Development of a Causal Relationship Model Affecting the Technopreneurship Competencies of Students at Rajamangala University of Technology Srivijaya, Thailand


  •  Chaiya Tanaphatsiri    
  •  Sutithep Siripipattanakul    
  •  Patchara Eamcharoen    

Abstract

This study aimed to develop and validate a causal relationship model of factors affecting students’ technopreneurship competencies at Rajamangala University of Technology Srivijaya in Thailand. A quantitative design was employed, involving the sample of 225 undergraduate students, in accordance with the general rule for Structural Equation Modeling (SEM) to ensure adequate statistical power and model stability. Data were collected through a validated questionnaire and analyzed using Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM). The findings indicated three latent variables: learning management, learner-related, and leadership factors, affecting technopreneurship competencies. The model showed an excellent fit with the empirical data (χ² = 36.60, χ²/df = 1.076, p-value = 0.44, GFI = 0.97, CFI = 1.00, AGFI = 0.94, RMSEA = 0.009, and RMR = 0.004). The learner-related factors exerted the strongest direct influence on technopreneurship competencies (β = 0.59), emphasizing the critical role of motivation, positive attitude, and learning behaviors of learners. The leadership factors showed a moderate effect (β = 0.36), highlighting its importance in supporting competency development and an entrepreneurial environment through various types of leadership. However, the learning management showed a non-significant direct effect (β = −0.05), indicating it serves as a foundation rather than a key factor. This suggests that strengthening learner-related and leadership factors is crucial for promoting technopreneurship competencies. This study provides evidence for the applicability of the causal relationship model in technopreneurship competency development, recommending future research on potential mediating variables, deeper investigation of learning management factor, and multi‑institutional, longitudinal research designs to enhance its explanatory power and generalizability.



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