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Using a case study from Delhi, India, this study aims to investigate why perceived safety endures despite crimes in the neighborhood. Local residents in Delhi feel considerably less fearful of crime in their neighborhoods, and a majority reported feeling safe in their neighborhoods, especially during the daytime.

This paper hypothesized that similar to the crime itself, perceptions of safety or the fear of crime, also tend to be concentrated in hotspots. Following a hotspot analysis based on the respondents’ perceptions of safety, the data gathered were applied to the perceived neighborhood structure. Using two perception-of-safety models, this paper could analyze the ripple effect of individual perception on the neighborhood by adding the calculated values of the perceived safety hotspot through hotspot analysis.

The results indicated that income, trust in others, attachment to the local neighborhood and police access can increase residents’ perceptions of safety. Additionally, the neighborhoods’ perception of safety was found to positively impact the individual’s perception of safety.

This study was limited in terms of generalizing the findings. Further studies could potentially include not only other cities in India but also, cities in developing countries in Africa and Latin America, where residents tend not to fear crime despite high crime rates.

Residents’ perceived safety does not necessarily reflect local crimes and security. Local policies to improve residents’ perceptions of safety have to often be separated from crime reduction because a reduction in some crimes would not necessarily improve residents’ perception of safety. Contrarily, if the crime rate is high, as in the case of Delhi, people may have a moderate fear of crime across the neighborhood.

Notably, this study found that, along with trust in others and attachment to the local neighborhood, individuals’ perception of safety is positively affected by neighborhoods’ perception of safety, which is assessed by the alternate analytic model.

This paper aims to suggest the structure of a platform for education and capacity building for Future Earth, which is an intensive program open to the eight stakeholders and which utilizes existing research programs/facilities associated with Future Earth. An intention of this paper is to facilitate a policy brief for projects associated with Future Earth.

This paper reviewed backgrounds and necessary items for education and capacity buildings in Future Earth projects by implementing three main priorities in Future Earth and current surrounding environments.

This paper then suggested a possible structure, competencies, contents and human resources for education and capacity building and education for Future Earth.

The suggestions can be implemented in capacity building and education programs associated with Future Earth.

The purpose of this paper is to provide the extensive review on dynamic monitoring of forestry area in China.

Countermeasure and suggestions were proposed for three aspects including the establishment of data sets with unified standards, top-level design of monitoring and assessment and analysis models, and establishment of the decision support platform with multiple scenario simulation.

Finally, the authors proposed key research area in this field, i.e., improving the systematic and optimal forest management through integrating and improving the data, models and simulation platforms and coupling the data integration system, assessment system and decision support system.

The authors explored the limitation of dynamic monitoring and state of the art research on data accumulation, professional model development and the analytical platform.

The purpose of this study is to analyze and empirically test the impact of Economic Freedom [(EF) measured by size of the government] and inequality on environmental pollutants in addition to macroeconomic variables like per capita GDP, governance indicators, etc. along with existence of non-linear (Kuznets) postulation between economic growth and per capita emissions.

The paper examines the select Asian nations' data attributes, first qualitatively using correlation data technique, followed by empirical testing using differenced Generalized Methods of Moments (GMM). Using the data of selected Asian countries for the period from 1981 to 2016, the authors have applied a dynamic panel technique.

The key findings that emerge from the study are as follows: first, there is weak evidence for the existence of the Kuznets curve based on the empirical results; second, the results indicate that increased EF (by lower government size) could enable to contain carbon emissions; third, there is a negative relationship between democracy and environmental quality (corroborating to the existing studies on carbon emissions); and fourth, there is a strong statistical evidence that increasing income inequality pairs with greater emissions in the middle range of Gini.

The paper conforms to the universally held conviction that government interventions are essentially less productive and the desirability of a reduced size of the government in realizing sustainable green growth with equity.

In an era of liberalization and privatization, it is argued that the role of the government needs to be redefined if not necessarily truncated.

The current paper incorporates Gini (inequality measure) through its intercountry range dummies to study the differential effect of Gini on carbon emissions. Also, in some of the recent studies, distributional issues have surfaced explicitly in the discussion of income–climatic change relationship, but EF largely remains missing. The purpose of the current study is to investigate the same empirically.

Green finance has shown the importance of being socially responsible and supporting the flow of financial instruments to develop environmentally sustainable and ethical business models. The growing trends raised the need for a quantitative study to address scientific performance analysis and intellectual development. This paper aims to cater quantitative statistics, through a bibliometric review to understand the vital intellectual and influential constitution of green and socially responsible finance.

The authors apply trending and cutting-edge quali-quantitative approach of bibliometric citation analysis and review of 280 journal articles from the Web of Science database for the period of 1981–2021.

The results identify the leading academic authors, journals, institutions and countries with relation to green and socially responsible finance literature. We also discuss three research streams in this field: (1) overview of green finance, perception and investor behavior; (2) analysis of performance models and growth factors of green finance; (3) pricing mechanism of SRI. Finally, we identify the research gaps within existing green finance literature, proposing 30 research questions for the future agenda.

The study confines on the Web of Science database, English published articles in known journals and reviews only. It relies on a reputable source and top scientific productions with the most direct link to green finance.

To the best of the authors knowledge, this paper is the first to discuss research streams in the literature of Green finance from a bibliometric aspect along with vast coverage of articles from reputed journals and databases till date. The results of this research along with future research questions will guide the researchers and academicians to further explore and stand on solid quantitative basis regarding the scientific development of Green finance.

Indonesia is the fourth most populous country in the world, which has a strong effect on primary energy use and depletion of natural resources. This paper considers energy intensity (EI) defined as a measure of the amount of energy it takes to produce a dollar's worth of economic output. The purpose of the paper is to explore how different factors contributed to the decline in Indonesia's EI.

The cointegration regression methodology is applied to explore the long-term nexus between EI and its factors in Indonesia during 1990–2016.

Results show that domestic credit to the private sector, as well as the share of alternative energy, has a significant impact on the decline of EI in Indonesia.

We do not try to rule out other possible determinants of EI. We consider the determinants of EI using time series data, while an ideal analysis would be based on panel-level data. Another limitation is that the study covers only the small-time period from 1990 to 2016.

Our findings serve to aid the government and policymakers in prioritizing improvements in the sphere of energy policy. An important policy implication, regarding Indonesia, that arises from our study is that, for the country to be able to decrease its EI, it must be able to develop its financial market and zero-carbon energy sources, mainly geothermal energy with its huge potential.

We show that energy prices, financial development and the share of alternative energy sources contribute to EI decrease. Policy recommendations include geothermal and solar energy development as one of the most prospective sources of alternative energy in Indonesia.