Knowledge spillovers and R&D subsidies to new,emerging technologies

Is knowledge spillover a rationale for supporting R&D on new, emerging technologies more than R&D on other technologies? In this paper, I analyze whether innovation externalities caused only by knowledge spillovers differ between technologies of different maturity. I show that R&D should not be subsidized equally across industries when the knowledge stocks differ. This is because knowledge spillovers depend on the size of the knowledge stock and the elasticity of scale in R&D production. R&D in the emerging technology should be subsidized more when the elasticity is smaller than one. However, R&D in the mature technology should be subsidized more when the elasticity is larger than one.     

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.     

Determinants of R&D in knowledge-intensive business services firms

Research and development (R&D) is a key factor enabling firms to gather information, create knowledge and innovate. Although often seen as the preserve of goods-producing sectors, knowledge-intensive business services (KIBS) in particular also engage in R&D. In this paper, we are interested in understanding the determinants of R&D in KIBS. We address this question by exploring factors connected to R&D in KIBS, with attention to whether it is connected with internal capabilities or to establishments' openness. We show that KIBS' R&D is associated with internal capabilities, and that recourse to external R&D is part of a strategy of openness that complements internal capacity. We also suggest that KIBS's own view of R&D is aligned with R&D in the goods-producing sector, leading establishments in non-technological KIBS sectors to under-report R&D.     

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.     

R&D competition, absorptive capacity, and market shares

This paper deals with an oligopolistic industry where firms are engaged in cost-reducting R&D activity to maximize their market shares. The existence and uniqueness of a feedback-Nash-optimal R&D strategy for each firm are discussed. Our simulations highlight that variations in spillovers hardly influence the firms' R&D investment, if their absorptive capacities to exploit extramural knowledge depend on their R&D efforts. Moreover, extramural knowledge cannot completely replace in-house R&D. However, a high level of public R&D favors the firm with the most restrictive R&D expenditure constraint and/or with the lowest initial R&D stock, provided it invests in R&D.     

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.     

R&D and foreign direct investment with asymmetric spillovers

This paper analyzes how firms’ R&D investment decisions are affected by asymmetries in knowledge transmission, considering different sources of asymmetry such as unequal know-how management capabilities and spillovers localization within an international oligopoly. We show that a better ability to manage knowledge flows incentivizes the firm to invest more in R&D. By introducing geographically bounded spillovers, we also find that one-way foreign direct investment (FDI) stimulates the multinational enterprise to raise its own R&D and that an FDI equilibrium is more likely to occur. Finally, spillovers localization leading to two-way FDI is welfare improving when compared with non-localized spillovers.     

On `indirect' trade-related R&D spillovers

An influential literature argues that trade promotes knowledge flows and technology transmission between trading partners. This literature focuses on `direct' research and development (R&D) spillovers which are related to the levels of R&D produced by the trading partners. In this paper, we argue that `indirect' trade-related R&D spillovers also take place between countries, even if they do not trade with each other. These `indirect' spillovers are associated with available rather than with produced levels of R&D. Our empirical results suggest that these `indirect' trade-related spillovers are at least as important as the `direct' ones, and strengthen the view that trade does matter for the international transmission of R&D. They also suggest that, due to the existence of these `indirect' effects, bilateral trade patterns are relatively less important determinants of the level of foreign R&D spillovers acquired through trade.     

Quantifying knowledge exchange in R&D networks: a data-driven model

We propose a model that reflects two important processes in R&D activities of firms, the formation of R&D alliances and the exchange of knowledge as a result of these collaborations. In a data-driven approach, we analyze two large-scale data sets, extracting unique information about 7500 R&D alliances and 5200 patent portfolios of firms. These data are used to calibrate the model parameters for network formation and knowledge exchange. We obtain probabilities for incumbent and newcomer firms to link to other incumbents or newcomers able to reproduce the topology of the empirical R&D network. The position of firms in a knowledge space is obtained from their patents using two different classification schemes, IPC in eight dimensions and ISI-OST-INPI in 35 dimensions. Our dynamics of knowledge exchange assumes that collaborating firms approach each other in knowledge space at a rate μ for an alliance duration τ. Both parameters are obtained in two different ways, by comparing knowledge distances from simulations and empirics and by analyzing the collaboration efficiency \(\mathcal {\hat {C}}_{n}\). This is a new measure that takes in account the effort of firms to maintain concurrent alliances, and is evaluated via extensive computer simulations. We find that R&D alliances have a duration of around two years and that the subsequent knowledge exchange occurs at a very low rate. Hence, a firm’s position in the knowledge space is rather a determinant than a consequence of its R&D alliances. From our data-driven approach we also find model configurations that can be both realistic and optimized with respect to the collaboration efficiency \(\mathcal {\hat {C}}_{n}\). Effective policies, as suggested by our model, would incentivize shorter R&D alliances and higher knowledge exchange rates.     

Strategic timing in R&D agreements

We study the endogenous formation of R&D agreements in a R&D/Cournot duopoly model with spillovers where also the timing of R&D investments is endogenous. This allows us to consider the incentives for firms to sign R&D agreements over time. It is shown that, when both R&D spillovers and investment costs are sufficiently low, firms may find difficult to maintain a stable agreement due to the strong incentive to invest noncooperatively as leaders. In this case, the stability of an agreement requires that the joint investment occurs at the initial stage, thus avoiding any delay. When spillovers are sufficiently high, the coordination of R&D efforts becomes a profitable option, although firms may also have an incentive to sequence noncooperatively their investment over time. Finally, when spillovers are asymmetric and knowledge mainly leaks from the leader to the follower, investing as follower may become extremely profitable, making R&D agreements hard to sustain unless firms strategically delay their joint investment in R&D.     

Public Technology Infrastructure,R&D Sourcing,and Research Joint Ventures

In this paper, we define public technology infrastructure to mean public resources that bring new R&D into existence. Examples are public research that yields knowledge spillovers and government contracts that broker new research. Using this definition we explore the effect of public infrastructure on cooperative R&D, especially R&D sourcing and research joint ventures (RJVs). Our findings strongly suggest that public infrastructure promotes cooperative R&D. We begin by studying the role of federal laboratories in R&D sourcing by private laboratories, finding that sourcing increases as a result. Then we examine patents arising from RJVs sponsored by the Advanced Technology Program (ATP). We find that R&D subsidies as well as difficulty and novelty increase patents produced by the RJVs. Contractual oversight by ATP has no direct effect but an indirect effect appears to exist, since firms value ATP oversight more highly for more difficult and novel projects, and these produce more patents.     

Synergizing independent and cooperative R&D activities: the effects of organisational slack and absorptive capacity

Firms undertaking independent and cooperative research and development (R&D) activities simultaneously often have difficulties to realise their synergistic effects. This study contends that such difficulties are caused by tensions between two types of R&D activities in terms of resource competition and knowledge leakage. Moreover, organisational slack and absorptive capacity may affect these tensions and thereby play important role in synergizing independent and cooperative R&D activities. Based on a survey data of 286 firms, this study finds that such two types of R&D activities jointly have a negative impact on firm performance. Furthermore, organisational slack aids in synergizing them, while absorptive capacity has an adverse impact. These findings enrich our knowledge on the interrelation of independent and cooperative R&D activities and shed light on how firms can synergize them.     

Asymmetric firms,technology sharing and R&D investment

We use a combination of theory and experiment to study the incentives for firms to share knowledge when they engage in research and development (R&D) in an uncertain environment. We consider both symmetric and asymmetric starting points with regards to the amount of initial knowledge firms have before conducting R&D and look at how differences in starting positions affect the willingness of firms to share knowledge. We investigate when and if firms find R&D cooperation beneficial and how investment in R&D is affected by the outcome of the sharing decisions. The experimental evidence shows that overall subjects tend to behave consistently with theoretical predictions for the sharing of knowledge, although leaders who are not compensated by a side payment from laggards are more willing to share than predicted by the theory, and leaders who are compensated are less willing. The data on investment suggests less investment with sharing than without, consistent with theory. Compared to exact numerical predictions, there is overinvestment or underinvestment except for symmetric firms under no sharing. All cases of overinvestment and underinvestment, regardless of sharing or not and regardless of starting positions, are well explained by smoothed-out best (quantal) responses.     

Detecting which firm-specific characteristics impact market-oriented R&D

This paper investigates which firm-specific characteristics lead multinational enterprises (MNEs) to increase their R&D expenditure in host countries as a way of expanding their business into local markets (market-oriented R&D). The literature that addresses this topic is quite limited because of the difficulty of separating market-oriented R&D expenditure from knowledge-sourcing R&D expenditure in the data. We argue that determining the relationship between local sales and R&D expenditure is a better way to identify whether MNEs are investing market-oriented R&D than is separating the two types of R&D. For connecting firm-specific characteristics, local-market sales, and R&D expenditure together, we adapt two-stage regressions. By employing data from Taiwanese multinationals from 2003 to 2006, we found that if an MNE moves its technology toward capital-intensive products, it increases its R&D expenditure to promote its sales in the local markets in the host country.     

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.     

Human resource management for learning through knowledge exploitation and knowledge exploration: Pharmaceuticals in Mexico

This paper investigates the influence of human resource management practices on the likelihood that a firm performs in-house R&D. R&D is broadly interpreted as learning—a mechanism promoting absorptive capacity and supporting technology capability-building. Firms can choose between two learning strategies: they can exploit existing knowledge, or perform more complex explorations and acquire new knowledge. Different knowledge requirements associate with distinct R&D outcomes with varying degrees of novelty for the firm. Findings are supported with evidence from the pharmaceutical industry in Mexico. The analysis reveals positive linkages between human resource management practices and learning at firm level. The relationship is contingent on factors such as expected R&D outcomes, or the novelty of the knowledge required by the firm. The provision of training revealed the more consistent, positive influence on the likelihood that pharmaceuticals firms perform R&D in Mexico.     

Origins of knowledge and innovation in R&D alliances: a contingency approach

Innovative performance is influenced both by the origins of the existing knowledge that is combined to generate innovation and by how economic actors search for new knowledge. Drawing on a sample of inter-firm dyadic R&D alliances, we found that whereas the integration of geographically distant knowledge and of organisationally proximate knowledge in R&D alliances are negatively related to the alliance innovative performance, search span positively moderates both relationships. We conclude that, in order to make the most of broad-span searching, firms participating in R&D alliances should integrate geographically distant but organisationally proximate knowledge. By doing so, firms take advantage of the diversity and novelty that characterises geographically distant knowledge, while preserving considerable levels of relative absorptive capacity that are needed for them to understand, internalise, and effectively use partners’ knowledge from different domains.     

International,intersectoral, or unobservable? Measuring R&D spillovers under weak and strong cross-sectional dependence

In the theoretical and empirical growth literature, private and social returns to R&D have been identified as the key drivers of productivity gains and economic development. However, recently the debate on the relative importance of private vis-à-vis social returns has been reinforced by contributions in two emerging fields of the applied econometric literature, namely spatial panel modeling and the common factor approach, which stress the role of cross-sectional dependence as a source for a potential estimation bias linked to the measurement of returns to R&D. In this paper, we account for these methodical advances when estimating sectoral knowledge production functions for OECD countries under weak and strong cross-sectional dependence. By doing so, we are able to uncover technology- and trade-related R&D spillover channels associated with social returns to R&D, while effectively controlling for other types of productivity spillovers and latent macroeconomic shocks. Our results highlight the role played by international-intersectoral R&D spillovers for the social rate of return to R&D, while we get limited evidence for private returns to R&D once cross-sectional dependence is properly accounted for.     

Profit-maximizing R&D in response to a random carbon tax

This paper determines a firm’s profit-maximizing R&D response to an uncertain carbon tax, for two different R&D programs: cost reduction of low carbon energy technologies and emissions reductions of currently economic technologies. We find that optimal R&D does not increase monotonically in a carbon tax. R&D into alternative technologies increases only if the firm is flexible enough; R&D into conventional technologies first increases then decreases in a carbon tax. Firms that are very flexible may increase R&D into alternative technologies when the uncertainty surrounding a carbon tax is increased; otherwise firms will generally decrease R&D investment in uncertainty.     

Tax policy endogeneity: evidence from R&D tax credits

This paper estimates the causal effect of research and development (R&D) tax incentives on R&D expenditures using new data on U.S. states. Identifying tax variation comes from changes in federal corporate tax laws that heterogeneously and, due to the simultaneity of state and federal corporate taxes, automatically affect state-level tax laws. Instrumental variables regressions indicate that a 1% increase in R&D tax incentives causes a statistically significant 2.8–3.8% increase in R&D. Alternatively, ordinary least squares (OLS) regressions of R&D expenditures on R&D tax incentives, which do not correct for the policy endogeneity of R&D tax incentives, indicate that a 1% increase in R&D tax incentives causes a statistically insignificant 0.4–0.7% increase in R&D. One possible explanation for these results is that tax policies are implemented before an economic downturn.