Influencer Marketing: How Message Value and Credibility Affect Consumer Trust of Branded Content on Social Media
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...
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TL;DR: In this paper , a model of influencer marketing effectiveness is analyzed using partial least squares with data from 281 followers of social media influencers, and the authors establish influencer characteristics of popularity and attractiveness as heuristic cues that inform judgments of influencers efficacy.
Abstract:
Purpose
The continued evolution of influencer marketing has created a need to better understand influencer marketing effectiveness. With brands increasingly partnering with influencers, research is yet to provide an integrated perspective examining the critical role of both parties. This study aims to draw on the source credibility model and signaling theory to explain the mechanisms that matter in influencer marketing effectiveness.
Design/methodology/approach
The proposed model of influencer marketing effectiveness is analyzed using partial least squares with data from 281 followers of social media influencers.
Findings
The authors establish influencer characteristics of popularity and attractiveness as heuristic cues that inform judgments of influencer efficacy. Further, category involvement and altruistic motives for collaboration are shown to moderate followers’ reliance on these heuristic cues. Then, a sequential mediating effect demonstrates the critical roles of the influencer and partner brand in three desired outcomes: enhanced perception of brand authenticity, enhanced brand engagement and positive attitudes toward influencer posts.
Research limitations/implications
Future research should consider other heuristic cues that could inform influencer efficacy judgments and switch the focus toward the partner brand’s impact on such judgments.
Practical implications
A step-by-step visual framework is presented to help marketers and influencers translate these findings into key responsibilities for developing more effective and collaborative partnerships.
Originality/value
Besides presenting an integrated perspective, signaling theory provides an original lens for explaining influencer marketing effectiveness, addressing the need to expand the theoretical boundaries of influencer marketing research.
5 citations
TL;DR: In this article, the impact of the credibility, attractiveness, expertise, and trustworthiness of the phenomena on the attitude toward advertising was examined and the correlation analysis made in the study to reveal if there is a significant correlation between the credibility dimensions of attractiveness and expertise and the attitude towards advertising shows that there are significant correlations between all three dimensions and attitude toward advertisement.
Abstract: Having a huge transformation in conjunction with transition from Web 1.0 to Web 2.0, the Internet gave rise to emergence of micro-celebrities called phenomena and led the concept of influencer marketing which uses these celebrities as the basic decision makers to gain popularity among today’s marketing activities. Many studies reveal that the phenomena (influencers) acting as “senders” in online marketing activities influence their followers and activate them in desired direction. In the present study conducted in this direction, the impact of the credibility, attractiveness, expertise and trustworthiness of the phenomena on the attitude toward advertising was examined. The research was done on university students. The correlation analysis made in the study to reveal if there is a significant correlation between the credibility dimensions of attractiveness, expertise and trustworthiness of the phenomena and the attitude toward advertising shows that there are significant correlations between all three dimensions and attitude toward advertising (r=0.46, p<0.01 for attractiveness; r=0.26; p<0,01 for expertise; r=0.31; p<0,01 for trustworthiness). Furthermore, the results of the research show that only the attractiveness dimension of the phenomena among their credibility dimensions (attractiveness, expertise, trustworthiness) has a significant impact on the attitude toward advertising.
5 citations
Cites background from "Influencer Marketing: How Message V..."
...They play an active role in marketing process by creating branded contents, promoting the brands and recommending them to their followers for a certain fee paid by the companies (Lou & Yuan, 2019:58)....
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01 Jan 2022
5 citations
TL;DR: Zhang et al. as mentioned in this paper used DEMATELP-ANP to sort out the relevant influencing factors that affect consumers' shopping motivation in livestream e-commerce by reviewing previous related literature.
Abstract: With the rapid development of e-commerce in China and the global pandemic of COVID-19, more and more sales personnel and brands have abandoned the physical retail industry and started investing in e-commerce. The consumer culture of livestream e-commerce is becoming popular in China. However, a report from Southern Finance Omnimedia Corp of China pointed out that among China's top 1,000 livestream sellers, the top 20 sellers have contributed to nearly half of the gross merchandise volume (GMV), using three major Chinese streaming platforms: Taobao, Douyin, and Kuaishou. Moreover, a novice in livestream e-commerce knows less about the important impact factors of the realm. Akin to the adage, “well aware is well prepared,” knowing more about the influencing factors of livestream e-commerce more will be the chances to promote the commercial value. A benchmark research is needed to systematically trace out the most important and influencing factors and to make possible the rising of selling with less effort, hence this study. The research intends to sort out the relevant influencing factors that affect consumers’ shopping motivation in livestream e-commerce by reviewing previous related literature. Then, through the Delphi method, eight experts constructed the 14 main influencing factors that affect consumers’ shopping motivation in livestream e-commerce. Through DEMATEL-ANP, we can not only find the key factors but also sort out the causal relationship between the main key factors, forming a preliminary evaluation model of the commercial value of livestream sellers. The importance-performance analysis (IPA) of these impact factors found that “seller popularity” is the most critical factor affecting consumers’ shopping motivation. At the same time, product discounts, product quality, and the attractiveness of the sellers are being included in effects by the “seller popularity.” The investigation followed in this study revealed that characteristics of the livestream seller are one of the most influencing factor achieving a total weight of 0.3020, whereas the streaming platform is the least influencing factor (total weight is 0.1333). The assessment made the study explore the sustainability of livestream e-commerce in China, and the proposed evaluation model can be used for the preliminary business value evaluation of people engaged in livestream sellers and related industries.
5 citations
TL;DR: In this paper , the authors identify the influence mechanism of user-generated content helpfulness by examining the systematic impacts of argument quality and source reliability, especially considering the effects of creator interactivity.
Abstract: A growing number of enterprises begin to utilize user-generated content (UGC) to help build brand awareness and loyalty on social media platforms. Thus, it is important to investigate what makes UGC more helpful under the new social media environment. This study attempts to identify the influence mechanism of UGC helpfulness by examining the systematic impacts of argument quality and source reliability, especially considering the effects of creator interactivity. Using a dataset of product-related UGC in a popular social media app, our empirical study finds that the detailedness, readability, and objectivity of the content, as well as the social recognition and popularity of the creator, all have a significant impact on UGC helpfulness. Furthermore, the results indicate that creator interactivity plays a vital role in building UGC helpfulness by moderating other factors. This study contributes to both UGC and social media literature by proposing a comprehensive model to better understand UGC helpfulness. It also provides several practical insights for content creators to improve their online performances.
5 citations
References
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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
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
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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