Facebook eWOM: Self-Shared Versus System-Generated Credibility Cue
TL;DR: The structural model results confirm that the perceived source and message credibility derived from self-shared and system-generated cues are significant antecedents to purchase-related consideration for a brand.
Abstract: The study examines how consumers, in a Facebook eWOM context, perceived source and message credibility by utilizing self-shared and system-generated cues. It investigates:(1) to what extent source and message credibility derived from these cues may lead to significant attitudinal responses and intentions to purchase; (2) and to what extent attitudinal responses are likely to vary with different levels and combinations of these credibility cues. Data was collected from 246 respondents who were exposed to Facebook eWOM scenarios. The structural model results confirm that the perceived source and message credibility derived from self-shared and system-generated cues are significant antecedents to purchase-related consideration for a brand. The results further confirm that these cues have an overall balancing effect: one compensates for the low level of the other leading to a significant persuasive response. The study evaluates traditional antecedents of WOM adoption, namely, perceived source and message credibility derived from unique interface-related features.
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13 May 2022
TL;DR: In this article , the role of need for self-enhancement, the need for entertainment, and deal-seeking behavior on the intention to follow brands on Instagram was examined.
Abstract: The research, based on uses and gratifications theory, identifies consumer motivation and factors that influence consumers' intention to follow brands on the social media platform of Instagram. Accordingly, this study empirically examines the role of need for self-enhancement, the need for entertainment, and deal-seeking behaviour on the intention to follow brands on Instagram. Further, the study investigates the mediation of social media usage behaviour for consumption decisions on eliciting brand following behaviour. Moderation of consumer skepticism on the relationship of deal-seeking behaviour, and intention to follow brands is also investigated. Findings reveal a significant direct effect of need for self-enhancement, need for entertainment, and deal-seeking behaviour on intention to follow brands. Indirect effect of social media usage behaviour for consumption decisions was also significant; however, moderation of consumer skepticism was not found to be significant. The study will help marketers create engaging content that enables consumer-brand interactions.
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TL;DR: This paper is the first study that integrates econometric, text mining, and predictive modeling techniques toward a more complete analysis of the information captured by user-generated online reviews in order to estimate their helpfulness and economic impact.
Abstract: With the rapid growth of the Internet, the ability of users to create and publish content has created active electronic communities that provide a wealth of product information. However, the high volume of reviews that are typically published for a single product makes harder for individuals as well as manufacturers to locate the best reviews and understand the true underlying quality of a product. In this paper, we re-examine the impact of reviews on economic outcomes like product sales and see how diff erent factors a ffect social outcomes such as their perceived usefulness. Our approach explores multiple aspects of review text, such as subjectivity levels, various measures of readability and extent of spelling errors to identify important text-based features. In addition, we also examine multiple reviewer-level features such as average usefulness of past reviews and the self-disclosed identity measures of reviewers that are displayed next to a review. Our econometric analysis reveals that the extent of subjectivity, informativeness, readability, and linguistic correctness in reviews matters in influencing sales and perceived usefulness. Reviews that have a mixture of objective, and highly subjective sentences are negatively associated with product sales, compared to reviews that tend to include only subjective or only objective information. However, such reviews are rated more informative (or helpful) by other users. Further, reviews that rate products negatively can be associated with increased product sales when the review text is informative and detailed.By using Random Forest based classi ers, we show that we can accurately predict the impact of reviews on sales and their perceived usefulness. We examine the relative importance of the three broad feature categories: 'reviewer-related' features, 'review subjectivity' features, and 'review readability' features, and find that using any of the three feature sets results in a statistically equivalent performance as in the case of using all available features. This paper is the first study that integrates econometric, text mining, and predictive modeling techniques toward a more complete analysis of the information captured by user-generated online reviews in order to estimate their helpfulness and economic impact.
1,036 citations
TL;DR: A survey of users of an on-line consumer discussion forum in China substantiated the effects of the determinants, although post-hoc analyses revealed that prior knowledge and involvement level moderate some of them.
Abstract: Word-of-mouth (WOM) study is extended to the on-line context (eWOM) by examining the informational and normative determinants of the perceived credibility of on-line consumer recommendations. A survey of users of an on-line consumer discussion forum in China substantiated the effects of the determinants, although post-hoc analyses revealed that prior knowledge and involvement level moderate some of them. Implications for research and practice are discussed.
1,032 citations
TL;DR: In this paper, the impact of reviews on economic outcomes like product sales and how different factors affect social outcomes such as their perceived usefulness was examined, and it was shown that the extent of subjectivity, informativeness, readability, and linguistic correctness in reviews matters in influencing sales and perceived usefulness.
Abstract: With the rapid growth of the Internet, the ability of users to create and publish content has created active electronic communities that provide a wealth of product information. However, the high volume of reviews that are typically published for a single product makes harder for individuals as well as manufacturers to locate the best reviews and understand the true underlying quality of a product. In this paper, we reexamine the impact of reviews on economic outcomes like product sales and see how different factors affect social outcomes such as their perceived usefulness. Our approach explores multiple aspects of review text, such as subjectivity levels, various measures of readability and extent of spelling errors to identify important text-based features. In addition, we also examine multiple reviewer-level features such as average usefulness of past reviews and the self-disclosed identity measures of reviewers that are displayed next to a review. Our econometric analysis reveals that the extent of subjectivity, informativeness, readability, and linguistic correctness in reviews matters in influencing sales and perceived usefulness. Reviews that have a mixture of objective, and highly subjective sentences are negatively associated with product sales, compared to reviews that tend to include only subjective or only objective information. However, such reviews are rated more informative (or helpful) by other users. By using Random Forest-based classifiers, we show that we can accurately predict the impact of reviews on sales and their perceived usefulness. We examine the relative importance of the three broad feature categories: “reviewer-related” features, “review subjectivity” features, and “review readability” features, and find that using any of the three feature sets results in a statistically equivalent performance as in the case of using all available features. This paper is the first study that integrates econometric, text mining, and predictive modeling techniques toward a more complete analysis of the information captured by user-generated online reviews in order to estimate their helpfulness and economic impact.
1,014 citations
TL;DR: The authors found that most users rely on others to make credibility assessments, often through the use of group-based tools, and that participants routinely invoked cognitive heuristics to evaluate the credibility of information and sources online.
Abstract: The tremendous amount of information available online has resulted in considerable research on information and source credibility. The vast majority of scholars, however, assume that individuals work in isolation to form credibility opinions and that people must assess information credibility in an effortful and time-consuming manner. Focus group data from 109 participants were used to examine these assumptions. Results show that most users rely on others to make credibility assessments, often through the use of group-based tools. Results also indicate that rather than systematically processing information, participants routinely invoked cognitive heuristics to evaluate the credibility of information and sources online. These findings are leveraged to suggest a number of avenues for further credibility theorizing, research, and practice.
964 citations
TL;DR: In this article, the authors test empirically a conceptualization of brand associations that consists of three dimensions: brand image, brand attitude and perceived quality, and explore whether the degree of dimensionality of brand association varies depending upon a brand's familiarity.
Abstract: The purpose of the research reported here was to test empirically a conceptualization of brand associations that consists of three dimensions: brand image, brand attitude and perceived quality. A better understanding of brand associations is needed to facilitate further theoretical development and practical measurement of the construct. Three studies were conducted to: test a protocol for developing product category specific measures of brand image; investigate the dimensionality of the brand associations construct; and explore whether the degree of dimensionality of brand associations varies depending upon a brand’s familiarity. Findings confirm the efficacy of the brand image protocol and indicate that brand associations differ across brands and product categories. The latter finding supports the conclusion that brand associations for different products should be measured using different items. As predicted, dimensionality of brand associations was found to be influenced by brand familiarity.
963 citations