| dc.description.abstract | The concept of open innovation has received much interest in management research of late. Open innovation paradigm considers that in order to advance technologies and markets, firms can and should leverage internal and external knowledge, ideas, expertise, and paths to market. This is in contrast to the traditional or closed model of innovation management, where organizations usually leverage the in- house capabilities for innovations. Past studies have looked at the principles, individual drivers, and organizational benefits of open innovation. Though a majority of the studies have focused on developing conceptual foundations, these have not been empirically validated. Research in the area of underlying facilitating factors of open innovation performance is limited. Constructs to measure degree of openness have not been defined in the existing literature. There exists no research identifying the benefits of external partners which is a critical element of open innovation. Current studies also show conflicting findings on the influence of partner characteristics on the technology transfer time. This thesis is focused on operationalization, measurement, and performance evaluation of open innovation principles, and attempts to fill some of these gaps.
We selected Information Technology (IT) sector for investigation of the above mentioned areas. IT sector has high scope for open innovation due to the inherent characteristics of the globally distributed network of solution providers and clients. IT applications also widen the possibility of open innovation in other sectors by creating platforms that enable collaboration. We used a mix of qualitative and quantitative research methodologies to explore implementation aspects of open innovation and to identify the influence of degree of openness on innovation performance. Twenty-four interviews were conducted with top management executives in IT firms across India, Europe, and Australia over a period of eight months. A content-based analysis of these interviews using open coding was used to investigate experts perspective of open innovation, strategic relevance of open innovation, and industry perception and trends of open innovation adoption. We developed a framework to classify open innovation projects based on the market knowledge strategy, innovation objective, and stage of the project. During the interviews, we did a preliminary analysis of the research questions and validated the scales developed. In the next stage, two in-depth case studies at SAP Co- Innovation Lab and IBM India Research Lab were conducted to study the operationalization aspects of open innovation principles. These cases were used to explain how firms identify, assimilate, and integrate externa! knowledge. As an output of this stage, a model was developed to explain the organizational rationale to collaborate, partner selection process, and execution aspects of open innovation projects. In the quantitative stage, we identified the influence of degree of openness, strength of appropriability regime, and project management maturity on the performance of open innovation projects. Performance was measured based on reduction of technology transfer time from research labs to business units, time to market innovations from the business units, and degree of innovativeness of the outcome. Specifically, we investigated the influence of the following factors on open innovation performance at the project level:
1. Partner variety - differentiated as collaboration with research and market partners
2. Number of partners - number of research and market partners
3. Innovation funnel openness - the phases of the project at which it goes open
4. Intensity of collaboration with the partners - as perceived by the focal firms
5. Strength of appropriabiiity regime-strength of measures that guarantee value for resource owners
6. Project management maturity by the focal firms.
Data from 92 open innovation IT projects across India and Europe were used to test the proposed hypotheses using multiple linear regression and binary logistic regression. We developed an index termed Partner Collaboration Intensity (PCI) to measure degree of openness based on the number of partners, intensity of collaboration, and innovation funnel openness. Results showed that specialized research or market partners reduced technology transfer time from research labs to business units. Results also indicated higher values of PCI index, higher strength of appropriabiiity regime, & higher levels of project management maturity positively influenced reduction of technology transfer time from research labs to business units. We also found that higher values of PC! index and higher levels of project management maturity had no significant role in the time to market innovations. However, partner variety and higher strength of appropriabiiity regime showed positive influence on the reduction of time to market innovations. Results of the logistic regression model showed that all parameters except higher strength of appropriability regime had a positive correlation with the occurrence of breakthrough innovations compared with incremental innovations. The region-wise differentiation highlighted, with improved degree of openness, Indian projects had faster commercialization; while European projects showed reduction of technology transfer time from research labs to business units. European data also showed positive correlation with the occurrence of break through innovations as compared to incremental innovations. Contributions:
The study contributes to both theory and practice. It contributes to open innovation literature by developing constructs to measure the degree of openness and open innovation project performance. It also identifies the influence of degree of openness, strength of appropriabiiity regime, and project management maturity on open innovation project performance. The operational model developed from the cases identifies factors influencing various stages of implementing open innovation principles. In practice, the results will act as a guide for managers to improve the performance of collaborative projects and adopt different open innovation principles according to the innovation objectives. | en_US |
