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This paper presents a framework for implementing R&D project. Fundamental R&D investment process framework and success factors while considering risks and uncertainties of project will be described to illustrate an efficient and effective R&D management system in a firm.

To explore the effects of contingency and the position of R&D professionals on R&D performance measurement.

Adopting a bottom‐up approach that reflects R&D professionals' opinion, this study investigated the relationship between preferred performance measures and contingency factors (project phase, structure, technology, and the position of R&D professionals). Fifty two senior researchers at a Korean telecommunications laboratory were surveyed.

The results suggest that the goal achievement dimension and technology factors are more important in earlier phases of an R&D project while production, economy/market, and external evaluation factors become more significant in later stages.

The findings suggest that the weights of R&D performance measures should be aligned with the contingency factors and the position of R&D professionals.

While most studies have adopted a macro‐level approach, this study examined R&D performance measurement at the micro‐level. While most previous works are conceptual, this study made an empirical investigation that enables statistical tests. And the findings provide useful recommendations for human resource managers who are interested in measuring the performance of technology innovation.

Research and development (R&D) projects are often pursued through a project portfolio (PP). R&D PPs involve many stakeholders, and without proactive management, their interactions may lead to conflict risks. These conflict risks change dynamically with different stages of the PP life cycle, increasing the challenge of PP risk management. Existing conflict risk research mainly focuses on source identification but lacks risk assessment work. To better manage the stakeholder conflict risks (SCRs) of R&D PPs, this study employs the dynamic Bayesian network (DBN) to construct its dynamic assessment model.

This study constructs a DBN model to assess the SCRs in R&D PP. First, an indicator system of SCRs is constructed from the life cycle perspective. Then, the risk relationships within each R&D PPs life cycle stage are identified via interpretative structural modeling (ISM). The prior and conditional probabilities of risks are obtained by expert judgment and Monte Carlo simulation (MCS). Finally, crucial SCRs at each stage are identified utilizing propagation analysis, and the corresponding risk responses are proposed.

The results of the study identify the crucial risks at each stage. Also, for the crucial risks, this study suggests appropriate risk response strategies to help managers better perform risk response activities.

This study dynamically assesses the stakeholder conflict risks in R&D PPs from a life-cycle perspective, extending the stakeholder risk management research. Meanwhile, the crucial risks are identified at each stage accordingly, providing managerial insights for R&D PPs.

The essential investments in new product development (NPD) made by industrial companies entail effective management of NPD activities. In this context, performance measurement is one of the means that can be employed in the pursuit of effectiveness.

New business practices and the globalization of markets force firms to take innovation as the fundamental pillar of their competitive strategy. Research and Development (R&D) plays a vital role in innovation. As technology advances and product life cycles become shorter, firms rely on R&D as a strategy to invigorate innovation. R&D project portfolio selection is a complex and challenging task. Despite the management's efforts to implement the best project portfolio selection practices, many projects continue to fail or miss their target. The problem is that selecting R&D projects requires a deep understanding of strategic vision and technical capabilities. However, many decision-makers lack technological insight or strategic vision. This article aims to provide a method to capitalize on the expertise of R&D professionals to assist managers in making informed and effective decisions. It also provides a framework for aligning the portfolio of R&D projects with the organizational vision and mission.

This article proposes a new strategic approach for R&D project portfolio selection using efficiency-uncertainty maps.

The proposed strategy plane helps decision-makers align R&D project portfolios with their strategies to combine a strategic view and numerical analysis in this research. The proposed strategy plane consists of four areas: Exploitation Zone, Challenge Zone, Desperation Zone and Discretion Zone. Mapping the project into this strategic plane would help decision-makers align their project portfolio according to the corporate perspectives.

The new approach combines the efficiency and uncertainty dimensions in portfolio selection into an integrated framework that: (i) provides a complete representation of the stochastic decision-making processes, (ii) models the endogenous uncertainty inherent in the project selection process and (iii) proposes a computationally practical and visually unique solution procedure for classifying desirable and undesirable R&D projects.

The paper aims to evaluate the real research and development (R&D) options value through the proposed model that can jointly consider the two types of risk management activities, i.e. hedging risks and making use of risks. Hedging is an important risk‐management tool that can diversify R&D risk internally since R&D organizations cannot transfer technological risks to another entity by conventional loss financing methods. Making use of risks means R&D organizations can benefit from proactively managing risks, and then can create management‐flexibility value from the real option reasoning viewpoint.

Using the real options pricing approach, the paper provides an applicable assessment method for R&D projects that can jointly consider the aforementioned two types of risk management activities. The paper also investigates the value‐enhancing effects of R&D risk management activities via interviews survey and secondary data analyses in the pharmaceutical industry of Taiwan.

Through numerical analyses, the results indicate that the hedging management can serve to be effective mechanisms of risk reduction as well as value enhancement for R&D projects. Additionally, the value‐enhancing effect of hedging management is more significant for those R&D projects with even higher risk‐level. The results of empirical study also are consistent with the model prediction.

To achieve great performance of R&D risk management, R&D organizations need to implement both the types of risk management activities. By this real‐options valuation approach incorporating together those risk management activities, R&D projects portfolio can be evaluated adequately.

The purpose of this paper is to study the effect of a critical subsystem development indigenously on the outcome of an Indian defence R&D project. Indigenous development of the critical subsystem requires the development of a number of technologies; hence the study is taken up for indigenously development of critical subsystem.

A simulation-based approach is used in this paper for studying the effect of indigenization decisions. A defence R&D project with the critical subsystems is modeled in Graphical Evolution and Review Technique (GERT) networks, and simulated in Arena simulation software using discrete event simulation model. The simulation model is thereafter experimented with decision options for the critical subsystem. Data were collected from the project management office (PMO) of short range homing guided missile (SRHGM) for this simulation study.

It has been found in this case that timely development of technology plays a key role in the Indian defence R&D projects. While indigenization of critical components reduces cost of development, the trade-off lies in much increased project development time. It is imperative that project teams should identify critical components early and work out appropriate strategies of indigenous development to avoid time overrun of the projects.

The accuracy of results of the study could perhaps be affected on account of the extent of data forthcoming from the PMO. However, GERT framework presented in this paper is realistically derived from the practices used in the SRHGM project.

The study would help the project teams to identify critical subsystems early and work out appropriate strategies of indigenous development to avoid time overrun of the projects. This study would also make the project as well as the R&D teams aware of the causes for delays and cost overruns, and assist to deliver a product meeting end-user requirements.

Schedule and cost overrun analysis for a typical research & development (R&D) project is necessary to identify and mitigate the non-feasible alternatives at the design stage. Typically, this should include an analysis of technological and economic factors of R&D project. This paper aims to discuss these issues.

This research proposes an integrated analytic network process (ANP) and reusable system dynamics (SD) model for a quick and strategically consistent decision making. The technological and economic factors of R&D project were first identified and compiled through a systematic literature review. An ANP model was first developed for calculating Risk Priority Index (RPI) for set of technological and economic factors. The computed RPI are considered as an input to SD models. Two SD models (technological and economic) are developed to undertake a detailed investigation on effect of individual factor on schedule and cost overrun. The approach is exemplified for a case of government R&D project in India.

ANP identifies “Testing & qualification facility” and “Raw material availability” as the highest RPI factors. A detailed sensitivity analysis of SD models suggests that technological factors such as “Design Changes,” “Hidden Activities,” and “Lack of Expertise” and economic factors such as “Project delays,” “Unexpected incidents” and “Conflicts” have the highest influence on schedule and cost overrun.

The outcomes of this research can help managers to estimate the severity of various technological and economic factors on cost and schedule overrun and develop an adequate risk mitigation contingency plan.

In case of R&D projects where systems are being developed for the first time, changes are inevitable, and hence schedule and cost management plays a very important role in its success. This paper proposes an integrated reusable approach of ANP and SD for analyzing the influence of technological and economic factors on schedule and cost overrun of R&D project.

The effect of global integration of businesses and interchange of ideas and technology through internet has many facets. Increase in economic recessions and decrease in research funding has forced both private and public sector research organizations to introduce measures of self-sustainability. Enhancing research and development (R&D) productivity of researchers can be one of those measures. The purpose of this paper is to attempt toward identifying and analyzing those factors of productivity that may be related to the manpower in R&D.

Based upon the theoretical background and the nature of data available, this empirical study has been carried out as a case study for a public sector research laboratory. The extent of involvement in research projects have been analyzed with respect to the R&D outputs generated by the researchers, which if found to be positively related, may be focussed upon, for increasing productivity of manpower in R&D. Several other determinants of R&D productivity were identified from the literature review and were analyzed in association with the “involvement.” “Robust Regression” technique was used for the statistical analysis.

It was found that the R&D productivity of researchers has a positive correlation with their extent of involvement in the R&D projects.

The result may help in creation of the policies for enhancing organizational self-sustainability.

Several prior studies have been conducted with different determinants of R&D productivity but hardly any studies were found considering “extent of manpower involvement in research projects.” This study can be useful for public sector research organizations to relate the findings with their endeavors of enhancing R&D productivity.