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Descriptive Framework for Project Management for the Implantation of Enterprise IT Applications in SMEs
Full text linkAdopting an Enterprise IT Application (EITA) is a complex process that requires effective management to ensure success. Studies show that failure rates for such projects range from 30% to 70%, with 57% of implementations taking longer than expected, 54% exceeding budget, and 41% failing to achieve the anticipated benefits. This paper proposes a framework for managing EITA implementation projects in small and medium-sized enterprises (SMEs). The framework was developed by coding and analyzing interviews with 18 professionals who have experience with EITA implementations. The interviews were transcribed and analyzed using the qualitative analysis software MaxQDA. The outcome is a descriptive framework that outlines the necessary activities for each phase of an EITA implementation project, taking into account the specific limitations and constraints of SMEs. This framework is designed to be a practical tool for project managers overseeing EITA implementations in SMEs, as well as for professionals new to this type of project, providing them with a foundational structure for effective project management.
Corporate social responsibility and the metaverse in the digital era: implications for firm performance
Full text linkThe metaverse can be generally described as a coherent, persistent and interrelated virtual ecosystem, integrating and combining virtual reality (VR), augmented reality (AR), blockchain, and artificial intelligence (AI) technologies to facilitate real-time social and economic connections. Thus, the implementation of the CSR in the metaverse is a sustainable business strategy perspective that is transformational. Companies can use immersive technologies to provide CSR experiences in new formats- virtual volunteering, tokenized philanthropy, simulations of sustainability with a digital twin, or community hubs around the world. The study acknowledged that Digital transformation is growing at a very high rate in Nigeria, which also opens the opportunity to innovate CSR, although the full-scale implementation of the metaverse is in its infancy. The study fingdings revealed that the CSR in the metaverse is not merely an Internet expansion of conventional CSR but more of a disruptive reconfiguring. Metaverse-based CSR allows interactive, immersive, and decentralized ways of communication, unlike traditional CSR campaigns, which take place in a physical or two-dimensional virtual environment. It was concluded in the study that CSR in the metaverse is a strategic opportunity, as well as an ethical imperative. When properly designed, it may not only allow firms to perform better, but also play a significant role in digital equity and sustainable development in the new virtual economy. It was recommended in the study that firms must make sure that CSR activities in the metaverse are material, open, or consistent with long-term sustainability objectives
Content validation of the questionnaire to measure knowledge, attitudes and practices (KAP) in postpartum women based on the Colombian maternal-perinatal route
Full text linkIntroducción: La ruta de atención materno-perinatal en Colombia busca garantizar la atención integral de las mujeres durante el embarazo, el parto y el puerperio. Para fortalecer esta atención, se requieren herramientas que recopilen los conocimientos, actitudes y prácticas (CAP) de las mujeres en el puerperio. La validación de estas herramientas permite el desarrollo de intervenciones eficaces que contribuyan a la reducción de la morbilidad y la mortalidad materna y perinatal.Objetivo: Validar cuestionario para medir los conocimientos actitudes y practicas (CAP) en mujeres puérperas basado en la ruta materno – perinatal colombiana.Metodología: Estudio descriptivo de validación de aspecto y de contenido de cuestionario para medir los conocimientos actitudes y practicas (CAP) basado en la ruta materno – perinatal, se distribuye en tres fases fase 1: revisión de literatura y diseño de la encuesta tipo CAP fase 2: validación contenido por 5 expertos.Resultados: Las pruebas de compresibilidad aplicadas a los 5 expertos reportaron una validez de contenido aceptable ya que CVC está por encima de 0.58.Conclusión: El cuestionario para medir los conocimientos actitudes y practicas (CAP) en mujeres puérperas basado en la ruta materno – perinatal para es válido para la aplicación clínica y ambulatoria de las mujeres que reciben atención en el marco de la ruta materno perinatal en el contexto colombiano. Este instrumento es un insumo para futuras investigaciones que propendan fortalecer las acciones para evitar la morbimortalidad materna-perinatal.
Breast Lump Assessment: An IoT-Integrated Framework with Advanced Localization Techniques
Full text linkInternet of Things (IoT) influences many areas such as healthcare, transportation, agriculture, industry control, environment monitoring, and water management. Healthcare is a major area in which the IoT enables a more personalized form of healthcare through smart healthcare systems. Breast cancer is the second leading cause of death among women globally, and its incidence is increasing every year. Early-stage detection of breast cancer is an important research challenge in the medical field. The aim of this article is to design an IoT - Integrated framework with advanced localization techniques for breast lump assessment. Through the proposed framework, breast lumps are monitored periodically using sensor embedded wearable jacket. The lump position and its depth in the breast are evaluated using localization techniques in sensor organization. Model outcome is analysed for six periodic tests data. Results evidence that periodic monitoring of breast health using the designed framework is effective to fix abnormal lumps at the early stage
Educational Performance and the Role of E-Learning, Digital Leadership, and Digital Innovation: A Study of High Schools in Jordan in the Context of 5G
Full text linkIntroduction: This study examines the impact of e-learning, digital leadership, and digital innovation on educational performance in high schools, focusing on Jordan\u27s transition to 5G technology. It explores how these factors enhance educational outcomes in a developing country facing technological and infrastructural challenges.Methods: A quantitative approach was used, collecting data from 385 high school teachers in Jordan through a cross-sectional survey. The study employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the relationships between e-learning, digital leadership, digital innovation, and educational performance.Results: The findings indicate that e-learning significantly improves educational performance by offering flexible and interactive learning environments. Digital leadership is crucial for guiding digital transformation and fostering innovation, while digital innovation, including AI, VR, and AR, enhances teaching methods and student engagement, leading to better educational outcomes.Conclusions: The study concludes that integrating e-learning platforms, effective digital leadership, and digital innovation is essential for improving high school performance. Policymakers and school administrators should invest in digital infrastructure, provide teacher training, and promote a culture of innovation to prepare students for a technology-driven future. This research offers valuable insights for enhancing educational practices in developing countries like Jordan
Forecasting Temperature of Earth Surface in Sragen Regency Using Semiparametric Regression Based on Penalized Fourier Series Estimator
Full text linkSragen regency that is located in Central Java Province of Indonesia, is one of the areas that feels the direct impact of the high earth surface temperature. The various sectors in Sragen regency, including agriculture, health, and the environment are affected by the high temperature of the earth\u27s surface. The Sragen regency is geographically dominated by agricultural areas, which are very vulnerable to extreme earth surface temperatures. This has a direct effect on agricultural productivity and the availability of water for irrigation. This study examines the use of a semiparametric regression model with a Penalized Least Squares (PLS)-based Fourier Series estimator to analyze the relationship between earth surface temperature and relative humidity in Sragen regency. The combining parametric and nonparametric components, the model effectively addresses complex climate data patterns. A dataset of 100 observations was analyzed under three training data scenarios N = 70, N = 80, and N = 90, yielding optimal Fourier coefficients of 1, 1, 1 and lambda values of 0.035, 0.028, and 0.02. The resulting minimum Generalized Cross Validation (GCV) values of 0.3534871, 0.3711413, and 0.3918924. This model successfully made good predictions for testing data sizes of 30, 20, and 10, with MAPE values of 1.606545, 1.518221, and 1.018482. These results underscore the model\u27s ability to capture the inverse relationship between earth surface temperature and relative humidity. The study highlights the Fourier-based semiparametric approach\u27s effectiveness in dynamic scenarios and recommends applying it to other climate variables or regions to further evaluate its adaptability and robustness
The Effects of (rs3765467) polymorphism in the gene encoding GLPR1 on Serum GLP1 Level and Response to Sitagliptin in Combination with Metformin Therapy in Iraqi Type 2 Diabetics Patients
Full text linkThe dipepdityl peptidase-4 (DPP-4) inhibitors, which prevent incretin degradation, have become popular oral hypoglycemic agents for type 2 diabetes. Despite the wide use of DPP-4 inhibitors, little is known of clinical and pharmacogenomics factors that specifically associated with DPP-4 inhibitor treatment response. Meanwhile, a genetics studies identify important factors involved in the progression of diabetes disease, and identify individuals at risk of developing T2DM. Purpose of present study is to assess the possible association of (rs3765467) polymorphism in the gene encoding GLP1R with serum level of GLP1 and glycemic response for the treatment with sitagliptin in combination with metformin in Iraqi diabetic patients. The results indicated that SNP (rs3765467) was not detected in our study population of 90 individuals. However, Sanger sequencing had successfully identified three SNPs for the study population, including rs3765466, rs910163& (rs910162), located within the same region of the target SNP, rs3765467, in the gene encoding GLP1R. Furthermore, these SNPs (rs3765466), (rs910163) & (rs910162) show no significant effect on the response to the treatment based on HbAIc level (patients with HbA1c of less than or equal to 7.0% are classified as clinical responders, while those with HbA1c greater than 7.0% are classified as non-responders), but these SNPs significantly affect the serum GLP1 level. Additionally, (rs910163) & (rs910162) genotypes were significantly associated with serum creatinine levels, suggesting a potential role of the (rs910163) & (rs910162) variant in renal function regulation.
The Effect of the Project Citizen Augmented Reality (PjCAR) Learning Model on Elementary School
Full text linkIntroduction: The study examines the effect of the Project Citizen Augmented Reality (PjCAR) learning model on students\u27 national awareness competence. The research was conducted in Langsa, Aceh, with fifth-grade elementary school students as the sample.Methods: A quasi-experimental research design was employed, and data were collected using tests, questionnaires, observations, and documentation. The validity and reliability of the data were tested, followed by prerequisite tests (homogeneity and normality) and hypothesis testing (t-test and n-gain test).Results: The results showed a significance value (2-tailed) of 0.001, smaller than 0.05. The average national awareness competence, comprising national sentiment and national spirit indicators, increased from 148.11 to 164.52 after implementing the PjCAR model. Meanwhile, cognitive understanding of national awareness improved from 66.30 to 80.43.Conclusions: These findings indicate a significant difference between pretest scores (before treatment) and posttest scores (after implementing the PjCAR model). This also suggests that students\u27 national awareness competence improved after applying the PjCAR model in Pancasila Education for fifth-grade students.
Impact of generative artificial intelligence on the decision-making of university students in the health sciences: A transversal study
Full text linkAdvanced AI systems, such as those in their generative phase, cause uncertainty among higher education students about their functionality and the academic level they may have when interacting with IAGs such as ChatGPT. The study aimed to examine how interaction with AI tools, such as generative language models, influences students\u27 ability to select learning strategies, manage academic resources, and make informed decisions during their professional training. A quantitative, descriptive, non-experimental approach was used. The initial population was 500 students from the Faculty of Medicine of two recognized higher education institutions in Ecuador, after applying certain inclusion criteria through random convenience sampling. The results showed that generative artificial intelligence significantly influences the academic decision-making of medical students, with scalability and efficiency standing out as key factors. In contrast, user satisfaction showed an inverse relationship, and institutional integration was not a determining factor. It is concluded that the impact of these tools depends on their strategic functionality rather than their superficial perception
Implementation of GWR and MGWR in Modelling Gross Regional Domestic Product (GRDP) in East Java
Full text linkIntroduction: One important indicator of national development success is the increase in real Gross Regional Domestic Product (GRDP), which reflects regional economic performance. The GRDP growth rate, calculated as the percentage increase from the previous year, serves as a critical measure for evaluating economic progress. In the case of East Java, identifying the factors influencing GRDP growth is essential to support more effective and region-specific policy-making. This research aims to analyze those influencing factors using spatial regression methods.Methods: In this research, Geographically Weighted Regression and Mixed Geographically Weighted Regression methods are used to model the factors that influence the growth rate of GRDP in East Java.Results: Based on the results of the research that has been analyzed, it is known that the GWR model has an AICc score of 136,646, while the MGWR model has an AICc score of 134,3184, so it can be concluded that the MGWR method with a fixed gaussian kernel has better performance in modeling the factors that influence the GRDP growth rate in East Java.Conclusions: Globally, the General Allocation Fund and the Open Unemployment Rate significantly affect GRDP growth. Locally, the Percentage of Poor Population, Average Minimum Wage, Local Original Income, and Production Agglomeration show significant effects in specific areas. On the other hand, the Human Development Index and Population Density do not exhibit significant influence on GRDP growth, either globally or locally