Digitalização e convergência da sustentabilidade: aplicação da inteligência artificial para melhorar a sustentabilidade das cadeias de valor agroalimentares na África

Autores

  • David Pooe PhD in Business Management, Professor and Acting Director, School of Management, University of Johannesburg, Johannesburg, GP, South Africa
  • Watson Munyanyi PhD in Business Management, Postdoctoral Research Fellow, Department of Business Management, University of Johannesburg, Johannesburg, GP, South Africa https://orcid.org/0000-0003-1727-8351

DOI:

https://doi.org/10.18472/SustDeb.v16n1.2025.55859

Palavras-chave:

Cadeia de abastecimento agroalimentar, Cadeias de valor, Inteligência Artificial, Resiliência, Sustentabilidade, SDGs

Resumo

A convergência entre digitalização e sustentabilidade oferece um potencial transformador para as cadeias de valor agroalimentares na África. Aplicando modelagem de equações estruturais, este artigo analisa a convergência entre digitalização e sustentabilidade nas cadeias de valor agroalimentares da África, incluindo o papel mediador da resiliência da cadeia de suprimentos agroalimentar. O papel crítico que a Inteligência Artificial desempenha no fortalecimento da resiliência da cadeia de suprimentos
de alimentos na África está no centro deste estudo. Esta pesquisa segue uma abordagem dedutiva para alcançar seu objetivo, apoiando-se em teorias consolidadas para orientar o desenvolvimento do modelo conceitual e das hipóteses. Os resultados destacam a importância de iniciativas impulsionadas por IA, tais como Farmers' Yield Optimization (Otimização do Rendimento Agrícola), Food Retail Demand Prediction (Previsão de Demanda no Varejo de Alimentos), Real-time Data Analysis (Análise de Dados em Tempo Real) e Enhanced Supply Chain Administration (Gestão Aprimorada da Cadeia de Suprimentos) na consolidação da resiliência das cadeias de suprimentos agroalimentares. Essas descobertas sugerem que investir em medidas de construção de resiliência pode gerar benefícios de longo prazo para a estabilidade e sustentabilidade dos sistemas agroalimentares.

Downloads

Não há dados estatísticos.

Biografia do Autor

David Pooe, PhD in Business Management, Professor and Acting Director, School of Management, University of Johannesburg, Johannesburg, GP, South Africa

Prof David Pooe is currently a Full Professor and Acting Director in the School of Management. His research areas include supply chains, enterprise development, and strategy. Prof Pooe has successfully supervised numerous Masters and PhD students and currently supervising a number of those. His work has been published in several journals both locally and internationally. Over the years, Prof Pooe has established international links with colleagues in his field of research.

Watson Munyanyi, PhD in Business Management, Postdoctoral Research Fellow, Department of Business Management, University of Johannesburg, Johannesburg, GP, South Africa

Dr Watson Munyanyi is an academic researcher and postdoctoral research fellow with the University of Johannesburg. The author has contributed to several research topics in small and medium-sized enterprises and financial services development. His contributions are rooted in a robust understanding of Fourth Industrial Revolution (4IR) implications for supply chains in SMEs. With a strong foundation in financial analysis, Dr Munyanyi’s research integrates into the realm of digital business strategy, enhancing the educational landscape and fostering innovation.

Referências

AFESORGBOR, S. K.; FIANKOR, D. D. D.; DEMENA, B. A. Do regional trade agreements affect agri‐food trade? Evidence from a meta‐analysis. Applied Economic Perspectives and Policy, v. 46, n. 2, p. 737-759, 2024.

AWOKUSE, T.; LIM, S.; SANTERAMO, F.; STEINBACH, S. Robust policy frameworks for strengthening the resilience and sustainability of agri-food global value chains. Food Policy, v. 127, p. 102714, 2024.

AYAZ, M.; AMMAD-UDDIN, M.; SHARIF, Z.; MANSOUR, A.; AGGOUNE, E. H. M. Internet-of-Things (IoT)-based smart agriculture: toward making the fields talk. IEEE access, v. 7, p. 129551-129583, 2019.

BAG, S.; GUPTA, S.; LUO, Z. Examining the role of logistics 4.0 enabled dynamic capabilities on firm performance. The international journal of logistics management, v. 31, n. 3, p. 607-628, 2020.

BEECHAM, R. Towards smart farming: agriculture embracing the IoT vision. Beecham Research, v. 3, p. 1-6, 2014.

BELHADI, A.; KAMBLE, S. S.; MANI, V.; BENKHATI, I.; TOURIKI, F. E. An ensemble machine learning approach for forecasting credit risk of agricultural SMEs’ investments in agriculture 4.0 through supply chain finance. Annals of Operations Research, p. 1-29, 2021.

BIGLIARDI, B.; BOTTANI, E.; CASELLA, G.; FILIPPELLI, S.; PETRONI, A.; PINI, B.; GIANATTI, E. Industry 4.0 in the agrifood supply chain: a review. Procedia Computer Science, v. 217, p. 1755-1764, 2023.

BRAUN, C. L.; BITSCH, V.; HÄRING, A. M. Developing agri-food value chains: learning networks between exploration and exploitation. The Journal of Agricultural Education and Extension, v. 29, n. 4, p. 417-438, 2023.

CAO, G.; DUAN, Y.; CADDEN, T. The link between information processing capability and competitive advantage mediated through decision-making effectiveness. International Journal of Information Management, v. 44, p.121-131, 2019.

CHESBROUGH, H. To recover faster from Covid-19, open up: managerial implications from an open innovation perspective. Industrial Marketing Management, v. 88, p. 410-413, 2020.

CORALLO, A.; DE GIOVANNI, M.; LATINO, M. E.; MENEGOLI, M. Leveraging on technology and sustainability to innovate the supply chain: a proposal of agri-food value chain model. Supply Chain Management. An International Journal, v. 29, n. 3, p. 661-683, 2024.

DASGUPTA, S.; ROBINSON, E. J. Attributing changes in food insecurity to a changing climate. Scientific Reports, v. 12, n. 1, 4709, 2022.

DEVAUX, A.; VELASCO, C.; ORDINOLA, M.; HORTON, D. Collective action for market chain innovation in the Andes: scaling up and diffusion of the “innovation with potato” experience. Agricultural Systems, v. 165, p. 74-81, 2018.

DI VAIO, A.; PALLADINO, R.; HASSAN, R.; ESCOBAR, O. Artificial intelligence and business models in the sustainable development goals perspective: a systematic literature review. Journal of Business Research, v. 121, p. 283-314, 2020.

DONOVAN, J.; POOLE, N. Changing asset endowments and smallholder participation in higher value markets: evidence from certified coffee producers in Nicaragua. Food Policy, v. 44, p. 1-13, 2014.

DORA, M.; WESANA, J.; GELLYNCK, X.; SETH, N.; DEY, B.; DE STEUR, H. Importance of sustainable operations in food loss: evidence from the Belgian food processing industry. Annals of operations research, v. 290, 47-72, 2020.

DUBEY, R.; GUNASEKARAN, A.; CHILDE, S. J.; PAPADOPOULOS, T.; LUO, Z.; WAMBA, S. F.; ROUBAUD, D. Can big data and predictive analytics improve social and environmental sustainability? Technological forecasting and social change, v. 144, p. 534-545, 2019.

EGWUCHE, O. S.; SINGH, A.; EZUGWU, A. E.; GREEFF, J.; OLUSANYA, M. O.; ABUALIGAH, L. Machine learning for coverage optimization in wireless sensor networks: a comprehensive review. Annals of Operations Research, p.1-67, 2023.

ELKINGTON, J. The triple bottom line. Environmental management: readings and cases, v. 2, p. 49-66, 1997.

ELUFIOYE, O. A.; IKE, C. U.; ODEYEMI, O.; USMAN, F. O.; MHLONGO, N. Z. Ai-Driven predictive analytics in agricultural supply chains: a review: assessing the benefits and challenges of ai in forecasting demand and optimizing supply in agriculture. Computer Science & IT Research Journal, v. 5, n. 2, p. 473-497, 2024.

FATORACHIAN, H.; KAZEMI, H. Impact of Industry 4.0 on supply chain performance. Production Planning & Control, v. 32, n. 1, p. 63-81, 2021.

FILDES, R.; GOODWIN, P.; LAWRENCE, M.; NIKOLOPOULOS, K. Effective forecasting and judgmental adjustments: an empirical evaluation and strategies for improvement in supply-chain planning. International Journal of Forecasting, v. 25, n. 1, p. 3-23, 2009.

FOERSTL, K.; MEINLSCHMIDT, J.; BUSSE, C. It's a match! Choosing information processing mechanisms to address sustainability-related uncertainty in sustainable supply management. Journal of Purchasing and Supply Management, v. 24, n. 3, p. 204-217, 2018.

FOOD AND AGRICULTURE ORGANIZATION. (Ed.). State of World Fisheries and Aquaculture: 2014. Food & Agriculture Organization of the UN (FAO).

FREDERICO, G. F.; GARZA-REYES, J. A.; ANOSIKE, A.; KUMAR, V. Supply Chain 4.0: concepts, maturity and research agenda. Supply Chain Management. An International Journal, v. 25, n. 2, p. 262-282, 2019.

GAITÁN-CREMASCHI, D.; KLERKX, L.; DUNCAN, J.; TRIENEKENS, J. H.; HUENCHULEO, C.; DOGLIOTTI, S.; ROSSING, W. A. Characterizing Diversity of Food Systems In view of sustainability transitions. A review. Agronomy for sustainable development, v. 39, p. 1-22, 2019.

GALBRAITH, J. R. Organization design: an information processing view. Interfaces, v. 4, n. 3, p. 28-36, 1974.

GAUDENZI, B.; PELLEGRINO, R.; CONFENTE, I. Achieving supply chain resilience in an era of disruptions: a configuration approach of capacities and strategies. Supply Chain Management. An International Journal, v. 28, n. 7, p. 97-111, 2023.

GAWANDE, V.; SAIKANTH, D. R. K.; SUMITHRA, B. S.; ARAVIND, S. A.; SWAMY, G. N.; CHOWDHURY, M.; SINGH, B. V. Potential of precision farming technologies for eco-friendly agriculture. International Journal of Plant & Soil Science, v. 35, n. 19, p. 101-112, 2023.

GU, B.; FU, Y.; YE, J. Joint optimization and coordination of fresh-product supply chains with quality-improvement effort and fresh-keeping effort. Quality Technology & Quantitative Management, v. 18, n. 1, p. 20-38, 2021.

GUPTA, S.; RIKHTEHGAR BERENJI, H.; SHUKLA, M.; MURTHY, N. N. Opportunities in farming research from an operations management perspective. Production and Operations Management, v. 32, n. 6, p. 1577-1596, 2023.

HAIR, J. F.; HULT, G. T. M.; RINGLE, C.; SARSTEDT, M. A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Sage Publications. 2019.

HAMANN, S. The global food system, agro-industrialization and governance: alternative conceptions for sub-Saharan Africa. Globalizations, v. 17, n. 8, p. 1405-1420, 2020.

HARSONO, I.; FADLIYANTI, L.; MULAWIANI, B. S. W.; USMAN, A.; ABUBAKAR, A. Analysis of Plant Productivity, Farmer Income and Availability of Supporting Infrastructure on Soybean Agribusiness Institutional Performance in East Java. West Science Agro, v. 2, n. 01, p. 35-43, 2024.

HUANG, Y. C.; BORAZON, E. Q.; LIU, J. M. Antecedents and consequences of green supply chain management in Taiwan's electric and electronic industry. Journal of Manufacturing Technology Management, v. 32, n. 5, p. 1066-1093, 2021.

JAVAID, M.; HALEEM, A.; KHAN, I. H.; SUMAN, R. Understanding the potential applications of Artificial Intelligence in Agriculture Sector. Advanced Agrochem, v. 2, n. 1, p. 15-30, 2023.

JOSHI, S.; SINGH, R. K.; SHARMA, M. Sustainable agri-food supply chain practices: few empirical evidences from a developing economy. Global Business Review, v. 24, n. 3, p. 451-474, 2023.

KARUNATHILAKE, E. M. B. M.; LE, A. T.; HEO, S.; CHUNG, Y. S.; MANSOOR, S. The path to smart farming: innovations and opportunities in precision agriculture. Agriculture, v. 13, n. 8, p. 1-26, 2023.

KAZANCOGLU, Y.; LAFCI, C.; KUMAR, A.; LUTHRA, S.; GARZA‐REYES, J. A.; BERBEROGLU, Y. The role of agri‐food 4.0 in climate‐smart farming for controlling climate change‐related risks: a business perspective analysis. Business Strategy and the Environment, v. 33, n. 4, p. 2788-2802, 2024.

KAZANCOGLU, Y.; SEZER, M. D.; OZBILTEKIN-PALA, M.; LAFÇI, Ç.; SARMA, P. R. S. Evaluating resilience in food supply chains during Covid-19. International Journal of Logistics Research and Applications, v. 27, n. 5, p. 688-704, 2024.

KIM, A.; KIM, H.; LEE, H.; LEE, B.; LIM, H. Comparative economic optimization for an overseas hydrogen supply chain using mixed-integer linear programming. ACS Sustainable Chemistry & Engineering, v. 9, n. 42, p. 14249-14262, 2021.

KLINE, R. B. Principles and practice of structural equation modeling. 4th ed. Guilford Press. 2015.

LE, T. T. How do food supply chain performance measures contribute to sustainable corporate performance during disruptions from the Covid-19 pandemic emergency? International Journal of Quality & Reliability Management, v. 40, n. 5, p. 1233-1258, 2023.

LECOUTERE, E.; ACHANDI, E. L.; AMPAIRE, E. L.; FISCHER, G.; GUMUCIO, T.; NAJJAR, D.; SINGARAJU, N. Fostering an enabling environment for equality and empowerment in agri-food systems: an assessment at multiple scales. Global Food Security, v. 40, p. 100735, 2024.

LEE, S.; JIANG, X.; MANUBOLU, M.; RIEDL, K.; LUDSIN, S. A.; MARTIN, J. F.; LEE, J. Fresh produce and their soils accumulate cyanotoxins from irrigation water: implications for public health and food security. Food Research International, v. 102, p. 234-245, 2017.

LI, X.; KRIVTSOV, V.; PAN, C.; NASSEHI, A.; GAO, R. X.; IVANOV, D. End-to-end supply chain resilience management using deep learning, survival analysis, and explainable artificial intelligence. International Journal of Production Research, v. 63, n. 3, p. 1174-1202, 2025.

LI, Y.; CHEN, K.; COLLIGNON, S.; IVANOV, D. Ripple effect in the supply chain network: forward and backward disruption propagation, network health and firm vulnerability. European Journal of Operational Research, v. 291, n. 3, p. 1117-1131, 2021.

LIU, P.; LONG, Y.; SONG, H. C.; HE, Y. D. Investment decision and coordination of green agri-food supply chain considering information service based on blockchain and big data. Journal of Cleaner Production, v. 277, p.123646, 2020.

MAHROOF, K.; DAMANPOUR, F.; ZMUD, R. W. The evolving nature of supply chain risk management. Journal of Business Logistics, v. 42, n. 3, p. 208-228, 2021. Available at: https://doi.org/10.1111/jbl.12289

MARAVEAS, C.; KARAVAS, C. S.; LOUKATOS, D.; BARTZANAS, T.; ARVANITIS, K. G.; SYMEONAKI, E. Agricultural greenhouses: resource management technologies and perspectives for zero greenhouse gas emissions. Agriculture, v. 13, n. 7, p. 1464, 2023.

MEHTA, N. Technical efficiency and reduction in input costs in agriculture: case of genetically modified cotton. Agricultural Economics Research Review, v. 32, n. 1, p. 105-116, 2019.

MEIER, M.; PINTO, E. Covid-19 supply chain disruptions. Covid Economics, v. 48, n. 1, p. 139-170, 2020.

MOHAN, D.; KHAN, H.; KUMAR, V.; KUMAR, R.; VERMA, A.; SINGH, R.; SINGH, G. Significance of yield sustainability to develop climate smart wheat (Triticum aestivum) in India. The Indian Journal of Agricultural Sciences, v. 93, n. 9, p. 954-959, 2023.

MSOMI, L.; ZENDA, M. An Analysis of Challenges Facing Smallholder Crop Farmers and Informal Food Traders in the Agri-Food Value Chain in Gauteng Province, South Africa. South African Journal of Agricultural Extension, v. 52, n. 2, p. 120-144, 2024.

MULLA, D. J. Twenty five years of remote sensing in precision agriculture: key advances and remaining knowledge gaps. Biosystems engineering, v. 114, n. 4, p. 358-371, 2013.

NOTARNICOLA, B.; SALA, S.; ANTON, A.; MCLAREN, S. J.; SAOUTER, E.; SONESSON, U. The role of life cycle assessment in supporting sustainable agri-food systems: a review of the challenges. Journal of cleaner production, v. 140, p. 399-409, 2017.

OLAN, F.; SPANAKI, K.; AHMED, W.; ZHAO, G. Enabling explainable artificial intelligence capabilities in supply chain decision support making. Production Planning & Control, p. 1-12, 2024.

OPOKU, E. K.; WANG, M. J. S.; GUEVARRA, S.; BAZYLEWICH, M.; THAM, A. Envisioning digitalised value chains inthe aftermath of Covid-19: a case study of Philippine coffee. Journal of Agribusiness in Developing and Emerging Economies, v. 13, n. 5, p. 797-811, 2023.

PANDEY, P. C.; TRIPATHI, A. K.; SHARMA, J. K. An evaluation of GPS opportunity in market for precision agriculture. In GPS and GNSS Technology in Geosciences, p. 337-349, 2021. Elsevier. 2021.

PETTIT, T. J.; FIKSEL, J.; CROXTON, K. L. Ensuring supply chain resilience: development of a conceptual framework. Journal of business logistics, v. 31, n. 1, p. 1-21, 2010.

RAJI, E.; IJOMAH, T. I.; EYIEYIEN, O. G. Integrating technology, market strategies, and strategic management in agricultural economics for enhanced productivity. International Journal of Management & Entrepreneurship Research, v. 6, n. 7, p. 2112-2124, 2024.

RANE, N.; CHOUDHARY, S.; RANE, J. Artificial intelligence for enhancing resilience. Journal of Applied Artificial Intelligence, v. 5, n. 2, p. 1-33, 2024.

REARDON, T.; MISHRA, A.; NUTHALAPATI, C. S.; BELLEMARE, M. F.; ZILBERMAN, D. Covid-19’s disruption of India’s transformed food supply chains. Economic and Political Weekly, v. 55, n. 18, p. 18-22, 2020.

REJEB, A.; REJEB, K.; ZAILANI, S. Big data for sustainable agri‐food supply chains: a review and future research perspectives. Journal of Data, Information and Management, v. 3, p. 167-182, 2021.

RUBBIO, I.; BRUCCOLERI, M.; PIETROSI, A.; RAGONESE, B. Digital health technology enhances resilient behaviour: evidence from the ward. International Journal of Operations & Production Management, v. 40, n. 1, p. 34-67,2020.

SAITONE, T. L.; SEXTON, R. J. Agri-food supply chain: evolution and performance with conflicting consumer and societal demands. European Review of Agricultural Economics, v. 44, n. 4, p. 634-657, 2017.

SANNOU, R. O.; KIRSCHKE, S.; GÜNTHER, E. Integrating the social perspective into the sustainability assessment of agri-food systems: a review of indicators. Sustainable Production and Consumption, v. 39, p. 175-190, 2023.

SARABIA, N.; PERIS, J.; SEGURA, S. Transition to agri-food sustainability, assessing accelerators and triggers for transformation: case study in Valencia, Spain. Journal of Cleaner Production, v. 325, p. 129228, 2021.

SARKER, I. H. AI-driven cybersecurity and threat intelligence: cyber automation, intelligent decision-making and explainability. Springer Nature. 2024.

SERAZETDINOVA, L.; GARRATT, J.; BAYLIS, A.; STERGIADIS, S.; COLLISON, M.; DAVIS, S. How should we turn data into decisions in AgriFood? Journal of the Science of Food and Agriculture, v. 99, n. 7, p. 3213-3219, 2019.

SHEKARIAN, M.; FARAHANI, R. Z.; KARIMI, H. A review of the applications of supply chain resilience: learnings from the Covid-19 pandemic. Computers & Industrial Engineering, v. 150, p. 106889, 2020.

TOORAJIPOUR, R.; SOHRABPOUR, V.; NAZARPOUR, A.; OGHAZI, P.; FISCHL, M. Artificial intelligence in supply chain management: a systematic literature review. Journal of Business Research, v. 122, p. 502-517, 2021.

TRAN-DANG, H.; KROMMENACKER, N.; CHARPENTIER, P.; KIM, D. S. Toward the internet of things for physical internet: perspectives and challenges. IEEE internet of things Journal, v. 7, n. 6, p. 4711-4736, 2020.

TRIENEKENS, J. H. Agricultural value chains in developing countries a framework for analysis. International food and agribusiness management review, v. 14, n. 2, p. 51-82, 2011.

TRIENEKENS, J.; ZUURBIER, P. Quality and safety standards in the food industry, developments and challenges. International Journal of Production Economics, v. 113, n. 1, p. 107-122, 2008.

VASANTHRAJ, A.; POTDAR, V.; AGRAWAL, H. Industry 4.0 adoption in food supply chain to improve visibility and operational efficiency—a content analysis. IEEE Access, v. 11, p. 73922-73958, 2023.

WINANS, K. S.; MACADAM-SOMER, I.; KENDALL, A.; GEYER, R.; MARVINNEY, E. Life cycle assessment of California unsweetened almond milk. The International Journal of Life Cycle Assessment, v. 25, p. 577-587, 2020.

WONG, L. W.; TAN, G. W. H.; LEE, V. H.; OOI, K. B.; SOHAL, A. Unearthing the determinants of Blockchain adoption in supply chain management. International Journal of Production Research, v. 58, n. 7, p. 2100-2123, 2020.

WOOD, A.; QUEIROZ, C.; DEUTSCH, L.; GONZÁLEZ-MON, B.; JONELL, M.; PEREIRA, L.; WASSÉNIUS, E. Reframing the local–global food systems debate through a resilience lens. Nature Food, v. 4, n. 1, p. 22-29, 2023.

YU, Y.; HUANG, G.; GUO, X. Financing strategy analysis for a multi-sided platform with blockchain technology. International journal of production research, v. 59, n. 15, p. 4513-4532, 2021.

YUAN, Y.; LI, W. The effects of supply chain risk information processing capability and supply chain finance on supply chain resilience: a moderated and mediated model. Journal of Enterprise Information Management, v. 35, n. 6, p. 1592-1612, 2022.

ZUREK, M.; INGRAM, J.; SANDERSON BELLAMY, A.; GOOLD, C.; LYON, C.; ALEXANDER, P.; WITHERS, P. J. Food system resilience: concepts, issues, and challenges. Annual Review of Environment and Resources, v. 47, n. 1, p.511-534, 2022.

Downloads

Publicado

2025-04-30

Como Citar

Pooe, D., & Munyanyi, W. (2025). Digitalização e convergência da sustentabilidade: aplicação da inteligência artificial para melhorar a sustentabilidade das cadeias de valor agroalimentares na África. Sustainability in Debate, 16(1), 285–303. https://doi.org/10.18472/SustDeb.v16n1.2025.55859

Edição

Seção

Artigos - Varia

Artigos Semelhantes

1 2 3 > >> 

Você também pode iniciar uma pesquisa avançada por similaridade para este artigo.