# The Extended Information Systems Success Measurement Model: e-Learning Perspective
## 1 Introduction  
In searching for an information system (IS) success measure, there are nearly as many measures as there are studies. The reason for this is understandable when one considers that \"information\", as the output of an IS or the message in a communication system, can be measured at different levels, including the technical, semantic, and effectiveness levels [1]. The IS creates information that is communicated to the recipient, who is then influenced or not by it. The information flows through a series of stages--from production to use or consumption to affect individual and/or organizational performance. Hence, it is acknowledged that the IS's success needs to be expanded by recognizing what measures need to be undertaken to obtain the most suitable outputs. Accordingly, for more than a decade, many researchers have debated IS success [2, 3, 4, 5, 6, 7, 8]. Since the beginnings of research in this field, with the advent of the first model by [PERSON] (D&M IS Success Model) [1], several authors have confirmed the proposed model by examining the success of different ISs [8]. After the D&M model, the literature was amplified with studies that not only suggested and tested other IS success models [2, 3, 4, 5, 6, 7], but also dealt with further development, modification, and adaptation of existing IS success models [9, 10]. Finally, the authors of the Unified Theory of Acceptance and Use of Technology (UTAUT) [2] published the UTAUT model in 2003, which was created by combining the previous eight theories and models of IS success. Through years of using the UTAUT model in examining the performance of ISs in different environments, researchers identified its shortcomings and suggested improvements to the model. Furthermore, there have been scientific contributions in the form of modified models for measuring the success of IS. For example, [11] found that many articles and studies cited the original UTAUT as a general reference for examining factors influencing the acceptance and use of technology. Still, researchers needed to deal with the expansion of UTAUT [11]. The literature review results show that there was some work on improving UTAUT. However, it only concerned improving existing model factors [11]. In 2012, authors [11] expanded the theory of the UTAUT, thus creating an Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) [11] by adding three new factors that directly affect the behavioral intention to use the IS and the use of technology itself. Based on the reports of the world's largest companies in the information technology industry [12; 13], information and technological structure investments have taken almost the largest share of company investments. Given that technology investments are mainly based on implementing new or upgraded ISs, companies strive to foresee that these investments will pay off in future business. Therefore, it is necessary to determine the success of ISs implemented in the workplace. Different factors affect their success depending on the context in which the ISs are observed. Accordingly, these factors need to be measured appropriately. In line with the current state-of-the-art findings, an IS success model with factors that emphasize the importance of people's responses to changes in the work environment has yet to be found. This study assessed the factors essential for measuring e-learning IS success when changes in the work environment happened. It was mainly motivated by the changes caused by COVID-19 witnessed after the shift to fully online learning environments, which forced the workforce to embrace technology. Observing that e-learning was spotlighted much before, it is noteworthy that the true power of ISs in higher education was revealed by the disruptions and changes COVID-19 brought. To face uncertainties, higher education institutions required an agile, proactive, adaptive workforce with a positive attitude towards changes.