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Delivering Smarter: How Artificial Intelligence Transforms Organizational Performance and Service Quality in a Public Postal Operator

Domain:

digital infrastructure

Record type:

paper
Creator:
ChiImeRym
Publisher:
AL-
Host:
In the era of digital transformation, artificial intelligence (AI) is emerging as a strategic lever for modernizing public postal operators, which have historically struggled with counter congestion and rising service-quality expectations. This research investigates the extent to which AI integration can improve organizational performance and service quality within the Tunisian Post. A qualitative triangulation strategy was used, combining fifteen semi-structured interviews with managers and staff and a netnographic study of 25 Google Maps reviews collected between May 2025 and April 2026. Convergent findings reveal recurring and clearly identified irritants on the users' side, spontaneously expressed in online reviews, concentrated on waiting times, parcel-tracking reliability and shipment security. Qualitative interviews confirm an overall positive perception of AI's potential contribution to the operational and economic dimensions of performance, but a more modest perception of its strategic dimension. The netnographic study corroborates these findings, revealing recurring irritants linked to service slowness, technical outages and opening hours. Based on these results, operational recommendations are proposed, including a smart queue-management system, predictive parcel tracking and a Tunisian-dialect conversational agent. Theoretically, the study argues that organizational readiness and public legitimacy for AI adoption operate as interacting, rather independent, conditions, and that internal optimism about AI's operational benefits does not by itself secure the external trust on which its acceptability depends. The article discusses the theoretical and managerial implications of these findings, positions the contribution within the literature on AI adoption in public and postal services, and identifies the study's methodological limitations along with avenues for future research.

Visit

doi.org

Licenses

https://creativecommons.org/licenses/by-nc/4.0

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