Sustainable Competitiveness and Applicative Comparative Analysis of Wine Production Through the Lens of Triple Bottom Line, Robotics, and Industry 5.0 Strategies

Simona Corina Dobre Gudei, Liane Tancelov, Rocsana Bucea-Manea-Țoniș, Daniel Manolache and Nicolae Ionescu ()
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Simona Corina Dobre Gudei: Faculty of Economy and International Affairs, Bucharest University of Economic Studies, 010404 Bucharest, Romania
Liane Tancelov: Faculty of Economy and International Affairs, Bucharest University of Economic Studies, 010404 Bucharest, Romania
Rocsana Bucea-Manea-Țoniș: Sport and Motor Performance Department, National University of Physical Education and Sport, 060057 Bucharest, Romania
Daniel Manolache: Manufacturing Engineering Department, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania
Nicolae Ionescu: Manufacturing Engineering Department, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania

Sustainability, 2025, vol. 17, issue 9, 1-25

Abstract: This study investigates sustainable competitiveness in the wine industry using Romania and Portugal as comparative case studies within the conceptual frameworks of Industry 5.0 and the Triple Bottom Line (TBL). While sustainability, robotics, and performance indicators are explored directionally, the core empirical contribution focuses on evaluating key wine industry metrics and their impact on export value. Using data from the International Organisation of Vine and Wine (OIV) and the World Trade Map, we perform a one-way ANOVA to examine differences between the two countries across five variables: vineyard area, wine production volume, grape production, consumption, and export value. The results reveal statistically significant differences in all indicators except vineyard area, with Portugal significantly outperforming Romania in production, consumption, and exports ( p < 0.001). To assess the drivers of export performance, we construct a Structural Equation Model (SEM) using SmartPLS. The model confirms that wine production volume and domestic consumption are the strongest positive predictors of export value (loading factors 1.003 and 0.909, respectively), while vineyard area has minimal influence. The model exhibits strong fit indices (e.g., SRMR = 0.009; NFI = 0.971), supporting the robustness of the results. The findings suggest that internal market strength and production efficiency, rather than land size, are critical for export competitiveness. Romania can enhance its performance by aligning production strategies with TBL principles and selectively adopting Industry 5.0 technologies in viticulture.

Keywords: industry 5.0; triple bottom line; wine exports; Romania; Portugal; SEM analysis; ANOVA; agro standard (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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