Total quality management (TQM) for sustainable growth performance in the private healthcare sector

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This study explores the influence of total quality management (TQM) on the sustainable growth performance of companies in the private healthcare sector. A quantitative research method and a purposive sampling method were used. A questionnaire comprising 25 items was spread among 282 administrative employees in private hospitals and healthcare centers in Negeri Sembilan, Malaysia. Structural equation modeling (SEM) via Smart PLS revealed that, except for leadership, all TQM variables exhibit positive and direct interrelationships within the sector. Key findings indicate that customer focus, continuous improvement, and employee involvement positively correlate with company performance, while leadership has a negative direct impact. Collectively, these exploratory TQM factors explain 73% of the variance in healthcare company performance (R² Adj = 0.732, P < 0.01), with employee involvement identified as the most critical component for enhancing performance. These results highlight the importance of prioritizing employee engagement in hospital management to achieve optimal performance outcomes. Additionally, the study suggests a need to reevaluate traditional leadership approaches, as they may hinder performance. This investigation advances the understanding of TQM in healthcare, advocating for a strategic emphasis on employee involvement and a reassessment of leadership practices to drive organizational success.

Acknowledgment
This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
The questionnaire was validated based on studies involving human participants that were reviewed and approved by the social sciences, arts, and humanities ECDA University of Hertfordshire (UK).

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    • Figure 1. Structural model
    • Table 1. Number of respondents from each hospital
    • Table 2. Internal consistency
    • Table 3. Discriminant validity through the Fornell-Larcker criterion
    • Table 4. Discriminant validity through heterotrait-monotrait (HTMT)
    • Table 5. Structural model path coefficient
    • Table 6. Coefficient of determination (R² and R² Adj)
    • Conceptualization
      Ganesh Ramasamy, Poovarasan Avadaiyar
    • Data curation
      Ganesh Ramasamy, Poovarasan Avadaiyar
    • Formal Analysis
      Ganesh Ramasamy, Poovarasan Avadaiyar
    • Investigation
      Ganesh Ramasamy, Poovarasan Avadaiyar
    • Methodology
      Ganesh Ramasamy, Poovarasan Avadaiyar
    • Resources
      Ganesh Ramasamy, Poovarasan Avadaiyar
    • Software
      Ganesh Ramasamy, Poovarasan Avadaiyar
    • Supervision
      Ganesh Ramasamy
    • Validation
      Ganesh Ramasamy
    • Visualization
      Ganesh Ramasamy
    • Writing – original draft
      Ganesh Ramasamy, Poovarasan Avadaiyar
    • Writing – review & editing
      Ganesh Ramasamy