A Comparison of the Online Shopping Behavior Patterns of Consumer Groups with Different Online Shopping Experiences
Bibliographic record
Abstract
The appearance of Internet does not only bring changes to consumption patterns, but also to the business modes of companies, as a result of which Internet has become a perfect sales channel. When a consumer shops online, s/he might be influenced by a huge variety of factors. In this study, ABC model of attitude was adopted to investigate empirically the influences of website characteristics and external stimulus on consumers’ online shopping behavior. A relationship model was also established to compare the differences of consumer groups with different online shopping experiences.Using convenience sampling, a total of 818 valid questionnaires were collected for the purpose of this study. Based on their online shopping experiences, consumers were divided into high frequency and low frequency groups in order to compare their consumption patterns as a group. According to the results, the two groups with different online shopping experiences were significantly different in three relational paths. To be specific: (1) Compared to the low frequency group, consumers in the high frequency group is more significantly positively influenced by website characteristics along the affection path during their online shopping. (2) Compared to the high frequency group, consumers in the low frequency group are more significantly positively influenced by website characteristics along the attitude path during their online shopping. (3) Compared with the low frequency group, a more significant positive influence is found among consumers in the high frequency group between consumer affection and consumer behavior path. These differences in the consumer behavior patterns of groups with different online shopping experiences according to the research results, therefore, could be used as references for online shopping business owners in their formulation of strategies.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".