Generation of breakthrough innovation through a knowledge management perspective: the case of small software firms
Bibliographic record
Abstract
The literature on how is managed by radical innovators is embryonic, and the domain is still being mapped out. With this thesis, we aim to further the understanding of how small software firms (SSFs) manage and organize internally to generate breakthrough innovations. Our two research questions are formulated as follows: (Q1) How do SSFs create, transfer, retain, and protect their knowledge? (Q2) How do SSFs organize internally to manage their knowledge? The first question (Q1) refers to the management of in SSFs engaged in breakthrough innovation activities. In this study we explored four management processes: creation, transfer, retention, and protection. The second question (Q2) concerns SSFs' organizational settings. We investigated SSFs' physical infrastructures, organizational structures, organizational cultures, and information technology tools, a set of variables that we called knowledge organizational infrastructure. In order to answer these two questions, five cases of SSFs engaged in breakthrough innovation activities were explored. The setting of this research is the Canadian software industry. This industry is the most important and fastest growing component of the Canadian Information and Communication Technology (ICT) sector since 1997 (Industry Canada, 2006). The research design is explorative multiple-case studies (Yin, 2003; Eisenhardt, 1989). Data was collected through diverse sources including, semi-structured interviews, non-participant observations, internal documents, and public data. This research follows an interpretative approach, since phenomena is understood through the meanings people assign to them. The five explored SSFs were analyzed through the lenses of the management (Nonaka, 1994) and resource-based view (Penrose, 1959) perspectives. This study extends the literature examining knowledge management and knowledge organizational in SSFs seeking to generate radical innovation. We found that SSFs put in place specific management processes, to mange knowledge, and particular organizational infrastructures, to organize internally and enable management processes. By analyzing the specificities of SSFs' knowledge management and knowledge organizational and the way these and infrastructures relate to each other in each explored SSF, we created a of small radical innovating firms. We propose five ideal organization types: (1) collaborative; (2) artistic; (3) formalized; (4) synergistic; and (5) balanced. We argue that classifying small radical innovating firms into a taxonomy of ideal organizational types helps scholars and practitioners to better understand specific relationships between management processes and organizational infrastructures, and elucidate the way those relationships influence the generation process of radical innovation. What emerges from our data is that radical innovation processes in SSFs are strongly influenced by the particularities of their organizational infrastructure, management processes, and technological mainstream activities. Keywords: small firms, software industry, management processes, organizational infrastructure, breakthrough innovation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.014 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".