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The purpose of this paper is to show that the environmental income drives economic growth of a large open country.

The authors detect that the relative environmental income has double effect of “conspicuous consumption” on the international renewable resource stock changes when a new social norm shapes to environmental-friendly behaviors by using normal macroeconomic approaches.

Every unit of extra demand for renewable resource consumption increases the net premium of domestic capital asset. Even if the technology spillovers are inefficient to the substitution of capital to labor force in a real business cycle, the relative income with scale effect increases drives savings to investment. In this case, the renewable resource consumption promotes both the reproduction to a higher level and saving the potential cost of environmental improvement. Even if without scale effects, the loss of technology inefficient can be compensated by net positive consumption externality for economic growth in a sustainable manner.

It implies how to earn the environment income determines the future pathway of China’s rural conversion to the era of eco-urbanization.

We test the tax incidence to demonstrate an experimental taxation for environmental improvement ultimately burdens on international consumption side.

The study investigates the influence of ChatGPT on the labor market dynamics, aiming to provide a structured understanding of the changes induced by generative AI technologies.

An analysis of existing literature serves as the foundation for understanding the impact, while the supply and demand model helps assess the effects of ChatGPT. A text-mining approach is utilized to analyze the International Standard Occupation Classification, identifying occupations most susceptible to disruption by ChatGPT.

The study reveals that 32.8% of occupations could be fully impacted by ChatGPT, while 36.5% might experience a partial impact and 30.7% are likely to remain unaffected.

While this study offers insights into the potential influence of ChatGPT and other generative AI services on the labor market, it is essential to note that these findings represent potential implications rather than realized labor market effects. Further research is needed to track actual changes in employment patterns and job market dynamics where these AI services are widely adopted.

This paper contributes to the field by systematically categorizing the level of impact on different occupations, providing a nuanced perspective on the short- and long-term implications of ChatGPT and similar generative AI services on the labor market.

No systematic review has previously been dedicated to comprehensively investigate predictors of well-being and ill-being in working contexts. Empirical studies have vastly associated well-being as the result of autonomous motivation and basic psychological needs satisfaction, while frustration results in ill-being. The purpose of this study is to integrate the variables identified in empirical studies associated with the occurrence of the phenomena, individual/organizational features and consequences associated with workers' well-being/ill-being.

This systematic review includes 44 empirical studies published up to February 2021. Findings are summarized based on quantitative analysis of the evidence.

Results reinforce the role of self-determined motivation and needs satisfaction in promoting well-being, while amotivation and needs frustration led to ill-being. Besides, they indicate that ill-being can both lead to negative consequences and diminish positive work outcomes. Findings also revealed that: integrated motivation does not seem to be empirically distinct from intrinsic and identified motivation in promoting well-being; introjected motivated behaviors may be less harmful to psychological health than externally oriented ones; the relationship between external motivation and well-being/ill-being requires prospective investigations; and amotivation seems to have a detrimental effect in workers' psychological health.

Results provide practical information for HRM practitioners to design work environments and practices that promote employees' psychological health.

An unprecedented framework that aggregates empirical findings regarding the antecedents, predictors and consequences of ill-being/well-being in working contexts is presented.

This research aims to analyze the primary social factors influencing the mental health and happiness of older adults. Specifically, the paper identifies the elements of social influences on the psychological well-being of elderly individuals.

Employing a quantitative research methodology, survey data were collected to examine the psychological well-being of older adults, utilizing SPSS software version 28.0 for data analysis.

Psychological well-being in the elderly is intricately linked to personal, cognitive, emotional and social aspects. Seniors experiencing reduced loneliness, ample communication opportunities, active social engagement and living with family members demonstrate higher levels of psychological well-being. Surprisingly, details of daily activities in senior age showed little impact on psychological well-being.

The research results may lack generalizability due to the chosen approach, prompting a need for further testing of proposed propositions.

This study fulfills an identified need to explore how psychological well-being is established in an elderly society, shedding light on critical social determinants.

The aim of this paper is to summarise the state-of-the-art debate on impact of artificial intelligence on unemployment and reporting up-to-date academic findings.

The paper is designed as a review of the labour vs capital conundrum, the differences between industrial automation and artificial intelligence, threat to employment, the difficulty of substituting, role of soft skills and whether technology leads to the deskilling of human workers or favors increasing human capabilities.

Some authors praise the bright future developments of artificial intelligence while others warn about mass unemployment. Therefore, it is paramount to present an up-to-date overview of the problem, compare and contrast its features with what happened in past innovation waves and contribute to academic discussion about the pros/cons of current trends.

The main value of this paper is presenting a balanced view of 100+ different studies, the vast majority from the last five years. Reading this paper will allow to quickly grasp the main issues around the thorny topic of artificial intelligence and unemployment.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0338

This paper explores the empirical relationship between population age structure and bilateral trade.

The author includes age structure in both log and Poisson pseudo-maximum likelihood (PPML) formulations of the gravity equation of trade. The author studies relative age effects, using differences in the demographic structure of each country-pair.

The author finds that a relatively larger share of population in working age increases bilateral exports. This is robust to various estimation models, as well as to changes in the method of specifying the demographic controls. Old-age shares have a negative, but less robustly estimated impact on trade. Estimating instead the balance of trade between trading partners produces similar results, with positive effects of age structure peaking later in working life.

Global populations are poised to undergo a massive transition. Trade a crucial way that the demographic deficits of one country may be offset by the dividends of another as comparative advantages shift along with the size and strength of their underlying workforce.

The author’s work is among the first to quantify the effect of relative age structure between two countries and their bilateral trade flows. Focusing on the aggregate flows, relative age shares and PPML estimates of the trade relationship, this paper provides the most comprehensive picture to date on how age structure affects trade.

This study aims to examine the influence of the blue economy factors on the economic growth of the South Asian Association for Regional Cooperation (SAARC) countries.

Secondary data from 1995 to 2018 have been used for the analysis of eight countries. The contributing factors that measure the fishing production are total aquaculture production, total fisheries production and agriculture, forestry and fishing. Trade and the rate of inflation are used as control variables. Using the feasible generalized least square technique.

It was found that the blue economy factors play a statistically significant role in the economic growth of SAARC countries and contribute to the achievement of Goal 14 of the United Nations’ sustainable development goals: to conserve and sustainably use the oceans, seas and marine resources for sustainable development.

This study highlights the fact that proper management and utilization of water resources may assist the stimulation of economic growth and meet the challenges of food insecurity by improving the supply of seafood in developing South Asian countries. The study proposes that the sustainable management of water resources requires an alliance across nation states. The alliance will be useful in understanding the concept of the blue economy and the role it plays in ensuring economic growth in developing nations throughout the world.

The study examines the impact of socio-economic governance on economic growth in Nigeria. It measures socio-economic governance from the perspective of fiscal policy, using indicators such as investment in education, research and development (R&D) and health.

This study employs the Autoregressive Distributive Lag (ARDL) Bound Testing method to achieve its objective.

The study finds that socio-economic policies aimed at increasing investment in education are crucial for Nigeria’s long-term economic growth. Additionally, investment in R&D positively impacts economic growth. However, the study reveals that investment in health negatively affects economic growth in Nigeria in the long run. This suggests that if a country overinvests in health, it may divert resources from other vital sectors such as education, infrastructure and R&D, which can hinder overall economic growth. The short-run parameter is, however, not statistically significant in this study.

The study’s originality lies in its exploration of the relationship between socio-economic governance and economic growth in Nigeria, specifically from a fiscal policy perspective. It highlights the importance of investing in education and R&D for long-term economic growth. Additionally, the finding that overinvestment in health may have a negative impact on long-term economic growth provides valuable insight for policymakers in Nigeria and other developing countries. Overall, this study’s findings can be beneficial for policymakers and researchers interested in the intersection between socio-economic governance and economic growth in developing countries.