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This paper aims to shed light on the linkage between research and development (R&D) networks and public funding presented in a given period by using network-based evaluation tools as a means of exploring the relational dimension in public projects designed to foster technology R&D activities.

This research uses co-occurrence network analysis of relevant public projects to assess how technological associations might occur within the R&D activities of given publicly funded projects as well as conducts correlation analysis to understand the extent to which linkages of R&D activity in technology fields are related to public expenditure.

Core technology fields, regarded as eligible to receive continued public funding, are critical for enhancing competitiveness and sustainable growth at the nationally strategic technology level. Thus, the relationship between R&D and the level of government funding for these fields is generally perceived as strong. However, a few technology fields, which did not actively form specific network relationships with other technology fields, are considered to exceptionally drive the largest government support. This trend indicates that the government-funded R&D should be designed and managed not only to curb the inefficiencies existing in the current funding programs but also to achieve the appropriateness for further technology development.

Despite the comprehensive findings, this study has several limitations. First, it is difficult to control any confounding factors, such as the determinants and constraints of the government budget allocation and expenditure decisions over S&T areas, strategic frameworks for public investment and evolving policy landscapes in technology sectors, which lead to bias in the study results. Second, this study is based on a narrow, single-year data set of a specific field of projects supported by the Korean government’s R&D program. Therefore, the generalization of findings may be limited. The authors assumed that influences caused by confounding variables during the initial phase of the public funding schemes would not be significant, but they did not take into account possible factors that might arise coincident with the subsequent phase changes. As such, the issue of confounding variables needs to be carefully considered in research design to provide alternative explanations for the results that have been ruled out. The limitations of this study, therefore, could be overcome by comparing the outcome difference between subsidized and non-subsidized R&D projects or evaluating targeted funding schemes or tax incentives that support and promote various areas of R&D with sufficiently large, evidence-based data sets. Also, future research must identify and analyze the R&D activities concerning public support programs performed in other countries associated with strategic priorities to provide more profound insight into how they differ. Third, there are some drawbacks to using these principal investigators-provided classification codes, such as subjectivity, inaccuracy and non-representation. These limitations may be addressed by using content-based representations of the projects rather than using pre-defined codes. Finally, the role that government investment in R&D has played in developing new science and manufacturing technologies of materials and components through network relationships could be better examined using longitudinal analysis. Furthermore, the findings suggest the need for further research to integrate econometric models of performance outcomes such as input–output relations into the network analysis for analyzing the flow of resources and activities between R&D sectors in a national economy. Therefore, future research would be helpful in developing a methodological strategy that could analyze temporal trends in the identification of the effects of public funding on the performance of R&D activity and demand.

Public funding schemes and their intended R&D relationships still depend on a framework to generate the right circumstances for leading and promoting coordinated R&D activities while strengthening research capacity to enhance the competitiveness of technologies. Each technology field has a relatively important role in R&D development that should be effectively managed and supervised to accomplish its intended goals of R&D budgeting. Thus, when designing and managing R&D funding schemes and strategy-driven R&D relations, potential benefits and costs of using resources from each technology field should be defined and measured. In this regard, government-funded R&D activities should be designed to develop or accommodate a coordinated program evaluation, to be able to examine the extent to which public funding is achieving its objectives of fostering R&D networks, balancing the purpose of government funding against the needs of researchers and technology sectors. In this sense, the examination of public R&D relations provides a platform for discussion of relational network structures characterizing R&D activities, the strategic direction and priorities for budget allocation of the R&D projects. It also indicates the methodological basis for addressing the impact of public funding for R&D activities on the overall performance of technology fields.

The value of this work lies in a preliminary exploratory analysis that provides a high-level snapshot of the areas of metallurgy, polymers/chemistry/fibers and ceramics, funded by the Korean Government in 2016 to promote technological competitiveness by encouraging industries to maintain and expand their competencies.

The paper develops a model for enhancing R&D productivity for Indian public funded laboratories. The paper utilizes the productivity data of five Council of Scientific and Industrial Research (CSIR) laboratories for analysis and to form the constructs of the model.

The weighted average method was employed for analyzing the rankings of survey respondents pertaining to the significant measures enhancing R&D involvement of researchers and significant non-R&D jobs. The authors have proposed a model of productivity. Various individual, organizational and environmental constructs related to the researchers working in the CSIR laboratories have been outlined that can enhance R&D productivity of researchers in Indian R&D laboratories. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to find the predictability of the productivity model.

The organizational factors have a crucial role in enhancing the R&D outputs of CSIR laboratories. The R&D productivity of researchers can be improved through implementing the constructs of the proposed model of productivity.

The R&D productivity model can be adapted by the R&D laboratories to enhance researchers’ R&D involvement, increased R&D outputs and achieving self-sustenance in long run.

The R&D laboratories can initiate exercises to explore the most relevant factors and measures to enhance R&D productivity of their researchers. The constructs of the model can function as a guideline to introduce the most preferable research policies in the laboratory for overall mutual growth of laboratory and the researchers.

Hardly any studies have been found that have focused on finding the measures of enhancing R&D involvement of researchers and the influence of significant time-intensive jobs on researchers’ productivity.

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.

This paper intends to explore the measure for aligning the goals of researchers toward achieving organizational R&D targets. The paper also explores the significance and ordering of R&D outputs and the factors that influence generation of R&D outputs, from the perspective of researchers working in the Indian public sector organizations.

Data were collected in five Indian R&D laboratories, and weighted average method Spearman correlation coefficient and rank regression were utilized for the analysis.

The findings indicated that various groups of researchers prefer to target different R&D outputs and not all the factors are considered as equally significant in influencing the generation of R&D outputs. Further, the R&D organization should include preferred real factors while policy making for achieving collaborative efforts toward fulfilling organizational objectives. The set of selected R&D outputs and influencing factors were also ordered according to the average rankings given by the researchers.

The findings can help R&D managers to identify the expectations of the researchers and include their preferences in R&D Planning. The study could be extended to a larger dataset of researchers working in other government as well as private R&D organizations.

Hardly any studies were found that explored the preferences of researchers with respect to R&D outputs and influencing factors with respect to the Indian public sector R&D laboratories.

The authors investigate the relationship between the structure and the functioning of scientific and technical (S&T) personnel and the quality research and development (R&D) performance output of laboratories functioning under the Council of Scientific and Industrial Research (CSIR), India. The purpose of this paper is to examine how rapid economic and social changes and the demand for better accountability are addressed by public R&D institutions in a specific developing economy.

The authors use the functions performed by the S&T personnel as indicators of their tacit knowledge. The authors use data from 27 different CSIR laboratories to analyze the specific functions carried out by knowledge workers (S&T personnel) in order to gauge the internal strengths and weaknesses of individual laboratories in different functional areas. The authors use the following measures to tap the quality R&D performance of these laboratories – number of Indian patents filed and granted, number of foreign patents filed and granted, and the number of published papers figuring among the top 50 CSIR publications in specific research areas over an extended period of 11 years (2003-2004 to 2013-2014).

The findings show that there is no readymade formula for identifying improvements in quality performance by a research laboratory, given a particular set of S&T worker profile in terms of the six functions defined in the study. The top-performing laboratories have excellent patent as well as publication record reinforcing the point that innovation encompasses both basic and applied research with success depending upon strategically emphasizing the different components of the innovation process.

The scope of the present research work is limited by the choice of the quality R&D performance measures adopted in the study that could be further expanded to better tap the social accountability of these public-funded institutions. In addition, inclusion of all CSIR laboratories in the study framework would add value to the study findings. The research highlights the importance of tacit knowledge management and organizational learning as central features of strategic organization development for technology practices incorporating R&D work, the support of pilot plants, experimental field stations, and engineering and design units.

The paper has particular implications for the leadership and management of public R&D organizations and public policy formulation for innovation in an emerging developing economy context.

This study extends the extant literature by drawing upon the role of tacit knowledge and organizational learning to inform the empirical research on managing public R&D and the innovations that result from it, in a particular emerging economy context, that is, India.

The purpose of this research is to conceptualize, define and measure resource orchestration capabilities of R&D teams pursuing advanced scientific research and technological innovation at public-funded R&D organizations in India.

A series of five mutually exclusive studies were designed over two years to develop and validate the ROCI scale within public research and development (R&D) organizations pursuing advanced scientific research and technological development in India. The first three studies address the refinement, reduction and rationalization of items for measuring the ROCI construct. The next study explores the factor structure underlying the ROCI construct whereas the subsequent one confirms the three-factor structure within empirical settings.

The resource orchestration capability towards innovation (ROCI) construct reflected through three sub-dimensions namely – adaptive structuring capability (ASC), synergistic leveraging capability (SLC) and decentralized decision-making capability (DDC), each loaded with their respective items can be used for capability measurement in public-funded R&D organizations.

R&D managers can use this ROCI scale to measure, monitor and improve the innovation-oriented resource orchestration capabilities of their R&D teams and help them improve their innovation performance.

This research contributes to the extant literature on resource orchestration for innovation management in three unique and original ways – theoretically-grounded conceptualization, empirical measurement and rigorous validation through multiple studies conducted in public-funded R&D organizations in India.

This study aims to conceptualize and measure strategic leadership capabilities within research and development (R&D) teams pursuing high-tech innovation at public-funded R&D organizations in India.

A rigorous five-stage multi-method approach defines, conceptualizes and validates the core construct “strategic leadership capabilities for innovation” (SLCI). The first stage correlates the insights generated from theoretical analysis and expert opinions on the importance of leadership for innovation. The second study identifies a three-dimensional factor structure underlying the SLCI construct and the third validates it through a confirmatory factor analysis. Replication provides additional validation.

SLCI emerges as a three-dimensional construct with sub-dimensions: dynamic envisioning, ambidextrous resource utilization and empowering support for innovation.

Conceptualization of the SLCI construct and its measurement through a 15-item scale that has been empirically validated in the public-funded R&D organizations in India.

The authors contribute to the literature on leadership by investigating how characteristics of principal investigators (PIs) affect innovation performance, and how collaborative and non-collaborative projects moderate this relationship within the context of inter-organisational research projects.

The authors analysed panel data from the National Science and Technology Information Service on 171 research projects within a biomedical and regenerative medicines programme overseen by the Korea Health Industry Development Institute. The authors used a hierarchical regression model, based on the ordinary least squares method, to examine the relationship between PI characteristics and performance, considering both quantity and quality.

The results show that the characteristics of PIs have diverse effects on the quantity and quality of innovation performance. Gender diversity within PIs negatively affects the quality of innovation performance, while the capacity of PIs positively influences it. Moreover, the degree of PI’s engagement is positively associated with the quantity of innovation performance but does not have a significant relationship with the quality of performance. In terms of moderating effects, collaborative projects with multiple leaders seem less reliant on PI capacity than non-collaborative projects led by a single leader, in terms of innovation performance.

The results contribute significantly to the literature on innovation management by examining the role of leadership in collaborative environments to enhance innovation performance, addressing the need for empirical evidence in this area. Analyses of PI characteristics in government R&D management can lead to improved team performance, more efficient processes and effective resource allocation, ultimately fostering innovation.

Council of Scientific and Industrial Research (CSIR)–National Metallurgical Laboratory (CSIR–NML) has launched a number of initiatives in different perspectives of e-Government. The “Mandays-Involvement” website was implemented by the laboratory in Government-to-Employee (G2E) perspective i.e. facilitating its research and development (R&D) manpower by providing data with respect to their own performance parameters through a single window. The development and implementation of the website had two major objectives : (1) to provide a system to the researchers for tracking and improving their own performance with respect to mandays and external cash flow generation and (2) to equip the management with a tool to enhance the organizational performance and enable optimum employee utilization.

Software Development Life Cycle approach was followed for the web-based system development and iterative model was used. Open source web development tools i.e. Php, My-Sql and CSS were used for the system development.

The new system helped in detailed profiling of current and future assignment of the researchers so as to have a check over preference-based allocation of work and providing equal opportunities of work to all.

The percentage average mandays utilization was stabilized after the implementation of the website. The percentage under and over engagements of researchers in R&D projects was controlled and reduced.

The system outputs are utilized for R&D Team formation, Project approvals and Annual Performance Evaluations.

This new information system acts as a decision support system that helps the management to align its organizational policies toward the Future Research Projects and R&D manpower.

This study aims to evaluate the effectiveness of national and international R&D support programmes on firms’ technology scouting, defined as firms’ use of external knowledge sources.

Drawing on a unique data set on R&D support programmes for small and medium-sized enterprises (SMEs) operating in both manufacturing and service sectors across 28 European countries, this study reports treatment effects estimated by the copula-based endogenous switching model, which takes into account unobserved firm heterogeneity.

Empirical results indicate that R&D support programmes have heterogeneous effects on technology scouting. In particular, a crowding-out effect arises in the case of informal sources of external knowledge, whereas additional effects are reported for formal, strategic sources.

For informal sources of external knowledge, a random distribution of R&D measures would have a substantially larger effect rather than using current selection criteria.

To the best of the authors’ knowledge, this is the first study to explore the policy effects on technology scouting applying a copula-based endogenous switching model. Most cross-sectional empirical studies use matching estimators, although their main disadvantage is the selection on observables.