Digital transformation is a significant phenomenon that affects almost every business sector, particularly the telecommunications industry, which is closely intertwined with information technology. This study is grounded in McLuhan’s concept of technological determinism and Martin Heidegger’s philosophy of technology, which asserts that media and technology shape human thoughts and interactions, benefiting individuals, society, and culture alike. The primary objective of this research is to investigate the environmental factors that influence digital transformation and to assess its impact on the strategic renewal of a company. This research employs exploratory qualitative methods, collecting in-depth information through interviews with the respondents from Indonesia’s leading telecommunications operator who can provide comprehensive and contextual insights into digital transformation. The findings reveal specific environmental factors that drive digital transformation. The major identified components of strategic renewal include advancements in information technology, the role of human resources, and interactions with external parties, including customers and partners.

This study aims to identify the risk factors causing the delay in the completion schedule and to determine an optimization strategy for more accurate completion schedule prediction. A validated questionnaire has been used to calculate a risk rating using the analytical hierarchy process (AHP) method, and a Monte Carlo simulation on @RISK 8.2 software was employed to obtain a more accurate prediction of project completion schedules. The study revealed that the dominant risk factors causing project delays are coordination with stakeholders and changes in the scope of work/design review. In addition, the project completion date was determined with a confidence level of 95%. All data used in this study were obtained directly from the case study of the Double-Double Track Development Project (Package A). The key result of this study is the optimization of a risk-based schedule forecast with a 95% confidence level, applicable directly to the scheduling of the Double-Double Track Development Project (Package A). This paper demonstrates the application of Monte Carlo Simulation using @RISK 8.2 software as a project management tool for predicting risk-based-project completion schedules.

This study analyzes the social and individual stigmatization toward Venezuelan immigrants in Peru within the context of the largest migratory movement in Latin America, driven by the political, economic, and humanitarian crisis in Venezuela. The study employs a qualitative approach, using semi-structured in-depth interviews with a diverse sample of 24 participants from major Peruvian cities, including Lima, Arequipa, Cusco, and Trujillo. These in-depth interviews provide insights into the complexity of perceptions toward Venezuelan migrants, ranging from stigmatizing views driven by associations with economic threats and criminality to more positive perceptions that acknowledge the migrants’ adaptability and economic contributions. The findings reveal that while negative stereotypes perpetuate social exclusion and pressures for cultural assimilation threaten the preservation of migrant identities, there are also narratives highlighting resilience and successful integration. The study emphasizes the importance of implementing intercultural education programs, promoting labor integration policies, and collaborating with the media to combat stigma. It concludes that addressing these challenges through a multidimensional, human-rights-based approach can foster greater social cohesion and better integration of migrants, benefiting both the migrant population and Peruvian society.

This study, drawing on the Knowledge-Based View (KBV) and Contingency Theory, explores how analyzer strategic orientation, learning capability, technical innovation, administrative innovation, and SME growth and learning effectiveness are interrelated. Analyzing cross-sectional data from 407 founders, cofounders, and managers of trade and service SMEs in Vietnam’s Southeast Key Economic Region through PLS-SEM, the research demonstrates that analyzer orientation positively impacts both technical and administrative innovation, thereby bolstering SME growth and learning effectiveness. However, learning capability does not significantly impact technical innovation or growth and learning effectiveness. Instead, learning capability negatively affects administrative innovation. Notably, technical and administrative innovations act as mediators between analyzer orientation and SME growth and learning effectiveness. The study provides practical insights tailored for SMEs navigating dynamic market environments like Vietnam, enriching theoretical understanding of SME strategic management within the trade and service sector.

The rapid advancement of artificial intelligence (AI) technology is profoundly transforming the information ecosystem, reshaping the ways in which information is produced, distributed, and consumed. This study explores the impact of AI on the information environment, examining the challenges and opportunities for sustainable development in the age of AI. The research is motivated by the need to address the growing concerns about the reliability and sustainability of the information ecosystem in the face of AI-driven changes. Through a comprehensive analysis of the current AI landscape, including a review of existing literature and case studies, the study diagnoses the social implications of AI-driven changes in information ecosystems. The findings reveal a complex interplay between technological innovation and social responsibility, highlighting the need for collaborative governance strategies to navigate the tensions between the benefits and risks of AI. The study contributes to the growing discourse on AI governance by proposing a multi-stakeholder framework that emphasizes the importance of inclusive participation, transparency, and accountability in shaping the future of information. The research offers actionable insights for policymakers, industry leaders, and civil society organizations seeking to foster a trustworthy and inclusive information environment in the era of AI, while harnessing the potential of AI-driven innovations for sustainable development.