The importance of trust for electronic commerce satisfaction: an entrepreneurial perspective
Bibliographic record
Abstract
Purpose Social commerce has seen a prosperous growth following the rise of social media, in particular, social networking sites have established novel ways to communicate and transact between firms and people. The rise of new technologies has also directed to changes in how entrepreneurs convey their business. Despite intensive social commerce research, the challenges of social commerce for entrepreneurs have attracted less attention and especially neglected the role of trust and satisfaction in electronic commerce. Design/methodology/approach This research use a survey to collect data. The authors use structural equation modeling-partial least square (SEM-PLS) to analysis the data. This quantitative research provides new insights in the food industry. Findings This research thus provides insights into social commerce by analyzing the role of trust in the relationship between customers' social media activities and customers' satisfaction. The present study finds a mediating effect of trust in developing satisfaction. Social media activities facilitate a positive level of trust that in turn creates a satisfying environment for customers in social commerce. The research provides theoretical and practical implications at the end of the study. Originality/value The findings provide good knowledge for the food industry to stay connected with customers and develop their satisfaction.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".