Effects of social media brand-related content on fashion products buying behaviour – a moderated mediation model

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Abstract

Purpose

This study aims to examine in which circumstances consumer’s self-congruity moderates the indirect influence of consumer-based brand equity (mediating role) in the relationship between firm-created and user-generated social media content and intention to purchase fashion products.

Design/methodology/approach

In this study, the authors carried out an online survey with social media users of fashion brands and collected data from 622 participants across two samples to investigate whether consumers’ perceptions of equity of fashion brands mediate the relationship between social media brand-related communication created by both firms and users and the intention to buy the fashion brands. The indirect relationship is further moderated by self-congruity.

Findings

The results indicate that brand equity mediates the relationship between social media communication and purchase intentions of fashion products, and self-congruity moderates the relationship between social media communication types and purchase intentions, such that higher/lower levels of self-congruity strengthen/weaken the impact of social media communication on purchase intentions.

Originality/value

This study contributes to the business and marketing literature by exploring how social media communication, branding and fashion align with the individual’s self-concept and buying behaviour.

Related collections

Most cited references 102

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Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

Franz Faul, Edgar Erdfelder, Axel Buchner … (2009)

G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

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The relative trustworthiness of inferential tests of the indirect effect in statistical mediation analysis: does method really matter?

Joseph Hayes, Michael Scharkow (2013)

A content analysis of 2 years of Psychological Science articles reveals inconsistencies in how researchers make inferences about indirect effects when conducting a statistical mediation analysis. In this study, we examined the frequency with which popularly used tests disagree, whether the method an investigator uses makes a difference in the conclusion he or she will reach, and whether there is a most trustworthy test that can be recommended to balance practical and performance considerations. We found that tests agree much more frequently than they disagree, but disagreements are more common when an indirect effect exists than when it does not. We recommend the bias-corrected bootstrap confidence interval as the most trustworthy test if power is of utmost concern, although it can be slightly liberal in some circumstances. Investigators concerned about Type I errors should choose the Monte Carlo confidence interval or the distribution-of-the-product approach, which rarely disagree. The percentile bootstrap confidence interval is a good compromise test.