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This paper aims to identify empirically the influence of learning mechanisms provided by organizations on knowledge sharing in the organizational environment.

A quantitative study was developed in which a sample of 268 individuals from civil and military organizations of the Federal Direct Administration was researched. The questionnaire used was composed of the Organizational Learning Mechanism Scale, which was adapted at the time of the present study, in addition to a scale on knowledge sharing, which was developed within the scope of this research. After performing the factorial analysis for both scales, a canonical correlation analysis was performed between the group of variables associated with the learning mechanisms (independent variables) and the group of variables on knowledge sharing (dependent variables).

The results found in the canonical correlation analysis indicate that the learning mechanisms are responsible for explaining 35 per cent of the variance (R² = 0.352) of the group of variables on knowledge sharing.

The findings of this research can help the researched organizations to increase the knowledge management actions, mainly in relation to the actions that favor social interaction among the individuals in the work environment, making possible the exchange of knowledge and experiences in the internal organizational context, and exploring in a positive way actions related to internal acquisition.

The deeper knowledge about the relationship between organizational actions promoted by top management and knowledge support decision-making in the organizational environment regarding contextual factors that influence social interaction between individuals. In relation to the sharing of knowledge, a high correlation of knowledge absorption and reproduction aspects with the knowledge sharing phenomenon was perceived, so that the possibility of organizations thinking in ways that provide the individual with formal and informal environments can be foreseen.

The main contributions of this research are to measure the intensity of the relationship between learning mechanisms and knowledge sharing; and to test the predictive effect of learning mechanisms on knowledge sharing. Regarding the methodological aspects, it was opportune to approach the phenomenon through a little used lens in the context of administration research: the analysis of canonical correlation, which represents another look at the influence of the actions of the top management and the interaction of individuals. The discussions and the data analysis carried out in this research allow us to envisage significant contributions of this work to the analysis and theoretical refinement of the study of the variables treated.

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

Measuring internal response of online learning is seen as fundamental to absorptive capacity which stimulates knowledge assimilation. However, the evaluation of practice and research of validated instruments that could effectively measure online learning response behavior is limited. Thus, in this study, a new instrument was designed based on literature to determine the structural variables that exist in the online learning response behavior.

A structured survey was designed and distributed to 410 Malaysian students enrolled in higher-education institutions. The questionnaire has 38 items, all of which were scored using a seven-point likert scale. To begin with, exploratory factor analysis with three types of extraction methods (i.e. principal component, principal axis factoring and maximum likelihood) was used as the method for comparing the outcomes of each extraction method's grouping variables by constantly using a varimax rotation method. In the second phase, reliability analysis was performed to determine the reliability level of the grouping variables, and finally, correlation analysis was performed to determine the discriminant nomological validity of the grouping variables.

The findings revealed that nine grouping variables were retrieved, with all items having a good value of factor loading and communalities, as well as an adequate degree of reliability. These extracted variables have good discriminant and nomological validity, as evidenced by correlation analysis, which confirmed that the directions of relationships among the extracted dimensions follow the expected theory (i.e. positive direction) and the correlation coefficient is less than 0.70.

This study proposes a comprehensive set of questionnaires that measure the student's online learning response behavior. These questionnaires have been developed on the basis of an extensive literature review and have undergone a rigorous process of validity and reliability for the purpose of enhancing students' online learning response behavior.

This study's findings will aid academic practitioners in assessing the online learning response behavior of students, as well as enhancing the questionnaire's boost factor when administered in an online learning environment.

This paper aims to investigate the correlation between banking sector non-performing loans (NPLs) and the level of sustainable development.

Pearson correlation test statistic was used to assess the correlation between bank NPLs and sustainable development.

There is a significant positive correlation between banking sector NPLs and the level of sustainable development measured by the sustainable development index (SDI). The significant positive correlation is evident in European countries and in countries in the region of the Americas. There is a significant negative correlation between banking sector NPLs and achieving SDG3 and SDG7 in African countries and European countries. There is also a significant negative correlation between NPLs and achieving SDG10 in European countries. There is a significant positive correlation between banking sector NPLs and achieving SDG4 and SDG7 in the region of the Americas. There is also a significant positive correlation between NPLs and achieving SDG10 in African countries and in countries in the region of the Americas.

The present study is unique and different from other studies because it used a unique SDI to capture the level of sustainable development. The analysis is also unique because it covers several regions, which have not been covered in previous studies.

Literature is replete with studies indicating the need to develop students’ language skills; however, little research has emphasized the importance of language proficiency in enhancing learning or performance in specific content-area courses. This study investigates whether a student’s English language proficiency can be associated with her performance in specific cognitive skills (knowledge, comprehension, application, and analysis) in an introductory accounting course. Data is summarized from students’ performance on their first financial accounting examination as well as from students’ academic history records as maintained by the university. A correlation analysis of the cognitive skills score with student language proficiency is used to identify initial relationships; and multiple regression analysis is subsequently used to identify interrelations between combined multiple dependent variables and the language proficiency variables. While the results show no association between TOEFL and overall performance, the mean of the English composition courses do show a significant association with knowledge and comprehension cognitive skills scores on the first financial accounting course. No associations are attached to the application and analysis cognitive skills. The results are meaningful to faculty in balancing language proficiency with quality instruction in content-area courses.

Outsourcing is recognized as one of the critical factors for efficient execution of pharmaceutical supply chain management (PSCM), and many pharmaceutical companies engage in international outsourcing of services (IOS) to survive in global highly competitive business. Since the key success factors for both domestic & international alliances are partnership characteristics and strategic fit management, but there is no empirical research on this issue in Thai pharmaceutical partnership offshore outsourcing. Therefore, this survey of Thai and foreign companies, both contract providers (CPs) and contract manufacturers (CMs), seeks to indicate significant relationships among both outsourcing strategic fit and partnership types, including outsourcing performance outcome. This research is two-fold. First, the partnership types (Type I, II, & III), the strategic fit types (low fit, moderate fit, and good fit), and their correlations are analyzed. And second, their outsourcing performance (company revenues and growth rates) are presented. The results showed that the most of the Thai pharmaceutical outsourcing manufacturing are classified as the partnership Type II, as well as the moderate strategic fit, and strongly support the relationship between the two models. Both of the companies’ revenue and growth rate could predict the companies’ performances outcome for each of partnership and strategic fit types. However, it is not necessary that the most integrative type of partnership, Type III, will be always the best, because it depends also on the strategic fit between each pair of partners as well.

This study aims to establish the position of the European Union (EU-28) countries in the dynamics of international trade openness linkages and the Global Competitiveness Index (GCI) in correlation with the gross domestic product (GDP) per capita, research and development (R&D) expenditures, innovation capability and information and communication technology (ICT) adoption.

In the panel data set, comparative analyses were applied to scatter diagrams, correlation and regression analyses and structural equation models using Eurostat and World Economic Forum (WEF) data for the EU-28 countries in the period 2008–2019.

The empirical results did not confirm the hypotheses that a positive correlation exists between GCI and trade openness indicators and between GDP per capita and GCI. The ICT adoption and innovation capability increase GCI, which affects GDP per capita.

The empirical results provide a better understanding of the importance of trade policies, particularly in terms of trade openness and trade shares of the EU-28 countries, as it could contribute to increasing the GCI of the EU-28 countries. Furthermore, the results of this study underline the importance of ICT adoption and innovation capability and the need for appropriate government policies that improve global competitiveness.

This study, through empirical analysis, demonstrates the existence of correlations between trade openness (exports as % of GDP, imports as % of GDP and export market shares as % of world trade), R&D expenditures, innovation capability, ICT adoption, GDP per capita and the GCI in the EU-28 countries. In addition, this study contributes managerial and policy-based implications on driving forces of global competitiveness.

This paper aims to study the affecting factors on bird nesting on electronic railway catenary lines and the impact of bird nesting events on railway operation.

First, with one year’s bird nest events in the form of unstructured natural language collected from Shanghai Railway Bureau, the records were structured with the help of python software tool. Second, the method of root cause analysis (RCA) was used to identify all the possible influencing factors which are inclined to affect the probability of bird nesting. Third, the possible factors then were classified into two categories to meet subsequent analysis separately, category one was outside factors (i.e. geographic conditions related factors), the other was inside factors (i.e. railway related factors).

It was observed that factors of city population, geographic position affect nesting observably. Then it was demonstrated that both location and nesting on equipment part have no correlation with delay, while railway type had a significant but low correlation with delay.

This paper discloses the principle of impacts of nest events on railway operation.

This study investigates the correlation between financial inclusion and legal system quality.

Pearson correlation analysis was used to assess the correlation between financial inclusion and legal system quality.

The author finds evidence for a positive correlation between financial inclusion and legal system quality. The findings suggest that improvements in legal system quality go hand in hand with improvements in the level of financial inclusion. More specifically, higher supply of ATM per 100,000 adults is correlated with stronger insolvency resolution framework among G7, European and non-European countries. Also, the number of bank branch per 100,000 adults is positively correlated with strong rule of law and legal rights in non-European countries. Also, the number of ATMs per 100,000 adults is positively correlated with strength of insolvency resolution framework and negatively correlated with the time it takes to resolve insolvency before, during and after the global financial crisis.

No study has explicitly analyzed the correlation between financial inclusion and legal system quality. This present study contributes to the literature by filling this research gap.