The Role of Social Media Content Format and Platform in Users' Engagement Behavior
Introduction
Due to the ongoing popularity of social media across the world, firms' social networks are growing at an increasingly rapid pace, intending to build online engagement among their customers (Hallock, Roggeveen, & Crittenden, 2019). Facebook, the most popular social media platform, has recorded a monthly active user rate of 2,375 million in April 2019 (Statista, 2019). Likewise, the number of monthly active Instagram users has increased from 90 million in January 2013 to 1,000 million in June 2018 (Statista, 2019). Correspondingly, social media content directed at customers continues to proliferate as customers' digital spending increases (Malthouse, Calder, & Vandenbosch, 2016). Social media advertising revenue has grown 30.6% in the U.S. in 2018 alone to $28.9b (PwC, 2019). Firms are cognizant of this and are ever-increasingly investing in content creation and distribution within the social space. However, such marketing investments will not succeed unless marketers understand how to effectively create and distribute their content within these platforms to promote their desired outcomes, with one of the most frequently listed desired outcomes being customer engagement (Lee, Hosanagar, & Nair, 2018).
Previous studies (e.g., Gavilanes, Flatten, & Brettel, 2018) have drawn attention to the relationship between social media advertising efforts and the resultant customer engagement. However, the pertinent literature is limited in several ways. For example, much of the earlier research was largely conceptual (e.g., Ashley and Tuten, 2015, Dolan et al., 2019, Dolan et al., 2019), or offered a limited conceptualization of social media engagement behavior, mainly through numbers of likes, shares or comments (e.g., Cvijikj and Michahelles, 2013, De Vries et al., 2012). Our understanding of social media content design was also limited, with earlier scholars using broadly defined and limited content types, such as informational vs. entertaining (De Vries et al., 2012) and employing a singular social media platform to test social media engagement, e.g., Facebook or Instagram (e.g., Gavilanes et al., 2018, Kim et al., 2015, Lee et al., 2018). Also, despite the numerous insights from previous work on the role of content type on users' engagement, very few studies have considered the role of content format, e.g., picture, video, etc. and the relationship with the choice of social media platform (e.g., Facebook vs. Instagram) on predicting users' engagement behavior. Finally, most of the relevant studies employ survey methods to collect primary data (see Voorveld, Van Noort, Muntinga, & Bronner, 2018), yet this is not comparable with actual secondary data.
In response to the aforementioned limitations, this study aims to provide a more in-depth and holistic investigation of this phenomenon by considering: (i) a more thorough range of social media content strategies, specifically 12 content types integrated into three overarching strategies, (ii) the role of the platform type by collecting data from both Facebook and Instagram, and (iii) the role of the content format in terms of richness, i.e., comparing both photo and textual social media posts. To achieve this, we utilize the Facebook and Instagram APIs to capture data of two Pacific Airlines and empirically demonstrate how these different contexts and types of social media content act as drivers of user engagement. By qualitative content-coding of the firms' posts, quantitative sentiment analysis of user comments and regression analysis we connect firms' content management activities to user engagement behavior.
This research provides managers with guidance for developing social media strategies, investigating the distinct effects of social media content (rational, emotional, and transactional) along with content context (platform type and content format), and lag effects between posts on active and passive engagement. In our study, we carefully explore how and why different platform environment will lead to active or passive engagement. Finally, in this study, we consider the important nature of engagement influence by considering possible lag effects between posts, such that the interactivity and engagement generated by one post may have carry-over effects on the engagement level of subsequent posts. In so doing, we go beyond numbers of likes and comments on posts to measure engagement.
The remainder of the paper is structured as follows. First, we introduce the background of the study, namely, the role of social media and users' engagement. Second, we introduce the conceptual model and hypotheses of the study. The research context in which the study is conducted is then presented, followed by an overview of the study design. After presenting the results of the study, we outline the key findings, implications, and important contributions and limitations of the study, leading to a range of ideas recommended for further research.
Section snippets
Users' Engagement
The emergence of social media platforms has dramatically altered the role of customers from passive observers of content, to active participants, who are now the co-producers (Lee et al., 2018) and co-creators of content through their online interactions and behaviors (Dolan, Conduit, et al., 2019). Behavior that reflects engagement with social media includes customers' creation of, contribution to, or consumption of brand-related content within a social network (Hallock et al., 2019, Muntinga
Theoretical Background: Media Richness Theory
Media Richness Theory is a widely known theory of media use which has been applied to multiple fields (e.g., Kaplan and Haenlein, 2010, Liu et al., 2009, Tseng et al., 2017). This theory regards the objective characteristics of media channels which determine their ability to carry information (Tseng et al., 2017). Media richness comprises four dimensions: (i) the ability to use multiple information channels to handle information cues simultaneously, (ii) the ability to facilitate rapid
Research Context
Social media has significantly changed the tourism industry, switching customers' role from passive to active users (Quach & Thaichon, 2017) who search for information, engage in collaborative planning, and memorialize travel experiences through various engagement behaviors, e.g., posting, messaging, and media sharing (Dolan et al., 2019, Zeng and Gerritsen, 2014). Although tourism research in social media context is still in the early stages, scholars (e.g., Luo and Zhong, 2015, Shu and Scott,
Validity Checks
To check the research validity, three different methods have been employed in this study, which are described as follows.
Results
Following the analyses presented in the previous section, we now assess the integrity of each proposed research hypotheses.
The output presented within Table 8 provides strong evidence to support H1, indicating that the format of content, i.e., video (H1a) or photo (H1b) (coded as 0 and 1 accordingly) has a significant effect on different types of engagement behavior. As proposed in H1a, video format posts encourage users to actively engage on fan page by sharing their opinion and comments
Discussion and Implications
Today's business environment has become more interactive, where customers are continuously are engaged with offerings and activities of firms (Dolan, Conduit, et al., 2019). Customers engage for various reasons through various objects, such as product or service offerings (Brodie et al., 2011), media (Calder et al., 2009), activities, and events (Vivek et al., 2012). Although recent research has explored both the antecedents and consequences of customer engagement (Gambetti et al., 2012, Leckie
Limitations and Directions for Future Research
This paper examined the literature of social media content and user engagement to develop an empirical model and related hypotheses which draw upon the theoretical foundations of Media Richness. This framework proposes three main social media content types; rational, emotional, and transactional, and explores how their effects of active and passive engagement behavior are altered by the content context, namely the format and platform. Using a dataset of 1,038 social media posts and 1,336,741
Acknowledgements
We thank Associate Professor Arvind Tripathi (The University of Auckland) for supporting this research financially and useful discussions. Also we thank Professor Ananth Srinivasan (The University of Auckland) for his useful guidance in the methodology section.
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