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Litter is a global issue that pollutes water, air, and land, and has esthetic and environmental repercussions. Therefore, this study utilized the value -belief -norm (VBN) theory to analyze residents' preventing littering behavior in Ghana. This study employed a random sampling approach and used an online survey to gather quantitative data from 511 participants. Partial least squares structural equation modeling (PLS-SEM) was used to analyze the data. The results show that the "biospheric value," "altruistic value," and "egoistic value" had substantial beneficial effects on the new environmental paradigm. The findings revealed that the new environmental paradigm increased awareness of consequences, which strongly enabled the ascription of responsibility to address environmental concerns. Personal norms influenced residents' preventing littering behavior. The study also discovered that the ascription of responsibility and new environmental paradigms promote residents' preventing littering behavior indirectly through personal norms and awareness of consequences. The study found that awareness of consequences moderates the association between personal norms and residents' preventing littering behavior. These findings provide new insights for litter prevention policymakers. [ABSTRACT FROM AUTHOR]

The quality of the environment has become one of the primary objectives of South Asian governments. The majority of South Asian nations are susceptible to the negative effects of climate change, so it is crucial to identify factors that can contribute to environmental sustainability in the region. As a result of globalization, South Asian economies have attracted the attention of developed economies due to their abundance of mineral resources. This study fills a gap in the body of literature by analyzing the impact of economic globalization, financial development, natural resource availability, and disaggregated energy consumption on the environmental sustainability of South Asian nations from 1990 to 2020, taking into account economic growth, trade openness, and urbanization. This study employs a cross-sectional autoregressive distributed lags (CS-ARDL) estimator for short-run and long-run estimation, which accounts for slope parameter variability and country-specific dependencies. The results show that 1% increase in natural resource abundance and economic globalization improve the environmental quality in South Asian nations by 1.987% and 0.158% respectively. Furthermore, increasing the amount of renewable energy in total energy consumption minimizes CO2 emissions by 0.295% for every 1% change in renewable energy consumption. By contrast, 1% change in trade openness, financial development, urbanization, non-renewable energy consumption, and economic growth have a negative impact on the environment by 0.178%, 0.182%, 1.131%, 0.352% and 0.854% respectively. There is a unidirectional connection between natural resources and economic globalization that creates trade openness. For sustainable development goals, this study delivers new practical evidence and policy suggestions. [ABSTRACT FROM AUTHOR]

The study of ecological footprint (ECF) and its antecedents has been a popular point of deliberation among experts in recent times. However, a West African perspective is scarce. Therefore, this study analyzes the impact of tourism, renewable energy, and biocapacity in fostering or constraining the impact of ecological footprint (ECF) in West African countries. The study adopted the Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), Pooled Mean Group (PMG) estimation, and Granger causality test for its analysis over 1995–2016. The study found that human capital, natural resources rents, tourism, and real income positively correlates with ECF. Also, biocapacity increases the ecological footprints of the region. In the short-run, the study found a unidirectional causality from ecological footprints to renewable energy consumption, human capital, urbanization but a bidirectional relationship with biocapacity and real income. The study also found a bidirectional causality from ecological footprints to all the variables in the long-run. The study recommends that countries undertake pragmatic policies and actions to prevent rising ECF per capita by minimizing overexploitation of indigenous natural resources and eco-services. [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]

This study explored the dynamic nexus between trade openness, non-renewable, renewable-energy consumption, urbanization, economic growth, and ecological footprint considering the Sustainable Development Goals (SDGs) 7 and 13 of ensuring access to reliable, renewable, and clean energy technology, as well as climate action, by employing a second-generation panel data technique for G11 economies from 1991 to 2018. The study used second-generation panel unit root tests, panel cointegration techniques, and the augmented mean group (AMG) approach to estimate the long-run magnitude of the parameters for this purpose. The empirical findings show that trade openness, economic growth, and urbanization all considerably increase the environmental deficit, but renewable energy use minimizes total environmental degradation in the long run. Furthermore, the Dumitrescu and Hurlin (D-H) causality test discovered that economic growth, non-renewable consumption, urbanization, and the EFP have long-term bidirectional correlation, whereas GDP, renewable energy consumption, and trade openness have long-term unidirectional causality. As a result, the industrial infrastructure of the G11 nations must be modernized, and renewable energy must be enhanced further. [ABSTRACT FROM AUTHOR]

Global health, as well as worldwide development regimes, was seriously threatened by the COVID-19 pandemic and Delta variant outbreaks. In addition to pledging to adapt to and mitigate climate change, experts, economists, and policymakers expressed their determination to do so. Green growth and sustainable development have become the focus of policymakers and governments. The progress toward green economic efficiency (GEE), which will benefit the economy, society, and environment, continues. In terms of green growth and development, implementing environmental regulations and policies has been one of the most challenging aspects of the process. China, the world's second-largest economy, has begun its journey to GEE. Nonetheless, the green economy faces many challenges. The objective of the study is to use AHP analysis to analyze environmental regulation and GEE in China. Accordingly, the study identified three alternative approaches to achieve GEE by analyzing four criteria and ten sub-criteria in the context of environmental regulations in China. The analytical hierarchy process (AHP) has been used to rank criteria, sub-criteria, and alternative approaches. According to the model, China's best path to GEE is through resource efficiency and green purchasing strategies. This article offers an insightful assessment of sustainable development in the Chinese economy. [ABSTRACT FROM AUTHOR]

Public electric bus (PEB) usage remains critical in reducing carbon emissions, traffic congestion, energy consumption, resource exhaustion, and environmental pollution. PEB usage revolves around consumer acceptance, and assessing the psychological factors accounting for using PEBs is essential in mitigating these challenges for a sustainable environment. The study extends the reasoned action theory (TRA) with environmental awareness, convenience, and personal norms in investigating residents' intention to use electric buses in Nanjing, China. 405 responses were gathered through an online survey and evaluated using Structural Equation Modeling (SEM). Statistical analysis showed that the structural model (66.4%) explained public electric bus use better than the original TRA model (20.7%). Attitude, subjective norms, personal norms, environmental awareness, and convenience directly influenced the intention to use PEBs. Personal norms related to attitude positively. Environmental awareness related to personal norms in PEB use. Subjective norms partially mediated the impact of personal norms on the intention to use PEBs. Convenience moderated the interaction between personal norms and intention to use PEBs. Respondents differed in income level, educational level, and employment but not gender in their inclinations to use PEBs. The current study recommends potent policy implications to enhance and ensure the maximum use of PEBs. • TRA is extended to investigate public electric bus (PEB) usage intention. • All constructs influenced the intention to use PEBs directly. • Attitude mediated environmental awareness towards PEB usage intention. • Convenience moderated personal norms and intention to use PEBs. • ANOVA analysis of respondents is examined. [ABSTRACT FROM AUTHOR]

In the past two years, 2020-2022, the developing construction industry has been a huge issue according to the negative effect of Covid-19 with the increasing pandemic situation in cities and areas. In Covid-19 pandemic situation, the cement manufacturing industry has been crucial and needed more scrutiny. As cement is the second significant component after water in concrete and construction industry. Meanwhile, locating a cement plant in a special area of the city is challenging and affecting more by local communities and other involved environmental factors. The location selection decisions need to grow by environmental, economic, technical and social attributes. This study aims to present the site suitability decisions through a case study of locating a new manufacturing plant for cement production in Tehran surrounding, Iran. In this process, some required technical and tactical criteria are deserved for evaluating and suitability of the plant through decision-makers for cement manufacturing. All the feasible industrial alternative locations were evaluated under various criteria and regarding the Covid-19 pandemic's negative impact to identify the most appropriate location for the cement industry. The authors proposed two Multi-Criteria Decision Attributes (MCDA) methods of MacBeth and COmplex PRoportional ASsessment (COPRAS) to evaluate and select the most suitable location for site suitability of the cement plant in this problem. Though the MacBeth method does not need to calculate weights of the Geographical Information System (GIS) criteria, the COPRAS method determined and used BWM (Best-Worst Method) as the weighing method. In sum, the comparison of the two methods was obtained according to the given results and ranks of volunteer cement suppliers for site suitability of the cement plant. [ABSTRACT FROM AUTHOR]

In this article, an instance-based naive Bayes (INB) method is proposed to interpret out-of-control signals. By training one for one classifier, this method considers the similar features between test instance and training instances. For three benchmark examples with small number of variables, the experimental results show that INB outperforms all techniques in overall average performance; in cases of more than two variables, INB performs better in most scenarios. For two examples with large number of variables, the experimental results show that INB can be applied to practical problems. This research indicates that INB is very encouraging for interpreting the out-of-control signals in multivariate statistical process control. [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]

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]

In this paper, the shortcoming of multi-objective mixed-model assembly line scheduling problem (MMSP) is pointed out firstly, and then grey relational analysis (GRA) is applied to address multi-objective MMSP. The methodology, solving steps and an instance are given. The result shows that GRA is a scientific and practical method of multi-objective decision of MMSP. [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]

Purpose: The purpose of this study is to address the global COVID-19 pandemic related to its sustainability, such as environmental, economic and social concerns. The short study also examined how various innovative approaches can help promote sustainable production. Design/methodology/approach: The methodology examines hypothetical scenarios of the current pandemic and tries to describe the quality of evidence to facilitate careful, critical engagement by readers. Secondary data is used to identify sustainability challenges, such as environmental, social and economic viability challenges. The information in this report was gathered from numerous media outlets, research agencies, policy papers, newspapers and other sources to gain a better knowledge of the issue. Findings: As a result, most industry executives and policymakers are looking for appropriate strategies and policies to improve their practices and meet consumer demand. The outcomes explore that the COVID-19 pandemic is a central factor in changes in people's behavior, reflecting sustainability such as environmental, social and economic responsibility. The COVID-19 outbreak, surprisingly, had a bigger effect on sustainable consumption, accompanied by environmental sustainability, and, to a lesser extent, social and economic viability. Research limitations/implications: Limited secondary evidence and data could not scrutinize the study's actual problem statements. Hence, it is recommended that the gap in research be fulfilled by conducting a primary survey among various groups of economists, environmentalists and industrialists using the cluster sampling technique by validating the questionnaire of the total sustainable production system. Proposing frameworks for improving the resilience of production and a systematic possible upgraded manufacturing system by using the Industry 4.0 technology during operational processes could advance market demand. Practical implications: The COVID-19 scenario has compelled manufacturing firms to put their production systems on hold for an extended period while they seek long-term solutions to assure simple delivery and cooperation from both business and consumer standpoints. Various aspects of supply and demand are discussed in the referendum, as well as production and consumption challenges during the COVID-19 era. There is a need to restore the production system and find the right source of raw materials. This work focuses on commodity inventory management systems due to mass production, but due to pandemics, it is not in demand and vice versa. The researcher made comprehensible remarks on the use of digitization in the pandemic, which improves social distancing and social well-being and promotes the production system as well. Besides, manufacturing plants should switch to digital manufacturing to reduce the number of workplaces and hence the risk of an outbreak. Therefore, a better supply chain network is needed to supply more manufacturing units. Social implications: There is a bright side of coronavirus that the public health crisis raised worldwide has brought many opportunities for governments and society to make eternal reforms in the public health sector door. During restricted movements for fulfilling market demand, the Industry 4.0 technologies for automation, mechanization and digitalization can help significantly advance a company. This technological advancement and computer digitization for the perspective people may improve the environment, economic and social sustainability also increase social media adoption, which can be crucial for agri-businesses to evaluate customers' behavior and consumption trends. Originality/value: The paper also instructed to identify critical success factors, barriers and drivers for dealing with the pandemic situation and to develop a strategic policy framework to improve production and process flexibility through the remarkable introduction of digital manufacturing. Before it is too late to stop the spread, producers and consumers must grasp the limits to which suppliers might drive nature. [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]

The Taguchi method (TM) and TM-combined methods [e.g., TM fuzzy method (TM-Fuzzy), TM data envelopment analysis (TM-DEA), TM coupled with grey relational analysis (TM-GRA), etc.] have been proven to be effective to achieve robust design performance. However, the efficient strategy to identify the significant design parameters, and the link between different quality characteristics and design parameters have not been fully studied. To fill the gaps, a combined method, i.e., TM–response surface methodology (RSM)–desirability function (DF), (TM–RSM–DF), was proposed. The significance of the TM–RSM–DF method is able to address the relationship between design parameters and quality characteristics, which facilitated to sort out the most significant design parameters precisely; besides, it also provided a robust strategy to optimize the multiple quality characteristics of the precision product. A design process of a precision amplification (PA) was taken as an example to prove the effectiveness of the TM–RSM–DF. The results showed that the TM–RSM–DF method improved the estimation performance of displacement amplification ratio (DAR) and natural frequency (NF) by 6.148% and 0.537% compared with the initial desired design. Besides, compared with others, the TM–RSM–DF method reduced the stress amount about 16% and had the lowest DAR and NF errors of 2.882% and 1.305%, respectively. Overall, the proposed TM–RSM–DF method outperformed the TM-DEA, TM-GRA, and TM-Fuzzy in the robustness of the PA design. [ABSTRACT FROM AUTHOR]

The staggering rise in global temperature and abrupt change of climate are the responses of nature alerting humanity to limit the emissions of hazardous gases and adopt environmentally-benign life style. The present study explores empirically whether any changes in environmental policy stringency (EPSI), political risk (PR), and the interaction term of EPSI*PR result in any alteration of consumption-based carbon emissions (CBCE) of the 24 advanced OECD economies over the period of 1990–2020. Prior to the empirical estimations, various diagnostic tests are employed. The empirical techniques include, panel cointegration check, Cross-sectional Augmented Autoregressive Distributed Lags (CS-ARDL), and Dumitrescu & Hurlin panel causality test. The findings confirm that imports, gross domestic product, and stringency of environment policies activate CBCE in short-run. Whereas, a unit improvement in political risk and its interaction with environmental policy stringency give rise to 0.231 MtCO 2 of CBCE in long run. Interestingly, the squared term of environmental policy stringency effectively tackles such emissions. Based on the findings, we conclude that the present environment related policies of OECD member states does not effectively limit CBCE. In order to achieve genuine emissions reduction goals, the selected nations should restructure their environment related policies by prioritizing increments in environmental policy stringency along with minimizing the risks involved in the political system. • The present environmental policies of OECD nations are not targeting consumption-based emissions. • The Lower the political risk, the minor the consumption-based carbon emissions. • Lower political risk along with efficient environmental policies curb such emissions. • Interestingly, augmenting the current environmental policies tackles the emissions. [ABSTRACT FROM AUTHOR]