Barriers to radical process innovation: a case of environmental technology in the oil industry
Bibliographic record
Abstract
Purpose While a radical innovation can be embedded in new products or new processes, most studies to date have concentrated on barriers to radical product innovations, with little insights available about the challenges for implementation of radical process innovations. Design/methodology/approach We theorize a set of barriers to radical process innovation based on a critical case study of an oil company. Our study employs data from 14 semi-structured interviews, one complete participant-observer in the process and access to all corporate documentation. The organization being studied was eventually unable to bring the new process technology to commercialization despite the technology having both technical feasibility and substantive cost savings potential. Findings We identify five groups of challenges that the company faced: (1) challenges in resource mobilization, (2) challenges in piloting strategy, (3) innovation leadership tensions, (4) tensions in managing shareholders' expectations and (5) product-process innovation tension (i.e. a unique situation when a company implementing a radical process innovation and simultaneously pursues the path to commercialize it as a product innovation). Practical implications Sustainable development is one of the major challenges in our era. Process innovations are crucial for achieving sustainability without changing the final product. By providing a list of challenges that executives face in the process of commercializing a radical process innovation, we can help them to achieve sustainability more effectively. Originality/value The paper responds to the call to increase our understanding of radical process innovations by utilizing a unique ethnographic research methodology of active participant-observation complemented by independent third-party face-to-face interviews.
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.012 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| 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".