Enhancing Sustainable Business Models for Green Transportation

Simões, Vasco M.; Pereira, Leandro; Dias, Álvaro

doi:10.3390/su15097272

Cited by 4 publications

(3 citation statements)

References 67 publications

(119 reference statements)

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“…This also allowed us to answer our second research question. With the potential analysis, we can provide important information for the development of business models, showing precisely the external factors and policies and their influences on the pricing model of multi-life lithiumion batteries [19,20,97,98].…”

Section: Discussionmentioning

confidence: 99%

Economic Potentials of Ecologically Attractive Multi-Life Products—The Example of Lithium-Ion Batteries

Jeppe,

Proff,

Eickhoff

2023

Sustainability

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The growth of the electric vehicle market is increasing the demand for batteries. The production of vehicle batteries has a high environmental impact and at the same time represents a high cost factor in the production of electric vehicles. Both the raw materials and the production capacity required for vehicle batteries are very limited. Driven by the increasing scarcity of resources and the rising internalization of external environmental costs, as well as by policy regulations, this paper shows a possibility of life cycle extension that goes beyond the circular economy approach and opens up additional economic and ecological potentials. In contrast to the current end-of-life strategies and the circular economy approach, a new innovation philosophy and business models for sustainable multi-life products are developed. To this end, we first conducted an economic analysis in three steps and developed a multi-life indicator in the process. Based on this, we integrated the influence of political regulations in a fourth step and elaborated on their effects in five scenarios. Our results show a savings potential of 5–30% (multi-life indicator M 0.95–0.70) compared to single-life batteries. This savings potential shows the importance of the new strategic multi-life approach and justifies the need for further research in this field.

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Section: Discussionmentioning

confidence: 99%

Economic Potentials of Ecologically Attractive Multi-Life Products—The Example of Lithium-Ion Batteries

Jeppe,

Proff,

Eickhoff

2023

Sustainability

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“…The higher the anticipated cost of participation, the less inclined individuals are to engage in the behavior. Taking the purchase of electric vehicles as an example, research indicates that the higher cost of purchasing an electric vehicle directly reduces consumer willingness to buy [39]. In addition to the objective direct purchase cost, the behavioral cost of participating in emission reduction measures is also an important factor influencing citizens to implement green behaviors.…”

Section: Cost Scenariosmentioning

confidence: 99%

Evolutionary Simulation of Carbon-Neutral Behavior of Urban Citizens in a “Follow–Drive” Perspective

Zhu,

Qian,

Liu

2023

Sustainability

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The implementation of low-carbon behavior by citizens is of the utmost importance in constructing China’s ecological civilization and achieving its dual-carbon objectives. As a result, exploring the formation and recurrence mechanisms of carbon-neutral citizenship behavior may have a positive impact on realizing China’s carbon reduction targets. This study explores a comprehensive analysis method of multi-subject interactive evolution of carbon-neutral citizenship behavior. It expands the connotation of behavioral intervention from individual single execution (citizens actively adhere to carbon-neutral behavior) to multi-driven implementation (citizens inspire other residents to comply with carbon-neutral behavior based on their own adherence). Furthermore, this study constructs a collaborative and interactive “follow–drive” mechanism for carbon-neutral citizenship behavior. Through Python software 3.8 simulation, this study examines the formation and stabilization process of carbon-neutral citizenship behavior under different influencing factors. The research findings are as follows: (1) If the government neglects its duties more severely, it is more inclined to adopt incentive policies, thereby increasing the likelihood that both kinds of the citizens will choose to follow carbon-neutral behavior. This suggests that the proactive introduction of relevant policies and regulations by the government has a positive influence on citizens’ carbon-neutral behavior. (2) With a higher perceived level of psychological–physical bimetric health among citizens, both kinds of the citizens are more inclined to follow and drive carbon-neutral behavior, while the chances of the government selecting incentive policies decrease, and it takes longer to attain final stability (i.e., selecting incentive policies). (3) In situations where there is a greater loss of group norms in the external environment of the citizen group, both kinds of the citizens are more likely to opt for and drive carbon-neutral behavior. This, in turn, reduces the likelihood of the government selecting incentive policies. Finally, based on the research findings, relevant policy recommendations are given.

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“…Green transportation, which includes electric vehicles, hybrid cars, biofuels, and effective public transit systems, could substantially reduce air pollution and improve public health. It also helps combat climate change by reducing emissions, conserving energy, and promoting efficient resource use [16][17][18]. Pakistan was among the top 10 nations most hit by extreme weather events from 1991 to 2010 [19].…”

Section: Introductionmentioning

confidence: 99%

Impact of Green Energy Transportation Systems on Urban Air Quality: A Predictive Analysis Using Spatiotemporal Deep Learning Techniques

Mumtaz,

Amin,

Khan

et al. 2023

Energies

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Transitioning to green energy transport systems, notably electric vehicles, is crucial to both combat climate change and enhance urban air quality in developing nations. Urban air quality is pivotal, given its impact on health, necessitating accurate pollutant forecasting and emission reduction strategies to ensure overall well-being. This study forecasts the influence of green energy transport systems on the air quality in Lahore and Islamabad, Pakistan, while noting the projected surge in electric vehicle adoption from less than 1% to 10% within three years. Predicting the impact of this change involves analyzing data before, during, and after the COVID-19 pandemic. The lockdown led to minimal fossil fuel vehicle usage, resembling a green energy transportation scenario. The novelty of this work is twofold. Firstly, remote sensing data from the Sentinel-5P satellite were utilized to predict air quality index (AQI) trends before, during, and after COVID-19. Secondly, deep learning models, including long short-term memory (LSTM) and bidirectional LSTM, and machine learning models, including decision tree and random forest regression, were utilized to forecast the levels of NO2, SO2, and CO in the atmosphere. Our results demonstrate that implementing green energy transportation systems in urban centers of developing countries can enhance air quality by approximately 98%. Notably, the bidirectional LSTM model outperformed others in predicting NO2 and SO2 concentrations, while the LSTM model excelled in forecasting CO concentration. These results offer valuable insights into predicting air pollution levels and guiding green energy policies to mitigate the adverse health effects of air pollution.

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Enhancing Sustainable Business Models for Green Transportation

Cited by 4 publications

References 67 publications

Economic Potentials of Ecologically Attractive Multi-Life Products—The Example of Lithium-Ion Batteries

Economic Potentials of Ecologically Attractive Multi-Life Products—The Example of Lithium-Ion Batteries

Evolutionary Simulation of Carbon-Neutral Behavior of Urban Citizens in a “Follow–Drive” Perspective

Impact of Green Energy Transportation Systems on Urban Air Quality: A Predictive Analysis Using Spatiotemporal Deep Learning Techniques

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