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To present a robust optimal design technique in the presence of system parameters uncertainties.

The properties of normally distributed random variables are exploited, together with surface response fitting techniques, with the aim to reduce the computational cost in assessing the effect of uncertainties.

A fast approximate method for computing statistical average is presented together with its implementation for the design of magnets for magnetic resonance imaging.

Future research will be focused to multi‐dimensional problems and to the best choose of closed form expressions to evaluate statistical moments fitting.

Robust optimal design methodologies are receiving an increasing interest in both academic and industrial research, due to their capability of coping with construction uncertainties and tolerances.

The effectiveness of the simplified method has been demonstrated for an analytical example and on a simplified superconducting magnet design. The proposed strategy is quite general and it can be applied to a wide class of optimal design problems.

An effective approach to the optimal design of electromagnetic devices should take into account the effect of mechanical tolerances on the actual devices performance. A possible approach could be to match a Pareto optimality study with a Monte Carlo analysis by randomly varying the constructive parameters. In this paper it is shown how such an analysis can be used to allow an expert designer to select among different Pareto optimal designs.

The role of the parameters uncertainness in the optimal design of electromagnetic devices is discussed and an efficient strategy to look for robustness of feasible solutions is proposed. A suitable modification of the objective function (OF) is used to rank different device configurations on the basis of their ability to maintain the required performances against small parameters modifications due to construction tolerances. In the frame of a genetic algorithm approach, the modified OF has been able to address the evolutionary optimisation towards more robust solutions.

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.

The purpose of this paper is to propose an integrated earned value management (EVM) approach to control quality, cost, schedule and risk of projects.

This study represents a new EVM framework by considering a quality control index. Particularly, some control indices and cumulative buffers are defined by two proposed, methods, namely the linear- and Taguchi-based methods. These methods are implemented in three different projects in different industries.

According to the results, integration of the quality index creates a better control situation by providing more accurate information. Hence, project managers could comprehensively monitor the status of important factors to make more precise decisions while maintaining the simplicity of their analysis.

From the methodological and theoretical features, this paper offers new visions because, to the best of authors’ knowledge, no comparable study has been conducted before.

Restorative experiences relieve fatigue or stress, leading people to feel more energetic. Activation theory and the nature–dose framework hold travel duration as a crucial influence on restorative effects, yet these factors may not demonstrate a simple linear relationship. This paper, thus, aims to explore the relationship between travel duration and restoration based on a survey conducted during a seven-day holiday (the longitudinal data spanned two months); and explore the reasons for this relationship and the mechanisms for lasting restorative effects based on diary analysis.

Mixed methods were used in this study. Questionnaires regarding restorative effects were administered to 232 people at six time points before, during and after a holiday. Participants were also asked to keep a diary during their trips. Data were first tested for common method bias and were then processed via independent sample t-tests, analysis of variance and time-series analysis.

Restorative effects were consistently higher in the travel group than in the non-travel group. Additionally, an inverted U-shaped relationship emerged between travel duration and the restorative effects of a holiday; a moderate duration had stronger restorative effects than a duration that was too long or too short. More importantly, the study found that participants who traveled for a moderate duration (longer or shorter) engaged in non-judgmental challenging (relaxing) activities at least once. They also demonstrated greater eudaimonism (hedonism) and stronger, more sustained restoration versus the original set point. In addition, results revealed how travel activities, emotions, moderators and restorative effects were constructed.

Longitudinal data indicated an inverted U-shaped relationship between travel duration and restoration. Achieving lasting restorative effects requires effort and non-judgmental challenging activities for a moderate travel duration and frequency. The study uncovered mechanisms influencing the relationship between travel experiences and restorative effects. The results offer guidance for research on “travel prescriptions” and for the health and stress relief market.

Inverted U-shaped curve for different travel durations and restorative effects at T3.

The non-judgmental challenging group showed lasting and stronger restorative effects over the next two months.

恢复性体验是指从疲劳或压力状态恢复到感觉更好或更有活力的状态。基于激活理论和自然剂量框架, 旅行停留时长是恢复效果的一个关键变量, 但两者之间可能并不是简单的线性关系。本文旨在（1）基于两个月的纵向数据, 探讨固定假期旅行停留时长与恢复效果之间的关系; （2）根据假期日记内容进一步分析以上关系产生的可能原因及达到持久恢复效果的作用关系。

该研究采用了混合方法。在度假前、度假中和度假后的六个纵向时间点, 对232人进行了与恢复效果有关的问卷调查。且参与者在整个假期中每天记日记。对数据进行了常见方法偏倚、独立样本t检验、方差分析和时间序列分析。

（1）在整个调查期间, 旅行组的恢复效果始终高于非旅行组; （2）旅行停留时长与恢复效果之间的关系呈倒U型, 适度的旅行停留时长可以得到更好的恢复效果; （3）适度（太长或太短）旅行停留时长的参与者更多地参与非评判的挑战性（享乐性）的活动, 表现出更大的实现主义（享乐主义）倾向, 并获得了更强、更持久的恢复效果。进一步地, 研究结果揭示了旅游活动类型、情绪、调节变量和恢复性效果之间的作用关系。

纵向数据分析表明旅行停留时长和恢复效果之间呈现倒U型, 要实现持久的恢复效果需要努力参与非评判的挑战性活动。这项研究揭示了旅行体验和恢复效果之间的关系, 研究结果为促进旅游成为健康和压力缓解市场的处方提供了理论基础和实践指导。

Las experiencias reparadoras alivian la fatiga o el estrés, haciendo que las personas se sientan con más energía. La teoría de la activación y el marco naturaleza-dosis sostienen que la duración del viaje es una influencia crucial en los efectos reconstituyentes que provocan en las personas, aunque estos factores pueden no demostrar una relación lineal simple. Así pues, este artículo pretende 1) explorar la relación entre la duración del viaje y la recuperación de las personas, a partir de una encuesta realizada durante unas vacaciones de 7 días (los datos longitudinales abarcaron dos meses); y 2) explorar las razones de esta relación y los mecanismos de los efectos reparadores duraderos a partir del análisis de diarios.

En este estudio se utilizaron métodos mixtos. Se administraron cuestionarios sobre los efectos reconstituyentes a 232 personas en seis momentos antes, durante y después de unas vacaciones. También se pidió a los participantes que llevaran un diario durante sus viajes. En primer lugar, se comprobó que los datos no presentaran sesgos por métodos comunes y, a continuación, se procesaron mediante pruebas t de muestras independientes, análisis de la varianza y análisis de series temporales.

Los efectos reparadores fueron sistemáticamente mayores en el grupo que viajó que en el que no viajó. Además, surgió una relación en forma de U invertida entre la duración del viaje y los efectos reconstituyentes de las vacaciones; una duración moderada tuvo efectos reparadores más fuertes que una duración demasiado larga o corta. Por último, los participantes que viajaron durante una duración moderada (más larga o más corta) realizaron más actividades estimulantes no perjudiciales (relajantes). También demostraron un mayor eudaimonismo (hedonismo) y una recuperación más fuerte y sostenida en comparación con el punto de partida inicial. Los resultados revelaron cómo se relacionaban las actividades de viaje, las emociones, los moderadores y los efectos reparadores.

Los datos longitudinales indicaron una relación en forma de U invertida entre la duración del viaje y la recuperación de las personas. Lograr efectos reparadores duraderos requiere esfuerzo y actividades para una duración moderada del viaje. El estudio descubrió mecanismos que influyen en la relación entre las experiencias de viaje y los efectos reconstituyentes. Los resultados ofrecen orientaciones para la investigación sobre las “recetas de viaje” y para el mercado de la salud y el alivio del estrés.

This study aims to analyze the influence of taxes and corporate governance on the dividend policy of Brazilian companies.

The authors identify the changes of the tax legislation in Brazil in the period 1986-2011 and check their effect on corporate dividend policies for preferred and common shares. The authors use panel data Probit and Tobit estimation to verify the probability of companies to pay dividends under different tax regimes. The final sample comprises 672 companies, 1,159 traded stocks and 30,134 observations

The authors’ results suggest that changes in the tax legislation have a significant influence on dividend payments. Also, firms do not follow target payout ratios, but dividends are moderately dependent on past payments. Dividend payouts are affected by stock voting rights, privatization and dividend deductibility. Changes in regulation that reduce the agency problems among shareholders affect positively payout ratios.

For managers, maximizing shareholders’ value requires taking into account the consequences of the taxation when designing financial policies for the firm. For investors, stock portfolio selection should take into account payout behavior and how changes in dividend taxation affect stocks’ value. For policymakers, the effects of changes in the tax code on corporate behavior are of utmost importance to stimulate private investment and economic growth.

There are several tax law changes in Brazil within the period analyzed, creating a good opportunity to study the effect of taxation on dividend policy and its dynamics over time.

Selecting the optimal supplier is a challenging managerial decision that involves several dimensions that vary over time. Despite the considerable attention devoted to this issue, knowledge is required to be updated and analyzed in this field. This paper reveals new opportunities to advance supplier selection (SS) research from a multidimensional perspective. Moreover, this study aims to formalise SS knowledge to enable the appropriate selection of sustainable, resilient and circular criteria.

This study is developed in two stages: first, a systematic literature review is conducted to select relevant papers. Descriptive and thematic analyses are employed to analyze criteria, solving approaches and case studies. Second, a criterion knowledge-based framework is developed and validated by experts to be implemented as ontology using Protégé software.

Evaluating the viability of suppliers need further studies to integrate other criteria and to align SS objectives with research advancement. Artificial intelligence tools are needed to revolutionize and optimize the traditional techniques used to solve this problem. Literature lucks frameworks for specific sectors. The proposed ontology provides a consistent criteria knowledge base.

For academics, the results of this study highlight opportunities to improve the viable SS process. From a managerial perspective, the proposed ontology can assist managers in selecting the appropriate criteria. Future works can enrich the proposed ontology and integrate this knowledge base into an information system.

This study contributes to promoting knowledge about viable SS. Capitalizing the knowledge base of criteria in a computer-interpretable manner supports the digitalization of this critical decision.