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Communication, principal–agent alignment and performance: Evidence from Brazilian agricultural co‐operatives

Celina Martinez Georges et al.

Annals of Public and Cooperative Economics2025https://doi.org/10.1111/apce.12506article
AJG 2ABDC B
Weight
0.44

Abstract

In response to increasing demands for decision‐making expertise in the global business environment, agricultural co‐operatives face the challenge of balancing governance adaptations with the risk of agency costs. While various mechanisms exist to align the interests of principals and agents within these organizations, communication – particularly digital – appears to hold the greatest potential. However, empirical evidence on its effectiveness remains limited. This study addresses this gap by examining the relation between both digital and non‐digital communication on principal–agent alignment and overall performance in agricultural co‐operatives. The empirical basis consists of a survey conducted in 2023 with 41 agricultural co‐operatives in Brazil. The results of a structural equation model show that (1) digital communication is related positively to principal–agent alignment, (2) non‐digital communication is not related significantly to principal–agent alignment and (3) principal–agent alignment is related positively to performance. These findings offer important insights for the governance of agricultural co‐operatives, which are further explored in the conclusion.

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https://doi.org/https://doi.org/10.1111/apce.12506

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@article{celina2025,
  title        = {{Communication, principal–agent alignment and performance: Evidence from Brazilian agricultural co‐operatives}},
  author       = {Celina Martinez Georges et al.},
  journal      = {Annals of Public and Cooperative Economics},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1111/apce.12506},
}

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Evidence weight

0.44

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.32 × 0.4 = 0.13
M · momentum0.57 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.