The need for strategic alignment within HR management increased managers' concern about individual behavior and how this behavior was related to the achievement of goals. In public management, effectively managing employees' performance has been necessary since Weber's bureaucratic administration. The individual performance appraisal is the right tool to assess employees' competencies. Thus, we proposed the following research question: Which factors, as pointed out by theory, have the most significant influence on the individual performance appraisal process? The quantitative method was applied to answer this question, developing and testing a scale via EFA and a hypothetical model via SEM-CB. The results indicated a scale with 25 items able to access the main points of the IPA process and a hypothetical model with 7 constructs that indicate the influence on employee engagement. The main finding is the significant influence of feedback on the whole process. The main theoretical contribution was the construction of the MIPAS scale, and the practical contribution was to identify the points where managers should focus on improving the IPA process with their subordinates.
Diabetic retinopathy (DR) is a major cause of blindness globally. Effective screening programs are essential to mitigate this burden. This review outlines key principles and practices in implementing DR screening programs, emphasizing the roles of technology, patient education, and healthcare system integration. Our analysis highlights key principles for establishing successful screening initiatives, including the importance of regular screenings, optimal intervals, recommended technologies, and necessary infrastructure. We emphasize the roles of healthcare providers, patients, and policymakers in ensuring the effectiveness of these programs. Our recommendations aim to support the creation of robust policies that mitigate the impact of DR, ultimately improving public health outcomes and reducing the incidence of blindness due to diabetic retinopathy.
Introduction: Chatbots are increasingly utilized in education, offering real-time, personalized communication. While research has explored technical aspects of chatbots, user experience remains under-investigated. This study examines a model for evaluating user experience and satisfaction with chatbots in higher education. Methodology: A four-factor model (information quality, system quality, chatbot experience, user satisfaction) was proposed based on prior research. An alternative two-factor model emerged through exploratory factor analysis, focusing on “Chatbot Response Quality” and “User Experience and Satisfaction with the Chatbot.” Surveys were distributed to students and faculty at a university in Ecuador to collect data. Confirmatory factor analysis validated both models. Results: The two-factor model explained a significantly greater proportion of the data’s variance (55.2%) compared to the four-factor model (46.4%). Conclusion: This study suggests that a simpler model focusing on chatbot response quality and user experience is more effective for evaluating chatbots in education. Future research can explore methods to optimize these factors and improve the learning experience for students.
In order to overcome negative demographic trends in the Russian Federation, measures to stimulate the birth rate have been developed and financed at the federal and sub-federal levels. At the moment, on the one hand, there is a tendency to centralize expenditures for these purposes at the federal level, on the other hand, the coverage of the subjects of the Russian Federation, which introduce sub-federal (subnational) maternity capital (SMC), is expanding. The study was recognized to answer the question: whether the widespread introduction of SMC is justified, whether the effect of its use depends on the level of subsidization of the region and the degree of decentralization of expenditures.
This research evaluates the regionalization of tourism in Hungary, revealing the breakdown of the national gross domestic product (GDP) of tourism. It also explores the density, spatial variations, and features of these indicators. A multimodal approach is used to evaluate the competitiveness of Hungarian counties, and the distribution of these tourism regions is analyzed using the tourism penetration index. Furthermore, regional GDP is calculated for the whole territory of Hungary. The study identifies significant regional disparities in tourism competitiveness, highlighting Budapest-Central Danube as the most competitive region and Lake Balaton as underperforming despite its potential. The research contributes by providing a detailed regional GDP analysis and emphasizing the need for targeted policy interventions to enhance tourism development across all regions.
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