The transportation sector is currently experiencing a significant transformation due to the influence of digital technologies, which are revolutionizing travel, goods transportation, and interactions with transportation systems. This study delves into the possibilities and obstacles presented by digital transformation in the realm of sustainable transportation. Moreover, it identifies the most effective methods for implementing digital transformation in this sector. Furthermore, our analysis sheds light on the potential impacts of digital transformation on sustainable development and environmental performance indicators within transportation systems. We discover that digital transformation can contribute to reduced greenhouse gas emissions, improved air quality, and increased resource efficiency, among other benefits. Nevertheless, we emphasize the potential risks and uncertainties associated with digital transformation, including concerns regarding data privacy, security, and ethics. Collectively, our research provides valuable insights into the opportunities and challenges presented by digital transformation in sustainable transportation. It also identifies best practices for successfully implementing digital transformation in this sector. The implications of our findings are significant for policymakers, businesses, and other stakeholders who aspire to drive the future of sustainable transportation through digital transformation.
This study aims to identify factors related to the impact of social capital on happiness among multicultural families using the 2019 Community Health Survey, which represents the South Korean population. The study utilized data from the 2019 Korea Community Health Survey, and the study participants, aged 20 years or older, included 3524 members of multicultural families from a total of 229,099 adult households. The study found a significant difference in happiness scores across different age groups (t = 57.00, p < 0.01). Based on the median value of happiness, significant relationships were found with the independent variables: Physical Environment of Trust (t = −5.13, p < 0.001), Social Networks (t = −5.51, p < 0.001), and Social Participation (t = −5.47, p < 0.001). Happiness was found to have a positive correlation with the Physical Environment of Trust (r = 0.12, p < .001), Social Participation (r = 0.11, p < 0.001), and Social Network (r = 0.13, p ≤ 0.001). In contrast, Age (r = −0.13, p ≤ 0.001) and Stress (r = −0.14, p ≤ 0.001) showed negative correlations with happiness (r = 0.57, p < 0.001). The analysis identified a positive community physical environment (t = 3.85, p < 0.01), increased social networks (t = 4.27, p < 0.01), and higher social participation (t = 6.88, p < 0.01) as significant predictors of happiness. This model suggests that the explanation power is 15%, which is statistically significant (R2 = 0.15, F = 57.72, p < 0.001). This study highlights the influence of social capital on the happiness of multicultural families living in Korea. Given the increasing number of multicultural families in the country, strategic interventions aimed at enhancing social networks and participation are necessary to promote their happiness.
The aim of this study is to examine the relationship between Environmental, Social and Governance (ESG) activities and the performance of Thai listed firms. The moderating roles of board size and CEO duality on this relationship are also assessed. The ESG score provided by LSEG (formerly Refinitiv) is chosen to measure ESG activities, both as an overall ESG combined scores and as Environment, Social, and Governance pillar scores. Multiple regression analysis is used to test the impact of ESG on firm performance while the PROCESS macro is used to test the moderating effects. Results reveal that the overall ESG combined score demonstrates no statistically significant effect on firm market-based performance. However, it shows the significant effects on firm performance for both the ESG combined score and the Environmental and Social pillar scores when moderated by board size and CEO duality; Governance pillar score exhibits no significant effect. Additionally, it is found that when the CEO operates only as the managing director and small board size and average board size are evident, higher ESG disclosure scores enhance firm performance. However, when the CEO serves as both managing director and chairman of the board of directors, and where there is a large board size, higher ESG disclosure scores diminish firm performance. This study contributes to the ESG literature and encourages companies to enhance their performance by implementing ESG combined activities with good governance policies.
The research aims to map environmental protection strategies and the related control tools and to identify the links among companies with the largest number of employees and sites in Hungary. The research questions were answered using a questionnaire survey method. The authors used cluster analysis to classify the 205 company strategies into the identified strategy clusters: Leaders, Awakeners, and Laggards. Then, the examined 21 environmental management control tools in the sample were divided into four groups: strategic, administrative, methodological and economic. Economic and strategic methods were the most common in the sample. The authors used cross-tabulation analysis to examine whether there is a statistically proven relationship between belonging to environmental strategy clusters and specific control tools. The analysis showed significant but weak to moderate relationships. According to Cramer’s V and the contingency coefficient, the closest relationship between the tested environmental management control tools and membership in environmental strategy clusters is shown by evaluating investments, assessing the economic viability of environmental strategies, and running an environmental training program for employees. In case of the robust lambda indicator, a significant relationship was found by examining the economics of environmental strategies and identifying environmental success factors and eco-balances. It can be concluded that the companies under examination follow a set of environmental goals, which they have incorporated into their strategic objectives. They use the available environmental management control toolbox to develop their strategies and to monitor their implementation to varying degrees.
This paper aims to contribute with a literature review on the use of AI for cleaner production throughout industries in the consideration of AI’s advantage within the environment, economy, and society. The survey report based on the analysis of research papers from the recent literature from leading database sources such as Scopus, the Web of Science, IEEE Xplore, Science Direct, Springer Link, and Google Scholar identifies the strategic strengths of AI in optimizing the resources, minimizing the carbon footprint and eradicating wastage with the help of machined learning, neural networks and predictive analytics. AI integration presents vast aspects of environmental gains, including such enhancements as a marked reduction concerning the energy and materials consumed along with enhanced ways of handling the resulting waste. On the economic aspect, AI enhances the processes that lead to better efficiency and lower costs in the market on the other hand, on the social aspect, the application of any AI influences how people are utilized as workers/clients in the community. The following are some of the limitations towards AI adoption as proposed by the review of related literature; The best things that come with AI are yet accompanied by some disadvantages; there are implementation costs, data privacy, as well as system integration that may be a major disadvantage. The review envisages that with the continuation of the AI development in the following years, the optic is going to be the accentuation on the enhancement of the process of feeding the data in real-time mode, IoT connections, and the implementation of the proper ethical approaches toward the AI launching for all segments of the society. The conclusions provide precise suggestions to the people working in the industry to adopt the AI advancements appropriately and at the same time, encourage the lawmakers to create favorable legal environments to enable the ethical uses of AI. This review therefore calls for more targeted partnerships between the academia, industry, and government to harness the full potential of AI for sustainable industrial practices worldwide.
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