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The purpose of the study is to investigate the correlation between credit supply to government and credit supply to the private sector to determine whether there is a crowding-out or crowding-in effect of credit supply to government on credit supply to the private sector.

The study used data from 43 countries during the 1980–2019 period. The study employed the Pearson correlation methodology to analyze the data.

There is a significant positive correlation between credit supply to government and credit supply to the private sector. There is also a significant positive relationship between credit supply to government and credit supply to the private sector, implying a crowding-in effect of government borrowing on private sector borrowing. The positive correlation between credit supply to government and credit supply to the private sector by banks is stronger and highly significant in the period before the Great Recession, while the positive correlation is weaker and less significant during the Great Recession, and the correlation further weakens after the Great Recession. The regional analyses show that the positive correlation between credit supply to government and credit supply to the private sector by banks is stronger and highly significant in the African region than in the Asian region and the region of the Americas.

There is no evidence on the correlation between credit supply to government and credit supply to the private sector during the Great Recession.

The purpose of the paper is twofold: first, to observe the relationship between sale to list ratio (SLR)/ for-sale inventory (FSI)/ sale count nowcast (SCN) and real/nominal housing value, and second, to produce a handbook of empirical evidence that can serve as a foundation for future research on this topic.

This paper broadly compiles empirical evidence, using three of the most common causality tests in the field of housing economics. The analysis methods include lagged Pearson correlation test, Granger causality test and cointegration test.

Causal relationships were observed between SLR/FSI/SCN and both nominal and real housing values. SLR and SCN showed positive long-term correlations with housing value, whereas FSI had a negative correlation. Adjusting the housing value with the Consumer Price Index (CPI) to derive real housing values could potentially alter the direction of the causal relationships. It is crucial to distinguish the long-term relationship from temporal dynamics, as FSI displayed a positive immediate impulse–response relationship with nominal housing price despite the negative long-term correlation.

SLR/FSI/SCN are housing market parameters that have only recently begun to be documented and have seen little use in research. So far, housing market research has revolved around traditional macroeconomic indicators such as unemployment rate. To the best of the authors’ knowledge, this study is one of the first studies that introduce these three parameters into housing market research.

This study aims to determine the most similar set of recommendation books to the user selections in LibraryThing.

For this purpose, 30,000 tags related to History on the LibraryThing have been selected. Their tags and the tags of the related recommended books were extracted from three different recommendations sections on LibraryThing. Then, four similarity criteria of Jaccard coefficient, Cosine similarity, Dice coefficient and Pearson correlation coefficient were used to calculate the similarity between the tags. To determine the most similar recommended section, the best similarity criterion had to be determined first. So, a researcher-made questionnaire was provided to History experts.

The results showed that the Jaccard coefficient, with a frequency of 32.81, is the best similarity criterion from the point of view of History experts. Besides, the degree of similarity in LibraryThing recommendations section according to this criterion is equal to 0.256, in the section of books with similar library subjects and classifications is 0.163 and in the Member recommendations section is 0.152. Based on the findings of this study, the LibraryThing recommendations section has succeeded in introducing the most similar books to the selected book compared to the other two sections.

To the best of the authors’ knowledge, itis for the first time, three sections of LibraryThing recommendations are compared by four different similarity criteria to show which sections would be more beneficial for the user browsing. The results showed that machine recommendations work better than humans.

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.

The unitized curtain wall system (UCWS), a symbol of modern architecture, is gaining popularity among prefabricated components. Previous studies have focused on both construction technology advances and material selection strategies to facilitate the UCWS. However, the topic of client satisfaction, which drives industry development by targeting clients' demands, has gone unnoticed. Therefore, the current study aims to investigate client satisfaction with UCWS products in Hong Kong by finding its influential factors.

A systematic review was employed to first identify the influential factors. A semi-structured interview was employed to validate the reliability of the extracted factors. The machine learning algorithm Extreme Gradient Boosting (XGBoost) and the Pearson correlation were then employed to rank the importance and correlation of factors based on the 1–5 Likert scale scores obtained through a questionnaire survey.

The findings revealed that “reduction in construction time” and “reduction in construction waste” are the most important factors and have a strong positive influence on client satisfaction.

Unlike previous studies, the present study focused on a novel research topic and introduces an objective analysis process using machine learning algorithms. The findings contribute to narrowing the knowledge gap regarding client preference for UCWS products from both individual and collaborative perspectives, providing decision-makers with an objective, quantitative and thorough reference before making investments in the curtain wall management development.

The purpose of this paper was to identify talent development practices and processes that enhance professional and career growth of employees in South African higher education institutions (HEIs).

A quantitative study was carried out to investigate the subject matter. A structured questionnaire was used to collect the data from 265 academics in three South African HEIs. The Statistical Package for the Social Sciences, version 27.0, was used to analyse the data. Cronbach’s alpha coefficient and factor analysis were used to test the reliability and validity of the measuring instrument. Pearson’s correlations and regression analysis were used to interpret the relationship between the independent and dependent variables.

The results of the Pearson correlation test established a strong positive influence of training development, coaching and mentoring and career development on talent development. On the other hand, linear regression results indicated that training and development, coaching and mentoring and career development made a strong contribution to the model.

The scope of the study only applied to South African HEIs, making the generalisation of the findings to be limited because of the differences in an organisational context. Hence, future research should focus on different industries.

The study contributes to understanding how talent development can be leveraged to assist academics in HEIs to improve their professional and career goals. The findings suggest that HEIs must invest in talent development to help academics acquire the skills, knowledge and competencies required to perform their tasks.

This paper sheds more light on talent development practices and processes that enhance academic skills, knowledge and competencies in HEIs. Moreover, the study expands on the findings of prior studies concerning talent development in learning organisations.

This study aims to investigate the correlations between latent variables embedded into three clusters (equine agritourism, therapeutic horse riding and equine sports) and entrepreneurial intentions of people interested to invest in equestrian sector.

The authors propose a conceptual framework focused on three latent variables that influence the interest of horse enthusiasts to embrace an entrepreneurial career. Statistical analyses via Pearson’s chi-square tests, analysis of variance (statistical formula used to compare variances across the means (or average) of different groups) and regression analysis have been performed to validate our assumptions.

Findings reveal a high level of interest of from horse enthusiasts to opt for an entrepreneurial career, as funding opportunities in this sector are growing due to European union and national funding available for this endeavour.

Very limited research studies have been explored the entrepreneurial intentions in equine industry. This study proves that sports and therapeutic activities influence to the greatest extent, the entrepreneurial intention in the equestrian sector.

This research aimed to define the factors that may impact the effectiveness of online architectural education during COVID-19 and to examine the degree of students' and instructors' satisfaction with these factors among Jordanian governmental universities. Further, the research examines the relationships/interrelationships between the degree of their satisfaction with these factors and the students' and instructors' age, gender, education level, home size, and family size.

Different research methods were used to achieve the research purposes, including semi-structured interviews, online questionnaires and reviewing recent literature. This research used descriptive statistics and Pearson product-moment correlation coefficient (Pearson r) to analyze the data.

This research found that online architectural education during COVID-19 was stressful. It was ineffective in teaching practical architectural courses like design and negatively affected the architectural learning process and outcomes. In contrast, the online teaching of architectural theoretical courses was reliable and convenient if the students and instructors had intentional, sufficient technological and appropriate resources. Online architectural education negatively affected the students' design ability and skills, peer review, intended learning outcomes (ILOs) achievements, the quality of feedback, workload, interaction mode, participation, collaboration, productivity and increased cheating on online exams. The home environment was unsuitable for online architectural education. Family interventions, privacy, home size and family size significantly influence online architectural education's effectiveness.

Students' and instructors' satisfaction determines the continuity of using online teaching mode, which depends on information quality, system quality, service quality, perceived ease of use, perceived usefulness, achieved intended learning outcomes, cognitive absorption, skills, motivation, engagement, implementing resources and strategies and positive emotions as hope and enjoyment. Students' and instructors' satisfaction reflects how they view their learning experience, which is crucial in assessing the effectiveness of online education quality that focuses on the context, input, process and product, which is still not clearly understood, particularly for developing countries.

In daily marketing practices, when launching and promoting new products, marketers often induce consumers’ awe of nature via exposing consumers to beautiful natural scenes. Does this marketing practice really facilitate consumers’ subsequent new product choice? Existing awe research and new product research have not examined this issue yet. The purpose of this study is to study whether the marketing practice of awe induction faciliates consumers' new product choice.

This paper examines the double-edged sword effect of different types of awe on consumers’ adoption of new products. The authors conducted five experiments using various product categories (soft drinks, juices, cookies and watches), various many sources of sample types (college student samples and adult samples) and various manipulation of awe. The authors also focused on both new products with incongruent visual appearance (Experiment 1a, Experiment 1c, Experiment 2 and Experiment 3) and new products with incongruent conceptual attributes (Experiment 1b) to enhance the rigor of the experiments and the generalizability of the conclusions.

The authors find that when consumers perceive awe of threatening natural phenomena, they decrease their choice of moderately incongruent new products (positive effect), while when consumers perceive awe of beautiful natural phenomena, they increase their choice of moderately incongruent new products (negative effect). Also, this paper finds that the emergence of the positive of the double-edged sword effect is driven by the sequential mediation of the need for accommodation and openness to new experiences, while the emergence of the negative of the double-edged sword effect is driven by the uncertainty reduction motive.

This research has important theoretical implications. First, this paper advances existing awe research by reconciling the inconsistent findings in existing awe research by categorizing awe of nature. Second, this paper advances existing research on new products and moderate incongruity effects by exploring when the moderate incongruity effect exists and when it reverses in the new products field through the classification of awe of nature.

This study has rich implications for marketing management. First, marketers can facilitate consumers’ adoption of moderate incongruent new product via priming consumers’ awe of beautiful nature. Second, this paper suggests that marketers and brand managers should carefully choose the timing of new product launches to avoid inducing consumer awe of threatening nature (e.g. immediately after a severe natural disaster). Finally, the results of Experiment 3 in this paper suggest that when marketers want to launch new products with moderate incongruity, they need to target consumers with high cognitive flexibility.

This paper discusses how different types of awe affect consumers’ attitudes and choice of moderately new products. This research question has its social value in helping marketers, companies, consumers and society know the power of awe of nature on the behaviors and decision-making.

To the best of the author’s knowledge, this paper is among the first ones to examine the double-edged sword effect of different types of awe of nature on consumers’ new product adoption.

The Denial of Service (DoS) attack is a category of intrusion that devours various services and resources of the organization by the dispersal of unusable traffic, so that reliable users are not capable of getting benefit from the services. In general, the DoS attackers preserve their independence by collaborating several victim machines and following authentic network traffic, which makes it more complex to detect the attack. Thus, these issues and demerits faced by existing DoS attack recognition schemes in cloud are specified as a major challenge to inventing a new attack recognition method.

This paper aims to detect DoS attack detection scheme, termed as sine cosine anti coronavirus optimization (SCACVO)-driven deep maxout network (DMN). The recorded log file is considered in this method for the attack detection process. Significant features are chosen based on Pearson correlation in the feature selection phase. The over sampling scheme is applied in the data augmentation phase, and then the attack detection is done using DMN. The DMN is trained by the SCACVO algorithm, which is formed by combining sine cosine optimization and anti-corona virus optimization techniques.

The SCACVO-based DMN offers maximum testing accuracy, true positive rate and true negative rate of 0.9412, 0.9541 and 0.9178, respectively.

The DoS attack detection using the proposed model is accurate and improves the effectiveness of the detection.