It is possible to provide green, ecological, and innovative products and services through green and sustainable public procurement. This study analyzes the opportunity offered to public contracting authorities in the Republic of Croatia (RH) in transformation from existing economy to a sustainable one through the inclusion of small and medium sized (SME) companies and inclusion of selection criteria that promote all three sustainable goals. The study employed a qualitative method and empirical analysis of public procurement procedures for eggs in the period from 2013 to 2021 in RH. The product was procured in many social institutions, hospitals, schools, student canteens and by procuring a sustainable product, added value could be created for the entire community. Data from the Electronic Public Procurement Classifieds of the Republic of Croatia (EOJN RH) and Data from the State and European Union (EU) Statistical Office were used. The research showed that sustainable procurement criteria were used for the first time in 2021, and that public contracting authorities put a stronger focus on the environmental pillar of sustainability and less or almost none on the economic and social pillar. The volume of demand and production was also calculated. The study found that the first contractor for sustainable product was SME company, producer of food, who adapted to the green conditions of public procurement in a short period of time. The paper empirically demonstrated that public procurement can be a powerful tool, but it was not used enough in the observed period for the observed products in RH.

The study examines the economic and social impacts of a Southeast Asian multinational company operating in the northwestern region of Hungary, with a particular focus on the local labor market and community responses. The research aims to explore the company’s location choice motivations, its integration process into the local economy, and its cooperation with the local government and communities. The research provides a comprehensive picture of the company’s impacts by employing qualitative and quantitative methodologies—including management interviews and household surveys. The findings indicate that the company has significantly increased employment, enhanced infrastructure, and promoted cultural diversity. However, challenges related to cultural integration persist. The study offers valuable guidance for policymakers and businesses on leveraging the economic benefits of foreign investments and fostering cultural cooperation. Future research could delve deeper into the long-term socio-economic impacts.

Personal branding is a conscious activity that utilizes classic product marketing methods to make a person more marketable. In our study, we employed a quantitative research methodology. Through a survey, we examined the importance respondents assign to visible and non-visible traits and characteristics. During the data analysis, we established a ranking of the most important traits identified by the survey participants, which they believe contribute to a more favorable perception. Among the top five ranked traits—reliability, appearance, charisma, grooming, and authenticity—three are recognizable during the first encounter. Our findings suggest that women place greater emphasis on social perception than men, making them more likely to remain unnoticed. At the same time, younger generations tend to overvalue their presence on social media platforms.

This study investigates the career expectations of individuals in Thailand’s emerging economy, emphasizing the critical factors that shape these expectations within the context of a rapidly evolving labour market in the digital era. A quantitative approach was employed, collecting data from 1230 Thai respondents through convenience sampling, utilizing a structured survey as the primary research instrument. Data analysis involved the use of percentages, means and logistic regression to provide a comprehensive understanding of the findings. The results indicate that factors such as gender, age, monthly income, professional identity, values, culture and technology usage (including devices like laptops, social media platforms, home internet access and usage hours) significantly influence career expectations. Understanding these influential factors is crucial for developing targeted strategies to enhance career satisfaction, preparedness and overall competitiveness in an increasingly globalized and digital economy. By addressing the unique needs and aspirations of the Thai workforce, particularly in this digital age, stakeholders can cultivate a more responsive and adaptive professional environment, ultimately contributing to national economic growth in the digital era.

This study addresses the critical issue of employee turnover intention within Malaysia’s manufacturing sector, focusing on the semiconductor industry, a pivotal component of the inclusive economy growth. The research aims to unveil the determinants of employee turnover intentions through a comprehensive analysis encompassing compensation, career development, work-life balance, and leadership style. Utilizing Herzberg’s Two-Factor Theory as a theoretical framework, the study hypothesizes that motivators (e.g., career development, recognition) and hygiene factors (e.g., compensation, working conditions) significantly influence employees’ intentions to leave. The quantitative research methodology employs a descriptive correlation design to investigate the relationships between the specified variables and turnover intention. Data was collected from executives and managers in northern Malaysia’s semiconductor industry, revealing that compensation, rewards, and work-life balance are significant predictors of turnover intention. At the same time, career development and transformational leadership style show no substantial impact. The findings suggest that manufacturing firms must reevaluate their compensation strategies, foster a conducive work-life balance, and consider a diverse workforce’s evolving needs and expectations to mitigate turnover rates. This study contributes to academic discourse by filling gaps in current literature and offers practical implications for industry stakeholders aiming to enhance employee retention and organizational competitiveness.

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.