Favorable strategies for the success of entry into new technological areas: an entrepreneurial perspective

This study considers the act of entering into new technological domains for R&D purposes as one of the most intense entrepreneurial activities within large established firms, referring to it as R&D entrepreneurship. Attempting to detect factors that could strengthen (or weaken) the impact of R&D entrepreneurship on innovation performance, I examine the moderating role of three important R&D strategies, namely the knowledge plurality, internal focus, and R&D collaboration. I empirically test the hypotheses developed in this study on secondary, longitudinal economic and patent data from a sample of 139 firms from the industries of pharmaceuticals, biotechnology, and chemicals for a 7-year period, using fixed-effects negative binomial regression models. Findings support that the relationship between R&D entrepreneurship and innovation performance is positively moderated by knowledge plurality but negatively by internal focus and R&D collaboration.

     

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.     

An analysis of firm-level innovation strategies in the US biotechnology industry

This study examines factors that may affect innovation strategies and performance of firms in the biotechnology industry. Specifically, differences between factors common to firms with high R&D intensity and those to firms with low R&D intensity are investigated. Biotechnology firms with relatively higher levels of R&D intensity attribute their innovation performance to research-based innovation factors and strategies such as strengthening their own research capabilities, entering into research collaborations with universities, industry leaders and other biotech firms, and licensing their technology. These strategies can be summarized as alignment within the industry. Firms with relatively lower R&D intensity have a hybrid focus—they invest in R&D but may also have products on the market. These firms attribute their innovation performance more so to production-based innovation factors and strategies such as gaining market access and maintaining connections with customers. Their strategy focuses on competitiveness, marketing, and distribution channels, while not ignoring the importance of a strong research base and the need to advance technologically. In a sense, strategies employed to achieve successful innovation reflect the stage of innovation in which a firm is operating for a particular product or process.     

How does R&D intensity influence firm explorativeness? Evidence of R&D active firms in four advanced countries

Despite R&D is seen as a starting point of innovation, firms usually confront a trade-off in allocating limited R&D resources to either exploratory or exploitative activities. Relative to the latter, the former produces a more distinctive variation from the prior knowledge base and helps the firm tap into new opportunity. Given the increasing importance of firm explorativeness in the fast changing environments, the influence of R&D investment on firm explorativeness is not yet conclusive in the literature, not to mention whether the increased R&D investment induces firms to become more explorative. This study aims to generate insight into how and when firm explorativeness is determined by their R&D intensity. As a notion of the use of knowledge new to the organization, firm explorativeness is treated as the degree of using knowledge new to the organization in the pursuit of innovation. Based on a panel data of 1267 firm-year observations in four advanced countries during 1999–2003, the results reveal that a higher level of R&D intensity makes firms more exploitative and less explorative. Nevertheless, the negative relationship between R&D intensity and firm explorativeness is found to be alleviated in the presence of technological opportunity or financial slack. The configurational model sheds further light on the combined and relative weight of two moderators.     

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.     

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.     

MNEs,technological efforts and channels of export spillover: An analysis of Indian manufacturing industries

The present study provides some empirical evidence for the export spillover effect examining the case of an emerging market economy, namely India, using firm level data for the period 1994–2006. We disentangle different spillover channels, namely the demonstration effect, the imitation effect (R&D spillover) and a proxy to measure spillover effects coming from higher MNEs’ skills. We also account for the heterogeneous technological behaviour of local firms considering how in-house R&D efforts and disembodied technological imports may affect the exporting performance. Our findings show how export spillover effects are mainly mediated by an imitation effect, contrary to the case of other emerging market economies like China, where a demonstration effect is evident. We also recognise that both the decision to export and export intensity are influenced most of all by the technological activities of local firms. Moreover, the findings of the analysis suggest that in-house R&D is more relevant than other external sources of technological knowledge such as disembodied technology imports to internalise the positive spillover effect emanating from MNEs.     

Building absorptive capacity to organise inbound open innovation in traditional industries

The discussion on open innovation suggests that the ability to absorb external knowledge has become a major driver for competition. For R&D intensive large firms, the concept of open innovation in relation to absorptive capacity is relatively well understood. Little attention has; however, been paid to how both small firms and firms, which operate in traditional sectors, engage in open innovation activities. The latter two categories of firms often dispose of no, or at most a relatively low level of, absorptive capacity. Open innovation has two faces. In the case of inbound open innovation, companies screen their environment to search for technology and knowledge and do not exclusively rely on in-house R&D. A key pre-condition is that firms dispose of “absorptive capacity” to internalise external knowledge. SMEs and firms in traditional industries might need assistance in building absorptive capacity. This paper focuses on the role of collective research centres in building absorptive capacity at the inter-organisational level. In order to do so, primary data was collected through interviews with CEOs of these technology intermediaries and their member firms and analysed in combination with secondary data. The technology intermediaries discussed are created to help firms to take advantage of technological developments. The paper demonstrates that the openness of the innovation process forces firms lacking absorptive capacity to search for alternative ways to engage in inbound open innovation. The paper highlights the multiple activities of which absorptive capacity in intermediaries is made up; defines the concept of absorptive capacity as a pre-condition to open innovation; and demonstrates how firms lacking absorptive capacity collectively cope with distributed knowledge and innovation.     

Types of innovation and inter-firm co-operation

The paper presents the results of an empirical study that aims to investigate the impact of interfirm co-operation over innovation on four different types of innovation: product, process, incremental and radical innovation. Drawing on the innovative milieu literature, the impact on the above four types of innovation was tested for both external and internal factors of innovation such as inter-firm co-operation over innovation, production networking, as well as R&D investment and R&D personnel. Four probit models were run by using a unique data set compiled as part of the Regional Innovation Strategy for the West Midlands (UK) Project. The main findings of the paper seem to provide substantial evidence that, for any of the four types of innovation considered, firms' capacity to innovate could greatly improve if they co-operated with other firms over innovation in addition to or instead of investing in R&D. Innovation policy should not overlook, therefore, the systemic component of innovation and ought to attempt to initiate and support inter-firm co-operation. This would mean a renewed and more focused analysis of firms' clusters as part of a multi-faceted approach to innovation policy.     

The impact of technological relatedness, prior ties, and geographical distance on university-industry collaborations: A joint-patent analysis

Empirical studies on R&D collaborations between universities and firms have mainly centered their attention on universities and firms' characteristics that favor the establishment of collaborative agreements. In this paper, I extend the current research framework investigating the role that specific technological and relational attributes may play on the relevance of such collaborations. Specifically, I focus on the effects exerted by three relevant factors, namely technological relatedness, prior collaboration ties, and geographical distance, on university-industry joint innovation value. I develop testable hypotheses about their impact on the innovative performance of R&D university-industry collaborations, and test them on a sample of 796 university-industry joint patents, developed by 33 universities located in 12 different European countries. Our results suggest that partners' technological relatedness has an inverted U-shaped relationship with innovation value. In addition, prior ties and geographical distance between universities and firms are both positively related to the achievement of higher innovative outcomes.     

Value and risk dynamics over the innovation cycle

This paper studies investment in intellectual capital and corresponding value and risk dynamics over the innovation cycle. We assume that the innovation cycle consists of three phases, R&D, trial, and market introduction phases. We use a real option investment model to characterize firm value and risk dynamics over the innovation cycle and find that firm value is the sum of the value of assets in place and non-linear option values related to breakthrough, exit, and market introduction options. Firm risk over the innovation cycle is highly non-linear and quite distinct in different phases. During the R&D phase risk is high as the firm faces high operating leverage originating from R&D fixed costs together with technological uncertainty. During the trial phase risk is significantly lower and dominated by option risk to launch the product in the market while after the introduction of the product in the market risk is equivalent to the asset risk of the company. Our model is consistent with the view that positive excess returns of R&D intensive firms are a compensation for risk. Based on this insight we derive several testable predictions.     

Mining the R&D innovation performance processes for high-tech firms based on rough set theory

The research and development (R&D) innovation of firms continues to be viewed as an important source of competitive advantage to academics and practitioners. To explore and extract the R&D innovation decision rules, it is important to understand how the R&D innovation rule-base works. However, many studies have not yet adequately induced and extracted the decision rule of R&D innovation and performance based on the characteristics and components of the original data rather than on post-determination models. The analysis of this study is grounded in the taxonomy of induction-related activities using a rough set theory approach or rule-based decision-making technique to infer R&D innovation decision rules and models linking R&D innovation to sales growth. The rules developed using rough set theory can be directly translated into a path-dependent flow network to infer decision paths and parameters. The flow network graph and cause-and-effect relationship of decision rules are heavily exploited in R&D innovation characteristics. In addition, an empirical case of R&D innovation performance will be illustrated to show that the rough sets model and the flow network graph are useful and efficient tools for building R&D innovation decision rules and providing predictions. We will then illustrate that integrating the flow network graph with rough set theory can fully reflect the characteristics of R&D innovation, and, through the established model, we can obtain a more reasonable result than with artificial influence.     

Dynamics in research joint ventures and R&D collaborations

We investigate the short- and long-term effects of different types of R&D collaborations on firms, consumers, and the industry. To that end, we consider a differentiated-product market in which firms compete à la Bertrand and invest in process innovation in order to lower the production cost over time. Investments are stochastic and there can be cartelization or competition strategies among firms at the moment of making the decision on the amount to invest in R&D. Our results show that in equilibrium, the long-run welfare is larger under a research joint venture than under other environments. Discounted present value profits increase with the level of the spillover but there are asymmetries that depend on the firms’ asymmetry on marginal costs.     

The R&;D and productivity relationship of Korean listed firms

This study analyzes the relationship between R&D investment and the productivity of Korean R&D-engaged firms. An interdependent chain of equations including the propensity to invest, R&D investment and productivity are estimated in a multi-step procedure accounting for selectivity and simultaneity biases. Using Korean firm level panel data of listed firms from 1986 to 2002, we find four main empirical results. First, there is a two-way causal relationship between R&D investment and productivity for Korean listed firms. Second, Chaebol firms were associated with lower R&D growth as well as lower labor productivity growth in comparison to non-Chaebol firms. Third, there was a substantial reduction in growth rates both in R&D investment and labor productivity in 1997-1998, immediately following the Asian financial crisis. Fourth, considering the positive feedback effect from productivity growth to R&D growth, a decrease in R&D investment growth after the Asian financial crisis should have been harmful by further decreasing productivity growth.     

The effect of R&D novelty and openness decision on firms' catch-up performance: Empirical evidence from China

This paper explores the strategic dimensions of R&D decisions toward novelty and openness in explaining the performance of latecomer firms in a developing economy. A structural equation model of R&D decision-making is formulated using survey data from 279 Chinese firms. The dimension of R&D novelty is defined as the degree of technological newness found in firms' R&D projects, while R&D openness describes the degree to which technologies are acquired from external sources. Our results indicate that firms' R&D decisions regarding novelty and openness are associated with demand opportunities, market competition, technological capability, and external networks. Greater R&D novelty contributes positively to innovative output but does not affect sales growth. Greater R&D openness contributes positively to sales growth but negatively to innovative output.     

How do firm characteristics affect behavioural additionalities of public R&D subsidies? Evidence for the Austrian transport sector

Interest of STI policies to influence the innovation behaviour of firms has been increased considerably. This gives rise to the notion of behavioural additionality, broadening traditional evaluation concepts of input and output additionality. Though there is empirical work measuring behavioural additionalities, we know little about what role distinct firm characteristics play for their occurrence. The objective is to estimate how distinct firm characteristics influence the realisation of behavioural additionalities. We use survey data on 155 firms, considering the behavioural additionalities stimulated by the Austrian R&D funding scheme in the field of intelligent transport systems in 2006. We focus on three different forms of behavioural additionality—project additionality, scale additionality and cooperation additionality—and employ binary regression models to address this question. Results indicate that R&D related firm characteristics significantly affect the realisation of behavioural additionality. R&D intensive firms are less likely to substantiate behavioural additionalities, while small, young and technologically specialised firms more likely realise behavioural additionalities. From a policy perspective, it may be concluded that direct R&D promotion of firms with a high R&D intensity may be misallocated. Attention of public support should be shifted to smaller, technologically specialised firms with lower R&D experience. The findings deliver important insights into interactions of public R&D support and R&D behaviour of firms operating in the Austrian transport sector, bearing significant implications for future policy designs.     

Assessing the technological innovation efficiency of China's high-tech industries with a two-stage network DEA approach

As significant strategic players in China's economy, high-tech industries need to evaluate and analyze the technological innovation activities from a system point of view to understand and improve their technological innovation efficiency and, thereby, promote their development. Different high-tech industries have different characteristics and thus benefit from different industrial development policies. However, few studies to date have discussed this issue from a systematic perspective. In this study, technological innovation activities are divided into a research and development (R&D) stage and a commercialization stage. A high-tech industrial evaluation framework of technological innovation efficiency based on two-stage network data envelopment analysis (DEA) is constructed with shared inputs, additional intermediate inputs, and free intermediate outputs. Our empirical results indicate that the overall efficiency of most industries is relatively low and the differences between the five high-tech industries (i.e., sub-sectors) we examined are large. The Spearman correlation shows that overall efficiency and R&D efficiency are more correlated than overall efficiency and commercialization efficiency. Additionally, R&D has better average efficiency. The sub-sector with the highest average efficiency is computers and office equipment, and the one with the lowest average efficiency is medicines. These findings indicate the inadequacy but potential for breakthroughs in the evolution of high-tech industries in China. The analysis proves that it is necessary to create different industrial policies to encourage effective progress in certain high-tech industries, and some guidelines for doing so are provided.     

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.     

Firms' human capital,R&D and performance: a study on French and Swedish firms

This paper studies the effects of human and technological capital on productivity in a sample of large French and Swedish firms. While the role of technological capital as measured by R&D has been intensively investigated, almost no work has been done on the role of human capital as measured by firm-sponsored training and even less its interaction with technological capital. The level of intangible capital may also have a lasting effect on productivity growth, as emphasised by some endogenous growth models in a macroeconomic setting.The study uses data from two panels of large French and Swedish firms for the same period (1987–1993). It constructs measures of a firm's human capital stock, based on their past and present training expenditures. The results confirm that firm-sponsored training and R&D are significant inputs in the two countries, although to a different extent, and have high returns. However, except for managers and engineers in France, we do not find evidence of positive interactions between these two types of capital. Finally, growth effects at the firm level do not appear.     

Technological opportunity and the relationship between innovation output and market structure

This study examines influences of technological opportunity on the relationship between market structure and the innovation output of different‐size firms. A simultaneous‐equations model is specified and estimated separately for technologically progressive and technologically unprogressive industries. The study finds that innovation activities of small firms and large firms bear different relationships to market structure, in part resulting from interindustry differences in technological opportunity. In technologically progressive industries, innovation output (especially of small firms) is lower in the presence of high concentration and is increased substantially by high R&D intensity. Large‐firm innovation output has a positive effect on industry concentration, but only in technologically unprogressive industries. Copyright © 2005 John Wiley & Sons, Ltd.