Bibliographic record
Abstract
ABSTRACTInnovation has been referred to as the process by which value enhancement is planned and achieved for the benefit of society. Industrial innovation is comprised of several factors which constitute the input, process, and output dimensions of the innovation process. Industrial innovation has been assessed via several indices and primarily by patents and research and development (RD Eveleens, 2010; Greer and Lei, 2011). Innovation has been defined as a '... process by which varying degrees of measurable value enhancement is planned and achieved, in any commercial activity' Knowledge 2007: 6). This process which may be breakthrough or incremental, and it can occur systematically or sporadically in an organization. The innovation process can be achieved by: (a) the introduction of new or improved goods or services, (b) the implementation of new or improved operational processes, or (c) the implementation of new or improved organizational and administrative processes. The final outcome can result in the improvement of market share, competitiveness, and the quality of the product/services that are produced by an organization. An associated benefit of the innovation process can be reduction in costs.In this paper, we focus on the status of innovation in India. We assess innovation using two metrics drawn from the literature: patents and R&D intensity. We cite reports which have used these metrics for analyzing the extent of innovativeness of various Indian sectors such as in drug and pharmaceutical sector, manufacturing sector. We argue that the results indicate that India is lagging behind many developed and developing nations in terms of successful innovation. We develop new measures which we argue can be helpful for identifying suitable policy interventions which can, in turn, enhance the dissemination of the value of innovation at all levels of a society. In India, most research and educational programs are carried out by the government through its various institutes, universities and public sector organizations. It is therefore imperative that the government and its institutions take an active role in improving India's innovativeness. Appropriate policies and programs to address these issues are identified in this paper, developed and implemented by the government in conjunction with industry and academia which can contribute to an ecosystem conducive to innovation in India.Innovation in IndiaIndustrial innovation includes new products, processes, operations, marketing and sales techniques, manpower management, resource allocation, and the development of new specific know-how etc. (National Knowledge Commission, 2007). Each of these types of innovations alone or in combination represents areas where an organization can innovate in order to achieve competitive advantage. …
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 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 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".