Validating a Self-Service Technology Adoption Model(STAM) across Operational Conditions and Consumer Characteristics

The purpose of this study is to assess the self-service technology adoption model (STAM)’s generalizability across several operational conditions (the hotel’s star rating, price level, and the length of the waiting line at the service station) and customer background (gender, previous direct experience with SSTs at hotels, and prior experience with SSTs at other retail outlets such as grocery and hardware stores). Based on the tests of measurement invariance, especially via structural equation modeling with mean structures, the STAM appears to be valid and generalizable across gender, hotel SST user groups. 3- and 5- star hotel segments, and mid- to high-price markets. The STAM’s structure is generalizable across both short and long waiting line operation conditions, although the mean values differed at the measurement item and latent factor levels. The STAM is not generalizable across the guest groups with or without previous retail SST experience in both the model’s structure and item/latent factor mean levels. The results collectively suggest that the STAM is robust across a variety of service situations, save previous experience with SSTs, and that it can be used in understanding hotel customers’ adoption process of SSTs.