# Chatots in Airport Customer Service--Exploring Use Cases and Technology Acceptance
## 4 Conceptual Model  
Following the literature, users' acceptance and consequent adoption of technology are usually assessed either via the so-called _Technology Acceptance Model_ (TAM), developed by [PERSON] (2018), or via the more holistic _Unified Theory of Acceptance and Use of Technology_ (UTAUT), proposed by [PERSON] and colleagues [PERSON] et al. (2018). Both research models aim to understand the factors that determine the acceptance or rejection of a given technology by its users [PERSON] et al. (2018). The TAM, which, due to its simpler structure, has been employed more often, focuses on information technology adoption, i.e., an individual's intention to use the technology, based on its _Perceived Usefulness_ (PU) and its _Perceived Ease of Use_ (PEU). To this end, PU is considered the degree to which a person believes that using the technology would enhance his or her job performance, and PEU is the degree to which using the technology would be free of effort. PEU has been shown to have a direct effect on PU and a positive relationship with a user's _Behavioral Intention_ (BI), both directly and indirectly via its PU. Research has furthermore shown that there is a positive relationship between PU and a user's BI via his/her Attitude (A) [PERSON] et al. (2018). [PERSON] original TAM is illustrated in Figure 1.  
Over the years, the original TAM has been expanded to TAM2, consisting of five additional factors directly impacting PU (i.e., _Subjective Norm_, _Image_, _Job Relevance_, _Output Quality_, _and Result Demonstrability_) and two factors moderating these relationships (i.e., _Experience_ and _Voluntariness_) [PERSON] et al. (2018). Finally, the most recent adaptation of the model, i.e., TAM3, elaborates on the PEU branch, adding _Computer Self-efficacy_, _Perception of External Control_, _Computer Anxiety_, _Computer Plafulness_, _Perceived Enjoyment_, and _Objective Usability_ as respective predictors [PERSON] et al. (2018). The UTAUT model, on the other hand, aims to unify a number of existing IT acceptance theories [PERSON] et al. (2018). Just like the TAM, it suggests that the actual user behavior with regard to technology adoption is determined by a user's _Behavioral Intention_ (BI). Yet, with UTAUT, BI is directly influenced by a user's _Performance Expectancy_, _Effort Expectancy_, _Social Influence_, and other _Facilitating Conditions_. The effect of these factors is then moderated by _Gender_, _Age_, _Experience_, and _Voluntariness of Use_. [PERSON] et al. 's original UTAUT model is depicted in Figure 2.  
Figure 1: The Technology Acceptance Model according to [PERSON] (2018). A later revision of the model, i.e., UTAUT2, tried to tackle the prevailing criticism of most technology acceptance research being targeted at organizational as opposed to private settings, which led to the introduction of additional factors, such as _Price Value_, _Hedonic Motivation_, and _Habit_[49]. Although UTAUT aims to provide a more holistic understanding of technology acceptance, it is considered a more complex model and thus less suitable for the initial explorations of a field. Furthermore, with respect to the acceptance of chatbots, the use of the TAM has seen a higher uptake in the literature [46; 50], reporting on investigations in online shopping [16; 46; 51], veterinary consultation [52], mental health care, and online banking [53]. In all of these instances, researchers have used the original version of the TAM, which, for simplicity reasons, neglects factors that impact users' PU and PEU. Consequently, we decided to also use this base version of the TAM as a starting point for our investigations. When applying the TAM to a specific focus of interest, researchers usually adapt and extend the model, adding factors such as _Perceived Enjoyment_, _Price Consciousness_, _Perceived Risk_, _Trust_, _Compatibility_, _Technological Anxiety_, or _Level of Anthropomorphism_.