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In order to make sure of the safety of a long-span suspension bridge under earthquake action, this paper aims to study the traveling wave effect of the bridge under multi-support excitation and optimize the semi-active control schemes based on magneto-rheological (MR) dampers considering reference index as well as economical efficiency.

The finite element model of the long-span suspension bridge is established in MATLAB and ANSYS software, which includes different input currents and semi-active control conditions. Six apparent wave velocities are used to conduct non-linear time history analysis in order to consider the seismic response influence in primary members under traveling wave effect. The parameters α and β, which are key parameters of classical linear optimal control algorithm, are optimized and analyzed taking into account five different combinations to obtain the optimal control scheme.

When the apparent wave velocity is relatively small, the influence on the structural response is oscillatory. Along with the increase of the apparent wave velocity, the structural response is gradually approaching the response under uniform excitation. Semi-active control strategy based on MR dampers not only restrains the top displacement of main towers and relative displacement between towers and girders, but also affects the control effect of internal forces. For classical linear optimal control algorithm, the values of two parameters (α and β) are 100 and 8 × 10–6 considering the optimal control effect and economical efficiency.

The emphasis of this study is the traveling wave effect of the triple-tower suspension bridge under multi-support excitation. Meanwhile, the optimized parameters of semi-active control schemes using MR dampers have been obtained, providing relevant references in improving the seismic performance of three-tower suspension bridge.

The purpose of this paper is to explore the teaching performance of Turkish Business Schools (BSs). It also aims to determine the degree of importance of factors affecting the teaching performance of Turkish BSs. The final objective is to test the functionality and applicability of the model.

This study presents a ranking approach based on grey relational analysis (GRA). While evaluating the BSs, data were collected for 19 Turkish BSs in terms of five main criteria such as OSS score; Number of faculty members; Number of students per faculty member; the mean of KPSS score; and the standard deviation of KPSS score. In the analysis, three weighted methods were integrated into the GRA in order to weight the criteria.

According to this result, the main factor influencing the teaching performance of Turkish BSs is the OSS score. This study can also confirm that the results obtained from the ranking orders using the proposed methods are reliable and these results can help decision makers to identify the best alternative.

In order to provide benchmarking data more effectively, in future, it would be helpful to collect data from both foundation and state universities with a research focus. Moreover, as an interesting suggestion for future research, fuzzy environment may be further integrated into the framework of GRA.

In contrast to prior research, this study makes comparisons based on the scores of national exams instead of different bibliometric indicators. Furthermore, there are no studies which have used GRA and these weighted methods as combined in education sector.

Clothing quality, performance, safety and health have become important considerations for consumer welfare. Properties of these aspects are encompassed on standards which regulates clothing products reaching consumers. The purpose of this paper is to categorize these aspects in a common platform by suggesting minimum requirements expected on readymade garments from which clothing standards compliance assessment is performed.

With the aid of standard compliance assessment model, scored Standard Compliance Rate (SCR) values of the discussed properties of clothing standardization are synthesized from a standard compliance matrix, and the compliance of any clothing standards are assessed and assigned a “Standard Compliance Index/Level (SCI/SCL)” ranging from non compliance to full compliance at six levels.

In reference to the standard compliance assessment model, 12 children and infant clothing standards, three from Kenya and nine from China, and eight protective clothing standards from Kenya, China, Britain and USA, two from each country, were assessed and the compliance level of each standard evaluated and results presented. The results of the study reveal the importance of every aspect of clothing standardization properties to fulfil the requirements of standard compliance assessment whereby, though they meet their role in developing Standard Compliance Index (SCI), they may have different impact depending with the context applied and the scope of every standard.

The selection of standardization parameters and characteristics, and the criteria for scoring some of the Standard Compliance Rating was subjective and may require mutual agreements between relevant bodies. Furthermore, this method can only be applied on clothing standards and not other textile testing standards.

The proposed method can be applied when evaluating and comparing specific clothing standards between bodies or countries. Clothing SCI would be of primary importance as a guide on required clothing quality specifications to designers, manufacturers, standard regulators and consumer welfare bodies.

This research reports the development of an original framework to assess compliance level of any clothing standard using standardization parameters and characteristics considered when determining the quality of a garment. It establishes a theoretical framework of clothing standards compliance assessment, which has not been reported in the literature to date.

Despite unanimity in the literature that eco-innovation (EI) leads to sustainable development, evidence remains limited on measuring EI efficiency with the Malmquist productivity index (MPI). In conventional data envelopment analysis (DEA) models, decision-making units (DMUs) are inclined to assign more favorable weights, even zero, to the inputs and outputs to maximize their own efficiency. This paper aims to overcome this shortcoming by developing a common set of weights (CSW).

Using goal programming, this study develops a CSW model to evaluate the EI efficiency of the organization for economic co-operation and development (OECD) countries and track their changes with MPI during 2010–2018.

Achieving a complete ranking of DMUs, findings show the higher discrimination power of the proposed CSW compared with the original DEA models. Furthermore, results reveal that Iceland, Latvia and Luxembourg are the only OECD countries that have incessantly improved their EI productivity (MPI > 1) from 2010 to 2018. On the other hand, Japan is the OECD country that has experienced the highest yearly EI efficiency during 2010–2018. This paper also found that Iceland has the highest MPI over 2010–2018.

More investment in environmental research and development (R&D) projects instead of generic R&D enables OECD members to realize more opportunities for sustainable development through minimizing energy use and environmental pollution in any form of waste and greenhouse gas emissions.

In addition to developing a novel common weights model for DEA-MPI to measure and evaluate the EI of OECD countries, this paper develops a CSW model by including the undesirable outputs for EI analysis.