A Study of e-Government Business Model with Customer Relationship Management Driven in Taiwan
Bibliographic record
Abstract
The study examined the relationship among customer relationship management (CRM) readiness, e-government (e-Gov) business model and customer equity to indicate the advisable actions on citizen-centric e-Gov business model. Based on the benchmarking concept, the study used the questionnaire to analyze the influences of CRM readiness (blueprint management, change management, human resource, process management, ICT resource) on e-Gov business model (administration innovation, customer interface, service infrastructure, resources allocation) and the effect of citizen-centric e-Gov business model through customer equity (value, brand, relationship). The results can identify the level of CRM readiness in Taiwanese leading departments/agencies and improve the service process for e-Gov business model with a CRM perspective. The study found that: 1. Governments can enhance the effects of e-Gov business model through CRM readiness examining. 2. The sustainable customer equity can be transformed through e-Gov business model. 3. CRM participation and experience sharing could be broadened through the mechanisms of life-long learning for public servants further.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".