The impact of design thinking on entrepreneurial competencies among university students in Peru

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Type of the article: Research Article

Abstract
In emerging economies, youth unemployment and limited entrepreneurial education remain persistent challenges for higher education institutions. This study aims to examine how the dimensions of design thinking (empathy, creativity, and problem-solving) influence the development of entrepreneurial competencies among university students in Peru. A structured questionnaire was administered to 385 undergraduates enrolled in business programs at two private universities in Metropolitan Lima between August and November 2024. Business undergraduates were selected because they represent the segment most actively involved in university-based entrepreneurial initiatives in Peru. Data were analyzed using covariance-based structural equation modeling (CB-SEM) to assess the structural relationships between design thinking dimensions and entrepreneurial competencies. The results reveal strong and statistically significant associations across all constructs. Problem-solving exerted the strongest effect on willingness to innovate (β = 0.42), followed by entrepreneurial motivation (β = 0.37) and creativity (β = 0.33). Empathy demonstrated positive effects on motivation (β = 0.35) and resilience (β = 0.28), with all coefficients significant at p < .001. Model fit indicators confirmed robust adequacy (CFI = 0.94; GFI = 0.92; NFI = 0.91; RMSEA = 0.06). These findings indicate that design thinking strengthens the cognitive and behavioral foundations of entrepreneurial performance, particularly adaptability, creative ideation, and user-centered problem-solving. Integrating this human-centered iterative methodology into higher education represents an effective strategy for enhancing students’ innovation capacity and resilience. The study advances theory by empirically validating design thinking as a pedagogical mechanism for entrepreneurship education, and advances practice by offering evidence-based guidance for universities operating in emerging economies.

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    • Table 1. Participant characteristics
    • Table 2. Descriptive statistics and inter-construct correlations
    • Table 3. Reliability and convergent validity
    • Table 4. Discriminant validity
    • Table 5. Model fit indices
    • Table 6. Structural coefficients
    • Table A1. Measurement instrument
    • Conceptualization
      Luis Miguel Olortegui-Alcalde
    • Data curation
      Luis Miguel Olortegui-Alcalde
    • Investigation
      Luis Miguel Olortegui-Alcalde, Franklin Cordova-Buiza
    • Methodology
      Luis Miguel Olortegui-Alcalde
    • Validation
      Luis Miguel Olortegui-Alcalde
    • Visualization
      Luis Miguel Olortegui-Alcalde
    • Writing – original draft
      Luis Miguel Olortegui-Alcalde, Franklin Cordova-Buiza
    • Writing – review & editing
      Luis Miguel Olortegui-Alcalde, Franklin Cordova-Buiza
    • Formal Analysis
      Franklin Cordova-Buiza
    • Funding acquisition
      Franklin Cordova-Buiza
    • Project administration
      Franklin Cordova-Buiza
    • Resources
      Franklin Cordova-Buiza
    • Supervision
      Franklin Cordova-Buiza