Search results

This study aims to investigate the service performances of a new full-section asphalt concrete waterproof sealing structure (FSACWSS) for the high-speed railway subgrade through on-site tracking, monitoring and post-construction investigation.

Based on the working state of the waterproof sealing structure, the main functional characteristics were analyzed, and a kind of roller-compacted high elastic modulus asphalt concrete (HEMAC) was designed and evaluated by several groups of laboratory tests. It is applied to an engineering test section, and the long-term performance monitoring and subgrade dynamic performance testing system were installed to track and monitor working performances of the test section and the adjacent contrast section with fiber-reinforced concrete.

Results show that both the dynamic performance of the track structure and the subgrade in the test section meet the requirements of the specification limits. The water content in the subgrade of the test section is maintained at 8–18%, which is less affected by the weather. However, the water content in the subgrade bed of the contrast section is 10–35%, which fluctuates significantly with the weather. The heat absorption effect of asphalt concrete in the test section makes the temperature of the subgrade at the shoulder larger than that in the contrastive section. The monitoring value of the subgrade vertical deformation in the test section is slightly larger than that in the contrastive section, but all of them meet the limit requirements. The asphalt concrete in the test section is in good contact with the base, and there are no diseases such as looseness or spalling. Only a number of cracks are found at the joints of the base plates. However, there are more longitudinal and lateral cracks in the contrastive section, which seriously affects the waterproof and sealing effects. Besides, the asphalt concrete is easier to repair, featuring good maintainability.

This research can provide a basis for popularization and application of the asphalt concrete waterproof sealing structure in high-speed railways.

There are two aims of this research: one is to prove the interactive effect of supply chain integration (SCI) on performance and the other is to ascertain gaps in performance among levels of SCI. The population of this research is international freight forwarders and the collected data is used in testing hypotheses through various analytical methods such as factor analysis, Cronbach’s alpha, cluster analysis, ANOVA, MANOVA, ANCOVA, post hoc analysis and regression analysis. First, the interaction between internal integration and external integration improves customer performance and financial performance. The forwarders improve internal processes following information acquired from customers and the information is shared with logistics service providers, followed by high performance. Second, gaps in performance among levels of SCI are verified. Managers of the forwarders make strategic decision making on the basis of their recognition of environment and, as a result, the forwarders enjoy different performance.

Technical solutions can be important when key communicators take on the task of making sense of social media flows during crises. However, to provide situation awareness during high-stress assignments, usability problems must be identified and corrected. In usability studies, where researchers investigate the user-friendliness of a product, several types of data gathering methods can be combined. Methods may include subjective (surveys and observations) and psychophysiological (e.g. skin conductance and eye tracking) data collection. This chapter mainly focuses on how the latter type can provide detailed clues about user-friendliness. Results from two studies are summarised. The tool tested is intended to help communicators and journalists with monitoring and handling social media content during times of crises.

The purpose of this work is to optimize the monitoring of vibrations on dynamometric test rigs for railway brakes. This is a quite demanding application considering the continuous increase of performances of high-speed trains that involve higher testing specifications for brake pads and disks.

In this work, authors propose a mixed approach in which relatively simple finite element models are used to support the optimization of a diagnostic system that is used to monitor vibration levels and rotor-dynamical behavior of the machine. The model is calibrated with experimental data recorded on the same rig that must be identified and monitored. The whole process is optimized to not interfere with normal operations of the rig, using common inertial sensor and tools and are available as standard instrumentation for this kind of applications. So at the end all the calibration activities can be performed normally without interrupting the activities of the rig introducing additional costs due to system unavailability.

Proposed approach was able to identify in a very simple and fast way the vibrational behavior of the investigated rig, also giving precious information concerning the anisotropic behavior of supports and their damping. All these data are quite difficult to be found in technical literature because they are quite sensitive to assembly tolerances and to many other factors. Dynamometric test rigs are an important application widely diffused for both road and rail vehicles. Also proposed procedure can be easily extended and generalized to a wide value of machine with horizontal rotors.

Most of the studies in literature are referred to electrical motors or turbomachines operating with relatively slow transients and constant inertial properties. For investigated machines both these conditions are not verified, making the proposed application quite unusual and original with respect to current application. At the same time, there is a wide variety of special machines that are usually marginally covered by standard testing methodologies to which the proposed approach can be successfully extended.

The purpose of this paper is to shed light on the relationship between the adoption of Social Accountability 8000 (SA8000) – which is considered the most important ethical certification standard – and firm performance, building on agency and contingency theories.

The authors analyse secondary longitudinal balance sheet data of listed firms employing a rigorous event-study approach and compare SA8000-certified companies to different control groups based on three matching criteria, i.e., industry, size, and pre-certification performance. The authors then study the moderating effects of the cultural features, the country’s development level, and the labour intensity on the causal relationship through multiple regression methods.

The authors find that SA8000 certification positively affects labour productivity and sales performance but has no effect on profitability. Furthermore, the study supports that the relationship between SA8000 and profitability is moderated by two cultural features of the home country of the firms (i.e. power distance and uncertainty avoidance).

This is the first study, which empirically tests the effects of the ethical certification SA8000 on firm performance using a cross-country sample. In addition, the authors contribute to the wider debate on the effects of corporate social responsibility practices on firm performance.

This study examines the test's predictive validity of English language performance and compares test constructs to identify the most effective predictors of English language performance.

Data were collected and analysed from test scores of students enrolled in the foundation year (N = 84) and level 2 (N = 127) in the faculty of English at a Saudi university using correlation and regression tests.

The findings revealed that the General Aptitude Test (GAT) is effective in predicting English performance for students in level 2 and that the error detection task is the most effective predictor of performance in English reading.

The study provides support for the validity of the GAT as a university admission requirement for English language courses in the Arabic-speaking world.

This study examines the GAT's power using a fine-grained approach by deriving scores from its breakdown constructs to predict the performance of English skills at the university level.

People seem to function according to different models, which implies that in business and social sciences, heterogeneity is a rule rather than an exception. Researchers can investigate such heterogeneity through multigroup analysis (MGA). In the context of partial least squares path modeling (PLS-PM), MGA is currently applied to perform multiple comparisons of parameters across groups. However, this approach has significant drawbacks: first, the whole model is not considered when comparing groups, and second, the family-wise error rate is higher than the predefined significance level when the groups are indeed homogenous, leading to incorrect conclusions. Against this background, the purpose of this paper is to present and validate new MGA tests, which are applicable in the context of PLS-PM, and to compare their efficacy to existing approaches.

The authors propose two tests that adopt the squared Euclidean distance and the geodesic distance to compare the model-implied indicator correlation matrix across groups. The authors employ permutation to obtain the corresponding reference distribution to draw statistical inference about group differences. A Monte Carlo simulation provides insights into the sensitivity and specificity of both permutation tests and their performance, in comparison to existing approaches.

Both proposed tests provide a considerable degree of statistical power. However, the test based on the geodesic distance outperforms the test based on the squared Euclidean distance in this regard. Moreover, both proposed tests lead to rejection rates close to the predefined significance level in the case of no group differences. Hence, our proposed tests are more reliable than an uncontrolled repeated comparison approach.

Current guidelines on MGA in the context of PLS-PM should be extended by applying the proposed tests in an early phase of the analysis. Beyond our initial insights, more research is required to assess the performance of the proposed tests in different situations.

This paper contributes to the existing PLS-PM literature by proposing two new tests to assess multigroup differences. For the first time, this allows researchers to statistically compare a whole model across groups by applying a single statistical test.

The study’s objective was to ascertain the connection between secondary school students' test anxiety, academic self-concept, motivation and academic performance in mathematics. The difference between the academic performances of male and female secondary school students who exhibit high and low test anxiety, academic self-concept and motivation levels in mathematics.

Four hypotheses and four research questions were adopted. The design is a correlation. 42,299 mathematics students in senior school year two (SS2) made up the research population. A sample of 1,650 students was selected through a multi-stage sampling procedure. The main instruments used were the Mathematics Test Anxiety Questionnaire (MTAQ), Academic Self-Concept Questionnaire (ASQ) and Academic Motivation Questionnaire (AMQ) and students’ math scores. These instruments were validated by three experts and the reliability coefficients of 0.69, 0.68 and 0.68 were obtained for MTAQ, ASQ and AMQ, respectively, using Cronbach alpha. Pearson product moment correlation was used to analyze the data.

The study’s results showed a correlation between secondary school students' academic performance in mathematics and test anxiety, academic self-concept and motivation. There was a significant difference between secondary school male and female students' test anxiety; there was a significant difference between secondary school male and female students' self-concept and academic performance in mathematics, and there was a significant difference between secondary school male and female students' motivation and academic performance in mathematics.

The major contribution of this study is to investigate the connection between test anxiety, academic self-concept motivation and students’ mathematics performance. There is a difference between psychological variables, gender and mathematics performance.