Keeping in mind the fact that organizations in the region of Vojvodina are moving from a negotiated to market economy, this study aims to analyze how the dimensions of collaborative climate affect the various activities of knowledge management. The degree to which collaborative climate influences knowledge work is investigated on 190 participants in the region of the Province of Vojvodina (Serbia). Two standardized questionnaires were used to collect data: a knowledge management questionnaire, which included 32 questions, and a collaborative climate questionnaire of 20 questions. To test the hypothesis of the study, the technique used was descriptive statistics, confirmatory factor analysis, and structural equation modeling. The results show that only the organizational culture as a dimension of collaborative climate contributes to the explanation of all the activities of knowledge management, except the activity of leaving knowledge, which fails to achieve a statistical relationship with any dimension of collaborative climate. This study provides useful insights for practitioners wanting to improve an organization’s performance and to increase organizational sustainability and learning. It is a useful base to expand further research in a way of better understanding the impact that collaborative climate has on the implementation of knowledge management in a transition towards a knowledge economy.

The main purpose of this paper is to empirically analyse the state of knowledge management (KM) practice in one particular region. In order to access the state of Vojvodina firms regarding the applicability of KM program, the Knowledge Management Diagnostic model was applied. Hypotheses based on the specific integrated set of KM were established and statistically tested on a sample of 190 Vojvodina companies from various industries, government institutions and public enterprises. Survey methodology was used with the aim to gather data about KM practice and other related organizational aspects. Our findings show the extent to which individual steps of KM at the whole sample deviate from the maximum value assigned. This survey provides a foundation for practicing engineering managers to position company and recognize the steps of KM that can be improved in order to achieve strategic value and close the gap between the average and maximum value assigned to each step.

The main idea of the paper is researching AI and other technologies for Wealth Management. Implementation of the AI in WealtTech helps in giving the best investment advises. Wealth Management includes retirement planning, inheritance tax, estate planning, and other activities according to investment preferences. WealthTech aims to manage investment funds and assets more efficiently, accessible, and personalized through data-driven insights and smart automation. Besides improving their efficiency, WealthTech aims to automate investment and wealth management services. WealthTech utilizes innovations like blockchain, artificial intelligence, and machine learning to improve investment decisions combining technologies for fund transformation and asset handling. These technologies include a wide range of solutions and include robo-advisors, social trading, robot-retirement, quant advisors, and micro-investing. This approach use the best technology solutions more advanced than typical analysis used in financial institutions. WealthTech AI applications are developed to create wealth data dashboards tailored to the clients needs. The applications enable clients to see full and transparent picture of their entire wealth and visualise wealth maps and data-driven analytics to uncover valuable investment insights. The aim of the applications is to convert diversified investment portfolio in clear reports and graphs. Because of the advancements in AI, the programs provide personalized advice concerning wealth management and business strategies. The Manuscript will present WealthTech solutions on the practical example and recommend the most attractive investment opportunities on the global market.

Understanding the relationship between work stress and job satisfaction is crucial for promoting employee well-being and also for sustainable organizational performance. This study proposes and validates, within the population of employees in Serbia, the Stress Symptoms Survey (SSS), an 18-item instrument for measuring physical and psychological symptoms of work-related stress. The scale shows strong internal consistency where a general factor is highly saturated with all survey items. Regression analysis indicated that lack of organizational support was the strongest predictor of lowered job satisfaction, followed by stress symptoms and general job stress; job pressure showed a positive association with job satisfaction when other stressors were controlled. These results highlight the practical value of the SSS and underscore the crucial role of supportive work environments in mitigating stress, enhancing satisfaction and achieving sustainable work performance.

The paper aims to research the latest technologies for Wealth Management and use them to present the WealtTech approaches that give the best advice for investment management decisions and refer to the use of technology to provide financial services and solutions for Wealth Management. Wealth Management is a combination of financial planning and investment strategy analysis for capital growth. It includes retirement planning, inheritance tax, estate planning, and other activities according to investment preferences. Since WealthTech is a part of FinTech, it aims to manage investment funds and assets more efficiently, accessible, and personalized through data-driven insights and smart automation. Besides improving their efficiency, WealthTech aims to automate investment and wealth management services. WealthTech utilizes innovations like blockchain, artificial intelligence, and machine learning to improve investment decisions combining technologies for fund transformation and asset handling. These technologies include a wide range of solutions and include robo-advisors, social trading, robot-retirement, quant advisors, and micro-investing. WealthTech refers to the delivery of many kinds of financial services for Wealth Management based on digital solutions. Besides improving investors’ decision-making, the technology enables people to manage their finances efficiently. This approach use the best technology solutions more advanced than typical analysis used in financial institutions. Because of the advancements in software as a service (SaaS), big data, AI and machine learning, the programs provide personalized advice concerning wealth management and business strategies. This manuscript will present WealthTech solutions on the practical example and recommend the most attractive investment opportunities on the global market.