Investigating social media influencer attributes on attitude and intention towards pro-environmental awareness marketing campaign: the moderating effect of issue involvement / Siti Fatimah Lailatul Qadrina Awang
Bibliographic record
Abstract
The advertising preferences have changed, putting massive pressure on marketers to create impactful advertising sources. With the advent of social media penetration today, the entire mechanism and ideology experienced a transformation. Social media influencer medium has become the digital world's sensation during the new wave of transition. According to a Google analysis in the first quarter of 2020, internet searches for 'How to live a sustainable lifestyle' surged by approximately 4,550 per cent. Consequently, the millennials are reported as the most relevant generation to embrace the more substantial concern of interacting with social media, which is also seen as a generic group that emphasizes becoming more pro-environmental in their lifestyle. Hence, in response to this issue, the focus of this research dissertation is to determine the impact of social media influencer attributes on millennials' intentions to engage in pro-environmental behaviour in Kota Kinabalu. This dissertation established four social media influencer qualities that were expected to have an impact on pro-environmental attitudes. Furthermore, the issue of involvement was believed to moderate the association between the four attributes and the individual's pro-environmental attitude in this study. The effect of pro-environmental attitude in mediating the relationship between social media influencer attributes and pro-environmental behaviour intention was also investigated. A quantitative approach was conducted using a set of questionnaires that were distributed among the millennials in Kota Kinabalu, Sabah. The research model was further analysed using the Partial Least Square-Structural Equation Modelling (PLS-SEM) technique. Based on the research questions, four core findings have been derived as follows: 1) source credibility, source attractiveness and SMI -meaning transfer significantly influenced the attitude towards pro-environmental; on the other hand, SMI-cause congruence was insignificant to the attitude towards pro-environmental 2) as a mediating variable, attitude mediated the relationship between source credibility, SMI-meaning transfer with intention towards pro-environmental behaviour. Contrastingly, source attractiveness and SMI meaning transfer demonstrated an insignificant influence when tested indirectly through attitude as a mediating variable. In this study, issue involvement played a significant role in strengthening the relationship between source credibility and attitude. This dissertation contributes the relevant empirical evidence, which indicates that the social media influencer’s attributes play a significant role in influencing social/ awareness marketing. Industry practitioners are encouraged to adopt this research framework in developing a model that can provide a comprehensive guideline on the importance of selecting the crucial attributes to achieve the success of the social/ awareness campaign. An in-depth review of the implications, limitations and future studies will be further discussed.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.005 | 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".