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Record W2522198449 · doi:10.5539/ass.v12n10p180

The Role of Personal Values and Perceived Social Support in Developing Socially Responsible Consumer Behavior

2016· article· en· W2522198449 on OpenAlexvenueno aff
İmran Ali, Saud Mandurah

Bibliographic record

VenueAsian Social Science · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate social responsibilitySocial responsibilityStructural equation modelingPsychologySocial psychologyConsumer behaviourMarketingPublic relationsBusinessPolitical science

Abstract

fetched live from OpenAlex

Corporate social responsibility (CSR) is a longstanding theme in marketing research. Although plenty of research have been done to examine the influence of CSR activities on consumer behavior, less attention is paid to explore the psychological factors that shape consumer’s socially responsible behavior (SRB). The current research addresses this gap by reviewing and comparing the literature from psychology and marketing streams that moves towards a degree of convergence. It examines the psychological role of personal values and external factors like perceived social support to build pro-social behavior among consumers. The personal values include; self-transcendence and self-enhancement values and perceived social support by social network in shaping consumer’s socially responsible behavior. The study proposed and tested the theoretical model using Structural Equation Model (SEM) technique. Data is collected through self-administered survey from 450 consumers in Pakistan. The study found that higher self-transcendence values leads to higher level of socially responsible behavior among consumers. Whereas self-enhancement values has negative influence on consumers in adopting socially responsible behavior. The social networks including; parents, friends/peers, teachers’ play important role in development of socially responsible behavior among consumers as individuals tend to pay focus on the recommendations of their members in their social networks. The findings of this study provide important recommendations to the corporate policy makers to ensure sustainable organizational performance in today’s competitive business environment.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.744
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.289
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2016
Admission routes1
Has abstractyes

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