Indian Journal of Agricultural Research
SCOPUSWeb of Science
  • Year: 2026
  • Volume: 60
  • Issue: 3

A Multisectoral Systems Analysis of Digital Engagement and Agricultural Productivity in Sub-Saharan Africa

  • Author:
  • Tiavina Andriamahenina Nasolomampionona12, Qin Zhaohui1*, Andrianarimanana Mihasina Harinaivo3, Manana Gaddis Elia1, Mazheti Winnie Kudzai1, Dhornor Tarir Duok Gai1, Randrianasolo Laza-Aina Ambinintsoa4
  • Total Page Count: 10
  • Page Number: 450 to 459

1College of Economics and Management, China Three Gorges University, Yichang, 443002, China.

2Doctoral School GOUVSOMU Fianarantsoa, University of Fianarantsoa, 301, Madagascar.

3Department of Agri-Food Economics and Consumer Sciences, Laval University, Paul Comtois Bldg, Quebec City, QC G1V 0A6, Canada.

4School of Economics and Management, Harbin University of Science and Technology, Harbin, China.

*Corresponding Author: Qin Zhaohui, College of Economics and Management, China Three Gorges University, Yichang, 443002, China. Email: qinzhaohui@ctgu.edu.cn

Abstract

Intersectoral synergies between technology, environment and farming are vital for sustainable agricultural development. This requires innovative solutions to overcome low productivity and environmental stress; digital technologies offer potential to transform smallholder agricultural systems.

This study evaluates the sustainability impacts of digital engagement (DE) in Sub-Saharan African agriculture through a systems-based assessment framework. Using Partial Least Squares-Structural Equation Modeling (PLS-SEM) on World Bank datasets (2000-2023), this research quantifies DE’s effects on agricultural productivity while accounting for critical moderators: environmental stress, feasibility assessment (FA), technical skills (TS) and livestock farming (LF).

Results reveal significant positive interactions, with coefficients of 1.690 for natural environment (NE), 2.387 for FA, 3.901 for TS and 77.202 for LF, demonstrating the moderating role of environmental performance between DE and agricultural productivity. The findings contribute to impact evaluation methodologies by demonstrating how PLS-SEM can assess complex technology- environment interactions, while providing actionable criteria for appraising digital agriculture projects in resource-constrained settings. However, challenges such as inadequate infrastructure and limited farmer technical skills must be addressed. By bridging digital innovation with environmental stewardship, this research offers actionable insights for policymakers to advance sustainable agricultural practices in resource-constrained settings.

Keywords

Agricultural productivity, Digital engagement, Environmental sustainability, Partial least squares-structural equation modeling