RESILIENCE AND DIGITAL TRACEABILITY IN INFORMAL AGRICULTURAL SUPPLY CHAINS IN KENYA: LEVERAGING MOBILE TECHNOLOGIES POST-COVID-19

Robert Kipng’etich Lagat

Abstract


The performance of informal agricultural supply chains in Kenya remains a critical concern for food security, rural livelihoods, and market access, particularly in the wake of disruptions such as the COVID-19 pandemic. This study examined the influence of mobile-based digital traceability and supply chain resilience capabilities on the performance of informal agricultural supply chains in selected counties in Kenya. Guided by the Resource-Based View (RBV) and Technology Acceptance Model (TAM), the study adopted a cross-sectional explanatory research design and collected data from 317 respondents across Kisii, Meru, Nakuru, and Machakos counties. Structured questionnaires were used to capture perceptions related to traceability, resilience, and performance outcomes. Descriptive results revealed that respondents generally perceived mobile-based digital tools as useful for improving product verification and market information access, though satisfaction with existing platforms remained moderate. Similarly, actors demonstrated varying levels of resilience, particularly in their reliance on informal networks, flexible sourcing, and logistical adaptability. Pearson correlation analysis indicated positive and statistically significant relationships between all variables, with the strongest correlation observed between digital traceability and performance (r = 0.617, p < 0.01). Multiple regression analysis confirmed that both mobile-based digital traceability (β = 0.444, p < 0.001) and resilience capabilities (β = 0.369, p < 0.001) significantly influenced supply chain performance, with the model explaining 47.0% of the variation in performance outcomes (R² = 0.470). The findings underscore the dual importance of technological innovation and resilience strategies in enhancing the effectiveness, adaptability, and competitiveness of Kenya’s informal agricultural supply systems. The study recommends scaling user-friendly traceability platforms, strengthening resilience through decentralized storage and transport networks, and promoting inclusive policy support for informal actors. These results provide actionable insights for policymakers, development partners, and agri-tech innovators aiming to modernize and stabilize informal food systems in Kenya and similar contexts.

 

Keywords: mobile-based digital traceability, supply chain resilience, informal agricultural markets, performance, Kenya

 


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References


Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120.

Chanda, C. T., Mpolomoka, D. L., & Muvombo, M. (2020). Understanding COVID-19 variants and coping strategies in Zambian communities: A systematic review. Journal of Health Research. https://www.researchgate.net/publication/384691359

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.

Sokame, B. M., Wamalwa, M., & Tonnang, H. E. Z. (2023). System dynamics modeling for assessing the impact of COVID-19 on food supply chains: A case study of Kenya and Rwanda. Sustainability, 15(6), 4717.

Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). Sage.

Gebremichael, H. S., Gebreslassie, M. G., & Mezgebe, T. T. (2023). Contextualizing entrepreneurship for Africa’s post-COVID-19 recovery and growth. Scientific African, Elsevier.

Ishengoma, F. (2020). The potential of blockchain technology in addressing the challenges posed by the COVID-19 pandemic in African developing countries. Israa University Journal of Applied Sciences. https://www.researchgate.net/publication/378333848

Klibi, W., Shawa, L. B., & Mkansi, M. (2022). Supply chains in Africa: Current status and emerging trends. Supply Chain Forum: An International Journal, 26(1), 10–24.

Mensah, P., Pimenta, A. S., de Melo, R. R., & Amponsah, J. (2022). The global supply chain of wood products: A literature review. Forests, 16(7), 1036. https://www.mdpi.com/1999-4907/16/7/1036

Ngongolo, K., & Gayo, L. (2020). Synergistic impact of COVID-19 and climate change on agricultural resilience and food security in Sub-Saharan Africa. Discover Agriculture. https://link.springer.com/content/pdf/10.1007/s44279-024-00056-9.pdf

Saunders, M., Lewis, P., & Thornhill, A. (2019). Research methods for business students (8th ed.). Pearson Education.

Sokame, B. M., Wamalwa, M., & Tonnang, H. E. Z. (2023). System dynamics modeling for assessing the impact of COVID-19 on food supply chains: A case study of Kenya and Rwanda. Sustainability, 15(6), 4717.

Sokame, B. M., Wamalwa, M., & Tonnang, H. E. Z. (2023). System dynamics modeling for assessing the impact of COVID-19 on food supply chains: A case study of Kenya and Rwanda. Sustainability, 15(6), 4717.

Thorpe, J., Odame, H., & Kangai, E. (2023). Horticulture in Kenya: Lessons from the COVID-19 Pandemic. Institute of Development Studies.

Yamane, T. (1967). Statistics: An Introductory Analysis (2nd ed.). Harper & Row.


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