The influence of spirituality, ethics and religiosity on green buying behavior: a cross-cultural study of Chinese and Pakistani consumers
Bibliographic record
Abstract
Purpose The purpose of this study is to investigate the relationship between spirituality, ethics, and intrinsic and extrinsic religiosity as antecedents of green buying behavior, addressing a gap in the literature despite increasing sustainability challenges faced by Pakistan and China. Design/methodology/approach This research has developed a conceptual model based on the value belief norm (VBN) theory, examining the effects of religiosity, ethics and spirituality on the green buying behavior of Chinese and Pakistani consumers. The enumerators collected 415 valid samples from China and 410 from Karachi business universities, using convenience sampling, and analyzed reliability, validity and convergent validity using smart partial least square-structural equation modelling. Findings Results suggested a significant association between ethics and green buying behavior for Chinese and Pakistani consumers. Results also indicated that both intrinsic religiosity and spirituality positively influence the green buying behavior of Chinese and Pakistani consumers. In contrast, this study found a significant association between extrinsic religiosity and green buying behavior for Pakistani consumers, but the same relationship was insignificant for Chinese consumers. Originality/value The study extends the model based on the VBN theory, moving beyond the commonly used theory of reasoned action and theory of planned behavior, thus contributing to theoretical diversity in the field.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".