Using machine learning-based binary classifiers for predicting organizational members' user satisfaction with collaboration software.

ABSTRACT:

Background

In today's digital economy, enterprises are adopting collaboration software to facilitate digital transformation. However, if employees are not satisfied with the collaboration software, it can hinder enterprises from achieving the expected benefits. Although existing literature has contributed to user satisfaction after the introduction of collaboration software, there are gaps in predicting user satisfaction before its implementation. To address this gap, this study offers a machine learning-based forecasting method.

Methods

We utilized national public data provided by the national information society agency of South Korea. To enable the data to be used in a machine learning-based binary classifier, we discretized the predictor variable. We then validated the ef

SUBMITTER: Feng Y 

PROVIDER: S-EPMC10403168 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature