We outline the management performance measures (MPMs)' boundaries based on the upcoming introduction of MPM's definition to International Financial Reporting Standards (IFRS). The literature investigates business performance measures concentrating on managers' needs, while IFRS aims to provide financial information to external users who provide resources to the entity. This indicates a gap between how performance metrics have been investigated so far and how IFRS will adopt them. We used analysis of the exposure draft of the planned standard together with working materials developed in the consultation process. Further, a case study is presented. Results show that the scope of MPM to be introduced to IFRS is limited compared to the broad spectrum of performance measures presented in the literature. We contribute by showing the avenues for future performance measures research using signalling and agency theory and by indicating the limited scope of MPMs and thus bound prospects for using them for a full assessment of the entity‘s performance.

Purpose: The aim of this study is to determine how habit, social influence, and facilitating conditions influence accounting students’ use of ChatGPT. Methodology/approach: The study was conducted among bachelor’s, master’s, doctoral, and postgraduate students studying accounting-related majors at the University of Economics in Katowice. Ordinal logistic regression was used to analyze 237 responses. Findings: The study confirms that the accounting students use ChatGPT primarily for self-studying and preparing projects and homework, with facilitating conditions, habits, and gender having a statistically significant impact on its use. Maintaining habits positively impacts the use of ChatGPT. The gender comparison indicates that women are less likely to use it than men. Research limitations: The study was conducted only at one economic university in Poland. Originality/value: The results reveal that ChatGPT use is a habit for 5% of accounting students. The results of our study highlight the need to conduct further research in this area, to include ChatGPT in professional activities and teaching to make users aware of the dangers (including ethical ones) associated with the use of artificial intelligence in accounting practice and to familiarize accounting teachers with it to help shape good habits among future accountants.

This study investigates the extent of digital technology adoption among Polish beekeepers and how socio-demographic factors influence this adoption. Data were gathered through semi-structured interviews with 30 beekeeping experts and a survey of 949 randomly selected beekeepers. A Random Forest machine learning algorithm was employed to predict digital adoption, and SHAP values were applied to interpret the model’s output. The findings reveal that only 28.6% of beekeepers have adopted digital technologies. Experts highlighted several key themes related to adoption, including the perceived need for technology, types of technologies used, data collection practices, benefits for management and marketing, as well as associated risks and challenges. Among the socio-demographic factors, beekeeping experience had the strongest impact on digital technology adoption, followed by formal education in apiculture and the beekeeper’s age. These factors allowed the identification of three distinct beekeeper profiles: education- and engagement-driven beekeepers, experience-driven beekeepers, and highly experienced beekeepers. These insights can help beekeeping associations and policymakers promote the effective adoption of digital tools to support more sustainable and efficient apiary management.