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For a fundamental research project examination two main issues are considered: the financial aspect and the research environment structure. The kind of outcome from each scientific project should be carefully planned and the funding should also follow some essential steps. The same ones considered for a common mutual fund shares investment.

Strategic Foresight Introduction

Risk analysis and the fund investment history are indispensable to guide a decision. Moreover, for a customer, potential donor or stakeholder involved in the budget approval is very important to feel satisfied not only with the project but the possible results and their impact in business or society. This impact perception must be clearly defined for each study and presented in a friendly language to reflect reliability. The suggested strategy evaluation on scientific investment return can also be part of science. A ranking of acceptable results for a specific research project and its complex variables could be better defined.

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The adequate limits included in an inspection process may be useful in the institutional routine. If the results of a project cross these earlier defined limits, the strategy policy may possibly become vulnerable. A strategy with a high level of susceptibility jeopardizes the expected outcomes.

Certain sensible elements, with respect to research institutions appeal, comprise the policy ambiance, innovative process network, expertise fields and their consequences and new research application spots. These elements core may constitute a scientific and technologic network, integrating different qualified competences yielding more competitive atmosphere for room and resources seeking. Knowledge acquisition and technological assignment allied to human resource training and political capability is considered as an important strategic role in any research institute.

Again, the need of an administrative tool applied to research programs or projects and their potential outcomes is crucial to succeed. Thus, new indexes or indicators are necessary to be developed to a research scope. There is no evidence of such index adopted in private or public research projects evaluation in spite of its risk factors and perspectives. The aim of the present study was to propose an expected risk measure of return index adapted to scientific projects. The proposed indicant addressed as RoSI Return on Scientific Investment is based on the ulcer index 9 created to characterize the financial investment risk, a modeling tool based on variables that interact in semi-quantitatively environments.

To propose a measure index of expected risks to evaluate and follow up the performance analysis of research projects involving financial and adequate structure parameters for its development. This index is a stock market risk measure devised by Peter Martin 9 , in It was established as a measure of volatility in downward direction drawdowns that occurs in a determined time or era.

The ulcer index is defined by the root mean square of these values expression. The calculation is robust for the sampling rate used and the percentage may be expressed as positive or negative values. This concept is showed in three profit curves strategies Figure 2. The method presented herein measures scientific projects performance exploring distinct aspects or earlier established milestones.

The main goal is to reach a pricing proceeding useful for scientific projects managing.

Semi-quantitative computational modeling approach. Artificial neural network applied to theory of variable interaction with animate causal diagrams. These diagrams are graphical tools that enable the visualization of causal relationships between all variables in a determined system. Moreover, this approach provides a systematic interpretation of a causal diagram and permits the creation of models regarding natural and human science.

Foresight Defs and Frameworks - Global Foresight

Distinct levels or states and rates or actions are considered to occur in a determined time-lapse. Despite constant values, both are necessary for the data representation and to integrate the results provide by the system. The variable quantification is calculated through the changing rate that alters a previous value level. On the other hand, levels are also defined by early effects accumulation and can be traced even in a non-activity scenario. Rather, the developed semi-quantitative model comprises the causal relationships through a specific topology in an artificial environment.

This environment is considered as an interactive framework and will be available to be explored by its users. In this context, modeling seems to act as a managing process component. Therefore, the pricing of a project is a given variable originated from this semi-quantitative model Figure 3.

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The project pricing depends on diverse outcomes, such as publication quality, funding, patent registry and others. The modeling stands for project risk analysis simulation represented by possible risk variables characterized in an independent structure or network.

Additionally, these project models may interact with other levels of the research grid where different projects are considered to have a common subject interface. Choosing variables criteria. The definitions of the several variables to fulfill distinct levels of the semi-quantitative model are based on important concepts regarding transdisciplinarity.

Rapid Foresight Metodology

This concept comprehends a scientific approach for the creation of a knowledge unity. It articulates elements and diverse research groups beyond and between the disciplines and integrates new or revised perspectives into our ways of thinking.

These variables comprise not only the professional or technical skills of a person, but include personnel character attributes as well as tacit knowledge compounds. Other set of variable types are related with established milestones involving crucial parts of a project to accomplish its objectives. Lastly, an acute interface among these defined levels and possible interactions between projects pertaining to different research groups are also considered by the system. Innovation for Development.

Directorate for Science, Technology and Industry; Corporate foresight at the strategicresearch institutes. Recent Developments in Foresight Technology. Qualitative futures research for innovation. Delft: Eburon Academic Publishers; The involvement of middle management in strategy development - Development and implementation of a foresight-based approach. Regionalny Foresight Gospodarczy. Metodologia i instrumentarium badawcze [Regional Economic Foresight.

However, the disciplines of foresight are not well articulated or disseminated across domains, leading to re-inventions and practice that does not make best use of experience in other domains. The methodological development of foresight is an important task that aims at strengthening the pool of the tools available for application, thereby empowering the actors involved in foresight practice. Elaborating further on methodological issues, such as those presented in the present book, enables the actors involved in foresight to begin to critique current practice from this perspective and, thirdly, to begin to design foresight practice.

After an introductory section, Part II considers theorizing about foresight methodologies. JavaScript is currently disabled, this site works much better if you enable JavaScript in your browser. Buy eBook. Buy Hardcover. Are you sure you want to Yes No. Browse by Genre Available eBooks Show More. Chaiyatorn Limapornvanich at National Innovation Agency.

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No Downloads. Views Total views. Actions Shares. Embeds 0 No embeds. No notes for slide. An overview of foresight methods 1. A taster only 4. Context: why foresight? Definition The ability to take a forward view and use the insights gained in organisationally useful ways Richard Slaughter, Foresight International 8.

Change Ecosystem 9. This is a common reaction when people are asked to deal with that ecosystem in the strategy process Think tomorrow is going to be more of today, and assume a linear future Are not prepared for the unexpected or the unfamiliar Prefer quantitative over qualitative information Frameworks for Challenging The goal: futures ready strategy Strategy that is flexible enough to allow organisations to be agile in their response to future change.