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Food waste is a significant issue in many developed and emerging countries and has significant environmental, social, and economic impacts. As China's urban population increases and restaurants expand, so does food wastage, resulting in many environmental and social issues. Therefore, this study investigates how the economic feasibility and environmental benefits of energy generation using biogas from food waste in Jiangsu Province can help achieve sustainable development goals and China's 14th Five-Year Plan. This study used Buswell's formulation, mathematical formulation, and economic metrics methods to analyze data from 2004 to 2020. The findings of the study are as follows: 1. The results show that 109.1 Mt. of food waste was produced in Jiangsu Province. 2. The total amount of electricity production potential from biogas yield during the 17 years is 16,126.0 GWh. 3. The study revealed that 3090.32 million tons (3.43% of the coal employed for energy production during the period) of coal combustion could be saved. 4. This prevented the release of 7262.26 million kilograms of carbon dioxide, 149.49 million kilograms of nitrous oxide, and 996.63 million kilograms of methane emissions. 5. The avoided coal consumption also helped reduce global warming by 76,727.33 kt of CO 2 equivalent. 6. The project is economically beneficial with a shorter net present value (NPV) for 1 year, a positive NPV (US$34.7 Million), an internal rate of return (23%), a return on investment (33.0%), and a lower levelized cost of energy (US$ 0.039/kWh). Policy recommendations are also discussed. • Electricity production potential from food waste in Jiangsu is analyzed. • The economic feasibility and environmental impacts were assessed. • Biogas derived from food waste has a high electricity generation potential. • Food waste to energy project is economically viable. • Food waste-to-energy projects can save coal combustion. [ABSTRACT FROM AUTHOR]

Driving range (mileage) limitations and long charging times associated with electric vehicle (EV) usage have necessitated the emergence of battery-swappable electric vehicles (BSEV) for sustainable mobility. In enhancing BSEV proliferation, a thorough comprehension of consumer adoption is needed. Understanding consumer adoption or hesitancy of BSEV is important for environmental sustainability. Consequently, this study explores the adoption intention of BSEVs by extending an amalgamated technology acceptance model (TAM) and the innovation resistance theory (IRT) with knowledge. Using 552 responses obtained through a survey, hypotheses were assessed using a structural equation model (SEM). Results from the study expressed that the conceptual framework explained 70.2 % of the overall variance, better than the individual TAM (40.7 %) and IRT (20.2 %), as well as the integrated model (60.7 %). Perceived ease-of-use, attitude, and perceived usefulness were positive in influencing BSEV. Value barrier and usage barrier were negatively significant in influencing BSEV adoption intention. However, the barrier of risk was insignificant in affecting the adoption intention of BSEVs. Tradition and image barriers were negative in influencing attitude. Perceived usefulness and attitude were discovered as mediators. This research provides policymakers and stakeholders with apt recommendations to promote acceptance and mitigate BSEV adoption hesitancy. • Investigates BSEV adoption using TAM, IRT, and knowledge constructs. • Responses were analyzed using structural equation modeling. • The structural model was responsible for 70.2 % of the total variance explained. • All constructs except risk barrier were significant in affecting BSEV adoption. • Attitude and perceived usefulness impacted BSEV adoption directly and indirectly. [ABSTRACT FROM AUTHOR]

Renewable energy-generated electricity can improve the reliability of the power grid and contribute positively to environmental sustainability. This study expanded the theory of planned behavior (TPB) with government involvement and awareness of benefits to assess Ghanaian's willingness to pay (WTP) for renewable green electricity (RGE) in Ghana. With questionnaire responses, hypothetical statements were evaluated using partial least square-structural equation modeling (PLS-SEM). The findings are: (1) The research revealed that government involvement impacted WTP for RGE in Ghana through attitude and subjective norm except perceived behavioral control. (2) The study found that awareness of benefits influenced WTP for RGE in Ghana via attitude and subjective norm except perceived behavioral control. This research showed that the explanatory ability of the current structural research model (R2 = 52.2%) was better than that of the original TPB model (R2 = 42.3%), affirming that the structural model better explained the WTP for renewable green electricity in Ghana. Ghanaians' WTP for RGE typically stimulates the execution of renewable energy objectives that will enhance sustainable development if the government and investors give information on the environment. Governments can also increase Ghanaians willingness to pay for RGE by educating on the importance of renewable green electricity in providing a sustainable energy source for everybody. [ABSTRACT FROM AUTHOR]

Recently, there has been rising global concern regarding the importance of achieving environmental sustainability. Consequently, researchers and policymakers have focused on identifying and evaluating the various elements that contribute to an individual's ecological footprint and environmental consequences. Therefore, this study provides an in-depth understanding of the roles of green technology, research and development (R&D), and environmental policies that help attain environmental sustainability in Ghana. The present study utilized both the nonlinear autoregressive distributed lag (NARDL) and autoregressive distributed lag (ARDL) techniques to evaluate the long and short-run relationships between explanatory variables from 1990 to 2022. The study compares the results of NARDL and ARDL techniques. The findings reveal that the NARDL (0.999) analysis had a greater impact on the ecological footprint in Ghana than the ARDL (0.996) analysis. Under the ARDL technique, green technology has a negative impact on ECF in both the short and long run, and R&D also decreases ecological footprint (ECF) in the long run. Environmental policies had a negative impact on ECF in both the short and long run. Based on the NARDL approach, an adverse change in GT had a negative impact (0.004) on the ECF in both the short and long run. In contrast, a negative change in R&D has a negative impact (0.007) on the ECF in the short run, and a positive change in R&D negatively affects the ecological footprint in the long run. Notably, a positive change in environmental policies had a significant negative impact (0.040) on the ECF in the short and long run. This study suggests that policymakers should encourage and support the adoption and application of green technology and the development of robust environmental policies, as these measures can significantly contribute to decreasing the ecological footprint and fostering environmental sustainability. • This research assesses factors for attaining environmental sustainability in Ghana. • This study utilizes the ARDL and NARDL methodologies. • Research and development decrease ecological footprint. • Green technology can contribute to reducing ecological footprint in the long run. • Environmental policies decrease ecological footprint in the short run. [ABSTRACT FROM AUTHOR]

The increasing demand for local anaerobic waste-to-energy projects triggered by citizens' environmental consciousness has forced communities, practitioners, and academicians worldwide to prioritize this subject. This research extends the theory of planned behavior (TPB) model with egoistic value. This study assessed residents' willingness to accept energy from food waste via anaerobic digestion (AD) projects. This study compares the new research framework with the original TPB framework. Using 408 questionnaires from Chinese residents in Jiangsu Province, hypothetical statements were assessed using a covariance-based structural equation model (CB-SEM). Egoistic values influenced all TPB constructs. The study found that TPB constructs mediated the association between egoistic value and residents' willingness to accept energy from food waste through AD projects. The findings suggest that the actual research framework can better explain outcomes than the original TPB model. This shows that the actual framework is more effective in understanding residents' willingness to accept energy from food waste through AD projects. Policymakers and investors should communicate the health benefits of energy from food waste via anaerobic digestion schemes to citizens. Also, the policymakers or experts should focus on egoistic values or the health benefits of the citizens before they hurry to uptake the projects. • The study assessed residents' willingness to accept energy from local anaerobic digestion projects. • The partial least square-structural equation modeling (PLS-SEM) was used for the study. • The explanatory ability of the current research model is better than the original TPB model. • Egoistic values influenced TPB towards citizens' willingness to accept energy from the project. • Egoistic values positively influence citizens' willingness to pay for energy from the project. [ABSTRACT FROM AUTHOR]

South Asian economies have had substantial development in recent decades, but policymakers are concerned about long-term output stability. Considering this, institutional quality and green technical innovation are recognized as effective mechanisms to mitigate CO 2 emissions and promote sustainable growth as guided in core of COP 26. Consequently, the goal of this study is to investigate the long-run effect of institutional quality, green technology innovation, renewable energy, trade openness, population and economic growth on CO 2 emissions from 1995 to 2020 in selected South Asian countries. Due to the possibility of residual cross-sectional reliance and heterogeneity, the study examined the relationship between the variables using second-generation panel techniques. The empirical findings show that green technological innovation and renewable energy reduce CO 2 emissions by 0.084% and 0.054% respectively. Institutional quality, population growth, trade openness and economic growth degrade the environment 0.215%, 0.300%, 0.195% and 0.182% respectively. Dumitrescu and Hurlin (D-H) found a bidirectional causality association between green technological innovation, renewable energy consumption, trade openness, population size, economic growth, and CO 2 emissions. This study offers policy recommendations for achieving a low-carbon economy, increasing the use of renewable energy, improving the institutions, making more investments in green technology, and ensuring environmental sustainability in South Asian economies. • Investigate the relationship between institutional quality, green technological innova-tion and CO 2 emissions. • A second-generation panel technique is used in this study. • Green technological innovation and renewable energy mitigate CO 2 emissions. • Institutional quality and economic growth degrade the environment. • Trade openness and population growth significantly increase CO 2 emissions. • This study also contributes to the body of literature by considering the COP 26 resolu-tions. [ABSTRACT FROM AUTHOR]

Recycling has emerged as a critical global environmental and economic issue. Recycling helps achieve primary sustainability goals, including better waste management and climate change mitigation. This study tackles the research gap on how place identity and natural bonding affect recycling decision-making. The research investigates citizens' recycling intention by incorporating place identity and natural bonding into an extended norm activation model (NAM). The study proposes that openness to change, awareness of consequences, environmental concern, personal norms, and attitudes are responsible for place identity and natural bonding's indirect effect on citizens' recycling intention. Based on 815 survey responses, hypothetical claims were examined using partial least square structural equation modeling (PLS-SEM). The results revealed that place identity and natural bonding indirectly affect citizens' recycling intention through personal norms, awareness of consequences, and attitudes. Place identity also indirectly affects citizens' recycling intention, mediated by openness to change and environmental concern. The expanded NAM helps comprehend place identity and natural bonding's role in citizens' recycling intention. Theoretical and practical implications are discussed. [ABSTRACT FROM AUTHOR]

Battery swap technology (BST) is an innovative means of mitigating range satisfaction in using electric vehicles (EVs), advancing decarbonized vehicular transport, and enhancing environmental sustainability. The readily replaceable dead battery pack is swapped with an already charged one at a Battery Swapping Station (BSS) rather than connecting to a charger. Research is yet to pay attention to what motivates and influences BST adoption. There is a need to understand users' acceptance of the battery swap technology as it is fundamental to carbon emission reduction, sustainable transport, and EV proliferation. The research examines the psychological variables that affect battery swap technology adoption. The study extends the technology acceptance model (TAM) with knowledge, risk and safety concerns, and convenience. Hypothetical assertions were analyzed using partial least square structural equation modeling (PLS-SEM) based on 405 survey responses. The results revealed that attitude, convenience, perceived usefulness, and knowledge positively influenced the intention to adopt BST for EVs. Risk and safety concerns adversely affected intention significantly. Risk and safety concerns, convenience, and knowledge were mediated by perceived usefulness and attitude. The research findings offer practical policy recommendations to policymakers and industry players to enhance the popularity, maximum usage, expansion, and growth of battery swap technology. • BST adoption intention was assessed using technology acceptance model. • PLS-SEM was used in testing hypotheses. • All constructs significantly influenced the adoption intention of BST. • Suggestions are made to industry players to ensure maximum acceptance. [ABSTRACT FROM AUTHOR]

Growing industry, urbanization, and population in developing nations like Ghana is increasing waste generation. Municipal solid waste (MSW) mishandling has serious environmental, public health, and socio-economic implications. This study analyzed the direct and indirect influence on citizens' intention to invest in MSW to energy projects in Ghana and expanded the norm activation model (NAM) and theory of planned behavior (TPB) with perceived value and health consciousness. With 412 questionnaire responses, hypothetical statements were evaluated using partial least square-structural equation modeling (PLS-SEM). The findings are: (1) The study found that awareness of consequences indirectly influenced citizens' intention to invest in MSW to energy projects through attitude, personal norms, perceived value, perceived behavioral control, subjective norm, and health consciousness. (2) This study indicated that the explanatory ability of the current structural research model (R2 = 40.1%) is better than that of the extended TPB model (R2 = 38.0%) and NAM (R2 = 28.4%) with perceived value and health consciousness, and the structural model can better explain their intention to invest. Additionally, several recommendations are suggested for investing in MSW to energy projects in Ghana. This study has the potential to assist academics, researchers, government officials, and investors engaged in MSW to energy projects in making knowledgeable decisions. • Citizens' intention to invest in MSW to energy projects was assessed in Ghana. • The study assessed the explanatory power of TPB and NAM using PLS-SEM. • All the hypothesis influenced citizens' intention to invest in the projects. • The study compare the current research model, NAM, and the TPB model. • The recommendations for citizens' intention to invest in the projects are detailed. [ABSTRACT FROM AUTHOR]

There are growing concerns worldwide about the release of harmful gases from fossil-fueled vehicles into the environment, motivating the emergence of electric vehicles (EVs). However, consumers are hesitant to adopt EVs as they are scared of the long charging times and being stranded midway through a journey. Addressing this concern is the introduction of Battery swap technology (BST). BST assures an uninterrupted driving range in EVs. In this study, the adoption intention of BST for EVs is explored as BST′ success depends on consumer acceptance to guarantee pro-environmental consumption and pollution reduction. The current study extends the theory of planned behavior (TPB) with perceived benefits and knowledge. 407 responses from China's Beijing-Tianjin-Hebei region were used in this investigation. Findings revealed that the extended TPB improved the explanatory power from 39.5% to 45.7%. Attitude, perceived behavior control (PBC), subjective norms, knowledge, and perceived benefit directly influenced adoption intention. Subjective norms influenced PBC and attitude. PBC was insignificant in impacting attitude towards BST. Knowledge influenced attitude and perceived benefit. Attitude mediated Subjective norms and knowledge. Policy implications are enumerated to enhance BST acceptance and proliferation. • Battery swap technology adoption intent was assessed by extending the TPB model. • Hypothetical statements were assessed using PLS-structural equation modeling. • All constructs except PBC influenced the adoption intention of battery swap. • Subjective norms and knowledge were mediated by attitude towards intention. • Implications for total acceptance and proliferation of BST are enumerated. [ABSTRACT FROM AUTHOR]

Range satisfaction and "refueling" of battery electric vehicles (EVs) have become a major challenge hampering consumer acceptance. Battery Swap Technology (BST) is a trusted option in mitigating these obstacles. Available studies are yet to explore the psychological determinants of consumers' BST adoption intention. In addressing this gap, this study used a framework encompassing the technology acceptance model (TAM), theory of planned behavior (TPB), perceived risk, and knowledge in investigating consumers' adoption intention of BST using structural equation modeling. With responses from Chinese consumers in the Jiangsu province (n = 405), the results revealed that the structural model had a better fit and explanatory power (R2 = 0.58). Perceived usefulness, attitude, subjective norm, and knowledge positively influenced adoption intention towards battery swap technology. Perceived risk was negatively linked to attitude, perceived usefulness, and adoption intention, whiles perceived behavior control (PBC) was insignificant towards BST adoption intention. Also, knowledge fully mediated PBC and adoption intention. The findings confirmed that consumers' adoption intention differed by gender, family size, and residency type. The study provides meaningful policy implications to stakeholders to enhance adoption and enriches the understanding of consumers' adoption intentions in the context of battery swap technology. • Chinese' residents adoption intention of battery swap technology was investigated • Assessed the explanatory power of TPB, TAM, and structural model • Key constructs influencing BST adoption intention were assessed • Mediating effects of knowledge was investigated • ANOVA analysis of respondents was explored [ABSTRACT FROM AUTHOR]

In the wake of global climate change and environmental degradation, an urgent action on a global scale is required to decarbonize the energy sector. From fossil fuel to renewables, energy efficiency and technological advancement are the most important factors responsible for an effective energy transformation. The present study investigates the magnitude of mitigating role of energy efficiency (EE), renewable energy (REC), technological advancement (ENVTECH) on Ecological footprint (ECFP) for the sixteen high-income economies of the Organization of Economic Cooperation and Development (OECD) over the period of 1990–2020 by employing various econometric estimations such as panel co-integration, Augmented Mean Group, Common Correlated Mean Group, Random effect, Fixed effect and Mean Group estimation techniques. Moreover, the role of gross domestic product (GDPP) is also observed as a proxy for economic growth. The empirical findings reveal that EE, REC, and ENVTECH improve environmental quality, whereas GDPP is a carrier of environmental degradation in the selected economies. Interestingly, energy efficiency holds the leading position among all observed factors to decarbonize and effectually transform the energy sector to greener production and consumption in the presence of environmentally friendly advancements in technology. The robustness tests results also support the findings of our basic empirical output. Furthermore, a unidirectional causality running from REC, GDPP, and ENVTECH to ECFP, whereas, a bi-directional causality between EE and ECFP is also validated. Any change in these factors will granger cause ECFP. The findings are of significant consequences as the selected OECD economies are expected to gain from energy transition to renewables enabled by energy efficiency and enhancement of environment-friendly technology in the near future. • The role of energy efficiency is evaluated for ecological footprints. • Updated data from 1990 to 2020 is employed via panel methods. • Energy efficiency and renewable energy curb emissions. • Environmental technology also promotes less emissions. • Transition to renewable energy with efficiency is encourage. [ABSTRACT FROM AUTHOR]

• Sustainability evaluation for a circular economic eco-city is conducted by applying emergy analysis approach. • Rizhao suffered a low sustainability with high reliance on local non-renewable resources. • Rizhao's sustainability shows an increasing trend in recent years under the effect of circular economy. • Suggestions based on local realities are proposed for overall sustainability. The construction of the circular economy eco-city (CEE) is the most effective way to solve the problem of sustainable urban development. To promote its development, the evaluation and tracking of its sustainability have become significant in academic exploration. However, few efforts have been made in this regard. Thus, this paper aims to fill this gap by choosing Rizhao city, a coastal CEE, as a case study and employing an emergy-based method to assess its sustainability from 2005 to 2017. The study results show that the socio-economic development depends on the utilization of local non-renewable resources. Moreover, the self-support ratio was found to be above 94 %, which, in turn, led to an increase in the environmental loading ratio. However, due to a rise in resource recycle ratio, the emergy sustainability index and sustainable development index first showed a decreasing trend and then an increasing one. Consequently, the performance of the circular economy has improved, especially in terms of resolving the dilemma between a superior environment and a backward economy. Nevertheless, the coordinated development within the system was not adequate. Therefore, further policy recommendations have been made to improve the overall sustainability of the circular economy in Rizhao city. [ABSTRACT FROM AUTHOR]

Sustainable development is essentially a practice way. A great number of the National Sustainable Development pilot Zones (NSDPZs) has been rapidly developed in recent years in China, which is a practice to explore the road of sustainable development. In order to regulate and promote their better development, suitable comprehensive measurement of sustainability is essential. However, few efforts have been made in this regard. This paper aims to fill such a gap by using grey relational analysis to evaluate the development performances, principal component analysis to discuss the influencing factors of 13 pilot zones in Shandong Province from 2009 to 2015. The results showed that the development performances of pilot zones had generally improved, while there were obvious differences between subsystems after years of development. The spatial variations revealed a gradually decreasing trend from east to west as well as from north to south. The development performances of pilot zones were subject to the influence of various factors such as technology, efficiency, and industry. According to the leading factors and their development performances, the 13 pilot zones could be divided into six different types. The difference of dominant influencing factors among pilot zones caused to the difference of development performances. The technological innovation was the endogenous driving force in stimulating high-quality development of pilot zones. These results would not only provide theoretical reference for the establishment of efficient management mechanism of pilot zones in Shandong Province, but also provide practical reference for the effective implementation of the 2030 Sustainable Development Agenda in China. [ABSTRACT FROM AUTHOR]

• We examine a platform retailer's selling strategy with customer return. • A supplier may sell through both the platform retailer and its direct channel. • We identify the platform retailer's optimal selling strategy (as marketplace or reseller). • Choosing reselling strategy if selling efficiencies are significantly different or close. • We identify conditions when an MBG should be offered in supplier's direct channel. This paper examines the selling strategy of an internet platform retailer in the presence of customer returns. A supplier may sell its product through the platform retailer and also through its own (direct) channel. The platform retailer may either be a reseller of the supplier's product or a marketplace (charging a commission to provide platform services to the supplier, who sells the product through the platform). When the platform retailer is a reseller it offers a money-back guarantee (MBG) returns policy; when it is a marketplace, it requires that the supplier offer the MBG on sales through the marketplace. We identify the conditions under which the supplier should also offer an MBG in the direct channel. We identify the platform retailer's optimal selling strategy (as marketplace or reseller) and the associated conditions. We show that the platform retailer should choose a reselling strategy if the selling efficiencies in both channels are either significantly different or sufficiently close, and otherwise the platform retailer should choose a marketplace strategy. The regions that achieve win–win for both supply chain members are identified. [ABSTRACT FROM AUTHOR]