The Impact of Artificial Intelligence Acceptance on Customer Satisfaction in the Telecommunication Industry in Egypt | ||
| المجلة العلمية للإقتصاد و التجارة | ||
| Volume 54, Issue 4, December 2024, Pages 13-52 PDF (472.69 K) | ||
| Document Type: المقالة الأصلية | ||
| DOI: 10.21608/jsec.2024.395919 | ||
| Author | ||
| Mohamed Mahmoud Hanafy Mohamed Salim | ||
| جامعة | ||
| Abstract | ||
| This study explores the relationship between Artificial Intelligence (AI) acceptance and customer satisfaction in Egypt's telecommunications sector, utilizing the Technology Acceptance Model (TAM) as the theoretical framework. The purpose is to investigate how perceived usefulness (PU) and perceived ease of use (PEOU) influence AI acceptance and to understand the mediating role of trust in AI. Additionally, demographic factors such as age, income, and education are examined as potential moderators in this relationship. A quantitative research methodology was employed, collecting data from 442 telecom service customers across Egypt through structured questionnaires. These questionnaires focused on customer perceptions of AI-powered services, including AI-driven customer support, predictive services, and network management. The data were analyzed using multiple regression analysis to assess the impact of PU and PEOU, mediation analysis to explore the role of trust, and moderation analysis to evaluate the effects of demographic factors. The key findings reveal that both PU and PEOU are significant predictors of AI acceptance. Customers are more likely to adopt AI technologies when they perceive them as enhancing their telecom experience through faster customer service, better network reliability, and personalized offerings. Trust in AI emerged as a critical mediating factor; customers who trust the accuracy, reliability, and security of AI systems report higher satisfaction levels. A lack of trust can deter customers from embracing AI technologies, negatively impacting their overall satisfaction. Age was found to be a significant moderating factor, with younger customers (aged 18-35) showing higher levels of AI acceptance, while older customers (aged 50 and above) expressed more reservations. Income level did not significantly influence AI acceptance or satisfaction, and education level had a minor effect. The study suggests that telecom service providers should highlight the functional benefits of AI technologies and invest in developing user-friendly AI systems to foster adoption. Building trust through transparent data handling practices and ensuring the security of AI-driven services is essential. Tailoring AI deployment strategies to cater to different demographic groups—offering advanced features to younger, tech-savvy customers and providing personalized support to older customers—can enhance overall customer satisfaction. This research contributes to the understanding of AI acceptance in emerging markets and underscores the importance of customer-centric AI strategies that cater to diverse demographic groups. | ||
| Keywords | ||
| Artificial Intelligence; Telecommunications; AI Acceptance; Technology Acceptance Model; TAM; Customer Satisfaction; Trust; Demographic; Customer Experience; AI-Powered Services; Perceived Usefulness; Perceived Ease of Use | ||
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