Determinants of Eco-Innovations in Agricultural Production Cooperatives in Iran

Document Type : Original Research

Authors
M. Alizadeh
A. R. Ommani
A. Noorollah Noorivandi
T. Maghsoodi
Department of Agricultural Extension and Education, Shoushtar Branch, Islamic Azad University, Shoushtar, Islamic Republic of Iran.
Abstract
The purpose of this study was to identify determinants of Eco-Innovations (EI) in agricultural production cooperatives in Iran. Qualitative and quantitative methods were applied to the research. The qualitative section included semi-structured interviews, face-to-face interviews, and brainstorming sessions, and the quantitative section included descriptive statistical and spatial and Bayesian probit models to estimate the model of research. SPSS and MATLAB software was used in this study. SPSS software was used to describe the variables, explain the types of EIs and their effects and comparison of adopters and non- adopters, and MATLAB software was used for the estimation of the model. The data of 300 members of agricultural production cooperatives in Khouzestan Province, Iran, were collected based on random sampling, in 2020 summer. The research examined the different types of EIs. For comparison of adopter and non-adopter characteristics, a t-test and Mann-Whitney test (MW) were used. The results of the t-test showed that there was a significant difference between age, income, crop yield, and farm size for adopters and non-adopters of EI. The Mann Whitney U test (MW) showed significant difference between farmers’ education level, EI awareness, attitude toward EI, EI knowledge, willingness to creativity, being risk oriented, and access to information of adopters and non-adopters of EI. Based on the results obtained from the spatial models, with a probability of 99%, both models were significant. Based on the results of the estimation of spatial models, the independent variables and the spatial autoregressive coefficient had significant role on adoption of EI. For practical implications, it can be said that cooperative members, when adopting the EIs, can use the proposed model that is appropriate to their field of work. This study conducted a critical review before specifically recommending how cooperatives become eco-innovators.

Keywords

Subjects

1) Anselin, L. (1998). Spatial econometrics: Methods and models. Dorddrecht: Kluwer Academic Publishers, 1988.
2) Arranz, N., Arroyabe, M. F., Molina-García, A and Fernandez de Arroyabe, J. C. (2019). Incentives and inhibiting factors of eco-innovation in the Spanish firms, Journal of Cleaner Production, Volume 220, Pages 167-176.
3) Azevedo, S., M. Brandenburg, H. Carvalho, V. Cruz-Machado. (2014). Eco-innovation and the development of business models: Lessons from experience and New Frontiers in Theory and Practice, Greening of Industry Network Studies series" Springer (ISBN: 978-3-319-05076-8).
4) Cai, W and Li, G. (2018). The drivers of eco-innovation and its impact on performance: Evidence from China, Journal of Cleaner Production, Volume 176, 1 March 2018, Pages 110-118.
5) Chizari, M.; Ommani, AR. (2009). The analysis of dryland sustainability, Journal of Sustainable Agriculture, 33, 848-861
6) Colombo, L. A.; Pansera, M.; Owen, R. (2019). The discourse of eco-innovation in the European :union:: An analysis of the Eco-Innovation Action Plan and Horizon 2020, Journal of Cleaner Production,214, Pages 653-665.
7) Costantini, V., Crespi, F., Marin, G and Paglialunga, E. (2017). Eco-innovation, sustainable supply chains and environmental performance in European industries, Journal of Cleaner Production, Volume 155, Part 2, 1 July 2017, Pages 141-154.
8) Department for Environment, Food and Rural Affairs (DEFRA). (2006). Procuring the Future Sustainable Procurement National Action Plan: Recommendations from the Sustainable Procurement Task Force, Department for Environment, Food and Rural Affairs Nobel House 17 Smith Square London SW1P 3JR.
9) Dudek, M.; Wrzaszcz, W. (2020). On the Way to Eco-Innovations in Agriculture: Concepts, Implementation and Effects at National and Local Level. The Case of Poland, Sustainability 2020, 12, 4839; doi:10.3390/su12124839
10) Fussler, C.; James, P. (1996). Driving Eco-Innovation. London: Pitman Publishing.
11) García-Granero, E. M., Piedra-Muñoz, L and Galdeano-Gómez, E. (2018). Eco-innovation measurement: A review of firm performance indicators, Journal of Cleaner Production, Volume 191, 1 August 2018, Pages 304-317.
12) Hoji, J and Ruzzier, M. (2016). What drives eco-innovation? A review of an emerging literature, Environmental Innovation and Societal Transitions, Volume 19, Pages 31-41.
13) Holloway, G.; Shankar, B.; Rahman, S. (2002). Bayesian spatial probit estimation: a primer and an application to HYV rice adoption, Agricultural Economics, 2002, 27, 383-402.
14) Horbach, J. (2008). Determinants of environmental innovation—New evidence from German panel data sources. Res. Policy, 37, 163–173.
15) Kesidou, E and Demirel, P. (2012). On the drivers of eco-innovations: Empirical evidence from the UK, Research Policy, Volume 41, Issue 5, Pages 862-870.
16) Kesidou, E.; Demirel, P. (2010). On the Drivers of Eco-Innovations: Empirical Evidence from the UK. NUBS Research Paper Series No. 2010-03. Nottingham University Business School, Nottingham, UK, 2010.
17) LeSage, J. P. (2008). An Introduction to Spatial Econometrics , Revue d'économie industrielle, 2008, 123, 19-44.
18) Marin, G. (2014). Do eco-innovations harm productivity growth through crowding out? Results of an extended CDM model for Italy, Research Policy, Volume 43, Issue 2, March 2014, Pages 301-317.
19) Nidumolu, R., Prahalad, C. K., & Rangaswami, M. R. (2009). Why sustainability is now the key driver of innovation. Harvard Business Review, 87, 56–64.
20) Ociepa-Kubicka, A and Pachura, P. (2017). Eco-innovations in the functioning of companies, Environmental Research, Volume 156, Pages 284-290.
21) Ommani, A.; Noorollah Noorivandi, A. (2017). Bayesian Analysis of Spatial Probit Models in Wheat Waste Management Adoption. International Journal of Agricultural Management and Development, 2017,9, 37-44.
22) Organization for Economic Co-operation and Development (OECD). (2005). Oslo Manual: Guidelines for Collecting and Interpreting Innovation Data, 3rd ed.; OECD: Paris, France.
23) Ozusaglam, S. (2012). Environmental innovation: a concise review of the literature, Innovation et environnement, VSE, 191, 2-3, 15-38.
24) Paelinck, J., & Klaassen, L. (1979). Spatial econometrics. Farnborough: Saxon House, 1979.
25) Rammel, C. (2003). Sustainable development and innovations: lessons from the Red Queen, International Journal of Sustainable Development, 2003, 6, 4,395- 416.
26) Rennings, K. (2000). Redefining innovation, eco-innovation research and the contribution from ecological economics, Ecological Economics, Volume 32, Issue 2, February 2000, Pages 319-332.
27) Sehnem, S., Lazzarotti, F and Bencke, F. (2016). Sustainable practices and eco-innovations adopted by industrial companies, International Journal of Innovation, 4(2):42-58.
28) Smith, T.E.; LeSage, J.P. A. (2004). Bayesian Probit Model With Spatial Dependencies, Lesage, J.P. and Kelley Pace, R. (Ed.) Spatial and Spatiotemporal Econometrics (Advances in Econometrics), Emerald Group Publishing Limited, Bingley, 2004, 18, 127-160.
29) Szilagyi, A., Mocan, M., Verniquet, A., Churican, A and Rochat, D. (2018). Eco-innovation, a Business Approach towards Sustainable Processes, Products and Services, Procedia - Social and Behavioral Sciences, Volume 238, 2018, Pages 475-484.
30) Varadarajan, R. (2017). Innovating for sustainability: a framework for sustainable innovations and a model of sustainable innovations orientation. Journal of the Academy of Marketing Science. 45, 14–36 (2017). https://doi.org/10.1007/s11747-015-0461-6
31) Wooldridge, J. (2002). Econometric analysis of cross section and panel data. MIT Press, US, 2002.
Journal of Agricultural Science and Technology
Volume 24, Issue 1
January and February 2022
Pages 1-12