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The purpose of this paper is to select the optimal Lean Six Sigma (LSS) project using hybrid fuzzy-based Multi-Criteria Decision-Making (MCDM) approach for an automotive component manufacturing organization.

The LSS project selection has been formulated as the MCDM problem. Hybrid MCDM method based on Decision-Making Trial and Evaluation Laboratory Model (DEMATEL), Analytical Network Process (ANP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been used to select the optimal LSS project. The methodology enabled the practitioners to systematically prioritize LSS projects.

The finding of this study is that, out of five LSS projects, project P3 is the best LSS project. P3 is the optimal LSS project with reduced failure risk, and efforts are being taken to implement the selected project.

The problem formulation and methodology has been tested for a single study. In future, more number of studies could be conducted using the hybrid approach. This method is presently applied for an automotive component manufacturing organization; in future, the approach could be applied in different industrial sectors for improving its effectiveness.

The case study has been conducted in a real-time industrial problem. The practitioners expressed the usefulness of the methodology for prioritizing LSS projects Hence, the inferences derived are found to possess practical relevance.

The original contribution of the study is the selection of optimal LSS project using hybrid MCDM technique.

The purpose of this paper is to identify how project portfolio selection (PPS) methods have evolved and which approaches are more suitable for radical innovation projects. This paper addressed the following research question: how have the selection approaches evolved to better fit within radical innovation conditions? The current literature offers a number of selection approaches with different and, in some cases, conflicting nature. Therefore, there is a lack of understanding regarding when and how to use these approaches in order to select a specific type of innovation projects (from incremental to more radical ones).

Given the nature of the research question, the authors perform a systematic literature review method and analyze 48 portfolio selection approaches. The authors then classified and characterized these articles in order to identify techniques, tools, required data and types of examined projects, among other aspects.

The authors identify four key features related to the selection of radical innovation projects: dynamism, interdependency management, uncertainty treatment and required input data. Based on the content analysis, the authors identified that approaches based on different sources and nature of data are more appropriated for uncertain conditions, such as behavioral methods, information gap theory, real options and integrated approaches.

The research provides a comprehensive framework about PPS methods and how they have been evolving over time. This portfolio selection framework considers the particular aspects of incremental and radical innovation projects. The authors hope that the framework contributes to reinvigorating the literature on selection approaches for innovation projects.

Selecting a proper project delivery system is one of the critical issues for the success of a project. This paper discusses the application of project delivery systems in China and the existing project delivery system selection methods, analyzes project objectives and indicators influencing the selection of project delivery systems, and aims at finding an appropriate method to select project delivery systems.

A survey was conducted by postal questionnaire and Multivariate Statistical Analysis was applied to analyze the project data. A robust model was developed to analyze the selection of project delivery systems.

The results of survey and analysis show that design‐bid‐build (DBB)/project management (DBB+PM), design‐build (DB)/engineering, procurement and construction (EPC)/Turnkey, multi‐stage DB/EPC and EP+C are commonly used in China. The differences between DBB and DBB+PM, and differences between DB/EPC and Turnkey in China are not significant. Weights of project objectives in each project delivery system and the ranking of indicators influencing the selection of project delivery systems are acquired.

Analysis was conducted with a robust model instead of traditional model in consideration of efficiency. This research may assist owners in Mainland China in selecting project delivery systems, improve project performance, and encourage efficiency in project delivery process.

Project selection management is a matter of challenge for project-oriented organizations, particularly, if the decision-makers are confronted with limited resources. One of the main concerns is selecting an optimal subset that can successfully satisfy the requirements of the organization providing enough resources to the best subset of the project. The projects for which there are not enough resources or those requiring whole resources of the organization will collapse soon after failed to success. Therefore, the issue is in the risk of choosing a set of projects so that can make a balance in investment versus on collective benefit.

A model is presented for project selection and has been tested on the 37 available projects. This model could increase the efficiency of the whole subset of the project significantly in comparison to the other model and it was because of choosing a diverse subset of projects.

Provides a general framework for project selection and a diverse and balanced subset of projects to increase the efficiency of the selected subset. Also, reduces the impact of uncertainty risk on the project selection process.

For the purposes of project selection, any project whose results are uncertain is a risky project because, if the project fails, it will reduce combined project value. For example, a pharmaceutical company’s R&D project is affected by the uncertain results of a specific compound. If the company invests in different compounds, a failure with one will be offset by a good result on another. Therefore, with selecting a diverse set of projects, this paper will have a different set of risks.

This paper discusses the risk of selecting or being responsible for selecting a project under uncertainty. Most of the projects in the field of project selection generally consider the risks facing the projects or existing models that do not take into account the risk.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

This paper aims to identify and assess the key criteria for selecting green suppliers in the United Arab Emirates (UAE) construction industry.

A total of 20 criteria were identified and shortlisted through an extensive literature review. These criteria were grouped into four categories: technical and commercial bid, company characteristics, environmental and socioeconomic. A questionnaire was then developed and distributed to construction professionals in the UAE. A total of 39 professionals responded to the survey including contractors, consultants, owners and suppliers. The respondents performed pairwise comparisons among the selection criteria. Data was then analyzed using the Expert Choice Software.

The research findings highlighted that the technical and commercial bid category was ranked as the most important with a weight of 0.338, followed by socioeconomic, company characteristics and environmental categories weighing 0.239, 0.225 and 0.199, respectively. The UAE construction professionals also ranked health and safety, material’s quality and tender price as the top three most important criteria when selecting a sustainable supplier.

This research addresses the lack of literature toward green supplier selection in the UAE. In addition, it assists contractors in selecting the appropriate supplier and promotes sustainable practices in the construction industry.

Material suppliers play an important role in the successful delivery of construction projects. Selecting the appropriate supplier is of paramount importance to project success. Several methods can be used to evaluate and select the best-fit suppliers. However, the selection criteria in such methods are primarily based on traditional construction projects rather than sustainable construction projects. Recently, there is an increase in the number of sustainable construction projects in the UAE. Therefore, identifying and assessing the key criteria for selecting green suppliers is needed. This paper fills the gap in literature as to selecting green suppliers in construction projects.

The purpose of this paper is to investigate procedures and practices to promote transparency in best-value procurement for the design and construction of highway projects with the goal of improving this evolving procurement method.

The review of published empirical studies, a national survey of transportation agencies, and case studies of highway agencies form the basis of the conclusions in this research. In addition to the national survey, with 46 of 52 agencies participating, the research presents case studies from seven highway agencies in the USA including: California, Florida, Michigan, Minnesota, New York, Oregon, and Utah. These seven case studies were selected from agencies that employ mature best-value procurement methods. The case studies involved a thorough procedural review and structured interviews of agency personnel. The agencies then validated the results and conclusions.

The results showed that evaluation committees should include technical members who do not have a personal interest in the outcome of the selection to maintain transparency in best-value projects. The committees should receive best-value procurement training, which necessitates the development of consistent and transparent best-value selection procedures. Debriefing meetings should be conducted to provide comments about strengths and weaknesses of each proposal to enhance fairness and transparency of the best-value selection process.

Knowledge of the best-value procurement procedure will allow researchers to better understand the impact of procedures and practices on transparency in selecting best-value projects. The chief limitation of this research is that the primary data were collected from highway agencies in the USA. Any future research should include more data to enhance the validity of this study outside of the public transportation sector.

The result of this research will help transportation agencies and other public owners to improve their best-value procurement procedures. The findings of this research also address the construction and consulting industry’s concern about transparency and fairness of a best-value selection process.

This research is the first attempt to examine the impact of the evaluation committee, best-value training, and debriefings on transparency of best-value selection.

The purpose of this paper is to explore the practice of engaging key project consultants for the development of green projects in Malaysia.

A qualitative approach is adopted in this research using the face-to-face semi-structured interview process with 18 respondents consisting of developers and architects of green projects that have obtained green certification by the Malaysian Green Building Index.

The engagement of consultants is divided into three stages: engagement method; consultant selection method; and evaluation process. The engagement method can be initiated by the client or through the architect. The direct selection is the preferred strategy in engaging architects, while open strategy is commonly adopted for engaging other key consultants. The evaluation process consists of request for proposal evaluation and negotiation before appointment is awarded. In addition, there are four main criteria in selecting the consultants: client’s preference, fee flexibility, green project requirement and consultant firm’s internal strengths.

The study is based on the Malaysian context and based on the engagement of main consultants in green development projects and, thus, cannot be generalised to other consultants’ engagement in conventional projects.

This research presents the process that can contribute to better planning, controlling and management of the consultants’ engagement process. The selection criteria shall form a reference in selecting the most suitable consultants for the project.

This study attempts to understand how consultants are engaged in green projects, an important management stage in project initiation, but has received little attention in the past.

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.

This paper proposes selecting a construction project portfolio in the context of a public institution, which makes it possible to assess quantitative and qualitative criteria, thereby meeting the needs of the institution and the existing constraints.

The research design follows a framework using technique for order preference by similarity to ideal solution (TOPSIS) associated with integer linear programming.

The method involves a flow of assessments allowing criteria and weights to be elicited where outcomes are based on the experts' intra-criteria assessment of alternatives and decision-makers' inter-criteria assessment. This is of utmost interest to public organizations, where selections must result in benefits and lower costs, integrating the experts' technical and management perspectives.

Public institutions are characterized by having limited financial and personnel resources for project development despite having a high demand for requests not associated with profits, making it essential to have a framework that enables using multiple criteria to better evaluate the benefits related to these decisions.

The main contributions of this article are: (1) the proposition of a framework for selecting construction project portfolios considering the organization's strategic needs; (2) identifying quantitative and qualitative assessment criteria for project selection; (3) integrating TOPSIS with an optimization process for selecting the construction project portfolios and (4) providing a structured decision process for selecting the portfolio that best represents the interests of the institution within its limited resources and personnel.