Global consumer culture and national identity as drivers of materialism: an international study of convergence and divergence
Bibliographic record
Abstract
Purpose This paper studies the sociocultural drivers of materialism cross-culturally. Research in this area is scarce, even though rapid social transformations worldwide, fueled by globalization, make it imperative to identify the conditions under which commonalities and differences in materialistic tendencies are most likely to evidence among consumers as they seek to assert, restore, or enhance their self-concept and status in the context of global consumption trends. Design/methodology/approach The psychographic determinants of materialism were rigorously validated across a diverse set of eight countries, by investigating which facets of acculturation to global consumer culture and national ethnic identity, along with consumer ethnocentrism, encourage or repel materialism. Using multigroup SEM and other analyses, the authors confirmed construct dimensionality and ascertained the stability of the relationships. Findings The most consistent positive drivers of materialism were self-identification with global consumer culture and exposure to American-based global mass media. The results demonstrated the compatibility of national identity and traditions with materialistic tendencies. Materialism was positively related to or independent of consumer ethnocentrism. Research limitations/implications The findings offer consequential insights for both research and practice, although the cross-sectional character of survey research and certain sampling characteristics limit their generalizability. Practical implications The results pinpoint segments that spill over national boundaries, and those that remain geographically constrained, thus providing guidance for marketing and communication strategies to practitioners. Social implications The authors shed light on two widely held yet insufficiently researched assumptions: that the homogenizing effect of global consumer culture may be fomenting materialism worldwide, and that nationalistic, parochially oriented consumers may be more capable of resisting materialistic values. Originality/value The study design addresses several shortcomings of prior research, and its findings advance the understanding of materialism and its antecedents by identifying the conditions driving materialistic tendencies.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| 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".