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The sudden COVID-19 epidemic in 2019 has frustrated China's overall economy, and the implementation and development of the National Fitness Program has encountered huge obstacles. At a new historical starting point, in order to realize the dream of becoming a powerful country in sports, it is necessary to transform the successful experience gained since the reform and opening up into regular understanding and systematic theories, so as to make a theoretical response to the new contradictions and challenges faced in development and give full play to the National Fitness has comprehensive values and multiple functions in improving people's health, promoting people's all-round development, promoting economic and social development and demonstrating the country's cultural soft power.

Taking the topic of national fitness as an example, this paper sets out from the three dimensions of knowledge input, knowledge output and knowledge production, using citation analysis, social network analysis, co-word analysis and cluster analysis, to measure the characteristics and knowledge structure of interdisciplinary knowledge exchange.

China's national fitness is still in the primary development stage, and the strong boost of the national top-level policy is the biggest driving force of its development, driven by the policy together with the settlement of many major events, constantly improving and enriching the wings. The main body of knowledge production on the topic of national fitness is mainly colleges and universities, with low participation of government and enterprises, high degree of cooperation among authors, obvious interdisciplinary characteristics and strong application of research themes.

This study provides a strong theoretical basis for the promotion of the Healthy China strategy. Especially under the influence of COVID-19, this paper can contribute to the comprehensive value and multimodal functions of national fitness in improving the health of people, promoting economic and social development and demonstrating the soft power of national culture.

The primary objective of this research is to explore the potential of utilizing Global Consciousness Project (GCP) data as a tool for understanding and predicting market sentiment. Specifically, the study aims to assess whether incorporating GCP data into econometric models can enhance the comprehension of daily market movements, providing valuable insights for traders.

This study employs econometric models to investigate the correlation between the Standard & Poor's 500 Volatility Index (VIX), a common measure of market sentiment and data from the GCP. The focus is particularly on the largest daily composite GCP data value (Max[Z]) and its significant covariation with changes in VIX. The research employs interaction terms with VIX and daily returns from global markets, including Europe and Asia, to explore the relationship further.

The results reveal a significant relationship with the GCP data, particularly Max[Z] and VIX. Interaction terms with both VIX and daily returns from global markets are highly significant, explaining about one percent of the variance in the econometric model. This finding suggests that variations in GCP data can contribute to a better understanding of market dynamics and improve forecasting accuracy.

One limitation of this study is the potential for overfitting and P-hacking. To address this concern, the models undergo rigorous testing in an out-of-sample simulation study lasting for a predefined one-year period. This limitation underscores the need for cautious interpretation and application of the findings, recognizing the complexities and uncertainties inherent in market dynamics.

The study explores the practical implications of incorporating GCP data into trading strategies. Econometric models, both with and without GCP data, are subjected to an out-of-sample simulation where an artificial trader employs S&P 500 tracking instruments based on the model's one-day-ahead forecasts. The results suggest that GCP data can enhance daily forecasts, offering practical value for traders seeking improved decision-making tools.

Utilizing data from the GCP is found to be advantageous for traders as noteworthy correlations with market sentiment are found. This unanticipated finding challenges established paradigms in both economics and consciousness research, seamlessly integrating these domains of research. Traders can leverage this innovative tool, as it can be used to refine forecasting precision.

A variety of buffer allocation methods exist to distribute an aggregated time buffer among project activities. However, these methods do not pay simultaneous attention to two key attributes of disruptive events that may occur during the construction phase: probability and impact. This paper fills this research gap by developing a buffer allocation method that takes into account the synergistic impact of these two attributes on project activities.

This paper develops a three-step method, calculating the probability that project activities are disrupted in the first step, followed by measuring the potential impact of disruption on project activities, and then proposing a risk-informed buffer allocation index by simultaneously integrating probability and impact outputs from the first two steps.

The proposed method provides more accurate results by sidestepping the shortcomings of conventional fuzzy-based and simulation-based methods that are purely based on expert judgments or historical precedence. Further, the paper provides decision-makers with a buffer allocation method that helps in developing cost-effective buffering and backup strategies by prioritizing project activities and their required resources.

This paper develops a risk-informed buffer allocation method that differs from those already available. The simultaneous pursuit of the probability and impact of disruptions distinguishes our method from conventional buffer allocation methods. Further, this paper intertwines the research domains of complexity science and construction management by performing centrality analysis and incorporating a key attribute of project complexity (i.e. the interconnectedness between project activities) into the process for buffer allocation.

The paper analyzes the impact of bank opacity on financial stability in an emerging economy.

Based on a unique dataset of 31 Vietnamese commercial banks from 2007 to 2019, the paper captures earnings opacity via discretionary loan loss provisions and reflects individual bank stability through the accounting-based Z-score index and its disaggregate components. The least squares dummy variable corrected (LSDVC) approach is employed for empirical analysis.

In contradiction to most studies on developed economies, earnings management improves bank financial stability in Vietnam. Earnings management is more important for the financial stability of smaller banks. Further, the effect of financial information disclosure on bank stability is strengthened by unfavorable macroeconomic conditions, particularly economic downturns, the global financial crisis and uncertain times in banking.

This is the first study to shed light on how bank opacity influences bank financial stability in an emerging market. The evidence with the conditioning roles of bank size and macroeconomic factors, such as uncertainty in banking, is entirely novel in the related literature. Additionally, the paper contributes to a growing body of banking literature by using the LSDVC estimator to examine the association between bank opacity and bank stability.

This paper aims to develop a compound measure, which is fiscal vulnerability index, provides early warning signals of fiscal sustainability problems for Türkiye's economy.

The index is constructed using twelve distinct fiscal indicators and applying the portfolio method, which considers the time-varying cross-correlation structure between the subindices.

Dynamics of the fiscal vulnerability index indicate that it accurately predicts to the well-known fiscal crisis occurring in Türkiye's recent history. As a result, such a compound measure should be used in the early identification of fiscal vulnerability in Türkiye.

The main contribution of this paper, relative to existing papers, is that a fiscal vulnerability index was constructed by employing the most contemporaneous method and evaluating its performance in terms of capturing historical stress periods.

This study aims to examine the impact of economic freedom and corruption on bank stability in sub-Saharan Africa (SSA).

This study uses 38 countries in SSA from 2008 to 2019 using system GMM technique.

The authors found that greater economic freedom increases economic efficiency through improving bank stability. Besides this, the authors also find that banks in environments with greater business freedom, financial freedom, trade freedom and investment freedom are less prone to solvency. The results also show that corruption improves bank stability, suggesting evidence of the “grease the wheels” hypothesis.

The results suggest to policymakers that a high economic freedom may be an appropriate policy toward enhancing bank stability. Besides this, the results also suggest to policymakers to prioritize addressing the core issues that encourage corruption to extort bribes.

This study provides insightful discussion on whether economic freedom and its subcomponents and corruption have an effect on bank stability in SSA.

Global climate change characterized by an increase in temperature has become the focus of attention all over the world. China is a sensitive and significant area of global climate change. This paper specifically aims to examine the association between agricultural productivity and the climate change by using China’s provincial agricultural input–output data from 2000 to 2019 and the climatic data of the ground meteorological stations.

The authors used the three-stage spatial Durbin model (SDM) model and entropy method for analysis of collected data; further, the authors also empirically tested the climate change marginal effect on agricultural productivity by using ordinary least square and SDM approaches.

The results revealed that climate change has a significant negative effect on agricultural productivity, which showed significance in robustness tests, including index replacement, quantile regression and tail reduction. The results of this study also indicated that by subdividing the climatic factors, annual precipitation had no significant impact on the growth of agricultural productivity; further, other climatic variables, including wind speed and temperature, had a substantial adverse effect on agricultural productivity. The heterogeneity test showed that climatic changes ominously hinder agricultural productivity growth only in the western region of China, and in the eastern and central regions, climate change had no effect.

The findings of this study highlight the importance of various social connections of farm households in designing policies to improve their responses to climate change and expand land productivity in different regions. The study also provides a hypothetical approach to prioritize developing regions that need proper attention to improve crop productivity.

The paper explores the impact of climate change on agricultural productivity by using the climatic data of China. Empirical evidence previously missing in the body of knowledge will support governments and researchers to establish a mechanism to improve climate change mitigation tools in China.

This study investigates the reasons behind the very high net interest margins in the Greek banking industry compared to the euro-area, focussing on the association between bank competition and recapitalisations.

The author conducts a dynamic panel analysis covering the period from the early 2000s to 2021, that controls for possible endogeneity and treats for heterogeneity. The author also employs local projections impulse response functions that control for structural changes in Greek banking.

The author finds that low bank competition has contributed to high net interest margins in Greece. Interestingly, the impact of recapitalisations conditional to low bank competition has had a significant further impact on increasing net interest margins, which is a noteworthy case due to several Greek bank recapitalisations in the last ten years. The author’s findings are supported by local projections impulse response functions.

To mitigate distortions in bank competition, the author argues to accelerate steps toward the direction of the banking union and a common bank regulation framework in the euro-area.

Despite a reduction in poverty the global population in 2015, the incidence of poverty remains very high in Sub-Saharan African countries. Most of the countries in the region are agrarian, with most of their population residing in rural areas, and a majority of the poor in the region are found in Nigeria. This study examined the nexus between participation in nonfarm enterprises (NFEs) and poverty among rural farm households in Nigeria and across the six geopolitical zones.

The Nigerian Living Standard Survey (NLSS) conducted in 2018–2019 by the National Bureau of Statistics was used. We made use of 13,440 farm households with useful information for the purpose of this study. The sample comprises 6,885 households that participated in NFEs and 6,555 nonparticipating households. The data were analyzed with Foster, Greer, and Thorbecke (FGT) (1984) metrics, probit, and fractional probit models at p = 0.05.

The incidence of poverty was lower among the participating households than in the nonparticipating households. Participation in NFEs had a mitigating effect on poverty. We also established that zonal differentials in poverty rates exist among households in all the analyses. Participation in NFEs was influenced by individual, household, and institutional factors and was also able to explain the depth of poverty among the respondents.

It is suggested that poverty alleviation policies should be targeted at improving access to nonfarm economic activities by rural farm households residing in vulnerable geopolitical zones.

This study is the first attempt to profile household poverty based on the type of NFEs they are involved in. The study also provides an insight into the effect of the state of residence on zonal poverty models, which is expedient if the country must achieve Sustainable Development Goal 1 on the eradication of poverty everywhere.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0493

Participation in global value chains (GVCs) is increasingly related to the economic growth of any country. The conceivable beneficial impact of GVCs on economic growth differs across countries and could be modified with the countries' domestic institutional arrangements. However, ignoring the complementarity between the components of institutional quality led to ignorance of the institutional imbalance present in the country. Hence, the primary purpose of this study is to examine the role of institutional imbalance as a moderating variable between GVC participation and economic growth from 2000 to 2018.

To address the issue of endogeneity among the variables in the model, the study employs the generalized methods of moments (GMM) as an econometric analysis method.

The study finds that well-functioning domestic institutions facilitate the positive impact of GVC participation on economic growth. Conversely, an increased institutional imbalance harms the relationship between GVC participation and economic growth. These findings emphasize a balanced portfolio of institutional components. It advocates the holistic development of each component to reap greater benefits for GVC participation for any country. The study highlights that the weakness in one of the components must be addressed rather than substituted by increasing the strength of another component.

The policies should be framed to improve the weakest component first, followed by other components of institutional quality. Simultaneous reforms involving all the dimensions of institutional quality would smoothen the path of transforming GVCs trade to the country's economic development. Additionally, the high institutional imbalance can provide a bird's eye view to policymakers to work on specific aspects of institutional quality more rigorously.

The existing literature has used a combined measure of institutional quality as a mediator variable while measuring the impact of GVC participation on economic growth. While using a combined measure, it ignores the complementarity among its components. Assuming substitutability among various components may lead to an incorrect estimation. Using the arguments proposed by Bolen and Sobel (2020), the present study considers the existence of complementarity among various components of institutional quality. It calculates the institutional imbalance used as a moderating variable while estimating the impact of GVC participation on economic growth.