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Around the globe, all developing and developed economies focus on renewable energy sources for clean and sustainable economic growth and aim to decrease carbon emission to improve the climatic condition. This study aims to evaluate the feasible renewable energy source in Pakistan and study the criteria based on the investigation of wind energy, biomass energy, geothermal and solar energy, and their effects on Pakistan’s climate. As renewable energy, clean and sustainable production is only produced from renewable energy sources; the current paper bears the viability of five primary renewable energy sources in Pakistan. This article established an advanced fuzzy (AHP) with a multi-perspective approach based on the expert assessment to select the efficient renewable energy in Pakistan. Further in this study, we utilized the DEA model to investigate the relative efficacy of renewable energy. This study indicated that wind energy is the efficient renewable energy source in Pakistan, which showed an efficiency score of 0. 1000. Our results further suggested that wind energy’s next option for renewable energy solar best for renewable production in Pakistan. The results further exposed that the solar is the second-highest energy source with an efficiency score of 0. 777. Moreover, geothermal gets a less efficient score, that of 0.198. Further, our study showed that the economic benefits (EBs) and environmental implication criteria are significant in this research. This article gives a strong recommendation for a future wind energy source in Pakistan. Our results suggest that the best renewable energy source in the future is wind energy for the sustainable and economic development of Pakistan and other developing countries.

PurposeThis paper aims to provide a valid insight into consumers' minds while considering word of mouth (WOM), brand image and uniqueness as independent variables while considering the tourism industry as the primary stakeholder.Design/methodology/approachThe study adopts qualitative research methods and data collected from 1,033 respondents using convenience sampling methodology. The data are collected from different tourists spots in China and Pakistan. The PROCESS macro was utilized in this study using SPSS version 25.0 to inspect the impacts by using Model 4 and the conditional effects indirectly by utilizing Model 14.FindingsCustomer's intimacy, search for novel and unexplored destinations highlight WOM interactions and perceived service value. Service value, interactional justice and professional attitude of hotel management mediated all the given relationships significantly. The brand image does not mediate any significant associations. Perceived service value and brand image predict customer's loyalty, and WOM is the direct measure of their intentions, and these variables are market trend indicators. A tourist's response toward different destinations is described in this study with comparative analysis of Chinese and Pakistani tourists. The study results showed a significantly positive relationship between hotel management professional behavior, customer's loyalty, customer's intimacy and WOM.Research limitations/implicationsThe recruited population might not be represented as the broader and larger visitor population, resulting in restricting establishing tactics. Moreover, this study's results provide significant insight into a tourism industry, hence providing a chance to manage customer loyalty better.Social, managerial and theoretical implicationsThis study contributes significantly to the body of knowledge and provides remarkable insight from the managerial perspective. Interactional justice results in significant value for hotel management directors and top management, front desk staff and operatives and front level employees and managers. Consumer sensitivity of fairness in interpersonal dealings calls for behavioral changes in frontline employees, especially those directly dealing with hotel visitors. Hotel staff and management should formulate a system to deal with the demands and needs of visitors. It should describe the rights and obligations of visitors and ensure that each customer is treated equally and with respect. Customers should be motivated to read the survey questionnaires kept in their rooms and offer their views on the services provided. This strategy might increase the customers' sense of empowerment and leading to notions of fairness in individual encounters.Originality/valueThis study provides an insight into the customer's minds while considering essential variables that include WOM, brand image, perceived service value and uniqueness.

The ubiquitous increase in globalization and high carbon emissions, aiming to achieve non-zero emissions in the future, is a feasible challenge for a sustainable environment. Our study aims to investigate the impact of economic globalization on carbon emissions of the developed country covering the period of 1970-2019. The Wavelet Coherence (WC) and Quantile on Quantile Regression (QQR) approach have been used to analyse co-movements and feedback linkages of CO

The study is based on validating and exploring the effects of a mega project plan (CPEC) on infrastructure development and Sustainable Project Management. The CPEC has great importance to infrastructure development and economy-boosting. The current study's primary aim is to deal with environmental protection, economic boost up, international relations influencing to the Project's success. The paper also addressed project management as a moderator between environmental protection, economic boost up, international relations, and the CPEC project's success. The primary data has been gathered by using questionnaires, and PLS-SEM has been employed for the analysis. The results revealed that environmental protection, economy boost up, and international relations have a positive association with the success of CPEC. The outcomes also exposed that project management moderating among the nexus of economy boosts up the international relations and success of CPEC. The present study results guided how Pakistan and China make the CPEC project stronger with the efficient implementation of practices required for protecting the environment, with the economic growth and boost up, and good strong relations with foreign countries. This study was an attempt to validate the different factors to check their association with each other in a new environment, resulting in a leading edge for the success of mega projects that influence project management.

The emission and mitigation of greenhouse gases transforms the status of urban environments. However, a policy accounting for all the aspects associated with transport is lacking. Problems related to transport include a greater reliance on cars, increased congestion, and environmental impacts. The absence of an efficient public transport system is a notable cause of the prompt escalation of diverse problems, for example, increases in the number of personal automobiles causes congestion on the road, resulting in air pollution, ubiquitous greenhouse effects and noise pollution, which ultimately affect human health. Transit oriented development (TOD) has been suggested as a solution to these problems. This paper reviews the impacts of transit development on urban development, greenhouse impact, the environment, economy, property value, travel behavior, and health etc., highlighting the policy issues which hinder TOD. Implementation of TOD has a strong impact on shaping the urban form, redevelopment, and the upgradation of old areas. Controlling transit phenomena will also help to control the emission and mitigation of greenhouse gases. This study will help in improving the urban environment and climatic condition of regions.

Currently, there is an increasing trend in the organizations towards examining the artificial intelligence and nonartificial intelligence for the innovation and success of the new product, as well as getting the intentions of the upcoming researchers. Thus, the purpose of the ongoing study is to examine the role of artificial and nonartificial intelligence in the new product success along with the moderating role of new product innovation in the manufacturing organizations of China. The quantitative methods have been followed by the study and gathered the responses from the respondents using questionnaires, and analysis has been conducted by using the smart-PLS. The results exposed that artificial intelligence and nonartificial intelligence have positive and significant nexus with the new product success. The outcomes also revealed that the new product innovation significantly moderated the links among the nonartificial intelligence and new product success, but it insignificantly moderated the links among the artificial intelligence and new product success in the manufacturing organizations of China. These findings have provided the guidelines to the manufacturing companies and their policies developing authorities that they should be developed and implement the suitable policies regarding the adoption of artificial intelligence and nonartificial intelligence that enhance the success of the new product, which ultimately enhances the success of the organization.

In this paper, an accurate electricity load and price forecasting model has been proposed, which consists of feature engineering and classification. To remove irrelevant features, Decision Tree (DT) and Recursive Feature Elimination (RFE) are used. Features are extracted through Mutual Information (MI) after removing uncertainty. In order to attain accurate electricity load and price forecasting, Enhanced Logistic Regression (ELR) classifier is proposed. Simulation results testify that accuracy of ELR is better than Logistic Regression (LR) and MultiLayer Percepton (MLP). ELR beats LR and MLP by 0.26% and 7.287% in load forecasting, whereas, it outperforms LR and MLP in price forecasting by 1.413% and 3.057%, respectively. Smart* dataset is used, which contains the data of residential sector of Western Massachusetts. Prediction performance is evaluated by using Mean Absolute Error (MAE), Mean Square Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE).

The municipal solid waste (MSW) is widely considered as a heterogeneous source of energy, with numerous characteristics varying depending on its geographical region or origin from where it is collected. The development of correlations for the prediction of the higher heating value (HHV) of MSW is a sustainable and cleaner way based on data of specific region from where MSW is obtained. In this research, a new approach reported for the development of correlations to predict the energy content of MSW accurately. The developed correlations lie within the all parameter affecting the HHV of MSW. The models presented can predict the HHV of MSW accurately (R2 > 0.8) compared to other models reported in the literature. However, model 13 developed on the basis of ultimate analysis demonstrated maximum accuracy (R2 = 0.919) among all 7 developed models. The aim of developing the prediction model for the HHV of different MSW samples was to reliably predict using proximate or ultimate analytical data to save experimentation costs and provide theoretical foundations for modelling MSW combustion, pyrolysis processes and thermal conversion for the energy security.

In this study, we elucidated the effect of sewage drain on groundwater contamination as including different contaminants, microbes, and pathogens, which deteriorating the groundwater by poor infiltration and seepage This is getting severer in developing countries like India, Bangladesh, and Pakistan, where unprocessed effluent is discharged into the water bodies This study was planned to elucidate the effect of sewage drain (based on distance 0–5, 5–10, 15–20, 20–25 m) from two different sewage drains to explain the different physiochemical, and biological parameters including total soluble solids (TSS), chloride, total dissolved solids (TDS), calcium, total hardness, magnesium, nitrate, chemical oxygen demand (COD), dissolved oxygen (D O ), and biological oxygen demand (BOD) Drainage channel number-1 results showed that E coli (positive), coliform count (22 75–48 66 /100 mL), and BOD (8–25 75 mgL−1) remained above the permissible limit of the World Health Organization (WHO) Besides, drainage channel number 2 results exposed that E coli (positive), coliform count (17 7–47 /100 mL), and BOD (6 25–21 5 mg/ L) was not within the permissible limit of WHO The presence of COVID-19 in the stool has been significantly reported in the literature The presence of stool in sewage drain leading to groundwater contamination can be an emerging threat to water pollution and could lead to the spread of COVID-19 This study helps to minimize this threat with the help of corporate social responsibility (CSR) Because organizational responsibility towards its society is one of the critical factors to contain numerous issues related to the society © 2020 The Author(s)