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This study is based on a web-based advertising value model, adding emotional appeal, advertising credibility, advertising clicks, product evaluation and incentive to examine the impact on consumers' product evaluation and purchase intention.

In total, 313 valid online questionnaires were collected from those who had browsed the social media advertisement.

The results show that advertising credibility and emotional appeal have a higher impact on advertising attitude than informativeness and irritation in the original web-based advertising value model.

The findings strengthen the literature on the antecedents of advertising attitude in social media context, confirming advertising clicks as a predictor of product evaluation, and determining that advertising attitude, product evaluation and incentive play key roles as predictors of consumer purchase intention.

The findings are particularly relevant to advertising marketing managers. In the context of social media advertising, the advertising credibility of consumers is the key to increasing consumers' willingness to purchase. Advertisers must establish a good advertising reputation to consumers in the social media context.

This study combines the web-based advertising value model, advertising clicks, product evaluation and incentive to investigate the factors that influence customers' purchase decisions in the context of social media.

More people share their tourism experiences on social media today than in the past, and as a result, more people follow these posts in their trip planning. However, studies into tourists' intention to follow such posts are scarce. Therefore, this study investigates the antecedents influencing social media users' intentions to follow tourism-related posts (TRPs) when planning their trips.

Questionnaires were collected from 402 social media users who had followed TRPs for their trip planning. Data were then analyzed using partial least squares structural equation modeling (PLS-SEM) and artificial neural networks.

The authors found that blogger–user fit and users' involvement with TRPs influenced behavior components (attitudes toward TRPs and intention to follow TRPs) via assessment components (bloggers' credibility and content quality), and the authors developed a framework to explain this relationship.

The findings advance prior studies by investigating (1) the antecedents of intention to follow TRPs when trip planning, (2) the two main social media elements – bloggers and posts – to understanding the role of social media on travel behavior and (3) involvement with TRPs and their impacts on travel behavior. This study contributes to the research on social media and tourism marketing and proposes practical indications for bloggers, social media platforms and destination marketing organizations.

This study aims to examine consumers’ responses to crowdsourcing campaigns in the request initiation stage using the signaling theory from economics. The purpose of the research is threefold. First, it provides a comprehensive classification of various task types within crowdsourcing. Second, it conceptualizes crowdsourcing announcements as signals of customer orientation and empirically tests the differential effects of the two most common crowdsourcing task types (product- and communication-related) on customer orientation perceptions. Third, it illuminates the downstream behavioral consequences of crowdsourcing campaign announcements.

The authors conducted secondary data analysis of 883 crowdsourcing campaigns (pilot study) to provide evidence on the differential effects of crowdsourcing task types. In addition, four laboratory experiments were conducted to test the theoretical arguments. To test the main effect of crowdsourcing task types, Study 1A (N = 252 MTurk workers) used a one-factor (product- vs communication-related crowdsourcing vs control) between-subject design, whereas Study 1B (N = 171 undergraduate students) used a 2 (task type: product- vs communication-related) by 2 (product category: restaurant vs fashion) between-subject design. Study 2 (N = 93 MTurk workers) explored the underlying mechanism using a one-factor (product- vs communication-related) between-subject design. Study 3 (N = 375 MTurk workers) investigated the boundary condition for the effect of task type with a 2 (task type: product- vs communication-related) by 3 (company credibility: low vs neutral vs high) between-subject design.

The pilot study provides evidence for the conceptualized typology and the differential effects of crowdsourcing task types. Study 1A reveals that product-related crowdsourcing tends to have a more substantial impact than communication-related crowdsourcing on how customer-oriented consumers perceive a company. Study 1B validates the results of Study 1A in a different product category and population sample. Study 2 shows that the differential customer-orientation effect is mediated by the perceived cost of implementing the crowdsourcing outcome and unravels the differences in consumers’ purchase and campaign participation intentions depending on task type. Study 3 highlights that the customer-orientation effect attenuates as company credibility increases.

This research contributes to the crowdsourcing literature by categorizing the various types of crowdsourcing campaigns companies undertake and revealing the differential impact of the different types of crowdsourcing campaigns on consumers’ perceptions and behavioral intentions. In doing so, this research converges two lines of consumer research on crowdsourcing, i.e. product- and communication-related crowdsourcing. The findings add to the debate over the returns from research and development (R&D) versus advertising and extend it from marketing strategy to crowdsourcing literature.

The findings highlight the importance of choosing specific task types for crowdsourcing and lead to practical recommendations on designing crowdsourcing campaigns to maximize their benefits to crowdsourcing brands.

To the best of the authors’ knowledge, this is the first study that differentiates crowdsourcing task types and compares their effectiveness from a consumer perspective.

This study aims to investigate replies to the top 10 comments under Always “Like a Girl” YouTube femvertising video to gauge consumers’ responses regarding femvertising as well as relationships among commenters.

This study adopted a mixed research methods design. A user analysis and a qualitative content analysis were conducted to examine the replies of the top 10 comments with the most replies to reveal not only the topics but also relationships and patterns among those comments and commenters.

The user analysis found that across all the 10 comment-and-reply units, in 8 units, the user of the original primary comment, the conversation starter, was also the user who was targeted most often. The qualitative content analysis revealed four themes from the 10 comment-and-reply units: multilayered emotional responses, a gendered society, complex coexisting relationships and a melting pot.

The findings of this research offer significant extensions to the understanding of public sphere theory within the contemporary digital media landscape. By analyzing the nature of replies to digital advertisements, the study illuminates how various types of user engagement–whether it be inquiry, laudation, debate, or flame–play a critical role in shaping the digital public sphere.

The study underscores the importance for marketers to scrutinize both comments and replies to effectively utilize femvertising on social media, particularly YouTube. By understanding the emotional dynamics of user interactions, marketers can craft strategies that evoke positive responses and mitigate negative ones. Engaging with users who are open to changing their views or mediating discussions can also be beneficial, as can the use of AI tools to maintain focus on the content rather than on individual commenters. Such approaches can enhance the perception of femvertising campaigns and foster a more constructive dialogue within the social media space.

This study contributes to the literature by investigating the replies of comments, interactions, relationships and patterns among YouTube commenters that may generate valuable insights for advertisers and marketers to be aware of the possible issues and monitor the sentiment of commentaries, thus, developing effective strategies to better connect with consumers. This extends the understanding of public sphere theory in the contemporary digital media landscape.

This study examines the research that has been conducted on user-generated advertising content in the social marketing strategies of commercial brands to understand the phenomenon, explore academic interest in the topic and identify areas of limited thematic coverage.

A systematic review of existing scientific literature in the Web of Science (WoS) and Scopus was carried out using the PRISMA protocol. A co-occurrence matrix was used to review emerging topics on user-generated content (UGC) and influencer marketing, allowing the identification of articles (n = 59) related to the objective of this research.

Most research has analyzed UGC in images or text, but only very few have addressed videos and other digital formats (such as reels, image carousels or podcasts), although there is sufficient work focused on Twitter, Facebook and YouTube. There was no evidence of work exploring the effects, repercussions and possible dangers of uncontrolled brand exposure through Unofficial Brand Ambassadors.

The literature review has allowed finding important areas of future research that the scientific community has not sufficiently addressed. Likewise, this work shows structurally several classifications of UGC, which will facilitate future research to deepen and broaden these categories.

This study aims to investigate the relative impact of firm-created (FC) and user-generated (UG) social media marketing communication on fashionwear customers' purchase intention (CPI) in Sri Lanka. The primary objective is to identify the influence of social media marketing on the purchasing intention (PI) of customers in the fashionwear industry in Sri Lanka.

A standardized online survey was conducted, generating 312 datasets for analysis.

The empirical findings reveal that both firm-produced and UG social media fashionwear marketing communication has a significant influence on CPI. However, firm-produced social media fashionwear brands demonstrate a higher impact on CPI.

This study highlights the importance of social media marketing communication in shaping customers’ PI in the fashionwear industry in Sri Lanka. Both FC and UG content on social media platforms play a crucial role in influencing customers' intention to purchase fashionwear products. However, firm-produced social media fashionwear brands exert a stronger impact on CPI. These findings emphasize the need for marketers to incorporate effective social media strategies, including both FC and UG content, to enhance customer engagement and drive purchase decisions in the fashion-wear industry.

This paper aims to investigate an integrated, holistic assessment of the characteristics by which consumers judge non-sponsored product review video (PRV) source, message and medium components as credible, and how these are linked to personal values for a deeper understanding of multidimensional credibility assessments of PRVs.

Employing a means-end approach, the authors draw on credibility theory and the persuasion knowledge model to analyse data from 21 in-depth semi-structured laddering interviews.

First, the authors demonstrate distinctive contributions of the video modality towards PRV credibility assessments and the interplay between specific PRV characteristics, cognitive and socio-emotional consequences, and personal values in an ongoing process of credibility assessment. Second, high persuasion knowledge creates awareness of the potential phoniness of the market, revealing a dark side to PRV use even in non-sponsored PRV seemingly created and shared as an act of benevolent concern between consumers.

This paper focused on the credibility of non-sponsored PRVs, future studies might investigate motivations and attributes by which users judge sponsored reviews. Also, the roles of specific product categories and existing brand trust on PRVs credibility provide avenues for further research.

This research offers practical implications for reviewers and brand managers to leverage the unique informational values of video by focusing on the interplay between credibility attributes and customer values.

This work advances credibility theory in the PRV context by examining how non-sponsored PRVs are evaluated as credible, by highlighting consumer persuasion knowledge and scepticism and including the holistic effects of the interplay between source, message and video format characteristics and by linking these to consumers’ goals and values.

From the signaling theory perspective, the current study explores various drivers of brand transparency and its effect on users' interactions with food delivery apps.

First, a set of precursors of brand transparency of food delivery apps from focus group discussions was identified. Next, an integrated model tests the impact of brand transparency, perceived risk and brand trust on users' ordering frequency. Data collected from 522 users were analyzed using the partial least squares structural equation modeling method.

The outcomes showed the effectiveness of brand communications as the strongest indicator of brand transparency. Moreover, brand transparency favorably influences users' brand trust and ordering intention and negatively influences perceived risk. Hygiene rating attenuates the adverse effects of perceived risk.

The current study is a pioneering attempt that offers ways for online food delivery providers to build brand transparency, lessen users' risk perceptions and foster greater use of apps in the post-pandemic scenario.

This paper aims to explore consumer perception of “brand voice” authenticity, brand authenticity and brand attitude when the source of text is disclosed as either artificial intelligence (AI)-generated or human-written.

A 3 × 3 experimental design using Adidas marketing texts disclosed as either “AI” or “human”, or not disclosed was applied to data gathered online from 624 English-speaking students.

Text disclosed as AI-generated is not perceived as less authentic than that disclosed as human-written. No negative effect on brand voice authenticity and brand attitude results if an AI-source is disclosed.

Findings offer brand managers the potential for cost and time savings but emphasise the strong effect of AI technology on perceived brand authenticity and brand attitude.

Results show that brands can afford to be transparent in disclosing the use of AI to support brand voice as communicated in product description or specification or in chatbot text.

This research explores the differential effects of pixel-level and object-level visual complexity in firm-generated content (FGC) on consumer engagement in terms of the number of likes and shares, and further investigates the moderating role of image brightness.

Drawing on a deep learning analysis of 85,975 images on a social media platform in China, this study investigates visual complexity in FGC.

The results indicate that pixel-level complexity increases both the number of likes and shares. Object-level complexity has a U-shaped relationship with the number of likes, while it has an inverted U-shaped relationship with the number of shares. Moreover, image brightness mitigates the effect of pixel-level complexity on likes but amplifies the effect on shares; contrarily, it amplifies the effect of object-level complexity on likes, while mitigating its effect on shares.

Although images play a critical role in FGC, visual data analytics has rarely been used in social media research. This study identified two types of visual complexity and investigated their differential effects. We discuss how the processing of information embedded in visual content influences consumer engagement. The findings enrich the literature on social media and visual marketing.