Abstract
A better understanding of the linkage between the objectives and outcomes of innovation will enable firms to plan better for effective utilization of their resources for generation of innovation. The current study enhances the understanding of relationships between the intent to innovate and eventual outcome as the intent to innovate drives complex processes and resource allocation that leads to a successful innovation. We analyze the World Bank innovation survey data of IT firms in China and find that drivers of innovation significantly impact the configuration elements of the innovation phenomenon within firms and influence how firms execute collaboration with external partners. This is turn impacts the product and process innovation generated by the firm. The findings imply that firms should decide about their choice of partners for innovation and the mode of engagement with the partners based on the drivers for innovation.
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Notes
We have excluded state owned firms from analysis as these firms tend to invest disproportionately in R&D to uphold the public commitment of the government.
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Appendix: Supplementary Analysis
Appendix: Supplementary Analysis
We performed additional analysis for the study by considering four sub-samples as described in section 4.1. We only present the results for the model represented by Eq. (2) for large firms, (in terms of generated revenue) in Table 8. We have not shown the analysis for other cases and for small firms as the results are similar to the main results presented in the paper. From Table 8, we find that for large firms product and process antecedents become significant for choice of partner. Deep-diving into the results, we find that though suppliers are preferred partners for new technology based product innovation (coefficient is 0.685, p < 0.001).
Similarly, the coefficients for client as a partner indicates that for new technology-based product innovation, partnership with clients (coefficient is −0.365, p < 0.05) is low. A new product introduction as an objective of innovation leads to higher collaboration with academia (coefficient is 0.25, p < 0.05).
We also analyze the regression results by replacing the control variables size (sales) and specialized software (spec_soft) with R&D intensity. R&D intensity is defined as the R&D expenditure of the firm per unit sales i.e., R&D expenditure divided by the sales of the firm (in absolute number). From Table 9 we observe that the outcome is qualitatively similar to the results shown in Table 2.
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Jha, A.K., Bose, I. Linking Drivers and Outcomes of Innovation in IT Firms: The Role of Partnerships. Inf Syst Front 23, 1593–1607 (2021). https://doi.org/10.1007/s10796-020-10061-0
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DOI: https://doi.org/10.1007/s10796-020-10061-0