In today’s fast-moving, disrupted business environment, supply chain risk management is crucial. More critically, Industry 4.0 has conferred competitive advantages on supply chains through the integration of digital technologies into manufacturing and logistics, but it also implies several challenges and opportunities regarding the management of these risks. This paper looks at some ways emerging technologies, especially Artificial Intelligence (AI), help address pressing concerns about the management of risk and sustainability in logistics and supply chains. The study, using a systemic literature review (SLR) backed by a mapping study based on the Scopus database, reveals the main themes and gaps of prior studies. The findings indicate that AI can substantially enhance resilience through early risk identification, optimizing operations, enriching decision-making, and ensuring transparency throughout the value chain. The key message from the study is to bring out what technology contributes to rendering supply chains resilient against today’s uncertainties.

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.

This study explores how demographic factors shape perceptions of celebrity and influencer marketing in the context of promoting cryptocurrencies, particularly in the tourism sector. It evaluates whether such marketing strategies effectively promote cryptocurrencies and how their impact varies across demographic groups. By analyzing responses from a sample of 161 predominantly young and educated respondents, the study uses statistical methods to identify differences in perceived marketing effectiveness based on age, gender, and other demographics. Findings reveal no significant demographic differences in effectiveness; instead, the study underscores the importance of universal marketing qualities, such as authenticity, credibility, and relevance. These results suggest the need for inclusive marketing strategies that foster trust and transparency. Additionally, the study highlights avenues for future research, including cultural and ethical considerations, to refine marketing approaches and develop innovative campaigns that drive cryptocurrency adoption and trust in the tourism industry.

In the fast-paced modern society, enhancing employees’ professional qualities through training has become crucial for enterprise development. However, training satisfaction remains under-studied, particularly in specialized sectors such as the coal industry. Purpose: This study aims to investigate the impact of personal characteristics, organizational characteristics, and training design on training satisfaction, utilizing Baldwin and Ford’s transfer of training model as the theoretical framework. The study identifies how these factors influence training satisfaction and provides actionable insights for improving training effectiveness in China’s coal industry. Design/Methodology/Approach: A cross-sectional design that allowed the study to capture data at one point in time from a large sample of employees was employed to conduct an online survey involving 251 employees from the Huaibei Mining Group in Anhui Province, China. The survey was administered over three months, capturing a diverse sample with nearly equal gender distribution (51% male, 49% female) and a majority aged between 21 and 40. The participants represented various educational backgrounds, with 52.19% holding an undergraduate degree and most occupying entry-level positions (74.9%), providing a broad workforce representation. Findings: The research indicated that personal traits were the chief predictor of training satisfaction, showing a beta coefficient of 0.585 (95% CI: [0.423, 0.747]). Linear regression modeling indicates that training satisfaction is strongly related to organizational attributes (β = 0.276 with a confidence interval of 95% [0.109, 0.443]). In contrast, training design did not appear to be a strong predictor (β = 0.094, 95% CI: [−0.012, 0.200]). Employee training satisfaction was the principal outcome measure, measured with a 5-point Likert scale. The independent variables covered personal characteristics, organizational characteristics, and training design, all measured through validated items taken from former research. The consistency of the questionnaire from the inside was strong, as Cronbach’s alpha values stood between 0.891 and 0.936. We completed statistical testing using SPSS 27.0, complemented by multiple linear regression, to study the interactions between the variables. Practical implications: This research contributes to the literature by emphasizing the necessity for context-specific training approaches within the coal industry. It highlights the importance of considering personal and organizational characteristics when designing training programs to enhance employee satisfaction. The study suggests further exploration of the multifaceted factors influencing training satisfaction, reinforcing the relevance of Baldwin and Ford’s theoretical model in understanding training effectiveness. Ultimately, the findings provide valuable insights for organizations seeking to improve training outcomes and foster a more engaged workforce. Conclusion: The study concluded that personal and organizational characteristics significantly impact employee training satisfaction in the coal industry, with personal characteristics being the strongest predictor. The beta coefficient for personal characteristics was 0.585, indicating a strong positive relationship. Organizational characteristics also had a positive effect, with a beta coefficient of 0.276. However, training design did not show a significant impact on training satisfaction. These findings highlight the need for coal companies to focus on personal and organizational factors when designing training programs to enhance satisfaction and improve training outcomes.

This study aims to investigate what influences local workers over the age of 40 to work and stay employed in oil palm plantations. 414 individuals participated in a face-to-face interview that provided the study’s primary source of data. Exploratory Factor Analysis was used to analyse the given data. The study revealed that factors influencing local workers over the age of 40 years to leave or continue working in oil palm plantations can be classified as income factors, internal factors and external factors. The income factor was the most significant factor as the percentage variance explained by the factor was 26.792% and Cronbach Alpha was high at 0.870. Therefore, the study suggested that the oil palm plantation managements pay more attention to income elements such as basic salary, wage rate paid to the workers and allowance given to the workers since these elements contribute to the monthly total income received by the workers and in turn be able to attract more local workers to work and remain in the plantations.

The pressing need to redefine the tourism industry’s relationship with nature and local communities has never been more critical. Ecotourism, as a paradigm of sustainable travel, holds transformative potential—not only for preserving our planet’s fragile ecosystems but also for fostering local cultural and economic development. In this context, the integration of circular economy principles offers innovative pathways to enhance sustainability across the tourism sector. The application of circular economy frameworks in tourism not only reduces environmental impact but also enhances economic viability by creating closed-loop systems. My interest in this topic stems from a personal conviction: Tourism should leave a positive mark, one that enriches rather than diminishes the destinations we visit. This study delves into how the hotel industry can align itself with ecotourism principles by embracing innovative, sustainable practices that minimize environmental impact while delivering authentic, high-quality experiences for travelers. Through the lens of green energy, resource optimization, and cultural integration, the research demonstrates that sustainability is both an ethical responsibility and a pathway to long-term competitiveness in tourism. By supporting local economies and protecting natural heritage, the industry can shift from being a passive observer of environmental degradation to a proactive steward of change. This work serves as a call to action for stakeholders: Our choices today will define the landscapes and cultural legacies available to future generations.