Research on World Agricultural Economy

Examining the Factors Influencing the Level of Circular Economy Adoption in Agriculture: Insights from Vietnam

The Kien Nguyen

VNU University of Economics and Business, Vietnam National University, Hanoi, 100000, Vietnam

Nguyen Thi Minh Khue

VNU University of Economics and Business, Center for Socio-Economic Analysis and Databases (CSEAD), Hanoi,100000, Vietnam

Quang Phu Tran

Ho Chi Minh National Academy of Politics, Department of training management, Hanoi, 100000, Vietnam

Nguyen Thi Quynh Anh

VNU University of Economics and Business, Vietnam National University, Hanoi, 100000, Vietnam

Le Khanh Cuong

VNU University of Economics and Business, Vietnam National University, Hanoi, 100000, Vietnam

Nguyen Chu Du

Trade Union University, Hanoi, 100000, Vietnam

Chu Viet Cuong

Thuongmai University, Cau Giay, Hanoi, 100000, Vietnam

Vu Thi Thuong

VNU University of Economics and Business, Vietnam National University, Hanoi, 100000, Vietnam

Dang Hoang Anh

Thuongmai University, Cau Giay, Hanoi, 100000, Vietnam

Nguyen Anh Vu

Ministry of Education and Training, Hanoi, 100000, Vietnam

DOI: https://doi.org/10.36956/rwae.v5i1.992

Received: 25 November 2023; Received in revised form: 11 March 2024; Accepted: 13 March 2024; Published: 29 March 2024

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Abstract

The development of a circular economy in agricultural production has become a trend for many countries, especially as global natural resources worldwide are increasingly depleting. Therefore, the economic model transition to address the challenge of balancing economic growth and environmental protection, in general, and the plan for agricultural production development, in particular, is highly necessary. In this study, the authors examine the factors influencing the level of circular economy application in agriculture in Vietnam. The research employs a survey method using questionnaires to collect data from individuals and households engaged in the agriculture sector in Vietnam. Out of the 500 distributed questionnaires, 421 valid responses were collected. The influencing factors will be measured using a Likert scale, and to assess their reliability, the authors used Cronbach’s Alpha and inter-item correlation coefficients. To test the research hypotheses, the Structural Equation Modeling (SEM) method is utilized. The results reveal that among the factors included in the principal component analysis, financial factors have the strongest influence, followed by technological application, awareness, production scale, and finally, government policies. In summary, this study sheds light on the importance of various factors influencing the adoption of circular economy practices in agriculture. It can provide valuable information to policymakers, enabling them to make informed macro and micro-level decisions aimed at increasing the proportion of businesses applying circular economy principles in agricultural production.

Keywords: Circular economy, Income, Policies, Scientific and technical, Households

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References

[1] Nguyen, V. K., 2020. Perception of Challenges in Opportunities for Organic Food Research and Development in Vietnam. Regulatory issues in organic food safety in the Asia Pacific, 199-216.

[2] Abadie, A., Roux, M., Chowdhury, S., et al., 2023. Interlinking organisational resources, AI adoption and omnichannel integration quality in Ghana’s healthcare supply chain. Journal of Business Research, 162, 113866.

[3] Luoma, P., Toppinen, A., Penttinen, E., 2021. The role and value of data in realising circular business models–a systematic literature review. Journal of business models, 9(2), 44-71.

[4] Cezarino, L. O., Liboni, L. B., Oliveira Stefanelli, N., et al., 2021. Diving into emerging economies bottleneck: Industry 4.0 and implications for circular economy. Management Decision, 59(8), 1841-1862.

[5] Xu, Y., Zhang, L., Yeh, C.H., et al., 2018. Evaluating WEEE recycling innovation strategies with interacting sustainability-related criteria. Journal of Cleaner Production. 190, 618–629. DOI: https://doi.org/10.1016/j.jclepro.2018.04.078

[6] Zabaniotou, A., 2018. Redesigning a bioenergy sector in EU in the transition to circular waste-based Bioeconomy—A multidisciplinary review. Journal of Cleaner Production. 177, 197–206. DOI: https://doi.org/10.1016/j.jclepro.2017.12.172

[7] Zoboli, O., Zessner, M., Rechberger, H., 2016. Supporting phosphorus management in Austria: Potential, priorities and limitations. Science of the Total Environment. 565, 313–323. DOI: https://doi.org/10.1016/j.scitotenv.2016.04.171

[8] Rauw, W.M., Gomez‐Raya, L., Star, L., et al., 2023. Sustainable development in circular agriculture: An illustrative bee↺ legume↺ poultry example. Sustainable Development. 31(2), 639–648. DOI: https://doi.org/https://doi.org/10.1002/sd.2435

[9] Silvius, J., Hoogstra, A.G., Candel, J.J., et al., 2023. Determining the transformative potential of circular agriculture initiatives. Ambio. 52, 1968–1980. DOI: https://doi.org/10.1007/s13280-023-01894-5

[10] Moreira, S.G., Hoogenboom, G., Nunes, M.R., et al., 2024. Circular agriculture practices enhance phosphorus recovery for large-scale commercial farms under tropical conditions. The Journal of Agricultural Science. 161(6), 763–777. DOI: https://doi.org/10.1017/S0021859624000042

[11] Hoogstra, A.G., Silvius, J., de Olde, E.M., et al., 2024. The transformative potential of circular agriculture initiatives in the North of the Netherlands. Agricultural Systems. 214, 103833. DOI: https://doi.org/10.1016/j.agsy.2023.103833

[12] Kirchherr, J., Piscicelli, L., Bour, R., et al., 2018. Barriers to the circular economy: Evidence from the European Union (EU). Ecological Economics. 150, 264–272. DOI: https://doi.org/10.1016/j.ecolecon.2018.04.028

[13] Prieto-Sandoval, V., Jaca, C., Ormazabal, M., 2018. Towards a consensus on the circular economy. Journal of Cleaner Production. 179, 605–615. DOI: https://doi.org/10.1016/j.jclepro.2017.12.224

[14] Ghisellini, P., Cialani, C., Ulgiati, S., 2016. A review on circular economy: The expected transition to a balanced interplay of environmental and economic systems. Journal of Cleaner Production. 114, 11–32. DOI: https://doi.org/10.1016/j.jclepro.2015.09.007

[15] Shen, K.W., Li, L., Wang, J.Q., 2020. Circular economy model for recycling waste resources under government participation: A case study in industrial waste water circulation in China. Technological and Economic Development of Economy. 26(1), 21–47. DOI: https://doi.org/10.3846/tede.2019.11249

[16] Geissdoerfer, M., Savaget, P., Bocken, N.M., et al., 2017. The Circular Economy—A new sustainability paradigm? Journal of Cleaner Production. 143, 757–768. DOI: https://doi.org/10.1016/j.jclepro.2016.12.048

[17] Liu, Z., Adams, M., Cote, R.P., et al., 2018. How does circular economy respond to greenhouse gas emissions reduction: An analysis of Chinese plastic recycling industries. Renewable and Sustainable Energy Reviews. 91, 1162–1169. DOI: https://doi.org/10.1016/j.rser.2018.04.038

[18] Whicher, A., Harris, C., Beverley, K., et al., 2018. Design for circular economy: Developing an action plan for Scotland. Journal of Cleaner Production. 172, 3237–3248. DOI: https://doi.org/10.1016/j.jclepro.2017.11.009

[19] da Silva, C.L., 2018. Proposal of a dynamic model to evaluate public policies for the circular economy: Scenarios applied to the municipality of Curitiba. Waste Management. 78, 456–466. DOI: https://doi.org/10.1016/j.wasman.2018.06.007

[20] Liu, L., Liang, Y., Song, Q., et al., 2017. A review of waste prevention through 3R under the concept of circular economy in China. Journal of Material Cycles and Waste Management. 19, 1314–1323. DOI: https://doi.org/10.1007/s10163-017-0606-4

[21] Marra, A., Mazzocchitti, M., Sarra, A., 2018. Knowledge sharing and scientific cooperation in the design of research-based policies: The case of the circular economy. Journal of Cleaner Production. 194, 800–812. DOI: https://doi.org/10.1016/j.jclepro.2018.05.164

[22] Bassi, F., Dias, J.G., 2019. The use of circular economy practices in SMEs across the EU. Resources, Conservation and Recycling. 146, 523–533. DOI: https://doi.org/10.1016/j.resconrec.2019.03.019

[23] Bianchi, R., Noci, G., 1998. “Greening” SMEs’ competitiveness. Small Business Economics. 11(3), 269–281. DOI: https://doi.org/10.1023/A:1007980420087

[24] Hoogendoorn, B., Guerra, D., Van Der Zwan, P., 2015. What drives environmental practices of SMEs? Small Business Economics. 44, 759–781. DOI: https://doi.org/10.1007/s11187-014-9618-9

[25] Lepoutre, J., Heene, A., 2006. Investigating the impact of firm size on small business social responsibility: A critical review. Journal of Business Ethics. 67, 257–273. DOI: https://doi.org/10.1007/s10551-006-9183-5

[26] Aragón-Correa, J.A., Hurtado-Torres, N., Sharma, S., et al., 2008. Environmental strategy and performance in small firms: A resource-based perspective. Journal of Environmental Management. 86(1), 88–103. DOI: https://doi.org/10.1016/j.jenvman.2006.11.022

[27] Chen, M.J., Hambrick, D.C., 1995. Speed, stealth, and selective attack: How small firms differ from large firms in competitive behavior. Academy of Management Journal. 38(2), 453–482.

[28] Rao, P., 2004. Greening production: A south‐east Asian experience. International Journal of Operations & Production Management. 24(3), 289–320. DOI: https://doi.org/10.1108/01443570410519042

[29] Cherrafi, A., Elfezazi, S., Govindan, K., et al., 2017. A framework for the integration of Green and Lean Six Sigma for superior sustainability performance. International Journal of Production Research. 55(15), 4481–4515. DOI: https://doi.org/10.1080/00207543.2016.1266406

[30] Piyathanavong, V., Garza-Reyes, J.A., Kumar, V., et al., 2019. The adoption of operational environmental sustainability approaches in the Thai manufacturing sector. Journal of Cleaner Production. 220, 507–528. DOI: https://doi.org/10.1016/j.jclepro.2019.02.093

[31] Rajput, S., Singh, S.P., 2020. Industry 4.0 Model for circular economy and cleaner production. Journal of Cleaner Production. 277, 123853. DOI: https://doi.org/10.1016/j.jclepro.2020.123853

[32] Onyeaka, H., Tamasiga, P., Nwauzoma, U.M., et al., 2023. Using artificial intelligence to tackle food waste and enhance the circular economy: Maximising resource efficiency and Minimising environmental impact: A review. Sustainability. 15(13), 10482. DOI: https://doi.org/10.3390/su151310482

[33] de Mattos Nascimento, D.L., de Oliveira‐Dias, D., Moyano‐Fuentes, J., et al., 2024. Interrelationships between circular economy and Industry 4.0: A research agenda for sustainable supply chains. Business Strategy and the Environment. 33(2), 575–596. DOI: https://doi.org/10.1002/bse.3502

[34] Xie, Z., Tian, G., Tao, Y., 2022. A multi-criteria decision-making framework for sustainable supplier selection in the circular economy and Industry 4.0 era. Sustainability. 14(24), 16809. DOI: https://doi.org/10.3390/su142416809

[35] Sharma, S.K., Panda, B.N., Mahapatra, S.S., et al., 2011. Analysis of barriers for reverse logistics: An Indian perspective. International Journal of Modeling and Optimization. 1(2), 101–106.

[36] Jensen, S.F., Kristensen, J.H., Uhrenholt, J.N., et al., 2022. Unlocking barriers to circular economy: An ISM-based approach to contextualizing dependencies. Sustainability. 14(15), 9523. DOI: https://doi.org/10.3390/su14159523

[37] Hair, E., Halle, T., Terry-Humen, E., et al., 2006. Children’s school readiness in the ECLS-K: Predictions to academic, health, and social outcomes in first grade. Early Childhood Research Quarterly. 21(4), 431–454.

[38] Nunnally, J. C., Bernstein, I. H., 1994. Psychometric theory (3rd ed.). New York, NY: McGraw-Hill

[39] Arbuckle, J.L., Wothke, W., 1999. Amos 4.0 user’s guide. SmallWaters Corporation: Chicago, IL. pp. 1995–2005.

[40] Rupp, M.T., Segal, R., 1989. Confirmatory factor analysis of a professionalism scale in pharmacy. Journal of Social and Administrative Pharmacy. 6(1), 31–38.

[41] Cohen, J., 1988. Set correlation and contingency tables. Applied Psychological Measurement. 12(4), 425–434. DOI: https://doi.org/10.1177/014662168801200410

[42] Hu, L.T., Bentler, P.M., 1999. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal. 6(1), 1–55. DOI: https://doi.org/10.1080/10705519909540118