# The Extended Information Systems Success Measurement Model: e-Learning Perspective
## 3 Research Framework and Hypothesis Development
### Hypotheses Development
When looking at the factors influencing students' intention to use IS for e-learning, social influence was not evidenced to be a significant determinant of behavioral intention [5; 111]. Additionally, this relationship still needs to be confirmed in adopting social networks for data sharing [104]. However, all other studies have shown social influence on the behavioral intention to use the IS, thus confirming the existence of this relationship [3; 4; 109; 110; 112; 113; 114; 115; 116]. By analyzing previous empirical research, the authors defined the third hypothesis:  
**Hypothesis 3 (H3). **_Social influence positively affects end user behavioral intention to use the system_. Facilitating Condition \(\rightarrow\) Use Behavior Relation  
Facilitating conditions represent the subjective assessment of IS users on the organizational and technical infrastructure supporting the system's use. Even though, according to the original UTAUT model, the facilitating conditions factor significantly influences the use behavior of the IS, previous research results on the existence of this relation are divided. On the one hand, several studies confirmed the positive effect of facilitating conditions on use behavior in the context of e-learning [4; 5; 110; 115; 116]. On the other hand, also in the context of e-learning, this relationship was not confirmed [3; 6; 117; 113; 109]. Even though previous research results on this relation have been diverse, taking into account the original UTAUT model and the results that evidence the importance of this relation, the authors defined the fourth hypothesis as follows:  
**Hypothesis 4 (H4). **_Facilitating conditions positively affect use behavior_. Behavioral Intention \(\rightarrow\) Use Behavior Relation  
The behavioral intention factor, which addresses the assumed temporal determinant of system use according to the UTAUT, significantly impacts ultimate behavior in using the system. The existence of this relation was confirmed in many previous studies. In the context of IS success in e-learning, internet banking, knowledge management systems, etc. [4; 5; 110; 113; 115; 116], behavioral intention has been evidenced to be a significant determinant of use behavior. Therefore, the fifth hypothesis is defined as follows:  
**Hypothesis 5 (H5). **_End user behavioral intention to use the system positively affects use behavior_. Beyond the six factors from the UTAUT model, workforce agility is a component that affects how the IS will be used when brings changes to the work environment and the usual way of working [118]. Previous research on workforce agility only examined relations of proactivity, adaptability, and resilience as dependent factors [118; 119; 105; 107; 108; 120]. According to the results, no research was found in the literature examining the impact of workforce agility on the behavioral intention to use the IS and the use behavior. Therefore, to answer the research question, does the workforce's agility affect the success of IS? the authors constructed the hypotheses explained below that would help measure IS success more accurately. Workforce Agility \(\rightarrow\) Behavioral Intention Relation  
Minnesota's Theory of Changes in the Work Environment explains \"work\" as an interaction between the individual and the work environment. At the same time, adaptation to changes in work reflects the mutual action of one and the other to meet joint needs [106]. The workforce agility construct explains people's behavior in situations where changes occur. Introducing, replacing, or upgrading ISs as a form of innovation in the work environment is a persistent change in work processes. For this reason, it is important to examine whether and to what extent workforce agility affects the behavioral intention of users to use the IS. According to the above, the authors proposed the sixth hypothesis:  
**Hypothesis 6 (H6). **_Workforce agility positively affects end user behavioral intention to use the system_. Workforce agility is built by proactiveness, adaptability, and resilience [107].