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The ship recycling industry is a labor‐intensive field that often grapples with the issue of workers not adopting appropriate practices that are environmentally friendly and safe. However, the existing literature largely overlooks the consideration of workers' environmentally friendly and safety behaviors. Therefore, this study aims to explore the determinants of workers' environmentally friendly and safety behaviors during ship recycling by proposing a theoretical model that incorporates the theory of planned behavior. Survey data were collected from 170 participants in the ship recycling industry in China. Subsequently, structural equation modeling was applied to evaluate the proposed model. The findings highlight that factors such as attitude, perceived behavioral control, subjective norms, safety awareness, and perceived susceptibility directly or indirectly affect workers' environmentally friendly and safety behavior. The study offers important implications for ship recycling companies and environmental policies, fostering the emergence of sustainable development, and stakeholder engagement in the industry. [ABSTRACT FROM AUTHOR]

Guangdong Province enjoys a very high economic status in China especially in terms of port construction. In response to the port development directions in China, the Guangdong government released a policy about the construction of Guangdong ports in the next 15 years. Based on the policy, this study proposes to evaluate the port efficiency of major ports in Guangdong Province during 2011–2020 using the Super-efficiency EBM-DEA model that considers undesirable outputs, and the spatial effect of port efficiency and its influencing factors is further analyzed using the spatial Durbin model. The empirical results shows that the overall port efficiency in Guangdong Province is not high and varies widely among port clusters, thereby lacking synergistic development. The results of the spatial Durbin model show that port efficiency is positively correlated with the level of economic development, port-city relationship and transportation structure, as well as negatively correlated with the efficiency of neighboring ports. The findings have a far-reaching impact on the development of port construction. [ABSTRACT FROM AUTHOR]

E-tailing is an important feature of e-commerce in general. This is particularly true for the Dell Corporation (Dell). Literature on Dell generally focuses on its competitive features in direct sales, products and services, overlooking its e-consumer protection. This paper aims to address this gap by reviewing the information available on Dell's (Australia) website and secondary data to examine: (i) the current e-consumer protection regulatory framework, using Australia as a case study; (ii) consumer protection by Dell; (iii) consumer experiences with Dell; and (iv) implications for theories and practices concerning e-consumer protection. Overall, Dell has adhered to its corporate governance to comply with the existing legal framework for customer protection; however, less consistent with consumer redress. The study proposes that better treatment and education of consumer rights may help e-tailers retain existing customers and attract new customers. A blend of regulatory improvement and changes in stakeholders' mindset and behaviour are essential to enhance e-consumer protection. Proper compliance measures, including both regulatory and non-regulatory, are required to protect the interests of both e-tailers and e-consumers. [ABSTRACT FROM AUTHOR]

Reducing the incidence of seafarers' workplace injuries is of great importance to shipping and ship management companies. The objective of this study is to identify the important influencing factors and to build a quantitative model for the injury risk analysis aboard ships, so as to provide a decision support framework for effective injury prevention and management. Most of the previous research on seafarers' occupational accidents either adopts a qualitative approach or applies simple descriptive statistics for analyses. In this study, the advanced method of a Bayesian network (BN) is used for the predictive modeling of seafarer injuries for its interpretative power as well as predictive capacity. The modeling is data driven and based on an extensive empirical survey to collect data on seafarers' working practice and their injury records during the latest tour of duty, which could overcome the limitation of historical injury databases that mostly contain only data about the injured group instead of the entire population. Using the survey data, a BN model was developed consisting of nine major variables, including "PPE availability," "Age," and "Experience" of the seafarers, which were identified to be the most influential risk factors. The model was validated further with several tests through sensitivity analyses and logical axiom test. Finally, implementation of the result toward decision support for safety management in the global shipping industry was discussed. [ABSTRACT FROM AUTHOR]

In the contemporary port business environment, port resilience is of paramount importance for supply chain continuity. A result of the increased integration of ports into supply chains is ports’ potential to supply chain disruptions. This paper introduces a PSCD management model that incorporates the application of risk management, business continuity management, and quality management theories with the purpose of increasing port resilience such that supply chain continuity is enhanced. To validate this model, primary data were collected from samples of port operators and port authorities and analyzed using structural equation modeling with AMOS 22.0. The results indicate that managing PSCD using the management model contributes positively to the identification of internal and external opportunities and through that to port’s resilience of internal operations. This, in turn, positively influences port’s financial health and market reputation. The management model has several managerial and academic implications as it offers meaningful insights on policy development as well as theory building. [ABSTRACT FROM PUBLISHER]

Reducing the incidence of seafarers' workplace injuries is of great importance to shipping and ship management companies. The objective of this study is to identify the important influencing factors and to build a quantitative model for the injury risk analysis aboard ships, so as to provide a decision support framework for effective injury prevention and management. Most of the previous research on seafarers' occupational accidents either adopts a qualitative approach or applies simple descriptive statistics for analyses. In this study, the advanced method of a Bayesian network (BN) is used for the predictive modeling of seafarer injuries for its interpretative power as well as predictive capacity. The modeling is data driven and based on an extensive empirical survey to collect data on seafarers' working practice and their injury records during the latest tour of duty, which could overcome the limitation of historical injury databases that mostly contain only data about the injured group instead of the entire population. Using the survey data, a BN model was developed consisting of nine major variables, including "PPE availability," "Age," and "Experience" of the seafarers, which were identified to be the most influential risk factors. The model was validated further with several tests through sensitivity analyses and logical axiom test. Finally, implementation of the result toward decision support for safety management in the global shipping industry was discussed., (© 2019 Society for Risk Analysis.)