Transforming 4Cs capabilities into incremental innovation: Mediating role of knowledge co-creation in manufacturing SMEs

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Type of the article: Research Article

Abstract
This study examines how 4Cs capabilities, namely critical thinking, creativity, communication, and collaboration, contribute to incremental innovation through the mediating role of knowledge co-creation in resource-constrained manufacturing SMEs. Data were collected from 179 key informants, including owners, executives, engineers, and technicians, targeting manufacturing SMEs in Thailand between May and June 2025 using a structured questionnaire survey. These respondents were selected because they are directly involved in operational and innovation-related activities in their firms. The data were analyzed using partial least squares structural equation modeling (PLS-SEM). The results show that all four 4Cs capabilities have statistically significant positive effects on incremental innovation: critical thinking (β = 0.194, p < 0.01), creativity (β = 0.255, p < 0.01), communication (β = 0.183, p < 0.05), and collaboration (β = 0.157, p < 0.01). All four capabilities also positively influence knowledge co-creation, which in turn significantly affects incremental innovation (β = 0.257, p < 0.01). The findings further indicate partial mediation, suggesting that learning-oriented capabilities contribute to innovation both directly and through knowledge co-creation. These findings indicate that incremental innovation in resource-constrained manufacturing SMEs depends not only on the presence of learning-oriented capabilities but also on how these capabilities are integrated through knowledge sharing, integration, and application processes. Knowledge co-creation therefore functions as a central mechanism through which existing capabilities are translated into innovation outcomes.

Acknowledgment
This research was supported by Prince of Songkla University (Grant No. LAM6802035S).

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    • Figure 1. Conceptual framework
    • Figure 2. Results of the structural model
    • Table 1. Characteristics of the respondents
    • Table 2. Reflective measurement and structural models
    • Table 3. Predictor assessment
    • Table A1. Constructs and measurement items
    • Conceptualization
      Kritsakorn Jiraphanumes
    • Data curation
      Kritsakorn Jiraphanumes, Kanittha Pattanasing
    • Formal Analysis
      Kritsakorn Jiraphanumes, Kanittha Pattanasing
    • Funding acquisition
      Kritsakorn Jiraphanumes
    • Investigation
      Kritsakorn Jiraphanumes, Kanittha Pattanasing
    • Methodology
      Kritsakorn Jiraphanumes, Kanittha Pattanasing
    • Project administration
      Kritsakorn Jiraphanumes
    • Supervision
      Kritsakorn Jiraphanumes
    • Validation
      Kritsakorn Jiraphanumes, Kanittha Pattanasing
    • Visualization
      Kritsakorn Jiraphanumes
    • Writing – original draft
      Kritsakorn Jiraphanumes
    • Writing – review & editing
      Kritsakorn Jiraphanumes, Kanittha Pattanasing