• Energy Research
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Long-term spatiotemporal Land Use and Land Cover (LULC) analysis is an objective tool for assessing patterns of sustainable development (SD). The basic purpose of this research is to define the Driving Mechanisms (DM) and assess the trend of SD in the Burabay district (Kazakhstan), which includes a city, an agro-industrial complex, and a national natural park, based on the integrated use of spatiotemporal data (STD), economic, environmental, and social (EES) indicators. The research was performed on the GEE platform using Landsat and Random Forest. The DM were studied by Multiple Linear Regression and Principal Component Analysis. SD trend was assessed through sequential transformations, aggregations, and integrations of 36 original STD and EES indicators. The overall classification accuracy was 0.85–0.97. Over the past 23 years, pasture area has changed the most (−16.69%), followed by arable land (+14.72%), forest area increased slightly (+1.81%), and built-up land—only +0.16%. The DM of development of the AOI are mainly economic components. There has been a noticeable drop in the development growth of the study area in 2021, which is apparently a consequence of the COVID-19. The upshots of the research can serve as a foundation for evaluating SD and LULC policy.

This paper is occasioned by the current events in the crude oil markets throughout the Covid pandemic time. The study analyzes the evolving nature of crude oil cost unpredictability caused by the variations that influence the crude sector throughout the current contagion. Every day's dataset is within the first month of 2020 and December 30, 2021 were measured by applying VAR and GARCH models. The results corroborate that the current contagion has adverse effects on the crude sector, primarily in two ways. It resulted in the headwinds for demand and cut international demand for crude oil, increasing uncertainty for major advanced and developing nations. Next, it resulted in output headwinds as the pandemic caused hydrocarbons conflicts among the leading crude supplying countries. The two headwinds seem to have caused the more than necessary crude unpredictability. Moreover, it was found that the United States output, total requirements, and crude-leaning demand shocks adversely affect the supply unpredictability of the United States and the extractive sectors. The findings depict that crude price instability responded significantly to the contagion caused by crude headwinds. Specifically, the study recorded the effect of uncertainty because of these headwinds beyond financiers' concerns about crude price instability. This study indicates that spillovers do not have meaningful forecast data, igniting critical debates concerning the relevance of the spillover indicator for predicting at minimal sampling occurrence.

Abstract Achieving carbon peak and carbon neutrality is an inherent requirement for countries to promote green recovery and transformation of the global economy after the COVID-19 pandemic. As "a smoke-free industry", its agglomeration may have significant impacts on CO2 emission reduction. This study uses nightlight data to calculate the CO2 emissions of 268 cities in China from 2005 to 2017 and then employs dynamic spatial Dubin model and intermediary effect model to explore the impact and transmission mechanism of producer services agglomeration (PSA) on CO2 emissions. Furthermore, the dynamic threshold model is used to analyze the nonlinear characteristics of PSA on CO2 emissions under different degrees of government intervention. The findings indicate that: (1) Generally, China's CO2 emissions are path-dependent in the time dimension, showing a "snowball effect". PSA not only significantly inhibits local CO2 emissions, but also reduces CO2 emissions in adjacent areas through spatial spillover effect; (2) PSA can indirectly curb CO2 emissions through economies of scale, technological innovation and industrial structure upgrading, Heterogeneity analysis shows that there are significant differences in the impact of PSA on CO2 emissions in different regions, time nodes and sub-industries; (3) The impact of PSA on China's CO2 emissions has an obvious double threshold effect under different degree of government intervention. Accordingly, the Chinese government should increase the support for producer services, dynamically adjust industrial policies, take a moderate intervention, and strengthen market-oriented reform to reduce CO2 emissions so that the goal of "carbon peak and carbon neutrality” can be early achieved.

Understanding and examining energy markets correctly is crucial for stakeholders to attain maximum benefit and avoid risks. As a matter of fact, the volatility that occurred in energy markets and recent crises had major impacts on national economies. Dynamic connectedness relationships (DCRs) can make quite powerful predictions for both low-frequency data and limited time-series data. The objective of this study is to explicate the dynamic connectedness relationships among the BIST sustainability index, BIST 100 index, S&P Global Clean Energy index (S&P GCEI), and S&P GSCI carbon emission allowances (EUA). The daily data obtained over the period 11 April 2014–11 November 2022 were used for the research study. The DCRs among the variables used in the study were investigated by employing the time-varying parameter vector autoregressive (TVP-VAR) model. As a result of the study, the volatility from carbon emission allowances was determined to spill over to S&P GCEI, BIST 100, and BIST sustainability indexes. During the COVID-19 pandemic, significant reductions were detected in the volatility spillover (VS) from carbon emission allowances to S&P GCEI, BIST 100, and BIST sustainability indexes. Moreover, it was revealed that a weak VS existed from S&P GCEI to BIST sustainability and BIST 100 indexes. The findings reveal the importance of policymakers taking some incentive measures in EUA prices and also its role in portfolio diversification.

The relevance of the article is determined by the need to develop the potential of small business for the purpose of an innovative breakthrough in the economy of Kazakhstan. Countries that have been fully engaged in supporting innovative entrepreneurship have become leaders. The problem is that the development of small innovative business is not facilitated by a complex state system of regulation and support that is inadequate to the needs of entrepreneurs. However, this is not the main problem of the development of innovative entrepreneurship, which is presented in the most detail in the study. The directions of increasing the effectiveness of the influence of state support programs on the development of innovative entrepreneurship, which are largely borrowed from the foreign experience of developed countries, have been substantiated. The authors propose not only some ways of innovative development of entrepreneurship in Kazakhstan, which, according to the authors, will accelerate the implementation of the innovation process in rural tourism and in the country as a whole. But they also proposed some features that will help overcome the mental barrier and national traditions, both in Kazakhstan and in the post-Soviet space, since due to the lack of an effective legal framework, the problem of corruption is threatening a social explosion. In addition, during the COVID-19 pandemic, the most affected in a difficult epidemiological situation, such organizations that operate in the field of culture, sports, additional education, tourism, hospitality, etc.

The COVID-19 pandemic is bringing about changes, and alongside these, we can alter the way we design our living spaces. The need for a healthy and comfortable living space is essential to mental and physical well-being. The present study covers the most up-to-date documents, including peer-reviewed papers, blog posts, news, journal articles, and expert opinions, to critically review lessons learned from the COVID-19 pandemic and evaluates the expected changes in sustainability requirements of residential buildings. Health and safety, environment, and comfort are the three main aspects of residential buildings that have been tested during quarantines and are also expected to experience major transformations toward sustainability. Residential houses should provide certain health and safety protective measures to their occupants, such as the application of new touchless technologies, having proper sanitation to diminish the probability of getting infected, and developing greener and more intimate spaces that can help recover and improve mental states. Our findings address the need to reconsider sustainability requirements for residential buildings, which will provide adequate health and safety and comfort with no significant harm to the environment.

This study investigated whether mobile payment services could drive post-COVID-19 pandemic recovery in the ‘experience goods’ sector (e.g., tourism) utilising Bandura’s self-efficacy or social cognitive theory. It explored the factors influencing the intention to continue using mobile payment services and the intention to recommend these to others. An empirical survey was conducted to assess the study variables, and the data obtained therefrom were analysed using the industry-standard Cross-Industry Standard Process for Data Mining method. The study results suggest that personal innovativeness and perceived trust influence consumers’ intention to continue using mobile payment services and that perceived trust, personal innovativeness and outcome expectancy influence consumers’ intention to recommend the use of such services to others. The research findings have filled a research gap in emerging markets and can serve as the basis for formulating a winning marketing and operational strategy for nascent technologies such as mobile payment services. It would be naïve to extract findings from mature markets such as East Asia, the European Union and the United States and to apply these to developing markets. In addition, this study’s investigation of the variables that can influence the intention to continue using mobile payment services and to recommend the use of these to others goes into the heart of the sustainability issue because the study’s findings can help mobile payment service providers sustain the use of their applications and thus also sustain the advantages as such.

The COVID-19 virus in a short time has caused a terrible crisis that has been spread around the world. This crisis has affected human life in several dimensions, one of which is a sharp increase in urban waste. This increase in waste volume during the pandemic, in addition to the intense increase in costs associated with the risks of virus contagion through infectious waste. In this study, a hybrid mathematical modelling approach including a Bi-level programming model for infectious waste management has been proposed. At the higher level of the model, government decisions regarding the total costs related to infectious waste must be minimized. At this level, the collected infectious waste is converted into energy, the revenue of which is returned to the system. The lower level relates to the risks of virus contagion through infectious waste, which can be catastrophic if ignored. This study has considered the low, medium, high and very high prevalence scenarios as key parameters for the production of waste. In addition, the uncertainty in citizens' demand for waste collection was also included in the proposed model. The results showed that by energy production from waste during the COVID-19 pandemic, 34% of the total cost of collecting and transporting waste can be compensated. Finally, this paper obtained useful managerial insights using the data of Kermanshah city as a real case.