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This paper aims to analyse the impact of innovation on the productivity of firms in India using the data from the World Enterprise Survey. This paper first classifies three different types of innovation measures then further analyses their relation with the productivity of the firms.

The methodology used for this study has incorporated the structural Crépon-Douget-Mairesse (CDM) model wherein productivity is measured using both the innovation inputs and the innovation outputs. Three main equations have been used to quantify this relation includes the knowledge intensity function, innovation function and the productivity equation.

Findings indicate that decision to invest in research and development (R&D) is influenced negatively by financial obstacles and trade obstacles and positively influenced by telecommunication obstacles, government obstacles and the size of the firm in India. Similarly, financial obstacles and the size of the firm are affecting the firm’s research expenditure per employee. Also, financial obstacles seem to hinder the research intensity and larger firms seem to have higher research intensity. The size of the firm contributes significantly to product innovation. However, R&D spending seems to be negatively related to the innovation outcome. The findings relating to productivity shows neither product nor process innovation outputs, independently are not contributing significantly to the productivity of firms. However, product and process innovation, together serve as innovation outputs is a significant contributor to firm productivity. On the other hand, organisational innovation contributes significantly to the productivity of the firms in a negative manner.

The findings relating to productivity shows neither product nor process innovation outputs, independently are not contributing significantly to the productivity of firms (which has been measured by sales per worker is impacted by the capital and the labour inputs). However, product and process innovation, together serve as innovation outputs is a significant contributor to firm productivity. On the other hand, organisational innovation contributes significantly to the productivity of the firms in a negative manner. The reason could be due to the fact that the definition of organisational innovation incorporates both dissolutions and mergers.

The purpose of this paper is to analyze the effect of competition on both innovation inputs and outputs in Chilean firms. More specifically, the authors investigate whether there is an inverted-U relationship at different stages of the innovation process.

The sample covers 1,347 firms that responded to both the 4th Chilean Longitudinal Enterprise Survey and the 10th Chilean Innovation Survey. The CDM model (Crépon et al., 1998) is applied to correct for selectivity bias and endogeneity. Competition is proxied by measures of market concentration. The robustness of the results is checked using four alternative indicators.

The results strongly suggest that competition and both R&D and innovation intensities are linked by an inverted U-shaped curve. The estimated effects of competition on innovation output and labor productivity are rather ambiguous. Thus, market structure would be influencing the firms’ incentives to innovate, but not necessarily their innovation performance.

The model is based on cross-sectional data, hampering the possibility to control for unobserved heterogeneity. Competitive pressures from potential entrants and foreign markets are not captured in the analysis.

Moderate levels of competition would be the optimal market structure in terms of promoting more business R&D and innovation spending.

A previously unutilized data set covering the whole economy is used. Estimations are executed at three different stages of the innovation process. Two types of innovation input and four types of innovation output are taken into account.

El objetivo de este artículo es analizar los efectos de la competencia sobre los insumos y los productos de la innovación en empresas chilenas. Más específicamente, los autores investigan si existe una relación en forma de U invertida en diferentes etapas del proceso de innovación.

La muestra abarca 1.347 empresas chilenas que respondieron la 4ª Encuesta Longitudinal de Empresas y la 10ª Encuesta Nacional de Innovación. El modelo CDM (Crépon et al., 1998) es aplicado con el fin de corregir por sesgo de selección y endogeneidad. La competencia es representada por medidas de concentración de mercado. La robustez de los resultados es verificada usando cuatro indicadores alternativos.

Los resultados sugieren claramente que la competencia y las intensidades de I+D e innovación están vinculadas por una curva en forma de U invertida. Los efectos estimados de la competencia sobre la producción de innovación y la productividad laboral resultan ser más bien ambiguos. Así, la estructura de mercado estaría influyendo en los incentivos de las empresas para innovar, pero no necesariamente en los resultados del proceso de innovación.

El modelo se basa en datos de corte transversal, dificultando la posibilidad de controlar la heterogeneidad no observada. Las presiones competitivas de potenciales entrantes y mercados extranjeros no se reflejan en el análisis.

Niveles moderados de competencia serían la estructurada de mercado óptima para promover un mayor gasto en I+D e innovación en el sector empresarial.

Se usa un conjunto de datos no utilizado previamente y que cubre toda la economía. Las estimaciones se realizan en tres etapas diferentes del proceso de innovación. Se tienen en cuenta dos tipos de insumos de innovación y cuatro tipos de resultados de innovación.

Competencia, I+D, Innovación, Productividad, Chile

Trabajo de investigación

O objetivo deste artigo é analisar os efeitos da competição nos insumos e produtos de inovação em empresas chilenas. Mais especificamente, os autores investigam se existe uma relação na forma de um U invertido em diferentes estágios do processo de inovação.

A amostra inclui 1.347 empresas que responderam a 4ª Pesquisa Longitudinal de Empresas e 10ª Pesquisa Nacional de Inovação. O modelo CDM (Crépon et al., 1998) é aplicado para corrigir o viés de seleção e endogeneidade. A competição é representada por medidas de concentração de mercado. A robustez dos resultados é verificada usando quatro indicadores alternativos.

Os resultados sugerem claramente que a competição e as intensidades de P&D e inovação estão ligadas por uma curva em U invertido. Por sua vez, os efeitos estimados da concorrência na produção de inovação e na produtividade do trabalho revelam-se bastante ambíguos. Assim, a estrutura de mercado estaria influenciando os incentivos das empresas para inovar, mas não necessariamente nos resultados do processo de inovação.

O modelo é baseado em dados transversais, dificultando o controle da heterogeneidade não observada. As pressões competitivas de concorrentes potenciais e mercados estrangeiros não são refletidas na análise.

Níveis moderados de concorrência seriam a estrutura de mercado ideal para promover maior gasto em P&D e inovação no setor empresarial.

Este artigo usa um conjunto de dados anteriormente não utilizado e que abrange toda a economia. As estimativas são feitas em três etapas diferentes do processo de inovação. Dois tipos de insumos de inovação e quatro tipos de resultados da inovação são considerados.

Competição, P&D, Inovação, Produtividade, Chile

Trabalho de investigação

As high-tech industries are the main responsible for research and development (R&D), the purpose of this paper is to investigate some of the possible determinants of R&D investment in this type of industry.

The analysis is based on a sample of European high-tech industries represented both by countries of civil law origin and common law origin. The authors used data from 155 high-tech firms in the period between 2011 and 2016. The sample was collected from Amadeus database. The panel data methodology was used to test the dependence of R&D expenses ratio according to different variables. Specifically, the authors have used the generalized method of moments (GMM) estimation method.

The results point out that there are differences in the explanation of the R&D ratio depending on whether the authors are dealing with countries of civil legal origin or common legal origin. The evidence also suggests that the intangible assets, contrary to the expect result, have a negative influence on R&D. Probably in this recovery time, as de global financial crisis and the sovereign debt crisis for Eurozone countries, the high-tech firms are using their intangible assets to create value and not for more investments in R&D. Companies are not renewing their asset stocks.

As high-tech companies are traditionally rich in R&D, this research can contribute with additional pieces to the knowledge of the factors that contribute to this. Thereby, this study may be interesting for managers, investors and civil society. This study adds value as it is unique in addressing this topic on this new dimension, with respect to the sample and indicators presented.

Como las industrias de alta tecnología son las principales responsables por la I + D, proponemos investigar algunos de los posibles determinantes de la inversión en I + D en este tipo de industria.

Nuestro análisis se basa en una muestra de indústrias europeas de alta tecnología representadas tanto por países de origen civil como por derecho consuetudinario. Utilizamos datos de 155 empresas de alta tecnología en el período comprendido entre 2011 y 2016. Nuestra muestra se recopiló de la base de datos Amadeus. La metodología Panel Data se utilizó para evaluar la dependencia del índice de gastos de I + D de acuerdo con diferentes variables. Específicamente, hemos utilizado el método de estimación del Método Generalizado de Momentos (GMM).

Nuestros resultados señalan que existen diferencias en la explicación de la relación de I + D dependiendo de si estamos tratando con países de origen legal civil u origen legal común. Nuestra evidencia también sugiere que los activos intangibles, al contrario del resultado esperado, tienen una influencia negativa en la I + D. Probablemente en este tiempo de recuperación económica, desde la crisis financiera mundial y la crisis de la deuda soberana para los países de la zona euro, las empresas de alta tecnología están utilizando sus activos intangibles para crear valor y no para más inversiones en I + D. Las empresas no renuevan sus activos.

Dado que las empresas de alta tecnología son tradicionalmente ricas en I + D, esta investigación puede contribuir con piezas adicionales al conocimiento de los factores que contribuyen a esto. Por lo tanto, este artículo puede ser interesante para gerentes, inversores y la sociedad civil. Este artículo agrega valor, ya que es único al abordar este tema en esta nueva dimensión, con respecto a la muestra y los indicadores presentados.

Como as indústrias de alta tecnologia são as principais responsáveis pela investigação e desenvolvimento, neste trabalho propomos investigar alguns dos possíveis determinantes da I&D nesse tipo de indústria.

A Nossa análise é baseada em uma amostra de indústrias europeias de alta tecnologia representadas por países de origem do direito civil e de direito comum. Foram utilizados dados de 155 empresas de alta tecnologia no período compreendido entre 2011 e 2016. Os dados foram recolhidos da base de dados Amadeus. Foi usada a metodologia de Dados em Painel para testar a dependência entre as despesas de I&D e as diferentes variáveis explicativas. Especificamente, usamos o método de estimação Método generalizado de momentos (GMM).

Os nossos resultados apontam que existem diferenças na explicação do índice de I&D, dependendo de estarmos lidando com países de origem legal civil ou de origem legal comum. As evidências também sugerem que os ativos intangíveis, ao contrário do resultado esperado, influenciam negativamente a I&D. Provavelmente neste período de recuperação económica, desde a crise financeira global e a crise da dívida soberana dos países da zona do euro, as empresas de alta tecnologia estão a usar os seus ativos intangíveis para criar valor e não para mais investimentos em I&D. As empresas não estão a renovar os seus ativos.

Como as empresas de alta tecnologia são tradicionalmente ricas em I&D, este trabalho pode contribuir com peças adicionais para o conhecimento dos fatores que contribuem para esse facto. Assim, este artigo pode ser interessante para gestores, investidores e sociedade civil. Trata-se de uma investigação que agrega valor, pois é único ao abordar este tópico nesta nova dimensão, com relação à amostra e às variáveis apresentadas.

The estimation of regression models subject to linear restrictions is a widely applied technique; however, aside from simple examples, the equivalence between the linear restricted case to the reparameterization and the substitution case is rarely employed. We believe this is due to the lack of a general transformation method for changing from the definition of restrictions in terms of the unrestricted parameters to the equivalent reparameterized model and conversely from the reparameterized model to the equivalent linear restrictions for the unrestricted model. In many cases, the reparameterization method is computationally more efficient especially when estimation involves an iterative method. But the linear restriction case allows a simple method for adding and removal of restrictions.

In this chapter, we derive a general relationship that allows the conversion between the two forms of the restricted models. Examples emphasizing systems of demand equations, polynomial lagged equations, and splines are given in which the transformation from one form to the other are demonstrated as well as the combination of both forms of restrictions. In addition, we demonstrate how an alternative Wald test of the restrictions can be constructed using an augmented version of the reparameterized model.

The purpose of this paper is twofold: first, it aims to investigate how internal and external drivers affect innovation in the Italian food industry. Second, the authors are interested to understand to what extent these drivers are industry specific, and therefore, they are contrasted against those relevant for the pharmaceutical industry in Italy according to the increasing growth of cross-industry innovation between these two sectors. The paper aims, thus, to shed light on the differences between food and pharmaceutical industries in terms of innovation drivers to understand potential precursors of emerging industry convergence.

Both probit and bivariate probit models are estimated, using data from the Italian Community Innovation Survey, in order to provide empirical evidence on drivers affecting innovation in the food and pharmaceutical industries.

The innovation activity of Italian food and pharmaceutical companies strongly relies on the presence of in-house R & D activities. Whereas firms in the pharmaceutical industry combine both internal and external R & D activities and knowledge sources to produce innovation, the case of the food industry is strongly dependent on the acquisition of external technology. In particular, the increased need for absorptive capacity of both sectors emphasises the key role of university research for collaboration, knowledge transfer and product innovation.

The paper gives insights not only on drivers for innovation, but especially on the industry-specific differences which should be taken into account to have a contingent view. Limitations concern the impossibility to perform panel data analysis, due to the design of the database. Furthermore, both food and pharmaceutical sub-samples are not completely representative, since large companies tend to be overrepresented.

This paper provides managerial insights concerning the internal and external drivers affecting innovation. Moreover, it raises awareness as regards the possible differences between the food and pharmaceutical industries, which is crucial for establishing successful pathways for cross-industry innovation.

This study represents one of the few attempts to compare the innovation drivers of two manufacturing sectors (food and pharmaceutical), increasingly involved in cross-industry collaborations, and to highlight the industry-specific differences in those drivers which can act as forerunners of this phenomenon.

The objective of the study is to analyse the impact of research and development investment on the firm performance of “small” scale firms vis-a-vis “medium”-scale firms.

The dataset comprised of a balanced panel of 486 research and development conducting Indian manufacturing small and medium enterprises, constructed for the period of 2006–2017. Fixed Effects, Random Effects Model and Hausmann test were used to analyse the determinants of firm performance in manufacturing small and medium enterprises in India.

It was found that from firms’ research and development (R&D) investments in terms of performance could be attained if simultaneously internationalisation and higher capital intensity could be achieved.

Managers could pay specific attention to the antecedents of firm performance and calibrate their R&D investment, internationalisation efforts and capital intensity simultaneously to achieve higher growth and productivity. For policymakers, the results provide an insight into how the firms in both categories could be differently incentivised, such that resources are better utilised.

The study analysed the determinants of firm performance in small and medium-sized firms at a disaggregate level as well as at a sectoral level using fixed effects, random effects and lagged effects to arrive at novel results, which have important implications for their competitiveness.

44. The Author and Title Catalogue should comprise entries for all books under authors' names, under titles where necessary, and under series if any, and should include references under any other names or words necessary to its use as an efficient means of reference : the whole arranged in one alphabetical sequence.