The effect of perceived usefulness, perceived ease of use, and lifestyle on purchase intention
Bibliographic record
Abstract
Purpose-Advances in digital technology impact various business activities, such as digital marketing through e-commerce. Digital marketing through e-commerce can expand consumer reach while reducing business operating costs. In digital marketing, each seller will try to attract consumers to buy their products. Many factors certainly influence consumer intention to buy. Therefore, this study aims to determine the effect of perceived usefulness, perceived ease of use, and lifestyle on purchasing intentions in e-commerce users. Design/Methodology/Approach-This study's population consisted of all e-commerce users in Asia, and the sample obtained was 100 people selected based on specific criteria. The data was collected by distributing questionnaires online and measuring them using a Likert scale. The data obtained from respondents was then processed using SPSS software. Findings-Based on the test results, perceived usefulness, perceived ease of use, and lifestyle positively affect the purchase intention of e-commerce users. The perceived usefulness of this study has proven to be positive but insignificant to consumer purchase intentions. This means that perceived usefulness only partially encourages consumer buying intentions because other factors highly influence buying intentions, such as perceived ease of use, lifestyle, and other factors not examined in this study. Research limitations/implications-This research is limited in that the respondents' sample only represents e-commerce users in Asia, so the respondents' answers cannot represent all e-commerce users worldwide. In addition, e-commerce currently circulating is diverse, and this research has not discussed specific e-commerce users, so future research is expected to use specific e-commerce user respondents. Originality/value-Research on the factors that influence purchase intention through e-commerce in Asia still needs to be improved. This research discusses e-commerce users in the Asian region by considering the aspects of perceived usefulness, perceived ease of use, and lifestyle.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".