Enhancing Job Satisfaction and Productivity through Knowledge Management Infrastructure: A Case of Construction Industry

Abstract

This study rigorously investigates the influence of knowledge management infrastructures (KMI) on employees’ job satisfaction (JS) within the Iranian construction sector. It specifically investigates how structural, cultural, and technological facets of KMIs affect this satisfaction. The research adopts a quantitative methodology, utilizing established measurement tools from Gold et al. for KMIs and Hackman and Oldham for JS. The empirical Information was gathered via a survey distributed to stratified random sample of 150 employees and managers from five diverse construction firms in Iran. Examining the collected data with the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach, the study presents nuanced insights. It identifies that while cultural and technological infrastructures of KMIs significantly contribute to JS, the structural infrastructure does not exhibit a similar impact. Additionally, demographic factors such as age and professional experience were found to be non-contributory in the dynamics between KMIs and JS. However, gender and educational background emerged as significant moderating variables. Remarkably, employees with advanced academic qualifications reported higher satisfaction, likely due to the alignment of specialized knowledge with their professional roles. This research contributes to the current knowledge base by outlining the distinct components of KMIs that bolster JS in the construction industry, thereby offering a targeted framework for industry practitioners and policymakers to enhance employee well-being and organizational efficiency.