e3 — Revista de Economia, Empresas e Empreendedores na CPLP

RETHINKING LEARNING IN THE AGE OF ARTIFICIAL INTELLIGENCE:

2026-06-10T05:31:28-05:00

This study examines the transformation of learning processes in higher education within contexts mediated by artificial intelligence (AI), focusing on how students evaluate the quality and reliability of knowledge in algorithmic environments. Using a qualitative approach, 20 semi-structured interviews were conducted with undergraduate students in the final two semesters of their program who use AI tools in their academic activities. The analysis identified differentiated patterns in verification practices, levels of cognitive autonomy, and criteria for evaluating information. The findings suggest that students combine active validation strategies with judgments based on the coherence and immediacy of responses. Uneven bias detection was also observed, revealing limitations in the critical evaluation of AI-generated content. The study concludes that the quality of learning in AI-mediated environments depends in part on situated practices of verification, evaluation, and trust regulation. In this regard, the study proposes the incorporation of “epistemic hygiene,” understood as the systematic development of competencies in critical judgment, comparison, and validation of knowledge generated by algorithmic systems.

CLUSTER PROFILES OF ACTIVE LEARNING AND ACADEMIC ENGAGEMENT IN ECUADORIAN TECHNICAL EDUCATION

2026-07-25T09:23:39-05:00

Most quantitative research on active learning methodologies (ALM) and academic engagement (AE) in higher education compares predefined groups, such as academic programs, using a variable-centered logic that reports average differences between categories the researcher already knows. This study instead asks a person-centered question: do naturally occurring configurations of students exist within a single technical and technological higher education institution, independent of the program they are enrolled in? Using data from 130 students across six academic programs at an Ecuadorian technical and technological higher education institute, hierarchical (Ward's method) and k-means cluster analysis were applied to seven ALM and AE subdimension scores. A three-cluster solution was retained based on silhouette width, the Calinski-Harabasz index, and bootstrap stability (adjusted Rand index = .957 across 200 resamples): a Critically Disengaged profile (n = 13, 10.0%; ALM and AE means near 1.3 of 5), a Moderate-Favorable profile (n = 58, 44.6%; means near 3.9-4.0), and a Highly Engaged profile (n = 59, 45.4%; means near 4.8). Cluster membership was statistically independent of academic program (chi-square = 15.21, df = 10, p = .125) and gender (chi-square = 1.82, df = 2, p = .402), indicating that these profiles cut across, rather than coincide with, the program-based differences documented in a companion comparative study using the same dataset. The findings suggest that a small but identifiable subgroup of students combines low active-learning exposure with low engagement regardless of program, a pattern invisible to between-program comparisons alone, with direct implications for targeted, rather than program-wide, institutional support.

NOVELTY-BASED LEARNING EXPERIENCES AND THEIR INFLUENCE ON STUDENT PRESENCE

2026-07-18T10:27:42-05:00

This study analyses the relationship between novelty and student presence within the framework of experiential learning in higher education. A quantitative approach was adopted, with a non-experimental, cross-sectional, descriptive-correlational design. The sample consisted of 50 students enrolled in the Business Management and Organizational Theories course in an online higher education program. Data were collected using an adaptation of the Experiencing Scale, administered on a five-point Likert scale, and analysed using partial least squares structural equation modelling (PLS-SEM) with ADANCO software. The results show a positive and statistically significant relationship between novelty and student presence (β = 0.9248; p < .001), with high explanatory power (R² = 0.8553). These findings indicate that experiences perceived as novel are associated with higher levels of attention, concentration, and cognitive involvement during learning. It is concluded that the intentional design of innovative educational experiences, such as company visits, can strengthen the connection between theory and practice and foster meaningful learning in online higher education

RELATIONAL GOVERNANCE AND INTER-ORGANIZATIONAL PERFORMANCE: AN IN-DEPTH ANALYSIS OF TRUST, OPPORTUNISM, AND SOLIDARITY IN ECUADORIAN SMES

2026-06-10T05:32:54-05:00

This study analyzes relational governance in micro, small, and medium-sized enterprises (SMEs) in Ecuador, focusing on the paradox of coexistence between trust and opportunism. The objective is to quantify structural dependence and evaluate how institutional voids affect social capital under the lenses of Transaction Cost Economics and Social Exchange Theory. Using a sample of 107 companies, this quantitative correlational research measures trust, opportunism, and solidarity levels toward suppliers, clients, and competitors. Findings reveal extreme structural dependence: 89% of micro-enterprises rely on a remarkably small client group for 80% of their revenue. Furthermore, the coexistence paradox is empirically confirmed, where high levels of opportunism from clients (43.3%) are tolerated through unconditional hyper-solidarity (98.1%) and "calculative trust" acting as safeguard mechanisms against institutional weakness. In horizontal governance, low intra-industry trust (37.3%) hinders coopetition strategies. The article proposes a hybrid relational governance framework integrating digital technologies.

THE COMPUTE DIVIDE: AI-DRIVEN FINTECH, DATA CENTER INFRASTRUCTURE AND DIGITAL DEVELOPMENT IN EMERGING MARKETS

2026-08-28T06:06:11-05:00

The convergence of artificial intelligence (AI), financial technology (fintech), and digital infrastructure is reshaping economic development pathways in emerging markets, with data centers emerging as strategic sovereign assets critical to this transformation. This chapter examines the interplay between AI-driven fintech innovation and data center infrastructure development across Africa, Southeast Asia, and Latin America, analyzing the policy frameworks that enable or constrain this growth. Drawing on evidence from 2025-2026, the analysis reveals a stark digital divide: high-income countries host 77% of global data center capacity, while low-income countries hold less than 0.1%, directly constraining AI innovation capacity in emerging economies. Despite these disparities, significant investments—including NVIDIA's $700 million partnership in Africa, Malaysia's 690MW capacity surge, and Latin America's $7.16 billion market—signal transformative potential. The chapter argues that successful integration of AI and fintech depends on a triad of factors: robust data center infrastructure, enabling regulatory environments, and sustainable energy solutions. Policy recommendations emphasize public-private partnerships, regulatory sandboxes, renewable energy integration, and targeted international investment. The findings underscore that data centers are not merely technical infrastructure but strategic assets that determine whether emerging markets become active participants in the AI-driven digital economy or remain on its periphery.

CHALLENGE-BASED LEARNING AND LEARNING DEVELOPMENT IN HIGHER EDUCATION STUDENTS ENROLLED IN THE HIGHER TECHNOLOGY PROGRAM IN NEGOTIATION AND SALES

2026-07-18T09:49:21-05:00

The aim of this study was to analyze students' perceptions of the contribution of Challenge-Based Learning (CBL) to learning development in higher technological education, considering the dimensions of cognitive learning, critical thinking, academic motivation, meaningful learning, and collaborative learning. A quantitative, non-experimental, descriptive, and cross-sectional research design was adopted. The study involved 50 students enrolled in the Market Research course of the Higher Technology Program in Negotiation and Sales, who completed a market research project for a real organization as part of a challenge-based learning experience. Data was collected using a structured questionnaire consisting of 25 items measured on a five-point Likert scale. Descriptive statistics and Partial Least Squares Structural Equation Modeling (PLS-SEM) were employed to assess both the descriptive results and the psychometric properties of the instrument. The findings revealed favorable evaluations across all learning dimensions, with academic motivation (M = 4.50) and collaborative learning (M = 4.28) receiving the highest scores. The measurement instrument demonstrated satisfactory psychometric properties, with Cronbach's alpha and composite reliability values above 0.93 and Average Variance Extracted (AVE) values exceeding 0.74. Overall, the results suggest that students perceive Challenge-Based Learning as an effective pedagogical approach for promoting learning development through authentic, practice-oriented educational experiences.

SUSTAINABLE FOOD MARKETS BOOSTING TOURISM IN PERU

2026-07-18T10:09:59-05:00

The research aimed to gain a deeper understanding of how traditional food markets can promote tourism in Peru. A non-experimental and descriptive research design was applied in four stages. In the first stage, based on a literature review, a survey was designed and administered to six experts to identify critical variables. In the second stage, a MICMAC matrix was developed to determine the dependence and influence relationships among the identified variables, revealing cultural value and identity, as well as tourism promotion and marketing, as the key factors. In the third stage, five experts were consulted regarding potential solutions, leading to the formulation of 17 strategic actions. These actions were subsequently presented to a group of decision-makers, who prioritized the following: (1) preserving environmental resources and cultural identity, (2) promoting economically and environmentally sustainable practices, (3) modernizing infrastructure while maintaining local identity, (4) promoting and protecting gastronomic identity, and (5) establishing quality control and sanitation programs. In the fourth stage, an IGO matrix was developed, indicating that priority should be given to the strategies of (1) preserving environmental resources and cultural identity and (5) establishing quality control and sanitation programs.

COMPETING ON VOLUME OR VALUE? REPUTATION AND TIMING IN RESTAURANT INDUSTRY

2026-10-10T09:44:11-05:00

By considering a market competition with two asymmetric restaurants, this paper presents a comparative analysis of two dynamic duopoly models tailored to the restaurant industry, integrating principles of industrial organization and game theory. The first framework examines a Stackelberg (sequential) quantity competition where restaurants determine quality levels simultaneously before competing sequentially in output. Conversely, the second framework introduces a sequential quality competition model, wherein the smaller restaurant acts as the quality leader, while subsequent quantity decisions are made simultaneously. Both models examine how restaurant reputation shapes equilibrium quality, output, profits, consumer surplus and social welfare. By comparing two frameworks, we demonstrate that reputation asymmetry is a primary driver of market dominance and strategic positioning, though its impact is conditional on the decision-making sequence. In a Stackelberg quantity model, the high-reputation restaurant systematically dominates the market, leveraging its status to increase both quality and output while capturing superior profits. Conversely, in a sequential quality model, the timing of quality decisions serves as a strategic lever; leadership in quality can partially mitigate reputational disadvantages, allowing smaller restaurants to secure strategic gains under specific conditions. This research highlights the joint impact of reputation and decision-making sequences on market efficiency, contributing new insights to the literature on food industry competition.