This study identified a set of applicable and practical green performance evaluation indices for Chinese ports using the Delphi technique. The research was conducted by targeting three representative Chinese ports in Eastern China: the Shanghai Port, Ningbo Port, and Qingdao Port. An effective expert panel was structured with direct stakeholders related to green performance, which was based on a sufficient consideration of the unique and the special decision-making system for Chinese ports. Twenty-one green performance indices in six dimensions (i.e. liquid pollution management, air pollution management, noise control, low carbon regulations and energy savings, marine biology preservation, and organization and management) were eventually identified through three rounds of iterations. The identified green performance indices for Chinese ports are highly consistent with the Chinese Government’s environmental policies. Compared with European ports, the green port performance indicators in China are not as comprehensive. The indicators that are strictly consistent with national macro policies and the factors that are more easily seen, heard, and felt were perceived to be more important. From an academic perspective, this study offers a new approach for system establishment and green practice criteria exploration and thus provides a significant basis for further green port studies.

Over the past 30 years, there have been growing concerns on the environmental impacts of maritime transportation, which have attracted great attention from both academia and practitioners. Understanding developments in this area can help guide future research. We conducted a comprehensive review of green shipping research, comprising 213 papers published in transportation journals in SSCI of 2017 over the period 1988–2017. We find that research on green shipping has increased greatly since 2012, accounting for 77.5% of the reviewed papers. The main focus today on green shipping was on air pollution, and the classification of green shipping practice, such as technical measures, operational options, market-based measures, and recycling and reusing, is becoming clear. According to the existing studies, future research on green shipping must strengthen technology research to not only solve practical problems, but also to establish a theoretical green shipping system. Moreover, researchers from different countries could cooperate with each other to give effective suggestions on setting standards and laws of green shipping. Finally, we identify the future research themes will focus on setting up green shipping system and legislation and policy.

Social distancing due to the COVID-19 pandemic has driven some consumers to online shopping, and concerns about pandemic risks and personal hygiene have increased the demand for e-commerce. Providing personalized recommendations seems quite profitable for e-commerce platforms, and consumers also benefit from personalized content with the advancement of AI technologies. However, this possible win-win situation is marred by the increase in consumers' privacy concerns. Technical solutions have been widely studied to protect consumer privacy, while few analyses have been conducted from the perspective of psychological and behavioral implications. In this paper, an evolutionary game model of privacy protection between e-commerce platforms and consumers is established to determine the mechanisms by which various factors exert influence, and evolutionary stable strategies are obtained from equilibrium points. Then, the strategy selections are simulated with MATLAB 2020 software. Based on the results, the following conclusions are drawn: (1) the application of AI technologies in e-commerce will fundamentally benefit consumers, which makes them actively share personal information with e-commerce platforms with incentives for generous rewards; (2) it is profitable for e-commerce platforms to conduct data mining by improving the ability to use AI technologies and making efforts to reduce technical costs; and (3) regulators should improve the level of supervision instead of imposing a large penalty to enhance consumer trust, which could effectively increase the profits of e-commerce platforms and protect consumers' privacy.

With the development of new technologies, smart shipping makes possible one system that connects ports and ships to help stakeholders make decisions with greater efficiency, minimized costs and smaller ecological footprints. However, smart shipping is at the preliminary stage, and the related literature on smart shipping systems or domains is still lacking. To understand and develop smart shipping, our study intends to establish an index system based on the literature review and the Delphi method. Consequently, the system, which includes four first-level indexes, 17 second-level indexes, and 61 third-level indexes, is established. As the main domains, smart waterways, smart ports, smart ships, and maritime intelligence compose the smart shipping system. Among these four domains, the coordinated opinion of experts proposes that smart ports are very important for achieving smart shipping. Furthermore, based on the means of each index, indexes with higher scores can help stakeholders who want to participate in smart shipping make decisions.

Due to the COVID-19 pandemic, the international shipping market has been highly volatile, posing a serious threat to the survival and development of many maritime start-ups. With the development of the digital economy, digital transformation is affecting the evolution and upgrading of many traditional enterprises, including maritime enterprises. In the post-COVID-19 era, start-up small and medium-sized enterprises will need to consider the importance of enterprise risk management to achieve transformation and upgrading. The purpose of this study is to provide guidance for the establishment and upgrading of risk management systems for start-ups based on the identification of risk management strategies of maritime enterprises and the evaluation of their performance. The fuzzy analytic hierarchy process and importance-performance analysis methods were used to rank the operational risk, financial risk, market risk, innovation risk, and disaster risk according to sub-items and screen out the risk management schemes for priority improvements. Through empirical research, it was found that the financial risk and market risk response schemes have the lowest performance and need to be prioritised for improvement. This study argues that start-ups can appropriately challenge their risk management strategies to meet potential risk management needs based on their own circumstances.