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The manuscript aims to introduce the managerial practice of content recycling – that is, a firm's recycling of its posts on social media platforms. I define and distinguish the phenomenon from related ones and offer propositions for future research to test empirically.

Review of the practitioner literature, in-situ observations with content managers, and a survey of content managers and Facebook users.

Managers recycle their posts to recoup the costs of content. Under some conditions, recycled content may yield more benefits than costs.

I define the phenomenon of content recycling and differentiate it from related terms. I offer propositions for future research.

I inform managers of the benefits and costs of recycling content and conditions under which benefits may override costs.

The research is novel and helps develop a common managerial practice.

This research examines how universities enhance the virality of their social media messages among students. Specifically, we explore whether and how positive affective content in universities’ social media posts can influence sharing behavior. We also investigate the mediating roles of perceived effort and positive emotional reaction, as well as the moderating effect of visual content (i.e. photos).

Drawing upon the emotions as social information model, we conducted (1) an online experiment (N = 222) and (2) text analysis of 1,269,798 Twitter posts extracted from the accounts of 94 UK universities over 11 years (2010–2020) to test our hypotheses.

The findings show that social media posts containing positive affective content encourage sharing behavior and the relationship is mediated by both perceived effort and positive emotional reaction. An additional finding suggests that the use of visual content (photos) strengthens the relationship between positive affective content and sharing behaviors through an interaction effect.

This study contributes to the scant research focusing on positive affective content in the higher education context. The findings shed light on how universities could create social media communications that engage current and prospective students.

Everyday users of professional networks such as LinkedIn are flooded by posts presenting the achievements of their connections (e.g. I got a new job/award). The present research takes a self-discrepancy perspective to examine the mixed-emotional and behavioral consequences of viewing such idealized self-promotional content on professional networks.

The emotional and behavioral consequences following viewership of idealized self-promotional content on LinkedIn are explored through one pilot study (N = 109) and one online experiment (N = 714), which is evaluated using structural equation modeling.

Viewership of idealized self-promotional content on professional social networking sites acts as an emotional double-edged sword for LinkedIn users. Users feel both dejection and symhedonia (i.e. happiness for others), dependent on their reported career-based self-discrepancy. We find the experience of symhedonia to be bound by the relational closeness of the poster (acquaintance vs close friend). Furthermore, we show how resultant emotions drive self-regulatory compensatory IT-use behaviors (i.e. direct resolution, fluid compensation, dissociation, and escapism).

We offer four distinct contributions. Firstly, we disentangle inconsistent findings of mixed emotions by introducing symhedonia to IT literature. Secondly, we investigate the boundary condition of relational closeness. Thirdly, we extend our findings by investigating compensatory-consumption behaviors that stem from mixed-affective outcomes. Finally, we do so in the context of professional networks, which are greatly understudied and are distinctive from personal networks. Practical implications are discussed.

The purpose of this study is to address the surging reliance on influencer marketing in evolving business models, focusing on a novel approach – the influencer e-commerce storefront. This study investigates various influencer advertising disclosures, social media activities and their impact on consumer engagement and sales within the influencer e-commerce storefront.

Secondary data was collected on 734 influencers from an e-commerce website based on “influencer” storefronts, and the influencer’s social media activity and content were collected from Instagram. Two-stage seemingly unrelated regression model was used to examine the research model.

Influencer social media use, encompassing daily posts, story posts and average comments, positively influences consumer engagement and sales on influencer e-commerce storefronts. Notably, the study reveals that different advertising disclosure languages yield varying effects. Unclear disclosures (e.g. branded Highlights) positively impact engagement and sales, while obvious disclosures (e.g. “Sponsored Ad”) negatively affect both.

The study contributes to Persuasion Knowledge Theory, examining influencer e-commerce storefronts and revealing the persuasive impact of undisclosed language in advertising. This study innovatively explores the effects of obvious and undisclosed sponsorship on coping mechanisms, offering insights into consumer reactions. The recommended use of undisclosed language suggests that ambiguity can enhance ad persuasion, guiding practitioners in crafting more effective messages. Moreover, the study extends co-creation theory and service-dominant logic by underscoring the significance of influencers’ social media engagement in co-creating value for consumers. Influencers’ active engagement on social media fosters co-creation, strengthening connections and boosting consumer loyalty.

This research aims to understand the dynamics that drive consumer engagement of multinational brands' social media posts on platform X, formerly known as Twitter. Taking the emotional tone of posts into account, the effect of vivid, interactive, informative, entertaining and practical features of posts on consumer interactions are evaluated across English- and Turkish-speaking markets.

Inspired by the conceptual framework proposed in previous literature, features were extracted computationally using natural language processing from platform X posts of 33 Fortune 500 brands from various industries from June 2016 to June 2021. Following evaluation of regression models on alternative distributions of the dependent variable, which is total number of likes, shares and comments, random subspace regression using bootstrap resampling was applied to calculate an importance score and evaluate the effect of features.

Consumers in English- and Turkish-speaking markets perceive and engage with content differently. While informative and entertaining posts resonate more with English speakers, emotions play a broader role for Turkish speakers. English-speaking audience prefers happy and vivid daytime messages with questions, while Turkish-speaking audience is drawn to angry messages, lean toward nighttime posts.

This research is a pioneer to evaluate the factors that influence brands' platform X post engagements across markets of different cultural orientation. Beyond assessing the distinctions in brand post elements, the role of emotional content in brand messages were also analyzed across English- and Turkish-speaking markets.

The purpose of this paper is twofold: first, to propose a methodology to empirically investigate the longitudinal development of social media content concerning buildings characterized by iconic architecture and second, to report on the application of this methodology.

We collected and analyzed empirical data of social media content shared via Instagram between 2011 and 2019 on 16 buildings that can be considered iconic architecture projects. Using an automated pipeline, we collected and processed 264,000 posts and 140,000 images from Instagram for the selected case studies. By studying the posting activity of Instagram users through time series analysis and conducting content analysis of the social media posts by means of both image classification and topic modeling, we report on the development of users’ capturing and reception of the selected case studies on Instagram over time.

First, we identify two distinct time patterns of social media content: instantly popular buildings whose popularity fades over time and buildings that gradually gain popularity over time. Second, we distinguish differences in the content of social media posts: some buildings are primarily covered for their architectural features and others for their cultural function and facilities.

Using empirical investigation of Instagram data on iconic architectural projects, we have identified a correlation: buildings primarily posted for their architecture are generally also the ones to gain instant online popularity that subsequently faded over time. In contrast, buildings primarily posted for their function and facilities slowly gained popularity on the social media platform over time.

The study explores the impact of food influencers on consumer behaviour in the social media context. It assesses the interplay between the number of followers an influencer has and the type of content this influencer communicates to the audience. Doing so, the research contributes to the strategic refinement of influencer marketing practices, especially in the food industry.

The study employed an experimental between-subject design 2 (influencer type: micro vs macro) x 2 (content type: informational vs entertaining). It recruited 197 Prolific participants (45.7% female, Mage = 45.076), testing their perceptions towards the influencer and the endorsed product in the social media post.

There was a significant interaction between influencer type and content type on consumers’ attitudes towards and their willingness to buy the advertised product. Specifically, the notion that “the more followers, the better” may only be applicable when consumers peruse the content for entertainment purposes, whereas while they read it for information purposes, a micro influencer (with hundreds to thousands of followers) may have as much impact on consumer behaviour as a macro influencer (with hundreds of thousands to a million followers).

Our findings offer a nuanced understanding into the conventional wisdom that people often follow crowd behaviour. Using the Heuristic-Systematic Model (HSM), we explicate when the number of followers matters and when the content type prevails.

In a dynamic, continuously evolving sports landscape, social media have become an indispensable tool for sports organizations to cultivate meaningful connections with fans. The rapid pace of technological advancements has elevated these digital platforms from a supplementary role to a pivotal position within strategic management frameworks. The existing literature explores how football clubs can utilize social media, but analyzing social media strategies within the context of football leagues is lacking. The absence of comparative studies benchmarking clubs across different geographical regions while simultaneously analyzing multiple social media platforms is especially noteworthy. In this study, a comprehensive analysis of social media engagement is undertaken within esteemed football leagues spanning Europe, South America and North America.

Drawing on relationship marketing and employing content analysis as a methodological tool, the study examined 10,772 posts from the official accounts of eight football leagues on Facebook, Twitter and Instagram.

Across the leagues, the findings reveal that content quality drives engagement more than frequency. In addition, several format combinations were identified that facilitate engagement and Instagram emerged as the top social media platform for generating fan engagement.

This is one of the first empirical studies focusing on optimizing the use of social media to amplify fan engagement across various geographies and social media accounts and formats simultaneously.

This study aims to investigate the use of voluntary disclosure on mainstream social media platforms to examine strategic responses to the COVID-19 pandemic. It examines the influential factors and institutional pressures organisations faced when making disclosures on social media during the pandemic.

A two-stage qualitative approach was adopted. Stage one used content analysis to examine voluntary disclosures made by international organisations on social media during the emergence of the COVID-19 pandemic. Stage two comprised semi-structured interviews with individuals who were involved in the decision-making process around the social media disclosures.

This study’s findings reveal significant changes in disclosure practices due to COVID-19-related pressures. In addition to the utilisation of social media for signalling conformance with new pandemic-related norms and connecting with stakeholders, the evidence also reveals how organisations made use of strategic responses to COVID-19-related institutional pressures.

The findings reveal how social media was used as a means of timely voluntary disclosure during the examined crisis. The findings can inform the development of organisational guidelines and policies for the use of social media as a disclosure medium.

This study reveals how organisations used voluntary disclosure on social media as a strategic response to institutional pressures and the COVID-19 pandemic; this context is under-researched. The study also extends the application of the strategic response framework regarding voluntary disclosure via social media.

This study aims to investigate the influence of the reviewed establishment’s price level and the user’s social network size and reputation status on consumers’ tendency to post more visual imagery content. Furthermore, it explores the moderating effects of user experiences and geographic distance on these dynamics.

This study adopts a multi-method approach to explore both the determinants behind the sharing of user-generated photos in online reviews and their internal mechanisms. Using a comprehensive secondary data set from Yelp.com, the authors focused on restaurant reviews from a prominent tourist destination to construct econometric models incorporating time-fixed effects. To enhance the robustness of the authors’ findings, the authors complemented the big data analysis with a series of controlled experiments.

The reviewed establishments price level and the users reputation status and social network size incite corresponding motivations conspicuous display “reputation seeking” and social approval motivating users to incorporate more images in reviews. “User experiences can amplify the influence of these factors on image sharing.” An increase in the users geographical distance lessens the impact of the price level on image sharing, but it heightens the influence of the users reputation and social network size on the number of shared images.

As a result of this study, high-end establishments can increase their online visibility by leveraging user-generated visual content. A structured rewards program could significantly boost engagement by incentivizing photo sharing, particularly among users with elite status and extensive social networks. Additionally, online review platforms can enhance users’ experiences and foster more dynamic interactions by developing personalized features that encourage visual content production.

This research, anchored in trait activation theory, offers an innovative examination of the determinants of photo-posting behavior in online reviews by enriching the understanding of how the intricate interplay between users’ characteristics and situational cues can shape online review practices.