High-growth versus declining firms: the differential impact of human capital and R&D

We provide evidence that both human capital and R&D increase the likelihood that a firm will be a high-growth firm in the industry. However, different from human capital, being an R&D active firm also increases the probability of substantial decline or failure, underscoring the risky nature of innovation. Quantile regression results show that, different from R&D, human capital is growth-enhancing for all firms, hence also those located in the lower quantiles of the distribution of growth rates across firms.     

Nonparametric quantile regression analysis of R&D-sales relationship for Korean firms

This paper applies the nonparametric quantile regression estimation procedure to the analysis of the innovation-firm size relationship using Korean manufacturing firms data. Due to the high asymmetric distribution of R&D expenditure, the mean regression does not capture properly the stylized facts of R&D behavior; hence it underestimates the sales elasticity. Comparing the parametric estimates and nonparametric estimates allows us to see that there exists a nonlinear relationship in innovative activity and sales. Dividing the data into three groups according to the sales volume, the elasticity in the medium-sized firms is the biggest for scientific firms. This result conforms that the findings of Scherer (1965) coincide with findings from Korean manufacturing firms data in the sense that R&D expenditure tends to increase faster than firm size with size up to a point and then more slowly among larger firms. For the non-scientific firms, it steadily increases showing increasing returns to scale in innovative activity in large firms.     

Technology variation vs. R&D uncertainty: What matters most for energy patent success?

R&D is an uncertain activity with highly skewed outcomes. Nonetheless, most recent empirical studies and modeling estimates of the potential of technological change focus on the average returns to research and development (R&D) for a composite technology and contain little or no information about the distribution of returns to R&D – which could be important for capturing the range of costs associated with climate change mitigation policies – by individual technologies. Through an empirical study of patent citation data, this paper adds to the literature on the outcomes of energy R&D by focusing on the behavior of the most successful innovations for six energy technologies, allowing us to determine whether uncertainty or differences in technologies matter most for success. We highlight two key results. First, we compare the results from an aggregate analysis of six energy technologies to technology-by-technology results. Our results show that existing work that assumes diminishing returns but assumes one generic technology is too simplistic and misses important differences between more successful and less successful technologies. Second, we use quantile regression techniques to learn more about patents that have a high positive error term in our regressions – that is, patents that receive many more citations than predicted based on observable characteristics. We find that differences across technologies, rather than differences across quantiles within technologies, are more important. The value of successful technologies persists longer than those of less successful technologies, providing evidence that success is the culmination of several advances building upon one another, rather than resulting from one single breakthrough. Diminishing returns to research activities appear most problematic during rapid increases of research investment, such as experienced by solar energy in the 1970s.     

Technology variation vs. R&D uncertainty: What matters most for energy patent success?

R&D is an uncertain activity with highly skewed outcomes. Nonetheless, most recent empirical studies and modeling estimates of the potential of technological change focus on the average returns to research and development (R&D) for a composite technology and contain little or no information about the distribution of returns to R&D – which could be important for capturing the range of costs associated with climate change mitigation policies – by individual technologies. Through an empirical study of patent citation data, this paper adds to the literature on the outcomes of energy R&D by focusing on the behavior of the most successful innovations for six energy technologies, allowing us to determine whether uncertainty or differences in technologies matter most for success. We highlight two key results. First, we compare the results from an aggregate analysis of six energy technologies to technology-by-technology results. Our results show that existing work that assumes diminishing returns but assumes one generic technology is too simplistic and misses important differences between more successful and less successful technologies. Second, we use quantile regression techniques to learn more about patents that have a high positive error term in our regressions – that is, patents that receive many more citations than predicted based on observable characteristics. We find that differences across technologies, rather than differences across quantiles within technologies, are more important. The value of successful technologies persists longer than those of less successful technologies, providing evidence that success is the culmination of several advances building upon one another, rather than resulting from one single breakthrough. Diminishing returns to research activities appear most problematic during rapid increases of research investment, such as experienced by solar energy in the 1970s.     

An investigation over inbound open innovation in SMEs: insights from an Italian manufacturing sample

ABSTRACT

Building on the Open Innovation (OI) framework, the purpose of this paper is to examine the R&D inbound model of small and medium enterprises (SMEs). Specifically, we focus on the impact of different horizontal R&D collaborations on product innovation and innovation performance. Hypotheses are tested using a Probit/Tobit regression on an Italian sample of 2591 manufacturing SMEs. Our analysis shows that collaborating with different horizontal R&D partners brings to different innovation outcomes. In particular, R&D collaboration with universities has a positive impact on product innovation, but not on innovation performance. Whereas, R&D collaboration with research centres and other private companies has a positive impact on both product innovation and innovation performance. Our findings provide implications for SMEs managers and entrepreneurs who have to decide between R&D partners for their innovation strategy. Avenues for future research are discussed.     

R&D intensity,firm performance and the identification of the threshold: fresh evidence from the panel threshold regression model

This article tests whether there is an optimal level of research and development (R&D) intensity at which point a firm is able to maximize its performance. An advanced panel threshold regression model is employed to investigate the panel threshold effect of R&D intensity on firm performance among publicly traded Taiwan information technology and electronic firms. The results confirm that a single-threshold effect does exist and show an inverted-U correlation between R&D intensity and firm performance. This article demonstrates that it is possible to identify the definitive level beyond which a further increase in R&D expenditure does not yield proportional rewards. Some important policy implications emerge from the findings.     

Research & development and growth: A Bayesian model averaging analysis

We examine the effect of research and development (R&D) on long-term economic growth using the Bayesian model averaging (BMA) to deal rigorously with model uncertainty. Previous empirical studies, which applied BMA, investigated the effect of dozens of regressors on long-term growth, but they did not examine the effect of R&D due to data unavailability. We extend these studies by proposing to capture the investment in R&D by the number of Nobel prizes in science. Using our indicator, the estimates show that R&D exerts a positive effect on long-term growth. This result is robust to many different parameter and model prior structures as well as to alternative definitions of R&D indicator.     

Do R&D expenditures matter more than those of marketing to company performance? The moderating role of industry characteristics and investment density

Confronting competitive environment, enterprises differentiate their product by promoting their R&D or marketing capacities. Scholars have verified that there is a direct relationship and a deferred effect between R&D expenditures and firm performance, but that there exists an inconsistency between marketing expenditures and firm performance. However, previous studies have neglected to analyse and compare the impact of corporate R&D and marketing investment on performance, and also ignored the moderating effects of different industry characteristics and investment densities. The study attempts to fill the gap by constructing a model to accommodate all these factors. The empirical results indicate that R&D and marketing expenditures have a positive impact on enterprise operating performance, and that there is a longer deferred effect in R&D expenditures than in marketing expenditures. By investing in R&D expenditures, manufacturing enterprises can increase their performance more than in service enterprises, and electronic enterprises can improve their performance compared with other types of firms. Finally, investments with higher R&D density can result in a higher performance.     

Productivity in China's high technology industry: Regional heterogeneity and R&D

This paper analyzes the impact of Research and Development (R&D) on the productivity of China's high technology industry. In order to capture important differences in the effect of R&D on output that arise from geographic and socioeconomic differences across three major regions in China, we use a novel semiparametric approach that allows us to model heterogeneities across provinces and time. Using a unique provincial level panel dataset spanning the period 2000–2007, we find that the impact of R&D on output varies substantially in terms of magnitude and significance across different regions. Results show that the eastern region benefits the most from R&D investments, however it benefits the least from technical progress, while the western region benefits the least from R&D investments, but enjoys the highest benefits from technical progress. The central region benefits from R&D investments more than the western region and benefits from technical progress more than the eastern region. Our results suggest that R&D investments would significantly increase output in both the eastern and central regions, however technical progress in the central region may further compound the effects of R&D on output within the region.     

Managerial compensation and R&D investments: the role of the external managerial labour market

This paper investigates the importance of the external managerial labour market in the determination of managerial compensation and in the influence of the compensation incentives on a firm’s R&D investments. I design an empirical model including the compensation adjustment regression, of which the focus is the role of the external labour market, and the R&D regression that examines how the compensation incentives derived from the external labour market affect a firm’s R&D intensity. Empirical results suggest that the R&D intensity is positively related to the premium of the actual pay adjustments over the expected pay adjustments based on the external labour market comparisons. The effect of the compensation incentives on the R&D investments is strongest when managers expect pay to decrease but actually experience an increase in pay.     

Industry R&D intensity distributions: regularities and underlying determinants

This paper aims to examine the nature of the distributions of firm R&D intensities within industries and explore the factors that underlie the industry R&D intensity distributions. In particular, following the seminal study by Cohen and Klepper (1992) and using some new and rich data on firm R&D intensities for seven industries across six countries, this study examines the regularities in the industry R&D intensity distributions and demonstrates, based on a simple model of firm R&D, that the industry R&D intensity distributions are governed by the distributions of technological competence, a measure of firm R&D productivity, which corresponds to the notion of the “unobserved R&D-related capabilities” suggested by Cohen and Klepper (1992). This study found that firm R&D intensities within industries are lognormally distributed, displaying a strikingly regular pattern across industries, that the industry distributions of the levels of technological competence are also lognormal, and that, based on the formal model of firm R&D and the notion of the unobserved R&D-related capabilities, the distribution of firm technological competence within an industry underlies the industry's firm R&D intensity distribution.     

Business type,industry value chain,and R&D performance: Evidence from high-tech firms in an emerging market

This study focuses on how the business type and technological learning mode, which a high-tech firm chooses based on its core competence, influence the firm's R&D strategies, which in turn affect firm performance. This study also explores how the interaction between a firm's business type and industry value chain stage affects the relationship between R&D investments and operating performance. We suggest that the linkage of R&D investments and operating performance will increase gradually, when firms move from contract manufacturing to own brand business. R&D investments can contribute more to performance when firms adopt the hybrid business type. Furthermore, R&D investments generate more significant benefits for the own brand companies than the contract manufacturers at the same stage of the industry value chain. R&D investments of the downstream contract manufacturers have a negative impact on firm performance. Regardless of business type, firms in the upstream (midstream) stage of the industry value chain outperform downstream stage firms in deriving benefits from R&D activities. Finally, the lagged effects of R&D investments on operating performance are affected by the interaction between business type and industry value chain.     

Measuring universities’ R&D performance in China’s provinces: a multistage efficiency and effectiveness perspective

ABSTRACT

Evaluating universities’ R&D performance can serve as a tool for policymakers, enabling them to identify the best R&D practitioners for benchmarking and develop strategies for enhancing performance by highlighting areas of weakness. This study divides universities’ R&D performance into two dimensions: efficiency and effectiveness. We employ a network data envelopment analysis approach to measure universities’ R&D efficiency, and separately use a multi-index comprehensive evaluation method to assess their R&D effectiveness from a multistage perspective. We calculate the comprehensive R&D performance of universities in 30 provinces in China from 2004 to 2014. An analysis of temporal variation reveals that universities’ R&D performance in some provinces improved rapidly, increasing gaps in performance as a whole. The spatial pattern for the 30 provinces shows that universities in provinces with medium or strong R&D performance are mainly in coastal provinces and central areas in China. Finally, universities’ R&D activities are considered ‘efficient and effective’ only in a small number of provinces, while in most provinces, these activities can generally be considered ‘less efficient and effective.’ Hence, universities in provinces with different R&D performance modes should implement targeted improvement strategies according to their characteristics.     

Exploring the effect of diversification strategy on R&D intensity using quantile regression: evidence from France

This study examines the relationship between firm diversification strategy and R&D intensity for a sample of large French companies between 2008 and 2012. Applying quantile regression, we provide evidence that the choice of diversification affects R&D intensity in a differentiated way. The results indicate that a low level of diversification (below the twentieth quantile) has no significant impact on R&D intensity. Conversely, a moderate or high level of diversification has a negative and significant impact on R&D intensity. These findings suggest that R&D intensity seems to be significantly higher in related-business firms than in unrelated-business firms.     

The impact of corporate debt on long term investment and firm performance

Prior research indicates a linkage between debt, research and development (R&D) and physical investment, and that the relationship varies depending on the type of firm (science versus non–science). Leverage also plays a multidimensional role in corporate performance and growth. The relationship between financial leverage and R&D expenditure is analysed using a sample of large United States (US) manufacturing firms. Then, the impact of leverage on R&D expenditure is studied using corporate performance drivers as intermediate variables. The results indicate that there is a strong negative relationship between the degree of financial leverage and the level of R&D expenditure that firms undertake. The negative relationship is robust to changes in model specifications and sample periods. More importantly, the results show that it is higher leverage that leads to lower R&D expense rather than R&D causing variations in future leverage. In addition, the results indicate that higher leverage adversely influences future investment in R&D which may in turn lead to negative impact on long term operating performance and future growth opportunities.     

Vertical R&D Spillovers,Cooperation, Market Structure,and Innovation

This paper studies vertical R&D spillovers between upstream and downstream firms. The model incorporates two vertically related industries, with horizontal spillovers within each industry and vertical spillovers between the two industries. Four types of R&D cooperation are studied: no cooperation, horizontal cooperation, vertical cooperation, and simultaneous horizontal and vertical cooperation. Vertical spillovers always increase R&D and welfare, while horizontal spillovers may increase or decrease them. The comparison of cooperative settings in terms of R&D shows that no setting uniformly dominates the others. Which type of cooperation yields more R&D depends on horizontal and vertical spillovers, and market structure. The ranking of cooperative structures hinges on the signs and magnitudes of three "competitive externalities" (vertical, horizontal, and diagonal) which capture the effect of the R&D of a firm on the profits of other firms. One of the basic results of the strategic investment literature is that cooperation between competitors decreases R&D when horizontal spillovers are low; the model shows that this result does not necessarily hold when vertical spillovers are sufficiently high, and/or when horizontal cooperation is combined with vertical cooperation.     

R&D strategy and innovation performance: the role of standardization

Firms now increasingly recognise the important role of R&D strategy in building technological advantage. However, few attempts have linked standardisation with specific R&D strategies in explaining innovation performance. To bridge this gap, this study empirically examines the relationships between R&D strategies, standardisation, and firms’ innovation performance. Based on a sample of 371 firms in China, we use structural equation modelling (SEM) and find that novelty-oriented R&D strategy generates greater accumulation of standardisation knowledge and standards diversity, while R&D openness only positively relates to this standardisation knowledge accumulation. Moreover, standardisation knowledge accumulation is positively related to both administrative and technical innovation performance, while a greater variety of standards only leads to higher administrative innovativeness. More importantly, our results reveal that accumulation of standardisation knowledge mediates the relationships between R&D novelty and administrative and technical innovation performances. Both the theoretical and practical implications that arise from these findings are discussed.     

A simple theory and evidence on the determinants of firm R&D

This paper derives a simple, but informative, model of firm R&D to figure out key factors that determine firm R&D effort. The model suggests a demand-pull, technology-push theory of R&D by showing that a firm's profit-maximizing R&D expenditure is determined jointly by both demand-side factors and technology-side factors. The former includes demand size (firm sales) and consumer preference over quality and price and the latter includes R&D cost structure or the production-cost effect of product R&D and firm-specific technological competence. In addition, the model shows that other things being equal, the stock of exogenous technological knowledge, including the firm's previously accumulated technological knowledge, relevant to current R&D which is negatively related with current R&D effort. An empirical analysis of firm R&D intensities and technological capabilities of more than 1600 firms in nine industries across six countries provides supportive evidence for the theory. Further, the theory implies that R&D intensity or the R&D-to-sales ratio is independent of firm size unless firm size affects technological competence and that given consumer preference and R&D cost structure facing all firms in the same industry, the distribution of firm-specific technological competence among firms determines the distribution of firm R&D intensities within the industry.     

The effect of outward investment to China on domestic R&D: a two-hurdle model with endogenous ODI

Outward direct investment (ODI) and domestic R&D are interrelated, but empirical evidence is affected by the nature of a firm's data, which are heavily censored. Firm data contain a firm's yes/no decision to invest in China, yes/no decision of R&D, and the decision of R&D intensity. We thus adopt a two-hurdle model and allow the China investment decision to be endogenous in an R&D model in order to examine the effect of ODI in China on domestic R&D investment in Taiwan's electronics industry. In the model, a two-equation simultaneous subsystem is formed, in which three regression equations are specified: a decision of R&D intensity, and a yes/no decision of location to conduct R&D together with a yes/no decision to invest in China Our results indicate that China investment and R&D intensity are positively related such that ODI in China helps to raise significantly a firm's R&D intensity as compared to the estimate if the endogeneity of China investment and the nature of data were not properly accounted.     

Composition of R&D expenditures and firm performance

ABSTRACT

The explosion of research and development (R&D) expenditures in China brings a puzzling fact that the proportion of research in R&D is extremely small, and thus the proportion of development is large. This article distinguishes research from development in R&D and investigates the heterogeneous effects of the two components on the performance of Chinese listed firms. Using a generalized propensity score matching approach with continuous treatments, we present non-linear relationships between R&D composition and firm performance. While development-oriented firms benefit more from an increase in profit than a growth in productivity, orientation toward research contributes more to productivity gains than to profitability. Research and development activities are found to be complementary in promoting firm performance. The results suggest the existence of optimal proportions of the components of R&D for maximizing firm performance.