Performance Evaluation of Intelligent Agricultural Supply Chain Based on Structural Equation Model

Yujie Zhang; Na Li

doi:10.31181/dmame722024930

Authors

Yujie Zhang Department of Economics, Sejong University, Seoul, South Korea https://orcid.org/0009-0008-1014-7424
Na Li Department of Economics, Sejong University, Seoul, South Korea https://orcid.org/0009-0009-9545-4243

DOI:

https://doi.org/10.31181/dmame722024930

Keywords:

SC function, Structural equation model, Digital technology, Information sharing, Big data

Abstract

To solve the problems of unstable chain and poor supply chain (SC) function in the China’s agriculture industry, the relevant study is carried out on the function evaluation of the sustainable agricultural SC by structural equation modelling (SEM) under the background of digital technology. Primarily, the analysis is implemented on the research status of the sustainable SC and SC function. Then, starting with the relationship among big data (BD) application, information sharing, and sustainable SC function of agricultural production, a function evaluation model is implemented for the sustainable SC of SEM-based agricultural production. Next, a questionnaire is designed for the research on the impact of BD applications on the function of the sustainable agricultural SC. Ultimately, the statistical analysis of the obtained data reveals the correlation between the interaction and influence among the BD application, information sharing, and sustainable SC function of agricultural production. The results show that the BD application dimension, information sharing dimension, and all sub-dimensions have is beneficial to the function of the agricultural sustainable SC. The application of multidimensional cloud technology in BD has no obvious relationship with the dimensionality and level of information sharing, and the relationship between other corresponding dimensions shows a significant positive impact. A referenceable method is provided for the practice of sustainable SC management of agricultural production.

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References

Barbosa-Póvoa, A. P., da Silva, C., & Carvalho, A. (2018). Opportunities and challenges in sustainable supply chain: An operations research perspective. European journal of operational research, 268(2), 399-431. https://doi.org/10.1016/j.ejor.2017.10.036

Maia, A. L. M. D., & Frogeri, R. F. (2023). Optimizing business value via IT governance mechanisms: An examination of SMEs in Southern Minas Gerais, Brazil. J. Oper. Strateg Anal, 1(3), 106-114. https://doi.org/10.56578/josa010301

Aliahmadi, A., Nozari, H., Ghahremani-Nahr, J., & Szmelter-Jarosz, A. (2022). Evaluation of key impression of resilient supply chain based on artificial intelligence of things (AIoT). arXiv preprint arXiv:2207.13174. https://doi.org/10.48550/arXiv.2207.13174

Mankawade, A., Rothe, S., Shaikh, R., Bhavar, N., Narnaware, T., & Deshmukh, S. (2023, April). Processed Food Traceability using Blockchain Technology. In 2023 IEEE 8th International Conference for Convergence in Technology (I2CT) (pp. 1-7). IEEE. https://doi.org/10.1109/I2CT57861.2023.10126385

Eslamipoor, R., & Nobari, A. (2023). A reliable and sustainable design of supply chain in healthcare under uncertainty regarding environmental impacts. Journal of applied research on industrial engineering, 10(2), 256-272. https://doi.org/10.22105/jarie.2022.335389.1461

Mastrocinque, E., Ramírez, F. J., Honrubia-Escribano, A., & Pham, D. T. (2020). An AHP-based multi-criteria model for sustainable supply chain development in the renewable energy sector. Expert Systems with Applications, 150, 113321. https://doi.org/10.1016/j.eswa.2020.113321

Esmaeilian, B., Sarkis, J., Lewis, K., & Behdad, S. (2020). Blockchain for the future of sustainable supply chain management in Industry 4.0. Resources, Conservation and Recycling, 163, 105064. https://doi.org/10.1016/j.resconrec.2020.105064

Yadav, S., & Singh, S. P. (2020). Blockchain critical success factors for sustainable supply chain. Resources, Conservation and Recycling, 152, 104505. https://doi.org/10.1016/j.resconrec.2019.104505

Bui, T. D., Tsai, F. M., Tseng, M. L., Tan, R. R., Yu, K. D. S., & Lim, M. K. (2021). Sustainable supply chain management towards disruption and organizational ambidexterity: A data driven analysis. Sustainable production and consumption, 26, 373-410. https://doi.org/10.1016/j.spc.2020.09.017

Wang, T., Wang, Z., Guo, L., Zhang, J., Li, W., He, H., ... & Wen, Y. (2021). Experiences and challenges of agricultural development in an artificial oasis: A review. Agricultural Systems, 193, 103220. https://doi.org/10.1016/j.agsy.2021.103220

Qaim, M. (2020). Role of new plant breeding technologies for food security and sustainable agricultural development. Applied Economic Perspectives and Policy, 42(2), 129-150. https://doi.org/10.1002/aepp.13044

Farnam, M., & Darehmiraki, M. (2022). Supply chain management problem modelling in hesitant fuzzy environment. Journal of fuzzy extension and applications, 3(4), 317-336. https://doi.org/10.22105/jfea.2022.337573.1216

Zhou, Z. (2023). Soil quality based agricultural activity through IoT and wireless sensor network. Big Data and Computing Visions, 3(1), 26-31. https://doi.org/10.22105/bdcv.2022.332447.1056

Ehsani, A., Mehrmanesh, H., & Mohammadi, M. (2023). Identifying and Prioritizing Technology Capability Drivers in the Supply Chain Using the Fuzzy Hierarchical Analysis Process (Case Study: Iran Khodro and Saipa Automotive Company). International Journal of Research in Industrial Engineering (2783-1337), 12(1). https://doi.org/10.22105/riej.2022.332012.1301

Sıcakyüz, C. (2023). Bibliometric analysis of data envelopment analysis in supply chain management. Journal of Operational and Strategic Analytics, 1(1), 14-24. https://doi.org/10.56578/josa010103

Khan, S. A. R., Yu, Z., Golpira, H., Sharif, A., & Mardani, A. (2021). A state-of-the-art review and meta-analysis on sustainable supply chain management: Future research directions. Journal of Cleaner Production, 278, 123357. https://doi.org/10.1016/j.jclepro.2020.123357

Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International journal of production research, 57(7), 2117-2135. https://doi.org/10.1080/00207543.2018.1533261

Koberg, E., & Longoni, A. (2019). A systematic review of sustainable supply chain management in global supply chains. Journal of cleaner production, 207, 1084-1098. https://doi.org/10.1016/j.jclepro.2018.10.033

Asamoah, D., Agyei-Owusu, B., Andoh-Baidoo, F. K., & Ayaburi, E. (2021). Inter-organizational systems use and supply chain performance: Mediating role of supply chain management capabilities. International journal of information management, 58, 102195. https://doi.org/10.1016/j.ijinfomgt.2020.102195

Guan, Z., Zhang, X., Zhou, M., & Dan, Y. (2020). Demand information sharing in competing supply chains with manufacturer-provided service. International Journal of Production Economics, 220, 107450. https://doi.org/10.1016/j.ijpe.2019.07.023

Dhanaraju, M., Chenniappan, P., Ramalingam, K., Pazhanivelan, S., & Kaliaperumal, R. (2022). Smart farming: Internet of Things (IoT)-based sustainable agriculture. Agriculture, 12(10), 1745. https://doi.org/10.3390/agriculture12101745

Durán Peña, J. A., Ortiz Bas, Á., & Reyes Maldonado, N. M. (2021). Impact of bullwhip effect in quality and waste in perishable supply chain. Processes, 9(7), 1232. https://doi.org/10.3390/pr9071232

Ramanathan, U., He, Q., Subramanian, N., Gunasekaran, A., & Sarpong, D. (2023). Collaborative closed-loop supply chain framework for sustainable manufacturing: Evidence from the Indian packaging industry. Technological Forecasting and Social Change, 191, 122489. https://doi.org/10.1016/j.techfore.2023.122489

Xia, J., Li, H., & He, Z. (2023). The Effect of Blockchain Technology on Supply Chain Collaboration: A Case Study of Lenovo. Systems, 11(6), 299. https://doi.org/10.3390/systems11060299

Liu, M., Dan, B., Zhang, S., & Ma, S. (2021). Information sharing in an E-tailing supply chain for fresh produce with freshness-keeping effort and value-added service. European Journal of Operational Research, 290(2), 572-584. https://doi.org/10.1016/j.ejor.2020.08.026

Mehrjerdi, Y. Z., & Shafiee, M. (2021). A resilient and sustainable closed-loop supply chain using multiple sourcing and information sharing strategies. Journal of Cleaner Production, 289, 125141. https://doi.org/10.1016/j.jclepro.2020.125141

Liu, C., Xiang, X., & Zheng, L. (2020). Value of information sharing in a multiple producers–distributor supply chain. Annals of Operations Research, 285, 121-148. https://doi.org/10.1007/s10479-019-03259-2

Gawankar, S. A., Gunasekaran, A., & Kamble, S. (2020). A study on investments in the big data-driven supply chain, performance measures and organisational performance in Indian retail 4.0 context. International journal of production research, 58(5), 1574-1593. https://doi.org/10.1080/00207543.2019.1668070

Bamakan, S. M. H., Faregh, N., & ZareRavasan, A. (2021). Di-ANFIS: an integrated blockchain–IoT–big data-enabled framework for evaluating service supply chain performance. Journal of Computational Design and Engineering, 8(2), 676-690. https://doi.org/10.1093/jcde/qwab007

Kamble, S. S., & Gunasekaran, A. (2020). Big data-driven supply chain performance measurement system: a review and framework for implementation. International journal of production research, 58(1), 65-86. https://doi.org/10.1080/00207543.2019.1630770

Wan, P. K., Huang, L., & Holtskog, H. (2020). Blockchain-enabled information sharing within a supply chain: A systematic literature review. IEEE access, 8, 49645-49656. https://doi.org/10.1109/ACCESS.2020.2980142

Yoon, J., Talluri, S., & Rosales, C. (2020). Procurement decisions and information sharing under multi-tier disruption risk in a supply chain. International Journal of Production Research, 58(5), 1362-1383. https://doi.org/10.1080/00207543.2019.1634296

Jo, H. I., & Jeon, J. Y. (2021). Overall environmental assessment in urban parks: Modelling audio-visual interaction with a structural equation model based on soundscape and landscape indices. Building and Environment, 204, 108166. https://doi.org/10.1016/j.buildenv.2021.108166