Structured literature review (SRL) of logistic models of diffusion on agriculture
Submitted: 2024-05-06
|Accepted: 2025-03-10
|Published: 2025-12-19
Copyright (c) 2025 Francisco Cárdenas-Polonio, Julio Berbel-Vecino, Javier Martínez-Dalmau

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Keywords:
Logistic curve, adoption of innovations, diffusion, agriculture, structured review of the literature
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Abstract:
Diffusion models can help in the decision-making process. In this review, a structured literature review (SLR) approach has been used. Our analysis was based on 945 studies. After an exhaustive review, 31 studies were re-reviewed. Diffusion is a dynamic and complex decision-making process that in the literature has been strictly linked to the expected utility theory. The logistic model is applicable to agribusiness, marketing, the telecommunications industry, electronics products, and agricultural crop diffusion. Diffusion processes have a link to population dynamics, introduced by Verhulst in the mid-19th century.
References:
Alcón, F., Navarro, N., de-Miguel, M.D. & Balbo, A.L. (2019). “Drip irrigation technology: analysis of adoption and diffusion processes”. En Saukar, A., Sensarma, S. & van Loon, G. (Eds.): Sustainable Solutions for Food Security (pp. 269.285). Cham: Springer. https://doi.org/10.1007/978-3-319-77878-5_14
Bass, F.M. (1969). “A new product growth model for consumer durables”. Management Science, 15(5), 215-227. https://www.jstor.org/stable/2628128
Bass, F.M. (2004). “Comments on “A new product growth for model consumer durables, the Bass model”. Management Science, 50(12), 1833-1840. https://doi.org/10.1287/mnsc.1040.0300
Baumane-Vitolina, I. & Dudek, D. (2020). “Innovation ecosystems in the context of economic development: A case study of Kraków, Poland”. Studies of Transition States and Societies (STSS), 12(1), 32-52. https://doi.org/10.58036/stss.v12i1.770
Berbel, J. & Martínez-Dalmau, J. (2021). “Simple agro-economic model for optimal farm nitrogen application under yield uncertainty”. Agronomy, 11(6), 1107. https://doi.org/10.3390/agronomy11061107
Berkhout, P.H.G., Muskens, J.C. & Velthuijsen, W.J. (2000). “Defining the rebound effect”. Energy Policy, 28(6-7), 425-432. https://doi.org/10.1016/S0301-4215(00)00022-7
Bianco, V., Cascetta, F. & Nardini, S. (2021). “Analysis of technology diffusion policies for renewable energy. The case of the Italian solar photovoltaic sector”. Sustainable Energy Technologies and Assessments, 46, 101250. https://doi.org/10.1016/j.seta.2021.101250
Box, G.E.P. & Jenkins, G.M. (1970). Time series analysis: Forecasting and control. San Francisco: Holden-Day.
Calatrava, J., Franco, J.A. & González, M.C. (2007). “Analysis of the adoption of soil conservation practices in olive groves: The case of mountainous areas in southern Spain”. Spanish Journal of Agricultural Research, 5(3), 249-258. https://doi.org/10.5424/sjar/2007053-246
Calatrava, J. & Franco, J.A. (2011). “Difusión de prácticas de lucha contra la erosión en el olivar de la cuenca del Alto Genil Granadino”. Estudios de Economía Aplicada, 29(1), 359-384. https://doi.org/10.25115/eea.v29i1.3943
Cárdenas-Polonio, F., Martínez-Dalmau, J. & Berbel-Vecino, J. (2022). “Transferencia, Innovación y Agricultura: El caso de la difusión del cultivo del almendro en el sur de España”. ITEA, Información Técnica Económica Agraria, 118(3), 476-492. https://doi.org/10.12706/itea.2021.037
Cárdenas-Polonio, F., Martínez-Dalmau, J. & Berbel-Vecino, J. (2023). “Pistachio nut diffusion in Spain: Growth models”. Spanish Journal of Agricultural Research, 21(1), e0103. https://doi.org/10.5424/sjar/2023211-19474
Cárdenas-Polonio, F., Berbel-Vecino, J. & Martínez-Dalmau, J. (2024). Revisión bibliográfica estructurada (SLR) de modelos logísticos de difusión, presentado a la revista EARN [Dataset]. Obtenido de: Repositorio Digital de la Universidad de Córdoba HELVIA. http://hdl.handle.net/10396/32520
Carmona-Martínez, M.M., Gómez-García J. & Faura-Martínez, U. (2005). “La difusión de la agricultura ecológica en España: una propuesta de modelización matemática”. Revista Española de Estudios Agro-sociales y Pesqueros, 205, 39-63. https://www.mapa.gob.es/ministerio/pags/biblioteca/revistas/pdf_REEAP/r205_02.pdf
Carrillo, M. & González, J.M. (2002). “A new approach to modelling sigmoidal curves”. Technological Forecasting and Social Change, 69, 233-241. https://doi.org/10.1016/S0040-1625(01)00150-0
Centrone, F., Goia, A. & Salinelli, E. (2007). “Demographic processes in a model of innovation diffusion with a dynamic market”. Technological Forecasting and Social Change, 74(3), 247-266. https://doi.org/10.1016/j.techfore.2006.02.006
Christodoulos, C., Michalakelis, C. & Varoutas, D. (2010). “Forecasting with limited data: Combining ARIMA and diffusion models”. Technological Forecasting and Social Change, 77(4), 558-565. https://doi.org/10.1016/j.techfore.2010.01.009
Corró-Molas, A. (2007). Difusión de la agricultura de precisión en la Región Semiárida Pampeana Central. Obtenido de: Revista Iberoamericana de Ciencia, Tecnología y Sociedad. https://www.revistacts.net/difusion-de-la-agricultura-de-precision-en-la-region-semiarida-pampeana-central/
Dattée, B. & Birdseye-Weil, H. (2007). “Dynamics of social factors in technological substitutions”. Technological Forecasting and Social Change, 74(5), 579-607. https://doi.org/10.1016/j.techfore.2007.03.003
Dinar, A. & Yaron, D. (1990). “Influence of quality and scarcity of inputs on the adoption of modern irrigation technologies”. Western Journal of Agricultural Economics, 15(2). 224-233. https://www.jstor.org/stable/40988086
Dumay, J. & Cai, L. (2014). “A review and critique of content analysis as a methodology for inquiring into IC disclosure”. Journal of Intellectual Capital, 15(2), 264-290. https://doi.org/10.1108/JIC-01-2014-0010
Easingwood, C., Mahajan, V. & Muller, E. (1981). “A non-symmetric responding logistic model for forecasting technological substitution”. Technological Forecasting and Social Change, 20(3), 199-213. https://doi.org/10.1016/0040-1625(81)90021-4
Easingwood, C.J., Mahajan, V. & Muller, E. (1983). “A nonuniform influence innovation diffusion model of new product acceptance”. Marketing Science, 2(3), 273-295. https://doi.org/10.1287/mksc.2.3.273
Feder, G., Just, R.E. & Zilberman, D. (1985). “Adoption of agricultural innovations in developing countries: A survey”. Economic Development and Cultural Change, 33(2), 255-298. https://doi.org/10.1086/451461
Fishelson, G. & Rymon, D. (1989). “Adoption of agricultural innovations. The case of drip irrigation of cotton in Israel”. Technological Forecasting and Social Change, 35(4), 375-382. https://doi.org/10.1016/0040-1625(89)90073-5
Fleischer, A., Mendelsohn, R. & Dinar, A. (2011). “Bundling agricultural technologies to adapt to climate change”. Technological Forecasting and Social Change, 78(6), 982-990. https://doi.org/10.1016/j.techfore.2011.02.008
Floyd, A. (1968). “A methodology for trend forecasting of figures of merit”. En Bright, J.R. (Ed.): Technological forecasting for industry and government: Methods and applications (pp. 93-107). Englewood Cliffs, New Jersey: Prentice-Hall.
Fluchs, S. (2020). “The diffusion of electric mobility in the European Union and Beyond”. Transportation Research Part D: Transport and Environment, 86, 102462. https://doi.org/10.1016/j.trd.2020.102462
Foster, A.D. & Rosenzweig, M.R. (2010). “Microeconomics of technology adoption”. Annual Review of Economics, 2, 395-424. https://doi.org/10.1146/annurev.economics.102308.124433
Franco, J.A. & Calatrava, J. (2010). “Adopción y difusión de prácticas de no laboreo en el olivar de la provincia de Granada”. Economía Agraria y Recursos Naturales, 10(1), 135-154. https://doi.org/10.7201/earn.2010.01.08
Franco-Martínez, J. & Rodríguez-Entrena, M. (2009). “Adopción y difusión de la agricultura ecológica en España. Factores de reconversión en el olivar andaluz”. Cuadernos de Economía, 32(90), 137-158. https://doi.org/10.1016/S0210-0266(09)70055-X
Gao, J., Zhang, R., Zhao, T. & Liu, J. (2024). “Exploration of hydrogen technology diffusion and network characteristics across multiple channels”. International Journal of Hydrogen Energy, 85(4), 469-480. https://doi.org/10.1016/j.ijhydene.2024.08.294
Genius, M., Koundouri, P., Nauges, C. & Tzouvelekas, V. (2013). “Information transmission in irrigation technology adoption and diffusion: social learning, extension services, and spatial effects”. American Journal of Agricultural Economics, 96(1), 328-344. https://doi.org/10.1093/ajae/aat054
Gholizadeh, P, Esmaeili, B. & Goodrum, P. (2018). “Diffusion of building information modeling functions in the construction industry”. Journal of Management in Engineering, 12(8), 7762. https://doi.org/10.3390/su12187762
Griliches, Z. (1957). “Hybrid corn: An exploration in the economics of technological change”. Econometrica, 4, 501-522. https://doi.org/10.2307/1905380
Griliches, Z. (1960). “Hybrid corn and the economics of innovation”. Science, 132(3422), 275-280. https://www.jstor.org/stable/1705534
Harvey, A. & Kattuman, P. (2020). “Time series models based on growth curves with applications to forecasting Coronavirus”. Harvard Data Science Review, Special Issue 1: COVID-19: Unprecedented Challenges and Chances. https://doi.org/10.1162/99608f92.828f40de
Herman, R. & Montroll, E.W. (1972). “A manner of characterizing the development of countries”. Proceeding of the National Academy of Sciences, 69(10), 3019-3023. https://doi.org/10.1073/pnas.69.10.3019
Jarne, G., Sánchez-Choliz, J. & Fatas-Villafranca, F. (2007). “S-shaped curves in economic growth. A theoretical contribution and an application”. Evolutionary and Institutional Economics Review, 3, 239-259. https://doi.org/10.14441/eier.3.239
Jarvis, L.S. (1981). “Predicting the diffusion of improved pastures in Uruguay”. American Journal of Agricultural Economics, 63(3), 495-502. https://doi.org/10.2307/1240540
Karshenas, M. & Stoneman, P. (1995). “Technological Diffusion”. En Stoneman, P. (Ed.): Handbook of the Economics of Innovation and Technological Change (pp. 265-296). Cambridge: Ed. Blackwell.
LaMorte, W.W. (2019). Diffusion of innovation theory. Obtenido de: Boston University School of Public Health. https://sphweb.bumc.bu.edu/otlt/mph-modules/sb/behavioralchangetheories/behavioralchange theories4.html
Mahajan, V., Muller, E. & Bass, F.M. (1990). “New product diffusion models in marketing: A review and directions for research”. Journal of Marketing, 54(1), 1-26. https://doi.org/10.1177/002224299005400101
Marchetti, C & Nakicenovic, N. (1980). The dynamics of energy systems and the logistic substitution model. Laxenburg, Austria: International Institute for Applied Systems Analysis. https://pure.iiasa.ac.at/id/eprint/1024/1/RR-79-013.pdf
Massaro, M., Dumay, J. & Garlatti, A. (2015). “Public sector knowledge management: A structured literature review”. Journal of Knowledge Management, 19(3), 530-558. https://doi.org/10.1108/JKM-11-2014-0466
Massaro, M., Dumay, J. & Guthrie, J. (2016). “On the shoulders of giants: Undertaking a structured literature review in accounting”. Accounting, Auditing and Accountability Journal, 29(5), 767-801. https://doi.org/10.1108/AAAJ-01-2015-1939
Massiani, J. & Gohs, A. (2015). “The choice of Bass model coefficients to forecast diffusion for innovative products: An empirical investigation for new automotive technologies”. Research in Transportation Economics, 50, 17-28. https://doi.org/10.1016/j.retrec.2015.06.003
Michalakelis, C., Varoutas, D. & Sphicopoulos, T. (2010). “Innovation diffusion with generation substitution effects”. Technological Forecasting and Social Change, 77(4), 541-557. https://doi.org/10.1016/j.techfore.2009.11.001
Mishra, D., Gunasekaran, A., Papadopoulos, T. & Hazen, B. (2017). “Green supply chain performance measures: A review and bibliometric analysis”. Sustainable Production and Consumption, 10, 85-99. https://doi.org/10.1016/j.spc.2017.01.003
Modis, T. (2007). “Strengths and weaknesses of S-curves”. Technological Forecasting and Social Change, 74(6), 866-872. https://doi.org/10.1016/j.techfore.2007.04.005
Morrison, J. (1996). “How to use diffusion models in new product forecasting”. The Journal of Business Forecasting Methods and Systems, 15(2), 6-9. https://ibf.org/knowledge/jbf-articles/how-to-use-diffusion-models-in-new-product-forecasting-448
Parra-López, C. (2003). Sistemas de producción ecológica, integrada y convencional en olivar: Estudio de difusión de innovaciones y evaluación multifuncional. Tesis Doctoral. Obtenido de: Universidad de Córdoba. https://www.educacion.gob.es/teseo/imprimirFichaConsulta.do?idFicha=93528
Parra-López, C. & Calatrava-Requena, J. (2002). “Análisis de factores relacionados con la adopción de la forma de producción ecológica en el olivar del sur de España”. Comunicación presentada al First IFOAM Worldwide Conference of Organic Olive Farming, Sierra de Génave, Spain.
Parra-López, C., De Haro-Giménez, T. & Calatrava-Requena, J. (2007). “Diffusion and adoption of organic farming in the southern Spanish olive groves”. Journal of Sustainable Agriculture, 30(1), 105-151. https://doi.org/10.1300/J064v30n01_09
Petticrew, M. (2001). “Systematic reviews from astronomy to zoology: Myths and misconceptions”. BMJ, 322, 98-101. https://doi.org/10.1136/bmj.322.7278.98
Polanco-Gaytán, M. & González-Sánchez, R.F. (2015). “Un análisis econométrico de las redes de difusión de innovación en el sistema de producción del mango (Mangifera indica L.) en el estado de Colima”. Avances en Investigación Agropecuaria, 19(1), 7-30. https://ww.ucol.mx/revaia/portal/ver_pdf.php?articulo=203
Pronti, A., Auci, S., & Berbel, J. (2024). “Water conservation and saving technologies for irrigation. A structured literature review of econometric studies on the determinants of adoption”. Agricultural Water Management, 299, 108838. https://doi.org/10.1016/j.agwat.2024.108838
Rogers, E.M. (1962). Diffusion of innovations. Nueva York: The Free Press. Ed.
Rogers, E.M. (1995). Diffusion of innovations, 4th Edition. Nueva York: The Free Press. Ed.
Rogers, E.M. (2003). Diffusion of innovations, 5th Edition. Nueva York: The Free Press. Ed.
Ryan, B. & Gross, N.C. (1943). “The diffusion of hybrid seed corn in two Iowa communities”. Rural Sociology, 8(1), 15-24.
Scoponi, L., Durán, R., Pesce, G. & De Batista, M. (2011). “Difusión de la innovación tecnológica: El caso de la siembra directa en Argentina y su comparación con Brasil”. Revista Capital Científico – Guarapuava, 9(1), 11-25. https://revistas.unicentro.br/index.php/capitalcientifico/article/view/1563
Secundo, G., Ndou, V., Vecchio, P.D. & De Pascale, G. (2020). “Sustainable development, intellectual capital and technology policies: A structured literature review and future research agenda”. Technological Forecasting and Social Change, 153, 119917. https://doi.org/10.1016/j.techfore.2020.119917
Shehu, V. (2015). “Simple Logistic and Bi-Logistic growth used as forecasting models of greenhouse areas in Albanian agriculture”. Journal of Multidisciplinary Engineering Science and Technology (JMEST), 2(9), 2648-2653. https://www.jmest.org/wp-content/uploads/JMESTN42351100.pdf
Skaggs, R.K., (2001). “Predicting drip irrigation use and adoption in a desert region”. Agricultural Water Management, 51(2), 125-142. https://doi.org/10.1016/S0378-3774(01)00120-2
Skiadas, C. (1985). “Two generalized rational models for forecasting innovation diffusion”. Technological Forecasting and Social Change, 27(1), 39-61. https://doi.org/10.1016/0040-1625(85)90003-4
Skiadas, C.H. & Giovanis, A.N. (1997). “A stochastic Bass innovation diffusion model for studying the growth of electricity consumption in Greece”. Applied Stochastic Models and Data Analysis, 13(2), 85-101. https://doi.org/10.1002/(SICI)1099-0747(199706)13:2%3C85::AID-ASM298%3E3.0.CO;2-Z
Skoczkowski, T., Bielecki, S. & Wojtyńska, J. (2019). “Long-Term projection of renewable energy technology diffusion”. Energies, 12(22), 4261. https://doi.org/10.3390/en12224261
Sood, A. & Tellis, G., (2005). “Technological evolution and radical innovation”. Journal of Marketing, 69(3), 152-168. https://doi.org/10.1509/jmkg.69.3.152.66361
Sorrell, S. & Dimitropoulos, J. (2008). “The rebound effect: Microeconomic definitions, limitations and extensions”. Ecology Economics, 65(3), 636-649. https://doi.org/10.1016/j.ecolecon.2007.08.013
Stoneman, P. & Battisti, G. (2010). “The diffusion of new technology”. En Hall, B.H. & Rosenberg, N. (Eds.): Handbook of the Economics of Innovation – Vol. 2 (pp. 733-760). Amsterdam: North-Holland. https://doi.org/10.1016/S0169-7218(10)02001-0
Stoneman, P. (1986). “Technological diffusion: the viewpoint of economic theory”. Richerche Economiche, 40, 585-606.
Tsoularis, A. (2001). Analysis of logistic growth models. Research Letters in the Information and Mathematical Sciences. Obtenido de: Massey University. http://hdl.handle.net/10179/4341
Van de Bulte, C. & Stremersch, S. (2004). “Social contagion and income heterogeneity in new product diffusion: A meta-analytic test”. Marketing Science, 23(4), 530-544. https://doi.org/10.1287/mksc.1040.0054
Van den Bulte, C. (2000). “New product diffusion acceleration: measurement and analysis”. Marketing Science, 19(4), 297-398. https://doi.org/10.1287/mksc.19.4.366.11795
Verhulst, P.F. (1847). “La loi d’accoissemmt de la population (Deuxième mémoire)”. Mémoires de l’Académie Royale des Sciences et Belles-lettres de Belgique, 20, 1-32. https://www.persee.fr/doc/marb_0775-3225_1847_num_20_1_3457



