Brand-related User-generated Content Research Articles

Leave A Review! The Motives Of User-Generated Content And Its Influence On Customer-Based Brand Equity- Mediating Influence Of Brand Attachment

User-generated content, or UGC, is a marketing buzzword which means a form of customer-generated brand-related communication on social media sites. This study offers insightful information on how user-generated content affects consumer-based brand equity when present on social networking platforms. Purpose This study focuses on what motivates consumers to create User Generated Content (UGC) and what is the influence of Brand- Related UGC (Br-UGC) on Customer-Based Brand Equity (CBBE). It also studies the mediating role of Brand Attachment in influencing the Br-UGC on CBBE. Design The research was carried out by utilizing a survey questionnaire, which was administered to 364 participants selected through the convenience sampling method. Methodology Smart PLS 4.1 software has been used to establish the results of this study. Statistical tests have affirmed the validity and the reliability of the proposed framework. Findings The result of this research suggests that an urge to create, contribute, empowerment and self-recognition motivates the consumer to create content online. User-generated content serves as a powerful platform to motivate consumers to buy brands online on marketplaces and social media platforms. The powerful impact of Brand Attachment is also confirmed by the results of the study. Practical Implications This research aids the marketing professionals and brand managers in encouraging consumers to engage in generating content online. Originality/Value This study one of the first study to validate the mediating function of brand attachment between UGC and Brand Equity.

Using a Photo-Elicitation Procedure to Examine Consumers’ Motivations to Post Visual Brand-Related User-Generated Content

The recent popularity of visual social media has seen a parallel increase in the amount of visual brand-related user-generated content (Br-UGC). This brand-related content created by consumers can have a significant influence on brand outcomes. Yet little is known about why consumers post visual Br-UGC. Current research examines consumers’ motivations to post visual Br-UGC by departing from research on textual Br-UGC and research on visual content posting on Instagram. Moreover, we compare motivations to post branded selfies (e.g., pictures that feature the brand and the social media user together) to motivations to post other visual Br-UGC. Photo-elicitation interviews with 30 (M age = 21.77, SD age = 2.71, 83.3% women) participants revealed that consumers use brands as subtle cues to express their (ideal) online identities. Notably, this finding is present for both branded selfies as well as pictures without a person present. Other important motivations include social interaction, aesthetics (i.e., whether the picture is beautiful), and empowerment. Theoretical and practical implications are discussed.

Brand-related user-generated content in new media – systematic literature review

Brand-related user-generated content in new media – systematic literature review

Influence of emojis on user engagement in brand-related user generated content

Emojis are increasingly adopted in various platforms, such as text messages, social media, or blogs, as part of other digital communications. Recently, emojis have been used in brand-related user-generated content (UGC) as a strategic communication tool to promote positive outcomes. In spite of their increasing importance, little is known about the impact of incorporating emojis in brand-related UGC on consumer reactions. In particular, few research studies have investigated the joint effect of emojis with texts, which is the most important context where emojis function, and the contextual conditions that affect the influence of emojis on consumer reactions. To fill this research gap, we study brand-related UGC, focusing on the effect of emojis and the contextual conditions (e.g., texts). Using large-scale brand-related social media posts from Instagram, we find that, overall, the presence of emojis is positively associated with consumer engagement. Economically, the presence of emojis increases the average number of likes by 72% and the average number of comments by 70% in comparison to posts without any emojis. The interaction effects between emojis and texts reveal that emotional emojis have a positive and significant relationship with consumer engagement only when the texts in brand-related UGC are being skewed toward positive sentiments. However, informational emojis are negatively related with consumer engagement in the similar context. Additionally, the investigations regarding the contextual conditions show that using more emotional emojis has a positive influence on consumer engagement in commercial posts but a negative influence in general posts.

Effects of Materialism on Brand-Related User-Generated Content and Positive WOM on Social Media

This research investigates how materialism as a personality trait can impact consumers’ intention to create brand-related user-generated content (UGC) and positive WOM on Facebook. The research involved three studies. Study 1 was an online survey investigating the association between materialism and brand-related UGC and positive WOM creation on Facebook. Study 2 tested the mediating role of the perception of brand symbolism for the effect of materialism on brand-related UGC and positive WOM creation. Study 3 was an online experiment which manipulated materialism. It demonstrated that the perception of brand symbolism mediated the effect of materialism on brand-related UGC and positive WOM creation on Facebook. These findings show how materialism influences whether consumers create content about brands to express self-identity. They also show researchers and managers how to target consumers to encourage them to create brand-related UGC and positive WOM on social media. Specifically, by emphasising materialistic cues, marketers can enhance consumers’ perception of brand symbolism which can motivate consumers to create brand-related UGC and positive WOM.

How Many Likes Are Good Enough? An Evaluation of Social Media Performance

This paper considers the evaluation of social media performance from a user’s perspective using the expectation confirmation theory as the theoretical framework. The interplay between initial expectations and subsequent evaluations of social media performance, in particular, forms the basis of the evaluation. The research focuses on the influence that the performance of brand-related user-generated content is able to exert on a user’s brand attitude, self-image, and the development of their personal brand. This conceptual paper develops three propositions suggesting that the social media performance of brand-related user-generated content is able to influence one’s brand attitude, self-image, and personal brand respectively. A typology of four different social media user types is developed through an evaluation of the disconfirmation experienced as a result of the interplay between initial expectations and the actual evaluation of the performance of brand-related, user-generated content. The concept of social media performance is proposed, which considers the subjective evaluation of the performance of a brand-related post shared on social media platforms. In addition, the research expands the expectation confirmation theory to a new context in order to offer a more nuanced understanding of an existing yet under researched phenomenon.

An Empirical Study of the Motivations for Intention to Read Brand-related User-generated Content on Social Media in Vietnam

This study investigates the motivations of social media users for their intention to read brand-related user-generated content (B-UGC). The study applies the uses and gratifications (U&G) approach to identify the typology of UGC reading motivations. It examines other possible motives from theory of planned behavior to a conceptualized research model. Following quantitative methodology, a questionnaire survey was carried out with 263 valid respondents. The assessment of the research model and hypotheses is analyzed using confirmatory factor analysis and structural equation modeling. The research found that information-seeking and social interaction have a significant impact on attitude towards UGC, which is the most significant predictor of intention to read B-UGC. Entertainment and passing time gratifications are significantly related to attitude toward B-UGC, and the perceived power of control would not significantly affect the intention to read B-UGC. This study discusses managerial implications for directing and managing the brand-related content in social media.

Reading between the lines: untwining online user-generated content using sentiment analysis

PurposeOne of the major challenges within the airline industry is to keep pace with the changing customer perception toward their service quality. This paper aims to demonstrate how sentiment analysis of user-generated big data can be used to research airline service quality as a more comprehensive alternative to other survey-based models by investigating real-time passenger insights.Design/methodology/approachThe present research uses the case of Indigo airlines by studying passenger's trip advisor reviews regarding the low-cost commercial airline service. The authors analyzed 1,777 passenger reviews, which were classified, to uncover sentiments for five dimensions of airline service quality (AIRQUAL).FindingsThe findings of the study demonstrate the need for harnessing the brand-related user-generated content shared on online platforms to identify the critical attributes for airline service quality. Further, through the application of sentiment analysis, the paper provides much-needed clarity in the processing of user-generated content. It illustrates the investigation of passenger interactions as a reflection of their satisfaction, expectation, intention and overall opinion toward the airline service quality.Practical implicationsThe analytical framework adopted in the study for examining user-generated content (UGC) can be functional for the marketing managers and equip them for handling large-scale data readily available in action-oriented interactive marketing research.Originality/valueThis paper demonstrates how sentiment analysis of user-generated data can be used to research airline service quality as a more comprehensive alternative to other survey-based models. The study supplements the methodological advances in the field of UGC analysis and adds to the existing knowledge domain.

Non-sponsored brand-related user-generated content: effects and mechanisms of consumer engagement

PurposeThis study aims to investigate whether users’ engagement with a social media platform is affected as they engage in non-sponsored brand-related user-generated content (UGC). The concept of non-sponsored brand-related UGC encapsulates various social media patterns in which individuals choose how to consume, contribute or create brand-related content with no formal brand incentive or control.Design/methodology/approachThe study focuses on the question of how users engage with non-sponsored brand-related UGC on Instagram and assesses the influence of UGC perceived value, using partial least squares variance-based structural equation modeling.FindingsThe research shows significant and positive effects of UGC on Instagram users’ intentions to engage with the platform and the influence of UGC perceived value on UGC uses. The findings deepen the understanding of the mechanisms underlying non-sponsored brand-related UGC in consumer engagement marketing, with significant implications for brand managers and the future development of Instagram and other social media platforms.Originality/valueThe UGC functional, social and emotional values are evaluated for their effects on generating the three distinct patterns of consumer online brand-related activities (consumer, contribute and create) in the non-sponsored brand-related UGC context.

Brand-Related User-Generated Content in Simulation Video Games: Qualitative Research Among Polish Players

Purpose: The article sought to answer research questions regarding investigated branded content generated by players in simulation video games. How does the process work in video games? What are the characteristics of branded user-generated content in video games? To what extent players are willing to participate in branded content creation? Methodology: I conducted 20 in-depth interviews among Polish players, with the application of snowball sampling. The study participants were adult users of chosen simulation video games: The Sims, Second Life, and Euro Truck Simulator 2. Findings: We can distinguish content based on game mechanism, official add-ons, or game modding. Players frequently check some brands from a set offered by game developers and create content (e.g. in The Sims users can design house interiors with IKEA furniture). Some players are not satisfied by what a game offers and generate content based on modding (e.g. DHL trucks or McDonald’s restaurants inside the Euro Truck Simulator 2). In this respect, the article refers to Smith’s, Fischer’s, and Yongjian’s content dimensions. Branded game modifications described by respondents are characterized by a high level of similarity towards real brands and positive brand sentiment (valence). I noted no statement about player and marketer (brand) communication in gathered material. The biggest challenge for practitioners in the field of UGC in video games is how to manage brand messages. Practical Implications: Brand-related user-generated content is an important phenomenon in terms of the brand-building process and its impact on brand reception, which all require marketers’ attention. For game developers, such a content is a source of information about customer expectations. Players show their personal expectations by game modding. Originality/Value: Brand-related content generated by users is frequently associated with social media. The scholarship shows a lack of knowledge of branded user-generated content in video games.

Purchase Situations and Information-Seeking in Brand-Related User-Generated Content

Consumers use brand-related user-generated content (UGC), such as online consumer reviews, for their pre-purchase information seeking. However, previous research on consumer information seeking has scarcely explored how purchase situations and product type influence one’s use of brand-related UGC. The purpose of this study is to shed light on this area of consumer behavior. By utilizing linear mixed effect models, we examined several hypotheses relevant to relationships between four purchase variables (PDI, think purchase, feel purchase, online/offline purchase) and one’s reliance on brand-related UGC. The results indicate that all of the purchase variables are positively associated with the use of UGC. Furthermore, the study found several more associations between demographic factors and the reliance on UGC. Age, gender, marital status, number of children in a household, and employment status showed significant associations, whereas education, household income, and ethnicity did not. Implications, limitations and suggestions for future research are also noted.

The role of facial expression and tie strength in sender presence effects on consumers’ brand responses towards visual brand-related user generated content

The popularity of visual social network site Instagram has led to an increase of visual brand-related user-generated content (Br-UGC), which has the potential to affect brand outcomes. Previous research identified sender presence as an important content characteristic that can influence consumer's brand responses. However, the effect of sender presence in visual Br-UGC seems to be different from that of traditional advertising. The current research extends this sender presence scholarship by examining two explanations for the effects of sender presence: sender facial expression, and tie strength between sender and receiver. We expect that the effects of sender presence will be stronger for happy-as compared to neutral-looking senders, and that these effects are stronger when there is a stronger tie between sender and receiver. The current research adopts a two-step approach to examine sender presence effects in various levels of tie strength. Results show that a happy facial expression significantly increases like intention and brand attitude. Moreover, there is a moderating effect of tie strength on sender presence for comment intention: stronger levels of tie strength result in stronger effects of the presence of the sender. Theoretical and practical implications are discussed.

The Social Side of Brick and Mortar: The Impact of Brand-Related User-Generated Content on Different Consumer Typologies in Food Retailing

The Social Side of Brick and Mortar: The Impact of Brand-Related User-Generated Content on Different Consumer Typologies in Food Retailing

Defining the relationship between consumers and retailers through user-generated content: insights from the research literature

PurposeThe purpose ofthis study is to synthesise the findings of existing research on brand-related user-generated content (UGC) in the context of fashion retail and to come up with future research directions.Design/methodology/approachA systematic literature review of 33 research papers, selected using well-defined criteria, was done. Further, the thematic analysis identified underlying themes and their inter-linkages.FindingsThe inter-linkages of 12 emergent themes were showcased in the form of a causal-chain conceptual framework, highlighting antecedents, mediators, moderators and consequences.Research limitations/implicationsFuture research involves six directions, and researchers should empirically test out the proposed conceptual framework and take the given research directions forward.Practical implicationsRetailers should understand UGC motivators to launch targeted campaigns to amplify UGC with firm-generated content and increase overall engagement and sales of a brand.Originality/valueFirst, this study fills the gap of missing synthesis of existing studies on UGC about fashion retail by analysing the publication distribution, paper types, data collection tools and techniques and data analysis methods. Second, the authors have proposed a causal-chain conceptual framework based upon thematic analysis of the research literature. The emergent themes touch upon three crucial aspects of marketing on enabling technology, consumer behaviour and marketing tactics. Finally, the academic contribution of this study lies in coming up with six vital research agenda for future research.

The Use of Computer Vision to Analyze Brand-Related User Generated Image Content

With the increasing popularity of visual-oriented social media platforms, the prevalence of visual brand-related User Generated Content (UGC) have increased. Monitoring such content is important as this visual brand-related UGC can have a large influence on a brand's image and hence provides useful opportunities to observe brand performance (e.g., monitoring trends and consumer segments). The current research discusses the application of computer vision for marketing practitioners and researchers and examines the usability of three different pre-trained ready-to-use computer vision models (i.e., YOLOV2, Google Cloud Vision, and Clarifai) to analyze visual brand-related UGC automatically. A 3-step approach was adopted in which 1) a database of 21,738 Instagram pictures related to 24 different brands was constructed, 2) the images were processed by the three different computer vision models, and 3) a label evaluation procedure was conducted with a sample of the labels (object names) outputted by the models. The results of the label evaluation procedure are quantitatively assessed and complemented with four concrete examples of how the output of computer vision can be used to analyze visual brand-related UGC. Results show that computer vision can yield various marketing insights. Moreover, we found that the three tested computer vision models differ in applicability. Google Cloud Vision is more accurate in object detection, whereas Clarifai provides more useful labels to interpret the portrayal of a brand. YOLOV2 did not prove to be useful to analyze visual brand-related UGC. Results and implications of the findings for marketers and marketing scholars will be discussed.

Measuring brand-related content in social media: a socialization theory perspective

PurposeBuilding on consumer socialization theory, the purpose of this paper is to examine antecedents and consequences of generating and sharing brand-related content on social media in a restaurant context.Design/methodology/approachA scale development process was undertaken to develop the scale for brand-related user-generated content (BRUGC). Then the authors tested the antecedents and consequences of BRUGC using 375 responses obtained through a mall-intercept survey. The hypotheses were tested using structural equation modeling with AMOS.FindingsStudy findings revealed that age, time on Facebook, number of Facebook friends, Facebook usage intensity, and need for self-enhancement were key antecedents of both the generation and sharing of BRUGC. The results also indicated that gender, race and need for self-affirmation were not significantly related to generating and sharing BRUGC. Both generating and sharing BRUGC were positively associated with attitude and intentions toward the restaurants.Originality/valueThis study is the first to develop a BRUGC scale through a rigorous scale development process. It thus contributes to consumer socialization theory literature in considering social media as a socialization agent. The findings provide valuable insights for both academicians and social media managers and aid in enhancing BRUGC.

A big data approach to examining social bots on Twitter

PurposeSocial bots are prevalent on social media. Malicious bots can severely distort the true voices of customers. This paper aims to examine social bots in the context of big data of user-generated content. In particular, the author investigates the scope of information distortion for 24 brands across seven industries. Furthermore, the author studies the mechanisms that make social bots viral. Last, approaches to detecting and preventing malicious bots are recommended.Design/methodology/approachA Twitter data set of 29 million tweets was collected. Latent Dirichlet allocation and word cloud were used to visualize unstructured big data of textual content. Sentiment analysis was used to automatically classify 29 million tweets. A fixed-effects model was run on the final panel data.FindingsThe findings demonstrate that social bots significantly distort brand-related information across all industries and among all brands under study. Moreover, Twitter social bots are significantly more effective at spreading word of mouth. In addition, social bots use volumes and emotions as major effective mechanisms to influence and manipulate the spread of information about brands. Finally, the bot detection approaches are effective at identifying bots.Research limitations/implicationsAs brand companies use social networks to monitor brand reputation and engage customers, it is critical for them to distinguish true consumer opinions from fake ones which are artificially created by social bots.Originality/valueThis is the first big data examination of social bots in the context of brand-related user-generated content.

Challenging Traditional Culture? How Personal and National Collectivism-Individualism Moderates the Effects of Content Characteristics and Social Relationships on Consumer Engagement with Brand-Related User-Generated Content

Consumers across the globe increasingly engage with user-generated content about brands on social networking sites (i.e., brand-related user-generated content [Br-UGC]). As online consumer behavior does not occur in a cultural void, the present study extends earlier research by explicitly examining how the collectivism-individualism dimension, both at the national and at the personal level, influences consumers’ engagement (“liking,” commenting on, and sharing) with different types of Br-UGC created by different sources. Results based on a diverse sample of participants from South Korea, Thailand, the Netherlands, and the United States (N = 812) suggest that collectivism-individualism at the national level moderates the effects of content characteristics and social relationships on Br-UGC engagement. Moreover, consumers who hold the same values as others in their national culture are more comfortable sharing informative Br-UGC.

An emoji-based metric for monitoring consumers’ emotions toward brands on social media

PurposeThe purpose of this paper is to introduce and test a new emoji-based metric that could be used to monitor consumers’ emotions toward brands on social media.Design/methodology/approachTo test this new metric, 720 consumer tweets were retrieved from official Twitter accounts of 18 leading global brands representing 6 product categories/markets. In order to check its validity, the emoji-based metric was correlated with two measures: the percentage of positive emojis from Brandwatch’s (2018) Emoji Report and the American Customer Satisfaction Index (ACSI) for 2017.FindingsThe findings of this paper indicate that consumers tend to use more (vs less) positive emojis when expressing their feelings toward Coca-Cola (vs Taco Bell). They also show that the new metric is highly and positively associated with the ACSI, hence supporting its validity.Research limitations/implicationsThe new metric is only applicable to brands that have a social media presence.Practical implicationsThe proposed metric is easy to implement and interpret by almost every researcher and manager.Originality/valueWhile all extant brand sentiment analyses focus on analyzing the words in brand-related user-generated content, this paper considers an alternative source of information about emotions, that is, emojis. Beyond being valid, the proposed emoji-based metric is unique, easy to implement and interpret, and generalizable.

Understanding Social Media: The Effect of Belief Type and Product Type on Consumers’ Social Media Use

This study advances the knowledge of social media by examining brand-related user-generated content (UGC) on three social media platforms: Facebook, Twitter, and YouTube. Using content analysis of posts from these sites, the authors show important differences between utilitarian and hedonic products with regard to the type of brand belief (functional, experiential, and symbolic) as well as sentiment (positive and negative) included in UGC. The results provide managers with insights on how to identify content that is likely to make a real impact on consumers on each platform, as well as how to allocate resources across platforms, depending on product type.