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Global environmental concerns have prompted organizations to adopt green human resource management practices that will eventually lead to green innovations. Given that understanding, this study aims to converge multidimensional research published on green human resource management (GHRM) and green innovation. In addition, it seeks to discuss the topic's research trends in the context of what, how, when, where, and by whom. The data were retrieved from the Scopus database (until March 2023), and VOSviewer was used to investigate the research trends. A total of 312 documents were extracted from the Scopus database, and 46 published articles were finalized using the PRISMA flow approach. The results indicate that there has been an upward trend in terms of published articles on the topic, and the highest number of articles (15) were published in the current year, 2023. The co-occurrence results indicate that GHRM is strongly associated with environmental performance and green innovation. The journals Environmental Science and Pollution Research and Sustainability (Switzerland) stand out in this domain. The Abu Dhabi University of United Arab Emirates is the most cited institution, whereas Saudi Arabia has the highest co-authorship at the country level. Furthermore, this study summarizes the major developments in this research domain and suggests research gaps and possible future directions. [ABSTRACT FROM AUTHOR]

Recently, sustainable economic growth has taken the front line of the global development agenda. The common dependency on fossil fuel energy, greenhouse gas (GHG) emissions and the continuous rising demands for energy have posed challenges that put the world in a climate change trap. This work empirically analyzes the effect of innovation, oil price, oil price volatility and economic growth on GHG emissions over the period of 1991–2015. The study compares the emission level between European Union countries (EU) (26), oil-producing countries (22), China and the United States of America (USA) using the Driscoll–Kraay model. The main empirical finding points to a positive effect of innovation on GHG emission reduction initiatives in oil-importing economies. Particularly, EU countries significantly minimized emissions due to innovation, followed by China and the USA. Contrarily, the effect of innovation increases GHG emission in oil-exporting economies. The results also indicate broader significant effects of oil price and oil price volatility on GHG emission. Interestingly, the effect of oil price on GHG emission is asymmetrical between oil-exporting and -importing economies. Oil price increases in oil-importing countries decrease GHG emission; contrarily, its effect increases emissions in oil-exporting countries. Thus, oil-exporting countries lack motivation to decrease emission levels due to oil price escalation. Unlike the oil price, oil price volatility comparably decreases GHG emissions in oil-exporting and -importing economies. Thus, one might be tempted to take oil price volatility and the future uncertainty of oil price as a virtuous instance rather than oil price increment. Thus, policymakers need to pay attention to market forces and policy measures to monitor GHG emissions due to economic activities. The results are also robust under the alternative econometrics estimation model of generalized method of moments (GMM)-Differenced. [ABSTRACT FROM AUTHOR]

Today's agricultural management decisions impact food security and sustainable ecosystems, even when operating with back-to-basic operations. In such endeavors, policymakers usually need a quantitative tool, such as trade-offs margins, to effectively adjust resource consumption or production. This paper applies the weighted slack-based measurement (SBM-DEA) program to 136 developing countries' agricultural performance. First, it finds the current agricultural efficiency and then makes marginal trade-offs on desirable-output variables (such as crop yield and forest area) to see the effective changes in undesirable-output (such as methane and nitrous oxide emissions). The results show that choosing effective marginal trade-offs does not deteriorate the relative efficiency of the decision-making units (DMUs) below the efficient frontier line. Thus, such a method enables the decision-makers to determine the best marginal trade-off points to reach the optimal efficiencies and decide which output factor needs special brainstorming to design effective policy. [ABSTRACT FROM AUTHOR]

Agricultural sector is significant for Sub-Saharan African countries and is highly exposed and sensitive to climate change. This study aims to investigate the overall long-run impacts of temperature and precipitation on agricultural growth in 32 Sub-Saharan African countries. As proposed by Chudik and Pesaran, our estimations are based on augmented autoregressive distributed lag(ARDL) modelling and panel estimators with multifactor error structures. We estimate the "dynamic common correlated long-run effects (DCCE)" through the cross-sectionally augmented distributed lag (CS-DL) approach as well as through the cross-sectionally augmented autoregressive distributed lag (CS-ARDL). For robustness check, we also consider the cross-sectionally augmented error correction method (CS-ECM) and the common dynamic process augmented mean group (AMG). The study suggests that rising temperatures have significantly developed a negative long-term relationship with the agricultural growth in Sub-Saharan Africa. At the same time, the long-run effect of precipitation is less important and not statistically significant in most estimations. According to the CS-DL approach, the negative impact of a 1°Crise in temperature could be as high as a 4.2 to 4.7 percentage point decrease in the agricultural growth rate. The results indicate that the warming climate has considerably damaged the agrarian activities in Sub-Saharan Africa, necessitating adaptive climate measures to avoid any food scarcity or economic stagnation in agricultural driven African countries. [ABSTRACT FROM AUTHOR]

Since the introduction of the measure of economic policy uncertainty, businesses, policymakers, and academic scholars closely monitor its momentum due to expected economic implications. The US is the world's top-ranked equity market by size, and prior literature on policy uncertainty and stock prices for the US is conflicting. In this study, we reexamine the policy uncertainty and stock price nexus from the US perspective, using a novel dynamically simulated autoregressive distributed lag setting introduced in 2018, which appears superior to traditional models. The empirical findings document a negative response of stock prices to 10% positive/negative shock in policy uncertainty in the short-run, while in the long-run, an increase in policy uncertainty by 10% reduces the stock prices, which increases in response to a decrease with the same magnitude. Moreover, we empirically identified two significant thresholds: (1) policy score of 4.89 (original score 132.39), which negatively explain stock prices with high magnitude, and (2) policy score 4.48 (original score 87.98), which explains stock prices negatively with a relatively low magnitude, and interestingly, policy changes below the second threshold become irrelevant to explain stock prices in the United States. It is worth noting that all indices are not equally exposed to unfavorable policy changes. The overall findings are robust to the alternative measures of policy uncertainty and stock prices and offer useful policy input. The limitations of the study and future line of research are also highlighted. All in all, the policy uncertainty is an indicator that shall remain ever-important due to its nature and implication on the various sectors of the economy (the equity market in particular). [ABSTRACT FROM AUTHOR]

The purpose of innovation is to consume fewer natural resources in order to create sustainable performance; therefore, innovation can ease the pressure of the ecological load and promote the sustainable development of the economy. Taking the 269 enterprises listed on the main board of the electronic information industry from 2010 to 2019 as samples, using the threshold panel data model, the nonlinear relationship between the knowledge-based network structure hole and the short-term and long-term innovation performance of the enterprises were studied, and the threshold effect of R&D investment intensity was discussed. When the R&D investment intensity is from 1.96% to 15.96%, the knowledge-based network structure hole has a significant positive impact on short-term innovation performance. When the R&D investment intensity is from 5.72% to 10.64%, the knowledge-based network structure hole has a significant positive effect on long-term innovation performance. Lower R&D investment intensity can make the knowledge-based network structure hole promote the increase of short term innovation performance, but to make the knowledge-based network structure hole have a positive impact on long term innovation performance, the R&D investment intensity should be increased by more than 5.72%. When R&D investment intensity is not higher than 15.96%, the knowledge-based network structure hole has a significant positive impact on short term innovation performance, but to make the knowledge-based network structure hole maintain the positive effect on long term innovation performance, R&D investment intensity should not exceed 10.64%. Therefore, enterprises should be guided to optimize the knowledge-based network structure according to the R&D investment intensity in order to improve the short term and long-term innovation performance of an enterprise. These research results can help enterprises to save resources and promote the sustainable development of the economy. [ABSTRACT FROM AUTHOR]

Water governance is a widely acknowledged as an important factor for sustainable development. This study attempts to assess if the water governance in eight Indian states has improved after the announcement of the United Nations Sustainable Development Goals (SDGs). We utilize the Institutional Decomposition and Analysis (IDA) framework developed by Saleth and Dinar. Using survey data from two periods and 152 respondents, we calculate the scores on 17 indicators of water law, policy, and administration. We found that average scores on water law, policy, and administration have increased between the first and the second survey. We attributed this improvement to the fact that the Indian government is paying special attention to the provision of clean drinking water after the announcement of the SDGs. We also calculated nominal and weighted water governance indices (WGIs) for eight Indian states. This study made an important contribution to the existing water governance literature by capturing improvements in the water governance scores of eight Indian states after the announcement of the SDGs. [ABSTRACT FROM AUTHOR]

Background and objectives : We aimed to assess the prevalence of periodontal disease among obese young adults in Saudi Arabia and to analyze the association between different body mass indexes and the severity of periodontal disease. Materials and methods : This descriptive cross-sectional study consisted of 307 obese patients aged 18-39 years, with body mass index (BMI) ≥30. Demographic variables for periodontal disease, anthropometric parameters such as BMI along with clinical parameters such as oral hygiene index-simplified, community periodontal index (CPI) score and loss of attachment (LOA), were assessed. Multivariate binary logistic regression analysis was used to identify the predictors for chronic periodontitis in obese young adults between 18-40 years of age. Results : The majority of the participants (71.3%) had periodontal disease. Obese and extremely obese patients together showed a statistically significant difference in the age group of 21-30 years in terms of CPI score for inflammation ( p < 0.05) and LOA ( p < 0.001). Logistic regression analysis showed age (OR: 3.180; 95%CL: 1.337-7.561; p <.001), occasional dental visit (OR: 5.965; 95%CL: 3.130-11.368; p < 0.001), smoking >10 cigarettes (OR: 11.868; 95%CL: 3.588-39.254; p < 0.001) and poor oral hygiene status (OR: 17.250; 95%CL: 6.958-42.764; p < 0.001) were associated with a significantly higher risk of having periodontal disease. Conclusions : This study showed a high prevalence of periodontal disease in obese patients among the Saudi Arabian population.