A Research on the Comparison of the Effect of Benefits Obtained from Social Media Marketing to Brand Commitment in Terms of Domestic and Foreign Consumers
Bibliographic record
Abstract
Nowadays businesses make enormous effort be one step ahead of their rivals and therefore, they evaluate every innovation to gain advantage in the rivalry. Lately, the lead of the new rivalry tools is social media. The utility of social media, that has an increasing amount of users, provides important gains for businesses. While it provides important advantages to manage this new environment well, mistakes could cause unrecoverable consequences. Therefore, businesses who want to have a place on social media have to know the methods of reaching the target markets and the strategies to use in this environment. In this context, target groups, especially on social media, should be determined wisely and it is important to use right social media tools for the target market. In addition, to know the benefits that target market gains from social media marketing helps for meeting the needs and claims in a better way. In this research, it is aimed to investigate the effect of the benefits that consumers gain from social media marketing on brand commitment. Accordingly with this aim, domestic and foreign consumers of a hotel that offers an all-inclusive service in tourism sector have been taken under the scope of this research. The research has been implemented on 385 domestic and 385 foreign consumers that follow the Facebook page of the hotel. For the analysis of data, methods of average, frequency distribution, reliability analysis, confirmatory factor analysis and structural equation modelling have been used. As a result of these analyses, it is seen that hedonic and monetary benefits affect community participation in regards of domestic consumers, while functional, social and monetary benefits affects community participation in terms of foreign consumers.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".