This study investigates the escalating complexity and unpredictability of global supply chains, with a particular emphasis on resilience in the agricultural sector of Antioquia, Colombia. The aim of the study is to identify and analyze the dynamic capabilities, specifically flexibility and adaptability that significantly enhance resilience within agri-food supply chains. Given the sector’s vulnerability to external disruptions, such as climate change and economic volatility, a thorough understanding of these capabilities is imperative for the formulation of effective risk management strategies. This research is essential to provide empirical insights that can inform stakeholders on fortifying their supply chains, thereby contributing to enhanced competitiveness and sustainability. By presenting a comprehensive framework for evaluating dynamic capabilities, this study not only addresses existing gaps in the literature but also offers practical recommendations aimed at bolstering resilience in the agricultural sector.

This study explores the scale efficiency of four star hotels in a small tourist destination in Croatia. The number of overnight stays and the increase in hotel beds are two indicators of the development of a tourist destination. Among the accommodation facilities, hotels play a significant role in the development of a tourist destination, but they are increasingly facing a labor force crisis. Data envelopment analysis is used to rank hotels by efficiency coefficient. The aim of the paper is to investigate the efficiency of the hotel by taking certain inputs and outputs, which are explained in detail in the paper. The paper uses the CCR (Charnes, Cooper, and Rhodes) and BCC (Banker, Charnes, and Cooper) models to calculate hotel scale efficiency and also presents an overview of previous research around the world.

This paper is the third in a series focused on bridging the gap between secondary and higher education. Our primary objective is to develop a robust theoretical framework for an innovative e-business model called the Undergraduate Study Programme Search System (USPSS). This system considers multiple criteria to reduce the likelihood of exam failure or the need for multiple retakes, while maximizing the chances of successful program completion. Testing of the proposed algorithm demonstrated that the Stochastic Gradient Boosted Regression Trees method outperforms the current method used in Lithuania for admitting applicants to 47 educational programs. Specifically, it is more accurate than the Probabilistic Neural Network for 25 programs, the Ensemble of Regression Trees for 24 programs, the Single Regression Tree for 18 programs, the Random Forest Regression for 16 programs, the Bayesian Additive Regression Trees for 13 programs, and the Regression by Discretization for 10 programs.

Since 2022, global geopolitical conflicts have intensified, and there has been a notable increase in the international community’s demand for currency diversification. This has created a new opportunity for the internationalization of the Renminbi (RMB). This paper examines the factors influencing the internationalization of the RMB, with a particular focus on its role as a unit of account, medium of exchange and store of value. These functions are considered in conjunction with the digital technological innovation represented by e-CNY. The methodology employed is based on the vector autoregression (VAR) model, Granger causality test and variance decomposition analysis. The Granger causality test indicates that digital technology innovation is not the primary driver of RMB internationalization at this juncture. The impulse response analysis and variance decomposition analysis revealed that the impact and direction of influence exerted by the various factors on RMB internationalization exhibit considerable discrepancies.

This research presents an in-depth examination of the emotional effects of synchronous hybrid education on undergraduate university students at a pioneering private institution in educational innovation. The study had encompassed all courses that were delivered in a synchronous hybrid format, covering 16 courses and involving 241 students. Each student had been observed and recorded on two separate class sessions, with each recording lasting approximately 30 min. This comprehensive data collection had resulted in 409 recordings, each approximately 30 min in duration, translating to nearly an hour of observation per student across the classes, totaling close to 205 h of recordings. These recordings were subsequently processed using neuroscience software tools for advanced statistical analysis, effectively serving as a comprehensive survey of courses within this modality. The primary focus of the research was on the emotions experienced during both face-to-face and online classes and their subsequent influence on student behavior and well-being. The findings reveal higher emotional time ratios for positive emotions such as joy and surprise in face-to-face students. Notably, both groups exhibited comparable ratios for negative emotions like anger and sadness. The research underscores the emotional advantages of face-to-face interactions, which elicit stronger emotions, in contrast to online students who often feel detached and isolated.