaboration among various stakeholders. Finally, the paper discusses the adoption and adaptation of artificial intelligence and Industry 4.0 technologies and their potential to drive productivity gains and transform the Philippine economy.
... Kravtsova and Radosevic (2011) show that productivity growth in the post-socialist region is based mainly on production capability, not innovation capability. CDM is a workhorse model in the economics of innovation; it postulates that R&D leads to innovation, which in turn leads to productivity (Crepon, Duguet, and Mairesse 1998). Fedyunina and Radosevic (2022) showed that the CDM model does not capture stylized facts of the determinants of productivity based on a large sample of rms in Central and Eastern Europe, former Soviet republics, and Turkey. ...
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... Few studies highlight the difference between low-middle income and high income countries, for instance, Raffo et al. (2008) study the relationships between innovation inputs (usually R&D), output (for instance, product innovation), and economic performance (expressed by labour productivity) for three European countries (France, Spain and Switzerland) and three Latin American countries (Argentina, Brazil and Mexico) using firm-level data and the CIS survey and Latin American innovation surveys. The study presents empirical evidence using the Crepon, Duguet and Mairesse's (1998) structural model (CDM model 1 ) where R&D intensity affects product innovation. Results indicate innovation has a positive effect on labour productivity in countries studied for Latin America (Brazil and Mexico) except Argentina (however, the result is not robust). ...
... A reasonably large number of studies in innovation economics have investigated the factors that have led to the investment in R&D (Nelson, 1959). As expected, much of the literature on R&D determinants has majorly focused on the Schumpeterian hypothesis and the factors that determine inter-industry R&D activities (Cohen & Klepper, 1996;Crépon, Duguet, & Mairessec, 1998). Significant investigations have been around how characteristics of markets and firms (such as R&D, patents, collaborative innovation, physical and human capital, size of the firm, and sales revenue) influence industrial R&D and its output. ...
This study examines the firm-level R&D determinants of Indian high R&D intensive industries recognized for their historically weak R&D initiatives and global competitiveness. This study intends to use inflation-adjusted financial balanced panel data for 2001–2021 and apply the random effects Tobit model with bootstrapped standard errors. The study has found that stronger intellectual property regime dummy, export intensity, firm size square, and industry dummies for pharmaceutical, automobile, and electronics industries firm's market power and operational efficiency have positively impacted firm-level R&D intensity. In contrast, the negative and statistically significant impact of raw material import intensity and firm size indicates the requirement for planning and implementing appropriate managerial strategies. A bigger firm size does not stimulate R&D investment and offers a competitive edge to the R&D active firms, so managers may think about launching small R&D subsidiaries for innovation building. Policymakers may also focus on improving the outward orientation of the firm by facilitating exports and discouraging raw material imports.
... While in Solow's (1956) economic growth model the technological change was external and simply explained by the unexplained component in the model, Mansfield (1968) and later on Romer (1990) endogenised the technological progress and established it as a relevant component in macro-economic modelling, giving especially way to analyses of the technological competitiveness of countries, regions or sectors. At about the same time, analyses at the micro-economic level of the firm began to focus on effects of innovations on firm performance and competitiveness (Crépon et al. 1998;OECD 1996;Teece 1986Teece , 1998. R&D expenditures became the main input indicator to measure and assess the efforts to achieve new scientific and technological knowledge that lays the foundation of this competitiveness, both at the level of countries and at the level of firms. ...
Innovation indicators are instruments to systematically analyse the performance of innovation processes and systems. In this chapter we discuss the evolution of innovation indicators alongside conceptual developments as well as technical and methodological progress. We identify four driving factors, namely (1) new theories/concepts, (2) lower technical thresholds for data analyses and availability of new data, (3) increasing policy demands and (4) technological and economic developments. Our discussion shows that at different stages of the indicator development different factors were the driving forces. The early innovation indicators were mainly R&D-centred with a strong focus on the manufacturing industry and R&D processes in companies as well as the science systems. The innovation system’s perspective widened the focus and introduced additional indicators, among them indicators on transfer and collaboration. Data availability and better options for data treatment and analysis gave another push. More recently, information and computer science methods have entered the innovation indicators scene and widened the scope even further. We conclude that indicators are a means to measure and assess constructs which are otherwise not directly measurable. They should not become a means in itself.
... The literature on the economic impacts of innovation activities has gone from studying the use of innovation inputs such as R&D expenditures (see, e.g., the seminal paper by Griliches (1979)) to examining the whole innovation process, including innovation output, through productivity equations (Crepon et al. (1998)). The argument is that high levels of R&D expenditures do not guarantee any given innovation level, and innovation in general may occur through channels other than R&D expenditures. ...
Innovation is often seen as crucial for firm survival and as a way for firms to differentiate themselves from their rivals. However, innovation studies are vague about the actual importance of different innovation strategies. In this study, we distinguish between pure product, process, organizational, and marketing innovations and their combinations. We use a (balanced) panel data set with more than 15,000 firm-year observations for manufacturing firms to analyze the performance of firms with different innovation strategies. Additionally, we investigate from a societal perspective whether innovation facilitates less efficient firms to catch up, or whether firms already utilizing best practices are the main beneficiaries. Using Data Envelopment Analysis (DEA), we find the highest increase in firms’ performance among the firms with innovation strategies that combine product innovation with other innovation types. This finding applies to both the short and the longer term. We also conclude that catch-up is strongest among the firms adopting pure process innovation, whereas the other innovation strategies are primarily associated with frontiers shifts.
... We run three types of regressions 4 : (i) models on a firm's propensity to introduce new processes and product quality improving processes; (ii) models on the output of new processes: increases in sales due to quality improvement, percentage reductions in costs, percentage reductions in defect 3 The skill requirement is a subjective judgement of the respondent, and this should be viewed in that context. 4 The model is similar to the reduced form model proposed by Crépon et al., (1998 rates, percentage reductions in production cycle time, and percentage increases in production capacity; and (iii) models on the impact of new processes on measures of firm performance: labor productivity, sales, and employment. ...
... La evidencia empírica muestra que las empresas que logran innovar tienen resultados en mejoras en su desempeño, en términos de ventas (M. Tello, 2020) y productividad laboral (Crepon et al., 1998;Lööf & Heshmati, 2006). Por esta razón, juega un rol fundamental en la asignación óptima de los recursos de una economía hacia agentes de alta productividad (PRODUCE, 2016). ...
This paper addresses the determinants of the introduction of new goods and services, or significant improvements in existing ones, in the market (product innovation) by firms in the manufacturing sector. Using data from the 2018 Peru National Innovation Survey, count models are employed, specifically the Poisson Regression Model (RPM) and the Zero Inflated Poisson Model (ZIP). The findings reveal that research and development (R&D) spending and innovation training have the largest significant impact on the number of innovations introduced. In addition, a significant effect of firm size and collaboration with universities and/or firms on the product innovation process is observed. These results contribute to a better understanding of the drivers of innovation in the manufacturing industry.
Balanced combinations of technological and non‐technological innovations, or ‘complex innovation strategies’, are associated with better firm performance. However, the mechanisms through which different internal and external knowledge sources influence the resulting innovation profiles of firms are underexplored. This paper addresses these mechanisms, by establishing a theoretical framework and empirically assessing the direct effect of the main knowledge sources, as well as the indirect effect via absorption and spillovers, on the likelihood of adopting simple or complex innovation strategies. Using data from the three most recent waves of the Italian Community Innovation Survey (2014, 2018, 2020), we find that all sources of knowledge contribute to increase the likelihood of being a complex innovator along an inverted U‐shaped curve. Moreover, we find a significant impact of the absorption of knowledge embodied in machinery, equipment and software, while no evidence of spillovers from external applied knowledge, here measured by extramural R&D, significantly emerges.
The first micro-empirical study conducted in Georgia revealed significant correlations between innovation and productivity by firm size. The CDM model explores both the factors influencing innovation and the impact of innovation on labor productivity. It was revealed that research and development in Georgia is not an essential factor affecting innovation. In particular, research and development are statistically significant negatively correlated with product and process innovation. It was found that innovations in Georgia do not have a significant impact on productivity, which contradicts the widely held view. On productivity, a statistically significant positive affected by fixed capital growth and number of employees. This is confirmed by the results reflected in the Global Competitiveness Reports, according to which Georgia is in the "investment-oriented stage" of economic development. Based on the above, we can assume that the country should move from investment - to a proactive policy focused on productivity.
Recent statistics have shown that carbon dioxide emissions in Indonesia are increasing due to its booming economy. However, the adoption of environmental management measures consumes labor for their execution, which may reduce manufacturing outputs due to the extracted workforce. Previous literature reported mixed results of environmental investments in different production contexts. This paper examines how the adoption of environmental management measures influences labor productivity in Indonesian enterprises. The regression analysis results of a World Bank Enterprise Survey for Indonesia in 2023 show that increasing labor investments such as wages, training, and bonuses, significantly increase the positive impact of the adoption of environmental management on labor productivity. The finding indicates that with more significant labor inputs, the adverse impact of environmental management on labor productivity diminishes. The study results suggest that firms should integrate their investments in environmental management with labor inputs to leverage productivity.
In contemporary times, there is a widespread and continuous technological transformation driven by the scientific-technical revolution, affecting all countries. Consequently, the focus of a nation's development has shifted from a static, short-term, and resource-based business approach to more innovative, dynamic, and creative models. For Georgian companies seeking to establish themselves as competitive entities in the global business landscape, it is crucial to conduct a comprehensive analysis of technological environmental factors and integrate them into their international business strategies. One critical aspect in this direction is the empirical examination of the relationship between innovation processes and productivity at the micro-level. To achieve this, the study employs microdata provided by the World Bank and employs structural model known as the CDM model. This approach allows for an analysis of the impact of product/service and process innovations on the productivity of Georgian companies, considering their specific scale and size. The research proceeds in several stages. Firstly, it investigates the factors influencing research and development, followed by an analysis of the determinants of product/service and process innovation. Finally, the study identifies the overall impact of innovation on productivity. Notably, the results highlight significant causal connections between innovation and productivity concerning the size of the company. Surprisingly, the empirical research conducted on Georgian firms revealed unexpected outcomes. Specifically, it was found that research and development (R&D) exerted a statistically significant negative influence on innovation processes. Furthermore, the contribution of innovation to labor productivity was not statistically significant. However, on a positive note, the study demonstrated that investments in fixed capital and the number of employees had a favorable impact on labor productivity. In conclusion, the ongoing technological advancements driven by the scientific-technical revolution have led countries to shift their developmental focus towards innovation-oriented and dynamic business models. For Georgian companies aiming to thrive in the global business arena, it is essential to consider the relationship between innovation and productivity at the micro level. The study conducted using the CDM model and microdata from the World Bank revealed interesting insights, indicating the need for further investigation and exploration of these findings.
This study utilizes both cross-sectional and year-by-year settings of Propensity Score Matching with Difference-in-Differences (PSM-DID) method to analyze the impact of the 2015 Environmental Protection Law (NEPL) on green innovations and total factor productivity in heavy polluting firms within manufacturing industries, spanning 2010–2018. Employing the Cobb-Douglas production function framework, it posits green innovation as a crucial technological resource augmenting tangible assets and technological productivity. The analysis reveals differentiated effects of NEPL on various types of green innovations: a negative impact on alternative energy and green transportation patents, while energy-saving and waste management patents remain largely unaffected. This suggests a crowding-out effect of environmental regulations on certain green innovations. Interestingly, heterogeneity analysis shows that smaller, less profitable heavy-polluting firms economically gain more from green innovations, particularly in waste management and energy-saving, while strict policies pose challenges for the alternative energy sector, highlighting the need for diverse, more supportive and adaptive policy approaches.
This study examines the role of perceptions about environmental regulations and their influence on the innovative performance and productivity of firms in Germany, Southern Europe, and Central and Eastern Europe. Utilizing the CDM model for innovative performance and data stemming from the Community Innovation Survey (CIS), we explore the alignment with the Porter hypothesis, which posits that well-designed environmental regulations can stimulate technological innovation and enhance market competitiveness. Our findings present a mixed view: in Germany, positive perceptions about environmental regulations correlate with the initiation of innovation activities, contributing to an increase in labour productivity. This supports the Porter hypothesis, evidencing that regulations can lead to beneficial ‘innovation offsets’ such as reduced resource use and pollution. Conversely, in Southern Europe and Central and Eastern Europe, the perceptions about these regulations on innovation activities are insignificant, with no considerable correlation observed between perceptions about environmental regulations and innovation output. Our findings are crucial for policymakers, environmental regulators, and business leaders aiming to leverage environmental regulations to boost innovation and competitiveness within their regions.
This chapter examines the role of different types of innovation in helping latecomer firms survive and succeed during adverse economic conditions in developing countries, using Argentina’s 1998–2001 economic crisis as a case study. The study draws on latecomer firm theory and firms’ differences in evolutionary theory to investigate the competitive strategies of latecomer firms, focusing not only on product and process innovations but also on nontechnical areas such as organizational innovations. The empirical analysis is based on data from the Second Innovation Survey in Argentina, covering a sample of 1688 manufacturing firms.
The results show that technological innovation, particularly the introduction of product and process innovations, positively impacted firm performance during the economic crisis. Process innovations had a greater impact on total sales and labor productivity compared to product innovations, suggesting that latecomer firms prioritized the sale of cheaper goods through process innovations. The role of non-technological innovations, such as marketing and organizational innovations, had mixed results. Organizational innovations, when measured as inputs or efforts toward organizational change, had a positive impact on firm performance. This suggests that organizational capabilities, such as new business strategies and quality management systems, are important during times of crisis.
The study also highlights the preference for flexibility among firms operating in crisis-ridden countries like Argentina. Organizational innovations were found to have a stronger impact on total sales than on labor productivity, indicating their relevance in improving corporate flexibility and customer-oriented structures.
Overall, the findings suggest that latecomer firms in developing countries can benefit from both technological and non-technological innovations to navigate and succeed during economic crises. The chapter concludes by emphasizing the need for further research and case studies to enhance our understanding of the relationship between innovation and firm performance in developing country contexts.
This chapter provides a summary of the concluding remarks from the statistical analysis and case studies conducted in this research. The main research question of this study was why and how a latecomer firm facing adverse policy regimes in Argentina might be able to survive, grow, and eventually catch up, while many other firms lagged behind. The statistical analysis showed that innovative firms performed better than non-innovative ones during the economic crisis in Argentina. Process innovations had a greater impact on total sales than product innovations, indicating that latecomer firms prioritized the sale of cheaper goods through process innovations. Organizational innovations had a nonsignificant effect on firm performance, but when measured as inputs or efforts toward organizational change, they positively impacted performance. The case studies of TENARIS and IMPSA further supported these findings and highlighted the importance of long-term vision, strategic adaptability, innovative behavior, and an entrepreneurial spirit in the success of latecomer firms. TENARIS and IMPSA both followed a contrarian path, ignoring prevailing policy regimes and focusing on strategies, structures, and capabilities that allowed them to catch up with global competitors. TENARIS prioritized the sale of cheaper goods through continuous production, while IMPSA focused on small-batch production and technological modernization. Both firms overcame technological backwardness, gained access to global markets, and managed adverse macroeconomic conditions through their corporate strategies. They also maintained corporate coherence and developed specialized capabilities in their respective industries. The findings of this study have theoretical implications for understanding the strategic maneuvering of latecomer firms and the role of governments and institutions in the process of structural transformation. Methodologically, the study suggests the importance of combining quantitative and qualitative approaches to capture the impact of macro variables on firm behavior. The implications for corporate strategy and policy highlight the need for latecomer firms to be proactive and develop innovative strategies to overcome adverse circumstances. Policymakers should consider supporting successful domestic firms that have the potential to succeed in advanced export markets. Overall, this research provides insights into the factors that contribute to the success of latecomer firms in developing countries.
We examine the effects of innovation, productivity and export on small and medium‐sized enterprises (SMEs) in the Swedish wood manufacturing sector. Previous studies have produced mixed results on these topics, which may be due to methodological limitations, contextual differences and inadequate operationalisation of key variables. To address these gaps, we adopt a more specific and rigorous approach, focusing on product innovation and using sophisticated statistical methods to account for endogeneity and other confounding factors. We use a longitudinal dataset to analyse how SMEs select into export markets and learn from exporting, as well as how other factors influence their export performance. We find that innovation and export have a nonlinear relationship, which depends on the level of interaction between SMEs and their international customers, and the degree of fit between their innovative products and the export market. In particular, when SMEs have high international customer engagement, they are more likely to innovate in ways that enhance their export potential. Regarding productivity, we find that self‐selection is more advantageous for SMEs, while learning‐by‐exporting is more consistent in controlling for unobserved factors.
سرمایهگذاری جسورانه به تازگی در محافل علمی و پژوهشی در کشور ما مطرح شده است. این سرمایهگذاری مخصوص شرکتهای دوران مخاطره[1] طراحی شده است و امروزه به عنوان یکی از موثرترین و کاراترین روشهای تامین مالی طرحها و شرکتهای نوپا[2] در سطح دنیا مطرح است و توانسته است با حمایت و نقش آفرینی از ایدههای برتر، چهره دنیا را در بسیاری از زمینه ها تغییر دهد.
در این پژوهش، بهصورت تجربی، بینِ شرکتهای دانشبنیانی که از سرمایهگذاری مخاطرهپذیر استفاده کردهاند و شرکتهای دولتی که از بودجۀ دولتی بهره گرفتهاند، مقایسه انجام دادهایم. فعالیتهای نوآورانۀ آنها را درمقابل دیگر ویژگیهای سازمانی بررسی و نقش سرمایهگذاری مخاطرهپذیر بر استراتژیهای نوآورانه را مورد تجزیه و تحلیل قرار دادیم. در این راستا، دریافتیم که شرکتهای دانشبنیان پرتفوی خود را بهسمت جذب پتانسیلهای بیشتر در داخل شرکت سوق میدهند و اهمیت بیشتری برای نتایج واحد تحقیق و توسعه قائل هستند. برخلاف این امر، متوجه شدیم که تأمین مالی عمومی، محدودیتهای مالی زیادی به شرکتهای دولتی وارد نکرده است، اما این دسته از شرکتها ظرفیتها و استراتژیهای نوآورانۀ کمتری بهکار میبرند. نتایجِ بهدستآمده، بهصورت مشخصی نقش سرمایهگذاری مخاطرهپذیر را در شکلدهی استراتژیهای نوآورانه نشان میدهد.
The purpose of this article is to analyse the relationship between different innovation profiles, capabilities, and innovation results of manufacturing firms from Argentina. The premise that guides our research is that most of firms not performing formal R&D -92%- are a highly heterogeneous group in terms of innovative behaviour, capabilities and innovative performance. Thus, we propose to study firms’ innovation profile as a gradient that accounts for formal R&D, informal R&D, non- R&D performing firms and firms without innovation efforts. Then, the relationship between these profiles and five dimensions of firms’ capabilities -productive, organizational, connectivity, and accumulated and potential absorptive - is explored. Accordingly, the study of how these profiles correlate with firms’ innovation results -products and/or processes innovations, new marketing and/or organizational changes, patents and ratio of new product sales to total sales- is also carried out. The empirical evidence is based on Argentinean manufacturing firms with data from the second wave of the National Innovation Survey composed by around 4000 observations for the period of 2014-16. Results suggest that more complex R&D profiles require higher levels of capabilities. Moreover, there seems to be a threshold of capabilities in moving from the non-R&D to the informal R&D profile. Likewise, while informal R&D is a critical threshold to increase the probability of obtaining product, process, organization and marketing innovations, formal R&D is key to get patents and to increase the share of new products on total sales.
In this paper, we discuss several aspects related to innovation and entrepreneurship in Latin America (LATAM). First, we document how LATAM lags behing high-income economies using various innovation indicators and how heterogeneity is a relevant issue for the region. Then, we review the main research topics related to innovation and entrepreneurship covered by economic academic research focused on the region. Within this context, we summarize the main results and contribution of the selected papers for this special issue.
Background and objectives: This research analyzes the determinants of technological development in the manufacturing and service industries that receive state funding in Colombia. The objective is to identify the critical elements that affect innovation and technological development in these industries to propose improvements in public policies. Methods: A mixed-method approach was adopted, combining qualitative case analyses and Poisson regression techniques, using data from the Technological Development and Innovation Survey (EDITS IX), which included 7,762 manufacturing companies and 9,304 service and trade companies. Findings: The results indicate that the key factors influencing innovation and technological development are the insufficiency of internal financial resources, the lack of information about support mechanisms, and difficulties in accessing state funding. The insufficiency of internal financial resources limits the capacity of companies to invest in research and development activities. Additionally, the lack of information about available support mechanisms prevents many companies from accessing resources that could boost their technological development. Finally, due to bureaucratic processes and lack of clarity in requirements, difficulties in accessing state funding represent a significant barrier for many companies. Conclusion: These findings highlight the need for public policy reforms to strengthen Colombia's innovation and technological development ecosystem. The suggested reforms include simplifying the processes to access state funding, improving the dissemination of information about available support mechanisms, and increasing the availability of internal financial resources for companies. These measures would enhance companies' competitiveness and productivity, fostering a more favorable environment for innovation and technological development. The research underscores the importance of adjusting public policies to create a more conducive environment for innovation and technological development in Colombia, thereby improving business competitiveness and productivity.
Perseverance in R&D effort is the first fundamental step towards any kind of innovation. We investigate the beginning of the innovation story, rather than its end, through duration models. Among the drivers of our unconventional IO approach, we focus on heterogeneity, path dependence and market power, measured as elasticity of firm-specific demand. The Schumpeterian hypothesis emerges at the firm level. Heterogeneity at the industry level reveals Schumpeterian and Arrovian patterns, as well as U-shaped and inverted U-shaped patterns. We suggest considering the entire supply chain from a holistic perspective when evaluating mergers and innovation policies that support small firms by reducing their financial uncertainty and improving their institutional environment.
Developing countries exhibit unfavorable environmental conditions due to suboptimal technology utilization, low productivity, lower per capita income, and other factors that intensify environmental pressures. This situation underscores the significance of investigating the impacts of technology spillovers on environmental quality. In recent years, substantial attention has been devoted to assessing environmental quality and sustainability at national and international levels. Governments worldwide have recognized that environmental performance cannot be viewed solely through economic development; it must encompass other facets of development, particularly social development. Given that the Human Development Index (HDI) can concurrently gauge social and economic progress, this study aims to assess the influence of HDI components (life expectancy at birth, mean years of schooling, and gross national income) as well as technology spillover (resulting from the import of knowledge carriers) on environmental quality in D-8 countries during the period from 2003 to 2022, utilizing the autoregressive distributed lag method. The findings reveal a U-shaped relationship between HDI variables and long-term environmental quality. Furthermore, technology spillovers foster increased knowledge, the development of competitive advantages, and economic integration. The results also highlight a significant negative long-term relationship between technology spillover and environmental quality. Consequently, policymakers in D-8 countries are encouraged to establish a framework conducive to introducing and localizing eco-friendly technologies through adopting macroeconomic policies.
Artykuł porusza problematykę innowacyjności krajów Unii Europejskiej. Innowacyjność gospodarki jest rozumiana jako zdolność do tworzenia i wdrażania innowacji. Cel prowadzonych badań stanowi określenie siły i kierunku wpływu nakładów na działalność B+R na pozycję innowacyjną unijnych gospodarek. Pozycja innowacyjna to jedna z dwóch kategorii opisujących innowacyjność gospodarki. Wyraża efekty połączenia kreatywności społeczeństwa z zasobami finansowymi w określonym środowisku ekonomicznym i instytucjonalnym. Z kolei nakłady na działalność B+R są istotnym czynnikiem determinującym zdolność danej gospodarki do innowacji, tj. stopnia, w jakim ma ona możliwość tworzenia i komercjalizacji nowych pomysłów. W artykule nakłady rozpatrywane są w dwóch kategoriach: kapitału finansowego i kapitału ludzkiego. Weryfikacji podlega hipoteza główna mówiąca o tym, że nakłady na działalność B+R mają dodatni, istotny statystycznie wpływ na pozycję innowacyjną gospodarki. Do realizacji celu badań oraz weryfikacji sformułowanej hipotezy zastosowano modelowanie równań strukturalnych PLS-SEM (partial least squares structural equation modeling). Modele PLS-SEM oszacowano na podstawie danych przekrojowych dotyczących 27 krajów UE. Dane odnosiły się do trzech lat: 2017, 2019 i 2021. Wyniki modelowania wskazały, że w badanym okresie nakłady na działalność B+R wywierały silny, dodatni, istotny statystycznie wpływ na pozycję innowacyjną gospodarek krajów UE. Zarówno kapitał finansowy, jak i kapitał ludzki wpływały istotnie, dodatnio na pozycję innowacyjną analizowanych gospodarek, przy czym większe znaczenie miał kapitał finansowy. W artykule dokonano również porządkowania krajów UE ze względu na wielkość nakładów na B+R, kapitał finansowy i ludzki oraz pozycję innowacyjną gospodarki.
Objetivos: La presente investigación analiza los factores determinantes del desarrollo tecnológico en las industrias manufacturera y de servicios que reciben financiamiento estatal en Colombia. El objetivo es identificar los elementos críticos que afectan la innovación y el desarrollo tecnológico en estas industrias para proponer mejoras en las políticas públicas. Métodos: Se adoptó un enfoque mixto, combinando análisis cualitativos de casos y técnicas de regresión Poisson, utilizando datos de la Encuesta de Desarrollo e Innovación Tecnológica (EDIT IX), que incluyó 7,762 empresas manufactureras y 9,304 empresas de servicios y comercio. Resultados: Los resultados indican que los factores clave que influyen en la innovación y el desarrollo tecnológico son la insuficiencia de recursos financieros propios, la falta de información sobre mecanismos de apoyo y las dificultades en el acceso al financiamiento estatal. La escasez de recursos financieros propios limita la capacidad de las empresas para invertir en actividades de investigación y desarrollo. Además, la falta de información sobre los mecanismos de apoyo disponibles impide que muchas empresas accedan a recursos que podrían impulsar su desarrollo tecnológico. Por último, las dificultades en el acceso al financiamiento estatal, debido a procesos burocráticos y falta de claridad en los requisitos, representan una barrera significativa para muchas empresas. Conclusión: Estos hallazgos destacan la necesidad de reformas en las políticas públicas para fortalecer el ecosistema de innovación y desarrollo tecnológico en Colombia. Las reformas sugeridas incluyen la simplificación de los procesos para acceder al financiamiento estatal, la mejora de la divulgación de información sobre los mecanismos de apoyo disponibles y el aumento de la disponibilidad de recursos financieros propios para las empresas. Estas medidas contribuirían a mejorar la competitividad y productividad de las empresas, fomentando un entorno más favorable para la innovación y el desarrollo tecnológico. La investigación subraya la importancia de ajustar las políticas públicas para crear un entorno más propicio para la innovación y el desarrollo tecnológico en Colombia, mejorando así la competitividad y productividad empresarial.
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