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R Zanoli

Biographic Data

ID6318826
NAMER Zanoli
GIVEN NAMESR
FAMILY NAMEZanoli
SIGNATUREZANOLI R
AFFILIATIONSMarche Polytechnic University
ORCID0000-0002-7108-397X
VERIFIEDYes
TOTAL WORKS9
TOTAL CITATIONS11
AUTHOR COUNT9
EDITOR COUNT0
FIRST PUBLICATION YEAR2002
LATEST PUBLICATION YEAR2026
H-INDEX2
  • Artificial Intelligence in agriculture

    Serena Mandolesi, R Zanoli et al.•ARTICLE•British Food Journal•2026

    Purpose This study explores how stakeholders perceive and evaluate Artificial Intelligence (AI) in sustainable agriculture. While AI is often promoted as a solution to food security and climate challenges, its adoption raises ethical, social, and institutional concerns that remain underexplored. Design/methodology/approach Using Q methodology, the study captures subjective viewpoints from 20 stakeholders, including farmers, nutritionists, journal…

  • Scoring NutriScore

    Giuseppina Rizzo, Serena Mandolesi et al.•ARTICLE•British Food Journal•2025

    Purpose This study aims to understand consumers' subjective perceptions of the adoption of the NutriScore label on food packaging. In particular, the study focuses on the overall acceptance of the NutriScore label in Italy, with the aim of emphasising the importance of understanding consumer perspectives in order to encourage healthier food choices. Design/methodology/approach Q methodology was used to explore individuals’ subjectivity and attitu…

  • Estimating preferences for Mediterranean deep-sea ecosystem services

    Open Access•Lorenzo Carlesi, Emilia Cubero Dudinskaya et al.•ARTICLE•Marine Policy•2023

  • X-reality technologies for museums

    Open Access•Alma Leopardi, Silvia Ceccacci et al.•ARTICLE•Journal of Cultural Heritage•2021•Cited by: 2•References: 29

  • Using visual Q sorting to determine the impact of photovoltaic applications on the landscape

    Open Access•S Naspetti, Serena Mandolesi et al.•ARTICLE•Land Use Policy•2016•Cited by: 1•References: 29

  • Identifying viewpoints on innovation in low-input and organic dairy supply chains

    Open Access•Serena Mandolesi, Philippa Nicholas et al.•ARTICLE•Food Policy•2015•Cited by: 3•References: 8

  • Non-compliance in organic farming

    Open Access•Danilo Gambelli, Francesco Solfanelli et al.•ARTICLE•Food Policy•2014•Cited by: 3•References: 4

  • Organic farming policy development in the EU

    Open Access•Anna Maria Häring, Daniela Vairo et al.•ARTICLE•Food Policy•2009•Cited by: 2•References: 4

  • Consumer motivations in the purchase of organic food

    Open Access•R Zanoli, S Naspetti•ARTICLE•British Food Journal•2002

    The paper presents partial results from an Italian study on consumer perception and knowledge of organic food and related behaviour. Uses the means‐end chain model to link attributes of products to the needs of consumers. In order to provide insights into consumer motivation in purchasing organic products, 60 respondents were interviewed using “hard” laddering approach to the measurement of means‐end chains. The results (ladders) of these semi‐qu…

  • Identifying viewpoints on innovation in low-input and organic dairy supply chains

    Open Access•Serena Mandolesi, Philippa Nicholas et al.•ARTICLE•Food Policy•2015•Cited by: 3•References: 8

  • Non-compliance in organic farming

    Open Access•Danilo Gambelli, Francesco Solfanelli et al.•ARTICLE•Food Policy•2014•Cited by: 3•References: 4

  • X-reality technologies for museums

    Open Access•Alma Leopardi, Silvia Ceccacci et al.•ARTICLE•Journal of Cultural Heritage•2021•Cited by: 2•References: 29

  • Organic farming policy development in the EU

    Open Access•Anna Maria Häring, Daniela Vairo et al.•ARTICLE•Food Policy•2009•Cited by: 2•References: 4

  • Using visual Q sorting to determine the impact of photovoltaic applications on the landscape

    Open Access•S Naspetti, Serena Mandolesi et al.•ARTICLE•Land Use Policy•2016•Cited by: 1•References: 29

  • Consumer motivations in the purchase of organic food

    Open Access•R Zanoli, S Naspetti•ARTICLE•British Food Journal•2002

    The paper presents partial results from an Italian study on consumer perception and knowledge of organic food and related behaviour. Uses the means‐end chain model to link attributes of products to the needs of consumers. In order to provide insights into consumer motivation in purchasing organic products, 60 respondents were interviewed using “hard” laddering approach to the measurement of means‐end chains. The results (ladders) of these semi‐qu…

  • Organic farming policy development in the EU

    Open Access•Anna Maria Häring, Daniela Vairo et al.•ARTICLE•Food Policy•2009•Cited by: 2•References: 4

  • Non-compliance in organic farming

    Open Access•Danilo Gambelli, Francesco Solfanelli et al.•ARTICLE•Food Policy•2014•Cited by: 3•References: 4

  • Identifying viewpoints on innovation in low-input and organic dairy supply chains

    Open Access•Serena Mandolesi, Philippa Nicholas et al.•ARTICLE•Food Policy•2015•Cited by: 3•References: 8

  • Using visual Q sorting to determine the impact of photovoltaic applications on the landscape

    Open Access•S Naspetti, Serena Mandolesi et al.•ARTICLE•Land Use Policy•2016•Cited by: 1•References: 29

  • X-reality technologies for museums

    Open Access•Alma Leopardi, Silvia Ceccacci et al.•ARTICLE•Journal of Cultural Heritage•2021•Cited by: 2•References: 29

  • Estimating preferences for Mediterranean deep-sea ecosystem services

    Open Access•Lorenzo Carlesi, Emilia Cubero Dudinskaya et al.•ARTICLE•Marine Policy•2023

  • Scoring NutriScore

    Giuseppina Rizzo, Serena Mandolesi et al.•ARTICLE•British Food Journal•2025

    Purpose This study aims to understand consumers' subjective perceptions of the adoption of the NutriScore label on food packaging. In particular, the study focuses on the overall acceptance of the NutriScore label in Italy, with the aim of emphasising the importance of understanding consumer perspectives in order to encourage healthier food choices. Design/methodology/approach Q methodology was used to explore individuals’ subjectivity and attitu…

  • Artificial Intelligence in agriculture

    Serena Mandolesi, R Zanoli et al.•ARTICLE•British Food Journal•2026

    Purpose This study explores how stakeholders perceive and evaluate Artificial Intelligence (AI) in sustainable agriculture. While AI is often promoted as a solution to food security and climate challenges, its adoption raises ethical, social, and institutional concerns that remain underexplored. Design/methodology/approach Using Q methodology, the study captures subjective viewpoints from 20 stakeholders, including farmers, nutritionists, journal…

Business (6 works) · Computer Science (6 works) · Geography (6 works) · Agriculture (4 works) · Political science (4 works) · Viewpoints (4 works) · Economics (3 works) · Environmental resource management (3 works) · Environmental Science (3 works) · Psychology (3 works)

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