關鍵字搜尋意圖、涉入程度與資訊搜尋行為對廣告效果的影響－以Google Adwords為例
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Focus on marketing strategy digital age, most commonly used in the virtual environment than Internet advertising, according to Digital Marketing Franchise Association statistics, in 2013 the first half of Taiwan's overall Internet advertising market reached 6.265 billion, according to Worldstream another survey, from the third quarter of 2010 to the second quarter of 2011 were within a year's time, Google (Google) revenues of $ 33.3 billion, of which 97% are from the Google AdWords keyword advertising as the main source of income has become the most popular network one ad. In this study, we used the price effect concept proposed by Monroe and Krishnan (1985) to explore whether consumers were influenced by relevant variables. We used keyword search intentions, information searching behavior, involvement degrees, and advertising effect variables to develop a framework for the study. Based on the Google search engine, we explored whether the effects of keyword advertising on the Internet were influenced by the consumers' degree of involvement, and whether keyword search intentions increased the degree of consumer involvement, which eventually influences the effects of advertising. The research results showed that based on the empirical data of 356 valid questionnaires, the intensity of keyword search intentions positively affected information searching behaviors. In addition, the degrees of advertisement involvement positively affected information searching behaviors and advertising effects. The intensity of information searching behaviors also positively affected advertising effects, which supported the research hypothesis. We suggest that enterprises or manufacturers use keyword advertising frequently and enhance the layouts of their advertisements to increase the amount of sales generated through online marketing.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.046 |
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 it