This article investigates the expansion of organizational learning capabilities (OLC) and its growing utilization in the organization in order to identify whether OLC affects the relationship between training and development and organizational performance. This study further explores the correlation between organizational learning capabilities and organizational performance, offering insight into the different understandings of organizational triumph related to OLC. This research was conducted via survey method and data were collected from five service industries in Khyber Pakhtunkhwa (KP), Pakistan. A data sample of 300 employees was analyzed using quantitative approaches, such as descriptive statistics and partial least squares structural equation modeling (PLS-SEM). The results of the article addressed issues that are related to human capital regarding OLC, including training and development aspects which were not discussed by the literature in the past. The main findings of this paper are the formulation of an empirically and theoretically supported model related to the effect of OLC on the relationship between training and development and organizational performance. On the other hand, this study signifies that OLC is a better instrument for enhancing organizational performance, as well as in dealing with today’s indeterminate and continuously challenging economic atmosphere. This study is the first of its nature to shed light on training and development, organizational learning capabilities, and organizational performance in the service sector of KP, Pakistan.

This study examines the impact of digital technologies on the economic growth of Central Asian and European countries. With the increasing integration of digital technologies globally, understanding their economic implications is crucial, particularly in diverse regions like Central Asia and Europe. The research employs the Autoregressive Distributed Lag (ARDL) model, a robust econometric method suitable for analyzing both short-term and long-term relationships in time series data. This approach utilizes 22 years of data from the World Bank, focusing on variables such as internet usage, sanctioned phone subscriptions, and mobile cellular subscriptions, and their impact on GDP per capita. The ARDL model's findings reveal a positive correlation between the increase in digital technology usage (specifically internet users and phone subscriptions) and GDP per capita in Central Asian and European countries. A notable increase in GDP per capita is observed with the rise in internet users and sanctioned phone subscriptions, whereas the impact of mobile cellular subscriptions, though positive, is comparatively smaller. The results suggest that enhanced digital connectivity, as evidenced by increased internet usage and phone subscriptions, significantly contributes to economic growth. This underscores the importance of digital inclusion and infrastructure development in driving economic development in diverse geographical regions. The study highlights the significant role of digital technologies in economic growth, providing empirical evidence that underscores the need for policies and initiatives to promote digital inclusion and infrastructure development in Central Asia and Europe.

This research article explores the Impact of Digital Technologies on the Labor Market of Uzbekistan" using a comprehensive and robust econometric analysis. Drawing upon the State Statistics Agency's data from 2015 to 2022 for 13 regions in Uzbekistan, the study provides an in-depth examination of how digital technologies have influenced the country's labor market dynamics. Utilizing a total of 104 observations, we applied advanced econometric models, including the Pooled OLS estimator (POLSE), Fixed effects estimator (FEE), and Random effects estimator (REE), to assess the impacts accurately. Key analytical techniques employed in this study include the evaluation of the Gauss-Markov conditions and the implementation of Breusch-Pagan, Shapiro-Wilk, and Durbin Watson tests within the Pooled OLS framework. Additionally, our approach involved a thorough exploration of the relationships between dependent and independent variables, supported by the analysis of correlation linkages and graphical matrix methods, as well as a review of the state of descriptive statistical processes. A critical aspect of our methodology was identifying the most suitable model for our analysis. This involved using the Hausman test to effectively differentiate and select between the Fixed effects estimator and Random effects estimator models. Our findings provide significant insights into how digital technologies have reshaped the labor market in Uzbekistan, offering valuable implications for policymakers, businesses, and scholars in the field of labor economics and digital transformation.

The purpose of this study was to determine whether there is a difference in scientific literacy between students who follow the inquiry learning model and students who follow the STAD cooperative learning model to determine the difference between scientific literacy due to students' achievement motivation to describe the interaction between the learning model and achievement motivation on students' scientific literacy. This study used a Posttest-Only Control Group Design with a two-factor analysis. The population in this study were fifth-semester PGSD students at HKBP Nommensen University of Pematangsiantar, in 2024/2025 Academic Year, with totaling 186 students, which sample of 124 students determined by using Simple Random Sampling technique for the class. Data were obtained using the achievement motivation instrument and the science literacy test. Data analysis was carried out using two-way analysis of variance. The study found a significant difference in scientific literacy between students who followed the Inquiry Learning Model and those who followed the STAD Cooperative Learning Model, with a p-value of 0.000, which is less than 0.05. There is a difference in student science literacy based on achievement motivation with a value of Sig. 0.000 < 0.05 and there is no interaction between the learning model and achievement motivation on student science literacy, with a value of Sig. 0.230 > 0.05.