PEOPLE: International Journal of Social Sciences

EXPERIENCE-VALUE ORIENTED MANAGEMENT STRATEGIES FOR HEALTH CHECKUPS IN TAIWAN MEDICAL CENTERS

Ching-Kuo Wei — 2026-03-16

The study aims to analyze the consumption behavior and the mechanism of loyalty formation among customers at high-end health management centers affiliated with medical centers in Taiwan. It focuses on how service quality, customer satisfaction, and brand image interact to influence loyalty in a highly competitive market. A survey method was adopted, targeting high-end health checkup customers at medical centers in Taiwan. From June to November 2024, 500 questionnaires were distributed, resulting in 446 valid samples. The questionnaire was reviewed by experts for expert validity, and the data met the required standards after reliability analysis.

Demographic Impact: Age significantly affects service quality, satisfaction, brand image, and loyalty. Specifically, the 31-40 age group scored higher than the 21-30 group across multiple dimensions. Additionally, customers with lower education levels exhibited higher loyalty. Correlation Analysis: All main variables (quality, satisfaction, brand image, and loyalty) showed significant positive correlations. Regression Analysis: The model explained 55.4% of the variance in loyalty. "Brand Image" was the most critical factor (β = .428), followed by "Customer Satisfaction" (β = .306). Notably, "Service Quality" did not have a significant direct impact on loyalty. Loyalty in high-end health checkups is primarily driven by "experiential value" and "brand trust" rather than basic medical quality, which is now taken for granted by customers.Healthcare institutions should strengthen brand positioning and differentiate themselves through professional imagery and high-end facilities. They should optimize the customer experience process (e.g., managing waiting times) and cater to the specific needs of different groups. Ultimately, providers must shift from a "quality-oriented" approach to an "experience and value-oriented" management model.

HYBRID INTELLIGENCE (HI) IN THE HOSPITALITY INDUSTRY: EFFECTS ON TRUST, PERCEIVED SERVICE QUALITY AND CUSTOMER SATISFACTION

Hasna El Hamzaoui — 2026-03-18

In an emerging country like Morocco, the hospitality sector is facing gradual transformations due to the integration of artificial intelligence technologies, such as check in kiosks, chatbots, and assistance robots. While this dynamic is still limited and heterogeneous, it aims to improve service efficiency and personalize the customer experience, while also raising questions about the acceptability of these systems and their effects on three main dimensions of customer experience: perceived service quality, trust, and customer satisfaction. Given the limitations of fully automated services, hybrid intelligence, defined as collaboration between AI and human intelligence, appears as an alternative option that combines the relational component with technological efficiency. This study aims to examine the comparative impact of three types of hotel reception modalities; Human-only reception, AI-only reception, and reception based on hybrid intelligence on the three main dimensions of customer experience. To this end, we adopted a quantitative approach based on a comparative questionnaire administered to Moroccan hotel guests who have stayed at least once in a 4- or 5-star hotel in Marrakech. The results confirm that the hybrid model, where clients interact with AI and humans, generate higher levels of trust, perceived quality and satisfaction than either a purely human or purely AI based reception. The results also indicate that customers familiar with AI use demonstrate a higher degree of trust in AI-based systems. Furthermore, customers with a strong relationship orientation report being satisfied with the experience offered by hybrid or human-dominated models. This study enriches the understanding of the role of hybrid intelligence in hotel services within the Moroccan context and offers practical recommendations for hotels wishing to integrate AI technologies without compromising the customer experience. Due to the use of scenarios and a convenience sample, this study has limitations in terms of generalizing the results. However, it opens up avenues for future research based on real-world experimentation and the integration of in-depth qualitative approaches.

VIABLE SUPPLY CHAINS: THEORETICAL EVOLUTION AND EMPIRICAL EVIDENCE FROM THE ITALIAN FMCG SECTOR

Andrea Payaro — 2026-03-23

Over the past forty years, supply chain management has evolved from a technical–logistical discipline focused on efficiency into a dynamic and complex system oriented toward resilience, adaptability, and sustainability. This paper critically retraces the conceptual evolution of supply chains—from Lean to Agile, Resilient, Adaptive, and finally Viable Supply Chains—framing these paradigms in light of today’s volatile, uncertain, and digitalized environments. Through a narrative literature review and an empirical survey involving 112 Italian fast-moving consumer goods (FMCG) companies (245 respondents), the study investigates the adoption level of Viable Supply Chain principles across four key dimensions: end-to-end visibility, predictive capabilities through Artificial Intelligence, rapid reconfigurability, and integration of ESG criteria. Findings reveal that most firms have limited first-tier visibility, an embryonic adoption of AI (only 10.9% have pilot initiatives), and insufficient digital competences within procurement teams (44.2%). Nevertheless, 70% of firms collaborate with suppliers to reduce environmental impact, showing increasing awareness of sustainability. The study concludes that Italian FMCG firms are in a transitional phase: while recognizing the strategic importance of digitalization and sustainability, they have yet to fully embed viability into decision-making and operations. The paper contributes to the ongoing debate on the future of Supply Chain Management, advocating for a Complex-Aware Supply Chain—a system able to learn, adapt, and regenerate in highly complex contexts.