Application of structural equation modelling to develop a conceptual model for smallholder's credit access: The mediation of agility and innovativeness in organic food value chain finance

PLoS One. 2020 Aug 4;15(8):e0235921. doi: 10.1371/journal.pone.0235921. eCollection 2020.

Abstract

Developing a conceptual model is vital for small-scale organic farmer's credit access to sustain the livelihoods. However, smallholders continually face severe problems in getting finance that lead to reduce investment and in turn, challenges the livelihoods. Therefore, the aim of the present study was to establish and empirically test a theoretical model to explore how agility and innovativeness in organic food value chain finance are achieved through ITI, TRST, CG, ICT, and IS, and how these, in turn, can accelerate financial flow in the value chain and enhance competitiveness. The present study used a survey method and collected data from small-scale farmers, traders, and financial institutions. The model and hypothesis are tested using data obtained from 331 respondents through partial least square structure equation modeling techniques. We argue that development of theoretical model show potential to increase creditworthiness of smallholders and overcome uncertainties that impede traditional value chain credit arrangement. Thus, the present study could provide new ways to integrate the value chain partners, through information and communication technology and governance arrangements in the organic food value chain financing. This study demonstrates that the mediations of innovativeness and agility significantly affect the development of new financial products to make agile the financial flow, which in turn positively influences value chain competitiveness. Significant judgments are required for trustworthy relations among the value chain partners to positively harness innovative product development for swifter value chain finance. Therefore, this theoretical model should not be regarded as a quick solution, but a process of testing, error, and learning by doing so.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Farmers
  • Food, Organic / economics*
  • Humans
  • Least-Squares Analysis
  • Multivariate Analysis
  • Organic Agriculture / economics*
  • Pakistan

Grants and funding

This work was supported by Chinese Scholarship Council and Northeast Forestry University, Harbin, Heilongjiang, China. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.