Indonesia, as a maritime country, has many coastal areas with fishing villages that have significant potential, especially in sociological, economic, and environmental aspects, to be developed as models for sustainable development. Indonesia, with its long-standing fishing traditions, showcases the abundant potential and traditional that could help address global challenges such as climate change, rapid urbanization, and environmental and economic issues. This study aims to develop a conceptual model for sustainable cities and communities based on local potential and Wisdom towards the establishment of a Blue Village in the fishing village of Mundu Pesisir, Cirebon, Indonesia. The urgency of this study lies in the importance of developing sustainable strategies to address these challenges in coastal towns. This study involves an interdisciplinary team, including experts in sociology, social welfare, architecture, law, economics, and information technology. Through the identification of local natural and sociocultural resources, as well as the formulation of sustainable development strategies, this study develops a conceptual Blue Village model that can be applied to other coastal villages. The method employed in this study is qualitative descriptive, involving the steps of conducting a literature review, analyzing local potential, organizing focus group discussions, conducting interviews, and finalizing the conceptual model. The study employed, a purposive sampling technique, involving 110 participants. The results of the study include the modeling of a sustainable city and community development based on local potential and Wisdom aimed at creating Blue Villages in Indonesia, and It is expected to make a significant contribution to the creation of competitive and sustainable coastal areas capable of addressing the challenges of climate change and socioeconomic dynamics in the future.

Molan, an intangible cultural heritage of the Zhuang nationality in China, faces a crisis due to traditional communication and inheritance models. In the digital era, leveraging advanced digital technology is crucial for revitalizing this ancient heritage. From a communication theory perspective, this paper uses field investigation and applies the classic 5W communication model by Lasswell to deeply analyze the crisis facing Molan culture. Integrating the media evolution theory of Levinson, it explores the benefits and methodologies of digital dissemination for ancient intangible cultural heritage and proposes a digital communication model. The paper emphasizes adopting the PGC (Professional Generated Content) + UGC (User Generated Content) production model and strictly adhering to the “Content is King” principle. It advocates for models such as “Social Media + Molan,” “Short Video + Molan,” and “Algorithm + Molan” to enhance communication effectiveness. These viewpoints aim to revitalize and preserve Molan culture in the digital age.

Work can be demanding, imposing challenges that can be detrimental to the job performance of employees. Efforts are therefore underway to develop practices and initiatives that may improve job performance and well-being. These include interventions based on mindfulness, inclusive leadership and work engagement. In the present study, authors have presented an association of inclusive leadership and mindfulness towards job performance through employee work engagement among secondary teachers in the context of Hong Kong. The sample size of 263 teachers working from three secondary schools in Sha Tin, Hong Kong has been incorporated in this study. A structured questionnaire designed on a 5-point Likert scale has been used based on purposive sampling by analysis of IBM SPSS 27 and Smart PLS version 4.0.9 by applying a structural equation modelling approach (SEM). The results indicated a strong positive influence on employee work engagement and job performance. Moreover, the bootstrap investigation showed that mindfulness and inclusive leadership were significantly associated with employees’ work engagement in the presence of mediators’ work engagement. This study adds to the very scarce literature on inclusive leadership and mindfulness. In addition, this research is the first study to test the mindfulness skill, inclusive leadership and job performance relationship. Furthermore, this is the first study to explore the concept of mindfulness and inclusive leadership in the Hong Kong context. Moreover, the findings of this research can be beneficial for future theory development on mindfulness skill and inclusive leadership in cross-cultural contexts.

This study explores the advancement of ethical practices and environmental sustainability in Thai banking through an in-depth case analysis of Siam Commercial Bank (SCB), the country’s first indigenous bank founded in 1907. SCB has significantly influenced ethical banking practices and sustainability initiatives. The research provides a unique comparative analysis of SCB’s ethical frameworks and sustainability policies, assessing their impact on key stakeholders, including customers, employees, the community, and the environment. Employing a qualitative case study methodology, this study utilizes secondary data from SCB’s reports and CSR documents, analyzed through thematic analysis and descriptive statistics. The findings reveal SCB’s substantial progress in aligning ethical considerations with environmental sustainability, contributing new insights into ethical decision-making processes and the balance between profit and responsibility. Recommendations are provided to enhance ethical and sustainable practices in banking, adding to the discourse on corporate responsibility, environmental stewardship, and sustainable development.

This study evaluates the sustainability and ethical practices of Kerry Logistics Network Limited (KLN), a prominent logistics service provider headquartered in Hong Kong. Using normative ethical theories, stakeholder analysis, and the Circle of Sustainability framework, this research examines KLN’s alignment with global sustainability standards, particularly the United Nations Sustainable Development Goals (SDGs). The findings reveal that KLN has achieved significant milestones in environmental management, such as reducing greenhouse gas emissions by 11% from 2021 to 2022 through the deployment of electric trucks and incorporating renewable energy in warehouse operations. KLN has also enhanced social responsibility and governance practices by implementing fair labor policies and establishing a rigorous code of conduct, ensuring compliance with ethical guidelines across its supply chain. However, the study identifies areas for improvement, including biodiversity actions, battery recycling processes, and transparency in stakeholder engagement. Emphasizing the importance of third-party validation, this paper underscores KLN’s leadership in the logistics industry and provides insights for other companies aiming to improve sustainability performance through comprehensive, verifiable practices.

Among contemporary computational techniques, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are favoured because of their capacity to tackle non-linear modelling and complex stochastic datasets. Nondeterministic models involve some computational intricacies when deciphering real-life problems but always yield better outcomes. For the first time, this study utilized the ANN and ANFIS models for modelling power generation/electric power output (EPO) from databases generated in a combined cycle power plant (CCPP). The study presents a comparative study between ANNs and ANFIS to estimate the power output generation of a combined cycle power plant in Turkey. The inputs of the ANN and ANFIS models are ambient temperature (AT), ambient pressure (AP), relative humidity (RH), and exhaust vacuum (V), correlated with electric power output. Several models were developed to achieve the best architecture as the number of hidden neurons varied for the ANNs, while the training process was conducted for the ANFIS model. A comparison of the developed hybrid models was completed using statistical criteria such as the coefficient of determination (R²), mean average error (MAE), and average absolute deviation (AAD). The R² of 0.945, MAE of 3.001%, and AAD of 3.722% for the ANN model were compared to those of R² of 0.9499, MAE of 2.843% and AAD of 2.842% for the ANFIS model. Even though both ANN and ANFIS are relevant in estimating and predicting power production, the ANFIS model exhibits higher superiority compared to the ANN model in accurately estimating the EPO of the CCPP located in Turkey and its environment.