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The purpose of this paper is to test and develop a method for generation and selection of six sigma projects. This is done by testing the use of the generation and selection method for six sigma projects (GSM_SSP) in a Brazilian manufacturing industry with the participation of managers, aiming to gather the user’s perspective and improvement opportunities for the approach itself.

The work adopts the action research (AR) approach once the researchers were busily involved in the training, implementation and use of the GSM_SSP. The intervention was performed in on a series of 15 workshops, with a group of managers, during six months.

The application of the eight steps of the GSM_SSP approach assisted the company’s management team to generate nine project candidates and also to select three six sigma projects. This study also finds and discusses barriers and lessons learned used to improve the GSM_SSP.

This study presents an example of how six sigma project generation and selection has been applied to a manufacturing industry by adapting AR to the process using the eight steps of GSM_SSP, demonstrating how the management team was involved. This study should be replicated in different companies because AR is limited in its generalization.

To the best of the authors’ knowledge, this study represents the first use of AR methodology in six sigma project selection. This study contributes a method that can generate and select six sigma projects. In doing so, the research offers a simple approach that can be used by managers. In addition, the steps of the approach before selection were explored.

Given the critical role of project prioritization and selection process in Six Sigma efforts, this study aims to analyse the relevant literature to answer this question: What types of project prioritization and selection methods have been used in Six Sigma research?

The study implemented the systematic literature review (SLR) method to identify and review all relevant previous studies.

The study revealed that 59 articles focused on the topic used 111 methods, analytic hierarchy process appeared as the most frequently used method with 12 articles (20%) and one-third of the methods used in the current Six Sigma project selection literature contained multi-criteria decision-making methods. In total, 61% of 59 articles were not published in the journals ranked by the ABDC’s list. Only 17% of the articles reviewed in this study were published in journals ranked as B category and 12% of the articles were published in A category journals.

The findings of this literature review may help Six Sigma practitioners and researchers accurately identify project prioritization and selection methods, considering that qualitative and quantitative scientific methods guarantee to make better decisions than “gut feelings” of the decision makers in this process.

Although a variety of studies focused on the topic, an SLR is lacking in the area of Six Sigma project prioritization and selection. Therefore, this study was constructed using the SLR method to analyse the topic.

Firms engaged in new product development (NPD) have to achieve a balanced portfolio of NPD projects. Despite the large number of models purporting to support portfolio optimization, most of them do not take into account political bias in project selection decisions. This paper aims to analyze approaches of organizational politics to NPD project selection and their implications for NPD portfolio management and future research.

A review is made of the current literature at the intersection between organizational politics and NPD project selection. With regard to the underlying assumptions of organizational politics, similarities, differences, practical implications, and research perspectives are identified.

From the paper, insights could be gained into explaining the effects of organizational politics on NPD project selection. However, the differences in assumptions that can be generally observed in organizational politics are also reflected in the studies analyzed. Future research could benefit from integrating different political and methodological perspectives.

In order to reach a balanced NPD portfolio, the potentially dysfunctional biases which characterize political processes from idea generation to project selection should be addressed. A concept of NPD portfolio management is proposed which considers the management of power and politics.

This paper contributes to a more comprehensive overview of political approaches of NPD project selection and serves as a sound basis for future research. The relevance and implications of politics for NPD portfolio management are demonstrated.

Recent literature has proposed many theoretical methods to help decision makers choose an appropriate project delivery system (PDS) in a rational manner. None of these articles however systematically compare and systematize the available PDS selection methods and guide decision makers in choosing a method that best meets their PDS decision‐making circumstances. This paper aims to bridge this gap.

Four groups of PDS selection methods, namely, guidance (e.g. decision charts and guidelines), multi‐attribute analysis (e.g. multi‐attribute utility theory and analytical hierarchical process), knowledge‐ and experience‐based (e.g. case‐based reasoning), and mix‐method approaches are reviewed, compared and systematized.

The discussed methods vary in their underlying concepts, complexities of implementation and levels of required information. They also differ in the ways how decision makers' preferences are elucidated, expressed and measured. A conceptual framework is proposed to help decision makers match a PDS selection method with their decision‐making circumstances.

The paper highlights limitations of the discussed methods, and presents areas for future research.

This paper helps decision makers develop a fundamental understanding of the available PDS selection methods, and match a PDS selection method with their unique decision‐making circumstances. Using a suitable method will improve the decision‐making efficiency.

The purpose of this study is to develop a methodology in which alternate Six Sigma projects are prioritized and selected using appropriate multi-criteria decision-making (MCDM) methods in healthcare organizations. This study addresses a particular gap in implementing a systematic methodology for Six Sigma project prioritization and selection in the healthcare industry.

This study develops a methodology in which alternate Six Sigma projects are prioritized and selected using a modified Kemeny median indicator rank accordance (KEMIRA-M), an MCDM method based on a case study in healthcare organizations. The case study was hypothetically developed in the healthcare industry and presented to demonstrate the proposed framework’s applicability and validity for future decision-makers who will take place in Six Sigma project selection processes.

The study reveals that the Six Sigma project prioritized by KEMIRA-M assign the highest ranks to patient satisfaction, revenue enhancement and sigma level benefit criteria, while resource utilization and process cycle time receive the lowest rank.

The methodology developed in this paper proposes an MCDM-based approach for practitioners to prioritize and select Six Sigma projects in the healthcare industry. The findings regarding patient satisfaction and revenue enhancement mesh with the current trends that dominate and regulate the industry. KEMIRA-M provides flexibility for Six Sigma project selection and uses multiple criteria in two-criteria groups, simultaneously. In this study, a more objective KEMIRA-M method was suggested by implementing two different ranking-based weighting approaches.

This is the first study that implements KEMIRA-M in Six Sigma project prioritization and selection process in the healthcare industry. To overcome previous KEMIRA-M shortcomings, two ranking based weighting approaches were proposed to form a weighting procedure of KEMIRA-M. As the first implementation of the KEMIRA-M weighting procedure, the criteria weighting procedure of the KEMIRA-M method was developed using two different weighting methods based on ranking. The study provides decision-makers with a methodology that considers both benefit and cost type criteria for alternates and gives importance to experts’ rankings related to criteria and the performance values of alternates for criteria.

The purpose of this study is to investigate project selection in the context of business management with the specific aim of understanding the role of business models in project selection. The logic followed for making decisions and selecting projects significantly influences construction companies’ success.

The research objective is pursued by conducting a multiple-case study. Managers acting in key decision-making roles from eight construction companies are interviewed. A conceptual framework is developed for analysing the interview data and the prevailing project selection practices in construction.

The findings suggest that project selection is not guided by any specific business model, but that the decision-making process is dominated more by short-term factors such as need of work and profitability. Thus, estimation know-how largely determines the kind of projects companies are willing to consider, regardless of their competence to deliver them.

The study produces a hypothesis that ignorance of business models in project selection and their general underutilisation in management have negative effects on performance of the construction industry. More consistent management practice would enable the development of business models and processes, contributing to performance and help companies to distinguish themselves from each other.

As opposed to previous studies that have produced bidding models that emulate the current industry practices, this research analyses the prevailing logic of project selection from a more critical perspective. In addition, the project selection practices of Finnish construction companies have not been investigated previously.

This paper aims to deal with the selection of the sustainability-oriented Green Lean Six Sigma (GLS) project for the manufacturing industry in the complex decision-making environment. Moreover, the study also proposes a GLS implementation framework for improved organizational performance.

GLS project selection has been done based on the six sustainability-oriented criteria formed from 17 sub-criteria (found from the literature and developed by authors). The weights of the criteria have been determined through the entropy method. The projects have been ranked based on the criteria through the advanced decision-making approach: grey relation analysis (GRA). The results of the study were validated using best worst method and sensitivity analysis.

It has been found that the productivity-related criterion is the most significant among other criteria with entropy weight of 0.2721. GRA has been used in this research work to rank the potential GLS projects in a manufacturing industry based on six sustainability criteria, to select a project that exhibits the maximum potential for sustainable improvement. The machine shop has been found as the most significant GLS project with grey relation grade of 0.4742.

The present study facilitates practitioners and industrial managers to implement an inclusive GLS approach for improved sustainability dynamics through effective GLS project selection and implementation framework.

With increased globalized competition in recent times, new projects are being considered as the foundation stone for organizational success. The decision-making becomes quite complex to select an effective project due to the intriguing nature of various criteria, sub-criteria and different aspects of sustainability. To the best of the authors’ knowledge, the present study is the first of its kind that provides ways for the selection of sustainability-oriented GLS projects.

The consideration of the substitution phenomenon in the project portfolio selection problem can improve the robustness of project portfolio selection and help enterprises better achieve their strategic objectives. However, the existence of inter-project risk propagation will have a negative impact on project substitution. This paper proposes a new framework for project portfolio selection and constructs a risk propagation model based on strategic objectives to study the impact of risk propagation on substitution in the project portfolio.

The authors first construct a risk propagation model based on strategic objectives to describe the risk propagation between projects. Then the project substitution phenomenon based on risk propagation is put forward, and the calculation method of substitution loss is given. Finally, a robust project portfolio selection framework based on strategic objectives considering risk propagation is constructed.

The analysis of a case study demonstrates that (1) With the increase of risk intensity, the strategic loss of the same project portfolio increases linearly, and under the same risk intensity, the more projects in the portfolio, the stronger the robustness. (2) Considering risk propagation, the effect of project substitution is significantly weakened, and the strategic loss rate of the project portfolio is significantly increased compared with that of a direct attack.

This study is the first to take the project substitution into account in the project portfolio selection process. Moreover, the authors describe inter-project risk propagation and analyze the impact of risk propagation on the project substitution phenomenon. Finally, the authors extend the evaluation index of robustness. This paper puts forward a new way to solve the problem of project portfolio selection.

The 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.

This 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.

A “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.

This 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.

This study aims to develop a model for project portfolio selection considering organizational goals such as budgets, sustainability cash flow and reinvestment strategy under an uncertain environment.

A multi-objective mathematical programming model is proposed for project selection, which takes the social, environmental and financial aspects into account as the objectives of the project portfolio selection problem. The project evaluation and selection process in one of the large capitals in the Middle East with numerous urban construction projects was considered as a real case study, in which the subjects of environmental and social sustainability are of great importance. Then, the most significant criteria for project evaluation and selection based on sustainability were identified and ranked using the fuzzy best-worst method (BWM).

The criterion of “defining clear and real objectives” was ranked first, “project investment return period” was ranked second, “minimum changes in the predicted range” was ranked third, and the other ten sustainability indicators were ranked as well. Next, the presented mathematical programming model was solved using the augmented e-constraint method. The sensitivity analysis indicated that increasing the amount of investments in projects would increase their net present value. Also, increased investment had no effect on sustainability, while decreased investment caused sustainability to not being optimal.

This study focuses on the impact of the amount of investments on projects, and the associated costs of sustainable projects. Further to the authors' knowledge, there has been no relevant study taking uncertainty into account. Also, very few studies proposed a mathematical programming model for the project portfolio selection problem. Moreover, this research uses the brainstorming and Delphi method to identify the sustainability indicators influencing the organization and screens the evaluation indicators. Furthermore, the weights of the evaluation indicators are determined using the fuzzy BWM based on the consistency of opinions.