Bibliographic record
Abstract
Purpose Despite evidence that cashless payment modes influence spending behavior, researchers have yet to explain the underlying mechanism. Cash serves as a store of value, and transactions involve the transference of ownership in circulation. This study aims to unpack why the physical and visceral nature of cash embodies psychological ownership and how the physicality of cash attenuates the awareness of spending, curtailing instinctive and unnecessary spending. Design/methodology/approach Drawing on data collected in 2013 in New Zealand, the authors conducted another study in the quite different context of China in September 2023, using identical semistructured discussion protocols. The data from 2013 involved five focus group sessions containing at least six participants, involving 31 adults who also completed an open-ended questionnaire immediately before the group discussion commenced. The data collection in 2023 used the same open-ended and semistructured discussion protocol used in 2013, resulting in 180 adult open-ended responses – a nonprobability criterion-based purposive sampling guided participant selection in the 2013 and 2023 studies. Findings Findings reveal that psychological ownership does manifest in the app more than in the ownership of money itself. People felt happy, confident, safe and secure while using apps that stored their money. Physical attributes of cash result from sensory perceptions of handling, counting and touching cash and coins. A sense of psychological ownership heightens spending awareness and ramifies spending behavior. The research found sadness and guilt as negative emotions when parting with money. Originality/value This study offers empirical support to explain why psychological ownership of cash regulates spending and why the psychological processes that underlie “owned” money interrupt the spending with cash.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".