Article

Sectoral Disparities in the Digital Workplace: A Comparative Statistical Analysis of Remote Work Patterns and Productivity Scores in the Evolving Digital Society

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Abstract

The global transition to remote work has highlighted significant variations in efficacy across different industries. While the digital workplace is now standard, a data-driven understanding of the factors that determine productivity in this new paradigm is essential for optimizing performance and supporting workers. This study aims to move beyond anecdotal evidence by quantitatively analyzing the disparities in remote work patterns and their impact on productivity scores. A cross-sectional, comparative statistical analysis was conducted on a dataset of 300 remote workers across five key sectors: Healthcare, IT, Finance, Retail, and Education. The methodology involved using Analysis of Variance (ANOVA) to test for significant differences in mean productivity scores between sectors. A Multiple Linear Regression model was then developed to identify the most significant predictors of worker productivity from a range of variables related to demographics, work patterns, and digital tool usage. The ANOVA test confirmed a statistically significant difference in mean productivity scores across sectors (F-statistic: 3.6368, p-value: 0.0065), with the Retail sector exhibiting the highest mean productivity and Healthcare the lowest. The Multiple Linear Regression model was highly significant and explained 59.3% of the variance in productivity scores (R-squared = 0.593). Four key predictors were identified as statistically significant: task completion rate (positive), late task ratio (negative), calendar scheduled usage (positive), and tool usage frequency (positive). A planned machine learning classification phase was aborted due to a lack of variance in the categorical productivity label, as all participants were categorized as 'Low'. The study concludes that significant sectoral disparities in remote work productivity are prevalent and that effective work management behaviors are more predictive of performance than hours worked or demographic characteristics. The findings underscore the need for organizations to focus on optimizing task management systems and provide sector-specific support. Future research should employ mixed-methods and longitudinal designs to further explore these dynamics.

Keywords: Digital Workplace, Productivity, Remote Work, Sectoral Disparities, Task Management

How to Cite:

Hasibuan, M. & Fikri, R., (2025) “Sectoral Disparities in the Digital Workplace: A Comparative Statistical Analysis of Remote Work Patterns and Productivity Scores in the Evolving Digital Society”, Journal of Digital Society 1(3), 244-257. doi: https://doi.org/10.63913/jds.v1i3.53