This paper analyses the impact of an integrated business management system on business operations in trade in Republic of Croatia. The integration of management systems provides various benefits to a company, so the aim of this paper is to analyse the impacts of integrated management systems on the business operations of trade companies in the Republic of Croatia. The purpose of this paper is to examine and analyse, but also to adequately theoretically argue the impact of transformational leadership, quality culture, and the degree of integration on the development of integrated management systems. Empirical research investigated integrated management systems in companies in the trade sector in the Republic of Croatia. Based on the set conceptual model and research results, we conclude that companies with a highly developed quality culture have proven management system integration. Our research didn’t confirm the significance of transformational leadership in interpreting changes in the degree of management system integration, but it highlights the positive correlation between the application of quality culture and integration; confirms the substantial impact of integrated management systems on both internal and external benefits, emphasizing its strategic imperative for sustained business success.

This study aims to determine the extent to which talent identification is implemented in talent management. A Systematic Literature Review (SLR) was conducted to summarize the application of talent identification in the last six years. Researchers use Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) to process scientific articles. The literature reveals that while topics related to talent management garner significant attention, research on talent identification within talent management remains relatively scarce despite a gradual increase each year. We compared documents indexed by Scopus Q1 and Q2. The results show that the United States accounted for a significant portion of research on talent identification, representing 16% of the total existing research. Researchers have conducted extensive studies on the medical and pharmaceutical sectors, public services, tourism, and hospitality. The number of citations varied greatly from 1 to 93, with a median value of 20. These studies have also used various research methods with different theoretical bases and produced different analyses. This finding enriches the perspective of talent identification.

Indonesia, as a maritime country, has many coastal areas with fishing villages that have significant potential, especially in sociological, economic, and environmental aspects, to be developed as models for sustainable development. Indonesia, with its long-standing fishing traditions, showcases the abundant potential and traditional that could help address global challenges such as climate change, rapid urbanization, and environmental and economic issues. This study aims to develop a conceptual model for sustainable cities and communities based on local potential and Wisdom towards the establishment of a Blue Village in the fishing village of Mundu Pesisir, Cirebon, Indonesia. The urgency of this study lies in the importance of developing sustainable strategies to address these challenges in coastal towns. This study involves an interdisciplinary team, including experts in sociology, social welfare, architecture, law, economics, and information technology. Through the identification of local natural and sociocultural resources, as well as the formulation of sustainable development strategies, this study develops a conceptual Blue Village model that can be applied to other coastal villages. The method employed in this study is qualitative descriptive, involving the steps of conducting a literature review, analyzing local potential, organizing focus group discussions, conducting interviews, and finalizing the conceptual model. The study employed, a purposive sampling technique, involving 110 participants. The results of the study include the modeling of a sustainable city and community development based on local potential and Wisdom aimed at creating Blue Villages in Indonesia, and It is expected to make a significant contribution to the creation of competitive and sustainable coastal areas capable of addressing the challenges of climate change and socioeconomic dynamics in the future.

 This study explores the primary drivers influencing sustainable project management (SPM) practices in the construction industry. This research study seeks to determine whether firms are primarily motivated by external pressures or internal values when embracing SPM practices. In doing so, this study contributes to the ongoing discourse on SPM drivers by considering coercive pressures (CP), ethical responsibility (ER), and green transformational leadership (GTL) as critical enablers facilitating a firm’s adoption of SPM practices. Based on data from 196 project management practitioners in Pakistan, structural equation modeling (PLS-SEM) was employed to test the hypothesized relationships. Results highlight that CP influences the management of sustainability practices in construction projects, signifying firms’ concern for securing legitimacy from various institutional actors. As an ‘intrinsic value’, ER emerges as a significant motivator for ecological stewardship, driven by a genuine commitment to promoting sustainable development. This study also unveils the significant moderating effect of GTL on the association among CP, ER, and SPM. Lastly, the results of IMPA reveal that ER slightly performs better than CP as it helps firms internalize the essence of sustainability. This research study expands our understanding of SPM drivers in construction projects by exploring the differential impact of external pressures and the firm’s intrinsic values. These findings provide valuable insights for policymakers and practitioners, aiding them in promoting SPM to attain sustainable development goals.

While some conflict can serve as a more sophisticated stimulus to student achievement, significant or unresolved conflict can delay or even frustrate even the best-planned curriculum. The aim of our study is to get a clear picture of the conflicts with whom and to what extent the international students studying on our campuses have conflicts that affect their performance, and how they can manage them. In our study, based on a questionnaire survey (n = 480), we revealed that the international students at our university have the most conflicts with other foreign students, and the least with Hungarians, including their teachers. On the other hand, we found that according to the Thomas-Kilmann Conflict Instrument, they solve their problems by the Compromising and Accommodating style. The results obtained by detailed socio-demographic aspects show significant differences, mainly between gender, age, and country groups. Knowledge of the revealed facts and connections can offer conscious and careful solutions to understand and reduce tensions, and this can improve the understanding and management of conflict in the classroom, in collaborative projects, and even in non-teaching environments on campuses.

The study explores improving opportunities of forecasting accuracy from the traditional method through advanced forecasting techniques. This enables companies to optimize inventory management, production planning, and reducing the travelling time thorough vehicle route optimization. The article introduced a holistic framework by deploying advanced demand forecasting techniques i.e., AutoRegressive Integrated Moving Average (ARIMA) and Recurrent Neural Network-Long Short-Term Memory (RNN-LSTM) models, and the Vehicle Routing Problem with Time Windows (VRPTW) approach. The actual milk demand data came from the company and two forecasting models, ARIMA and RNN-LSTM, have been deployed using Python Jupyter notebook and compared them in terms of various precision measures. VRPTW established not only the optimal routes for a fleet of six vehicles but also tactical scheduling which contributes to a streamlined and agile raw milk collection process, ensuring a harmonious and resource-efficient operation. The proposed approach succeeded on dropping about 16% of total travel time and capable of making predictions with approximately 2% increased accuracy than before.