Dataset for predictive modelling and analysis of employee attrition and retention
Year: 2025
Type: data-paper
Study design: Observational Study
Abstract: This dataset provides insights into the factors affecting employee attrition in the private sector of Saudi Arabia. The data were collected through an online survey of 1191 participants working in Saudi Arabia's private sector companies and institutions across various industries. The questionnaire consists of three categories of variables: demographic information, job-related features, and psychological and satisfaction variables. For each category in the questionnaire, several questions were disseminated to a sample population. Preprocessing and analysis were conducted to identify the principal factors influencing employee attrition and job satisfaction. The dataset was formulated with 34 attributes and 1191 rows. In addition, the dataset includes nominal and ordinal answers for the variables, allowing for sophisticated analyses using machine learning classification techniques. The dataset also contains the independent variable (target variable), about employee attrition information, which acts as a class or label variable in machine learning scenarios. We intend for this dataset to serve as a valuable resource for researchers and organizations aiming to understand and predict employee turnover, as it provides a set of attributes that can help formulate workforce management strategies and policies.
Source: Data in Brief
Authors: Haya Alqahtani, Hana Almagrabi, Amal Alharbi
Institution: King Abdulaziz University
Language: English
Topic: AI and HR Technologies
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,220
OpenAlex ID: W4415972572