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Journal ArticleDOI

Influencer Marketing: How Message Value and Credibility Affect Consumer Trust of Branded Content on Social Media

12 Feb 2019-Journal of Interactive Advertising (Routledge)-Vol. 19, Iss: 1, pp 58-73
TL;DR: In this paper, preliminary research involves preliminary research to understand the mechanism by which influencer marketing affects the effectiveness of influencer campaigns, and the results show that the effect of influencers' marketing on the performance of online advertising has been studied.
Abstract: In the past few years, expenditure on influencer marketing has grown exponentially. The present study involves preliminary research to understand the mechanism by which influencer marketing affects...
Citations
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Journal ArticleDOI
TL;DR: A strong association between streamers’ health disclosures and public awareness regarding depression is demonstrated, extending previous studies around celebrity influencers as a promising opportunity for reducing social stigma around mental health discussions.
Abstract: Celebrities’ self-disclosures about their mental health issues can enhance public awareness of mental illness such as depression. As online live streaming becomes a popular choice for media enterta...

18 citations


Cites background from "Influencer Marketing: How Message V..."

  • ...Marketers and advertisers have experimented with ways to tap into their influence for brand building and to promote purchases (Lou & Yuan, 2019)....

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Journal ArticleDOI
TL;DR: In this article , the authors analyzed data from a survey of 411 consumers using partial least squares-structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) to understand the net and combined effects of content attributes, interaction strategies and parasocial relationships on purchase intention.
Abstract: PurposeThe emergence of social media has brought the influencer marketing landscape to an unprecedented level, where many ordinary people are turning into social media influencers. The study aims to construct and validate a model to yield strategic insights on the relevance of content curation, influencer–fans interaction and parasocial relationships development in fostering favorable endorsement outcomes (i.e. purchase intention).Design/methodology/approachThe present study analyzes data from a survey of 411 consumers using partial least squares-structural equation modelling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) to understand the net and combined effects of content attributes, interaction strategies and parasocial relationships on purchase intention.FindingsPLS-SEM results reveal that content attributes (i.e. prestige and expertise) and interaction strategies (i.e. interactivity and self-disclosure) positively influence parasocial relationships, and in turn, lead to high purchase intention. Findings from fsQCA indicate six solutions with different combinations of content attributes, interaction strategies and parasocial relationships that sufficiently explain high purchase intention.Originality/valueThe present study demonstrates the roles of content attributes and interaction strategies in engendering parasocial relationship and the endorsement outcome (i.e. purchase intention) from both linear and non-linear (complexity) perspectives.

17 citations

Journal ArticleDOI
TL;DR: In this paper , the authors investigated perceptions about online content attractiveness, interactive engagement and real-time conversation capabilities through travel and tourism social media groups, and found that Facebook subscribers were drawn to those groups that featured aesthetically pleasing content and to the ones that facilitated their engagement.

17 citations

Journal ArticleDOI
TL;DR: This paper examined consumer responses to empowerment hashtags in social media-based fashion advertising and found that consumers showed more favora cation for empowerment than women empowerment in fashion advertising, compared to men empowerment.
Abstract: Through two studies, this research examined consumer responses to empowerment hashtags in social media–based fashion advertising. The findings of Study 1 indicated that consumers showed more favora...

17 citations

Journal ArticleDOI
TL;DR: The authors investigated how experiences of using augmented reality, artificial intelligence-enabled chatbots, and social media when interacting with beauty brands affect body image, self-esteem, and purchase behavior among female consumers in Generation Z.
Abstract: Research is needed to identify novel ways to influence Generation Z female consumers' behavior when they interact with various technologies. This study investigates how experiences of using augmented reality, artificial intelligence-enabled chatbots, and social media when interacting with beauty brands affect body image, self-esteem, and purchase behavior among female consumers in Generation Z. Through three studies, we propose and test a model drawing on social comparison theory. In Study 1, a survey was completed by Generation Z women (n = 1118). In Study 2 and Study 3, two laboratory experiments were conducted with Generation Z women in Malaysia (n = 250 and n = 200). We show that (1) Generation Z women's perceived augmentation positively affects their body image, self-esteem, and actual purchase behavior; (2) although trust in social media celebrities positively affects Generation Z women's body image and self-esteem, the addictive use of social media does not have significant effects; (3) the chatbot support type (assistant vs. friend) has a significant impact on these women's experience; and (4) brand attachment, reputation, and awareness do not have significant effects. This article provides important implications for theory and practice on the behavior of Generation Z females when interacting with various technologies.

17 citations

References
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Journal ArticleDOI
01 Jan 1973
TL;DR: In this paper, a six-step framework for organizing and discussing multivariate data analysis techniques with flowcharts for each is presented, focusing on the use of each technique, rather than its mathematical derivation.
Abstract: Offers an applications-oriented approach to multivariate data analysis, focusing on the use of each technique, rather than its mathematical derivation. The text introduces a six-step framework for organizing and discussing techniques with flowcharts for each. Well-suited for the non-statistician, this applications-oriented introduction to multivariate analysis focuses on the fundamental concepts that affect the use of specific techniques rather than the mathematical derivation of the technique. Provides an overview of several techniques and approaches that are available to analysts today - e.g., data warehousing and data mining, neural networks and resampling/bootstrapping. Chapters are organized to provide a practical, logical progression of the phases of analysis and to group similar types of techniques applicable to most situations. Table of Contents 1. Introduction. I. PREPARING FOR A MULTIVARIATE ANALYSIS. 2. Examining Your Data. 3. Factor Analysis. II. DEPENDENCE TECHNIQUES. 4. Multiple Regression. 5. Multiple Discriminant Analysis and Logistic Regression. 6. Multivariate Analysis of Variance. 7. Conjoint Analysis. 8. Canonical Correlation Analysis. III. INTERDEPENDENCE TECHNIQUES. 9. Cluster Analysis. 10. Multidimensional Scaling. IV. ADVANCED AND EMERGING TECHNIQUES. 11. Structural Equation Modeling. 12. Emerging Techniques in Multivariate Analysis. Appendix A: Applications of Multivariate Data Analysis. Index.

37,124 citations

Journal ArticleDOI
TL;DR: This chapter discusses Structural Equation Modeling: An Introduction, and SEM: Confirmatory Factor Analysis, and Testing A Structural Model, which shows how the model can be modified for different data types.
Abstract: I Introduction 1 Introduction II Preparing For a MV Analysis 2 Examining Your Data 3 Factor Analysis III Dependence Techniques 4 Multiple Regression Analysis 5 Multiple Discriminate Analysis and Logistic Regression 6 Multivariate Analysis of Variance 7 Conjoint Analysis IV Interdependence Techniques 8 Cluster Analysis 9 Multidimensional Scaling and Correspondence Analysis V Moving Beyond the Basic Techniques 10 Structural Equation Modeling: Overview 10a Appendix -- SEM 11 CFA: Confirmatory Factor Analysis 11a Appendix -- CFA 12 SEM: Testing A Structural Model 12a Appendix -- SEM APPENDIX A Basic Stats

23,353 citations

Journal ArticleDOI
TL;DR: Relationship marketing, established, developing, and maintaining successful relational exchanges, constitutes a major shift in marketing theory and practice as mentioned in this paper, after conceptualizing relationship relationships as a set of relationships.
Abstract: Relationship marketing—establishing, developing, and maintaining successful relational exchanges—constitutes a major shift in marketing theory and practice. After conceptualizing relationship marke...

19,920 citations

Book
01 Jan 2014
TL;DR: The Second Edition of this practical guide to partial least squares structural equation modeling is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.
Abstract: With applications using SmartPLS (www.smartpls.com)—the primary software used in partial least squares structural equation modeling (PLS-SEM)—this practical guide provides concise instructions on how to use this evolving statistical technique to conduct research and obtain solutions. Featuring the latest research, new examples, and expanded discussions throughout, the Second Edition is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.

13,621 citations


"Influencer Marketing: How Message V..." refers background or methods in this paper

  • ...A collinearity assessment showed no significant levels of collinearity between any sets of predicting variables (with variance inflation factor [VIF] falling between tolerance range .20 and 5.0) (Hair et al. 2014)....

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  • ...Conversely, PLS-SEM estimates model parameters in a way that maximizes the variance explained in endogenous variables and is preferred for research aimed at theory development and prediction (Hair et al. 2014, p. 14)....

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  • ...CB-SEM uses a maximum likelihood estimation (MLE) procedure to estimate model coefficients “so that the discrepancy between the estimated and sample covariance matrices is minimized” (Hair et al. 2014, p. 27)....

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  • ...The latent variables in the current model all have reflective measurements: indicators which predict one particular construct and which are highly correlated to one another and represent the effects of the latent construct (Hair et al. 2014, p. 43)....

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Posted Content
TL;DR: An evaluation of double-blind reviewed journals through important academic publishing databases revealed that more than 30 academic articles in the domain of international marketing (in a broad sense) used PLS path modeling as means of statistical analysis.
Abstract: Purpose: This paper discusses partial least squares path modeling (PLS), a powerful structural equation modeling technique for research on international marketing. While a significant body of research provides guidance for the use of covariance-based structural equation modeling (CBSEM) in international marketing, there are no subject-specific guidelines for the use of PLS so far.Methodology/approach: A literature review of the use of PLS in international marketing reveals the increasing application of this methodology.Findings: This paper reveals the strengths and weaknesses of PLS in the context of research on international marketing, and provides guidance for multi-group analysis.Originality/value of paper: The paper assists researchers in making well-grounded decisions regarding the application of PLS in certain research situations and provides specific implications for an appropriate application of the methodology.

7,536 citations


"Influencer Marketing: How Message V..." refers methods in this paper

  • ...PLS path modeling is also recommended over CBSEM for testing complex models with many latent variables (Henseler, Ringle, and Sinkovics 2009)....

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  • ...Then we performed a second bootstrapping analysis, specifying 5,000 subsamples and a 95% significance level, to obtain each path coefficient’s standard error and p value (Henseler, Ringle, and Sinkovics 2009) (Table 3)....

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Trending Questions (2)
How message value and credibility affect consumer trust of branded content on social media?

The paper states that the informative and entertainment value of influencer-generated posts, along with influencers' credibility components, positively affect followers' trust in influencer-generated branded posts.

When users pay close attention to influencer content, they tend to have greater recall and trust?

Yes, when users pay close attention to influencer content, they are more likely to have greater recall and trust.