A New Policy-Making Model for Development of National Insurance Services Market Based on Resource-Based Approach
Bibliographic record
Abstract
Insurance industry is one of those industries providing financial services for people that couldn’t achieve a balanced development in provision of different services. In other words, insurance companies didn’t have a favorable performance as compared with other countries, except for provision of services for automobile industry. This actually pinpoints that the conditions for development and penetration into this market is not that much optimal. The main objective of this study is to provide a policy-making model for the development of service market under the light of a resource-based approach and investigation of model relations. The research method applied in this study is qualitative and it follows an applied objective. The population for this study are specified to the development of the model and interview was used to identify the criteria. The sample includes insurance companies’ managers and experts. These people have at least a bachelor’s degree and they have more than ten years of experience of managerial work. The number of experts included in this study include 20 people using saturation limit approach. The data were analyzed using grounded theory approach. The results showed that the main phenomenon was the concept of market-orientation. In addition, the causal conditions of this study include future-orientation and technological infrastructures. In intervention part of the study, dynamism of industry has been specified. In another part related to the context, culture has been identified. The identified strategies in the field of policy-making include innovativeness, entrepreneurialism, and a positive picture of the industry. Finally, the outcome of this model was the development of the market. The main suggestion of this study was to improve social culture. Besides, it will create a trusting mechanism with regard to policy-making and therefore the required atmosphere for the development and strengthening the market will be created.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 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 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".