Usability

Descriptive statistics

Process (computing)

Engineering

Biology

Statistics

Social psychology

Operating system

Continuance

Data mining

Computer science

Structural equation modeling

Paleontology

Mechanical engineering

Test (biology)

Process management

Psychology

Mathematics

Work (physics)

Decision support system

Knowledge management

Technology acceptance model

Human–computer interaction

Machine learning

Indonesian Journal of Electrical Engineering and Informatics (IJEEI)

Currently, the core trend of Higher Education Institutes (HEI) to invest in decision support systems (DSS) to improve their decision-making process. Due to technology emergence, HEI has been experiencing noteworthy changes. Many techniques such as DSS have adopted developed and implemented to support the educational process. Even though DSS has adopted and invested mainly in most sectors, a lack of research in investigating confirmed, the influencing factors on the intention of stakeholders to continue to use them. Consequently, the purpose of the study is to examine post-adoption users' satisfaction and users’ intention to continue using DSS. This study combining two theoretical models, the Technology Acceptance Model, and The Technology Organization Environment Framework, to examine users’ intentions to continue using DSS. The data collection process has conducted using 240 respondents, who belong to HEI institutions (Academia and management staff), who work on DSS. Structural Equation Modeling was utilized to analyze structural relationships among the proposed model’s factors. The authors used several methods such as hierarchical regression, one-way ANOVA, descriptive statistics, as well as t-test have applied to evaluate the model's components relevancy, understanding, and pertinence to each other. The result shows the proposed model fits the data and had a good explanation than the existing models. On the other hand, the results show the importance of equipping DSS with real-time support because they have positive repercussions in the decision-making process The implications as well as the limitations of this study have been extensively discussed.

M2CIM-DSS: A Model for Measuring Continuance Intention in Decision Support Systems