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Pre-commercial procurement (PCP), introduced by the European Commission in 2007, is the most important purchasing procedure available to the European Union public sector to solicit innovative solutions from the business sector. As such solutions are not yet in the market, they first require research and development (R&D) activities. PCP is concerned with procuring R&D services only, and typically consists of three phases. This paper aims to discuss how the budget available to the contracting authority (CA) may be optimally allocated along such three phases.

The paper is mostly theoretical and the CA is assumed to maximise the overall probability of success in the PCP, that is the probability of receiving at least one successful proposal at the end of the procedure.

The main finding of the paper suggests that, for a CA, the optimal budget allocation across the three phases of the PCP depends on how likely it is to receive successful proposals in various stages of the procedure, as well as on the rewards paid to the invited companies.

In this paper, the author proposes a methodology for the optimal budget allocation of a CA and discusses how the approach could be practically implemented, pointing out its potential difficulties.

The main social implication of the findings is represented by the best use of the available budget, hence taxpayers’ money.

To the best of the author’s knowledge, no existing paper has discussed the optimal budget allocation in a PCP as in this work.

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 electric utility industry, unlike most other technology‐intensive industries, does not spend much money or effort on research and development. Many utilities do not possess an in‐house R&D facility, nor is there an R&D line item in their budgets. Over the last several decades the rate of change in the electric utility industry has been very slow and in‐house R&D efforts have not been required. As the rate of change in the industry is beginning to change, the need to pursue R&D is increasing. The electric utility industry is responding to this increasing requirement by increasing R&D budgets, and in some cases re‐initiating the R&D process within individual utilities. The purpose of this paper is to focus on R&D portfolio management efforts of various actors from different industrial sectors, to find out the best practices by using benchmarking method.

The paper used case study approach and on‐site interviews as research methods.

The authors found that R&D management is in its infancy in the electric utility sector, while the methods established in the manufacturing sector are applicable there.

This study is exploring R&D management in the electric utility sector and contributes to the service innovation research stream.

Firms engaged in new product development (NPD) have to achieve a balanced portfolio of NPD projects. Despite the large number of models purporting to support portfolio optimization, most of them do not take into account political bias in project selection decisions. This paper aims to analyze approaches of organizational politics to NPD project selection and their implications for NPD portfolio management and future research.

A review is made of the current literature at the intersection between organizational politics and NPD project selection. With regard to the underlying assumptions of organizational politics, similarities, differences, practical implications, and research perspectives are identified.

From the paper, insights could be gained into explaining the effects of organizational politics on NPD project selection. However, the differences in assumptions that can be generally observed in organizational politics are also reflected in the studies analyzed. Future research could benefit from integrating different political and methodological perspectives.

In order to reach a balanced NPD portfolio, the potentially dysfunctional biases which characterize political processes from idea generation to project selection should be addressed. A concept of NPD portfolio management is proposed which considers the management of power and politics.

This paper contributes to a more comprehensive overview of political approaches of NPD project selection and serves as a sound basis for future research. The relevance and implications of politics for NPD portfolio management are demonstrated.

This paper seeks to compare the influence of self‐efficacy, organizational socialization and continuous improvement (CI) practices on the career aspirations of research and development (R&D) professionals in government research institutes (GRIs) and multinational corporations (MNCs) in Malaysia. R&D professionals in this study refer to a specific group of knowledge workers.

Social cognitive career theory (SCCT) was used as this study's theoretical framework. The study involved 164 respondents from GRIs and 120 respondents from MNCs in Malaysia. Descriptive statistics and inferential multiple linear regressions were used to analyse the data.

Self‐efficacy and organizational socialization were found to differ significantly in terms of their levels, and CI practices and career aspirations were not found to be significantly different between the two groups of respondents. Regression results showed MNCs reported higher explanatory power compared to that of the GRIs in terms of the variance in career aspirations.

The insights generated about the factors affecting career aspirations are based on three independent variables, namely: self‐efficacy, organizational socialization and CI practices that are most suitable for a R&D environment.

This study confirms the relevance of CI practices in the existing model of SCCT because it represents the organizational variables. HRD practitioners in both types of organizations should consider changing the work practices of R&D professionals by strengthening the quality improvement procedures because they affect the professionals' career aspirations.

Incorporating CI practices into the SCCT model is believed to be a contribution of this study to the theory.

For a nation to become a superpower, it's scientific and technological advancement is essential. Each country is exploring how to improve themselves in terms of science and technology. The authors analyzed the innovation capabilities of 35 OECD countries that have not recently joined Lithuania.

In recent years, a lot of research work has been done on trapezoidal interval type-2 fuzzy sets (TIT-2 FS), and many research works have been published. The trapezoidal interval type-2 fuzzy set helps effectively to represent the uncertainty comparatively than the type-1 fuzzy set. Taking advantage of this effectiveness, the authors extend the best multi-criteria decision making method (MCDM) for trapezoidal interval type-2 fuzzy sets. Here, ELimination and Choice Expressing REality III (ELECTRE III) method in the trapezoidal interval type-2 fuzzy set environment is proposed.

This analysis helps to the OECD countries to develop their level of innovation in the criteria. The authors are making this evaluation for the year 2018 based on the 31 criteria. Application of the proposed method expressed by evaluation of the national innovation capability problem. Based on the obtained results, the top five countries are United States, Switzerland, Canada, Germany and Japan.

The authors collected required data from different available data sources like OECD, IMD, USPTO, ITU and surveyed data reported by KISTEP. After collecting all the data from different sources, the authors calculated the standard values as KISTEP. After converting the standard values into trapezoidal interval type-2 fuzzy values, the authors construct a decision matrix based on these values. Then, the authors determined the possibility mean values and preference. Then, they calculated the concordance and discordance credibility degree values. Finally, they ranked OECD countries by the net credibility degree. The results are computed by using the MATLAB software.

Evaluating investments in new product development has been a much debated question over the last few years. Traditional methods are recognized as inadequate but there is no dominant methodology. Presents a case study, developed at Olivetti, in which new and old methodologies have been used together to analyse and evaluate an investment project in new product development. The suggested approach supports decision making better than scoring methods, and data obtained are more reliable than those provided by traditional financial methods.

This study aims to analyse the scientific relationship between technological innovation and carbon emissions. Taking the Chinese electric power industry as the empirical research object, this study examined the effect of power technological innovation on carbon emissions and proposed policy recommendations for the development of technological innovation in China.

This study first calculated the energy consumption and carbon emission level of the Chinese electric power industry from 2005 to 2018. Secondly, this study built an evaluation index system for technological innovation of electric power with six indicators: average utilisation hours of power generation equipment; power consumption rate of power plant; line loss rate; standard coal consumption for power generation; standard coal consumption for power supply; and number of patent applications granted for generation, conversion or distribution of electric power in China. Finally, from a practical point of view, the relationship between technological innovation and carbon emissions of the Chinese electric power industry from 2005 to 2018 is evaluated and analysed.

Power technology innovation has been found to have a long-term and relatively large effect on carbon emissions, and carbon emissions have a short-term and insignificant impact on power technology innovation.

This study puts forward relevant suggestions for developing technological innovation and technology transfer, which is essential to establishing a low-carbon or zero-carbon power system in China.

This study provides empirical evidence for clarifying the relationship between technological innovation and carbon emissions in the power industry and further develops research theories on technological innovation and carbon emissions.

Relevant authorities will adopt measures to promote technological innovation and development in the power sector to reduce carbon emissions.

This study built an evaluation index system with six indicators for technological innovation of electric power. The evaluation method was used to measure the technological innovation level of the Chinese electric power industry. The causal link between technological innovation and carbon emissions in China was analysed.

The purpose of this paper is to identify how project portfolio selection (PPS) methods have evolved and which approaches are more suitable for radical innovation projects. This paper addressed the following research question: how have the selection approaches evolved to better fit within radical innovation conditions? The current literature offers a number of selection approaches with different and, in some cases, conflicting nature. Therefore, there is a lack of understanding regarding when and how to use these approaches in order to select a specific type of innovation projects (from incremental to more radical ones).

Given the nature of the research question, the authors perform a systematic literature review method and analyze 48 portfolio selection approaches. The authors then classified and characterized these articles in order to identify techniques, tools, required data and types of examined projects, among other aspects.

The authors identify four key features related to the selection of radical innovation projects: dynamism, interdependency management, uncertainty treatment and required input data. Based on the content analysis, the authors identified that approaches based on different sources and nature of data are more appropriated for uncertain conditions, such as behavioral methods, information gap theory, real options and integrated approaches.

The research provides a comprehensive framework about PPS methods and how they have been evolving over time. This portfolio selection framework considers the particular aspects of incremental and radical innovation projects. The authors hope that the framework contributes to reinvigorating the literature on selection approaches for innovation projects.

Briefly reviews previous literature by the author before presenting an original 12 step system integration protocol designed to ensure the success of companies or countries in their efforts to develop and market new products. Looks at the issues from different strategic levels such as corporate, international, military and economic. Presents 31 case studies, including the success of Japan in microchips to the failure of Xerox to sell its invention of the Alto personal computer 3 years before Apple: from the success in DNA and Superconductor research to the success of Sunbeam in inventing and marketing food processors: and from the daring invention and production of atomic energy for survival to the successes of sewing machine inventor Howe in co‐operating on patents to compete in markets. Includes 306 questions and answers in order to qualify concepts introduced.