The aim was to examine the relationships between selected demographic and psychographic factors and consumers' willingness to accept content generated by advanced technological innovations (AIGC) in social infrastructure. The sample consisted of 1,308 respondents. Spearman's correlation coefficient was used to examine the relationships between ordinal variables. To assess the differences between groups of respondents, a one-way analysis of variance was used, during which multiple linear regression analysis was used to confirm the predictive power of awareness and experience in relation to AI-generated content in relation to the tendency to accept such content. The study confirmed a statistically significant but weak negative relationship between the age of respondents and their willingness to accept AIGC, with younger age groups showing a slightly higher rate of acceptance. Respondents' attitudes toward the use of personal data through AI and their overall awareness of technological trends had a more significant impact on acceptance. The findings show that respondents who are open to data collection through AI technologies show a significantly higher level of acceptance of automatically generated content. Similarly, respondents who positively evaluate the current quality of AIGC have higher expectations for the future transformation of marketing strategies and media practices. The decisive factors in the social infrastructure for the acceptance of AIGC are not so much the age of the respondents, but rather their awareness, technological literacy, and level of trust in the technology itself. The study therefore recommends increasing transparency and public awareness about the use of AI in marketing and media practices in order to strengthen consumer confidence in automated content.

This paper reviews and compares the opportunities and challenges in terms of port and intermodal development in China and India—the two fast-growing economic giants in the world. The study analyzes the future direction of these two countries’ port-hinterland intermodal development from the sustainability perspective. Both China and India face some major opportunities and challenges in port-hinterland intermodal development. The proposal of the Silk Road Economic Belt and the 21st-century Maritime Silk Road, also known as the Belt and Road Initiative (BRI), offers plentiful opportunities for China. A challenge for China is that its development of dry ports is still in the infancy stage and thus it is unable to catch up with the pace of rapid economic growth. As compared with China, India focuses more on the social aspect to protect the welfare of its residents, which in turn jeopardizes India’s port-hinterland intermodal development in the economic sense. The biggest challenge for India is its social institution, which would take a long time to change. These in-depth comparative analyses not only give the future direction of port-hinterland intermodal development in China and India but also provide references for other countries with similar backgrounds.

This study aims to develop a framework that helps organizations to fulfill their environmental and social responsibility amid constraints in selecting which stakeholders’ interest comes first and the essential to have an evolved strategic planning that can accommodate broader systemic planning and practice that will yield authenticity in business sustainability with components of environmental worldview of its leaders and organizational learning in the framework. This research uses the method of literature review with the data from interviews and content analysis of the report from one organization that has successfully implemented social and environmentally friendly practices. Based on an in-depth review of literatures on worldview, organizational learning, and strategic planning, and with empirical study from one organization, a conceptual framework by combination of the existing concepts is produced to enable an integration of theories in a range of possible actions for organizations to achieve sustainable development. The result from this research’s framework will allow further study to be carried out in the future to verify associations between existing concepts or variables within the framework, and to produce next empirical results in supporting those theories being reviewed in this paper.

This study explores the spatial distribution pattern of educational infrastructure development across districts and cities in North Sumatra, identifying significant disparities between urban and rural areas. The study aims to: (1) determine the distribution of educational development across districts and cities, (2) analyze global spatial autocorrelation, and (3) identify priority locations for educational development policies in North Sumatra Province. The methodology includes quantile analysis, Moran’s Global Index, and Local Indicators of Spatial Autocorrelation (LISA) using GeoDa software to address spatial autocorrelation. The results indicate that there are nine areas with a low School Participation Rate Index (SPRI), eleven areas with a low School Facilities and Infrastructure Index (SFII), and eleven areas with a low Regional Education Index (REI). Spatial autocorrelation analysis reveals that SFII shows positive spatial autocorrelation, while SPRI and REI exhibit negative spatial autocorrelation, indicating a high level of inequality between regions. Labuhan Batu Selatan and Labuhan Batu are identified as priorities for the provincial government in overseeing educational development policies.