Seleção e Análise do Perfil da Produção Científica sobre o tema Seleção de Projetos.

La relevancia del proceso de Selección de Proyectos para las organizaciones ha despertado el interés de diversos investigadores para estudiar el tema y dar soporte a los gestores. En ese sentido, con la finalidad de conocer los estudios ya publicados, la presente investigación selecciona una cartera bibliográfica sobre el tema Selección de Proyectos y analiza el perfil de esas publicaciones. Se trata de una investigación descriptiva, cuya recolección de datos fue realizada en el portal de Periódicos de la CAPES. La búsqueda resultó en una muestra de 23 artículos, que componen la cartera bibliográfica analizada. Como resultados, se destacan: i) Gestión & Producción, Producción y Expert Systems with Applications son los periódicos de destaque; ii) los autores más prolíficos son Elko J. Kleinschmidt y Prasanta K. Dey, por ser los autores de la cartera bibliográfica más citada en las referencias bibliográficas de los artículos; iii) entre los artículos analizados, tres se destacan por su relevancia académica: Product innovativeness from the firm's perspective: its dimensions and their relation with project selection and performance; A fuzzy AHP application in government-sponsored R&D project selection e Integrates project evaluation and selection using multiple-attribute decision-making technique.The relevance of the project selection process for organizations has aroused the interest of many researchers in studying the subject, to support the managers. In this sense, in order to know more about the already published studies, this research selected a bibliographic portfolio on the Project Selection topic and analyses the profile of these publications. This is a descriptive research, whose data collection was performed at CAPES Journals’ website. The search resulted in a sample of 23 articles that comprise the analyzed bibliographic portfolio. The following results can be highlighted: i) Gestão & Produção, Produção and Expert Systems with Applications are the journals that stood out; ii) the most prolific authors are Elko J. Kleinschmidt and Prasanta K. Dey, since they are the most quoted authors in the bibliographic references of the bibliographic portfolio; iii) among the analyzed articles, three stand out for their academic relevance: Product innovativeness from the firm's perspective: its dimensions and their relation with project selection and performance; A fuzzy AHP application in government-sponsored R&D project selection and Integrates project evaluation and selection using multiple-attribute decision-making technique.A relevância do processo de Seleção de Projetos para as organizações tem despertado o interesse de diversos pesquisadores em estudar o tema, para dar suporte aos gestores. Nesse sentido, com a finalidade de conhecer os estudos já publicados, a presente pesquisa seleciona um portfólio bibliográfico sobre o tema Seleção de Projetos e analisa o perfil dessas publicações. Trata-se de uma pesquisa descritiva, cuja coleta de dados foi realizada no portal de Periódicos da CAPES. A busca resultou numa amostra de 23 artigos, que compõem o portfólio bibliográfico analisado. Como resultados, destacam-se: i) Gestão & Produção, Produção e Expert Systems with Applications são os periódicos de destaque; ii) os autores mais prolíficos são Elko J. Kleinschmidt e Prasanta K. Dey, por serem os autores do portfólio bibliográfico mais citado nas referências bibliográficas dos artigos; iii) dentre os artigos analisados, três se destacam por sua relevência acadêmica: Product innovativeness from the firm's perspective: its dimensions and their relation with project selection and performance; A fuzzy AHP application in government-sponsored R&D project selection e Integrates project evaluation and selection using multiple-attribute decision-making technique

An intelligent group decision-support system and its application for project performance evaluation

Purpose: In any organization there are main goals, with lots of projects designed to achieve these goals. It is important for any organization to determine how much these projects affect the achievement of these goals. The purpose of this paper is to develop a fuzzy multiple attribute-based group decision-support system (FMAGDSS) to evaluate projects' performance in promoting the organization's goals utilizing simple additive weighting (SAW) algorithm and technique for order of preference by similarity to ideal solution (TOPSIS) algorithm. The proposed FMAGDSS deals with choosing the most appropriate fuzzy ranking algorithm for solving a given fuzzy multi attribute decision making (FMADM) problem with both qualitative and quantitative criteria (attributes), and uncertain judgments of decision makers. Design/methodology/approach: In this paper, a FMAGDSS model is designed to determine scores and ranks of every project in promoting the organization's goals. In the first step of FMAGDSS model, all projects are assessed by experts based on evaluation criteria and the organization's goals. The proposed FMAGDSS model will then choose the most appropriate fuzzy ranking method to solve the given FMADM problem. Finally, a sensitivity analysis system is developed to assess the reliability of the decision-making process and provide an opportunity to analyze the impacts of "criteria weights" and "projects" performance' on evaluating projects in achieving the organizations' goals, and to assess the reliability of the decision-making process. In addition, a software prototype has been developed on the basis of FMAGDSS model that can be applied to solve every FMADM problem that needs to rank alternatives according to certain attributes. Findings: The result of this study simplifies and accelerates the evaluation process. The proposed system not only helps organizations to choose the most efficient projects for sustainable development, but also helps them to assess the reliability of the decision-making process, and decrease the uncertainty in final decision caused by uncertain judgment of decision makers. Research limitations/implications: Future studies are suggested to expand this system to evaluate and rank the project proposals. To achieve this goal, the efficiency of the projects in line with organization's goals, should be predicted.Originality/value: This study contributes to the relevant literature by proposing a FMAGDSS model to evaluate projects in promoting organization's goals. The proposed FMAGDSS has ability to choose the most appropriate fuzzy ranking algorithm to solve a given FMADM problem based on the type and the number of attributes and alternatives, considering the least computation and time consumption for ranking alternatives. © Emerald Group Publishing Limited

Outlier detection algorithms over fuzzy data with weighted least squares

In the classical leave-one-out procedure for outlier detection in regression analysis, we exclude an observation and then construct a model on the remaining data. If the difference between predicted and observed value is high we declare this value an outlier. As a rule, those procedures utilize single comparison testing. The problem becomes much harder when the observations can be associated with a given degree of membership to an underlying population, and the outlier detection should be generalized to operate over fuzzy data. We present a new approach for outlier detection that operates over fuzzy data using two inter-related algorithms. Due to the way outliers enter the observation sample, they may be of various order of magnitude. To account for this, we divided the outlier detection procedure into cycles. Furthermore, each cycle consists of two phases. In Phase 1, we apply a leave-one-out procedure for each non-outlier in the dataset. In Phase 2, all previously declared outliers are subjected to Benjamini–Hochberg step-up multiple testing procedure controlling the false-discovery rate, and the non-confirmed outliers can return to the dataset. Finally, we construct a regression model over the resulting set of non-outliers. In that way, we ensure that a reliable and high-quality regression model is obtained in Phase 1 because the leave-one-out procedure comparatively easily purges the dubious observations due to the single comparison testing. In the same time, the confirmation of the outlier status in relation to the newly obtained high-quality regression model is much harder due to the multiple testing procedure applied hence only the true outliers remain outside the data sample. The two phases in each cycle are a good trade-off between the desire to construct a high-quality model (i.e., over informative data points) and the desire to use as much data points as possible (thus leaving as much observations as possible in the data sample). The number of cycles is user defined, but the procedures can finalize the analysis in case a cycle with no new outliers is detected. We offer one illustrative example and two other practical case studies (from real-life thrombosis studies) that demonstrate the application and strengths of our algorithms. In the concluding section, we discuss several limitations of our approach and also offer directions for future research

Outlier detection algorithms over fuzzy data with weighted least squares

In the classical leave-one-out procedure for outlier detection in regression analysis, we exclude an observation and then construct a model on the remaining data. If the difference between predicted and observed value is high we declare this value an outlier. As a rule, those procedures utilize single comparison testing. The problem becomes much harder when the observations can be associated with a given degree of membership to an underlying population, and the outlier detection should be generalized to operate over fuzzy data. We present a new approach for outlier detection that operates over fuzzy data using two inter-related algorithms. Due to the way outliers enter the observation sample, they may be of various order of magnitude. To account for this, we divided the outlier detection procedure into cycles. Furthermore, each cycle consists of two phases. In Phase 1, we apply a leave-one-out procedure for each non-outlier in the dataset. In Phase 2, all previously declared outliers are subjected to Benjamini–Hochberg step-up multiple testing procedure controlling the false-discovery rate, and the non-confirmed outliers can return to the dataset. Finally, we construct a regression model over the resulting set of non-outliers. In that way, we ensure that a reliable and high-quality regression model is obtained in Phase 1 because the leave-one-out procedure comparatively easily purges the dubious observations due to the single comparison testing. In the same time, the confirmation of the outlier status in relation to the newly obtained high-quality regression model is much harder due to the multiple testing procedure applied hence only the true outliers remain outside the data sample. The two phases in each cycle are a good trade-off between the desire to construct a high-quality model (i.e., over informative data points) and the desire to use as much data points as possible (thus leaving as much observations as possible in the data sample). The number of cycles is user defined, but the procedures can finalize the analysis in case a cycle with no new outliers is detected. We offer one illustrative example and two other practical case studies (from real-life thrombosis studies) that demonstrate the application and strengths of our algorithms. In the concluding section, we discuss several limitations of our approach and also offer directions for future research

Criteria Used in Research & Development Project Selection

Devido à corrida em busca de inovação, organizações do Brasil e do mundo todo enfrentam desafios constantes para se manterem relevantes no mercado, buscando as melhores formas de gerenciar seus projetos e utilizando dos recursos existentes para maximizar os benefícios e, em alguns casos, minimizar o risco ou custos de seus projetos. De acordo com uma revisão sistemática de 61 artigos, escritos entre 1970 a 2018, que utilizam métodos multi-critérios para tomada de decisões (MCDM) para selecionar projetos de Pesquisa & Desenvolvimento (P&D), apenas 19 deles dão uma explicação adequada dos critérios utilizados. Assim, a fim de contribuir com o processo de seleção de projetos, o objetivo principal deste trabalho é mostrar quais os tipos de critérios que apresentam maior relevância sobre os demais. Todo o processo é feito através de uma revisão sistemática da literatura: desde a seleção dos artigos, o agrupamento dos critérios e sua avaliação por dois especialistas utilizando o método Analytic Hierarchy Process (AHP). Ao final, percebe-se o quão importante é o benefício financeiro para os especialistas, e que a inovação não é considerada tão relevante para eles e para a maioria dos autores dos artigos analisados

Financiamento de inovação tecnológica: proposta de um modelo para avaliação de desempenho de projetos

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Sócio-Econômico. Programa de Pós-Graduação em ContabilidadeA atividade de pesquisa e desenvolvimento é um importante meio utilizado pelas organizações para se manterem competitivas, pois é a partir do desenvolvimento de pesquisas que as empresas identificam as demandas e restrições tecnológicas do mercado. Tal atividade resulta na elaboração de projetos para o desenvolvimento de produtos e/ou processos inovadores. No entanto, as empresas enfrentam vários obstáculos para esse desenvolvimento, dentre eles destacam-se a diversidade de fatores a serem considerados no processo de seleção do projeto a ser desenvolvido e os recursos necessários para o desenvolvimento do produto. No que tange à obtenção de recursos, as instituições governamentais são responsáveis por boa parte dos recursos investidos no desenvolvimento de produtos inovadores. Entretanto, um dos grandes desafios enfrentados pelas instituições está relacionado ao processo de seleção dos projetos, tendo em vista a diversidade de fatores a serem considerados no momento da avaliação de cada projeto. Nesse contexto, esta pesquisa busca responder à seguinte pergunta de pesquisa: Quais são os critérios a serem considerados em um processo para apoiar na Seleção de Projetos inovadores? Assim, esta tem como objetivo construir um modelo que permita avaliar o desempenho das propostas submetidas pelas MPEIs de Santa Catarina ao Programa Juro Zero (PJZ), com vista a apoiar a gestão do Programa no processo de qualificação. Esta pesquisa caracteriza-se como um estudo de caso, de natureza exploratório-descritiva; para a coleta dos dados, utiliza a técnica de entrevista e análise documental, com abordagem qualitativa e quantitativa dos dados. O instrumento de intervenção utilizado é a Metodologia Multicritério de Apoio à Decisão Construtivista - MCDA-C, por possibilitar a construção do entendimento sobre o contexto, resultando em um modelo que possibilita identificar, avaliar, mensurar, integrar e gerar ações de aperfeiçoamento. Como resultado, o modelo construído possibilitou: (i) identificar os 70 aspectos que, de forma suficiente e exaustiva, foram identificados para serem levados em conta no processo de Seleção de Projetos pelo PJZ; (ii) identificar as duas áreas de preocupação "Atendimento aos Requisitos" composto por quatro subáreas de preocupação (documentação; demonstrativos contábeis; enquadramento; e inovação) e a área de "Riscos" composta por cinco subáreas de preocupação (aspectos técnicos; capacidade financeira; mercado; concorrência; e perfil empreendedor); (iii) ilustrar o perfil de desempenho das seis propostas submetidas no ano de 2010 que é de 36 pontos, Proposta 1; 37 pontos, Proposta 2; 68 pontos, Proposta 3; 47 pontos, Proposta 4; 74 pontos, Proposta 5; e 64 pontos, Proposta 6; (iv) identificar os descritores cujas propostas não selecionadas encontram-se com desempenho comprometedor; e, (v) recomendar ações que, caso seja implantada, possibilita a melhora no desempenho global onde a: (i) Proposta 1 passaria de 36 pontos para 48 pontos; (ii) Proposta 2 passaria de 37 pontos para 48 pontos; e, (iii) Proposta 4 passaria de 47 pontos para 53 pontos, atendendo assim ao terceiro e quarto objetivos específicos.The activity of research and development is an important means used by organizations to remain competitive as it is from the development of research that companies identify the demands and technological constraints of the market. This activity results in the elaboration of projects for the development of products and / or innovative processes. However, companies face many obstacles to this development, they stand out among the numerous factors to consider in the selection process of the project to be developed and resources for product development. With respect to fundraising, government institutions are responsible for much of the resources invested in the development of innovative products. However, a major challenge faced by the institutions is related to the process of selecting projects, taking into account the diversity of factors to be considered when evaluating each project. In this context, this research seeks to answer the following research question: What are the criteria to be considered in a process to assist in the selection of innovative projects? Thus, it aims to build a model to assess the performance of the proposals submitted by the Santa Catarina#s ISMEs (Innovative Micro and Small Enterprises) the Zero Interest Program (ZIP), to support the management of the program in the qualification process. This research is characterized as a case study, exploratory-descriptive, for data collection, uses the technique of interview and documentary analysis, both qualitative and quantitative data. The intervention tool used is the Constructivist Multi-Criteria Decision Aid (MCDA-C) by allowing the construction of understanding of the context, resulting in a model that helps identify, evaluate, measure, integrate and generate improvement actions. As a result, the constructed model allowed: (i) 70 to identify the aspects that made adequate and comprehensive, were identified to be taken into account in the Project Selection by ZIP; (ii) identify the two areas of concern "Attendance to the Requirements#, composed of four sub-areas of concern (documentation, financial statements, guidelines, and innovation) and the area of "Risk" composed of five sub-areas of concern (technical, financial strength, market, competition, and entrepreneurial); (iii) illustrate the performance profile of the six proposals submitted in 2010 which is 36 points, a Proposal, 37 points, Proposal 2, 68 points, Proposal 3, 47 points, Proposal 4, 74 points, Proposition 5 and 64 points , Proposal 6; (iv) identify the descriptors whose proposals are not selected with compromising performance; and, (v) recommend actions which, if implemented, allows the improvement in overall performance where: (i) of Proposition 1 would 36 points to 48 points; (ii) Proposal 2 would increase from 37 points to 48 points; and (iii) Proposal 4 would increase from 47 points to 53 points, thus meeting the third and fourth specific objectives

R&D project selection: which criteria should we use?

Many companies around the world lay on R&D their chances to be profitable and still standing in a dynamic market. Tokeep the changes going, many ideas surge and some are transformed into projects. Since the resources are limited, organizations are obliged to select only the most suitable projects to attend their objectives. This is an old practice. However, project portfolio characteristics has changed. The portfolio objectives of today go beyond profit: strategy, environment and society has also become import, along with manyother decision criteria. The computational power was also enhanced, making multidata decision approaches feasible, even forsmall-profitable organizations. On the last half century, many author shave proposed multicriteria decision making (MCDM) methods for project portfolio selection (PPS) on Research and Development (R&D). However, only a few gave importance to the criteria used, which would be a central issue on any multicriteria decision. Thus, in order to contribute to R&D PPS field of study, this thesis investigates two propositions: (1) most criteria used in R&D PPS may be represented by a smaller list of criteria, and (2) the criteria used in R&D PPS can be selected in a fuzzy environment, according to their influence and importance. To do so, we explore the 227 criteria used in R&D PPS from 1970 to 2019, summarizing them in a list of 23 criteria with broader scopes and 8 criteria groups. We have also performed a Systematic Literature Review to get to the initial 227 criteria and to lighten the research opportunities in MCDM-based R&D PPS explored by this thesis. We also propose a novel MCDM approach for criteria selection, that integrates Fuzzy-based DEMATEL and Fuzzy-AHP Extend Analysis methods. Experts from a representative electrical-public Brazilian R&D organization have built and validated bothlist and method. Experts from other representative public Brazilian R&D organizations have also contributed in other research steps. All involved organizations manage together R&D portfolios valued around US$ 5 billion each year, which account for 38% of all Brazilian annually expenditures in R&D projects. In a overall manner, the results provide guidance on the topic and facilitate knowledge accumulation and creation concerning the criteria selectionprocessinMCDM-basedR&D PPS

La valoración de inversiones corporativas desde la perspectiva del capital intelectual : una aproximación multicriterio

El aumento de la complejidad en la definición y posterior adopción de estrategias corporativas, especialmente las relativas a las decisiones de inversión, es uno de los elementos más significativos derivados del escenario económico internacional en el que operan en la actualidad las empresas. Una serie de factores concretos explican esta circunstancia, tales como la intensificación de los problemas de agencia, el carácter multidimensional del factor riesgo, o la naturaleza intangible de buena parte de los beneficios que generan las inversiones de carácter estratégico adoptadas en el marco de la denominada economía del conocimiento. Todos estos factores de complejidad están condicionando la correcta y eficiente asignación de recursos en la empresa y los procesos de decisión que la modelan. Las técnicas financieras clásicas, que abordan la resolución de dichos procesos desde la perspectiva de la optimización de los atributos rentabilidad y riesgo, son en la actualidad criticadas por no considerar determinados beneficios intangibles que se derivan de los proyectos de inversión. El objetivo general de esta tesis doctoral es desarrollar un nuevo enfoque teórico de valoración de inversiones no financieras fundamentado en el constructo ampliamente aceptado de creación de valor de mercado entendido desde una perspectiva integral y completa. Este enfoque implica una redefinición del término creación de valor, incorporando a la generación de valor financiero la creación de valor no financiero o de capital intelectual, a la vista del decisivo protagonismo de los intangibles como fuente de valor y de ventaja competitiva sostenible. El enfoque teórico de valoración propuesto se articula a través de dos métodos de análisis multicriterio: el proceso analítico jerárquico y el proceso analítico en red. Ambos permiten integrar en el estudio tanto los criterios que inciden en la creación de valor financiero, como aquellos que contribuyen a la creación de valor no financiero o de capital intelectual. Esta integración permite que los dos modelos de valoración que aquí se proponen cuantifiquen el valor total que genera cada alternativa de inversión, con el fin de ayudar a los directivos en sus procesos de decisión corporativos. La metodología propuesta se implementa en dos casos de estudio de la industria agroalimentaria andaluza. El primero consiste en la valoración de tres alternativas de sistemas de gestión de la calidad en el sector cárnico y, en el segundo caso, se evalúan las posibles alternativas de sistemas de gestión ambiental en la industria almazarera. Los resultados de la implementación empírica, además de validar los modelos, han evidenciado la conveniencia de considerar los impactos de las inversiones sobre los activos intangibles de la empresa, pues estos determinan en el mundo real la selección de la alternativa de inversión óptima. Los dos métodos de valoración propuestos implican la formalización del proceso de valoración de inversiones no financieras que actualmente siguen los directivos en las empresas...Increasing complexity in terms of defining and subsequently adopting corporate strategies, especially those relating to investment decisions, is one of the most significant issues emerging from the international economic environment in which businesses operate today. A number of specific factors play a part in this situation, such as the intensification of agency problems , the multidimensional nature of the risk factor, or the intangible nature of many of the benefits generated by strategic investments within the so-called ‘knowledge economy’. All these factors of complexity affect the appropriate and efficient allocation of company resources and the decisionmaking processes that determine them. Classical financial techniques that seek to address these processes from the perspective of optimizing risk and return attributes are now criticized because this kind of analysis ignore several key intangible issues also involved in investment projects. The overall objective of this thesis is to develop a new theoretical approach to evaluating nonfinancial investments, based on the widely-accepted concept of ‘creating market value’, understood from a holistic, comprehensive perspective. This approach requires a redefinition of the term ‘value creation’ to incorporate the creation of nonfinancial value or intellectual capital alongside the concept of financial value creation. This reflects the decisive role of intangible benefits as a source of value and sustainable competitive advantage. The proposed theoretical valuation approach is applied via two multicriteria methods: the analytic hierarchy process and the analytic network process. These allow the inclusion in the analysis of both the criteria that influence the creation of financial value as well as those that contribute to the creation of nonfinancial value or intellectual capital. This integration allows the two proposed valuation models to quantify the total value generated by each investment alternative in order to assist decision-makers in corporate decision processes. The proposed methodology is implemented in two case studies of the Andalusian food industry. The first concerns the evaluation of three alternative systems of quality management in the meat sector, and the second case evaluates possible alternatives for environmental management systems in the olive oil industry. The results of the empirical implementation, as well as validating the models, demonstrate the merits of considering the impact of investments on an organization’s intangible assets, as these influence the selection of the optimal investment alternative in the real world. The two proposed methods of assessment involve formalizing the current process of evaluating nonfinancial investments carried out by a company’s decision makers..