## 2 Literature Review
### Technology Adoption in Information Systems  
In the 1960s, research in innovation adoption began with [PERSON] seeking to understand what influenced farmers' decisions to adopt agricultural innovations, with innovations described as an idea, practice, or object that is perceived as new to an individual or organization [23]. Early work in this area focused either on the characteristics of the individual adopting the innovation or the characteristics of the innovation [23]. Since the 1980s, researchers have focused on understanding the factors driving adoption of different technologies, leading to the development of a well-established literature stream and a number of theories. These theories can be discussed under two categories: (i) adopter-centered and (ii) innovation or organization centered. The prevailing theories are outlined in Table 1.  
The majority of models in the first category are based on the theory of reasoned action (TRA) [24], which posits that individuals' behaviors are formed based on their salient beliefs and attitude toward the behavior. While TRA does not prescribe what these salient beliefs are, it has been leveraged as the underlying foundation of several later models beginning with the technology acceptance model (TAM). TAM lists perceived usefulness and perceived ease of use as the salient beliefs which shape individuals' acceptance and usage of new technologies [25; 26]. TAM has been leveraged to examine technology adoption in various contexts and adapted to produce various new models. [PERSON] et al. [21] re-examined the popular technology models to create the Unified Theory of Technology Acceptance and Usage (UTAUT). UTAUT proposes that the likelihood an individual will accept a new technology is based on their perception of the performance expectancy (similar to perceived usefulness), effort expectancy (similar to perceived ease of use), social influence and facilitating conditions to adopt. The first theory in the second category, is Diffusion of Innovation (DOI) theory, which holds that the technology adoption decision is influenced by innovation characteristics: (i) relative advantage, (ii) compatibility, (iii) complexity, (iv) observability, and (v) trialability [23]. Similar to DOI, the TOE Framework proposed by [PERSON] and [PERSON] [27] suggests that IT adoption is influenced by three contexts--(i) technological, (ii) organizational, and (iii) environmental. These contexts are consistent with DOI theory in that the technological context incorporates the innovation characteristics. TOE theory also includes organizational factors, such as firm size, technology readiness, employee competence, and top management support [6; 7; 8; 9; 28; 29]. In congruence with DOI and TOE, the HOT-fit model, proposed by [PERSON] et al. [30], asserts that organizational and technological factors are determinants of successful IS adoption. The HOT-fit model also introduces human factors, claiming that user attitude and competence also have a positive impact on technology adoption [30]. Theories from both categories have been leveraged to study adoption across a widerange of contexts with several adaptations and combinations used. However, while the predictive power of adopter-centered theories has been established and human factors are relevant, we argue that the complex nature of HPC lends itself to a broader approach that considers organizational and technological factors.