Impacto das Dimensões Culturais na Confiança Online: Um Estudo Cross-Cultural
Bibliographic record
Abstract
Studies suggest that online trust is fostered by the perception of its antecedents, such as the ability of the online seller, his demonstrations of benevolence, the security system of his website, the presence of seals from external regulators and the perception of the competence of the sales system. These predictors of online trust can be perceived differently among consumers of different countries, influenced by cultural values related to their country. It is proposed that cultural dimensions, specifically individualism versus collectivism and uncertainty avoidance, may, even indirectly, influence the development of trust between consumers and online retailers. Using theoretical framework of Hofstede (2001) and others scholars (JARVENPAA; TRACKTINSKY, 1999; LEE; TURBAN, 2001; CHOI; GEISTFELD, 2004; AN; KIM, 2008 among others), the survey was conducted in Fortaleza (Brazil) and Montreal (Canada), between 2011 Q3 and 2012 Q1. A survey was implemented using scales validated by previous researches. A descriptive data analysis was carried, as well as the assembly of a multiple linear regression model with online trust as the dependent variable. The results indicated rejection of assumptions about the appreciation of the Brazilian public by characteristics of benevolence from online vendors compared to the Canadian public, as well as rejection of assumption appreciation of Canadians on Brazilian relating to the perception of the competence of sales systems and guarantees verified by third parties in online stores. The results also suggested the statement of the assumptions made about the predilection of Canadians over the Brazilians in relation to the perception of the abilities of online retailers as well as the statement of the assumptions that Brazilian indicative attribute more importance to security of online systems, compared to the Canadian public. The study shows that culture affects the perception of consumers in collectivist and low uncertainty avoidance on the security system sales, while acting on the perception of consumer’s individualistic profile and low uncertainty avoidance in relation to individual abilities of online retailers.
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 | 0.011 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".