Adoption of Cloud Computing Technologies in Hospitality Enterprises and Their Impact on Business Performance: The Case of Türkiye

Abstract

Background: Cloud computing (CC) has emerged as a transformative technology that offers flexibility, scalability, and cost efficiency to enterprises across various sectors, including tourism and hospitality. Despite its potential, the level and determinants of cloud computing adoption (CCA) in the hospitality industry, particularly in developing countries, remain insufficiently explored.

Purpose: This study aims to identify the key factors that facilitate or hinder the adoption process of cloud computing in accommodation businesses operating in Türkiye and to analyse the impact of this technology on business performance.

Study design/methodology/approach: A theoretical model was developed by integrating the Diffusion of Innovation (DOI) theory and the Technology-Organization-Environment (TOE) framework. Within this model, 11 constructs were formulated, their reliability and validity were tested and regression analyses were conducted to examine the relationships between CCA determinants and business performance outcomes.

Findings/conclusions: The results show that compatibility has a strong positive effect on the adoption of CC in hospitality enterprises, while complexity and security and privacy concerns negatively affect adoption. External support and technological readiness were also found to be significant positive predictors. Conversely, relative advantage, top management support, organizational resources and competitive pressure did not have significant effects. Importantly, the study reveals a positive and significant relationship between CCA and business performance, highlighting the strategic potential of this technology for hospitality enterprises.

Limitations/future research: The study is limited to hospitality enterprises in Türkiye and future research could extend the analysis to other countries or service sectors. Further studies employing longitudinal or mixed-method approaches may also deepen understanding of the long-term effects of CCA.