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Due to the conflicts between left turn traffic and opposite straight-going traffic in urban traffic network, some of the traffic lanes cannot be used to discharge vehicles during its green phases and the intersection capacity can be greatly reduced. This study/paper aims to reduce the effect of conflicts and increase its capacity through the reasonable pre-signal phase time with the exchangeable lanes.

This paper took into consideration various influence factors to intersection capacity and formulated the capacity optimization model based on 0-1 mixed-integer programming model. This model is efficiently solved by standard branch-and-bound algorithms.

The authors took an intersection as an example and solved the optimal signal timing and entrance lane capacity via this model. Then, simulations were carried out to verify the effect of the exchangeable lanes strategy of this intersection through the simulation software VISSIM and take the traffic volume and delay as outputs, which indicated that this model has better performance.

The front-end control strategy can not only exploit the full potential of the intersection but also significantly improve the operational efficiency of the intersection. It plays a positive role in improving urban intersection congestion.

The article addresses the tension between Corporate Social Responsibility (CSR) and the right to work in times of the COVID-19 pandemic. Accordingly, it explores the operation of corporations in adopting policies of mandatory vaccination and the role of the courts regarding these CSR patterns.

The article examines court case studies of CSR practices regarding unvaccinated employees during the COVID-19 pandemic in Israel and the United States.

The findings show that the Israeli system adopted the regulating for individual discretionary CSR approach, whereas the American system adopted the regulating for ethical-public CSR approach. Adopting the latter infringes upon the right to work of unvaccinated employees. While in Israel, the possibility of compelling employees to vaccinate is denied, in the American model, mandatory vaccination is possible. As opposed to the American model, in the Israeli model, there is an obligation to consider proportionate measures to isolate the employees while allowing them to continue working.

The article introduces two possible notions of regulating CSR in times of the pandemic – regulating for individual discretionary CSR which is labor-oriented and regulating for ethical-public CSR which is focused on public aspects. While the former posits that corporations should advance individual interests of employees and their right to work, the latter claims that corporations should advance the public interest in health. Following the problems resulting from the Israeli and American cases, the article draws on the lines for a suggested approach that courts should embrace.

The purpose of this paper is to draw attention to the potential of “small data” to complement research in learning analytics (LA) and to share some of the insights learned from this approach.

This study demonstrates an approach inspired by design science research, making a dashboard available to n=1,905 students in 11 study programs (used by n=887) to learn how it is being used and to gather student feedback.

Students react positively to the LA dashboard, but usage and feedback differ depending on study success.

More research is needed to explore the expectations of a high-performing student with regards to LA dashboards.

This publication demonstrates how a small data approach to LA contributes to building a better understanding.

The purpose of the study is to highlight the relevance of reactance theory for modeling consumer responses to COVID restrictions. The study also aims to critically evaluate the appropriateness of the most established reactance model (the intertwined model) for studying reactance specifically in relation to freedom threats arising from measures aimed at combatting the spread of the pandemic.

Following a conceptual analysis of the intertwined model of reactance, structural equation modeling is applied to Rain's (2013) meta-analytic data to compare the model to alternative model specifications.

The analysis reveals both conceptual and statistical shortcomings of the intertwined model of reactance in its current/traditional form. It also draws attention to other model specifications that provide just as good statistical fit and offer promising alternative ways of modeling reactance in a COVID context.

The study is the first attempt to explicitly discuss conceptual and statistical problems associated with the most widely accepted model of reactance, illustrate these issues with specific reference to consumer reactions to COVID restrictions, identify alternative promising model specifications and suggest a respecification of the intertwined model.

This study aims to propose an enhanced eco-driving strategy based on reinforcement learning (RL) to alleviate the mileage anxiety of electric vehicles (EVs) in the connected environment.

In this paper, an enhanced eco-driving control strategy based on an advanced RL algorithm in hybrid action space (EEDC-HRL) is proposed for connected EVs. The EEDC-HRL simultaneously controls longitudinal velocity and lateral lane-changing maneuvers to achieve more potential eco-driving. Moreover, this study redesigns an all-purpose and efficient-training reward function with the aim to achieve energy-saving on the premise of ensuring other driving performance.

To illustrate the performance for the EEDC-HRL, the controlled EV was trained and tested in various traffic flow states. The experimental results demonstrate that the proposed technique can effectively improve energy efficiency, without sacrificing travel efficiency, comfort, safety and lane-changing performance in different traffic flow states.

In light of the aforementioned discussion, the contributions of this paper are two-fold. An enhanced eco-driving strategy based an advanced RL algorithm in hybrid action space (EEDC-HRL) is proposed to jointly optimize longitudinal velocity and lateral lane-changing for connected EVs. A full-scale reward function consisting of multiple sub-rewards with a safety control constraint is redesigned to achieve eco-driving while ensuring other driving performance.

This paper is among the first case studies in developing countries that comprehensively investigate the historical evolution of a country's teacher professional development (TPD) system, the outcomes of the current TPD and the factors underlying the stagnation of TPD quality.

The authors collected data from three types of sources—documents, observations and interviews. Documents examined included the handbooks of the TPD program, handouts for teachers, training modules from TPD workshop sessions and research publications or reports on TPD programs in Indonesia introduced from the 1970s to 2018. The authors conducted formal interviews with trainers, education stakeholders and teachers who participated in recent TPD.

The findings indicate that, on paper, TPD initiatives in Indonesia have included some of the positive features of TPD highlighted in the literature. However, these factors have not been consistently included in the reforms rolled out over the decades, and, indeed, many of the less desirable features of those reforms have endured. The analysis also reveals the absence of four key factors in multiple TPD reforms that led to teachers' and other stakeholders' dissatisfaction with the TPD implementation. These include consideration of teachers' skills, background and capacities; relevance of training; feedback provided to teachers; and workshop follow-up.

The research indicates that the long-term issues of ineffectiveness of TPD in Indonesia are driven by the incoherence of different elements of the education system. This extends beyond the technical and operational elements of the TPD itself. The absence of a clear vision of the purposes of teacher development has created confusion and uncertainty for teachers.

This study aims to propose a centralized optimal control model for automated left-turn platoon at contraflow left-turn lane (CLL) intersections.

The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness. The proposed model is cast into a mixed-integer linear programming problem and then solved by the branch-and-bound technique.

The proposed model has a promising control effect under different geometric controlled conditions. Moreover, the proposed model performs robustly under various safety time headways, lengths of the CLL and green times of the main signal.

This study proposed a centralized optimal control model for automated left-turn platoon at CLL intersections. The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness

Emissions produced by oceangoing vessels not only negatively affect the environment but also may deteriorate health of living organisms. Several regulations were released by the International Maritime Organization (IMO) to alleviate negative externalities from maritime transportation. Certain polluted areas were designated as “Emission Control Areas” (ECAs). However, IMO did not enforce any restrictions on the actual quantity of emissions that could be produced within ECAs. This paper aims to perform a comprehensive assessment of advantages and disadvantages from introducing restrictions on the emissions produced within ECAs. Two mixed-integer non-linear mathematical programs are presented to model the existing IMO regulations and an alternative policy, which along with the established IMO requirements also enforces restrictions on the quantity of emissions produced within ECAs. A set of linearization techniques are applied to linearize both models, which are further solved using the dynamic secant approximation procedure. Numerical experiments demonstrate that introduction of emission restrictions within ECAs can significantly reduce pollution levels but may incur increasing route service cost for the liner shipping company.

Two mixed-integer non-linear mathematical programs are presented to model the existing IMO regulations and an alternative policy, which along with the established IMO requirements also enforces restrictions on the quantity of emissions produced within ECAs. A set of linearization techniques are applied to linearize both models, which are further solved using the dynamic secant approximation procedure.

Numerical experiments were conducted for the French Asia Line 3 route, served by CMA CGM liner shipping company and passing through ECAs with sulfur oxide control. It was found that introduction of emission restrictions reduced the quantity of sulfur dioxide emissions produced by 40.4 per cent. In the meantime, emission restrictions required the liner shipping company to decrease the vessel sailing speed not only at voyage legs within ECAs but also at the adjacent voyage legs, which increased the total vessel turnaround time and in turn increased the total route service cost by 7.8 per cent.

This study does not capture uncertainty in liner shipping operations.

The developed mathematical model can serve as an efficient practical tool for liner shipping companies in developing green vessel schedules, enhancing energy efficiency and improving environmental sustainability.

Researchers and practitioners seek for new mathematical models and environmental policies that may alleviate pollution from oceangoing vessels and improve energy efficiency. This study proposes two novel mathematical models for the green vessel scheduling problem in a liner shipping route with ECAs. The first model is based on the existing IMO regulations, whereas the second one along with the established IMO requirements enforces emission restrictions within ECAs. Extensive numerical experiments are performed to assess advantages and disadvantages from introducing emission restrictions within ECAs.

In confronting the challenge of climate change and progressing towards dual carbon goals, China is actively implementing low-carbon city pilot policy. This paper aims to focus on the potential impact of this policy on enterprise green governance, aiming to promote the reduction and balance of carbon emissions.

Based on the panel data of China's large-scale industrial enterprises from 2007 to 2013, this paper uses the Difference-in-differences (DID) method to study the impact and path mechanism of the implementation of low-carbon city pilot policy on enterprise green governance. Heterogeneity analysis is used to compare the effects of low-carbon city pilot policy in different regions, different enterprises and different industries.

The low-carbon pilot can indeed effectively enhance corporate green governance, a conclusion that still holds after a series of robustness tests. The low-carbon city pilot policy mainly enhances enterprise green governance through two paths: an industrial structure upgrade and enterprise energy consumption, and it improves green governance by reducing enterprise energy consumption through industrial structure upgrade. The impact of low-carbon city pilot policy on enterprise green governance shows significant differences across different regions, different enterprises and different industries.

This paper examines the impact of low-carbon city pilot policy on enterprise green governance. However, due to availability of data, there are still some limitations to be further tackled. The parallel trend test in this paper shows that the pilot policy has a significant positive effect on the green governance of enterprises. However, due to serious lack of data in some years, the authors only selected the enterprise data of a shorter period as our experimental data, which leads the results to still have certain deficiencies. For the verification of the impact mechanism, the conclusions obtained in this paper are relatively limited. Although all the mechanism tests are passed, the reliability of the results still needs to be further tested through future data samples. In addition, as the pilot policy of low-carbon cities is still in progress, the policy can be tracked and analysed in the future as more data are disclosed, and further research can be carried out through dimensional expansion.

Low-carbon city pilot policy plays an important role in inducing the green governance of enterprises. Therefore, policy makers can continue to strengthen the construction of low-carbon city pilots by refining pilot experience, building typical cases, actively promoting pilot policy experience, expanding pilot scope and enhancing the implementation efficiency of pilot policy nationwide, which will contribute to the optimization and upgrading of the regional industrial structure at the urban level and will provide experience and reference for the synergistic implementation plan of pollution reduction and carbon reduction.

The impact of the low-carbon city pilot policy on enterprise green governance not only exists in two separate paths of urban industrial upgrading and enterprise energy consumption but also exists in a chain transmission path from macro to micro. The authors find that the effect value of each influence path is different, and there is an obvious leading influence path for the role of enterprise green governance. Therefore, in the process of implementing a low-carbon city pilot policy, policies should be designed specifically for different mechanisms. Moreover, complementing and coordinating several paths should be advocated to give full play to the green governance effect of enterprises brought by different paths and to further expand the scope of industries and enterprises where policies play a role.

To the best of the authors’ knowledge, for the first time, this paper connects macro mechanisms with micro mechanisms, discovering a macro-to-micro transmission mechanism in the process of low-carbon city pilot policy affecting enterprise green governance. That is, the low-carbon city pilot policy can facilitate industrial structure upgrading, resulting in reduced enterprise energy consumption, ultimately enhancing enterprise green governance.