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Companies affected by California’s cap-and-trade legislation are allotted certain credits for production that can be used or sold and can purchase additional credits from the state, which become a revenue source to be used for activities that reduce carbon emissions. The purpose of this paper is to investigate who ultimately pays for this program, its effectiveness in reducing carbon emissions in accordance with established goals, and the related effectiveness to advance social, economic, and environmental equity.

The methodology used for this research is secondary data analysis, triangulating three sources: California’s Climate Change Investment Reports, 2019-2021; repositories maintained by the California High-Speed Rail Authority and the California Air Resources Board; and a review of the literature and websites from other professional sources which addressed, directly and indirectly, the topics and questions explored in the study.

Key findings include evidence of enhancing social and environmental equity but ineffectiveness in reducing carbon emissions in accordance with state goals. Furthermore, the program displays evidence of economic inequity as it demonstrates characteristics of regressive taxation and an inability of low-income persons to acquire electric vehicles due to high costs.

The research effort is unique in that no other academic efforts were located which attempt to examine the cap-and-trade program’s effectiveness in attaining its goals.

Environmental taxes have been in place for many years to reduce environmental damage and pay more attention to the environment. However, some of the adverse socio-economic impacts that may result from such taxes and the many challenges facing developing countries have necessitated policy reform. Therefore, identifying and prioritizing the factors related to environmental tax reform (ETR) is necessary to help governments and environmental protection agencies (EPAs) focus on this prioritizing to develop and improve this process. Awareness of the benefits of ETR encourages governments to use this policy to reduce adverse environmental impacts and contribute to economic growth.

The primary purpose of this work is to prioritize and taxonomy the factors related to ETR using the Fuzzy Analytic Hierarchy Process (FAHP) approach. In the first stage, 25 factors were extracted from the available literature. These factors were divided into five categories for more accessible review. In the second stage, the FAHP as a Multiple-Criteria Decision-Making (MCDM) Technique was used to prioritize and develop the taxonomy of identified factors and the categories of these factors.

The results show that reducing carbon emissions (DF4) is the essential prioritization factor that governments and environmental organizations can achieve if the ETR is implemented. Following that, reducing greenhouse gas emissions (DF1), double benefit (EcF7) and increase sustainability reports (EnF4) can be achieved by implementing ETR.

This study is geographically limited to Iran. In terms of the study population, this study is limited to 25 academic, tax and public policy experts. Moreover, in this study, FAHP is the only approach used. For further research, the results of this study can be compared with that of other multi-criteria techniques like FAHP, fuzzy TOPSIS or BWM.

Ratings of factors related to ETR can guide and help governments identify important factors that affect environmental tax reform, which can, in addition to controlling ecological pollution will, increase the economic benefits of governments.

This study is the first to identify factors related to environmental tax reform and to develop an MCDM technique for prioritizing these factors and finding important ones.

This research paper aims to examine the asymmetric impact of income and price on household consumption of kerosene in Cameroon.

The methodological approach consists of testing for stationarity using the augmented Dickey–Fuller and Andrews and Zivot tests, determining cointegration using nonlinear autoregressive distributed lag (NARDL) test approach and finally examining asymmetry using the Wald test.

Results of the stationarity tests reveal that variables are all integrated of order less than two I(2). The NARDL approach indicates that the (positive and negative) income shock and the positive price boom negatively influence consumption in the long- and short-run. The same is true for the negative price shock, but the latter remains insignificant. Furthermore, the Wald test carried out in the study confirms that the cumulative effects of the positive and negative income and price shocks are asymmetric.

The increase in the price of kerosene due to the lifting of subsidies has led to a decrease in household consumption and an unfortunate increase in the loss of tree cover in Cameroon. According to the results, this phenomenon will persist even if the price is reduced. Actions aimed at reducing its production at the expense of liquefied petroleum gas, electricity and renewable energy should be encouraged to limit the loss of vegetation cover. Thus, this study could contribute to solving the problem of deforestation and desertification in Cameroon.

This research explores mitigating carbon emissions and integrating sustainability in e-commerce logistics by optimizing the multi-depot pollution routing problem with time windows (MDPRPTW). A proposed model contrasts non-collaborative and collaborative decision-making for order assignment among logistics service providers (LSPs), incorporating low-carbon considerations.

The model is substantiated using improved adaptive large neighborhood search (IALNS), tabu search (TS) and oriented ant colony algorithm (OACA) within the context of e-commerce logistics. For model validation, a normal distribution is employed to generate random demand and inputs, derived from the location and requirements files of LSPs.

This research validates the efficacy of e-commerce logistics optimization and IALNS, TS and OACA algorithms, especially when demand follows a normal distribution. It establishes that cooperation among LSPs can substantially reduce carbon emissions and costs, emphasizing the importance of integrating sustainability in e-commerce logistics optimization.

This paper proposes a meta-heuristic algorithm to solve the NP-hard problem. Methodologies such as reinforcement learning can be investigated in future work.

This research can help logistics managers understand the status of sustainable and cost-effective logistics operations and provide a basis for optimal decision-making.

This paper describes the complexity of the MDPRPTW model, which addresses both carbon emissions and cost reduction. Detailed information about the algorithm, methodology and computational studies is investigated. The research problem encompasses various practical aspects related to routing optimization in e-commerce logistics, aiming for sustainable development.

Online food delivery service has evolved swiftly and stretched the bounds of the catering business. In the gig economy, being a food delivery rider draws employees with the promise of flexibility and independence. To this end, the purpose of this paper is to explore the main themes shared in online reviews by food delivery riders and which of these themes are linked to positive and negative ratings.

The authors used 729 employee reviews posted on the Glassdoor website. In addition, they used content analysis to examine reviews of Uber Eats online food ordering company shared by food delivery riders on an online platform.

The results of this study include seven main themes: “earning,” “customers,” “orders,” “tips,” “car,” “flexible schedule” and “app” (navigation). Positive concepts are associated with “earning,” “orders,” “tips” and “flexible schedule.” Negative themes are linked to the “app” (navigation), “car” and “customers.”

Management should consider online reviews as employees’ opinions and voices. Specifically, management should provide financial support to employees for car maintenance, offer insurance for income stability and arrange training programs to enable them to use several tip-enhancing behaviors.

No research has been conducted using online reviews from an employment search engine to investigate employees’ experiences of online food delivery. To the best of the authors’ knowledge, this study is one of the first attempts using user-generated content from an employment search engine to explore employees’ experiences.

This paper aims to: first, it studies expert opinions about the future of clean, decentralized energy technology in Australia; second, develop an interpretive and participatory foresighting methodology for a forthcoming study.

This paper reports a forecasting study about the future of clean energy. Driven mostly by economics and changing carbon policies, the energy sector is currently moving from fossil fuels to a variety of cleaner technologies. Energy experts have several incommensurate interpretations of how this change will happen. This paper describes the first phase of an ongoing study that foresight clean energy futures in Australia. By building on a participatory method in a scientific expert community, it describes the path from technological presumptions into four parallel yet interconnected scenarios. The paper also explores the social drivers behind these scenarios.

First, energy experts in Australia classify futures into four main scenarios: abundant, where energy will be mostly produced by solar cells; traded, where the future of energy lies in virtual power plants and microgrids; circular, which targets Australia’s NetZero goals through biomaterials, carbon capture and new powerful; secure, which secures the country’s energy supply through coal and nuclear energy. Second, they locate policy as the most important form of wildcards. The policy is multilayered from local to US politics and falls outside the scope of forecasting.

The most important limitations of the study are: first, its reliance on scientific and technological experts, which guarantees its scientific validity but may underrepresent the social drivers of energy; second, this study is a methodological pilot of a larger study that will target industrial, commercial and local drivers; third, its focus on Australia, where politics, the size of the country and climate shape the uptake of clean energy in specific ways, most notably in the case of rapid uptake of solar energy.

The main practical implications of the paper are its broad focus on clean energy futures and its participatory foresighting approach, which can be repeated in other studies.

The main social implication of the study is that it clearly shows that a technological perspective is necessary but not sufficient in understanding the future of clean energy. The paper also shows that local drivers importantly mold the future and should be taken into account in future studies and policy.

This paper makes two contributions. First, it organizes several technologies into four scenarios that clarify Australia’s clean energy futures better than a piecemeal study would do. Second, it developed and piloted an interpretive participatory methodology for studying futures by building on references from design research. This methodology will be used in subsequent studies.

The aim of this study was to determine if there are asymmetries in the pass-through of West Texas Intermediate (WTI) crude oil prices to its derivatives (diesel and gasoline) in the Brazilian market.

Initially, the future WTI oil price series was analyzed using the self-exciting threshold autoregressive (SETAR) and logistic smooth transition autoregressive (LSTAR) non-linear models. Subsequently, the threshold autoregressive error-correction model (TAR-ECM) and Markov-switching model were used.

The findings indicated high prices throughout 2008 due to the subprime crisis. The findings indicated high prices throughout 2008 due to the subprime crisis. The results indicated that there is long-term pass-through of oil prices in both methods, suggesting an equilibrium adjustment in the prices of diesel and gasoline in the analyzed period. Regarding the short term, the variations in contemporary crude oil prices have positive effects on the variations in fuel prices. Lastly, this behavior can partly be explained by the internal price management structure adopted during almost all of the analyzed period.

This paper contributes to the literature at some points. The first contribution is the modeling of the oil price series through non-linear models, further enriching the literature on the recent behavior of this time series. The second is the simultaneous use of the TAR-ECM and Markov-switching model to capture possible short- and long-term asymmetries in the pass-through of prices, as few studies have applied these methods to the future price of oil. The third and main contribution is the investigation of whether there are asymmetries in the transfer of oil prices to the price of derivatives in Brazil. So far, no work has investigated this issue, which is very relevant to the country.

The promotion of new energy vehicles (EVs) is an effective way to achieve low carbon emission reduction. This paper aims to investigate the optimal pricing of automotive supply chain members in the context of dual policy implementation while considering consumers' low-carbon preferences.

This article takes manufacturers, retailers and consumers in a main three-level supply chain as the research object. Stackelberg game theory is used as the theoretical guidance. A game model in which the manufacturer is the leader and the retailer is the follower is established. The author also considered the impact of carbon tax policies, subsidy policies and consumer preferences on the results. Furthermore, the author investigates the optimal decision-making problem under the profit maximization model.

Through model solving, it is found that the pricing of EVs is positively correlated with the unit price of carbon and the amount of subsidies. The following conclusions can be obtained by numerical analysis of each parameter. Changes in carbon prices have a greater impact on conventional gasoline vehicles. Based on the numerical analysis of parameter β, it is also found that when the government subsidizes consumers, supply chain members will increase their prices to obtain partial subsidies. Compared with retailers, low-carbon preferences have a greater impact on manufacturers.

The new energy automobile industry involves many policies, including tax cuts, tax exemptions and subsidies. The policy environment faced by the members of a supply chain is complex and diverse. Therefore, the analysis in this article is based only on partial policies.

The authors innovatively combine the three factors of subsidy policy, carbon tax policy and consumer low-carbon preference, with research on the pricing of EVs. The influence of policy factors and consumer preferences on the pricing of EVs is studied.

The purpose of this paper is to review studies on mathematical optimization of the sustainable gasoline supply chain to help decision-makers understand the current situation, the exact dimensions of the problem and the models provided in the literature. So, a more realistic mathematical optimization model can be achieved by fully covering all dimensions of the supply chain of this product.

To evaluate and comprehend the mathematical optimization of the sustainable gasoline supply chain research area, a systematic literature review is undertaken that covers material collection, descriptive analysis, content analysis and material evaluation steps. Finally, based on this process, 69 related articles were carefully investigated.

The results of the systematic literature review show the main areas of the published papers on mathematical optimization of sustainable gasoline supply chain problems and the gaps for future research in this field presented based on them.

This approach is subject to limitations because the protocol of the systematic review of the research literature only included searching for the considered combination of keywords in the Scopus and ProQuest databases. Furthermore, the protocol used in this paper restricts documents to English.

The results have significant implications for both academicians and practitioners in this field. It can be useful for academics to comprehend the gaps and future trends in this field. Also, for practitioners, it can be useful to identify and understand the parts of the mathematical optimization model, which can help them model this problem effectively and efficiently.

No systematic literature review has been done in this field by considering gasoline to the best of the authors’ knowledge and delivers new facts for the future development of this field.

The essence of finance has become essential in the sustainability discussion in recent times as a result of the capital intensive nature of sustainable projects. This has motivated financial experts and institutions to develop various financial instruments and mechanisms to further advance the course of protecting the environment, and decreasing the release of excess carbon and GreenHouse Gases. This is to also provide the opportunity for funding Green or sustainable infrastructure development. This chapter advances a discourse on matters relating to sustainable financing of infrastructure projects. The fundamentals of sustainable or green funding of infrastructure projects, and sustainable schemes of financing green infrastructure projects are discussed.