Mining external R&D

Open Innovation presses the case for timely and thorough intelligence concerning research and development activities conducted outside one’s organization. To take advantage of this wealth of R&D, one needs to establish a systematic “tech mining” process. We propose a 5-stage framework that extends literature review into research profiling and pattern recognition to answer posed technology management questions. Ultimately one can even discover new knowledge by screening research databases.Once one determines the value in mining external R&D, tough issues remain to be overcome. Technology management has developed a culture that relies more on intuition than on evidence. Changing that culture and implementing effective technical intelligence capabilities is worth the effort. P&G's reported gains in innovation call attention to the huge payoff potential.     

Globalisation,industrial diversification and productivity growth in large European R&D companies

This paper aims to assess the impact of both geographic and industrial diversification of economic activities on the productivity performance of large European R&D Multinational Enterprises (MNEs). Based on the worldwide subsidiaries of these firms, we measure the performance of the firms according to their level of industrial diversification and globalisation that we proxy with the presence and importance of subsidiaries in the EU, North America and Asia–Pacific regions. The sample consists of large R&D firms that represent about 80 % of total European R&D. In general, the results indicate a positive impact from globalisation on firms’ R&D productivity, especially in the US, while a negative impact for industrial diversification is found.     

Technology ladders and R&D in dynamic Cournot markets

Motivated by dramatic and unpredictable technological advances in energy production (for instance drilling and extraction of shale oil), we extend Cournot models of competition to incorporate research and development (R&D) that can lead to (stochastic) drops in production costs. Our model combines features of patent racing with dynamic market structure, capturing the interplay between the immediate competition in terms of production rates and the long-term competition in R&D. The resulting Markov Nash equilibrium is found from a sequence of one-step static games arising between R&D successes, and several numerical examples and extensive analysis of the emerging comparative statics are presented. Analyzing the relationship between current market dominance and the level of R&D investments, we find that market leaders tend to invest more, which in some sense makes oligopoly dynamically unstable. We show that anticipated market transitions have long-term impact; for example the potential of future monopoly can spur R&D investment now, even if the firm is presently uncompetitive and not actively producing. We also show that, surprisingly, random innovations have an ambiguous effect on R&D. This feature, which is driven by the Cournot framework, contrasts with the common situation whereby uncertainty lowers innovation and delays R&D investments. Finally, we demonstrate that increased competition may actually increase efforts to innovate through higher desire to achieve dominance. This would match the anecdotal evidence that the threat of market entrants forces incumbents to maintain high R&D.     

An investigation into international assignment directions of R&D MNE employees: evidence from Greece

In this study, we explore the effects of the roles of research and development (R&D) laboratories, roles of subsidiaries and level of technological intensity of the sector in which multinational enterprise (MNE) subsidiaries operate on international assignment directions of R&D employees. International assignments are an underinvestigated issue in the international human resource management literature despite its significant research and managerial importance. In particular, to the best of our knowledge, no prior research on international assignments of R&D employees has been undertaken and so the current study aims at filling this void in the literature. Based on a large quantitative research on MNE subsidiaries operating in Greece, the findings suggest that variables of the aforementioned categories of factors influence different international assignment directions, with roles of the R&D subsidiary exerting the most crucial effect. Researchers may examine the unexplored issue of R&D employee international assignments to a larger extent, while MNE management can particularly take into account the micro (laboratory) context of R&D international assignees when developing effective international human resource management programmes.     

Learning from R&D outsourcing vs. learning by R&D outsourcing

We analyze how research and development (R&D) outsourcing influences product innovation. We propose a separation between learning from R&D outsourcing, whereby the firm improves its ability to innovate by using outsourced R&D directly in new products, from learning by R&D outsourcing, whereby the firm indirectly uses outsourced R&D by integrating it with internal R&D to create new products. Building on the knowledge-based view, we argue that learning from R&D outsourcing is likely to have an inverse U-shaped relationship with product innovation, because the initial benefits of using outsourced component R&D knowledge to innovate products is eventually outweighed by the hollowing out of the firm's ability to innovate. In contrast, we propose that learning by R&D outsourcing is likely to have a U-shaped relationship with product innovation, because the initial challenges of integrating internal and external R&D are eventually overcome, resulting in more innovations. Finally, we distinguish between domestic and foreign R&D outsourcing and propose a liability of foreignness in R&D outsourcing as it has a lower impact on new products than domestic R&D outsourcing. The empirical analysis shows that outsourced R&D has an inverted U-shaped relationship with the number of new products, while the interaction between outsourced R&D and internal R&D has a U-shaped relationship with the number of new products. It also shows that domestic outsourced R&D has a higher positive impact on the number of new products than foreign outsourced R&D.     

Optimal R&D investment for a risk-averse entrepreneur

Entrepreneurs investing in R&D projects face technical uncertainty associated with the cost to completion of the project, which is idiosyncratic and inherently unhedgeable. We extend existing real options models of R&D investment to incorporate the cost of bearing this unhedgeable risk and find it decreases risk-averse entrepreneurs’ valuations of R&D projects and increases the minimum NPVs required for continued investment in R&D (threshold NPVs) relative to ‘unpriced risk’ values and threshold NPVs. As in the ‘unpriced risk’ case, for less risk-averse entrepreneurs with small R&D projects, threshold NPVs remain negative and decrease with technical uncertainty. However, for sufficiently risk-averse entrepreneurs with sufficiently large R&D projects, threshold NPVs can become positive and increase with technical uncertainty.     

The dark side of stock market liberalization: Perspectives from corporate R&D activities in China

This study explores how stock market liberalization impacts corporate research and development (R&D) activities and examines the impact channels. Based on a quasi-natural experiment on the Shanghai-Hong Kong Stock Connect, we report a significantly negative relationship between stock market liberalization and R&D activities in non-state-owned enterprises (non-SOEs) using a difference-in-difference approach. For one thing, a decrease in analyst coverage will reduce the supervision of R&D activities; for another, the alleviation of financing constraints will heighten corporate financialization, resulting in a greater crowding-out effect on R&D activities. Furthermore, R&D activities in SOEs, which are guided by government policies, are not significantly affected by stock market liberalization.     

Making sense of innovation by R&D and non-R&D innovators in low technology contexts: A forgotten lesson for policymakers

This paper attempts to use an integrated theory based on the framework of a firm's internal and external sources of knowledge to analyze how R&D activities differ in innovation from non-R&D activities, especially in the context of low and medium-low tech (LMT) sectors where most of the firms are SMEs. Simultaneously, the paper also explores the key differences between R&D and non-R&D innovators. The empirical analysis is based on a representative panel of 2023 Spanish manufacturing firms from the Spanish Ministry of Industry for 2005 and 2006. Innovation in product and process is explained using non-R&D variables such as marketing, design or the hiring of tertiary degree employees. Only innovation in product is explained by R&D expenditures. Regarding innovation in process, the R&D variables work in a few specific cases. Therefore, innovation can be explained using non-R&D variables. The firms with more internal resources, those which conduct R&D activities, present a better absorptive capacity (AC) and this leads them to engage in cooperation agreements and to access external flows of knowledge. The paper has important implications for policymakers due to the fact that most policies for R&D are based just on R&D programmes.     

Research collaboration and R&D outsourcing: Different R&D personnel requirements in SMEs

The literature on ‘open’ innovation emphasises the need to engage in external knowledge relations in order to innovate. Particularly for SMEs, research cooperation and R&D outsourcing can offer possibilities to complement the often limited internal research resources. However, they also bring in their wake requirements in terms of absorptive capacity and managerial skills of the internal R&D personnel.The paper focuses on the different requirements in terms of availability and training of research managers and R&D experts for research cooperation versus R&D outsourcing in SMEs. An empirical analysis of micro-level data provided by the OECD business R&D survey for Belgium reveals that the relation between R&D personnel requirements and research collaboration and R&D outsourcing depends upon the SME size. Therefore, to study this subject appropriately a distinction between very small, small, and medium-sized firms is relevant. Very small firms engage significantly less in research cooperation than medium-sized firms and the propensity to engage in research cooperation is positively associated with the share of PhD holders among the research managers and R&D experts. For R&D outsourcing a lower involvement is noted in medium-sized firms, and the propensity to outsource increases with the formal qualification level of the R&D personnel and with R&D training. Among the SME, small firms are most engaged in research cooperation and in R&D outsourcing. In the case of research cooperation they rely on highly qualified experts. For R&D outsourcing activities both the presence of research managers and R&D experts is important.     

The R&D knowledge base in city-agglomerations and knowledge searching in product innovative SMEs

ABSTRACT

This paper looks at the relation between the R&D knowledge base of city-agglomerations and knowledge sourcing in product innovative small and medium-sized enterprises (SMEs). The small open Belgian economy is used as a test case. The characteristics of the city-agglomeration’s R&D knowledge are posited to be instrumental for SMEs’ reliance on particular sources of information for innovation. The R&D knowledge base is studied as a multidimensional concept consisting of R&D capacity, R&D specialization and R&D diversification. A representative sample of product innovative SMEs drawn from two waves of the Community Innovation Survey between 2008 and 2012 reveals that a strong R&D capacity at city-agglomeration level favours private external information sources for innovation, but has no influence on the likelihood to rely on public sources for innovation. Accordance between specialization of the private R&D knowledge base and the SME’s activities positively influences the use of clients as information sources for innovation, whereas under these circumstances supplier responsiveness turns out to be less frequently solicited for. A more diversified private R&D environment reduces the reliance on universities and public research organizations as information sources for innovation. A public R&D knowledge base specialized in natural sciences or engineering favours information sources from universities.     

Short-term R&D bias,competition on cost rather than innovation,and time to market

Mounting evidence indicates that capital markets often apply short-term pressure on firms to gain short-term results by focusing primarily on reported financial performance. As a result of short termism, it has been argued that companies are likely to cut expenditure on R&D which might otherwise improve longer-term performance. As there is a growing consensus that R&D is critically important to both organizational and national performance, short termism may have significant detrimental organizational consequences. One implication arising from a short-term R&D bias, and examined in this paper, is its effect on market time reduction. Arguments are examined that suggest a dominant R&D strategy is to reduce product time to market. Concerns have been expressed, however, that such a strategy is applicable in specific circumstances only. A review of the literature suggests that analyst and shareholder bias against high-risk, long-term research in favor of lower-risk, short-term product R&D influences organizations to reduce the time it takes to get a product to market when the emphasis in the marketplace is on cost competition rather than product innovation. The findings of the study suggest that when the emphasis on competition on cost rather than innovation is low, short-term R&D bias does not affect market time. In contrast, when the emphasis on competition on cost rather than innovation is high, the results indicate that short-term R&D bias positively influences market time reduction. The study concludes with suggestions for further research.     

R&D and aggregate fluctuations

Empirical observations raise interesting questions regarding the sources of the excessive volatility in the R&D sector as well as the nature of the relation between the sector and aggregate fluctuations. Using US data for the period 1959–2007, we identify sectoral technology and capital investment-specific shocks by employing a Vector Autoregression. The identifying assumptions are motivated by a two-sector dynamic general equilibrium model. Controlling for real and nominal factors, we find that capital investment-specific shocks explain 70 percent of fluctuations of R&D investment, while R&D technology shocks explain 30 percent of the variation of aggregate output, net of R&D investment. Technology shocks jointly explain almost all the variation of output in the R&D sector and 78 percent of the variation of output in the rest of the economy. They also constitute the main factor of the procyclicality of R&D investment.     

The differential effects of public R&D support on firm R&D: Theory and evidence from multi-country data

This paper aims to evaluate the effects of various forms of public research and development (R&D) support on firms’ incentives to invest in R&D. First, in order to identify potential channels through which public R&D support influences firm R&D, a formal model of firm R&D with public R&D support is developed and analyzed. Four potential channels are identified: the technological-competence-enhancing effect, the demand-creating effect, the R&D-cost-reducing effect and the (project) overlap (or duplication) effect. These multiple channels indicate that it is difficult to evaluate the aggregate effect of public R&D support and that there are differential effects of public R&D support on firm R&D, depending on various firm- or industry-specific characteristics. Second, the differential effects of public R&D support are empirically tested using unique firm-level data for nine industries across six countries. Public support tends to have a complementarity effect on private R&D for firms with low technological competence, for firms in industries with high technological opportunities and for firms facing intense market competition. In contrast, firms with high technological competence and firms that have enjoyed fast demand growth in recent years show a crowding-out effect, and firm size and age do not show any discernible differential effect.     

R&D performance assessment of industrial enterprises in China: A two-stage DEA approach

With the growing expenditure on the R&D activities of industrial enterprises above designated size (IEDSs) in China, it is important to evaluate the R&D efficiency of the Chinese IEDSs. However, few studies about R&D efficiency measurement of Chinese IEDSs have considered the internal structure of the R&D production process. To fill this gap, this paper investigates the R&D performance of IEDSs of 30 sample provinces on China's mainland from 2009 to 2014, based on a two-stage data envelopment analysis (DEA) model. The major findings from the empirical results are shown as follows: (i) serious imbalance exists in the R&D resources among Chinese IEDSs of 30 provinces; (ii) there is a decline in the average overall efficiencies after 2012; (iii) there are great differences regarding the performances of R&D activities among the Chinese IEDSs of 30 provinces; (iv) high attention to the R&D activities or strong scientific research atmosphere may promote the R&D efficiency of Chinese IEDSs; and (v) the IEDSs with the relatively high profitability or high government support in terms of R&D activities have relatively poor performance. Based on these findings, several policy suggestions are proposed for the R&D activities of Chinese IEDSs.     

Stable R&D Cooperation with Spillovers

The literature on the incentives for R & D cooperation with spillovers typically deals only with the factors affecting cooperative profits. This paper focuses on the incentives to cheat and the stability of such cooperative agreements in a repeated game framework. It is shown that the stability of cooperation is influenced by the nature and magnitude of spillovers, relative to the nature and degree of product market competition. While cooperative profits are higher with large positive (exogenous, unintended) know-how spillovers, such as in fundamental research, our anslysis shows that it may be easier to sustain cooperation in areas with lower spillovers, such as applied research, because of the smaller incenfives to cheat on the initial agreement, at least when firms produce substitutes. Alternatively, the possibility of technology sharing (i.e., intended or endogenous spillovers), besides R&D coordination, not only increases cooperative profits but also reduces the incentives to defect from a cooperative equilibrium.     

Real options game models of R&D competition between asymmetric firms with spillovers

Using real options game models, we consider the characterization of strategic equilibria associated with an asymmetric Research and Development (R&D) race between an incumbent firm and an entrant firm in the development of a new innovative product under market and technological uncertainties. The random arrival time of the discovery of the patent protected innovative product is modeled as a Poisson process. Input spillovers on the R&D effort are modeled by the change in the leader’s hazard rate of success of innovation upon the follower’s entry into the R&D race. Asymmetry between the two competing firms include sunk costs of investment, stochastic revenue flow rates generated from the product, and hazard rates of arrival of success of R&D efforts of the two firms. Under asymmetric duopoly, we obtain the complete characterization of the three types of Markov perfect equilibria (sequential leader–follower, preemption and simultaneous entry) of the firms’ optimal R&D entry decisions with respect to various sets of model parameters. Our model shows that under positive input spillover, preemptive equilibrium does not occur in the R&D race due to the presence of dominant second mover advantage. The two firms choose optimally to enter simultaneously if the sunk cost asymmetry is relatively small; otherwise, sequential equilibrium would occur. When the initial hazard rate is low relative to the level of input spillover, simultaneous entry would occur as an optimal decision, signifying another scenario of dominant second mover advantage. On the other hand, when the initial hazard rate is sufficiently high so that the first mover advantage becomes more significant, simultaneous equilibrium does not occur even under high level of positive input spillover.     

Issues in Assessing the Effect of Interindustry R&D Spillovers

This paper aims to clarify three issues concerning the weighting methodol ogy generally used to evaluate interindustry R&D spillovers. These issues concern the likely nature of the spillovers estimated through different types of supporting matrices; the similarity between input–output (IO), technology flows and technological proximity matrices; and the relevance of the assumption that a single matrix can be used for different countries. Data analyses of weighting components show that technology flows matrices are in an intermediate position between IO matrices and technological proximity matrices, but closer to the former. The various IO matrices, as well as the three technological proximity matrices, are very similar to each other. The panel data estimates of the effect of different types of interindustry R&D spillovers on industrial productivity growth in the G7 countries reject the hypotheses that a technology flows matrix can be approximated by an IO matrix and that a single IO matrix can be usedfor different countries. By transitivity, the procedure that comprises using a single technology flow for several countries is not reliable. The international comparison shows that each country benefits from different types of R&D externality. In Japan and, to a lesser extent, in the US, the rate of return to direct R&D is very high and is likely to compensate for relatively weak interindustry R&D spillover effects. In the five other industrialized countries, the reverse observation is true: strong social rates of return to R&D counterbal ance the poor performances of direct R&D.     

Governance and effects of public R&D subsidies: Evidence from China

This study examines the effects of public research and development (R&D) subsidies and the governance of such subsidies on firm productivity based on the analysis of a firm-level panel dataset between 1998 and 2007 in China. It is found that public R&D subsidies tend to support more productive firms and the productivity of these government-backed firms is improved further after they get the government support. Less attention is paid to the observable or measurable performance measurements in ex-ante project selection, and the ex-post effects are stronger when the governance of the public R&D subsidies becomes more decentralized due to an exogenous policy change. In other words, better decentralization of governance is associated with more pronounced effects of R&D subsidies. Identification concerns are addressed with various approaches to confirm the treatment effect of public R&D subsidies and the governance of such subsidies.     

Selecting balanced portfolios of R&D projects with interdependencies: A Cross-Entropy based methodology

The intensive growth of technology makes firms rely on research and development (R&D) activities in order to adapt to technology changes in an ever-changing and uncertain environment. Due to R&D budget constraints and limited resources, firms are often forced to select a subset of all candidate projects by means of project portfolio selection techniques mitigating the corresponding risks and enhancing the overall value of portfolio. Projects' interdependencies and types were rarely considered in existing models of R&D portfolio selection that may result in selecting wrong projects. This flaw hinders the projects alignment with corporate objectives and strategy and leads to excessive risk and missing the promised values. In this paper, a balanced set of R&D project evaluation criteria was proposed. Next, to construct R&D project portfolio, a 0–1 nonlinear mathematical programming method for balancing portfolio values and risks was proposed, in which research projects' interdependencies, types and other constraints were all considered. Finally, a Cross-Entropy algorithm was developed to solve the proposed model and results were reported. The algorithm proved to be very effective in terms of solution quality and computational time. The proposed algorithm especially suits large scale instances while exact approaches are doomed to fail.     

On the R&D/marketing interface in knowledge intensive entrepreneurial firms

In this paper we focus on the performance impact associated with whether R&D or marketing takes the lead in product innovations and/or product development. We examine empirically the performance of a sample of entrepreneurial firms across 10 European Union countries for which we can identify alternative regimes in which R&D, or in which marketing, is viewed as being relatively more important in creating and sustaining the firm’s competitive advantage. We find that when R&D is the dominant strategy, firms realize greater growth in sales, other factors held constant.