Shahin Rezvanian
Last Name
Rezvanian
First name
Shahin
Email
shahin.rezvanian@unisg.ch
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Item type:Publication, Data-Driven Ecosystem Business Models in Agriculture with Focus on Sustainability: A Systematic Literature ReviewDigital transformation is reshaping agriculture through datadriven business models leveraging emerging technologies. Understanding these models' sustainability contributions is crucial given agriculture's challenges with climate change, resource constraints, and food security. Following PRISMA, Scopus and Web of Science were searched, yielding 1538 articles. After screenings, 80 papers were analyzed thematically. 32 distinct data-driven ecosystem business models were identified, categorized into three primary groups: Technology-Focused Models, Value Chain Integration Models, and Data & Governance Models. These models contribute to economic sustainability through resource optimization and new revenue streams; environmental sustainability through precision management and emissions reduction; and social sustainability through knowledge sharing and community development. Implementation challenges include technical integration, organizational adoption barriers, data governance concerns, and policy gaps. These models show significant potential for enhancing agricultural sustainability. Trust emerges as fundamental for implementation, while power dynamics remain critical concerns. Future research should focus on governance frameworks, user-centric design, and impact assessment.Type:conference paperJournal:38th Bled eConference: Empowering Transformation: Shaping Digital Futures for All: Conference Proceedings - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Automated image processing for visual sustainability communication: Methodological and practical insights for researchers on the example of Instagram(2024-04-19); ; Companies are increasingly turning to visual content for sustainability communication, particularly on social media platforms, such as Instagram and TikTok. However, researchers face considerable challenges in processing and analyzing visual sustainability communication (VSC) data. This is mostly because of an overreliance on conventional manual classification methods. Our presentation aims to share insights from our research related to emerging practical approaches how sustainability matters are visually depicted, how visual sustainability communication on social media can be automatically detected with machine learning, and applied for analysis of the effectiveness of VSC in terms of user engagement.Type:conference paper