Navigating the Evolution of Trust in Service Businesses

: From Human Interactions to AI Mediation and Cyber Risk

Abstract

This thesis examines the evolution of trust, authenticity, privacy, and autonomy across human, AI-mediated, and cyber-risk contexts in business relationships. A Three-Stage Trust Evolution Model is proposed to capture this progression. Interactions move from human-centred engagement in traditional hospitality services to AI-driven personalization in global banking, and finally to cyber-risk governance within SMEs confronting emerging technological threats. Paper 1 investigates human-centred service encounters in hospitality, demonstrating how locally sourced and culturally embedded offerings strengthen perceived authenticity and trust. Paper 2 analyses AI-mediated personalization in global B2B banking, revealing how trust, transparency, and perceived autonomy shape SME responses, and introduces the Sovereign Reliance Privacy Framework (SRPF) to guide ethical, data-driven decision-making. Paper 3 addresses organizational exposure to AI-enabled cyber threats by developing the Business Privacy Calculus Model to explain how SMEs balance operational efficiency, ethical responsibility, and stakeholder trust amid deepfake and synthetic risk challenges.
The Three-Stage Trust Evolution Model unifies these insights: Stage 1—Embodied Trust rooted in physical interactions and cultural authenticity; Stage 2—Algorithmic Trust shaped by data-driven personalization and autonomy–privacy balance; and Stage 3—Resilient Trust sustained through governance strategies that counter cyber manipulation and identity-based threats. Collectively, the thesis advances construal level theory, privacy calculus theory, social contract theory, and psychological reactance theory across diverse industry settings. Managerially, the model offers a practical roadmap for integrating human-centred practices, transparent and ethical AI systems, and proactive cyber governance to maintain trustworthy and authentic relationships in increasingly complex business environments.

Date of Award	20 May 2026
Original language	English
Awarding Institution	University of Portsmouth
Supervisor	Shynar Dyussembayeva (Supervisor), Gajendra Liyanaarachchi (Supervisor) & Giampaolo Viglia (Supervisor)