Managing innovation in a knowledge intensive technology organisation (KITO)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study aims to add to the existing knowledge of how innovation works in organisations. By understanding how to assess/evaluate processes that support and enable innovation, managers can better manage innovation as a business process. This paper addresses elements of organisational behaviour that relate to people management where innovation and technology management is concerned. Perception plays a crucial role in driving behaviour and therefore the widely accepted business scorecard methodology has been used to measure innovation practices in the organisation. The research was done in a knowledge intensive technology organisation (KITO) in South Africa. Interviews with managers of R&D were conducted. These interviews were used to adapt an existing audit instrument to suit the technology–based organisation. Thereafter, a comprehensive audit of innovation was conducted at three different management levels using the adapted instrument. Over 100, mostly R&D managers, were asked to complete a scorecard–based questionnaire and to draw a visual representation (VR) of innovation. The results of the interviews, audit and VRs were used to produce a management framework that is not only applicable to a KITO, but can also be used widely to improve innovation through enhanced visual understanding of any technology–based organisation. The results of the study indicate that measuring innovation through a validated instrument is highly valuable. The Holistic System Framework for innovation and the measurement instrument facilitated (1) management of, and (2) organisational learning about innovation. The comprehensive audit indicated, on a strategic level, the strengths and weaknesses of the innovation process as practised in the organisation. The instrument is valuable at a strategic management level as it indicates where in the organisation the gaps exist regarding the management of the process of innovation with the aim to create a competitive advantage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it