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The development of artificial intelligence has revolutionized higher education by increasing the efficiency and personalization of learning, but it has also posed a major challenge in the form of a decline in students' critical thinking skills due to their dependence on technology. Therefore, an in-depth philosophical study through the post-positivism, critical theory, and constructivism paradigms is needed to understand its impact on cognitive and epistemological processes. This study aims to analyze how these three paradigms guide the development of critical thinking in the context of AI. It uses a descriptive-analytical method based on secondary data from academic literature such as journals and books that have been critically synthesized. The findings show that post-positivism views AI as a tentative critical realism tool for empirical verification. Critical theory critiques power relations, ideology, and the ethics of technological domination. Constructivism emphasizes the construction of social knowledge through human-centered design that supports creativity and collaboration. The positive impacts of AI include instant feedback and content adaptation, while the negative impacts include social isolation, weak digital literacy, and data privacy. Therefore, the implication is the wise use of AI with the assistance of teaching staff to strengthen reflective analysis, ethical literacy, and paradigm adjustments in accordance with the exact or social sciences to create multidimensional learning in the digital era.

Customer satisfaction has become a major focus in the development of modern services as the role of the service sector in the regional economy increases, including in the city of Balikpapan. However, the literature discussing customer satisfaction models shows conceptual and methodological fragmentation, requiring a systematic synthesis to identify theoretical patterns and current research developments. This study aims to map customer satisfaction models in the service industry through a Systematic Literature Review (SLR) approach using the PRISMA guidelines. A total of 20 articles selected from the last five years were analyzed to identify dominant constructs, methodological approaches, and relevant research trends. The review results show that customer satisfaction models have evolved from traditional service quality-based approaches to models that integrate customer experience, perceived value, trust, and digital dimensions such as personalization and AI-based services. The findings also emphasize the importance of local context, especially in the service sector in Balikpapan, where cultural factors, customer behavior, and the dynamics of city growth influence the structure of satisfaction models. Overall, this study provides a synthesis framework that can be used as a theoretical and practical foundation for designing service quality improvement strategies and developing a further research agenda in the service sector.

The development of the digital economy has driven major changes in consumer behavior, from traditional transactions to online interactions. These changes present both challenges and opportunities for businesses, particularly in the e-commerce sector, where consumer trust, data privacy, and digital technology adoption are important factors in decision-making. This study aims to map global trends in online consumer behavior research in the context of the digital economy using bibliometric analysis. Data was collected from the Scopus database using the keyword “online consumer behavior” for the period 2020-2025. The dataset was exported in CSV format and analyzed using VOSviewer and R Studio (Biblioshiny). The analysis included annual publication trends, identification of authors, journals, countries, as well as keyword mapping and citation networks. The results show a significant increase in publications after 2020, with China, the United States, and India as the main contributors. Keyword mapping reveals four research clusters: consumer trust and data privacy, e-commerce and digital platform adoption, consumer experience and personalization, and social commerce and social media influence. These findings confirm a growing research focus on issues of digital trust and opportunities for utilizing new technologies such as artificial intelligence and social media. This study provides a comprehensive overview of global trends in online consumer behavior and an important contribution to academics, practitioners, and policymakers.

This study aims to analyze the business development strategy of Depot Kusen Rahmat by reviewing four main aspects, namely production, human resources (HR), finance, and marketing. The analytical approach used in this study is SWOT (Strengths, Weaknesses, Opportunities, Threats) and QSPM (Quantitative Strategic Planning Matrix). Primary data was obtained through a survey of 16 respondents who are active consumers of Depot Kusen Rahmat. The results of the SWOT analysis identified that the company has four strengths, four weaknesses, four opportunities, and four threats. The most dominant internal strength is efficient and neat products, with the highest weighted score of 0.509, which indicates that the quality of production results is the main competitive advantage. On the other hand, the main weakness found is the absence of a product catalog, with a score of 0.158, which indicates a lack of visual information media as a means of product promotion and communication to consumers. From external factors, the biggest opportunity is the increasing consumer interest in custom products, with a score of 0.479, which indicates a positive trend towards product personalization. The most significant threat is the rapidly changing design trends, with a score of 0.186, which requires the company to be more adaptive to changing market tastes. Based on the results of the SWOT matrix analysis, the company's position is in Quadrant I with an IFAS value of 1.368 and EFAS of 1.206, which indicates that the company is in a position to support an aggressive growth strategy. The QSPM results recommend prioritizing strategies in the form of emphasizing quality and balanced prices, followed by improving customer service and developing high-quality custom products as strategic steps to win market competition and increase business competitiveness sustainably.

Digitalization has been a key catalyst for change in the global business landscape, driving the transformation of companies' strategies, organizational structures, and operational models. For small and medium enterprises (SMEs), digital technology opens up great opportunities to expand market reach and compete in the international arena more effectively. Technologies such as e-commerce, social media, big data analytics, and cloud-based platforms enable SMEs to break through geographical boundaries, facilitate access to global customers, and accelerate product distribution and marketing processes. This paper explores the current academic literature that discusses the influence of digital technology on the internationalization of SMEs. A total of five relevant studies were analyzed to identify common patterns, challenges, and successful strategies in the use of digital technology. The results of the study show that the adoption of digitalization not only improves operational cost efficiency, but also encourages business model innovation, such as digital platform-based marketing, cross-border virtual collaboration, and the development of a more adaptive global business ecosystem. In addition, the ability to utilize digital technology gives SMEs a competitive advantage through access to real-time market information, personalization of offers, and more targeted branding strategies. However, the research also found obstacles, such as limited human resources, technological infrastructure, and digital literacy among SMEs. Therefore, synergy is needed between business actors, the government, and academia to support the acceleration of digital technology adoption through training, mentoring, and policies that support innovation. The paper also highlights future research opportunities, such as the integration of artificial intelligence (AI) technologies, automation, and blockchain in supporting the global expansion of SMEs. These findings are expected to be a strategic reference in designing sustainable internationalization policies in the digital era.

This study aims to analyze the relationship between marketing strategies and customer satisfaction on e-commerce platforms in Indonesia. Effective marketing strategies are essential in facing intense competition in the digital world, especially in enhancing customer satisfaction, which influences loyalty and business sustainability. This research uses a quantitative survey approach involving 100 active users of Shopee and Tokopedia platforms. Data were collected through questionnaires and analyzed using descriptive statistics, Pearson correlation, and simple linear regression. The results indicate a positive and significant relationship between marketing strategies and customer satisfaction, with a correlation value of 0.673 and a contribution of 45.3%. Digital promotions, personalized services, and loyalty programs are key factors in improving customer satisfaction. However, customer service aspects require more attention to support overall satisfaction. This study implies that e-commerce platforms must continuously develop integrated marketing strategies alongside quality service improvements to maintain and enhance customer satisfaction.

This study examines the application of big data analytics on Bhinneka.com, a leading e-commerce platform in Indonesia, to tackle the increasing in complexity of online user behavior in a swiftly changing digital environment. The primary issue is too challenges in evaluating extensive, unstructured, and heterogeneous user data, which obstructs personalization, marketing efficacy, and operational decision-making. The study seeks to assess the efficacy of big data instruments, specifically Artificial Intelligence Recommendation (AIRec) and Customer Data Platform (CDP), in improving user behavior forecasting. Service customization, and data-informed strategies. This study utilizes a qualitative case study methodology, including literature review and platform observation, to synthesis the many forms of big data analytics (descriptive, diagnostic, predictive, and prescriptive) and their implementation at Bhinneka.com. Significant findings indicate that the integration of AIRec and CDP has augmented the platform’s capacity to predict consumer preferences, improve marketing accuracy, and optimize logistics. However, obstacles stay the same, such as disjointed data systems, data quality concerns, and internal opposition to embracing a data-driven culture. The study suggests that although big data analytics substantially enhances Bhinneka.com’s digital competitiveness, ongoing investment in data infrastructure and organizational competence is crucial to fully harness its potential and preserve a competitive advantage in Indonesia’s e-commerce market.

The advancement of artificial intelligence (AI) technology has transformed the paradigm of shopping experiences on e-commerce platforms. This article examines the future of AI-powered virtual shopping assistants designed to provide personalized solutions in the digital marketplace experience. Virtual shopping assistants, driven by technologies such as chatbots, voice assistants, and machine learning, enable consumers to receive more relevant product recommendations and a shopping experience tailored to their preferences. This study aims to explore how the implementation of AI-powered virtual shopping assistants can enhance customer loyalty, sales conversion, and consumer satisfaction in online marketplaces. Using a mixed-method approach involving in-depth interviews and quantitative surveys, the research identifies consumer perceptions of this technology and its impact on their purchasing decisions. Findings reveal that consumers who engage with AI-powered virtual shopping assistants report more personalized and satisfying shopping experiences, contributing to increased loyalty and sales conversion for e-commerce platforms. This article provides practical insights for marketplace managers to optimize the use of AI in creating more personalized and responsive shopping experiences. Furthermore, this research opens opportunities for further exploration of AI integration across various digital shopping channels.

The development of artificial intelligence (AI) has significantly changed the digital advertising landscape. However, consumer trust in the use of AI in digital advertising is a crucial issue to understand. This study aims to analyze the influence of perceived intelligence, transparency, and personalization of AI-based advertising on consumer trust levels. Using a quantitative approach through a survey of 500 respondents who are active social media users in Indonesia, the data were analyzed using Structural Equation Modeling (SEM). The results of the study indicate that perceived intelligence and transparency have a significant positive influence on consumer trust, while personalization has a moderate influence. These findings provide theoretical contributions to the digital marketing literature and provide practical guidance for marketers in designing AI-based advertising strategies that are trusted by consumers.