Artificial intelligence (AI) has been integrated into higher education (HE), offering numerous benefits and transforming teaching and learning. Since its launch, ChatGPT has become the most popular learning model among Generation Z college students in HE. This study aimed to assess the knowledge, concerns, attitudes, and ethics of using ChatGPT among Generation Z college students in HE in Peru. An online survey was administered to 201 HE students with prior experience using the ChatGPT for academic activities. Two of the six proposed hypotheses were confirmed: Perceived Ethics (B = 0.856) and Student Concerns (B = 0.802). The findings suggest that HE students’ knowledge and positive attitudes toward ChatGPT do not guarantee its effective adoption and use. It is important to investigate how attitudes of optimism, skepticism, or apathy toward AI develop and how these attitudes influence the intention to use technologies such as the ChatGPT in HE settings. The dependence on ChatGPT raises ethical concerns that must be addressed with responsible use programs in HE. No sex or age differences were found in the relationship between the use of ChatGPTs and perceived ethics among HE students. However, further studies with diverse HE samples are needed to determine this relationship. To promote the ethical use of the ChatGPT in HE, institutions must develop comprehensive training programs, guidelines, and policies that address issues such as academic integrity, privacy, and misinformation. These initiatives should aim to educate students and university teachers on the responsible use of ChatGPT and other AI-based tools, fostering a culture of ethical adoption of AI to leverage its benefits and mitigate its potential risks, such as a lack of academic integrity.

ChatGPT, a large language model AI, has the potential to transform higher education by providing students with personalized learning support, assisting in writing tasks, and enhancing their level of engagement. This study examines the factors influencing the acceptance of ChatGPT among university students in Peru, following the extended UTAUT2 model with the addition of a construct called knowledge sharing (KS). A total of 772 students from seven universities in Lambayeque and La Libertad participated in an online survey, providing insights into their perceptions and experiences with using ChatGPT for academic purposes. The results from the structural equation model showed that effort expectancy, behavioral intention, and knowledge sharing positively influenced the actual use of ChatGPT. Furthermore, effort expectancy and performance expectancy were found to be determinants of the behavioral intention to use ChatGPT. The study also revealed that performance expectancy and behavioral intention serve as sequential mediating variables regarding the effect of effort expectancy on actual use. These findings suggest a positive adoption of ChatGPT among students, driven by individual and contextual factors, and highlight the importance of managing effort and performance expectations appropriately. This study represents a significant advancement in understanding the acceptance of ChatGPT in higher education and provides valuable guidance for practical implementation efforts, ensuring that this powerful AI tool is effectively leveraged to support student learning and success.

Global trade and globalization have driven growth and diversification in the horticultural industry. Fresh grapes, a key product, face challenges of market volatility, trade barriers, and logistics. Market diversification is essential for stability and competitiveness in international trade. This research focused on analyzing market diversification in Peru’s fresh grape exports during the 2013–2022 period, exploring its implications for international trade. A quantitative methodology was used, along with the analysis of publicly recorded data on the website of the National Superintendence of Customs and Tax Administration, specifically exports from companies shipping under the national subheading for Grapes (0806.10.00.00). Diversification was analyzed using the Herfindahl–Hirschman concentration index (HHI), and competitiveness through the Balassa index. The main findings were that between 2013 and 2022, Peruvian grape exports grew in value (CAGR of 12.02%) and volume (CAGR of 12.13%). The sector expanded with an average of 151.2 companies and 59.1 destination markets. Diversification varied: the USA (12.4%), the Netherlands (1.6%), Hong Kong (4.2%), and Mexico (63.2%). The Herfindahl–Hirschman index showed concentration in the USA (4533 in 2020, 4519 in 2022) and stability in companies (2318 in 2014, 2450 in 2022). Finally, it is recommended to strengthen the Peruvian viticultural sector by maintaining geographic diversification through policies seeking new markets, monitoring global trends, constantly analyzing market concentration, and promoting fair competition among participating companies, allowing new ones to enter this sector.

The study examines how Peru could maintain the sustainability of its blueberry exports through market diversification and competitiveness. Using a quantitative approach, the Herfindahl–Hirschman Index (HHI) and the Balassa Index were calculated. The results showed impressive growth in key markets such as the United States, where exports grew by an average of 115.03% annually, and robust growth in the Netherlands and the United Kingdom. Despite these increases, the study identified a high concentration in specific markets, particularly in the United States, where the HHI ranged from 2896 to 3828 throughout the evaluated period, indicating significant dependence. Regarding the RCA, the values showed that Peru has maintained a solid comparative advantage, especially towards the United States, where the values fluctuated between 0.09 and 0.55 throughout the study, indicating specialization and efficiency in the export of blueberries to this market. The conclusions highlight that, although Peru has achieved remarkable growth in its blueberry exports and has demonstrated competitive capabilities, it faces the challenge of effectively diversifying its export markets. Recommendations include expanding the exploration of new markets and improving logistic infrastructure and agricultural practices to foster environmental sustainability, as well as adapting marketing strategies to meet the demands of emerging markets and international regulations.

This systematic review examines digital transformation in post-pandemic supply chains through a bibliometric analysis of literature from 2020 to 2024. Using the PRISMA protocol, we analyzed publications from Scopus, Web of Science, and ScienceDirect databases. Results show that sustainability has become the dominant keyword in digital transformation research, with China, the United States, and India forming the main research triangle. The most influential technologies driving transformation are big data, blockchain, artificial intelligence, and Internet of Things (IoT). Co-citation network analysis revealed three major research clusters: the green cluster led by Gunasekaran and Angappa focusing on supply chain management; the red cluster led by Rahman and Muhammad Saddiq addressing implementation aspects; and the blue cluster led by Calatayud and Rodriguez examining innovation and adaptation. Organizations are shifting from purely operational approaches to more holistic transformations that integrate strategic and organizational dimensions. We identified important research gaps in developing regions and in the integration of emerging technologies with existing systems. This review enhances the understanding of post-pandemic supply chain digitization while providing a framework for future research in this rapidly evolving field.