Consumption behavior of Chinese urban residents during economic transition
Bibliographic record
Abstract
Purpose The paper aims to examine the consumption behavior of Chinese residents during economic transition. It explores whether Western theories of consumption are applicable to the Chinese situation, and then tests the hypothesis based on Chinese traditional culture and dynamic nature of system change. Design/methodology/approach The paper opted for an empirical‐based approach. A regression model was used to analyze annual consumption data from 1986 to 2008 in China. Findings The paper provides empirical insights and suggests that under the influence of Chinese traditional culture and dynamic change of the Chinese economic system, Chinese urban residents exhibit a special consumption pattern of an intermittent and cyclical nature. Research limitations/implications The paper concludes that in order to make the consumption stimulation policy in China more effective, it is necessary to establish a series of measures such as establishing a sound social welfare system as well as narrowing the gap between the rich and the poor, which will substantially increase the buying power of the less‐privileged groups and thus will increase the overall spending in the society. Although the econometric model used in this paper is adequate, a different approach like time series econometrics may give us additional insights. Researchers are encouraged to test the hypothesis further by employing other methodologies. Second, due to the lack of its own theories in the emerging market, this study remains exploratory. Originality/value This paper fulfils an identified need to study the special consumption behavior of Chinese urban residents during the economic transition.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".