An empirical study of the anticipated consumer response to RFID product item tagging
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose This empirical study of consumer/shopper response to radio frequency identification (RFID) product item tagging anticipates what is likely to take place in the retail marketplace. Using the theories of procedural justice/fairness, expected utility, and prior literature on personal privacy the purpose of this study is to use the survey method to measure consumer willingness to purchase RFID‐tagged product items within the Canadian context. Procedural justice/fairness is operationalized using the implementation of the Personal Information Protection and Electronic Documents Act (PIPEDA) enacted in Canada on January 1, 2004. Design/methodology/approach This study used the survey questionnaire method after the sample participants ( N =381) were exposed to an experimental treatment. Students and faculty members of the Faculty of Business Administration, University of New Brunswick Fredericton, Canada participated in this study. Findings Consumers responded positively to the procedural justice concept using PIPEDA law in Canada. The less privacy sensitive group valued the specific RFID benefits, was willing to buy the tagged items to obtain specific benefits, was willing to pay more for these items, and was also less concerned about selected RFID issues. Practical implications Practical suggestions are given to retailers thinking of implementing product item RFID tagging to make their initiatives more successful. Originality/value This is one of the first empirical studies on the likely consumer response to product item tagging based on solid theoretical foundations.
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.
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 | 0.013 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 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 it