This study examines how hospital environmental conditions influence perceived workforce productivity through the mediating roles of organizational support and job satisfaction. Grounded in Donabedian's structure–process–outcome (SPO) framework and informed by motivational theory, the study conceptualizes productivity as an organizational outcome shaped by structural and psychosocial processes rather than as a purely technical measure.
A quantitative, cross-sectional survey was conducted with 379 healthcare employees working primarily in public hospitals in Thailand. Partial least squares structural equation modeling (PLS-SEM) was used to estimate direct and indirect relationships among hospital environment, organizational support, job satisfaction, and perceived productivity. To assess out-of-sample performance, PLS-Predict and the cross-validated predictive ability test (CVPAT) were employed as complementary diagnostic tools.
The results show that a supportive hospital environment is positively associated with perceived productivity, both directly and indirectly via organizational support and job satisfaction. Predictive assessment indicates moderate-to-strong predictive adequacy (Q2_predict = 0.62–0.74), with model performance comparable to linear benchmarks and consistently superior to naïve indicator-average models. The findings highlight the value of integrating structural and motivational perspectives to inform evidence-based organizational decision-making in healthcare settings.
This study contributes to healthcare workforce research in four ways. First, it reframes productivity as an organizational outcome emerging from structural and psychosocial conditions rather than as an individual or technical metric. Second, it integrates Donabedian's SPO framework with Herzberg's two-factor theory to provide a multi-level explanation of workforce performance. Third, it provides empirical evidence from Thailand's public hospital system, an underexplored context in healthcare management research. Fourth, it extends prior explanatory studies by incorporating PLS-Predict and CVPAT to assess out-of-sample predictive validity, enhancing the model's practical relevance for managerial decision-making.
The illustration depicts a framework for evidence-based decision-making in hospital environments. It shows how physical and technological structures, such as ergonomic design, ventilation, noise control, rest facilities, and technological resources, influence staff productivity. The human connection section highlights job satisfaction and organizational support as key drivers of motivation. Job satisfaction is influenced by work-life balance, morale, teamwork, and fair compensation, while organizational support includes leadership support and access to resources. The result section explains how these factors enhance workforce productivity, with a high explanatory power of 82 percent. The managerial playbook provides actionable insights, such as treating the environment as core infrastructure, pairing infrastructure with people-focused policies, reducing organizational friction, and using predictive dashboards.The illustration depicts a framework for evidence-based decision-making in hospital environments. It shows how physical and technological structures, such as ergonomic design, ventilation, noise control, rest facilities, and technological resources, influence staff productivity. The human connection section highlights job satisfaction and organizational support as key drivers of motivation. Job satisfaction is influenced by work-life balance, morale, teamwork, and fair compensation, while organizational support includes leadership support and access to resources. The result section explains how these factors enhance workforce productivity, with a high explanatory power of 82 percent. The managerial playbook provides actionable insights, such as treating the environment as core infrastructure, pairing infrastructure with people-focused policies, reducing organizational friction, and using predictive dashboards.
