Nonlinear influence on R&D project performance

This study applies artificial neural network (ANN) to explore the relationships between the performance of R&D projects and its determinants. The results indicate that the quality of project environment has an inverse U-shaped effect on the performance of R&D projects, and both project managers' skills and the effectiveness of teamwork have monotonic positive influences on it. Besides, this study utilizes self-organizing map (SOM) to classify the Taiwanese information and electronics companies into three groups and further provides some suggestions. In addition, this paper uses an in-depth interview of qualitative research to explore why the quality of project environment has an inverse U-shaped effect on the R&D project performance, and finds out the main reason. There are two managerial implications in this study. First, the relationships between the performance of R&D projects and its determinants are not always linear in the complex and uncertain environment nowadays. Second, companies must care about the inverse U-shaped effect of the quality of project environment on the performance of R&D projects, although they can enhance the extent of project managers' skills and the effectiveness of their teamwork as much as possible.     

Joint R&D projects: Experiences in the context of European technology policy

Joint R&D projects have emerged as a significant model for the development of research and technological activities. Our study examines, through an exploratory analysis, the typology of joint R&D projects and the characteristics of R&D networks in which the projects are developed. In addition, the interrelation between the R&D projects in the context of European Technology Policy is analysed. Findings from survey data collected on joint R&D projects carried out in the context of European Framework Programmes indicate that three groups of R&D projects can be identified (invention, innovation and diffusion projects), and that each of these projects is managed inside the R&D network with a different degree of structuring and external opening. The analysis of interrelations between R&D projects also shows a low, non-linear and non-progressive interrelation. This conclusion is an important question to bear in mind in the design of scientific and technological policies.     

Boundary spanning leadership,resource mobilisation,and performance of university-industry R&D projects: a study in a Japanese university

Acquisition of university knowledge has grown significantly for firms to complement an internal knowledge base of technological innovation. Recognising the significance, an increasing body of literature has analysed the performance of university-industry R&D projects by adopting managerial and social approaches. Despite the important role played by project leaders, existing research paid scant attention to the critical ability and quality of successful project leaders in acquiring university knowledge. To address these limitations, this study performed a survey of firms that collaborated with the Ritsumeikan University in Japan and investigates the influence of boundary spanning leadership of project leaders in firms on both knowledge and commercial performance of R&D projects. Furthermore, it also evaluates the mediation effect of university resource mobilisation that links boundary spanning leadership and project performance.     

Types of cooperation partners as determinants of innovation failures

In this paper we analyse if specific R&D cooperation partners are related to an increase in the probability of innovation failures in terms discontinuing innovation projects. We distinguish between seven different R&D cooperation partner types, and we discriminate between product innovation failures and process innovation failures. Using German Community Innovation Survey data we find that, firstly, each type of R&D cooperation partner has a different effect on innovation failures. Secondly, we show that product innovation failures and process innovation failures are not affected in equal measure by the same type of R&D cooperation partner. Our results suggest that while R&D cooperation with public research institutes is significantly and negatively related to the probability to cancel a process innovation project, the coefficient is positive but insignificant for product innovation failures. Firms conducting partnerships with suppliers, however, run the risk of both product and process innovation failures. In turn, cooperation with competitors is positively correlated only to process innovation failures.     

Using scenarios for roadmapping: The case of clean production

Roadmapping and scenarios are two widely used futures techniques which help R&D managers set priorities for research. These techniques are combined in a Foresight exercise assessing development of clean production in metal manufacturing, drawing on the European CLEANPROD project. The aim of the project is to develop a set of roadmaps for metal processing R&D to achieve breakthrough sustainability — “clean production”.Scenarios, a frequently used Foresight method, are used to set the context for the exercise, inform the design of technology roadmaps and influence the wider policy context. Roadmaps are developed for three process areas of metal manufacture - surface preparation, machining and coating - on four levels including long run visions up to 2020, interim targets up to 2015, key R&D areas and specific project topics. Roadmaps are appraised in the light of alternative scenarios on the future of manufacturing. Promoting sustainability highlights gaps in a “business as usual” roadmap, suggesting a different portfolio of research projects. A revised overall scenario is used to shape public policy.R&D teams usually adopt one particular methodology to support resource allocation. However joint use of futures techniques helps if there is uncertainty over competing alternative technologies. Roadmapping often focuses on a single future. Scenario building as a Foresight technique introduces “multiple futures” thinking.     

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.     

On the economic performance of nascent entrepreneurs

This paper assesses the R&D performance of nascent and established technology-based small firms that receive a Phase II R&D award from the U.S. Small Business Innovation Research (SBIR) program. Our empirical analysis is based on a two-stage selection probit model, which is used to estimate the probability of commercialization conditional on the Phase II project having not failed. Our model predicts, and our analysis confirms, that nascent firms are more likely to fail in their SBIR-supported R&D endeavors. Further, we find that nascent firms that do not fail have a higher probability of commercializing their developed technology.     

Knowledge specialization and R&D collaboration

This paper contributes to the knowledge-based explanation of R&D networks. It argues that knowledge overlap and novelty are complementary inputs of a R&D alliance, in forms that depend upon the exploration breadth and depth of the R&D activity. The paper investigates how the hypothesis of specialization of the knowledge endowments can recover a number of characteristic empirical properties of a pattern of R&D collaboration in the economy. Implications for network evolution are discussed.     

Improving industrial R&D practices with social and ethical aspects: Aligning key performance indicators with social and ethical aspects in food technology R&D

Policy makers encourage integrating Social and Ethical Aspects (SEAs) in Research and Development (R&D) for the responsible development and deployment of future and emerging technologies, including Nanotechnology and Life Sciences. However, R&D project leaders in industry generally do not integrate SEAs explicitly in their daily practice. Furthermore, to what extent SEAs improve R&D remains unclear. We carried out a comparative research case study to assess to what extent R&D projects can be measurably improved through the integration of SEAs.We combined recent insights from Science and Technology Studies and Innovation Management to integrate SEAs in industrial R&D in the field of food technology and measured changes in project performance based on Key Performance Indicator (KPI) scores. We used Midstream Modulation with a group of project leaders and measured their projects' performance using a modified version of the Wageningen Innovation Assessment Toolkit.Results show that the integration of SEAs was not only perceived by participants to be functional and useful, but it also measurably improved KPI scores. We propose that the two methods can be integrated into a Success Factor based Live Innovation Project Scoring and Evaluation tool, which can be functionally deployed in R&D environments.     

Does partner type matter in R&D collaboration for product innovation?

Most firms tend to utilise various types of R&D collaboration partners simultaneously and partnerships between different types of partners show different properties. Thus, the effect of R&D collaboration may vary depending on partner types. This study considers four partner types: competitors, customers, suppliers and universities. It empirically examines the effect of R&D collaboration with each type of partner on product innovation, employing the Korean Innovation Survey data. Results show that R&D collaborations with customers and universities have a positive effect on product innovation, whereas R&D collaborations with suppliers and competitors have an inverted-U shape relationship with product innovation. This result can provide an explanation to the chaotic results of previous research and assist managers in selecting appropriate R&D partner.     

Research into ambidextrous R&D in product development – new product development at a precision device maker: a case study

Through research into new product development processes at a precision device maker, this paper discusses the skilful management of knowledge boundaries that lie between various organisations, and between specialised human skills and functions that make up a project organisation, and presents the ways in which new organisational capabilities are brought about for the development of new products as exploratory activities that dynamically merge and integrated the various knowledge within a company. This paper describes some of the implications derived from analysis and observations of the new organisational forms of the company's ambidextrous R&D management which the company uses to engage in both ‘uncertainty management (exploration)’ and ‘existing product management (exploitation)’, through the partnering of its existing formal organisations and dynamic structuring of diverse multifunctional teams formed as projects spanning different specialisations and capabilities.     

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.     

Environmental Policy with Endogenous Technology from a Game Theoretic Perspective: The Case of the US Pulp and Paper Industry

The merits of different types of regulatory tools in eliminating pollution and at the same time inducing innovation have long been an interest of researchers in both environmental economics and industrial organization. Although there is a substantial theoretical literature investigating the potential for various environmental policies to attain these dual goals, this is a challenging empirical problem because every industry has its own inherent characteristics that play an important role in determining the performance of different regulatory tools. The majority of the work to date focuses on pollution abatement while leaving pollution prevention understudied. In most of the literature firms are also assumed to be symmetric. Asymmetries among firms add another degree and level of complexity to their strategic interactions, and affect the performance of different regulatory tools. This paper investigates the performance of two alternative regulatory tools, an emissions performance standard and an emissions tax, in reducing pollution and inducing pollution prevention and abatement R&D in the US pulp and paper industry. We construct a model representing the industry in an asymmetric Cournot duopoly framework, calibrate the model to disaggregated industry data, and run scenarios to replicate the behavior of the firms in an imperfectly competitive output market. Our results suggest that pollution prevention R&D can respond quite differently than abatement R&D to different policy instruments. The results indicate that R&D spillovers among firms play crucial role in technology development and strategies of the firms. Our results also suggest that strategic interactions between firms in an imperfectly competitive industry can have significant impacts of the levels of both types of R&D.      

Effect of piracy on innovation in the presence of network externalities

This paper analyzes the impact of simultaneous increases in piracy (piracy effect) and network externalities (network effect) on R&D investment. A single firm's R&D investment increases (or decreases) if the network effect (or piracy effect) is dominant. With R&D competition, if the firms “significantly” differ with respect to their R&D efficiencies and if the piracy effect dominates the network effect then the less efficient firm's R&D investment increases and that of the more efficient firm's decreases. In this case, the overall probability of successful innovation increases. The reverse holds if the network effect dominates the piracy effect. If the firms are “less” asymmetric then their R&D investment either increases or decreases depending on the relative strengths of the piracy and network effects.     

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.     

Into thin air: using a quantile regression approach to explore the relationship between R&D and innovation

Applying quantile regression to 760 Finnish firms, we show that the relationship between R&D and firm performance is less straight forward than so far assumed. OLS regression analysis fails to capture the effect of R&D expenditure at different locations on the performance distribution. We reveal that R&D matters, especially on the medium quantiles, while regressing against the upper quantiles of the economic gains from innovation distribution exhibit decreasing returns scale in R&D. Our results confirm that Gaussian statistics fail to capture the most interesting part of the distribution – namely the extreme observations located in the tails.     

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.     

Stochastic innovation and product market organization

Summary This paper analyzes how different types of product market organization affect firms' R&D investments in a stochastic innovation framework. Product market competition determines payoffs to successful and unsuccessful firms. Restrictions on the research project success probability distribution are identified that yield an invariance result for expenditure per R&D project. The impact of the number of firms (n) on the amount of market R&D is shown to be sensitive to product market organization. For a major process innovation, firms undertake more R&D projects under Cournot product market competition than under Bertrand competition, forn sufficiently large. A numerical example is used to illustrate welfare tradeoffs.Tom Lyon, Herman Quirmbach, Ferenc Szidarovszky, Mark Walker and two anonymous referees gave us helpful comments and suggestions on prior versions of this paper. Lucy Atkinson provided expert research assistance on numerical computations. Special thanks to Ted Bergstrom who gave us valuable suggestions about the first proposition.     

The effect of risk-sharing government subsidy on corporate R&D investment: Empirical evidence from Korea

Despite the wide belief that the high social rates of returns to R&D investment justify government subsidy policy in advanced countries, there are only limited studies about whether the R&D subsidy as a means of risk-sharing stimulates R&D investment of small and medium sized enterprises (SMEs) in developing countries. This paper empirically investigates the issue, using a unique data set on government subsidy for new technology development of Korean manufacturing firms, listed and non-listed, for the period from 2000 to 2007. The paper employs the DID estimation procedure and controls for simultaneity of the subsidy for new technology development using 2SLS and two step Tobit procedure. Our empirical results show that there is no solid evidence for crowding-out effects of the government subsidy. These results suggest that government subsidies could help SMEs to overcome the barriers to risky R&D projects through sharing R&D failure risk with government and by reducing capital costs to undertake new technology development projects, and thus the subsidy policy for new technology development seems to be partly successful in promoting the R&D investment of the Korean SMEs.     

Do subsidies have positive impacts on R&D and innovation activities at the firm level?

In this paper we analyze whether and how “research” and “development” subsidies influence private R&D activity. Our empirical results show that “research” subsidies stimulate R&D spending within firms while “development” subsidies substitute such spending. At the theoretical level we find empirical support for the market failure argument that private R&D expenditure is best stimulated in areas where the gap between the social and the private rate of return to R&D is high. A policy implication is that technology programs should support research projects in the private sector in order to stimulate to more R&D.