Boris Lokshin

Complementarity in R&D Cooperation Strategies

This paper assesses the performance effects of simultaneous engagement in R&D cooperation with different partners (competitors, clients, suppliers, and universities and research institutes). We test whether these different types of R&D cooperation are complements in improving productivity. The results suggest that the joint adoption of cooperation strategies could be either beneficial or detrimental to firm performance, depending on firm size and specific strategy combinations. Customer cooperation helps to increase market acceptance and diffusion of product innovations and enhances the impact ofcompetitor and university cooperation. On the other hand, smaller firms also face diseconomies in pursuing multiple R&D cooperation strategies, which may stem from higher costs and complexity of simultaneously managing multiple partnerships with different innovation objectives.

Determinants of alliance portfolio complexity and its effect on innovative performance of companies

Alliance formation is often described as a mechanism used by firms to increase voluntary knowledge transfers. Access to external knowledge has been increasingly recognized as a main source of firm’s innovativeness. A phenomenon that has recently emerged is alliance portfolio complexity. In line with recent studies this article develops a measure of portfolio complexity in technology partnerships in terms of diversity of elements of the alliance portfolio with which a firm must interact. The analysis considers an alliance portfolio that includes different partnership types (competitor, customer, supplier, and university & research center). Factors that determine portfolio complexity and its impact on technological performance of firms remain largely unexplored. This article examines firms’ decisions to form alliance portfolios of foreign and domestic partners by two groups of firms: innovators (firms that are successful in introducing new products to the market), and imitators (firms that are successful at introducing new products, which are not new to the market). This study also assesses a non-linear impact of the portfolio complexity measure on firms’ innovative performance. The empirical models are estimated using data on more than 1800 firms from two consecutive Community Innovation Surveys conducted in 1998 and 2000 in the Netherlands. The results suggest that alliance portfolios of innovators are broader in terms of the different types of alliance partners as compared to those of imitators. This finding underlines the importance of establishing a ‘radar function’ of links to various different partners in accessing novel information. Specifically, the results indicate that foremost innovators have a strong propensity to form portfolios consisting of international alliances. This underlines the importance of this type of partnerships in the face of the growing internationalization of R&D and global technology sourcing. Being an innovator or imitator also increases the propensity to form a portfolio of domestic alliances, relative to non-innovators; but this propensity is not stronger for innovators. Innovators appear to derive benefit from both intensive (exploitative) and broad (explorative) use of external information sources. The former type of sourcing is more important for innovators, while the latter is more important for imitators. Finally, alliance complexity is found to have an inverse U-shape relationship to innovative performance. On the one hand, complexity facilitates learning and innovativeness; on the other hand, each organization has a certain management capacity to deal with complexity which sets limits on the amount of alliance portfolio complexity that can be managed within firm. This clearly suggests that firms face a certain cognitive limit in terms of the degree of complexity they can handle. Despite the noted advantages of an increasing level of alliance portfolio complexity firms will at a certain stage reach a specific inflection point after which marginal costs of managing complexity are higher than the expected benefits from this increased complexity.

The Productivity Effects of Internal and External R&D: Evidence from a Dynamic Panel Data Model

We examine the impact of internal and external R&D on labor productivity in a 6-year panel of Dutch manufacturing firms. We apply a dynamic linear panel data model that allows for decreasing or increasing returns to scale in internal and external R&D and for economies of scope. We find complementarity between internal and external R&D, with a positive impact of external R&D only evident in case of sufficient internal R&D. These findings confirm the role of internal R&D in enhancing absorptive capacity and hence the effective utilization of external knowledge. The scope economies due the combination of internal and external R&D are accentuated by decreasing results to scale at high levels of internal and external R&D. The analysis indicates that on average productivity grows by increasing the share of external R&D in total R&D.

Internal and External R&D: Complements or Substitutes? Evidence from a Dynamic Panel Data Model

We examine the impact of internal and external R&D on labor productivity in a 6-year panel of 304 innovating firms. We apply a dynamic linear panel data model that allows for decreasing returns to scale in internal and external R&D with a non-linear approximation of changes in the knowledge stock. We find complementarity between internal and external R&D, with a positive impact of external R&D only evident in case of sufficient internal R&D. The findings confirm the role of internal R&D in enhancing absorptive capacity and hence the effective utilization of external knowledge. These results suggest that empirical studies examining complementarities between continuously measured practices should adopt more general non-linear specifications to allow for correct inferences.

Do Firms Learn to Manage Alliance Portfolio Diversity? The Diversity-Performance Relationship and the Moderating Effects of Experience and Capability

Building on organizational learning theory, this study examines whether firms learn to manage alliance portfolio diversity. We argue that alliance portfolio diversity may be advantageous as well as disadvantageous for alliance portfolio performance. Subsequently, we theorize that the diversity-performance relationship is moderated by the firms alliance experience and capability. Bridging the previously separated literature of diversity and learning, our findings show a curvilinear relationship between diversity and performance. More important, using survey data, we reveal some key processes through which firms learn to manage alliance portfolio diversity.

Persistence of, and Interrelation Between, Horizontal and Vertical Technology Alliances

The authors explore to what extent there is persistence in, and interrelation between, alliance strategies with different partner types (customers, suppliers, competitors). In a panel data set of innovation-active firms in the Netherlands from 1996 to 2004, the authors find persistence in alliance strategies with all three types of partners, but customer alliance strategies are more persistent than supplier alliance strategies and competitor alliance strategies. A positive interrelation between customer and supplier alliance strategies and a high persistence of joint supplier and customer alliance strategies are consistent with the advantages of value chain integration in innovation efforts. Prior engagement in horizontal (competitor) alliances increases the propensity to engage in vertical alliance strategies, but this effect occurs only with a longer lag. Overall, the authors’ findings suggest that alliance strategies with different partner types are both heterogeneous in persistence and (temporally) interrelated. This suggests that intertemporal relationships between different types of alliances may be as important as their simultaneous relationship in alliance portfolios.

What Does it Take for an R&D Tax Incentive Policy to be Effective?

We take a critical look at how to assess the effectiveness of R&D tax incentives. The net welfare gain is shown to be sensitive to a certain number of parameters. In particular, the deadweight loss associated with level-based tax incentives depends on the ex-ante R&D level. We report on the success of a past policy changes and simulate the effect of various parameter changes in the existing Dutch R&D tax incentive scheme. We show that this policy is more effective for small firms than for large firms. We end with a discussion of the pros and cons of volume-based versus incremental R&D tax incentives.

Testing for Complementarity and Substitutability in the Case of Multiple Practices

Recent empirical studies of firm-level performance have been concerned with establishing potential complementarity between more than two organizational practices. These papers have drawn conclusions on the basis of potentially biased estimates of pair-wise interaction effects between such practices. In this paper we develop a consistent testing framework based on multiple inequality constraints that derives from the definition of (strict) super modularity as suggested by Athey and Stern (1998). Monte Carlo results show that the multiple restrictions test is superior for performance models with high explanatory power. If practices explain only a minor part of organizational performance no test is able to identify complementarity or substitutability in a satisfactory manner.

A Monte Carlo comparison of alternative estimators for dynamic panel data models

This article compares the performance of three recently proposed estimators for dynamic panel data models (LSDV bias-corrected, MLE and MDE) along with GMM. Using Monte Carlo, we find that MLE and bias-corrected estimators have the smallest bias and are good alternatives for the GMM. System-GMM outperforms the rest in ‘difficult’ designs. Unfortunately, bias-corrected estimator is not reliable in these designs which may limit its applicability.

Partner Type Diversity in Alliance Portfolios: Multiple Dimensions, Boundary Conditions and Firm Innovation Performance

Our research extends the current knowledge based view on the configuration of alliance portfolios and their deployment in different external knowledge environments. We study these alliance portfolios in a longitudinal sample (1996–2010) for over three thousand firms that operate in a large number of industries in the Netherlands. Our findings indicate that partner type variety and partner type relevance, as different dimensions of partner diversity in alliance portfolios, both have an inverted U‐shaped association with firm innovation performance. However, alliance portfolios characterized by both high partner type variety and high relevance cause inferior innovation performance. Different external knowledge environments, characterized by different levels of industry modularity and scope of knowledge distribution, moderate the inverted U‐shaped associations of partner type variety and relevance in alliance portfolios with firm innovation performance in opposing directions. While for partner type variety, a high level is found to be optimal in environments with greater modularity or broader scope of knowledge distribution, for partner type relevance it turns out that a low level is optimal under more modular industry conditions.