A comparative analysis of the change in R&D efficiency: a case of R&D leaders in the technology industry

This paper measures the cumulative change in research and development (R&D) efficiency of globally leading R&D companies in the technology industry. We use Data Envelopment Analysis /Malmquist index to analyse 49 such companies. The change in R&D efficiency is analysed by decomposing the Malmquist index into ‘catch-up’ and ‘frontier shift’ indices, and by comparing cumulative indices to those at the starting period. Those cumulative indices are obtained at both a firm and an industry level. Results indicate that the overall R&D efficiency of these globally leading R&D companies declined slightly during the period 2007–2013. At a firm level, this study determines in detail how the trend of each firm in R&D activities differs from other companies.     

Economic policy uncertainty,CEO characteristics and firm R&D expenditure: a Bayesian analysis

ABSTRACT

This paper applies a linear Bayesian regression model to study the effects of economic policy uncertainty (EPU) and Chief Executive Officer (CEO) characteristics on firm Research and Development (R&D) expenditure. We specifically analysed data from 1,163 Chinese companies listed as A-shares from 2008–2016. EPU is believed to curtail firm investments as it causes unexpected market conditions. Yet, our findings obtained with Bayesian analysis show a positive relationship between EPU and firm R&D expenditure. Specifically, we found that some CEO attributes (e.g., age, tenure and marketing/sales experience) led to a negative relationship between EPU and firm R&D expenditure, whereas other attributes (e.g., education, overseas study/work experience, product R&D experience, and process engineering experience) lead to a positive relationship. Our findings provide nuanced insights into how different CEO characteristics influence firms’ R&D expenditure in a context of uncertainty.     

Assessing the influence of differentiation strategy and R&D subsidies on R&D cooperation

This paper explores the R&D cooperation determinants of the innovative companies belonging to the Spanish manufacturing sector. Our findings suggest that the variable R&D subsidy is endogenous, significant, and has a strong positive influence on R&D cooperation. This is a clear indication that the achievement of public aid is often conditioned by the obligation for companies to cooperate in R&D. We have also found that the differentiation strategy variable is significant and has a negative influence on R&D cooperation. Companies positioned in a differentiation strategy probably own and use some different knowledge from other companies. Consequently, they will not have much interest in taking advantage of the spillovers generated by other companies. It is therefore logical that they are reluctant to establish cooperation agreements on R&D. Therefore, companies positioned in the differentiation strategy need public policies to support R&D that are not conditioned to the establishment of cooperation agreements.     

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.     

Innovation and productivity in the food vs. the high-tech manufacturing sector

ABSTRACT

The food sector is considered a mature industry characterized by low research and development (R&D) intensity. Nevertheless, food companies face numerous challenges and cannot do without innovation activity if they want to keep their competitiveness. In this study, we examine the impact of innovation on labor productivity in European food companies and compare it to results for firms operating in high-tech sectors. The central motivation of our study is that the low R&D intensity observed in the food sector should be mirrored in different productivity effects of innovation when compared to the high-tech sector. We use microdata from the European Union's ‘Community Innovation Survey’ (CIS) and apply an endogeneity-robust multi-stage model that has been applied by various recent studies. Our results point out major differences between the examined subsectors. While we find strong positive effects of innovation on labor productivity for food firms, we find insignificant effects in the high-tech sector. This might suggest that the returns to innovation might be best evaluated separately by sector rather than for the manufacturing sector as a whole.     

Revisiting measure of R&D spillovers: empirical evidence on OECD countries and industries

Using data for 17 Organisation for Economic Co-operation and Development (OECD) countries over 29 years for 28 industries, this paper estimates industry-wise research and development (R&D) spillovers from the largest R&D investors and the most R&D-intensive industries that contribute 80% of global R&D. In doing so, it tests several assumptions made in the literature, and data rejecting them, proposes a methodology on R&D return estimation devoid of these assumptions. Results show that R&D has substantial spillovers, justifying R&D support policy. Each dollar of R&D generates about 29 cents in spillovers domestically and 4 cents in foreign countries. However, both intra- and inter-industry spillovers vary by industries, implying that the policy of supporting each R&D dollar uniformly across industries is suboptimal. Contrary to industry heterogeneity, the R&D spillovers from an industry do not vary substantially across countries, suggesting that optimal R&D policy across OECD countries might be uniform. An industry-by-industry technology matrix shows that sometimes an idea generates a greater impact on other industries than where it is generated.     

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.     

Does market competition promote innovation efficiency in China’s high-tech industries?

ABSTRACT

Despite extensive discussion about the relationship between market competition and innovation performance, the impact of market competition on the innovation efficiency of high-technology industries in a transitional economy is still unclear. The article is based on panel data of 17 subsectors of China’s high-tech industry spanning the 2001–2016 period. Using stochastic the frontier analysis model, we empirically test the impact of market competition on two-stage innovation efficiency from the perspective of the industry. The results indicate that market competition and firm scale have positive and significant effects on the efficiency of two-stage innovation, the effects of industry export intensity and government intervention on R&D efficiency are negative, but the effects are different for the efficiency of the commercialisation of technology. Based on the results of the empirical analysis, this paper compares the trends and the differences between R&D efficiency and commercialisation efficiency, and then uses cluster analysis to reclassify China’s high-tech industries into three categories, thus revealing the disconnect and imbalance within China’s high-tech industries. At the end of the article, we present some possible policy recommendations.     

R&D and productivity: evidence from large UK establishments with substantial R&D activities

ABSTRACT

We use Office for National Statistics' micro data for large UK establishments in the production industries in the period 1997–2008 to study the relationship between their productivity and the presence of substantial R&D activities, either at the production unit itself, or at other UK reporting units owned by the same enterprise group. We estimate that total factor (revenue) productivity is on average about 14% higher at the establishments which have substantial R&D themselves, compared to those with no R&D. Among the establishments with no R&D themselves, we estimate that productivity is on average about 9% higher at those which belong to enterprise groups which do have substantial R&D elsewhere in the UK in the same sub-sector. For the establishments with substantial R&D themselves, we also estimate a significant positive relationship between current productivity and past R&D expenditure using dynamic specifications which allow for both establishment-specific ‘fixed effects’ and a serially correlated error component.     

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.     

Identifying R&D partners through Subject-Action-Object semantic analysis in a problem & solution pattern

Today’s companies still rely heavily on expert knowledge rather than quantitative data with a systematic approach to effectively identify and choose Research and Development (R&D) partners. It is advantageous to identify and select potential R&D partners using a Problem & Solution (P&S) pattern. This paper presents a novel process for identifying R&D partners on the basis of solution similarities that assist technology managers in understanding the relationships between research targets. First, we choose a thematic dataset that contains problems and quantitative data with relative topic terms. Then, we extract Subject-Action-Object semantic structures in a P&S pattern from the dataset, and identify various solutions to a technical problem, with each as a subject. In addition, we provide correlation mapping to visualise the text characters and identify R&D partners. Finally, we validate the proposed method through a case study of the dye-sensitized solar cells sector.     

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.     

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.     

Assessing measurement errors in the CDM research–innovation–productivity relationships

ABSTRACT

The Crépon-Duguet-Mairesse 1998 article, known as CDM, initiated a structural econometric framework to analyze the relationships among research, innovation and productivity, which has been estimated most generally on the basis of cross-sectional innovation survey-type data. Some econometric implementations of the CDM approach have suggested that such data give useful but imprecise measures of the innovation output (share of innovative sales), and to a lesser degree of the innovation input (R&D). These ‘measurement errors’ may result in attenuation biases of the estimated R&D and innovation impact elasticities in the two basic CDM ‘roots’ relations of R&D to innovation and innovation to productivity, as well as in the extended production function à la Griliches linking directly R&D to productivity. Using a panel of three waves of the French Community Innovation Survey (CIS), we assess these biases and the magnitude of the underlying measurement errors, assuming mainly that they are ‘white noise’ errors. We do so by comparing two pairs of usual panel estimators (Total and Between) in both the cross-sectional and time dimensions of the data (Levels and Differences). We find large measurement errors on innovation output in the innovation–productivity equation, resulting in large attenuation biases in the related elasticity parameter. We also find smaller but sizeable measurement errors on R&D, with significant attenuation biases in the corresponding elasticity estimates, in the R&D–innovation equation and the extended production function. Simulations suggest that the measurement errors on innovation and R&D are unaffected by similar measurement errors on the capital variable.     

世界油气工业空间结构模式初探

从世界油气资源的空间结构入手，根据其与社会经济空间结构的耦合关系，提出世界油气工业三大空间结构模式，即协同发展(就近供应)模式、通道发展模式和点轴发展模式，以期能为我国油气工业的发展提供有益的思路和借鉴。     

How do housing cycles influence listed firms’ R&D investment: evidence from the collateral channel

ABSTRACT

Firm innovation is essential to long-run economic growth. Financially constrained R&D firms may use firm-owned properties as collateral to finance their R&D projects. Therefore, the housing price cycle can affect firms’ R&D investment through influencing their real estate value. By examining listed R&D firms during the housing boom period 2002–2006 in the U.S., we find that a $1 increase in real estate value leads a firm to increase its R&D investment by $0.38. We also find that this collateral effect is more pronounced among financially constrained R&D firms than that among unconstrained ones. Additionally, we examine the housing bust period 2008–2012, and find that real estate depreciation retarded R&D investment, especially among constrained R&D firms.     

In-house R&D,external R&D and cooperation breadth in Spanish manufacturing firms: is there a synergistic effect on innovation outputs?

ABSTRACT

This study explores the nature of relationship between in-house R&D, external R&D and cooperation breadth and their joint impact on patent counts as well as technological, product and process, innovations in Spanish manufacturing firms. With regards to patent counts, empirical findings from a Generalized Method of Moments (GMM) estimator suggest a complementarity effect of internal and external R&D activities conditional on the breadth of R&D cooperation. Concerning technological innovation, results from dynamic random-effects probit models indicate no synergistic effects. In addition, we find evidence of persistence of all three innovation output measures. Our results suggest policy implications in relation to strengthening firms’ absorptive capacity that could have long-run effects.     

The interplay between target firm R&D,acquirer debt financing and takeover premia

The level of acquisition premia is of paramount importance in light of the vast sums paid to target shareholders and the often disappointing returns realized by corporate buyers. In this letter, we focus on the impact of R&D investments by targets on the acquisition premium contingent upon the acquirer’s financing choices. Based on a unique hand-collected sample of 407 listed European transactions, we find a positive effect of target R&D on premia paid. Yet, when acquirers finance the acquisition of an R&D intensive target with debt, the positive relation disappears. Consequently, we establish that financing sources affect bidding strategies of acquiring companies in case of difficult-to-value targets.     

Patents and R&D expenditure effects on equity returns in pharmaceutical industry

As costs of pharmaceutical R&D soar and productivity falls, the role of research pipelines in firm valuations is changing. To date, surprisingly little work has been published on the effects of R&D pipeline performance on equity returns, while controlling for coincident factors, such as legacy patents and presence of blockbuster drugs in production. Using 1996–2013 data for nine largest pharmaceutical companies in the world, this article assesses the role of the above factors on returns to pharmaceutical companies equity. We show significant positive link between changes in the number of blockbusters on patent six months prior and returns in excess of pharmaceutical equity index. The number of patents granted by United States Patent and Trademark Office in a quarter is also a significant factor. On the other hand, we find that increases in R&D expenditure in large-cap pharmaceutical companies are viewed negatively by investors in the short term.     

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.