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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.

Financial flexibility and investment efficiency are of vital importance in strategic choices at boardrooms, particularly in post-crisis recovery strategies. This study examines the moderating effects of investment efficiency and investment scale on the relationship between financial flexibility and firm performance.

The authors use sample of 10,755 US-listed firms over the period 2010–2021 to examine the relationships between investment scale, investment efficiency, financial flexibility and firm performance. Particular attention is paid to overinvestment and underinvestment.

Findings of this study reveal that financial flexibility mitigates investment inefficiency through reducing overinvestment. Financial flexibility contributes to boost a firm’s accounting and market performance. Additionally, investment efficiency and investment scale have moderating effects on the relationship between financial flexibility and firm performance. However, the influence of investment efficiency is greater than the influence of investment scale. Finally, the authors find that the direct and indirect effects of financial flexibility are stronger on market performance than accounting performance, implying that market is more sensitive to corporate financial policies.

Findings of this study have implications for scholars, decision-makers policymakers, investors and other stakeholders.

This study has its own limitations due to the sample selection issues, country context and the research model adopted by this study.

The novel contribution to the extant literature is incorporating the influence of investment scale and investment efficiency into the relationship between financial flexibility and firm performance.

Financial flexibility, investment efficiency and effective corporate governance mechanisms have been issues of concern to stakeholders. Yet, little empirical evidence on the combined moderating effects investment efficiency and corporate governance mechanisms on the nexus between financial flexibility and firm performance. This study aims to address this gap and extend the extant literature by examining the moderating effects of corporate governance and investment efficiency on the nexus between financial flexibility and financial performance.

The empirical study is based on progression analysis using a sample of 13,865 US listed companies selected from BoardEx (WRDS) for the period (2010–2022) with 89,198 firm-year observations.

Findings of this study indicate that financial flexibility improves firm value as well as accounting performance. Furthermore, the results reveal that both investment efficiency and corporate governance moderate the effect of financial flexibility on firm performance. The authors complement and extend the literature on the optimal investment strategies domain by showing that the combined impact of corporate governance mechanisms and investment efficiency strengthens the nexus between financial flexibility and firm performance.

Key limitations of this study due to the characteristics of the sample selection: country-specific context and proxies used by this study.

Findings of this study have managerial and theoretical implications for firms’ boardrooms, institutional and individual investors, regulators, academics and other stakeholders regarding behavioural aspects of investment decision-making.

The authors’ novel contribution to the extant literature is articulated by the conceptual framework underlying this study and by the new evidence regarding exploring the combined effect of corporate governance mechanisms on nexus between financial flexibility and companies’ performance.

The purpose of this paper is to present a low-cost, highly mobile system for performing street-level imaging. Street-level imaging and geo-location-based services are rapidly growing in both popularity and coverage. Google Street View and Bing StreetSide are two of the free, online services which allow users to search location-based information on interactive maps. In addition, these services also provide software developers and researchers a rich source of street-level images for different purposes – from identifying traffic routes to augmented reality applications. Currently, coverage for Street View and StreetSide is limited to more affluent Western countries with sparse coverage throughout south-east Asia and Africa. In this paper, we present a low-cost system to perform street-level imaging targeted towards the congested, motorcycle-dominant south-east Asian countries. The proposed system uses a catadioptric imaging system to capture 360-degree panoramic images which are geo-located using an on-board GPS. The system is mounted on the back of a motorcycle to provide maximum mobility and access to narrow roads. An innovative backwards remapping technique for flattening the images is discussed along with some results from the first 150 km which have been captured from Southern Vietnam.

The design was a low-cost prototype design using low-cost off-the-shelf hardware with custom software and assembly to facilitate functionality.

The system was shown to work well as a low-cost omnidirectional mapping solution targeted toward sea-of-motorbike road conditions.

Some of the pictures returned by the system were unclear. These could be improved by having artificial lighting (currently only ambient light is used), a gyroscope-stabilised imaging platform and a higher resolution camera.

This paper discusses a design which facilitates low-cost, street-level imaging for a sea-of-motorcycle environment. The system uses a catadioptric imaging approach to give a wide field of view without excessive image storage requirements using dozens of cameras.

The Covid-19 pandemic and the war in Ukraine are a real example of how uncertainty can trigger radical changes in the socio-economic system on a macro and micro scale. The indicated events contributed to the increase in the level of uncertainty, and its effects appeared in the real conditions of the functioning of international communities.

The purpose of the chapter is to determine the impact of the Covid-19 pandemic and the war in Ukraine on the situation of Polish consumers and the resulting behaviour in the context of business–consumer relations.

This goal was achieved through literature studies, analysis of changes in selected indicators of the economic situation and analysis of basic variables determining the relationships between consumers and suppliers.

The presented research results allow us to conclude that both the pandemic and war had an impact not only on the economic indicators but also the financial standing of households. We are seeing an increase in the differences between the nominal and real value of these incomes. Inflation is on the rise, forcing households to change their spending structure and look for savings. Of course, there have been and will be companies that do not have to be significantly affected by the effects of these events. In this group, companies related to the provision of IT infrastructure and specialising in establishing multidimensional relationships in the digital space should be pointed out.

Even though austenitic stainless steels have been extensively used in industries, owing to some of the characteristics of the material, its performance in machining is difficult to understand, in particular at high cutting speeds. There is no availability of dependable and in-depth studies pertinent to this matter. In this work, performance of AISI 304 austenitic stainless steel was studied in terms of surface roughness (Ra) and material removal rate (MRR) at high cutting speeds. Subsequently, parametric optimization and prediction for responses were carried out.

Turning operations were conducted using L9 orthogonal array and the outcomes were analyzed to attain optimal set of machining parameters for the responses using signal-to-noise (S/N) ratio and Pareto analysis of variance (ANOVA). In the present work, the cutting speed values were considered beyond the recommended range as designated by tool manufacturers. Finally, multiple regression models were developed to predict responses.

From the results, 350 m/min was found to be a significant speed. The investigation reveals that even though the speeds are taken beyond the recommended values, the results are favorable. The optimal machining parameters values for surface quality obtained were cutting speed of 350 m/min, feed of 0.15 mm/rev and depth of cut of 2.0 mm. In case of MRR, the optimal values were: cutting speed of 400 m/min, feed of 0.25 mm/rev and depth of cut of 2.0 mm. It was found out that there was an improvement in Ra and MRR (around 15 and 4%) due to optimization. The results indicate that Pareto ANOVA is easier than S/N ratio. This revealed that the feed rate and depth of cut were mostly affected parameters for Ra and MRR. The developed models are capable of predicting the responses accurately.

The outcome of the work reveals that even though the speeds were taken beyond the recommended value, the results are favorable for manufacturing industries when the tool cost is considered insignificant.

No work was reported on machining of the chosen material beyond the recommended cutting speed. Moreover, it was observed from the past works that cutting speeds were limited to 100–300 m/min.

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 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.