Service Science
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Item Will Customers Appreciate Service Transformation via Digital Technologies?(2025-01-07) Hu, Pei-Jen; Chang, Wei-LunThis study aims to investigate consumers' views, intentions, and actual use of self-service technologies in supermarkets, lifestyle retail stores, and restaurants by integrating the TPB model and the Markov chain. The results show that intention and usage were significantly influenced by perceived behavioral control in supermarkets, but attitude had the biggest impact on intention in lifestyle retail stores, where intention influenced actual usage. In restaurants, attitude mostly drove intention, but perceived behavioral control directly influenced usage. Based on the results of the Markov chain, the initial service decision impacted the continuity of later self-service technology usage: those who chose self-service preferred to stick with it, but those who were manually serviced were less likely to switch. These insights help firms understand real consumer wants and improve digitalized process design to improve the overall service experience across contexts.Item Unlocking Hidden Insights with fsQCA Analysis and Two-factor Perspective(2025-01-07) Yu Ho, Yeh; Hsu, Jack Shih-ChiehIn addition to exploring symmetric effects, researchers have sought to categorize service attributes based on asymmetric effects. Symmetric impacts imply that customer (dis)satisfaction directly correlates with an attribute's presence or absence. Conversely, certain attributes, known as "delighting" attributes, cause satisfaction when present, but their absence does not result in a corresponding level of dissatisfaction. On the other hand, "must-be" attributes lead to dissatisfaction when absent, but their presence does not cause a significant level of satisfaction. Service providers can leverage this understanding to allocate resources more effectively. However, customers often evaluate quality based on multiple attributes simultaneously, rendering individual categorization insufficient. Therefore, it is essential to understand the asymmetric effects of attribute configurations. We propose employing fuzzy set Qualitative Comparative Analysis (fsQCA) to identify configurations as delighting, performance-related, must-be, or even reversed. This involves identifying configurations associated with high and low outcomes and determining their types. This study shifts the focus from individual attributes to configurations, thereby enriching the literature on asymmetric effects.Item Introduction to the Minitrack on Service Science(2025-01-07) Maglio, Paul; Lin, Fu-Ren; Windasari, Nila