In the current competitive global marketplace, innovation is key for high-tech firms to thrive. Open innovation offers a promising approach, but its effectiveness remains unclear. Therefore, this research explored the connection between open innovation, knowledge management capability, and innovation performance within high-tech firms. We used a mediation approach to highlight the central role of knowledge management capability in the relationship between open innovation and innovation performance. We used a survey questionnaire approach to collect data from the 462 employees of high-tech firms on open innovation, knowledge management capability, and innovation performance using a convenient sampling technique. We used partial least square structural equations modeling through PLS-SEM statistics. Results indicated that open innovation has a direct, positive and significant connection with innovation performance. Similarly, the current research serves as a pioneering exploration into mediation analysis, highlighting the mediating role of knowledge management capability that influences the relationship between open innovation and innovation performance. Empirical studies offer valuable insights for leaders of high-tech firms, guiding them to identify effective knowledge management practices and determine the ideal extent of open innovation to boost innovation performance. The current study reveals novel insights into the benefits of knowledge management capability in enhancing open innovation efforts within firms. This research provides valuable implications and future research directions.

The paper considers an important problem of the successful development of social qualities in an individual using machine learning methods. Social qualities play an important role in forming personal and professional lives, and their development is becoming relevant in modern society. The paper presents an overview of modern research in social psychology and machine learning; besides, it describes the data analysis method to identify factors influencing success in the development of social qualities. By analyzing large amounts of data collected from various sources, the authors of the paper use machine learning algorithms, such as Kohonen maps, decision tree and neural networks, to identify relationships between different variables, including education, environment, personal characteristics, and the development of social skills. Experiments were conducted to analyze the considered datasets, which included the introduction of methods to find dependencies between the input and output parameters. Machine learning introduction to find factors influencing the development of individual social qualities has varying dependence accuracy. The study results could be useful for both practical purposes and further scientific research in social psychology and machine learning. The paper represents an important contribution to understanding the factors that contribute to the successful development of individual social skills and could be useful in the development of programs and interventions in this area. The main objective of the research was to study the functionalities of the machine learning algorithms and various models to predict the students’s success in learning.

The study aims to explore the role of artificial intelligence in enhancing the efficiency of public relations practitioners in Jordanian telecommunication companies. This study belongs to the category of descriptive research and adopted a survey methodology. The study surveyed (86) individuals representing the community of public relations practitioners and customer service personnel in the Jordanian telecommunication companies Zain and Orange.The study findings revealed that less experienced public relations personnel in Zain and Orange, with less than five years of experience, exhibit greater acceptance and enthusiasm for using artificial intelligence applications compared to their more experienced counterparts. The study also indicated that most public relations practitioners in Zain and Orange perceive artificial intelligence applications to have a moderate to significant contribution to achieving public relations functions and enhancing their work, reflecting technological advancement and the need to adapt to rapid changes in the business environment. Moreover, the study also discussed the limits, including that artificial intelligence can analyze large amounts of data related to the market and the audience, which provides further research and study.

The relationship between aid and corruption remains ambiguous. On the one hand, aid may benefit a country if the aid management system runs efficiently and transparently. On the other hand, aid tends to create new problems, namely corruption, especially in developing countries. This research examines the aid-corruption paradox in Indonesian provinces from a spatial perspective. The data was obtained from the Indonesian Ministry of Finance, the National Development Planning Agency of Indonesia, the Corruption Eradication Commission of Indonesia, and the Electronic Procurement Service, referring to 34 Indonesian provinces between 2011 and 2019. The research applies the spatial panel method and uses Haversine distance to construct the weighted matrix. The spatial error model (SEM) is the best for Model 1 (Grants) and Model 2 (Loans) and the best corruption model in Model 3 (Gratification). The spatial autoregressive model (SAR) is the best approach for Model 4 (Public Complaints) and Model 5 (Corruption). The findings show that there is no spatial dependence between provinces in Indonesia in terms of grants or loans. However, corruption in Indonesia is widespread.

This study seeks to examine the factors affecting the intention of Indonesian MSMEs to adopt QRIS. It leverages variables from the Technology Acceptance Model (TAM), customizing the TAM framework to address the unique perceptions of risk and cost among MSMEs in Indonesia. Data were gathered from 212 MSME participants in Brebes Regency through convenience sampling, a non-probability sampling technique, using Google Forms for survey distribution. The findings indicate that perceived ease of use positively and significantly influences attitudes, which, in turn, positively and significantly impact the intention to continue using QRIS. However, perceived benefits, perceived risks, and perceived costs did not significantly affect the intention to continue use.