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The objective of this work is to demonstrate the relationships between the two main processes of research and development (R&D) activities: the knowledge generation phase (KPP) and the knowledge commercialization, or transfer, phase (KCP), in a sector that is intensive in this type of activity, such as the pharmaceutical sector. In addition, within the framework of the general objective of this work, the authors propose two other objectives: (1) make advances in network efficiency measurement models, and (2) determine the factors associated with efficiency in the KPP and in the KCP in companies of the pharmaceutical sector in Spain.

A Network Data Envelopment Analysis (NDEA) model (Färe and Grosskopf, 2000) with categorical variables (Lee et al., 2020; Yeh and Chang, 2020) has been applied, and a sensitivity analysis of the obtained results has been performed through a DEA model of categorical variables, in accordance with the work of Banker and Morey (1986), to corroborate the results of the proposed model. The sample is made up of 77 companies in the pharmaceutical sector in Spain.

The results obtained point to a greater efficiency of pharmaceutical companies in the KPP, rather than in the KCP. Furthermore, the study finds that 1) alliances between companies have been the accelerating factors of efficiency in the KCP (but patents have slowed this down the most); 2) the quality of R&D and the number of R&D personnel are the factors that most affect efficiency in the KPP; and 3) the quality of R&D again, the benefits obtained and the position in the market are the factors that most affect efficiency in the KCP.

The authors have not found studies that show whether the efficiency obtained by R&D-intensive companies in the KPP phase is related to better results in terms of efficiency in the KCP phase. No papers have been found that analyse the role of alliances between R&D-intensive companies and patents, as agents that facilitate efficiency in the KCP phase, covering the gap in the research on both problems. Notwithstanding, this work opens up a research path which is related to the improvement of network efficiency models (since it includes categorical variables) and the assessment of the opinions of those who are responsible for R&D departments; it can be applied to decision-making on the aspects to improve efficiency in R&D-intensive companies.

The purpose of this paper is to explore the impact of peer-to-peer (P2P) supply chain financing on companies' innovation efficiency.

This study takes the core companies that invest in the P2P platform as the research background and uses data for Chinese companies and the systematic Generalised Method of Moments (the systematic GMM) to explore the relationship between the improvement of supply chain efficiency, research and development (R&D) investment, and innovation efficiency.

This study indicates that core enterprise investment in P2P can cause a significant improvement in the efficiency of the supply chain and that this improvement can significantly motivate enterprises to increase R&D investment. Although the improvement of supply chain efficiency has no significant effect on improving companies' innovation efficiency, it can have a positive impact on innovation efficiency through the regulating role of R&D investment.

This research shows several limitations such as single industry and few companies involved, but it analyses the impact of P2P supply chain financing on R&D investment, and companies' innovation efficiency and broadens the research field of P2P supply chain financing.

This article provides a theoretical direction for listed companies to invest in P2P platforms and achieve supply chain management. The research on the regulating role of this article provides a new way of thinking for the study of enterprise innovation.

This paper analyses the impact of the core enterprise investment in P2P on R&D investment and its subsequent impact on the companies' innovation efficiency, thus broadening the research field of P2P supply chain financing.

This study examines the innovation-efficiency linkage for Indian and Chinese manufacturing and service firms.

We applied the stochastic production and cost frontier approach to determine the output and cost efficiency of the firms surveyed in World Bank enterprise surveys. We then used both unconditional and conditional propensity score matching (PSM) estimation techniques to examine the effects of innovation as well as R&D on output and cost efficiency of the firms surveyed.

The study results suggest that innovation-efficiency linkage varies between countries and sectors. Innovations significantly raise output and cost efficiency of Indian manufacturing firms, whereas innovations in Chinese manufacturing firms are cost-oriented and negatively affect output efficiency. For the service firms of both countries, innovations are significantly positively linked with output and cost efficiency. The study also suggests that R&D acts as a crucial moderator for innovation-efficiency linkage for Chinese manufacturing firms but not for Indian firms, and the interaction effects of innovations are not substantially higher in magnitude than their individual effects. Finally, conditional PSM results suggest knowledge spillover for effective innovations of Indian firms, whereas R&D is a must for substantial innovation-efficiency linkage in Chinese firms.

This study offers quite a few crucial policy decisions concerning the relationship between innovation and efficiency as well as the moderation effect of R&D on innovation-efficiency linkage. It concludes that the effects of innovation on firms' efficiency and the role of R&D as a moderator of the innovation-efficiency relationship differ between India and China across the manufacturing and service sectors.

Previous studies demonstrate that market-oriented reform has contributed significantly to China's economic growth from the efficiency-based economic view. But some argue that state-owned firms have access to policy information, scarce resources, and government support, and thus state-owned firms might foster innovation. This study tries to find out either market force or state ownership helps improve firms' R&D efficiency.

Using data from China's high-tech industry, we employed the fixed-effect stochastic frontier model and the spatial panel Han-Philips linear dynamic regression model to investigate the relationship between market-oriented reform and the dynamic evolution of R&D efficiency in both temporal and spatial dimensions. Moreover, we examined whether the relationship is affected in a state-owned economy and an industry protection environment.

The results indicate the following: (1) the R&D efficiency of China's high-tech industry has improved steadily and has converged gradually across its regions during the market-oriented reform; (2) the marketization degree is positively correlated with R&D efficiency and its regional convergence; (3) the state-owned economy and industry protection have significantly weakened the ability of market forces to shape R&D efficiency — i.e. they reduce, rather than enhance, R&D efficiency.

This investigation helps understand the drivers of R&D efficiency in transition economies, and the findings are also helpful in defining the boundaries and constraints of market forces.

This study aims to examine whether the pay gap between the chief executive officer (CEO) and non-executive employees affects the firm’s research and development (R&D) efficiency.

The dependent variable is the firm’s R&D efficiency, defined as a percentage increase in revenue from a 1-per cent increase in R&D spending. The main independent variable is the CEO-employee pay gap, defined as the ratio of annual total compensation for the CEO to the average of non-executive employees of the firm. The authors estimate fixed-effects models to examine the association between R&D efficiency and the pay gap between CEO and non-executive employees.

Results indicate a negative and significant association between R&D efficiency and CEO-employee pay gap, which suggests that a wider pay gap reduces employee motivation and effort, consistent with pay equity theory. We also find that the CEO-employee pay gap negatively moderates the relationship between employee pay growth and R&D efficiency

Recently enacted pay gap disclosure requirements mandated by the Dodd-Frank Act will make the disparity between CEO and non-executive compensation more salient. This study provides evidence of a firm outcome associated with that disparity.

This study is among the first to investigate the impact of the pay gap on R&D efficiency, a firm outcome not previously explored in the literature. This study also investigates CEO-employee pay gap’s role as a factor that moderates the effects of employee pay growth and institutional ownership on R&D efficiency

Countries in Africa have a common goal policy of industrialisation that is expected to be driven by investing in innovation that yields efficiency. The purpose of this paper is to investigate the technical efficiency effects arising from innovation inputs including internal R&D, human capital development (HCD), and foreign technology adoption in manufacturing firms in Africa.

This study uses cross-sectional firm-level survey data from the 2013 World Bank Enterprise Survey and the linked 2013 Innovation Follow-up Survey. A heteroscedastic half-normal stochastic frontier is used for analysing the technical efficiency effects of innovation inputs of 418 firms.

This study reveals that internal R&D, and foreign technology have negative effects on technical efficiency. Notwithstanding, the combination of foreign technology and internal R&D, and foreign technology and HCD reinforce each other’s effects on technical efficiency.

This study provides evidence that whereas individual innovation inputs may not yield positive efficiency outcomes, the combination of absorptive capacity enhancing inputs comprising internal R&D and HCD with foreign technology is vital for enhancing technical efficiency in manufacturing firms in Africa. This study offers important lessons for managers in manufacturing firms in Africa.

This study is virtually the first to investigate the relationship between innovation inputs and efficiency in Africa. This study demonstrates that investing in foreign technology in isolation from absorptive capacity enhancing innovation inputs diminishes efficiency. HCD and internal R&D are imperative for building absorptive capacity that enhances efficiency outcomes arising from foreign technology.

The authors aim to discuss the impact of research and development (R&D) internationalization on emerging market enterprises' (EMNEs') innovation efficiency, as well as the moderating effects of top management team (TMT) human capital.

The authors empirically tested the hypotheses based on Chinese listed manufacturing company data from 2008 to 2017.

R&D internationalization helps to increase EMNEs' innovation efficiency. Incorporating TMT human capital into this framework, the authors found that international experience, education level and technical background would all strengthen the above relationship.

First, the authors contribute to the R&D internationalization literature by providing the first empirical evidence that R&D internationalization will influence EMNEs' innovation efficiency. Second, this study enriches the research results on the driving factors of enterprise innovation efficiency and expands the related research results on the relationship between R&D internationalization and production efficiency. Third, the research highlights the prominent position of TMT human capital in the relationship between R&D internationalization and EMNEs' innovation efficiency, which strengthens the contextual characteristics of the “R&D internationalization-innovation performance” framework.

First, this study assesses the link between research and development (R&D) expenses and firm efficiency. Second, this study explores how family control moderates the link between the two.

This study uses two measures of time-based firm efficiency, namely, a window slacks-based measure (WSBM) and a window epsilon-based measure (WEBM) of data envelopment analysis (DEA). Then, 216 firm-year observations are analyzed in the Taiwanese cultural and creative industries from 2005 to 2017.

This study finds that R&D expenses significantly worsen firm efficiency, and that family control positively moderates this effect. A further test separating the sample into family-controlled and nonfamily-controlled firms indicates that R&D expenses negatively affect the efficiency of nonfamily-controlled firms but positively affect that of family-controlled firms.

The existing literature has examined the link between R&D expenses and corporate performance. However, the process by which R&D expenses affect corporate performance from a production perspective remains unknown.

Overall, this study provides insights for policymakers to scrutinize resource management and R&D expenses from the production and resource-based perspectives.

Deriving a measure of efficiency of public-funded organizations (primarily not-for-profit organizations) and ranking these efficiency measures have been major subjects of debate and discussion. The purpose of this paper is to evaluate the relative performances of public-funded research and development (R&D) organizations functioning across multiple countries working on similar research streams. The authors use multiple measures of inputs and outputs for this purpose.

The authors use the data envelopment analysis (DEA) as the primary methodology of analysis The keywords highlighting the major research areas in the field of non-metrology, conducted by National Physical Laboratory (NPL), India, were utilized to select the global comparators working on similar research streams. These global comparators were three R&D organizations located in the USA and one each located in Germany and Japan. The relative efficiencies of the organizations were assessed with the following output variables – external cash flow, and the numbers of technologies transferred, publications and patents; and the following input variables – amount of grants received from the parent body, and the number of scientific personnel working in these public R&D organizations. The authors follow the output-oriented measure of efficiency at constant return to scale and variable return to scale, along with scale efficiencies.

The performance of NPL, India under multiple dimensions has been evaluated relative to its global comparators – the National Institute for Materials Science, Japan; the National Renewable Energy Laboratory, USA; Fritz Haber Institute of the Max Planck Society, Germany; the National Centre for Atmospheric Research, USA; and the Oak Ridge National Laboratory, USA. The study indicates suggested measures and a set of targets to achieve the best possible performance for NPL and other R&D organizations. In most cases of efficient local but not so efficient global efficiency scores indicate that, on an average, the actual scale of production has diverged from the most productive scale size.

The approach highlights the utilization of the DEA methodology for relative R&D performance assessment of global comparators. The discriminatory analysis has brought into sharp focus the dichotomy between local efficiency and global efficiency scores of these units and issues of scale size and regional disparities. The outcome of this approach is dependent upon correct selection of input and output variables and data availability.

The study results have profound implications for the management of public R&D institutions across nations working on similar-focused research streams, but functioning within different societal, economic, and political contexts.

The present work, being perhaps one of the few multinational studies of relative performance assessment of pubic-funded R&D organizations working on similar research streams, signifies the relevance of such an approach in the field of R&D/innovation management. This has opened up new avenues for further research in this area.

Open innovation (OI) has become increasingly popular as an enterprise strategy in both industry and academia, and has been adopted, at least in part, by many companies. Despite this popularity, there is a dearth of evaluation of OI efficiency and a lack of suitable quantitative indices. The paper aims to discuss these issues.

In this study, the authors used both data envelopment analysis (DEA) and Malmquist techniques to compare the pre- and post-transition levels of performance achievement of Procter & Gamble (P&G), a widely recognised and public early adopter of OI, with a group of its main competitors.

Most detailed analysis of the time-course revealed that the innovation efficiency of P&G improved rapidly and substantially after its embracing of OI, an effect we term the “open rise”. However, there is also a transient decline in R&D efficiency at the beginning of OI adoption (“open dip”) and an unexpected and marked decline (“open drop”) after the peak positive effect.

The quantitative methods appear to meet the needs identified in the preceding literature for more quantitative approaches to the measurement of OI.