Open AccessSuccess model for measuring information system implementation: Literature review
Author(s) -
Beki Subaeki,
Aedah Abd Rahman,
Sopiyanshah Jaya Putra,
Cecep Nurul Alam
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1402/7/077015
Subject(s) - computer science , implementation , measure (data warehouse) , adaptation (eye) , information system , data science , management science , software engineering , data mining , engineering , psychology , neuroscience , electrical engineering
Many researchers have done research on information systems before; this is because of the breadth of studies or topics about IS. There is some example of a study on how to measure Information System Success by testing instrument factors. Some researchers can produce different judgments regarding the success of implementation of IS; this is because the first definition of success of each researcher is changed, the two perspectives on success assessment, the three variables used, the four implementations in different environments. Several models can be used as references to assess the success of IS, Delone and McLean are examples that are widely used as references, which use six variables in measuring IS implementation. From the model used, later there will be a gap in determining the model, and this becomes an opportunity for the development of the model as follows. The development of models to measure information system success can be done by adoption, adaptation, and combination. This is legitimately valid as long as the development of the model is accompanied by supporting theories. The purpose of this review literature is especially researchers can provide an overview of related to the method of previous researchers. Then it can be used as a framework for solving problems.