Project Selection Methodology Research Articles

UNIQUE PROJECT SELECTION METHOD FOR INSTITUTE

Selecting projects can be a complex task due to the multiple dimensions involved in measuring their impact, especially when there are multiple decision-makers. This paper focuses on a real application of project selection for academic projects, utilizing the opinions of experts through a group decision-making model known as the Topic Selection method. Four types of criteria, including qualitative, quantitative, negative, and positive criteria, are considered for selecting the best project among five options and ranking them accordingly. Additionally, the study utilizes the data from the last five-to-six years to check if any group has already taken up the topic. To achieve this, Support Vector Machine (SVM) Data Mining algorithms are employed. SVMs are chosen for their ability to handle both linear and non-linear data efficiently, making them suitable for this task. By combining the expertise of experts and the power of SVMs, this study aims to provide a robust methodology for project selection in academic settings, considering various dimensions of impact and availability of topics. In conclusion, the project selection process for academic projects requires careful consideration of multiple criteria and the use of advanced techniques such as SVMs for data analysis. By incorporating expert opinions and historical data, the Topic Selection method offers a comprehensive approach to selecting and ranking projects, ensuring that the chosen projects are both impactful and unique within the academic context. Key Words: project selection, academic projects, group decision-making, Topic Selection method, criteria.

Multiple criteria decision analysis of public investment options: application to streetlighting renewal projects

The last global economic crisis set fiscal consolidation as one of the most relevant goals of economic policy. At the same time, efforts are necessary to increase economic growth rates, particularly by increasing quantity and quality of public investment. However, the lack of fiscal space and other impediments make these goals hard to attain. On the contrary, in many countries data show negative dynamics of quantity and quality of public investment. In terms of energy efficiency investment, trends are positive. However, the pace of investment significantly underperforms the goals set. We argue that one of the major reasons is the lack of financial innovation and project selection methodology. For this reason, projects have still been mainly financed under traditional procurement models. Surprisingly, most countries do not exploit the advantages of alternative models of financing which do not affect public debt level, significantly reduce fiscal deficits and reduce fiscal risks. This article argues that a multi-criteria approach used at the initial stages of project preparation increases the potential for project realisation and the overall quantity and quality. In order to provide empirical evidence, we use information on energy efficiency streetlighting projects and present a case of a traditional versus alternative financing models. Highlights a need for a systematic approach when selecting optimal financing model is a must; a lack of financial innovation is one of the most critical impediments to a higher level of investment in revenue-generating projects common for the energy efficiency sector; alternative models of financing enable public investment increase without harming the fiscal position; a new methodology for selecting the most preferable model is presented; a policy mix should take more comprehensive stance towards complexity of public investment projects.

Collaborative and Participatory Design: Assignment of Team Members to Engineering Projects with the Consideration of Designer’s Expectations

AbstractWith the trend of global collaboration and development of Internet of Things in industry 4.0, the collaboration relationships between designers is getting more close and important than before. Therefore, when project manager assign designers to design projects, it is very important for them to select design projects with the consider about the expectations of the designers regarding the different projects and collaboration ability for the designers in the projects while it is very important to identify the projects with the consideration of skills, experiences, availabilities and so on. Even though, there are various methods for selecting projects, most of these methods not consider about the expectations of designer and the collaboration ability. Therefore, in this paper, we propose a project selection methodology, which consider about the designers’ expectations to the candidate multi-project and collaboration ability in the candidate multi-project. The main objective of our research is to help project manager to find an adaptable and comfortable multi- project to the designer.

녹색기술 유망 R&D 과제 선정 방법론 : 개도국향 기술사업화를 중심으로

녹색기술 유망 R&D 과제 선정 방법론 : 개도국향 기술사업화를 중심으로

Avaliação do risco regulatório em pesquisa & desenvolvimento no setor elétrico brasileiro

O artigo propõe metodologia de avaliação ex-ante de projetos de P&D&I do setor elétrico, incorporada a uma ferramenta de análise multicritério, com foco em risco. A P&D do setor elétrico é regulada pela Agência Nacional de Energia Elétrica (ANEEL) e obriga as empresas a investirem parte de sua Receita Operacional Líquida (ROL) em P&D&I. A imposição de P&D&I ao setor levou suas empresas a buscarem formas de alocar recursos em projetos que tentam harmonizar o contexto regulatório com seus direcionadores de mercado, forçando-as a estruturarem em suas rotinas uma gestão da inovação que mitigasse riscos regulatórios. Uma forma de se viabilizar essa mitigação é o uso de metodologias de seleção de projetos capazes de ponderar múltiplos elementos, de certo modo, antagônicos. A PiTech, Prioritization in Technology, é uma ferramenta de análise multivariada paramétrica, flexível e propícia a essa ponderação. Neste artigo, aplicaram-se critérios operacionais, mercadológicos e regulatórios, em múltiplas combinações, para 19 projetos de um grupo empresarial de energia elétrica. A ferramenta mostrou-se útil ao permitir aos tomadores de decisão verificarem a pertinência de investimento em 16 projetos, totalizando R$ 61 milhões em 2010, com riscos de glosa minimizados e concomitante aderência a interesses empresariais.

A framework for Six Sigma project selection in higher educational institutions, using a weighted scorecard approach

Purpose – This paper discusses the importance of the Six Sigma selection process, describes a Six Sigma project in a higher educational institution and presents a weighted scorecard approach for project selection. Design/methodology/approach – A case study of the Six Sigma approach being used to improve student support at a university computer help desk was used. An error related to the timeliness of service was defined and improved over the course of the project. Findings – The Six Sigma approach was useful for improving timely service, but a methodology for selecting the project was needed by the project leader. Using such a methodology would have ensured higher probability of project success. Practical implications – This framework provides directions for selecting a Six Sigma project in a higher educational setting. The weighted scorecard method is presented and may be used for selecting a project which would likely be the most efficient use of time and resources. Originality/value – While project selection methodologies have been published with regard to Six Sigma projects in business, this paper fills the need for selection criteria as they relate to higher educational settings.

A Multistage Value-Based Model for Prioritization of Distribution Projects Using a Multiobjective Genetic Algorithm

This article addresses the project prioritization problem as a part of the distribution system planning process. The projects must be selected and scheduled in a multistage planning horizon, to fit the utility available budget. The proposed decision model is value based, and prioritizes the local projects in a systemic way. The value attributes consider the financial impacts, number of consumers and some aspects of the distribution system operational performance and power quality. An analytic model optimizes the project portfolios by means of the NSGA-II multiobjective genetic algorithm. The optimization obtains a set of Pareto-optimal solutions, which are the trade-off project portfolios, with respect to the problem objectives and constraints. The presented case studies indicate some changes in the choice of priority projects. The proposed project selection methodology helps in raising strategic investments and allows for better distribution system planning.

Highway improvement project selection by the joint consideration of cost-benefit and risk criteria

Since highway improvement project selection requires screening thousands of road segments with respect to crashes for further analysis and final project selection, we provide a two-step project selection methodology and describe an application case to demonstrate its advantages. In the first step of the proposed methodology, we will use odds against observing a given crash count, injury count, run-off road count and so on as measures of risk and a multi-criteria pre-selection technique with the objective to decrease the number of prospective improvement locations. In the second step, the final project selection is accomplished based on a composite efficiency measure of estimated cost, benefit and hazard assessment (odds) under budget constraints. To demonstrate the two-step methodology, we will analyze 4 years of accident data at 23 000 locations where the final projects are selected out of several hundred of potential locations.

Six Sigma project selection methodology

PurposeThe selection of right projects in a Six Sigma program is a major concern for early success and long‐term acceptance within any organization. One of the ever‐increasing challenges is to define and select right measure for improvement and appropriate problem definition. Many projects encounter the problem of no linkage with business objectives or customer needs, too large or high‐level project scope along with unclear problem and goal statement. Improperly, chosen metrics lead to sub‐optimal behavior and can lead people away from the organization's goal instead of joining them. This paper aims to propose a project selection methodology for different situations.Design/methodology/approachThis research develops a model for project identification; ensuring well‐defined projects are selected having large impact on customer satisfaction or bottom line. The model is described for the situations: availability of performance data, balanced business score card implemented and no data is available.FindingsA “top‐down approach” model is developed for project selection, since top management support for Six Sigma initiatives is absolutely critical to see tangible, significant results. The authors suggest establishing the linkage with data (either reactive or survey), otherwise through prioritization tool for project selection. Finally, factors influencing successful Six Sigma projects include management commitment; project selection and control skill, irrespective of whether this is a define, measure, analyze, improve and control or define, measure, analyze, design and validate/verify project.Originality/valueThis approach will help the organizations to select the specific project from multivariate organizational and customer needs. Three different methods for project selection are explained with examples and reasons for selection. Merits and demerits of each method are also highlighted.

Fuzzy multicriteria R&D project selection with a real options valuation model

Real options valuation is a financial technique for evaluating investments under conditions of uncertainty, particularly uncertainty associated with market variables such as future product demand or the future value of an asset. The real option value of the investment opportunity is what a value-maximizing firm would pay the right to undertake the investment project with its inherent decision points. This paper proposes a fuzzy multi-criteria R&D project selection methodology based on the hierarchical fuzzy TOPSIS, which includes a fuzzy real options valuation model.

Interdependent Urban Renewal Project Selection under the Consideration of Resource Constraints

This paper proposes an application of the fuzzy Delphi method, the analytic network process (ANP) and zero – one goal programming (ZOGP) for the urban renewal project selection problem in a redeveloping urban area in Taichung City, Taiwan. Urban renewal project selection means the identification of the most cost-beneficial projects (the projects that will produce most cost benefit) in order to maximize the net benefit to the public and to allocate resources most efficiently. In order to evaluate different urban renewal projects, a hierarchical network model based on various factors and the interactions of factors is presented. By incorporating experts' opinion, a priority index can be calculated for each urban renewal project studied, and a performance ranking of urban projects renewal can be generated. In this paper an improved urban renewal project selection methodology, which reflects interdependencies among evaluation criteria and candidate project using an integrated approach, is suggested. Finally, we introduce a method of solution through an empirical real-world urban renewal project selection example on an ongoing decision-making project in Taichung City, Taiwan using ANP – ZOGP. The results provide guidance to the government regarding strategies for accepting orders for redeveloping urban environments.

Ranking projects for an electricity utility using ELECTRE III

AbstractRanking and selecting projects is a common yet often difficult task with typically more than one dimension for measuring project impacts and more than one decision maker. We describe a project selection methodology developed and used since 1998 for Mighty River Power, a New Zealand electricity generator, which incorporates the ELECTRE III decision support tool. Although several other multiple criteria approaches could have been used, features of ELECTRE III such as outranking, and indifference and preference thresholds were well received by our decision makers. More than the use of a specific decision support tool, we focus particularly on the successful implementation of a simple, structured multicriteria methodology for a yearly project selection exercise and document this over 8 years in a changing managerial context.

Using ANP priorities with goal programming in resource allocation in transportation

Transportation Infrastructure (TI) project selection means identifying some alternative projects in order to maximize the net benefit to the organization and allocating resources only among those alternatives, within the given constraints on resources. To select the best set of proposed TI projects in an organization is difficult because there are lots of multiple factors such as project risk, corporate goals, limited availability of firm’s TI resources, etc., in the candidate TI projects. The TI project selection problems are Multi-Criteria Decision Making (MCDM) problems. Prior project selection techniques are useful. However, they have restricted application because they generally depend on the assumption of independence among the candidate projects and criteria. In this paper, we suggest an improved TI project selection methodology which reflects interdependencies among evaluation criteria and candidate projects using analytic network process (ANP) within a zero–one goal programming (ZOGP) model. In order to provide a systematic approach to set priorities among multi-criteria and trade-off among objectives, ANP is suggested to be applied prior to GP formulation. Although goal programming incorporates multiple objectives and arrives at an optimal solution, its major drawback is that the decision maker(s) must specify goals and priorities a priori. In order to overcome this problem, group discussion is needed. In this research, we suggested an integrated approach for interdependent TI project selection problems using Fuzzy Delphi, Analytic Network Process concept and Zero-One Goal Programming. Finally, in project selection, it is very important to consider the interdependent relationship among projects or criteria because of the characteristics of interdependence that exist in real problems. In addition, developing a methodology for considering interdependent factors is a very difficult problem. We introduce a method of solution through a real-world TI empirical example on an ongoing decision-making project in Taichung City, Taiwan using ANP/ZOGP. Using this method we solve problems having multiple criteria, interdependence and resource feasibility.

Using analytic network process and goal programming for interdependent information system project selection

Information system (IS) project selection problems are multi-criteria decision-making (MCDM) problem. Existing methods for IS project selection does not reflect interdependencies among criteria and candidate projects. Considering these interdependencies among criteria provides valuable cost savings and greater benefits to organizations. When we evaluate project problems, we need to collect a group opinion because to know the interdependence relationship among criteria and criteria in considered project problems is very important. In order to collect group opinion for interdependent project problem, we use expert interview. In this paper, we suggest an improved IS project selection methodology which reflect interdependencies among evaluation criteria and candidate projects using analytic network process (ANP) within a zero–one goal programming (ZOGP) model. Scope and purpose When information system (IS) projects are selected from a suggested competing projects they are evaluated according to different criteria. Prior research neglected an important aspect of information technology, namely the interdependencies that exist among IS projects. When we select IS project in organization, to select IS project through recognizing and modeling these project interdependencies provides valuable cost savings to organizations. Among the proposed methodologies of multi-criteria decision making (MCDM), goal programming (GP) is widely used for IS project selection. Although GP incorporates multiple objectives and arrives at an optimal solution, its major drawback is dependent on the judgment of decision maker(s). In order to provide a systematic approach to set priorities among multi-criteria and trade-off among objectives, analytic network process (ANP) is suggested to be applied prior to GP formulation. In this paper, we present a methodology using analytic network process and zero–one goal programming (ZOGP) for IS projects selection problems that have multiple criteria and interdependence property.

Application of an interactive method for MOILP in project selection decision — A case from Indian coal mining industry

In this paper an attempt is made to develop a methodology for project selection in an Indian coal mining company. The methodology involves the formulation of the project selection problem as a multiple criteria integer linear program and its solution by an interactive method. A case example problem is studied and solved using the proposed methodology.

Application of an interactive method for MOILP in project selection decision - a case from an Indian coal mining industry

In this paper an attempt is made to develop a methodology for project selection in an Indian coal mining company. The methodology involves the formulation of the project selection problem as a multiple criteria integer linear program and its solution by an interactive method. A case example problem is studied and solved using the proposed methodology.

Using the analytic hierarchy process and goal programming for information system project selection

One of the basic information system (IS) management activities is the planning of IS projects. Specifically, such planning requires the selection of IS projects and allocation of resources to complete them. This paper presents an improved IS project selection methodology that combines the recently applied IS project selection methodologies of the analytic hierarchy process (AHP) within a goal programming (GP) model framework. This new combination of the AHP and GP methodologies helps to overcome the weaknesses observed when either methodology is used separately. The combined AHP and GP methodology is illustrated through an example.