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Purpose: Microfinance emerged as an essential catalyst for socio-economic development and financial inclusion to reduce poverty. Microfinance institutions cannot meet their primary objective of poverty reduction if they are not sustainable financially. With the theoretical support of profit incentive theory, this paper aims to investigate the impact of organizational structure (OS), growth outreach (average loan per borrower [ALPB] and number of active borrowers), women empowerment (percentage of women borrowers [PWB]), liquidity, leverage and cost efficiency (cost per borrower) on the financial sustainability of microfinance providers (MFPs) in India and explore the possible moderating effect of the national governance indicators (NGIs). Design/methodology/approach: A financial sustainability index has been developed by using principal components analysis, including both conventional measures (return of assets and return on equity) and efficiency measures (operational self-sufficiency and financial self-sufficiency). Due to the existence of endogeneity and heteroskedasticity, this study uses two-step system generalized method of moments estimates to examine the relationships for a period of 2006 to 2018. Findings: The finding reveals that there is a strong significant relationship between financial sustainability and its influential factors. Organizatioanl Structure, loan size, women borrowers, Gross Domestic Products and inflation enhance the financial sustainability of India's microfinance sector. However, a number of borrowers, liquidity, leverage and operating costs negatively affect the financial sustainability of MFPs of India. The estimates demonstrate that NGIs significantly moderate the association between financial sustainability and its influential factors. The NGIs negatively affect the positive impact of Organizatioanl Structure on financial sustainability. National governance increases the positive effect of loan size (ALPB) and reduces the negative effect of a number of borrowers and leverage on the financial sustainability of MFPs of India. However, NGIs negatively affect the positive relationship between Percentage of Women Borrowers and Financial sustainability of Microfinance Providers of India. Originality/value: To the best of the authors' knowledge, this study is the first of its kind that incorporates all of the six dimensions of the National Governance Indicators (NGIs) and uses as a moderator. Secondly, a financial sustainability index has been developed for measuring the financial sustainability of Microfinance Providers (MFPs). [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Impact of Economic Growth, Environmental Pollution, and Energy Consumption on Health Expenditure and R&D Expenditure of ASEAN Countries." The authors have made updates to the original publication to improve understanding. The updates include replacing terms such as "carbon dioxide emanations" with "carbon dioxide emissions" and "greenhouse emanations" with "greenhouse gas emissions." Additionally, there are corrections to the references cited in the article. The authors state that these updates do not affect the scientific conclusions of the article. [Extracted from the article]

Purpose: The purpose of this research is to investigate the synergistic impact of workplace spirituality (WPS), responsible leadership (RL), and pro-environmental behavior (PEB) within the context of Pakistan's Small and Medium Enterprises (SMEs) along with the mediating mechanism of Affective commitment (AC).Methods: Our study utilizes structural equation modeling (SEM) to analyze survey data collected from 390 employees within Pakistani SMEs. We develop a single unified framework to test the hypothesized relationships between RL, PEB, and AC as a mediator.Results: Our results unveil significant positive relationships between WPS, RL, and PEB. Our findings endorse both the direct connections between WPS, RL, and PEB, as well as the mediating mechanisms through AC. This study offers novel insights into the influence of PEB in the context of Pakistan's SMEs.Conclusion: The research significantly contributes to the existing literature by examining WPS, RL, PEB, and AC in the context of Pakistan's SMEs. The study's conclusions emphasize the potential benefits of integrating WPS and RL into business practices to encourage PEB. Additionally, we discuss the limitations of our research and suggest future avenues for further exploration in this vital area of sustainable business management. [ABSTRACT FROM AUTHOR]

Recently, biomass sources are important for energy applications. There is need for analyzing of the biomass model based on different components such as carbon, ash, and moisture content since the biomass sources are important for energy applications. In this paper, an extreme learning machine (ELM) is used to estimate efficiency. ELM was implemented for single-layer feed-forward neural network (SLFN) architectures. Because biomass modeling could be a very challenging task for conventional mathematical, it is suitable to apply machine learning models which could overcome nonlinearities of the process. The main attempt in this study was to develop a machine learning model for prediction of the higher heating values of biomass based on proximate analysis. According the prediction accuracy (coefficient of determination and root mean square error) of the higher heating value of the biomass, the inputs' influence was determined on the higher heating value. According to the obtained results, fixed carbon has less moderate coefficient, ash has less correlation coefficient, and volatile matter has the most correlation coefficient. Therefore, the volatile matter percentage weight has the highest relevance on the higher heating value of the biomass. On the contrary, the ash has the smallest relevance on the higher heating value of the biomass based on machine learning approach. [ABSTRACT FROM AUTHOR]

Since there are large requirements for green energy sustainability, in this study, optimization of in situ transesterification of microalgae slurry conversion into biodiesel was performed. The main aim was to perform a selection procedure of the optimal predictors for fatty acid methyl ester yield and exergy efficiency in situ transesterification process. The adaptive neuro fuzzy inference system (ANFIS) as a soft computing approach was used for the optimization of the predictors for the fatty acid methyl ester yield and exergy efficiency. Based on the obtained results, the optimal combination for fatty acid methyl ester yield was ultrasonic power and reaction time while the optimal combination for the exergy efficiency was concentrations of methanol and chloroform in oil. These selected predictors could be used effectively in order to maximize the fatty acid methyl ester yield and exergy efficiency. [ABSTRACT FROM AUTHOR]

Recently, biomass sources are important for energy applications. Therefore, there is need for analyzing the biomass model based on different components such as carbon, ash, and moisture content. Since the biomass modeling could be very challenging task for conventional mathematical, it is suitable to apply soft computing models which could overcome the nonlinearities of the process. The main attempt in the study was to develop a soft computing model for the prediction of the higher heating values of biomass based on the proximate analysis. Adaptive neuro-fuzzy inference system (ANFIS) was used as soft computing methodology. According to the prediction accuracy of the higher heating value of the biomass, the inputs' influence was determined on the higher heating value. According to the obtained results, fixed carbon has a correlation coefficient of 0.7644, the volatile matter has a correlation coefficient of 0.7225, and ash has a correlation coefficient of 0.9317. Therefore, the ash percentage weight has the highest relevance on the higher heating value of the biomass. On the contrary, the volatile matter has the smallest relevance on the higher heating value of the biomass. [ABSTRACT FROM AUTHOR]

A green economy has an impact on improving welfare, but it takes continuous efforts to achieve it from various fields. Contribution in the context of banking on a small scale is one of the initiatives that can show participation in achieving a green economy. This study aims to explore people's behavior in financial transactions and analyze the practice of rural credit banks in encouraging the achievement of a green economy through the National Financial Inclusive Strategy (NFIS) program despite the COVID-19 pandemic. This study used quantitative approaches; observations were conducted at a certain time by collecting data taken directly as a complement to this study, as well as taking questionnaire data involving 363 samples and analyzing them using the structural equation model (SEM). The result is that green economic support is found in using paper for fewer savings transactions compared to branchless banking with conventional savings transactions. The high number of residents exposed to COVID-19 does not affect branchless banking. In addition, the use of branchless banking can show the penetration of financial literacy in the community. The results of the path analysis explain that perceived ease of use (7.468) and perceived usefulness (2.152) have an influence on attitude; intention is greatly influenced by attitude (15.357); and actual usage is influenced by intention (11.682). This research has specific implications for the Magelang City Rural Bank (MCRB), which needs to conduct market research to find out the potential of branchless banking that is specifically needed by the people of Magelang. Branchless banking innovation needs to be strengthened by presenting easy-to-understand and easy-to-use applications to improve the attitude of the Magelang people in adopting branchless banking applications and using them sustainably. [ABSTRACT FROM AUTHOR]

The world is entering an era of awareness of the preservation of natural energy sustainability. Therefore, electric vehicles (EVs) have become a popular alternative in today's transportation system as they have zero emissions, save energy, and reduce pollution. One of the most significant problems with EVs is an inadequate charging infrastructure and spatially and temporally uneven charging demands. As such, EV drivers in many large cities frequently struggle to find suitable charging locations. Furthermore, the recent emergence of deep reinforcement learning has shown great promise for improving the charging experience in a variety of ways over the long term. In this paper, a Spatio-Temporal Multi-Agent Reinforcement Learning (STMARL) (Master) framework is proposed for intelligently public-accessible charging stations, taking into account several long-term spatio-temporal parameters. When compared to a random selection recommendation system, the experimental results demonstrate that an STMARL (master) framework has a long-term goal of lowering the overall charging wait time (CWT), average charging price (CP), and charging failure rate (CFR) of EVs. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "The Causal Connection of Natural Resources and Globalization with Energy Consumption in Top Asian Countries: Evidence from a Nonparametric Causality-in-Quantile Approach." The authors have made updates to the text and references to improve clarity and accuracy. Changes include replacing terms like "carbon emanations" with "carbon emissions," "trade barricades" with "trade barriers," and "atmospheric downfall" with "climate disaster." The authors have also corrected citations for several references. The scientific conclusions of the article remain unaffected. [Extracted from the article]

The disruptions in this era have caused a leap forward in information technology being applied in organizations to create a competitive advantage. In particular, we see this in tourism services, as they provide the best solution and prompt responses to create value in experiences and enhance the sustainability of tourism. Since scheduling is required in tourism service applications, it is regarded as a crucial topic in production management and combinatorial optimization. Since workshop scheduling difficulties are regarded as extremely difficult and complex, efforts to discover optimal or near-ideal solutions are vital. The aim of this study was to develop a hybrid genetic algorithm by combining a genetic algorithm and a simulated annealing algorithm with a gradient search method to the optimize complex processes involved in solving tourism service problems, as well as to compare the traditional genetic algorithms employed in smart city case studies in Thailand. A hybrid genetic algorithm was developed, and the results could assist in solving scheduling issues related to the sustainability of the tourism industry with the goal of lowering production requirements. An operation-based representation was employed to create workable schedules that can more effectively handle the given challenge. Additionally, a new knowledge-based operator was created within the context of function evaluation, which focuses on the features of the problem to utilize machine downtime to enhance the quality of the solution. To produce the offspring, a machine-based crossover with order-based precedence preservation was suggested. Additionally, a neighborhood search strategy based on simulated annealing was utilized to enhance the algorithm's capacity for local exploitation, and to broaden its usability. Numerous examples were gathered from the Thailand Tourism Department to demonstrate the effectiveness and efficiency of the proposed approach. The proposed hybrid genetic algorithm's computational results show good performance. We found that the hybrid genetic algorithm can effectively generate a satisfactory tourism service, and its performance is better than that of the genetic algorithm. [ABSTRACT FROM AUTHOR]

The metaverse is an innovation that has created the recent phenomenon of new tourism experiences from a virtual reality of a smart tourism destination. However, the existing metaverse platform demonstrated that the technology is still difficult to develop, as the service provider did not disclose the internal mechanisms to developers, and it was a closed system, which could not use or share the user's data across platforms. The aim of this paper was to design and develop an open metaverse platform called the "extensible metaverse", which would allow new developers to independently develop the capabilities of the metaverse system. The acquisition of this new technology was conducted through requirements analysis, then the analysis and design of the new system architecture, followed by the implementation, and the evaluation of the system by the users. The results found that the extended metaverse was divided into three tiers that created labels, characters, and virtual objects. Furthermore, the linking tier combined the 3D elements, and the deployment tier compiled the results of the link to use all three parts by using the Blender program, Godot Engine, and PHP + WebGL as their respective key mechanisms. This system was tested in Suphan Buri province, Thailand, which was evaluated by 428 users. The results of the metaverse satisfaction, created tourism experience, and overall satisfaction of the variation of the satisfaction of using the metaverse were 86.0%, 79.7%, and 92.9%, respectively. The relative Chi-square (χ2/df) of 1.253 indicated that the model was suitable. The comparative fit index (CFI) was 0.984, the goodness-of-fit index (GFI) was 0.998, and the model based on the research hypothesis was consistent with the empirical data. The root mean square error of approximation (RMSEA) was 0.024. In conclusion, the extended metaverse is more flexible than other platforms and also creates the user's satisfaction and tourism experience in the smart destination to support sustainable tourism. [ABSTRACT FROM AUTHOR]

This document is a retraction note for an article titled "Analyzing the energy performance of buildings by neuro-fuzzy logic based on different factors." The article has been retracted by the Editor-in-Chief after an investigation revealed manipulation of the peer review process and authorship. The authors have not responded to correspondence from the publisher regarding this retraction. Springer Nature, the publisher, remains neutral in terms of jurisdictional claims and institutional affiliations. [Extracted from the article]

This document is a retraction note for an article titled "The step towards environmental mitigation in Pakistan: do transportation services, urbanization, and financial development matter?" published in Environmental Science & Pollution Research. The publisher has retracted the article due to concerns identified during an investigation, including compromised peer review process, inappropriate references, nonstandard phrases, and being out of scope for the journal. The authors Salman Sarwat, Arshian Sharif, Danish Iqbal Godil, and Muhammad Sajjad Ashraf disagree with the retraction, while the authors Kittisak Jermsittiparsert, Paiman Ahmad, and Syed Hassan have not responded to correspondence regarding the retraction. Springer Nature, the publisher, remains neutral regarding jurisdictional claims and institutional affiliations. [Extracted from the article]

The prime objective of this study is to investigate the role of microfinance institutions towards women's self‐sustainability in Pakistan because women are the most vulnerable community in Pakistan and in the world, too. Due to various issues like gender discrimination, women's self‐sustainability is quite low, and this accounts for the negligible contribution of women in Pakistan's economy (up to 20 to 25%). In addressing this issue, the current study adopted a quantitative research approach and cross‐sectional research design. By using a survey questionnaire, data were collected from female clients of microfinance institutions during May 1, 2018 to August 30, 2018. SmartPLS 3 was utilized to analyse the data. The results of the inquiry revealed that microfinance institutions have an essential role to play in promoting women's self‐reliance. With the help of micro‐enterprises for women, services offered by microfinance institution such as micro‐credit, micro‐savings, micro‐insurance, micro‐training and social capital have a major role in developing women's self‐sustainability. However, an environmental disaster is one of the crucial factors, which limits the positive contribution of microfinance institutions towards women's self‐sustainability. Our thorough research and knowledge on the subject indicates that the current study is the pioneer study that has investigated microfinance institutions as major facilitators of women's self‐reliance but which has been limited by many factors such as environmental disasters. Hence, the current study appears salient for microfinance institutions, the government of Pakistan and other practitioners that desire to boost women's self‐sustainability. [ABSTRACT FROM AUTHOR]

Due to the remarkable progress in the field of the manufacturing process, smart composites have become the desired target for high-tech engineering applications. Accordingly, for the first time, thermal buckling, critical voltage and vibration response of a thermally affected graphene nanoplatelet reinforced composite (GPLRC) microdisk in the thermal environment are explored with the aid of generalized differential quadrature method (GDQM). Also, the current microstructure is coupled with a piezoelectric actuator (PIAC). The extended form of Halpin-Tsai micromechanics is used to acquire the elasticity of the structure, whereas, the variation of thermal expansion, Poisson's ratio, and density through the thickness direction is determined by the rule of mixtures. Hamilton's principle is implemented to establish governing equations and boundary conditions of the GPLRC microdisk joint with a PIAC. The compatibility conditions are satisfied by taking perfect bonding between the core and PIAC into consideration. Maxwell's equation is employed to capture the piezoelectricity effects. The numerical results revealed the important role of distribution patterns and weight fraction of GPL ( g GPL ), non-dimensional piezoelectric thickness (hp/h), outer to the inner ratio of the radius ( R o / R i ) and applied voltage on the frequency behavior, critical voltage and thermal buckling of the system. Another valuable consequence is that the influence of the h p parameter is hardly dependent on the value of the temperature changes ( Δ T). The favorable suggestion of this survey is that for optimized designing of the GPLRC microsized circular plate should pay special attention to pattern 3 of the GPLs, because in this pattern by increasing the g GPL parameter the critical voltage of the structure increases but for other patterns of GPL, this phenomenon is inverse. [ABSTRACT FROM AUTHOR]

Energy expenditures are now the main cost for two businesses that generate huge incomes each year for Thailand, which are agribusiness and community tourism. As entrepreneurs have to share a portion of their income as energy utility bills each month. This is a factor which results in them getting a low net return. Recognizing the need for energy management for sustainable use in agriculture focusing on durian cultivation in Kantharalak district and community tourism in Sisaket province, this research used a newly developed optimization algorithm called Kouprey-inspired optimization (KIO) to assist energy management in smart agriculture to support community-based tourism. This was initiated with a smart energy node to reduce the energy and labor costs for volcanic durian planting and accommodation in community-based tourist attractions in Sisaket province. The results showed that the combination of the KIO algorithm and smart energy node allowed for efficient management of the volcanic durian orchards and the use of clean energy in combination with traditional electric power for volcanic durian cultivation and community-based tourism. As the research area in Sisaket province had eight hours of solar power per day, this was sufficient for smart agriculture and community-based tourism in the daytime and in the evening. Furthermore, this allowed operators in both the agricultural and tourism sectors to reduce the labor costs of the durian orchard business and community-based tourism by about 30%, and in the energy sector, the costs could be reduced by 50%. As a consequence, this prototype would lead to the expansion and trial in durian orchards in the Eastern Economic Corridor area, which is an important economic area producing durian for export of the country. [ABSTRACT FROM AUTHOR]

Background: Mass vaccination campaigns have significantly reduced the COVID-19 burden. However, vaccine hesitancy has posed significant global concerns. The purpose of this study was to determine the characteristics that influence perceptions of COVID-19 vaccine efficacy, acceptability, hesitancy and decision making to take vaccine among general adult populations in a variety of socioeconomic and cultural contexts. Methods: Using a snowball sampling approach, we conducted an online cross-sectional study in 20 countries across four continents from February to May 2021. Results: A total of 10,477 participants were included in the analyses with a mean age of 36±14.3 years. The findings revealed the prevalence of perceptions towards COVID-19 vaccine's effectiveness (78.8%), acceptance (81.8%), hesitancy (47.2%), and drivers of vaccination decision-making (convenience [73.3%], health providers' advice [81.8%], and costs [57.0%]). The county-wise distribution included effectiveness (67.8–95.9%; 67.8% in Egypt to 95.9% in Malaysia), acceptance (64.7–96.0%; 64.7% in Australia to 96.0% in Malaysia), hesitancy (31.5–86.0%; 31.5% in Egypt to 86.0% in Vietnam), convenience (49.7–95.7%; 49.7% in Austria to 95.7% in Malaysia), advice (66.1–97.3%; 66.1% in Austria to 97.3% in Malaysia), and costs (16.0–91.3%; 16.0% in Vietnam to 91.3% in Malaysia). In multivariable regression analysis, several socio-demographic characteristics were identified as associated factors of outcome variables including, i) vaccine effectiveness: younger age, male, urban residence, higher education, and higher income; ii) acceptance: younger age, male, urban residence, higher education, married, and higher income; and iii) hesitancy: male, higher education, employed, unmarried, and lower income. Likewise, the factors associated with vaccination decision-making including i) convenience: younger age, urban residence, higher education, married, and lower income; ii) advice: younger age, urban residence, higher education, unemployed/student, married, and medium income; and iii) costs: younger age, higher education, unemployed/student, and lower income. Conclusions: Most participants believed that vaccination would effectively control and prevent COVID-19, and they would take vaccinations upon availability. Determinant factors found in this study are critical and should be considered as essential elements in developing COVID-19 vaccination campaigns to boost vaccination uptake in the populations. Author summary: This large-scale multi-country study explores perceived COVID-19 vaccine effectiveness, acceptability, and hesitancy rates and their related factors among the general adult populations from 20 countries. We found that a considerable proportion of the participants has an intention to receive the COVID-19 vaccine. However, more than half still expressed their hesitancy to receive the vaccines. Countries where the majority of respondents responded that they would accept COVID-19 vaccination included Malaysia (96.0%), Bangladesh (93.6%), and Iraq (91.8%). The majority of the participants from Vietnam (86.0%) and Turkey (74.7%) expressed hesitance to receive COVID-19 vaccine. Perceived vaccine effectiveness ranged from 67.8% in Egypt to 95.9% in Malaysia. The participants believed that convenience, health providers' advice, and costs of vaccines are important for people to decide whether to accept COVID-19 vaccines. Country of residence, age, sex, level of education, area of residence, marital status, and family economic status were significantly associated with tendency to undergo COVID-19 vaccination and the perception that COVID-19 vaccine decision-making is influenced by convenience. The findings of this study provide useful guidance for tailored interventions to enhance the acceptance of COVID-19 vaccine. Promotional program addressed on detected socioeconomic factors is warranted. [ABSTRACT FROM AUTHOR]

Energy performance of buildings is an important issue to estimate the energy waste of buildings and their impact on the environment, so designing energy-efficient buildings could improve their energy performance. In this case, the estimation of heating and cooling loads plays an important role in this regard. However, there are few factors with unpredictable influences on the heating and cooling loads. This study has attempted to analyze the eight parameters that can significantly affect the heating and cooling loads through the Neuro-fuzzy logic approach. Accordingly, the eight parameters of relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area and glazing area distribution were considered as inputs and predicting the cooling and heating load changes was regarded as the output of this study. The model was developed and its results were measured in two regression indicators of r and RMSE. Based on the obtained results it was found that roof has the strongest impact on heating and cooling loads (RMSE: 4.3596), moreover, if two factors were concurrently changed, then the combination of relative compactness and wall area can significantly affect the heating and cooling loads (RMSE: 2.6312). The most influential combination of three factors is observed as well for the heating and cooling load and these factors are relative compactness, wall area and glazing area (0.5948). The most influential combination of three factors is observed as well for the hearing load and these factors are relative compactness, wall area and glazing area (RMSE: 0.5948 and RMSE: 1.5769 for heating and cooling load, respectively). However, Neuro-fuzzy logic showed overfitting for more than two inputs, therefore it is not recommended for more than two inputs. [ABSTRACT FROM AUTHOR]

In many engineering problems, the systems dynamics are uncertain, and then, the accurate dynamic modeling is required. Type-2 fuzzy neural networks (T2F-NNs) are extensively used in system identification problems, because of their strong estimation capability. In this paper, the application of T2F-NNs is reviewed and classified. First, an introduction to the principles of system identification, including how to extract data from a system, persistency of excitation, preprocessing of information and data, removal of outlier data, and sorting of data to learn the T2F-NNs, is presented. Then, various learning methods for structure and parameters of the T2F-NNs are reviewed and analyzed. A number of different T2F-NNs that have been used to system identification are reviewed, and their disadvantages and advantages are described. Also, their efficiency in different applications is reviewed. Finally, we will look at the horizon ahead in this issue and analyze its challenges. [ABSTRACT FROM AUTHOR]

This study is a scholarly effort to broaden the existing literature on the impact of transportation services, urbanization, and financial development on ecological footprints in Pakistan. Data used in this study covers the period of 39 years from 1980 to 2018. This study adopted the QARDL model to tackle the non-linear association of variables and test their long-run stability across the different quantiles. The findings of this study indicated a significant negative association of transportation services and financial development with ecological footprints in Pakistan at almost all quantiles whereas, the urban population was found to be positively associated with the ecological footprint in Pakistan. Results also justify the existence of the EKC hypothesis in the scenario of Pakistan. Policymakers are advised to frame strategies for investors to invest more in eco-friendly projects to curtail the ecological footprints in Pakistan. Minimizing the dependency of the transportation sector on fossil fuel, and increased use of energy-efficient appliances in the urban population would be beneficial to control the negative influence on ecological footprints in Pakistan. [ABSTRACT FROM AUTHOR]

We employ the new Method of Moments Quantile Regression approach to expose the role of natural resources, renewable energy, and globalization in testing Environment Kuznets Curve (EKC) in MINT panel covering the years 1995–2018. The outcome validates the EKC curve between economic progress and carbon emissions from the third quantile to the extreme highest quantile. The result also shows that natural resources increase CO2 emissions at the lowest quantile and then turn insignificant from the middle to the highest quantiles due to the potential utilization of resources in a sustainable manner. The renewable energy mitigates CO2 emissions at the lower half quantiles. Still, for upper quantiles, the results are unexpected and imply that the countries' total energy mix depends heavily on fossil fuels. As far as globalization is concerned, the significant results from medium to upper quantiles reveal that as globalization heightens due to foreign direct investment or trade, energy consumption also expands, leading to the worst environment quality. Thus, the present study's consequences deliver guidelines for policymakers to utilize natural resources sustainably and opt technologies based on clean energy, which may offset environmental degeneration. [ABSTRACT FROM AUTHOR]

For an economy to excel in growth, there is usually a trade-off between financial development and environment deterioration. For a country like Singapore, which has shown a radical growth and is known for its population density, it is important to explore the role of green technology innovation in the pursuit of economic excellence with the least possible cost to the environment. By employing the novel bootstrap autoregressive-distributed lag (BARDL) technique using a time series data from 1990 to 2018, the results reported a positive and significant relationship of green technology innovation with economic growth and negative and significant relationship with carbon emissions in both long run and short run. Based on the findings, several managerial implications were discussed, whereas based on the limitations, directions for future researchers are also given. [ABSTRACT FROM AUTHOR]

Purpose: current study intends to examine key human resources practices (human capital, training and rewards) that influence employee commitment and service recovery performance (SRP) of Takaful industry agents in Southeast Asian region. The Takaful industry is facing stiff competition with conventional insurance industry in Malaysia and Indonesia as the Southeast Asian region has a large Muslim population. SRP is crucial in insurance industry specifically in the Islamic Insurance (Takaful) industry and plays a vital and key role in sustainable competitive advantage for value addition for firms in future to acquire market. Design/methodology/approach: The data was collected from 350 front line agents of the Takaful industry operating in Malaysia and Indonesia on convenience sampling technique. Data was analyzed by using PLS-SEM to examine the relationship between constructs. Findings: The results show that human capital, training and reward significantly influence commitment of employee which further influenced SRP to be improved. Mediation effect was also found to be influential and statistically positive and significant by employee commitment between key HR practices (human capital, training, rewards) and SRP. Originality/value: current study contributed to the body of knowledge in explaining relationship of human capital to employee commitment and SRP, further, inconclusive findings between training and rewards was also explained in the Takaful industry of the Southeast Asian region. [ABSTRACT FROM AUTHOR]

This study examines the association between tourism development, technology innovation, and carbon emissions by simultaneously testing Environment Kuznets Curve (EKC) hypothesis in China. The study develops and uses a novel composite index of tourism development and technology innovation. Utilizing quarterly data from 1995Q1 to 2017Q4, the study employs QARDL (Quantile Autoregressive Distributive Lag) approach and Granger causality‐in‐quantiles. The outcome of the study reveals that the observed relationship is quantile‐dependent, which may disclose misleading results in previous studies using traditional linear methodologies (such as OLS/ARDL) that address the averages. Primarily, the findings indicate that tourism development (TOR) and technology innovation (TII) significantly mitigate the level of carbon dioxide emissions (CO2) in the long run at lower‐higher (0.05–0.95) emissions quantiles and higher‐highest (0.7–0.95) emissions quantiles, respectively. Economic growth (GDP) and globalization (GLO) exert a positive asymmetric influence on CO2 only at lower‐medium (0.05–0.40) emissions quantiles and medium‐higher emissions quantiles (0.50–0.95), respectively. In the short run, TII, and GDP2 possess an insignificant impact across all emissions levels, while TOR shows a positive influence on CO2 only at lowest‐lower (0.05–0.20) emissions quantiles. The study confirms the presence of the EKC hypothesis at lower‐higher (0.05–0.70) emissions quantiles in the long run. Moreover, the outcomes of Granger causality in quantiles confirm asymmetric bidirectional quantile causality between TOR, TII, GLO, and CO2, while a unidirectional causality running from GDP to CO2. The results recommend that the Chinese government should implement integrated "tourism‐technology" policies based on the asymmetric emissions‐reduction effects of tourism and technology innovation in the long run. [ABSTRACT FROM AUTHOR]

Automatic speaker recognizing models consists of a foundation on building various models of speaker characterization, pattern analyzing and engineering. The effect of classification and feature selection methods for the speech emotion recognition is focused. The process of selecting the exact parameter in arrangement with the classifier is an important part of minimizing the difficulty of system computing. This process becomes essential particularly for the models which undergo deployment in real time scenario. In this paper, a new deep learning speech based recognition model is presented for automatically recognizes the speech words. The superiority of an input source, i.e. speech sound in this state has straight impact on a classifier correctness attaining process. The Berlin database consist around 500 demonstrations to media persons that is both male and female. On the applied dataset, the presented model achieves a maximum accuracy of 94.21%, 83.54%, 83.65% and 78.13% under MFCC, prosodic, LSP and LPC features. The presented model offered better recognition performance over the other methods. [ABSTRACT FROM AUTHOR]

This research article aims at examining the nature of the relationship between the real effective exchange rate and oil prices in Thailand for the period 1997 to 2019. It is expected that bilateral exchange rates have more fluctuation under a floating exchange rate than under a fixed exchange rate. The monthly data of real oil prices and real effective exchange rate have been employed for the analysis. The results indicate that these two series do not have co-integration and causality connections. However, a raise in the instability in oil prices brings to a raise in rate of exchange instability. These findings have important policy implications for the government. [ABSTRACT FROM AUTHOR]

With the growing interest among researchers in analyzing the ecological footprint of any country, this study focuses on new dimensions to analyze the long-run and short-run asymmetric impact of tourism, financial development, and globalization on ecological footprint in Turkey by using Quantile Autoregressive Distributed Lag model for the period from 1986 to 2018. Further, the EKC hypothesis was also tested. The results show that tourism, globalization, and financial development are positively and significantly associated with the EFP. This means that the increase in these variables will further increase the ecological footprint in Turkey. The U-shaped EKC curve was found to be valid in Turkey. The results also depict nonlinear and asymmetric association among most of the variables. Hence, based on the results, further research directions and practical implications can be suggested. [ABSTRACT FROM AUTHOR]

BRICS are among the rising nations which drive economic growth by excessive utilization of resources and resulting in environment degradation. Although there is bulk of research on environmental Kuznets curve (EKC), very limited studies explored the scope in context of tourism in BRICS countries. So this research is conducted to explore the association of tourism, renewable energy, and economic growth with carbon emissions by using annual data of BRICS countries from the year 1995 to 2018. By using the recent approach of method of moments quantile regression (MMQR), the finding shows that tourism has stronger significant negative effects from 10th to 40th quantile while the effects are insignificant at remaining quantiles. Furthermore, an inverted U-shape EKC curve is also apparent at all quantiles excluding 10th and 20th quantiles. For renewable energy, the results are found negatively significant across all quantiles (10th–90th) which claim that CO2 emission can be reduced by opting renewable sources. Hence, the empirical results of the current study provide insights for policymakers to consume renewable energy sources for the sustainable economic growth and solution of environmental problems. [ABSTRACT FROM AUTHOR]

The adoption of AI is an ongoing phenomenon in today's economy in all the industries. The purpose of this paper is to examine the economic impact of AI adoption in the region of ASEAN. To achieve this objective, structural questionnaire was developed for the various industry experts in targeted region. A sample of 240 experts was finally obtained over a time span of 6 weeks through online structural questionnaire approach. For measuring AI adoption, twelve items, initial economic impact (seven items), and subsequent economic impact (six items) were finally added in the questionnaire. For analyses purpose, descriptive statistics, structural equation modelling, and regression analyseswereapplied, examining the both initial and subsequent economic impact of AI adoption. Findings through structural model indicates that overall both initial and subsequent impact are significantly determined by AI adoption in related industries. Additionally, in depth analyses for the individual AI items as their initial and subsequent economic impact indicate that Usage of the data for AI adoption, clear strategy for AI adoption, successful mapping for AI adoption and overall positive attitude towards AI adoption have their significant and positive influence on initial economic indicators. Whereas, as per subsequent economic impact, factors like effective usage of data for AI adoption, assessing the right skills of individuals for AI adoption and positive attitude towards AI adoption are significantly impacting on material investment, capital investment, increasing unemployment, higher economic output, higher return on capital and higher wages for the existing labor. These findings have provided an outstanding evidence in the field of AI and its economic impact in the region of ASEAN and can be considered as initial contribution in related fields. Both industry exports and macroeconomic decision makers can significantly utilize the findings to develop their conceptual framework and understanding for the integration between AI adoption and economy. Additionally, this study can work as reasonable justification for implementing the more adoption of AI in various industries as it has positive economic outcome (both initial and subsequent). However, one of the key limitations of this study is limited sample size and only 240 industry exports were targeted from selected industries in ASEAN. Future study could be reimplemented on similar topic with expanding the sample size for better findings and more generalization. [ABSTRACT FROM AUTHOR]

The main purpose of the study is to explore the impact of defense expenditure, internal threats, and political instability on the economic growth of Thailand. This study focuses mainly on investigating the impact of Thailand's defense expenditures at its aggregate and disaggregate components on the economic growth. The study has used ARDL to examine the data of 33 years gathered over the period from 1986 to 2018. It specifically examines the impacts of defense expenditures in the presence of internal threat, political instability and arms import on the Thailand's economic growth. This study is constrained by the availability of similar data on other countries particularly the ASEAN countries. Thus, it induces the researcher to focus on Thailand alone. The study has argued that the rising instability, regional conflicts and terrorism in recent years have given rise the demand for greater defense outlays and domestic security in developed and developing countries. These conflicts generally emerge due to resource conflicts and disputes arising from power tussle. The nature of conflicts, wars, economic, political, technological, military and industrial compositions have been changing. Such trends influence budget allocation process which in turn influence the share of defense expenditures. Defense expenditures has implications for RGDP and needs to be analyzed explicitly as a significant input to the political process engaged to determine the composition of public spending. The research is concerned with the expenditure within the defense sector, threats and political instability and their effects on Thailand's economic growth. It also examines the impacts of the disaggregate defense expenditures components on economic growth. Data is accessed from the SIPRI, World Bank Development Indicators Data Bank, Thailand's Ministry of Defense. The findings of the study have provided support to the hypothesized results. This analysis could isolate a direct economic contribution of the defense activities in Thailand. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate the relationship between sustainable development and the circular economy in ASEAN region. To address this objective, five economies (Malaysia, Indonesia, Thailand, Singapore, and Philippine) were selected from 1995 to 2013 with annual observations. For measuring the factor of sustainable development, overall, twopak dimensions have been observed; functional wellbeing and economic wellbeing. Besides, circular economy is measured through three measures in terms of generation of municipal waste per capita, per GDP, and per DMC respectively. Based on the panel nature of the data, present study has applied three models under the title of OLS estimator, fixed effect and random effect. The findings of the study indicate that there is a significant impact of various factors of functional and economic wellbeing on the circular economy in the ASEAN region. In terms of originality/value, country representatives and policymakers specifically those working for better economic output through circular economy can get significant knowledge with current findings. Additionally, sustainable development is also under significant attention of the researchers in recent years for the betterment of planet earth. This study will also provide a good contribution to the field of sustainability as it observes its two dimensions, functional wellbeing and economic well-being. However, future research contributions can meaningful contributions while integrating the CE ownership models, and operational principles of CE for sustainable development in different regions too. [ABSTRACT FROM AUTHOR]

E-government involves the use of latest skills by the government while providing the services and other information management systems to its citizens. Open data refers to the openness of all the data related to government to its citizens so that the government becomes more and more transparent and to decrease negative activities. Transparency refers to the clear and clean image of a government towards its people, which increases the trust of people on their government. The motive of this study is to analyze the impact of e-government adoption and open government data on transparency in ASEAN countries. Two control variables i.e. literacy rate and corruption have also been used in the study. The past literature has also been discussed in literature review section of this study. In order to conduct research, data about the concerned variables of the study has been collected from ASEAN countries consisting of 29 years. After applying several tests and approaches for research purpose, the two major hypotheses of this study are accepted along with the impact of a control variable, corruption. However, the impact of other control variable i.e. literacy rate has been rejected. There are various theoretical, practical and policy making benefits that will increase the transparency. [ABSTRACT FROM AUTHOR]

A central concentrating solar power (CSP) plant is increasing in the power systems as novel technology in the solar energy sources. Also, solar thermal storage unit is combined with the CSP plant to increase flexibility and decrease the dependence on the instantaneous solar radiation. Furthermore, the CSP plant can be obtained the optimal offering strategies to submit to the electricity market in order to sell the produced power and increase the expected profit. In this paper, the uncertainty modeling of solar irradiation and electricity market price is a big challenge for a CSP plant. Therefore, the scenario-based stochastic framework is proposed for optimal scheduling of a CSP plant in the presence of uncertainties to obtain optimal offering curves in order to sell to power market. Also, the risk related to uncertainties is considered via the downside risk constraints (DRC), which leads to obtain risk-constrained stochastic optimization of a CSP plant. The proposed model is formulated as mixed-integer linear programming, which is solved via CPLEX solver under GAMS optimization software. Risk-averse strategy is introduced in comparison with risk-neutral strategy to investigate the impacts of DRC implementation, which leads to decrease the expected profit while the expected risk-in-profit reduced. [ABSTRACT FROM AUTHOR]

This novel research is an argumentative subject which was needed to be addressed and to fill this gap, the author examined the effect of financial development, information and communication technology, and institutional quality on CO2 emission in Pakistan by using quantile autoregressive distributed lag (QARDL) model. The data were obtained for the period from 1995Q1 to 2018Q4. In the long run, GDP and institutional quality have a positive impact on CO2 emission when this emission is already high, which shows that if the GDP and institutional quality increases, the CO2 emission also increases. Moreover, financial development and ICT has a negative impact on CO2 emission irrespective of emission level that whether it is high or low in the country, which shows that if financial enhancement and ICT increases, carbon emission decreases. The study also supported the EKC hypothesis in Pakistan. [ABSTRACT FROM AUTHOR]

Education is an inevitable aspect for any country and without it; no country can flourish and grow effectively. Therefore, the quality of education must not be compromised. As the impact of human development, public spending on education and trained teachers’ availability is being studied in context of quality of education, a whole study and research plan has been prepared by the author. Data collection process involves the gathering of data from Asian countries for 25 years from reliable data bases. After data collection, several tests and approaches were used for the analysis of data. LLC unit root test was applied for order of integration and stationarity of data, Kao cointegration test was applied to find out cointegrated and long run relationships between the variables and finally DOLS estimation approach was used to measure the relationship between the variables. According to the results of these tests, it has been found that the variables that have significant impact on quality of education include human development, public spending on education, trained teachers’ availability and literacy rate. In the last, several theoretical, practical and policy making implications have been discussed by the author. Different limitations have also been identified and future research recommendations have also been given for the assistance of other researchers. [ABSTRACT FROM AUTHOR]

The purpose the current study is to investigate the moderating impact of leadership on the association of customer intention, employee satisfaction and organizational performance in the pharmaceutical industry of Thailand. For this purpose, data was collected from managers of pharmaceutical industry by using a selfadministered questionnaire. The SEM analysis of the study has shown that there is a positive and significant relationship between the customer orientation and organizational performance. The employee satisfaction has an insignificant relationship with the organization. The indirect effect of the study has shown that the leadership has positive and significant moderating effect among all the exogenous and endogenous variables in the pharmaceutical industry of Thailand. These findings have shown that these variable does not only have a direct effect on organizational performance but also indirectly effect to the organizational performance. These findings, therefore, could provide help to business owners to know the importance of good leadership to increase the performance of the organization. The research limitations and future direction are also discussed at the end of the study. [ABSTRACT FROM AUTHOR]

In the current work with innovative combination of sonochemical method with freeze-drying technique graphene/Pd-doped TiO2 nanocomposite was successfully synthesized which has high photocatalytic performance for degradation of Remazol navy blue a textile azo-dye under visible-light radiation. In the designed method, the ultrasound waves were used for dispersion of the Pd-doped TiO2 nanospheres between the graphene layers, which subsequent quick freezing of the obtained suspension by liquid N2 results in the fixing of the positions of the Pd-doped TiO2 nanospheres and the good dispersion of the graphene sheets in the nanocomposite. According to the obtained results, the freeze-dried sample has higher photocurrent, surface area and photocatalytic performance than the conventional dried one. All of these results are related to the best distribution of the graphene layers in the nanocomposite structure. Fast freezing of the graphene/nanoparticles suspension prevents from the stacking (due to the π-stacking interactions) and aggregation of graphene layers during drying, and results in the well distribution of graphene in the final nanocomposite. [ABSTRACT FROM AUTHOR]

The aim of this study is to explore the role of urbanization and economic growth in natural resources using a time series data from 1971 to 2018. The current study applied a novel methodology of nonlinear ARDL proposed by Shin et al. (2014). This methodology is ideal to answer the asymmetric effect on the independent variable on the dependent variable. Furthermore, we also applied asymmetric Granger causality introduced by Hatemi-J (2012) to confirm the causal relationship between the variables. The results of NARDL affirmed that all the variables have a significant impact on natural resources rent. The findings confirm that negative shocks of urban intensity decrease the natural resources rents; however, the positive shocks increase the rents of natural resources. On the one hand, the positive and negative shocks of GDP increase the natural resources though, the magnitude of positive shocks are significantly different from the negative shocks. On the other hand, the results of asymmetric Granger causality confirm that positive and negative shock of urban intensity does granger cause positive shocks of natural resources. Whereas, positive shocks of natural resources (economic growth) have a causal connection with positive and negative shocks of economic growth (natural resources) in Indonesia. [ABSTRACT FROM AUTHOR]

Indonesia has many gifted young scientists, who need to get support and good opportunities to work. Numerical ability is one element that must be mastered in mathematics. This study aims to determine the effect of numerical ability of students who take part in learning using the Team Assisted Individualization (TAI) learning model with those who follow conventional learning models. The type of research is quasi experimental design. The instrument used to test numerical ability on the topic of sequences and series is an essay. Data were analyzed from the results of the posttest using t-test. Based on the calculation, obtained that tcount of 3,977 and ttable of 2,005, it can be concluded that ttable = table means that the Team Assisted Individualization (TAI) learning model has a good impact on the numerical ability of students. [ABSTRACT FROM AUTHOR]

Human Resource Management (HRM) has been renowned applied theme in the professional field. However, corporations have completed the great funds for HRM technology, pragmatic investigation proposals unpredictable sustenance that HRM technology increases the administrative performance. Though, investigation that observes the associations amid HRM and organization's performance is yet scarce. This study empirically studies the connection amid HRM and performance of firm in pharmacy business of Thailand. It also examines the mediating impact of marketing capability on the connection amid HRM and organizational performance. Data collected using survey method whereby an overall of 270 surveys were dispersed to employees of pharmacy and received 250 questionnaires. The results show a constructive connection amid HRM technology and organizational performance. They, moreover, specify that marketing capability mediated amid HRM technology and organizational performance. This study verified that HRM technology is the main cause of influence on marketing capabilities and organizational performance. Overall, this investigation contributes by enlightening the importance of HRM in improving organizational performance. [ABSTRACT FROM AUTHOR]

Business prosperity is only possible through effective human capital in place and has, therefore, been noted as the key success prospect in the history of management and business. Different studies have indicated towards numerous factors whereby, prominent scholars have outlined an important role of emotional demands, supervisor support and training opportunities. This study aims to explore the influence of emotional demands, supervisor support, and training opportunities on work engagement. A self-administered questionnaire was distributed using a convenient sampling technique. The unit of analysis in this selected the employees of the pharmaceutical companies from any level of the organization, including top-level, medium level and lower level. A total of 355 respondents interviewed form six pharmaceutical companies. After data screening 340 useable questionnaires received and proceeded for further analysis of the study. This study confirm that employees perceive good training opportunities from the organization, they are more engaged at work. The study also found that support from coworkers, more specifically from the supervisor is higher, the employee is obliged to pay back to the organization by engaging more at work. This is the proper implementation of the social exchange theory. The study revealed that emotional support was also a significant predictor of employee engagement in the context of the pharmaceutical industry in Thailand though the effects are comparatively lower than other two factors such as training and supervisor support. [ABSTRACT FROM AUTHOR]

The aim of this work is to analyze the role of human resource practices (HRP) such as employee selection, performance appraisal, and reward system on the services innovation behavior of the employee working in pharmacy firm in Thailand. Additional purpose of this research is to examine the mediating role of organizational commitment on the nexus of HRP such as employee selection, performance appraisal, reward system and services innovation behavior. The current managers of HR and their selected employees are the respondents and data were gather through questionnaires by personal visit to the outlet of pharmacy situated in the Bangkok. The results indicated that HRP such as employee selection, performance appraisal, and reward system have positive association with the services innovation behavior and the findings also revealed that the organizational commitment positively mediates among the link of HRP such as employee selection, performance appraisal, reward system and services innovation behavior. These outcomes provided the insight to the regulation making personals that they should developed and also making arrangement for the effective implementation of HRP in the business that enhance the organizational commitment and services innovation behavior. [ABSTRACT FROM AUTHOR]

It has become important for the organization to gain a competitive advantage over other companies which is not easy in a challenging environment. The biggest challenge in the situation is retaining experienced employees. The organizations can retain their employees for a longer period of time through effective practices of Human Resource as they help organizations in getting a competitive edge. The purpose of this study was to analyze the effectiveness of HR practices including Training Facilities, Benefits and Compensation, and Performance Appraisal in the pharmaceutical industry of Thailand. The job satisfaction is taken as the mediating factor between HR practices and employees retention. The nature of the study is quantitative and the data has been collected through questionnaires that were distributed among 6 pharmaceutical companies using purposive sampling. The study has found that all of these three HR functions positively impact the retention of employees through the development of skills and increased satisfaction. The path analysis of the study shows that job satisfaction is a true mediator of the relationship between different HR policies and employees' retention. [ABSTRACT FROM AUTHOR]

Turnover intention is an individual's thinking on the probability of switching the job within a certain stretch of time. Due to turnover intention on employee's mind, employee's responsibilities in the organization might be hampered which will make ultimate damage to working productivity of the company. It has been extensively discussed by a lot of researchers from various perspectives on main reasons for studying turnover intention. There are several aspects which would make influence on employees to have an intention to switch the jobs. In this study, the researchers attempt to investigate the influence of workplace stress and work life balance on turnover intention of the employees in pharmaceutical industry of Thailand. Workplace stress is one of the major contributors of how the employees perform for their job. Work-life balance deals with the techniques for balancing the professional life and private life that an individual request for the home and work. This research is a quantitative research which utilizes structural equation modelling by using Smart PLS version 3. The unit of analysis is the individual employee working in one of the pharmaceutical companies in Thailand. Total 300 employees selected from these 13 companies for distributing the questionnaires. A total of 277 usable questionnaires were collected back and proceeded for further analysis. Findings showed that, work life balance and workplace stress significantly influence the turnover intention of the organization. [ABSTRACT FROM AUTHOR]

The functions of Human Resource are greatly affected by the prevalent phenomena of discrimination at workplaces. There are different types of discrimination and an in-depth analysis of gender-based, age-based, and race-based discrimination has been conducted to analyze their presence in the pharmaceutical industry of Thailand and their impact on the employees' job satisfaction and performance. The study has used quantitative data analysis method and 300 questionnaires were distributed among the employees of pharmaceutical companies. The results have shown that all three types of discrimination negatively impact the job satisfaction and performance of employees. However, in the case of the pharmaceutical industry of Thailand, only race-based discrimination has been found. [ABSTRACT FROM AUTHOR]