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Compliant mechanism has been receiving a great interest in precision engineering. However, analytical methods involving their behavior analysis is still a challenge because there are unclear kinematic behaviors. Especially, design optimization for compliant mechanisms becomes an important task when the problem is more and more complex. Therefore, the purpose of this study is to design a new hybrid computational method. The hybridized method is an integration of statistics, numerical method, computational intelligence and optimization.

A tensural bistable compliant mechanism is used to clarify the efficiency of the developed method. A pseudo model of the mechanism is designed and simulations are planned to retrieve the data sets. Main contributions of design variables are analyzed by analysis of variance to initialize several new populations. Next, objective functions are transformed into the desirability, which are inputs of the fuzzy inference system (FIS). The FIS modeling is aimed to initialize a single-combined objective function (SCOF). Subsequently, adaptive neuro-fuzzy inference system is developed to modeling a relation of the main geometrical parameters and the SCOF. Finally, the SCOF is maximized by lightning attachment procedure optimization algorithm to yield a global optimality.

The results prove that the present method is better than a combination of fuzzy logic and Taguchi. The present method is also superior to other algorithms by conducting non-parameter tests. The proposed computational method is a usefully systematic method that can be applied to compliant mechanisms with complex structures and multiple-constrained optimization problems.

The novelty of this work is to make a new approach by combining statistical techniques, numerical method, computational intelligence and metaheuristic algorithm. The feasibility of the method is capable of solving a multi-objective optimization problem for compliant mechanisms with nonlinear complexity.

This study aims to identify key knowledge enabling factors (KEFs) which can enable construction companies to improve various organizational effectiveness outcomes (OEOs).

Using a questionnaire, data are collected from construction companies in Vietnam. Mean score method is used to calculate the mean values of KEFs. In addition, regression analysis is used to identify KEFs which significantly affect OEOs.

A list of 32 KEFs, whose ranking orders of importance are provided according to different types of construction companies, is presented. In addition, different lists of specific KEFs which could significantly affect different OEOs are identified. Furthermore, seven key KEFs which could have a significant impact on many OEOs are highlighted.

The findings of this study could help construction companies to know the controllable KEFs, on which they should focus more. Hence, they could perform these KEFs properly to improve various aspects of organizational effectiveness.

This study identifies 32 KEFs and 10 OEOs specifically for knowledge management in construction companies. This study also provides construction companies with a better understanding of the impact of KEFs on various aspects of organizational effectiveness. Hence, they could develop effective KEFs-based management strategies to enhance various aspects of organizational effectiveness.

Official development assistance (ODA) education projects have played a crucial role in improving education and training fields in developing countries, but are often facing several considerable challenges (e.g. long implementation time). Thus, this study aims to identify critical success factors (CSFs) in ODA education projects and investigate the influences of CSFs on ODA project performance measured by 11 nonprofit outcomes (NPOs).

A comprehensive literature review and expert interviews were conducted to compile a list of 35 potential success factors for ODA education projects. Using a survey questionnaire, 143 valid responses were collected from practitioners joining ODA projects in Vietnam. Various statistical methods (e.g. mean score method, Spearman rank correlation test, analysis of variance test, factor analysis and regression analysis) were used to analyze the collected data.

This research identified seven CSFs for ODA education projects in Vietnam: comprehensive project management competency (C1), clarity and compliance in project execution (C2), transparency and committed funding (C3), external context conditions (C4), well-controlled design and project management procedures (C5), preparations in equipment and complexity insight (C6) and punctual site delivery (C7). Furthermore, the results of regression analysis indicated that comprehensive project management competency (C1) and transparency and committed funding (C3) could significantly affect various NPOs.

This study offers significant insights for practitioners (e.g. project managers) to improve ODA projects’ performance and effectiveness in the education and training sector of a developing country context (like Vietnam).

The purpose of this paper is to identify risk patterns of road and bridge projects in Vietnam, where the construction market is emerging but attractive to construction organizations, especially foreign companies.

Using a questionnaire, experienced practitioners of various contractors were interviewed to collect risk-related data in terms of actual likelihood and impact from road and bridge construction projects in Vietnam. Using the collected data of actual likelihood and impact, the specific probability and impact of risk factors were determined for different types of road and bridge projects, including small and medium type, big type, government-funding type, and other-funding type (e.g. official development assistance funds, public-private partnership).

The results of analysis indicate the specific probability and impact of risk factors in four risk themes, including contractor-related, project-related, owner-related, and external risks. Actual risk patterns for different types of road and bridge projects in Vietnam were identified.

The identification of actual risk patterns could help practitioners to know which risk factors are severe in frequency and/or impact. Hence, they could establish proper strategies to manage risk-related problems of road and bridge projects, in which they are directly involved.

The findings of this study could provide construction companies, especially foreign companies, with a better understanding of real risk panorama in Vietnamese road and bridge construction. Hence, they could make effective improvements on risk management of road and bridge projects in Vietnam.

This article traces the transformation of hát bội, a form of traditional opera in Southern Vietnam, from its primary role as entertainment into a religious activity after the Reform (Đổi Mới) were enacted in 1986.

This research is based on ethnological fieldwork complemented by a review of historical documents and of the available literature on hát bội, cultural policies and on data collected from interviews with artists and spectators at the festival at the shrine to the Lady of the Realm.

Before 1986, hát bội was performed either as a stand-alone entertainment during the fair portion of community festivals or as part of religious ceremonies. The Reform and the accompanying relaxation of state control over religion and culture promoted the resurgence of popular religious fairs across the nation. New opportunities for hát bội to revive opened, artists left state-sponsored troupes to join private companies that catered to religious festivals. But almost exclusive involvement in religious rites has led to artistic stasis for private hát bội troupes.

This research constitutes novel insights of how the Reform in Vietnam affects the transformation of a traditional performance form.

Public–private partnership (PPP) projects play a pivotal role in fostering infrastructure development in developing countries. This study aims to identify major barriers and critical success factors (CSFs) for PPP projects in Vietnam.

The study initially conducted an extensive literature review and interviewed industry experts to compile a comprehensive list of barriers and success factors. Subsequently, a survey involving 250 construction professionals was conducted to assess these identified factors. The research used both ANOVA test and hierarchical regression analysis to explore the relationship between participants’ characteristics and assessments.

The results could provide a valuable reference for practitioners by assessing barriers and CSFs in PPP projects. Specifically, the ANOVA analysis indicated a positive correlation between barrier assessment and participants’ experience, while the influence of participants’ sector on the evaluation was minor. Furthermore, the hierarchical regression analysis demonstrated that participants’ sector did not moderate the relationship between barrier assessment and industry experience.

This research contributes to the existing literature by offering empirical insights into barriers and CSFs specific to PPP projects in a developing country context. The findings highlight the crucial role of experienced professionals in ensuring PPP project success. Moreover, the study provides construction practitioners with a better understanding of the essential factors and supports the development of effective management strategies for future PPP projects.

The purpose of this paper is to develop several predictive models for estimating the structural construction cost and establish range estimation for the structural construction cost using design information available in early stages of residential building projects.

Information about residential building projects is collected based on project documents from construction companies with regard to the design parameters and the actual structural construction costs at completion. Storey enclosure method (SEM) is fundamental for determining the building design parameters, forming the potential variables and developing the cost estimation models using regression analysis. Nonparametric bootstrap method is used to establish range estimation for the structural construction cost.

A model which is developed from an integration of advanced SEM, principle component analysis and regression analysis is robust in terms of predictability. In terms of range estimation, cumulative probability-based range estimates and confidence intervals are established. While cumulative probability-based range estimates provide information about the level of uncertainty included in the estimate, confidence intervals provide information about the variability of the estimate. Such information could be very crucial for management decisions in early stages of residential building projects.

This study could provide practitioners with a better understanding of the uncertainty and variability included in the cost estimate. Hence, they could make effective improvements on cost-related management approaches to enhance project cost performance.

This study aims to develop a strategic framework for the success of coastal urban projects in Vietnam, which is one of the Asia Pacific countries significantly affected by climate change.

A questionnaire was used to collect data from practitioners in Vietnam. Principal component analysis (PCA) technique was used to identify critical success factors (CSFs) of coastal urban projects. A strategy map for the success of coastal urban projects was also proposed using the balanced scorecard (BSC) method.

This study identified 41 project success factors that could contribute to project success, and thence, extracted 11 CSFs for coastal urban projects using the PCA technique. In addition, 11 key performance indicators (KPIs) for coastal urban projects were listed and their linking with project success factors and CSFs was explored. Furthermore, a strategy map for the success of coastal urban projects was proposed using the BSC method. The strategy map included five perspectives: learning and growth, internal processes, social and environmental performance, financial performance, and stakeholders' satisfaction.

This study identified 11 CSFs for coastal urban projects and proposed a strategy map for the success of coastal urban projects.

The purpose of this paper is to predict implementation cost contingencies for residential construction projects in flood-prone areas, where floods with storms frequently cause serious damage and problems for people.

Expert interviews are conducted to identify the study variables. Based on bills of quantities and project documents, historical data on residential construction projects in flood-prone areas are collected. Pearson correlation analysis is first used to check the correlations among the study variables. To overcome multicollinearity, principal component analysis is used. Then, stepwise multiple regression analysis is used to develop the cost prediction model. Finally, non-parametric bootstrap method is used to develop range estimation of the implementation cost.

A list of project-related variables, which could significantly affect implementation costs of residential construction projects in flood-prone areas, is identified. A model, which is developed based on an integration of principle component analysis and regression analysis, is robust. Regarding range estimation, 10, 50 and 90 percent cost estimates, which could provide information about the uncertainty levels in the estimates, are established. Furthermore, implementation cost contingencies which could show information about the variability in the estimates are determined for example case projects. Such information could be critical to cost-related management of residential construction projects in flood-prone areas.

This study attempts to predict implementation cost contingencies for residential construction projects in flood-prone areas using non-parametric bootstrap method. Such contingencies could be useful for project cost budgeting and/or effective cost management.