Article: From service failures to customer acceptance: the role of managerial response and adaptive innovation in AI-enabled service systems Journal: International Journal of Business Innovation and Research (IJBIR) 2026 Vol.41 No.7 pp.1 - 28 Abstract: This study examines how service failures in AI-enabled hospitality systems relate to customer acceptance, managerial response, organisational adaptation, and workforce pressures. Using a multi-method design combining customer survey data (N = 308), organisational survey data (N = 65), and semi-structured interviews (N = 19), the study distinguishes customer-level acceptance mechanisms from organisational response and adaptation processes. Customer-level analysis shows that trust and perceived service performance are positively associated with acceptance, while fear is negatively associated with acceptance. Organisational and qualitative evidence indicates that service disruptions require situational interpretation, human intervention, operational adjustment, and continued learning. Workforce pressure emerges as an important contextual condition associated with service instability and response capacity. Integrating these complementary sources of evidence, the study advances a process-oriented understanding of AI-enabled service transformation and highlights the importance of aligning technological performance, managerial action, workforce capacity, and customer evaluation. Inderscience Publishers - linking academia, business and industry through research

Title: From service failures to customer acceptance: the role of managerial response and adaptive innovation in AI-enabled service systems

Authors: Marko Petrovic

Addresses: Satbayev University, 22a Satpaev Street, 050013 Almaty, Republic of Kazakhstan

Abstract: This study examines how service failures in AI-enabled hospitality systems relate to customer acceptance, managerial response, organisational adaptation, and workforce pressures. Using a multi-method design combining customer survey data (N = 308), organisational survey data (N = 65), and semi-structured interviews (N = 19), the study distinguishes customer-level acceptance mechanisms from organisational response and adaptation processes. Customer-level analysis shows that trust and perceived service performance are positively associated with acceptance, while fear is negatively associated with acceptance. Organisational and qualitative evidence indicates that service disruptions require situational interpretation, human intervention, operational adjustment, and continued learning. Workforce pressure emerges as an important contextual condition associated with service instability and response capacity. Integrating these complementary sources of evidence, the study advances a process-oriented understanding of AI-enabled service transformation and highlights the importance of aligning technological performance, managerial action, workforce capacity, and customer evaluation.

Keywords: digital transformation; service innovation; adaptive innovation; workforce pressure; customer acceptance; AI-enabled services.

DOI: 10.1504/IJBIR.2026.157380

International Journal of Business Innovation and Research, 2026 Vol.41 No.7, pp.1 - 28

Received: 22 Apr 2026
Accepted: 11 Sep 2026
Published online: 30 Oct 2026 *

Title: From service failures to customer acceptance: the role of managerial response and adaptive innovation in AI-enabled service systems

Keep up-to-date