Bibliographic record
Abstract
The rapid convergence of collaborative technologies, democratisation of digital communication and consumerisation of Smart Grid infrastructure (i.e.: smart metering and distribution substation automation) have faltered the efficacy of centralised command-and-control and its insular sub-culture. For complex firms in today's creative economy, this infers that management innovation (MI)??an induced managerial capacity to search for novel ways to create value?, is rapidly becoming liabilities unless it is innovatively managed for overcoming the inertia of discontinuity opportunities.The raison d'�tre of this thesis is to investigate the generative managerial processes through which MI can be fostered for experimentation and innovatively managed for acceleration. It comprises four qualitative case studies that involved in-depth interviews, surveys, public records and archival documentaries of four Canadian energy and utilities organisations. The conclusions are fascinating both expected and unanticipated. I found that many, if not most, of the contemporaneous routines of pyramidal target-setting and benchmark-driven cultures are ubiquitously evident. Business planning and risk management still function, albeit the objects of those tenets are different. These quasi-objects include, but are not limited to, organic structures, web-enabled paradigm, pragmatic mindset of middle-down-up crowdsourcing and fragmented evaluation of efforts to evoke the innovative management of management innovation (IMMI). Further adjacent to the quest for driving renewed growth, a new governing dynamic is hinging upon the IMMI that forges a pattern for resiliency and sustainability. Managers capitalise on the epistemic IMMI to regain competitive advantage while enduring endogenous fiefdoms and exogenous disruptions. They catalyse information semantically, harness collective capability effectively, stage prolifically faster MI experimentations and accelerate the cycle of MI more pervasively. I henceforth propose a unified managerial process, dubbed the Cloverleaf 4S Model (Strategise?Synchronise?Steward?Sustain). Implicit in this approach, managers believe that their finely-tailored practices epitomise an evolutionary process of deliberate selection in the pursuit for distinctive MI capabilities and expanding authority dynamics in the managership. This allows for self-adaptive mechanisms shifting from silos to swarming as well as the indigenous aspects of IMMI practices?exaptation, cognitive flexibility, speed to adaptation and executional excellence. The implication of this study presents heuristical insights to managers in galvanising perennial innovation and unlocking their IMMI to build an agile, intelligent enterprise.
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.
How this classification was reachedexpand
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 | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".