R&D and innovation project selection: can optimization methods be adequate?

This article proposes a comprehensive framework for R&D and innovation project selection under uncertainty and subject to real-world constraints applicable to the Brazilian electricity sector, using a combination of integer programming formulation and a PROMETHEE-based method. The objective is to contribute to this domain by offering an approach suitable for the challenges of this sector, but also applicable to other situations involving R&D and innovation investments under similar conditions. The manuscript presents applications using real data from an electricity company. It also compares the proposed method with similar approaches found in the literature such as PROMETHEE II and V. The application revealed the best performance of the proposed framework in dealing with the sector's regulatory constraints, which emphasize the companies' accomplishment with R&D and innovation expenditures obligations. In this way, although R&D and innovation project selection is not a typical case of optimization, under some particular regional, sector-based or organization boundaries this can be a better solution. (C) 2015 Published by Elsevier B.V.This article proposes a comprehensive framework for R&D and innovation project selection under uncertainty and subject to real-world constraints applicable to the Brazilian electricity sector, using a combination of integer programming formulation and a P55613621sem informaçãosem informaçã

Selection factor to bid or not to bid for extra low voltage system (ELV) project

Improper selection of Extra Low Voltage (ELV) projects by contractors might lead to many problems including underestimating cost of the project, lack of experience and bad quality of work. ELV system requires in-depth knowledge of technologies and a strong team of domain experts, who design, integrate and deliver Integrated ELV Systems that meet diverse needs. Therefore, the objectives of this study are to determine the factors of selecting an ELV Project by contractors, determine problems associated with current practice of project selection and to establish solutions that could improve future ELV projects selection. The methodology of this study will be divided into two stages which is primary data and secondary data. Secondary data will be collected by literature review by focusing on writing related materials and primary data will be collected by distributing a number of questionnaires that will determine later to selected respondents within company undertaking ELV projects. The collected data will then be analyzed using frequency distribution and average index method. The results of the study show resource pricing continuity of work/possible future project and return of investment is the most critical factors; meanwhile cost overrun, losing tender and defective works are among common problems that occurs with the current selection process; and submit the bid early, understand the client well and to sell on value are among the solutions with regard to ELV project selection criteria. The improvement will enhance business strategy for ELV contractors in project selection and future planning

Managing Uncertainty in Projects: A Review, Trends and Gaps

Nowadays an increasing number of projects are being developed in high complexity and uncertainty environment, requiring different approaches for project management: less rigid and more flexible. Thus, the purpose of this paper is to present a framework for managing uncertainties, through a systematic literature review. The developed framework, based on the contingency theory, suggests that approaches for uncertainty management are, in part, determined by the characteristics of the existing uncertainties. The responses for uncertainty can be driven by the cause or consequence of the uncertainties and those are chosen according to the ability to influence the cause, which is higher for internal uncertainties and lower for external uncertainties. The flexibility of the project management approach, in its turn, is impacted by the uncertainty degree.Nowadays an increasing number of projects are being developed in high complexity and uncertainty environment, requiring different approaches for project management: less rigid and more flexible. Thus, the purpose of this paper is to present a framework for managing uncertainties, through a systematic literature review. The developed framework, based on the contingency theory, suggests that approaches for uncertainty management are, in part, determined by the characteristics of the existing uncertainties. The responses for uncertainty can be driven by the cause or consequence of the uncertainties and those are chosen according to the ability to influence the cause, which is higher for internal uncertainties and lower for external uncertainties. The flexibility of the project management approach, in its turn, is impacted by the uncertainty degree

Estudo de métodos de análise multicritério aplicados à gestão de projetos

Monografia (graduação)—Universidade de Brasília, Faculdade De Tecnologia, Departamento De Engenharia De Produção, 2014O presente trabalho se propõe a realizar uma análise dos métodos de decisão baseados em análise multicritério (Multi Criteria Decision Analysis - MCDA) aplicados no âmbito da gestão de projetos. São estudados casos diversos de problemas relacionados a projetos, como hierarquização e classificação de atividades, alocação de orçamento, dentre outros. Em cada análise, são identificados os fatores que influenciaram o tomador de decisão a escolher determinado método MCDA. Com essas informações, é possível estabelecer uma estratificação dos dados coletados, identificando em quais situações cada método MCDA estudado é mais adequado. Isso permitirá ao tomador de decisão definir com maior consistência e eficiência o método aplicável à sua situação problema. Identificou-se que o assunto mais abordado nos artigos estudados foi o problema seleção de projetos, sendo os métodos mais utilizados o PROMETHEE e o ELECTRE. ___________________________________________________________________________________ ABSTRACTThe purpose of this work is to analyze the decision methods based on multi criteria analysis (Multi Criteria Decision Analysis – MCDA) applied in project management. Several problems related to projects are studied, such as activities sorting and ranking, budget allocation, among others. In each analysis, the factors which influenced the decision maker to choose a specific MCDA method are identified. With these informations, it is possible to establish a stratification of the collected data, in order to identify in which situations each MCDA method studied is more adequate. This will enable the decision maker to define with more consistency and efficiency the applicable method in accordance with the problem situation. The subject most discussed in the studied papers was the project selection problem, and the methods most applied were the PROMETHEE/ELECTRE

Value of agreement in decision analysis: concept, measures and application

In multi-criteria decision analysis workshops, participants often appraise the options individually before discussing the scoring as a group. The individual appraisals lead to score ranges within which the group then seeks the necessary agreement to identify their preferred option. Preference programming enables some options to be identified as dominated even before the group agrees on a precise scoring for them. Workshop participants usually face time pressure to make a decision. Decision support can be provided by flagging options for which further agreement on their scores seems particularly valuable. By valuable, we mean the opportunity to identify other options as dominated (using preference programming) without having their precise scores agreed beforehand. The present paper quantifies this Value of Agreement and extends the concept to portfolio decision analysis and criterion weights. The new concept is validated through a case study in recruitment

Bayesian-adjusted estimates in project selection - a comparison study of Bayesian and non-Bayesian decision makers with empirical evidence from the pharmaceutical industry

Companies select projects to invest in based on uncertain estimates of their performance. Theories and empirical evidence suggest that if the uncertain estimates are taken at face value, the true performance of the selected projects tends to be lower than estimated, causing the decision makers (DMs) to experience post-decision disappointment. Taking prior information into account through Bayesian adjustment can result in more realistic estimates of the project performances and thus higher expected performance among the selected projects. However, Bayesian adjustment makes it less likely to predict extreme outcomes and, consequently, may lead to missing out on big wins. This thesis studies the differences in the investment strategies of Bayesian and non-Bayesian DMs and outcomes of these strategies. This is done by employing a combined approach of both qualitative and qualitative research methodology. The quantitative approach of this thesis is in the form of a mathematical model that is used both to derive analytic results and for Monte Carlo simulation. The qualitative approach of this thesis is utilized to test theoretical findings empirically. The key results reveal that when fewer than 50% of project proposals would truly perform well (e.g., have truly positive NPV), a Bayesian DM invests in too few and a non-Bayesian DM to too many projects. Moreover, the average ex post performance of the projects funded by a Bayesian DM is higher than that of a non-Bayesian DM. However, a non-Bayesian DM will have a higher proportion of funded projects that result in big wins, but also a higher proportion of projects that result in losses. If, on the other hand, more than 50% of project proposals would truly perform well, the roles of a Bayesian and non-Bayesian DM are reversed. The less accurate the performance estimates, the more pronounced the differences between the investment outcomes of a Bayesian and a non-Bayesian DM. These analytic results are testified empirically in the R&D portfolio selection decisions in the pharmaceutical industry. Accordingly, the decision-making environment of the pharmaceutical industry displays characteristics of an environment with high estimate errors that amplify the differences in outcomes of a Bayesian DM’s versus a non-Bayesian DM’s investment decisions. As the DMs in this industry show quintessential characteristics of non-Bayesian DMs and the observed empirical outcomes perfectly coincide with the theoretical outcomes for non-Bayesian investment decisions, our theoretical findings are well-reflected empirically. From a theoretical perspective, this thesis contributes novel analytic results on the differences between the investment strategies adopted by Bayesian and non-Bayesian DMs and validates these results with empirical evidence. From a practitioner’s point of view, this thesis gives insights into how estimation uncertainties affect investment decisions and outcomes. Understanding such effects can help managers make better-informed decisions

Karayolu projelerinin fayda-maliyet analizleri için risk eklentili yeni bir bulanık bilişsel harita modeli

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Fayda Maliyet Analizi (FMA) ülkemizde ve dünyada ulaştırma projelerinin ekonomik değerlendirmelerinde yaygın olarak kullanılan önemli bir karar verme tekniğidir. Ancak bu metot çok sayıda verinin analiz edilmesini gerektirmektedir. Bu sebeple doğasında yer alan ve sonuçları olumsuz yönde etkileyen belirsizlik etkisiyle başa çıkmaya ihtiyaç duymaktadır. Bir karayolu projesi veri eksikliği, gelecek yıllara ait tahminler, ekonomik belirsizlik vb. nedenlerden dolayı yüksek belirsizlik etkisine sahiptir. Geleneksel yaklaşımda söz konusu problemi çözmek için Duyarlılık Analizine (DA) dayalı bir risk analizi uygulanmaktadır. Ancak bu yaklaşım iki temel sorunu sunmaktadır: bunlardan ilki tüm belirsizlik etkisinin analiz edilmesinde ortaya çıkan zaman kaybı diğeri de elde edilen sonuçların yorumlanabilme zorluğudur. Bu sorunları aşmak için araştırmacılar son yıllarda FMA'daki belirsizlikle başa çıkmada etkili bir yaklaşım olan Monte Carlo Simülasyonu (MCS) üzerinde araştırmalarını sürdürmektedirler. Literatürdeki çalışmalar bu metodun ulaştırma projelerinin ekonomik risk analizlerinde elverişliliğini ortaya koymaktadır. Ancak analiz sonucunun doğruluğu, bir modelde kullanılacak olan değişkenlere atanacak olasılık dağılımlarının doğruluğuna dayanmaktadır. Böylelikle MCS'deki bu zaman alıcı süreç risk analizi için önemli bir dejavantaj oluşturmaktadır. Bu çalışma, karayolu projeleri FMA'daki belirsizlik etkisiyle kolay ve kullanıcı dostu bir yaklaşımla mücadele edebilen yeni bir yaklaşımın kullanılabilirliğini ve faydasını araştırmayı amaçlamıştır. Bu amaca ulaşmak için karmaşık problemleri modelleyebilmesindeki kolaylığından dolayı Bulanık Bilişsel Harita (BBH) metodu kullanılmıştır. Bu metotla, bir RİSK parametresi kullanılarak karayolu projelerindeki fayda ve maliyetleri değerlendirebilen bir BBH modeli geliştirilmiştir. Modelde geleneksel FMA'da bulunan değişkenler kullanılmış ve bir de modele RİSK parametresi dâhil edilmiştir. Geliştirilen modelin kullanılabilirliği ülkemizdeki ulaştırma otoritelerinden elde edilen gerçek birkaç fizibilite çalışması yardımıyla araştırılmıştır. Gerçekleştirilen simülasyonlar sonrasında BBH modelinden elde edilen karar verme sonuçlarının gerçek fizibilite çalışmalarına ait karar verme sonuçları ile örtüştüğü görülmüştür. Bunun yanı sıra bir durum çalışması yapılarak geliştirilen BBH modelinin performansı ortaya konulmuş ve ulaştırma projelerinin FMA'da geleneksel risk analizleri olan DA ve MCS yaklaşımlarıyla karşılaştırılarak BBH yaklaşımının avantajları sunulmuştur. Yapılan karşılaştırmalar sonucunda BBH yaklaşımının FMA'nın risk analizi için ümit verici olduğu ortaya konulmuştur.Cost Benefit Analysis (CBA) is a method widely used in all over the world for decision making focused mainly on economical evaluation of the transportation projects. However, this method requires the analysis of a relatively large amount of data and also needs to handle the inherent uncertainty which affects the results negatively. In a highway project there are high uncertainties due to lack of data, future predictions, economic indeterminacy etc. In conventional approach, a risk analysis, which is based primarily on a Sensitivity Analysis (SA) is conducted in order to solve the problems mentioned above. However, this approach presents two main drawbacks (as follows) the first one refers to time consumption in analyzing all the influences of uncertainty and the second one is related to the difficulty on interpretability of the results. To cope with these drawbacks, researchers have studied Monte Carlo Simulation (MCS) which has recently been considered as an effective approach in tackling uncertainty of CBA. Previous studies have already shown its usefulness in this field however the accuracy of analysis results is based on providing proper probability distributions assigned to variables in a model. Thus, the time consuming process is a significant limitation for MCS. This study aims to investigate usability and utility of a new approach in highways CBA in order to cope with uncertainty easily and more user-friendly. To achieve the above-cited goal, the technique of Fuzzy Cognitive Map (FCM) was utilized for decision making due to its popularity in modeling complex problems. Thus, a FCM model which is capable of evaluating benefit and costs of highway projects was developed using RISK parameter. The concepts of CBA took part in the construction of the developed model. In addition, a RISK parameter was considered for the model. As was observed, the final decisions of the developed model concurred with the final decisions of the feasibility studies. The usability of the developed FCM model was investigated through a number of real feasibility studies obtained from Turkish transportation authorities. In addition, a case study was conducted in order to validate the performance of the developed model. In consequence of comparisons with results of SA and MCS known as conventional risk analysis for CBA, it is obtained promising results for validation of developed FCM model