International Journal of Professional Business Review
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USE OF ARTIFICIAL INTELLIGENCE TOOLS AT A TECHNOLOGICAL UNIVERSITY IN THE EAST OF THE STATE OF MEXICO
Full text linkObjective: This study identify the impact of AI usage among students at the Instituto Tecnológico de Estudios Superiores de Chalco, Mexico, in order to determine the most commonly used academic activities for learning and the effect on academic performance.
Theoretical Framework: The use of Artificial Intelligence (AI) as a tool for university students is becoming increasingly common, drawing the attention of various authors, as noted by Gamboa et al. (2025). Despite advantages such as personalized learning, increased efficiency in administrative tasks, and improved communication, there are also disadvantages, including data privacy concerns, excessive dependence on AI, and ethical considerations.
Method: A convenience sample was selected based on the inclusion criteria: university students from the Technological Institute of Chalco, men and women aged 17 to 34, who were willing to participate in the study. Exclusion criteria were: students who did not wish to participate in the survey and those who did not answer the instrument correctly. A total of 238 students were considered, corresponding to 12% of the population. This sample size is based on the Central Limit Theorem. The data collection instrument was applied, which corresponds to a survey designed by the working group and consists of 19 questions divided into three sections.
Results and Discussion: As a result, 238 responses were collected, representing 12% of the total student body, with 99.6% of respondents reporting that they use AI tools. The most frequent uses include information retrieval, text translation, problem-solving, and image generation. While the majority of respondents did not report perceiving an impact on their academic formation, some highlighted the importance of independently developing ethical and moral values to ensure the responsible use of AI. We conclude that AI is undeniably a support tool in managing the teaching-learning process, though it necessitates the promotion of ethical and moral values. Students should be encouraged to use these tools to strengthen their academic and professional training, while avoiding increased dependency on technology, fostering effort, and complementing—rather than replacing—other learning tools.
Research Implications: This research provides an in-depth analysis of the use and adoption of AI tools, offering evidence on how these technologies are transforming educational processes. The findings serve as a foundation for institutional policy-making aimed at promoting teacher training, digital infrastructure, and curriculum design aligned with 21st-century competencies.
Originality/Value: This is a pioneering study that addresses, from a contextualized and applied perspective, the integration of AI tools in a technological university located in eastern Mexico—a region that faces specific challenges in terms of infrastructure and access to emerging technologies. The originality of the study lies in its combination of quantitative and qualitative analysis to evaluate not only the extent of AI usage, but also students’ perceptions, the barriers they face, and the opportunities they identify. The value of this research lies in its provision of key inputs for designing educational digital transformation strategies adapted to regional contexts, helping to reduce technological gaps and improve the quality of education in technological higher education institutions
MONITORING AND EVALUATION PLANNING AND PERFORMANCE OF GLOBAL PARTNERSHIP FOR EDUCATION PROJECTS IN UGANDA
Full text linkObjective: The objective of this study was to examine how Monitoring and Evaluation Planning influence performance of global partnerships for education project.
Theoretical Framework: The theories that anchored the study were (i) System Theory: which explains how interconnected components within GPE projects influence overall performance. (ii) Results-Based Management Theory which emphasizes outcome driven planning and accountability. (iii) Organizational Learning Theory highlights continuous improvements through knowledge acquisition and adoption, ensuring that monitoring and evaluation ehance project effectiveness and sustainability.
Method: The empirical study was conducted in Bukedea and Katakwi districts, Uganda. It employed a descriptive cross-sectional survey and correlational design, using simple random sampling and purposive sampling to select 198 respondents from 10 schools based on Krejci and Morgan (1970) data table. Pearson’s Product Moment correlation (r), simple regression and multiple regression analysis were used to generate inferential statistics.
Results and Discussion: The results were; r = 0.499, R2=0.249, F (1, 69) = 22.525, p < 0.05, therefore, H0 was rejected and concluded that Monitoring and evaluation Planning has a significant influence on Performance of Global Partnership for Education projects. Work planning had the greatest impact on GPE project outcomes, according to inferential statistics, which also found that budgeting and staffing were important contributors. As a result, it was inferred that schools with better work planning would profit more than those without. There is therefore need to develop a clear understanding of M & E Planning diversity at the schools in Bukedea and Katakwi districts. The study concludes that improving the success of GPE programs in Uganda necessitates addressing all areas of monitoring and evaluation methods.
Results Implication: The recommends that GPE secretariat, district authorities, and SMC members should diversify M&E planning in terms of work planning, budget planning, and staff planning. The study further recommends that since the GPE project teams should be composed of diverse employees, GPE’s professional certification standards should include an assessment of project success based on the inclusion of a policy to that effect.
Originality/Value: This study provides original insights by empirically confirming the significant influence of Monitoring and Evaluation Planning on Global Partnership for Education project performance, guiding policy improvements for enhanced success
MONITORING AND EVALUATION PRACTICES AND PERFORMANCE OF GLOBAL PARTNERSHIP FOR EDUCATION PROJECTS IN UGANDA: THE ROLE OF ORGANIZATIONAL CULTURE
Full text linkObjective: The significance of the Project Monitoring, Evaluation and Quality of Education is a topical theme because project performance has been a concern to project managers and project stakeholders across the world. The aim of this study was to establish how organizational culture moderates the relationship between Monitoring and Evaluation practices and performance of Global Partnership for Education projects in Uganda.
Theoretical Framework: The theories that anchored the study were (i) System Theory: which explains how interconnected components within GPE projects influence overall performance. (ii) Results-Based Management Theory which emphasizes outcome driven planning and accountability. (iii) Organizational Learning Theory highlights continuous improvements through knowledge acquisition and adoption, ensuring that monitoring and evaluation enhance project effectiveness and sustainability.
Method: A pragmatism research paradigm integrating positivist and interpretivist perspectives was adopted, utilizing a mixed-methods approach. The study employed a descriptive cross-sectional design, incorporating correlational and survey research methods. A sample of 198 respondents, drawn from a target population of 260 school staff using the Krejcie & Morgan (1970) table, included teachers, school management committee members, and GPE officials. Data were collected through questionnaires, focus group discussions, and key informant interviews. Quantitative data were analyzed using descriptive and inferential statistics, while qualitative data underwent thematic content analysis.
Results and Discussion: The results were: R = 0.486, R² = 0.236, F (5, 232) = 14.316, p < 0.05, therefore, H₀ was rejected, and it was concluded that organizational culture significantly moderates the relationship between monitoring and evaluation practices and the performance of Global Partnership for Education.
Results Implication: The implication of the result is that organizational culture plays a key role in enhancing the effectiveness of monitoring and evaluation (M&E) practices in improving the performance of Global Partnership for Education (GPE) projects. Since the study found that organizational culture significantly moderates the relationship between M&E practices and project performance, it suggests that a supportive organizational culture strengthens the impact of M&E activities on project outcomes. Therefore, for GPE projects to achieve better performance, it is important to foster a positive organizational culture that aligns with M&E practices.
Originality/Value: This study delivers new perceptions by empirically confirming the substantial influence of organizational culture and how it moderates the relationship between Monitoring and Evaluation practices on Global Partnership for Education project performance, guiding policy improvements for enhanced success
MANAGEMENT OF ROAD INTERSECTION AND PERFORMANCE OF INTELLIGENT TRAFFIC CONTROL SYSTEMSNAIROBI COUNTY, KENYA: DOES TRAFFIC LEGAL FRAMEWORK MATTER?
Full text linkObjective: The study aimed to examine the moderating role of traffic legal framework on the relationship between road intersection management and the performance of Intelligent Traffic Control Systems (ITCS) in Nairobi County, Kenya.
Theoretical Framework: This study is anchored on systems theory, which explains how interconnected components within traffic management influence ITCS performance; regulatory governance theory, which emphasizes the role of legal frameworks in ensuring compliance and enhancing system effectiveness; and the Technology Acceptance Model (TAM), which highlights the adoption and impact of ITCS based on regulatory and infrastructural support.
Methods: A pragmatic research paradigm was adopted, utilizing a mixed-methods research design. The study targeted a population of 942 traffic stakeholders. Primary data collection methods included key informant interviews and structured questionnaires. Both qualitative and quantitative data were collected analyzed using descriptive and inferential statistics.
Results and Discussion: The model was statistically significant (R² = 0.531, F = 13.64, p < 0.05), indicating that 53.1% of the variance in ITCS performance was explained by the independent variables and their interaction. Road intersection management positively and significantly predicted ITCS performance (β = 0.017, p < 0.05). Similarly, the traffic legal framework had a significant positive effect on ITCS performance (β = 0.12, p < 0.05). The interaction term (β = 0.17, p < 0.05) confirmed that a robust traffic legal framework enhances the impact of intersection management on ITCS efficiency.
Research Implication: The findings highlight the critical role of a well-structured traffic legal framework in improving ITCS effectiveness. Strengthening traffic law enforcement, conducting periodic legal reviews, and implementing data-driven intersection management strategies can enhance urban mobility. A holistic approach that integrates legal, infrastructural, and technological components is necessary to improve traffic flow, travel time efficiency, and pedestrian control in Nairobi County.
Originality/Value: This study contributes to the literature by demonstrating how regulatory frameworks moderate the impact of road intersection management on ITCS performance. It provides valuable insights for policymakers and urban planners on optimizing traffic management strategies to enhance intelligent traffic control efficiency in urban settings
AVALIAÇÃO DO SISTEMA DE ILUMINAÇÃO EM UM EDIFÍCIO UNIVERSITÁRIO – ASPECTOS DA EFICIÊNCIA ENERGÉTICA
Full text linkObjetivo: Este estudo tem como objetivo propor a Etiqueta Parcial Nacional de Conservação de Energia em um edifício universitário, com o intuito de avaliar o nível de eficiência energética do sistema de iluminação.
Referencial Teórico: O trabalho foi fundamentado nas publicações do PBE (Programa Brasileiro de Etiquetagem), com finalidade de combater o desperdício de energia e incentivar o uso racional da energia nas edificações residenciais, comerciais, públicas e de serviços.
Método: A metodologia adotada compreendeu a caracterização do local de estudo, análise do desempenho do sistema de iluminação artificial e aplicação do método prescritivo do RTQ-C. A coleta de dados foi efetivada por visitas in loco, levantamento iconográfico e análise dos projetos executivos.
Resultados e Discussão: A potência instalada total do edifício não ultrapassou o limite para nível A, comparando-se com as DPIL. Entretanto, quando da aplicação dos pré-requisitos, o nível foi rebaixado para B, em função do ambiente “circulação” não possuir desligamento automático, não atendendo ao pré-requisito do RTQ-C. Caso seja adotado o sistema de desligamento automático, a classificação será otimizada.
Implicações da Pesquisa: As implicações práticas e teóricas desta pesquisa são discutidas, fornecendo insights sobre como influenciar práticas no campo da eficiência energética das edificações, abrangendo desde a economia de energia até a utilização de recursos naturais, contribuindo para a sustentabilidade ambiental.
Originalidade/Valor: Apresenta-se uma contribuição científica e social, evidenciando a difusão da sustentabilidade ambiental em edifícios, por meio de estudos que abranjam a preocupação energética, conscientizando o profissional atuante para que este seja personagem importante na preservação do meio ambiente
THE ROLE OF PROJECT TEAM INTEGRATION ON TIME, COST, SITE DISPUTE AND QUALITY DURING THE EXECUTION OF COURT BUILDINGS IN KENYA
Full text linkBackground: Project team integration is a critical characteristic influencing the effective execution of projects. However, court-building projects in Kenya, funded by the World Bank and the Government, have experienced significant delays and cost overruns.
Objective: This study hypothesizes that project team integration does not significantly affect the execution of court buildings in Kenya concerning time, cost, site disputes, and quality.
Methods: A mixed-methods research strategy was employed, incorporating questionnaires, interview guides, and document content analysis. The validity and reliability of the results were verified using principal component analysis and Cronbach alpha approaches. Descriptive statistics analysed quantitative data, while correlation and regression analyses were used for inferential statistics.
Results: The findings indicated that project team integration significantly influenced project execution in terms of time but did not have a notable impact on cost, site disputes, or quality.
Conclusion: This study highlights the importance of team integration as a key driver for efficiency and success within the construction industry. By fostering collaborative and cohesive team environments, organizations can achieve substantial improvements in project scheduling and timely completion, ultimately ensuring the successful delivery of high-quality infrastructure projects.
Implications: The research provides valuable insights for project management practitioners, policymakers, scholars, and stakeholders involved in court construction implementation in Kenya
VENERABLE LESSONS FROM GLOBALIZATION: THE IMPACT OF ARTIFICIAL INTELLIGENCE (AI) ON LIBYAN HUMAN RESOURCE (HR) ACTIVITIES
Full text linkObjective: artificial intelligence (AI) has profoundly influenced the landscape of human resource (HR) activities. This transformation underscores the critical need for a dialogue between Libyan technological advancements and HR strategies to foster an inclusive and adaptive workforce capable of thriving in a globalized economy.
Theoretical Framework: the literature review had demonstrated a comprehensive grasp of existing knowledge by addressing the challenges and ethical considerations associated with AI integration by Libyan human resource (HR).
Method: inductive approach has allowed the authors to gather data from the literature about how Ai impact Libyan human resource (HR), which were able to later compare and support with the help of established theory from the field.
Results and Discussion: To fully leverage the potential of AI, HR professionals must focus on developing technical skills related to emerging technologies while embracing data analytics to inform strategic HR initiatives like workforce planning.
Results Implication: By prioritizing human capital development through AI applications in HRM, Libya can work towards adopting new technologies, enabling a smoother transition into a more digitally driven HR landscape
PHISH OR LEGIT? QUANTIFYING WEB-BASED THREAT SIGNALS THROUGH PREDICTIVE ANALYTICS AND FEATURE ATTRIBUTION
Full text linkObjective: This study investigates web-based threat signals using predictive analytics and feature attribution to determine whether a webpage is phishing or legitimate.
Theoretical Framework: The research is grounded in Protection Motivation Theory (PMT), which offers a behavioral lens to interpret phishing indicators. PMT connects web features to users’ cognitive threat and coping appraisals, providing a theoretical rationale for selecting and organizing features.
Method: A logistic regression model, regularized with L1 (Lasso), was developed for its interpretability and ability to handle feature sparsity and convergence issues. Using a dataset of 11,055 labeled websites, the model incorporates three core feature sets: structural (e.g., IP-based URLs, SSL status), behavioral (e.g., redirection, form handler anomalies), and domain metadata (e.g., traffic rank, Google indexing).
Results and Discussion: The model rejects the null hypothesis that website-level features are non-predictive, confirming that structural, behavioral, and metadata-based signals significantly distinguish phishing from legitimate sites. This thematic decomposition supports both the conceptual framework and the empirical model design.
Research Implications: The findings offer actionable insights for cybersecurity professionals, especially those in regulated industries. The model enhances detection capability while maintaining transparency, crucial for compliance and risk management.
Originality/Value: This study contributes to literature by integrating PMT into a predictive modeling framework for phishing detection, an approach that bridges behavioral theory and machine learning. Its originality lies in aligning cognitive appraisal theory with interpretable statistical methods. The results are highly relevant to cybersecurity practice, offering scalable, transparent tools that support real-time decision-making and inform strategic defenses in high-risk sectors
IMPACTO EN LAS DECISIONES DE CONSUMO: ANÁLISIS COMPARATIVO DE PRECIOS AL CONSUMIDOR DE LA CANASTA BÁSICA EN MÉXICO
Full text linkObjetivo: Analizar las variaciones en los precios al consumidor de la canasta básica en México y su capacidad de influir en la toma de decisiones informadas sobre la compra de bienes y/o servicios según los grupos y ámbitos utilizados por instituciones públicas mexicanas.
Marco Teórico: Se analiza indicadores económicos clave para medir la inflación y su efecto en el poder adquisitivo en México. Se consideran factores como la oferta y demanda, política monetaria (Cavazos y Rivas, 2009), comercio internacional e impactos de eventos globales (Almagro, 2007; Gopinath, 2021; Alvarado, 2022; Hernández et al., 2023) Asimismo, se incorporan teorías motivacionales que destacan la importancia de cubrir necesidades básicas como fundamento para el diseño de políticas públicas eficaces.
Método: Se utilizó un diseño no experimental, transeccional correlacional con alcance descriptivo. Se aplicó un análisis de varianza (ANOVA) de dos vías con interacción para estudiar cómo las combinaciones de grupos y ámbitos de bienes y servicios (variable independiente) ofertados por diferentes empresas afectan el valor de la Canasta de Consumo Mínimo (variable dependiente).
Resultados y Discusión: El impacto del grupo y ámbito de bienes sobre el valor de la CCM depende del nivel de clasificación geográfica de la empresa ofertante. Las diferencias en precios entre organizaciones influyen en las decisiones de compra, permitiendo a los consumidores ajustar sus patrones y buscar alternativas económicas.
Implicaciones de la investigación: El análisis de precios en la canasta básica identifica tendencias de costos según contexto geográfico, facilitando el diseño de estrategias comerciales efectivas y una mejor respuesta a las necesidades del consumidor.
Originalidad/Valor: El estudio ofrece una visión integral de los costos de la canasta básica en México, considerando la variabilidad geográfica y criterios institucionales, con el fin de optimizar decisiones familiares y ampliar el conocimiento del mercado
MAXIMIZING MARKETING IMPACT THROUGH DATA-DRIVEN SEGMENTATION WITH PCA AND CLUSTERING
Full text linkObjective: This study aims to improve customer segmentation in marketing by integrating Principal Component Analysis (PCA) with clustering techniques. The main goal is to overcome challenges posed by high-dimensional customer data to generate actionable segments for targeted marketing.
Theoretical Framework: The research builds upon established segmentation methods in marketing and machine learning. It focuses on the synergy between PCA for dimensionality reduction and clustering algorithms (K-means and Agglomerative Clustering) for pattern detection in customer behavior. Key references include works on data-driven segmentation and dimensionality reduction.
Method: The study used a real-world dataset containing socio-demographic and purchasing behavior variables. After preprocessing and normalizing the data, PCA was applied to reduce dimensionality, followed by K-means and Agglomerative Clustering for segmentation. Cluster performance was evaluated using Silhouette Scores and Sum of Squared Errors.
Results and Discussion: Three customer profiles emerged: cost-sensitive shoppers, high-income bulk buyers, and niche wine enthusiasts. Clustering on PCA-transformed data significantly improved results, with K-means reaching a Silhouette Score of 0.512. These findings highlight the value of dimensionality reduction in segmentation and reveal distinct behavior patterns, informing personalized marketing strategies.
Research Implications: This work offers practical guidelines for businesses to design targeted campaigns, allocate resources intelligently, and enhance customer retention. It also proposes a replicable methodological pipeline for researchers and practitioners.
Originality/Value: The study contributes a robust hybrid approach combining PCA and clustering for real-world marketing segmentation. Its originality lies in the clear demonstration of how dimensionality reduction enhances the interpretability and performance of clustering in complex customer datasets