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A sample of elementary schools and a sample of high schools were employed in a replication of a study conducted on corporations to determine the influence exerted by principals on the instructional performance of schools. An analysis of the components of variation was conducted to estimate principals' effects while controlling for environmental and organizational factors. It was found that principals exert a small but important influence on school performance, as measured by standardized achievement tests.

This study aims to construct a mental health service system for middle school students in the post-COVID-19 era with the framework of Six Sigma DMAIC (define, measure, analyze, improve and control) and analyze the influencing factors of the mental health service system to study the implementation strategies of quality-oriented mental health services in middle schools.

This study was conducted in Tianjin, China, from September to November 2022, and 350 middle school students from Tianjin Public Middle School were selected as subjects. A questionnaire survey was used to collect data. In this study, the Six Sigma DMAIC method, sensitivity analysis method, exploratory factor analysis and principal component analysis were used to analyze the mental health services provided to middle school students.

Based on the Six Sigma DMAIC framework, this study indicates that the contribution rate of the mental health service process factor is the largest in the post-COVID-19 era. The mental health cultivation factor ranks second in terms of its contribution. Mental health quality and policy factors are also important in the construction of middle school students’ mental health service system. In addition, the study highlights the importance of parental involvement and social support in student mental health services during the post-COVID-19 era.

To the best of the authors’ knowledge, a study on middle school students’ mental health in the post-Covid-19 era has not yet been conducted. This study developed a quality-oriented mental health system and analyzed the influencing factors of mental health for middle school students based on data analysis and the Six Sigma DMAIC method.

Defining and measuring competitiveness has been a major focus in the business and competition literature over the past decades. The paper aims to use data-driven principal component analysis (PCA) to measure firm competitiveness.

A “3Ps” (performance, potential, and process) firm competitiveness indicator system is structured for indicator selection. Data-driven PCA is proposed to measure competitiveness by reducing the dimensionality of indicators and assigning weights according to the endogenous structure of a dataset. To illustrate and validate the method, a case study applying to Chinese international construction companies (CICCs) was conducted.

In the case study, 4 principal components were derived from 11 indicators through PCA. The principal components were labeled as “performance” and “capability” under the two respective super-components of “profitability” and “solvency” of a company. Weights of 11 indicators were then generated and competitiveness of CICCs was finally calculated by composite indexes.

This study offers a systematic indicator framework for firm competitiveness. The study also provides an alternative approach to better solve the problem of firm competitiveness measurement that has long plagued researchers.

The data-driven PCA approach alleviates the difficulties of dimensionality and subjectivity in measuring firm competitiveness and offers an alternative choice for companies and researchers to evaluate business success in future studies.

The purpose of this study is to measure the availability, accessibility and usability of financial products and services in both rural and urban India from 1991 to 2014.

This paper uses principal component analysis (PCA) method to construct financial inclusion index that serves as a proxy variable for indicating the inclusiveness of financial products and services among the rural and urban people. To fulfill this objective, the study proposes separate indexes of financial inclusion for both rural and urban India from 1991 to 2014. The paper uses annual time series data from 1991 to 2014 to construct the rural-urban financial inclusion index. The used data have been collected from the basic statistical returns of Reserve Bank of India and Economic Political Weekly research foundation.

The study inferences that though there is a remarkable increase in financial inclusion in India from 1991 onwards, it does not result in sizeable growth of financial access to rural masses in comparison to urban masses. The rural India does not substantiate an equivalent growth to that of urban India, contrasting a perceptible increase in financial inclusion. The finding of this study will help the researchers and policymakers to understand the status of financial inclusion in the context of both rural and urban India. Furthermore, policymakers can take appropriate policy initiatives to fulfill the financial inclusion gap that exists between rural and urban people. Additionally, the proposed index is easy to compute and can be used to make comparison across countries for further studies.

The present paper attempts to include all possible dimensions (and indicators within a dimension) that have been considered so far by various authors. Therefore, the authors hope that this index will be more indicative and accurate than previous index. Again, the authors propose to use PCA for the first time to assign the weight of factors in the financial inclusion index for rural and urban India separately.

This study aims to delve deeply into the role of infrastructure on economic growth in 59 belt and road initiative (BRI) participating countries from various regions of the world as the main objective of BRI is to encourage the participating countries to improve investment and trade facilitation via infrastructure. Besides, the development of infrastructure is in line with the United Nations’ 2030 sustainable development goals (SDG).

This study encompasses all of the important physical infrastructure factors to compute a composite infrastructure index. Thereafter, this study used both the panel cointegration and the panel Granger causality tests to investigate the impact of the infrastructure index and other essential factors on economic growth.

The empirical results signify the importance of infrastructure development on economic growth in both the long-run and short-run. Besides, it is evident that capital, expenditure on health and education, as well as exports, will accelerate economic growth.

The findings of this study could contribute to the literature regarding BRI in two ways. First, it will provide insight to the policymakers of China and the BRI participating countries on whether infrastructure development is worthy of huge investment so as to enhance the success of the BRI. Second, the outcome of this study will give policymakers a better understanding of the determinants of economic growth, which, in turn, will help them in designing effective policies.

The purpose of this paper is to determine the effect of information and communications technology (ICT) on the provision of social services, as well as the moderating effect of institutional quality on the relationship between ICT and the provision of social services for 31 low-income countries.

This study is based on panel data from World Development Indicators and Worldwide Governance Indicators spanning 1996 to 2020 for 31 low-income countries. To analyze the data, the study uses cross-sectional dependence tests, slope heterogeneity tests, panel unit root tests, panel cointegration tests and cross-sectionally augmented autoregressive distributed lag (CS-ARDL) analysis.

The results overwhelmingly show that ICT has a significant positive effect on the provision of social services in both the short- and long-run. Also, the study reveals that institutional quality has a significant positive impact on the provision of social services in the short- and long-run. The results further provide empirical evidence of the positive and significant moderating effect of institutional quality on the relationship between ICT and the provision of social services.

This study points out the significant potential of identifying appropriate scales of ICT infrastructure and institutional quality needed to support the various governments in low-income countries to improve social services delivery mechanisms and outreach efficacy and impact. The study can be invaluable for ICT innovators and policymakers in promoting the provision of social services.

To the best of the authors’ knowledge, this study represents the first attempt to determine the effect of ICT on the provision of social services, as well as the moderating effect of institutional quality on the relationship between ICT and the provision of social services, especially for low-income countries using CS-ARDL.

The purpose of this study is to construct a financial conditions index (FCI) for the South African economy to enable the gauging of financial conditions and to better understand the macro-financial linkages in the country. The global financial crisis that began in 2007-2008 demonstrated how severe the impact of financial markets’ stress on real economic activity can be. In the wake of the financial crisis, policy-makers and decision-makers across the world identified the critical need for a better understanding of financial conditions, and more importantly, their impact on the real economy.

The FCI is constructed using monthly data over the period 1966 to 2011, and is based on a set of 16 financial variables, which include variables that define the state of international financial markets, asset prices, interest rate spreads, stock market yields and volatility, bond market volatility and monetary aggregates. The authors explore different methodologies for constructing the FCI, including full sample and rolling-window principal components analysis. Furthermore, the authors investigate whether it is beneficial to purge the FCI of the real effects of inflation, economic growth and interest rates, and evaluate the performance of our constructed FCIs by comparing their ability to pick up turning points in the South African business cycle, and by running in-sample causality (forecast) tests.

The authors find that the estimated FCIs are good predictors of economic activity; with the rolling-window FCI being the “best” performing index. Causality tests indicate that this FCI is a good in-sample predictor of industrial production growth and the Treasury Bill rate, but a weak predictor of inflation.

The authors find that the resulting FCI can act as an “early warning system”. This, in turn, may serve to indicate that monetary policy should take broader financial conditions into account.

This study offers three main contributions to the existing literature on financial conditions in South Africa: the authors construct an FCI over a sample period that is three decades longer than existing indices, the FCI of this paper comprises a wider coverage of financial variables than others and the authors make use of rolling-window estimation techniques that allow them to account for parameter instability and to capture the real-time constraints faced by a policymaker.

The aim of this paper is to identify some specificities of production planning and control (PPC) activities in the one-of-a-kind-production (OKP) process through an extensive literature review. Relevant aspects related to systems and PPC activities in the context of OKP environment are discussed, and six opportunities for future research are highlighted.

The following research is based on a review of 53 articles published in peer-reviewed journals over the past three decades. After an initial descriptive analysis based on bibliometric indicators, a cluster analysis of 15 most cited articles was carried out using multivariate data analysis techniques and in-depth analysis.

The results reveal some specificities inherent to the clusters featured in the research, including aspects of planning, control and systems for OKP process. This cluster addresses information regarding next-generation manufacturing systems, scheduling and design science, computer simulation and project approach. On the other hand, the authors point out six topics for future research regarding contemporary issues associated with PPC in the context of OKP.

This paper fills an important gap regarding OKP production planning and control practices. The results provide a theoretical overview of different PPC practices suitable for the OKP environment. Furthermore, it can provide insights for scientific developments in order to manage the complexity inherent in the OKP process.

The purpose of this paper is to provide an analysis of the relationship between expected risk premia on property stocks and some major macroeconomic risk factors as reflected in the general business and financial conditions

Employs a three‐step estimation strategy (principal component analysis, GARCH (1,1) and GMM) to model the macroeconomic risk variables (GDP growth, INDP growth, unexpected inflation, money supply, interest rate and exchange rate) and relate them to the first and second moments on property stock excess returns of four major markets, namely, Singapore, Hong Kong, Japan and the UK. Macroeconomic risk is measured by the conditional volatility of macroeconomic variables.

The expected risk premia and the conditional volatilities of the risk premia on property stocks are time‐varying and dynamically linked to the conditional volatilities of the macroeconomic risk factors. However there are some disparities in the significance, as well as direction of impact in the macroeconomic risk factors across the property stock markets. Consequently there are opportunities for risk diversification in international property stock markets.

Results help international investors and portfolio managers deepen their understanding of the risk‐return relationship, pricing of macroeconomic risk as well as diversification implications in major Asia‐Pacific and UK property stock markets. Additionally, policy makers may play a role in influencing the expected risk premia and volatility on property stock markets through the use of macroeconomic policy.

Limited attention to messages transmitted between principals and teachers led to the general question for this study: is principal support of student psychological needs related to functional social conditions within the instructional core? Therefore, the purpose of this paper is to define principal support of student psychological needs and explain its leadership function through the lens of conversation theory. Without much empirical evidence to draw from, a theoretical argument for how principal support of student psychological needs might influence the features of the teaching and learning environment is advanced then tested empirically.

Hypotheses were tested using a non-experimental, correlational research design based on ex-post facto data collected from teachers and students in 93 schools in a metropolitan city of the USA. Data were collected in the spring of 2017 from randomly sampled teachers and students in the 93 schools. Usable responses were received from 1,168 teachers, yielding a response rate of 66 percent. A total of 4,523 students received surveys and usable responses were received from 3,301, yielding a response rate of 73 percent. Multi-level modeling was used to analyze the data.

Principal support of student psychological needs was related to school-level differences in faculty trust in students, collective teacher efficacy and student perceived autonomy support. Leadership practices surrounding professional development and instructional coherence had moderately strong, positive relationships with the outcome variables; however, the strength of these relationships diminished when principal support was included in the analysis.

The argument in this study proposes that principal–teacher conversations enhance leadership practices and support a vibrant and engaging instructional core when intentional messages build mental representations that enable teachers to understand sources of optimal student growth. Such use of conversation extends the functionality of principal–teacher interactions beyond that of teacher control and toward an ongoing sense-making and learning process.