Giovanbattista Califano

Giovanbattista Califano (MA, MSc, PhD) is a researcher at the University of Naples Federico II (Italy), Department of Agricultural Sciences. He holds a PhD in Food Science, with a dissertation on consumer perceptions of food technology innovations, an MSc in Agricultural Economics and Policy, and a Master’s degree in Psychology, all from the University of Naples Federico II.

His current research interests lie at the intersection of behavioral and experimental economics, agrifood marketing, and sustainability, with a particular focus on the adoption of food innovations such as cultured meat, 3D-printed foods, and AI-generated recipes. Giovanbattista adopts a transdisciplinary approach, combining choice modeling, advanced econometric techniques, and psychological theory to analyze consumer attitudes and preferences.

 

 

Address

Dept. of Agricultural Sciences
Via Università 96 – 80055 Portici, Naples, Italy

Tel. +39 081 2539094

Selected publications

  • Califano, G., Lombardi, A., Del Giudice, T., Caracciolo, F., & Cembalo, L. (2024). Bioplastics in the basket of Italians: A hybrid framework for understanding the adoption of bioplastic food packaging. Australian Journal of Agricultural and Resource Economics, 68(4), 826-846. DOI: 10.1111/1467-8489.12578
  • Califano, G., Zhang, T., & Spence, C. (2024). Would you trust an AI chef? Examining what people think when AI becomes creative with food. International Journal of Gastronomy and Food Science, 37:100973. DOI: 10.1016/j.ijgfs.2024.100973
  • Califano, G., & Spence, C. (2024). Assessing the visual appeal of real/AI-generated food images. Food Quality and Preference, 116:105149. DOI: 10.1016/j.foodqual.2024.105149
  • Califano, G., & Spence, C. (2024). Consumer preference and willingness to pay for 3D-printed chocolates: A discrete choice experiment. Future Foods, 9:100378. DOI: 10.1016/j.fufo.2024.100378
  • Califano, G., Crichton-Fock, A., & Spence, C. (2024). Consumer perceptions and preferences for urban farming, hydroponics, and robotic cultivation: A case study on parsley. Future Foods, 9:100353. DOI: 10.1016/j.fufo.2024.100353
  • di Santo, N., Califano, G., Sisto, R., Caracciolo, F., & Pilone, V. (2024). Are university students really hungry for sustainability? A choice experiment on new food products from circular economy. Agricultural and Food Economics, 12(1):21. DOI: 10.1186/s40100-024-00315-9
  • Raimondo, M., Spina, D., D’Amico, M., Di Vita, G., Califano, G., & Caracciolo, F. (2024). Taste matters more than origin: An experimental economics study on consumer preferences for native and foreign varieties of walnuts. Food Quality and Preference, 115:105106. DOI: 10.1016/j.foodqual.2024.105106
  • Lombardi, A., Califano, G., Caracciolo, F., Del Giudice, T., & Cembalo, L. (2024). Eco-packaging in organic foods: Rational decisions or emotional influences? Organic Agriculture, 14(2), 125-142. DOI: 10.1007/s13165-023-00442-5
  • Fantechi, T., Califano, G., Contini, C., & Caracciolo, F. (2024). Puppy power: How neophobia, animal empathy, and sustainability affect the demand for novel food in pet food. Food Research International, 177:113879. DOI: 10.1016/j.foodres.2023.113879
  • Di Vita, G., Califano, G., Raimondo, M., D’Amico, M., Spina, D., Hamam, M., & Caracciolo, F. (2024). From roots to leaves: Understanding consumer acceptance in implementing climate-resilient strategies in viticulture. Australian Journal of Grape and Wine Research, 2024:8118128. DOI: 10.1155/2024/8118128
  • Capasso, M., Califano, G., Caracciolo, F., & Caso, D. (2023). Only the best for my kids: An extended TPB model to understand mothers’ use of food labels. Appetite, 191:107040. DOI: 10.1016/j.appet.2023.107040
  • Califano, G., Furno, M., & Caracciolo, F. (2023). Beyond one-size-fits-all: Consumers react differently to packaging colors and names of cultured meat in Italy. Appetite, 182:106434. DOI: 10.1016/j.appet.2022.106434
  • Caracciolo, F., Furno, M., D’Amico, M., Califano, G., & Di Vita, G. (2022). Variety seeking behavior in the wine domain: A consumers segmentation using big data. Food Quality and Preference, 97:104481. DOI: 10.1016/j.foodqual.2021.104481