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Nowcasting and forecasting aquaponics by Google Trends in European countries

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  • Palma Lampreia Dos Santos, Maria José

Abstract

Aquaponics, an innovation in agricultural systems of production and food supply which combines aquaculture fish production with hydroponic production of vegetables, represents a valuable option to overcome the food needs of a constantly increasing world population, it can do so by improving production and supply with less inputs and in a sustainable way. Despite recent developments in this scientific area, there are still not enough commercial firms at a European level that allow for a consistent view of how this activity is evolving in society, as well as, to understand the impact of Aquaponics Hub in promoting the development of this activity in Europe - aquaponics is still at an early age and, despite innovative, it needs time to grow and evolve.

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  • Palma Lampreia Dos Santos, Maria José, 2018. "Nowcasting and forecasting aquaponics by Google Trends in European countries," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 178-185.
    • Handle: RePEc:eee:tefoso:v:134:y:2018:i:c:p:178-185
    DOI: 10.1016/j.techfore.2018.06.002
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    1. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
    2. Simon Goddek & Boris Delaide & Utra Mankasingh & Kristin Vala Ragnarsdottir & Haissam Jijakli & Ragnheidur Thorarinsdottir, 2015. "Challenges of Sustainable and Commercial Aquaponics," Sustainability, MDPI, vol. 7(4), pages 1-26, April.
    3. Bram Klievink & Bart-Jan Romijn & Scott Cunningham & Hans Bruijn, 2017. "Big data in the public sector: Uncertainties and readiness," Information Systems Frontiers, Springer, vol. 19(2), pages 267-283, April.
    4. Dietrich, Jan Philipp & Schmitz, Christoph & Lotze-Campen, Hermann & Popp, Alexander & Müller, Christoph, 2014. "Forecasting technological change in agriculture—An endogenous implementation in a global land use model," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 236-249.
    5. Konstantin Kholodilin & Maximilian Podstawski & Boriss Siliverstovs, 2010. "Do Google Searches Help in Nowcasting Private Consumption?," KOF Working papers 10-256, KOF Swiss Economic Institute, ETH Zurich.
    6. Devi Buehler & Ranka Junge, 2016. "Global Trends and Current Status of Commercial Urban Rooftop Farming," Sustainability, MDPI, vol. 8(11), pages 1-16, October.
    7. Bram Klievink & Bart-Jan Romijn & Scott Cunningham & Hans Bruijn, 0. "Big data in the public sector: Uncertainties and readiness," Information Systems Frontiers, Springer, vol. 0, pages 1-17.
    8. Miklós Antal & Jeroen C.J.M. Van Den Bergh, 2016. "Green growth and climate change: conceptual and empirical considerations," Climate Policy, Taylor & Francis Journals, vol. 16(2), pages 165-177, March.
    9. Konstantin A. Kholodilin & Maximilian Podstawski & Boriss Siliverstovs, 2010. "Do Google Searches Help in Nowcasting Private Consumption?: A Real-Time Evidence for the US," Discussion Papers of DIW Berlin 997, DIW Berlin, German Institute for Economic Research.
    10. Amankwah-Amoah, Joseph, 2016. "Emerging economies, emerging challenges: Mobilising and capturing value from big data," MPRA Paper 85625, University Library of Munich, Germany.
    11. Betz, Ulrich A.K., 2018. "Is the force awakening?," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 296-303.
    12. Marcelo S. Perlin & João F. Caldeira & André A. P. Santos & Martin Pontuschka, 2017. "Can We Predict the Financial Markets Based on Google's Search Queries?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(4), pages 454-467, July.
    13. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    14. Simeon Vosen & Torsten Schmidt, 2011. "Forecasting private consumption: survey‐based indicators vs. Google trends," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(6), pages 565-578, September.
    15. Amankwah-Amoah, Joseph, 2016. "Emerging economies, emerging challenges: Mobilising and capturing value from big data," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 167-174.
    16. Yang, Xin & Pan, Bing & Evans, James A. & Lv, Benfu, 2015. "Forecasting Chinese tourist volume with search engine data," Tourism Management, Elsevier, vol. 46(C), pages 386-397.
    17. Vicente, María Rosalía & López-Menéndez, Ana J. & Pérez, Rigoberto, 2015. "Forecasting unemployment with internet search data: Does it help to improve predictions when job destruction is skyrocketing?," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 132-139.
    18. Bangwayo-Skeete, Prosper F. & Skeete, Ryan W., 2015. "Can Google data improve the forecasting performance of tourist arrivals? Mixed-data sampling approach," Tourism Management, Elsevier, vol. 46(C), pages 454-464.
    19. Chris Hand & Guy Judge, 2012. "Searching for the picture: forecasting UK cinema admissions using Google Trends data," Applied Economics Letters, Taylor & Francis Journals, vol. 19(11), pages 1051-1055, July.
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    Cited by:

    1. Quevedo Cascante, Mónica & Acosta García, Nicolás & Fold, Niels, 2022. "The role of external forces in the adoption of aquaculture innovations: An ex-ante case study of fish farming in Colombia's southern Amazonian region," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    2. Claudio Liberati & Concetta Cardillo & Antonella Di Fonzo, 2021. "Sustainability and competitiveness in farms: An evidence of Lazio region agriculture through FADN data analysis," Economia agro-alimentare, FrancoAngeli Editore, vol. 23(3), pages 1-22.
    3. Caetano, Marco Antonio Leonel, 2021. "Political activity in social media induces forest fires in the Brazilian Amazon," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    4. Yakubu, Hanan & Kwong, C.K., 2021. "Forecasting the importance of product attributes using online customer reviews and Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 171(C).

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