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Knowledge Sourcing and Innovations of Firms in Synthetic and Symbolic Knowledge Base Sectors: Evidence from Thailand

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Abstract

This paper examines the geographical extent of knowledge sourcing of firms with synthetic and symbolic knowledge bases, drawing on the differentiated knowledge base (DKB) perspective. We contribute to the knowledge-sourcing studies and the DKB literature by analyzing the effects of local, national, and international knowledge-sourcing on firms’ innovations in the context of Thailand. The data from the postal survey were employed for statistical analysis. The results reveal that synthetic industry firms benefit from local knowledge sourcing regarding process innovations, while national and international knowledge sourcing is not significant for innovation performance. On the other hand, firms in the symbolic sector, though sourcing knowledge intensively from local sources, local knowledge sourcing does not help improve their product and process innovations. Instead, symbolic firms can enhance their product innovation by sourcing knowledge from national and international sources. We also find the substitution effect of local and national knowledge sourcing and the complementary effect of local and global knowledge sourcing in the group of symbolic firms. This evidence indicates the importance of global knowledge networks on innovations in the symbolic knowledge base sector. We suggest that when applying the DKB perspective to analyze the spatial extent of firms’ knowledge sourcing, it is necessary to pay more attention to the innovation effects generated by knowledge sourcing at different spatial configurations.

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Notes

  1. See www.eec.vec.go.th

  2. See www.boi.go.th

  3. www.dataforthai.com

  4. The low response rate may be attributable to the Thai government’s lockdown measures from March to August 2020 in response to the Covid-19 pandemic.

  5. We removed 63 questionnaires from firms in the R&D, business consulting, and medical product sectors, as these sectors are not categorized as synthetic or symbolic knowledge base industries. Also, 17 questionnaires were removed because of incomplete data.

  6. These questions are included in the questionnaire but not used in this paper.

  7. Collinearity analysis was done by regressing one independent variable on other independent variables and checking whether the resulting values of collinearity diagnostic statistics — the variance inflation factor (VIF) and tolerance statistics — were above the cut-point where the multicollinearity problem is likely to be present.

  8. In the last specification, knowledge sourcing variables are mean-centered to reduce a structural multicollinearity problem (Frost, 2019).

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Authors and Affiliations

  1. Thammasat University, Bangkok, Thailand

    Phakpoom Tippakoon, Nattapon Sang-arun & Panisa Vishuphong

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  1. Phakpoom Tippakoon
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  2. Nattapon Sang-arun
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Tippakoon, P., Sang-arun, N. & Vishuphong, P. Knowledge Sourcing and Innovations of Firms in Synthetic and Symbolic Knowledge Base Sectors: Evidence from Thailand. J Knowl Econ (2023). https://doi.org/10.1007/s13132-023-01620-2

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