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Abstract: Lean manufacturing is widely recognized as an operational philosophy of process improvement; however, its relationship with financial performance remains relatively underexplored empirically. The purpose of this study is to examine the relationship between lean manufacturing and return on equity (ROE), and to link operational improvements with financial outcomes through the DuPont model. The research comprises a comparative financial analysis of a selected manufacturing company for the period 2019–2023, as well as a quantitative analysis of a sample of 240 Slovenian manufacturing enterprises. Descriptive statistical methods, correlation analysis, and linear regression with a composite lean maturity index were employed. The results indicate that ROE in the analyzed company increased from 4.74% to 11.99%, with growth primarily driven by improvements in net profit margin and process efficiency rather than by increased financial leverage. The empirical analysis demonstrates a statistically significant positive association between the level of lean maturity and ROE (β = 0.255; R² = 0.065; p < 0.001; N = 240). Although the explained variance is moderate, the findings indicate that lean maturity represents a statistically significant and managerially relevant determinant of financial performance within a multifactor business environment. The contribution of the study lies in the integration of the Lean approach with the DuPont model as an analytical bridge between production and financial functions, as well as in the empirical validation of this relationship within the Slovenian industrial context.
Keywords: return on equit, DuPont analysis, operational efficiency, productivity, lean manufacturing, Toyota Way
Published in RUP: 07.07.2026; Views: 86; Downloads: 6
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Abstract: This study investigates the implementation and impact of ChatGPT and Gemini in a four-star hotel in Ao Nang, Krabi, Thailand, during January–February 2024. Through a mixed-methods approach combining quantitative analysis and qualita-tive insights, the research assessed operational metrics across multiple service areas and gathered detailed feedback from the hotel owner. The study revealed significant improvements in operational efficiency, with check-in processing times decreasing from 3.3 to 2.7 minutes and AI system adoption increasing from 82% to 93%. Gu-est satisfaction scores showed notable enhancement, with overall satisfaction rising from 4.6 to 4.8 out of 5. The AI systems demonstrated impressive multilingual ca-pabilities, handling 28 languages with 98.7% accuracy, while document processing achieved 99.2% accuracy across various types. Internal communications benefited from 32% time savings, with efficiency rates exceeding 96% across all categories. Staff adaptation, though initially challenging, was successfully managed through comprehensive training and gradual implementation, resulting in improved job satisfaction and team collaboration. The findings provide empirical evidence that strategic AI integration can enhance both operational efficiency and guest satisfa-ction while complementing human service elements. This research contributes va-luable insights for hospitality managers considering AI implementation and offers a practical blueprint for successful technology integration in the hospitality sector, while also highlighting areas for future research in different hotel categories and geographical contexts.
Keywords: AI integration, ChatGPT, Gemini, hospitality, operational efficiency
Published in RUP: 16.12.2025; Views: 594; Downloads: 1
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