Journal of Innovations in Digital Marketing


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Eva Lahuerta-Otero

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Research Article

Investigating the Nexus Between the Types of Advertising Messages and Customer Engagement: Do Customer Involvement and Generations Matter?

Table Of Contents


Through the theoretical lenses of the Elaboration likelihood model, this research develops an experimental study to examine the cause-and-effect relationship of two advertising message types, drawn from the two routes of persuasion (peripheral route and central route), on consumers’ online brand-related activities (COBRAs) and its three key behavioral types of customer engagement, namely, consuming, contributing, and creating. The moderating effect of generations and the mediating role of personal relevance (involvement) were investigated in the proposed research model. Drawing on a sample of 202 students from a University in North Cyprus, the results of the study revealed that consumer engagement level differs between the two message types, in particular, when the cognitive copy ad is shown, the three COBRA engagement levels tend to be higher than when the emotional copy is given. The findings indicate different levels of personal relevance between the two messages with higher involvement in the cognitive appeal. Further, consumer generation served as a moderator in the study, and that people from generations X, Y, and Z evaluated the advertising stimulus differently. The findings of this research extend the literature with theoretical and managerial contributions to social media marketing.



Do generations evaluate advertising messages on social media differently? Do their engagement levels differ? Does using different message strategies impact consumers’ social media engagement behaviors in different ways? Both practitioners and scholars in the marketing field are trying to find answers to these enduring questions. According to Facebook, copy text is the second key element of an advertisement that users look at. Marketers consistently acquire new techniques when preparing their advertisements to create persuasive and rich social media content. Nowadays, advertisements on social networking sites (SNS) such as Facebook play a crucial part in increasing sales, brand awareness, and engaging customers. Facebook alone has around 2.7 billion monthly users (Statista, 2020) ; this figure accounts for 35% of the world population, with people of different ages and generations, are being exposed to various advertisements every day. In 2020, more than 3.6 billion individuals were actively using social media around the world. This number is estimated to grow in 2025 to around 4.41 billion (Statista, 2020).

Social media usage in everyday life has notably increased in the past years (Dwivedi et al., 2021) . Social networking platforms such as Facebook and Instagram, among other websites, link businesses to a pool of customers, where they can easily interact with the brands through various channels (Lemon & Verhoef, 2016; Weiger, Hammerschmidt, & Wetzel, 2018). Advertisers’ efforts are escalating to create content that engages users by implementing various tactics to creatives’ visual assets, copy text, and call to action to grab users’ attention and increase engagement levels, whether they were post likes, comments, or shares, when customer engagement increases, sales will increase too (Manchanda, Packard, & Pattabhiramaiah, 2012) and hence, assists in building better relations with consumers (Ma, Sun, & Kekre, 2015). Customer engagement is an essential key performance indicator of advertisements effectiveness on social media; therefore, marketers nowadays are highly interested in

growing their digital advertisements engagement rates (Weiger et al., 2018). However, advertisers now face greater challenges in creating content that drives higher engagement levels with the increased competition on social network sites (Erskine, 2018).

The competition is increasing, and brands heavily rely on social networking platforms through exposing customers to numerous advertisements daily. Nevertheless, only those creatives with effective copy ad that grabs the user’s attention are the ones that achieve the required results. (Dwivedi et al., 2021) proposed that Digital content marketing (DCM) creates an opportunity for marketers to achieve better results with their advertisements in today’s digital environment. The researchers stated that “DCM has the ability to grab consumers’ shorter attention spans in the environment of multi-screen and multitasking where consumers are exposed to a higher quantity of media in a lower quality of time.” (p.11); They also suggested that content marketing significantly impacts the effectiveness of the marketing message. Moran, Muzellec, and Johnson (2019), discussed that content marketing in terms of message types is becoming an essential consideration for researchers. While (Lee, Hosanagar, & Nair, 2016) and Stephen, Sciandra, and Inman (2015) explained how consumer engagement levels are affected by the advertising message, taking into account the copy ad’s length, tone, appeal, and type. However, there is still very little research and practical guidance about this topic in the literature.

According to Weiger et al. (2018), previous research on persuasive marketing techniques has not been reliable. The study of Dwivedi et al. (2020) highlighted that using emotional appeal in the content message improves brands’ equity and competitive advantages. In contrast Lee and Hong (2016) argued that informative message type was more effective than the emotional appeal, Moreover, Lee and Hong provided insightful information about the use of elaboration likelihood model (ELM) and how peripheral route (emotional appeal) and central route (informativeness) could be perceived by the users. Also, recent studies (Cheung, Pires, III, & Oliveira, 2021; Liu, Shin, & Burns, 2019; Piehler, Schade, Kleine-Kalmer, & Burmann, 2019; Schivinski, Christodoulides, & Dabrowski, 2016) investigated consumers’ online brand-related activities (COBRAs) and their three key behavioral types of customer engagement, namely, consuming, contributing, and creating. However, these studies lack focus on which message type, considering the ELM theory classification, would work best in generating higher engagement levels on social media. Thus, this leaves us with a crucial question: which social media message type has the most effect on customer engagement levels, and under what conditions do we achieve the wanted results from the digital advertisements? Unfortunately, literature provides the little answer to this enduring question.

The purpose of this experimental study is to explore the relationship between personal relevance, also referred to it as involvement in the literature, and advertising message types on engagement levels (consuming, contributing, and creating) using the stimulus-organism-response (SOR) framework. Also, this research intends to evaluate whether the message of the advertisements has the same or different engagement effects on generations X, Y, and Z. The theory of this study will be based on valuable insights from the ELM postulation and the SOR framework to investigate the relationships and differences between the variables.

Literature review

Academic literature indicates inconsistencies in the findings regarding the effects of advertising messages on consumer engagement (Tafesse & Wien, 2018). The impact of social media (emotional and rational) message context on consumer engagement have been addressed by studies (Dolan, Conduit, Frethey-Bentham, Fahy, & Goodman, 2019; Lee et al., 2016; Weiger et al., 2018), and among others; the researchers suggested the importance of furthering research in this area to aid the understanding. Nonetheless, these studies lack to provide how customers’ generations, in particular, Gen Y, and Z react to social media posts, and which customers from these generations appeal to peripheral or cognitive route when evaluating the advertisement’s message. Further, Lee, Hosanagar, and Nair (2013) discussed that with the rapid growth of content marketing, digital marketers’ efforts and spending increase to attract consumers; however, these attempts will fail if the social media content is not effectively designed to generate customer engagement.

Elaboration likelihood model (ELM)

One of this research’s theoretical backbones is the ELM proposed by Petty and Cacioppo (1986). The ELM framework theorizes the attitude change caused by persuasive communication methods. Petty and Cacioppo, in their theory of persuasion, explained how the quality of the message argument is processed, analyzed, and elaborated on by recipients and what makes the context of a message persuasive; elaborating on the content of a message is seen as “the degree to which individuals evaluate the issue-relevant arguments contained in a message” (p.6), they suggested that “elaboration likelihood” is considered at its highest levels when individuals put effort to relate to and are motivated to think about the issue presented in a message. The researchers viewed elaboration as the process from which individuals hold no thoughts about a subject to developing complete elaboration of the message content. Moreover, The ELM implies that people tend to process the information presented to them by either looking at the argument’s strength or other cues.

The degree to which a message is considered persuasive depends on how the content is processed by the receiver (Petty et al., 1986). The ELM framework proposes two main routes to persuasion that form and alter the receivers’ attitude: the central and peripheral. The first type of persuasion, the central route, is associated with the consumers’ rational thinking about the message content. Some of the examples of central cues in advertising message content include product details (Petty, Cacioppo, & Schumann, 1983), and rational appeals (Heinze, 2010). Also, words, written material, and texts that are contained in the advertising message are another critical aspect that interests individuals using the central route (Morris, Woo, & Singh, 2005).

On the other hand, the peripheral route processing, as the name implies, this type of persuasion uses peripheral cues such as humor, emotions, and credibility of the persuader (Limbu, Huhmann, & Peterson, 2012). Under this route, individuals are influenced and persuaded by factors other than the message's context (Lee et al., 2016; Limbu et al., 2012). This form of persuasion occurs due to some message cues that include the advertisement's attractiveness, celebrity endorsers, or credibility (Heinze, 2010; Petty et al., 1983). These factors work as a negative or positive stimulus that leads consumers to change their attitude without scrutinizing the merits of the argument (Petty et al., 1986). Petty and Cacioppo, suggested, when the likelihood of elaboration is high, information processing and persuasion take the central route, whereas, when elaboration is low, individuals are persuaded as a result of evaluating the content using the peripheral route.

Tafesse et al. (2018) and Wu and Wang (2011) categorized the advertising message into three main types, which are informational, transformational, and interactional, where the informational message type presents factual and clear information about the products or services promoted, where the users engage in a rational thinking process to assess and analyze the message’s content under this type; while the transformational content, in which emotional cues and focuses will be used on the products or services’ hedonic and symbolic features. This type is identified with the psychological experiences that users connect with when evaluating the social media post (Laskey, Day, & Crask, 1989). The last form, the interactional message strategy, is related to actively connecting with the consumers through social media (Tafesse et al., 2018). The first two strategies are the focus of this study (informational and transformational); these content message types follow the ELM categorization of central route processing and peripheral route processing, respectively. Additionally, Wu et al. (2011), classified the message appeals in their research to rational and emotional appeal; the former refers to when consumers cognitively think about the product or service benefits, whereas the latter refers to the positive or negative emotions that users experience.

For a solid theoretical foundation and background and to better hypothesize the relationship between the variables, the mass media content categorization of the uses and gratification theory (UGT), introduced by Katz and Foulkes (1962)Katz and Foulkes (1962), is examined. The ELM’s two routes of persuasion confirm with the classification introduced by UGT theory. Dolan et al. (2019) used the UGT to divide social media message content into two rational appeals; informative and remunerative content, and two emotional appeals: entertaining and relational content, they anticipated that these four types would gratify customers motives to take part in social media engagement behavior.

Katz et al. (1962) in their study about the UGT theory, discussed how and why people use the media to fulfill and satisfy their needs. It postulates how people deal with the media, rewards rather than what the media does to people (Ko, Cho, & Roberts, 2005). This theoretical approach focuses on the role of the audience when creating the message’s content (Dolan et al., 2019). Additionally, Cordero-Gutiérrez (2018); Lemon et al. (2016) in her research explored the use of the UGT theory in the context of social networks to understand the intentions of users’ behavior; therefore, this approach is seen to be consistent with the purpose of this study to gain a thorough understanding of the classifications of advertising message types.

Stimuli-Organism-Response Framework (SOR

This study applies the principles of the Stimuli-Organism-Response framework (SOR) (Mehrabian & Russell, 1974) to examine consumers’ engagement behavior through cognitive and emotional stimuli (S), that causes the internal feeling of involvement (O) which, in turn, result in a social media engagement response (R). Scholars have widely used the SOR model in the retail shopping environment and online shopping to predict consumers’ purchase behavior (Chopdar & Balakrishnan, 2020; Hetharie, Surachman, Hussein, & Puspaningrum, 2019; Peng & Kim, 2014), as well as in investigating customer engagement behaviors on social media (Blasco-Arcas, Hernandez-Ortega, & Jimenez-Martinez, 2016; Carlson, Rahman, Voola, & Vries, 2018; Iraqi, Zohaib, & Mohammad, 2017; Zhang, Lu, Wang, & Wu, 2015). Figure 1 presents the conceptual research model that incorporates the research framework of the hypothesized relationships and the moderating role of generations and customer involvement as a mediator.

Advertising message types as environmental stimuli (S)

Scholars associated different terms to the advertising message types concepts such as central route or cognitive processing (Hollebeek, Glynn, & Brodie, 2014; Petty et al., 1986; Petty et al., 1983) informational (Barreto & Ramalho, 2019; Lee et al., 2016; Tafesse et al., 2018), and rational appeal (Dolan et al., 2019; Wu et al., 2011). However, all these terms combine a general meaning and indicate that customers objectively process the message context. At the cognitive appeal, people are highly motivated to analyze the content, and they tend to evaluate specific features of the advertisement such as product or service-related details, benefits, and qualities (Dolan et al.,). On the other hand, the terminology peripheral route (Petty & Cacioppo), transformational (Tafesse & Wien), and emotional appeal (Dolan et al., 2019; Lee et al., 2016; Wu et al., 2011), refer to posts that induce psychological cues that prompt the consumers’ positive or negative emotions. The emotional appeal involves message cues such as humor, fear, guilt, entertainment, and others (Lee et al., 2016). Researchers implied that when people’s ability to evaluate a message is low, the peripheral route occurs (Petty et al., 1986). Figure 1. Illustrate the conceptual research model.

Advertising messages are considered digital stimuli that grab users’ attention and provide the information they seek about the promoted product or service (Chen et al., 2020; Wang, Chen, Ou, & Ren, 2019). Chen et al. (2020) asserted that it is essential for businesses to understand how to use these marketing message types on social media, and hence, they can gain better results from their marketing campaigns. Therefore, copy ad content that encompasses cognitive processing (central route), or emotional appeal (peripheral route) are considered as environmental stimuli in this study which will result in different engagement levels (Pentina, Guilloux, & Micu, 2018).

Prior research indicated inconsistencies in the literature regarding how these types affect SMEB, some scholars argued that advertising that contains information about the product would interest SNS users more than other types (Reinartz & Saffert, 2013; Taylor, Lewin, & Strutton, 2011). On the contrarily, (Alhabash et al., 2013; Dolan et al., 2019) implied that message effectiveness relies on the usages of emotional appeals in the context. However, Lee et al. (2016) presented in their findings that emotional appeal failed to hold to the argument while informativeness proved to be effective. Furthermore, Chen et al. (2020) noted that a marketing message that contains informative content positively impacts consumers’ purchase behavior. Tafesse et al. (2018) reported that transformational messages (emotional appeal) have a more significant impact on consumers than informational types. As a result of these conflicting arguments, the following variables are hypothesized as:

H1: The advertising message types (cognitive vs. emotional) differ in their effect on consumer engagement (consuming, contributing, creating).

Personal relevance (involvement as a customer’s organism state (O)

The SOR framework, in Figure 1, illustrates that the impact of environmental stimuli on consumers’ engagement behavior is mediated by their internal state of feeling personally involved with the message. The term involvement was called in several variations in the literature. For instance, Sivacek and Crano (1982) identified the term as “vested interest”. Other scholars described it as “issue-involvement” (Kiesler, Collins, & Miller, 1969), “personal involvement” (Sherif, Kelly, Rodgers, Sarup, & Tittler, 1973), and “intrinsic importance” (Sherif & Hovland, 1962). Petty et al. (1986) labelled the term involvement as “personal relevance,” and they defined it as the degree to which an issue has personal significance to the individual.
Figure 1: Conceptual model

Moreover, researchers reported various definitions for the concept of involvement, most notably; the one developed by Mitchell (1979, para. 23) “involvement is an internal state variable that indicates the amount of arousal, interest, or drives evoked by a particular stimulus or situation.” Mittal and Lee (1989) defined involvement as the interest in a specific goal. They highlighted that it plays a critical part in understanding consumers’ behavior and mediating the impact of product and brand-related decisions such as persuasive messages and word-of-mouth. Also, the ELM argued that involvement is one of the most critical variables that affect an individual’s ability to elaborate on a message.

Petty et al. (1986) addressed in their ELM theory that involvement or relevance can be assessed from different aspects such as the level, duration, and the number of relatable objects in the matter. Petty and Cacioppo, argued that people would remain involved with some issues for longer periods than others. Further, the researchers proposed that involvement can be categorized based on its level: low versus high involvement. According to ELM theory, the central route or cognition appeal is more important in high involvement situations, whereas peripheral cues or emotional appeal plays a critical part when involvement is low (Petty & Cacioppo). The ELM theory suggested that individuals who are highly involved with a message will be motivated to process and analyze the argument’s issue, and thus, the central path is taken. In contrast, Petty and Cacioppo stated that if recipients are uninvolved and unable to process the content, in that case, the peripheral route is followed. Moreover, prior literature in this field asserted that low and high levels of involvement impact how messages are evaluated and how the receiver responds to advertising stimuli (Barreto et al., 2019; Dholakia, 2001). L Lahuerta-Otero, Cordero-Gutiérrez, and Prieta-Pintado (2018), identified how different message elements in high and low purchase involvement situations in the context of social networks will affect users' re-tweeting behavior and how it leads to EWOM. Although the literature offers ample studies about involvement, yet little do we know about the role of involvement as a mediator in social media marketing literature. B Barreto et al. (2019) urged the need for more research about how the different types of posts promoted by brands affect users and if consumers’ relevance level mediates that impact. Given these findings, the following is hypothesized:

H2: The advertising message types (cognitive vs. emotional) differ in their effect on personal relevance (involvement).

H3: Personal relevance (involvement) mediates the relationship between advertising message types and customer engagement (consuming, contributing, and creating).

Customer engagement as a response (R)

Prior literature implied that consumer engagement and involvement are related, in which for engagement to occur, other factors such as involvement must exist (Gligor, Bozkurt, & Russo, 2019). R Rosado-Pinto and Loureiro (2020) highlighted that involvement is a construct of engagement. Involvement is noted as a cognition state, whereas engagement has broader dimensions (So, King, & Sparks, 2014). Other researchers as well discussed the relation between involvement and engagement (Barreto et al., 2019). Consumer engagement behavior is seen as a result of the extent of consumers’ involvement level, it points out important aspects such as how much product-related information users need to make a response (Hollebeek et al., 2014). Nevertheless, the main difference between the two concepts is that involvement refers to consumers internal feelings, values, and interest (Zaichkowsky, 1994), whereas consumer engagement is a behavior occurs as a result of motivational drivers (Barreto et al., 2019). Therefore, in applying the SOR model, consumer engagement is regarded as a response (R) such as measured in (Carlson et al., 2018; Iraqi et al., 2017).

The concept of customer engagement has been addressed in several definitions in the literature. For example, Hollebeek et al. (2014) defined customer engagement as a consumer’s cognition, affective, and behavioral activities when interacting with a brand. Doorn et al. (2010) referred to customer engagement as a result of motivational drivers that stimulate certain engagement behaviors other than purchase decisions. (Barger, Peltier, & Schultz, 2016) viewed social media engagement behavior as “a mutually beneficial process through which firms and consumers co-create brand-related content and social experiences on social media”. Moreover, several researchers measured consumer engagement on social media platforms as the act of clicking, liking, commenting on, or sharing the brand’s content (Kim, Spiller, & Hettche, 2015; Moran et al., 2019; Weiger et al., 2018).

The most notable conceptualization of customer engagement behavior is the consumers’ online brand-related activities (COBRAs) proposed byMuntinga, Moorman, and Smit (2011) and Shao (2009) and its three behavioral dimensions related to social media online content that was further developed by Schivinski et al. (2016) to measure customer engagement (Cheung et al., 2021; Liu et al., 2019). According to Muntinga et al. (2011), COBRA entails three types of online CBE: consuming, contributing, and creating. These behaviors are categorized based on consumers’ engagement levels ranging on a continuum of minimum, medium, and high levels, respectively (Piehler et al., 2019). For instance, when people view pictures, watch videos, or read comments of a product shown on a brand’s SNS, they are considered as passive consumers- the least active or at the minimum level of engagement- of brand-related activities (Schivinski et al., 2016). At the medium level (moderately active), Muntinga et al. (2011), implied that people engage with the social media page by, for example, liking or commenting on a post. Hence, users will move from the consuming to the contributing stage. Finally, creating is perceived as the highest (most active) level of engagement; this stage occurs when customers publish user-generated content (UGC) such as uploading pictures and videos or writing articles, blogs, and product reviews (Liu et al., 2019). Overall, following (Cheung et al., 2021; Liu et al., 2019; Piehler et al., 2019; Schivinski et al., 2016), these three behavioral COBRA typology dimensions are used as a measure of customer engagement in this research.

The emergence of SNS allowed consumers to interact with the brand’s digital content in new ways with a greater focus on social media engagement behavior (Kabadayi & Price, 2014). Customer engagement received extensive interest from both academicians and practitioners as an important key performance indicator of a brand’s performance (Barreto et al., 2019; Dolan et al., 2019; Gligor et al., 2019; Su, Mariadoss, & Reynolds, 2019; Tafesse et al., 2018). In addition, Kumar and Pansari (2016) highlighted that it is essential to engage users with the brand’s content to achieve a competitive advantage. It is asserted that brands’ digital content affects consumers’ engagement levels; however, few studies have investigated the impact of message types and strategies on consumer engagement (Dolan et al., 2019; Pezzuti, Leonhardt, & Warren, 2021).

Furthermore, previous literature lacks limitations in investigating the effects of all three types of COBRA; prior studies focused only on one or two behaviors of this typology (Liu et al., 2019; Piehler et al., 2019). Few of the recent studies examined customer engagement in the context of luxury brands’ entertainment, interaction, trendiness, and customization of social media activities (Cheung et al., 2021; Liu et al., 2019). Nevertheless, no research studies the impact of ELM central and peripheral routes copy ad types on COBRA. Therefore, this study aims to extend the literature by identifying which advertising message strategy drives more engagement and which generation prospects engage more with which type.

Generations X, Y, and Z

The way generations interact with social networking sites gained greater attention from managers in the marketing field in recent years (Heinze, 2010). It is critical to focus on generational cohorts’ segmentations to understand how each segment interacts with brand pages on social media and what drivers push them to engage with its content (Bento, Martinez, & Martinez, 2018). They also emphasized the importance of using generational cohorts to better understand the consumers’ characteristics in each segment. Moreover, Ambrose, Meng, and Ambrose (2020) urged the need for research to examine the drivers of social media use. Therefore, this study will compare the three generational cohorts, generations X, Y, and Z, in terms of investigating how individuals within these groups moderate the impact of the message strategy on social media engagement behavior.

According to the generation cohort theory (GCT), individuals are classified into generations and grouped based on their ages. It is believed that people within these segments share similar beliefs, values, and behaviors (Djafarova & Bowes, 2021). Thus, it is expected that the three generations will react differently to each other when evaluating advertising message types (Bento et al., 2018). This research will follow the generational cohorts’ classification by the Khosrow-Pour (2018) in the Encyclopaedia of Information Science and Technology. Gen X are classified as individuals born between (1965-1980) and Gen Y (also called Millennials) represents those born between (1981-1997), considering that there is little research about Gen Z and following the authors’ classification and hence, for this study, it is assumed that this generation is people born in 1998 and after.

Academic research focused on comparing previous generations’ behaviors, mainly Gen-Xers and Gen-Yers, in different marketing fields (Bento et al., 2018; Eastman & Liu, 2012; Lissitsa & Kol, 2016). However, research investigating the behavior of Gen-Zers members is still new. In reviewing the literature, some differences between these generations were noted. For instance, Millennials and Gen Zers are considered as ‘digital natives, whereas older individuals (Gen-Xers) are seen as ‘digital immigrants’ (Prensky, 2001). Gen Y emerged with the digital era while growing up (Bento et al., 2018), and generation Z was the first generation born and surrounded by digital communication (Djafarova et al., 2021). In their study, Djafarova and Bowes implied that Generation Z is interested in communication with images compared to previous generations who focus on innovative content. This study will add to the gap in the literature in developing an understanding of how individuals from these generations respond to marketing strategies; in addition, the moderating role of generations will be studied. Therefore, the relationship is hypothesized as:

H4: Generation moderates the relationship between advertising message type and customer engagement (consuming, contributing, and creating).

Research Methodology

Data collection procedure

The experimental study was conducted using the SurveyMonkey tool to distribute an A/B testing online link for the survey. The self-administered online survey was distributed by asking students to participate in the study during their online classes. The data collection period lasted for one week, and no incentives or rewards were given for taking part in the study. Additionally, participants were assured of the confidentiality of all information collected in the questionnaire and that no personal identity will be released. In this research, a Facebook page post from a fictitious coffee shop brand called “Infinity Coffee” was used as a treatment for the experiment. To eliminate brand awareness bias fictitious coffee shop setting was used in this study. The researcher developed two variations of messages and displayed them in the survey to participants as an image post on Facebook. One stimulates the emotional appeal through a humorous copy ad (see Figure 2), whereas the other post triggers the cognitive appeal with product information (see Figure 2). The fictitious company’s logo and image were designed by the researcher on Photoshop, and both posts used the same photo and showed the same number of reactions (likes, comments, and shares). In both the pre-test and the main experiment participants were randomly divided into two groups using the A/B testing feature in SurveyMonkey, one group would see scenario A (peripheral route message type), while the other would be shown scenario B (the central route message type).

Sampling method

Before the main experiment, a pre-test was conducted to ensure that subjects were able to recognize the stimulus of the message types central route (cognitive appeal) and peripheral route (emotional appeal) as manipulated in the main study. A total of 39 students from the business faculty at a university in North Cyprus took part in the survey; 38 subjects completed the questionnaire, and 1 incomplete questionnaire was discarded. The sample for the main study comprised a total of 220 undergraduate and postgraduate students which were selected randomly from the business faculty at the same university in North Cyprus. University students were chosen as subjects for this study because of the diverse age groups, allowing the researcher to investigate the impact of message strategies generations X, Y, and Z. Another reason is that the majority of coffee shop visitors in North Cyprus are students. The final sample accounts for a response rate of 92%; consisting of 202 respondents where 18 invalid and incomplete questionnaires were removed. The sample profile is shown in Table 1.

The research questions focus on differentiating and studying the impact of message types on customers’ consuming, contributing, and creating engagement behaviors and analyzing the mediation effect of personal relevance (involvement) and the moderation effect of generations between advertising message type and personal relevance (involvement). Random distribution sampling method was adopted for this study; for hypotheses 1 and 2, the mean and standard deviation were computed for each attribute; emotional message type, cognitive message type, and customer engagement (consuming, contributing, and creating) using SPSS statistical analysis software. Also, the data were analyzed using t-test significance scores to determine if a significant difference occurs between the effect of the two message types on consuming, contributing, and creating engagement behaviors. Lastly, Hypotheses 3 and 4 were tested using PROCESS macro for SPSS (Version 3.5), developed by Hayes (2013). H3 examined the indirect effect of personal relevance (involvement), and H4 investigates the moderating relationship between message type and customer engagement behavior.

Measurement scales

The measurement items used in this study are adopted from previous research, using a measurement construct of a seven-point Likert-type scale that ranged from 1 (strongly disagree) to 7 (strongly agree). To measure emotional appeal, three items were adopted from Carlson et al. (2018); three items to measure cognitive appeal from Lee et al. (2016); three items fromZhang et al. (2015) were used to measure personal relevance (involvement); and six items provided byCheung et al. (2021) were applied to measure the three COBRA engagement behaviors of consuming, contributing, and creating. In addition, demographic questions such as age, gender, and social media usage were added in the last section of the survey (see Appendix A)

Research findings

Manipulation check

The manipulation check results in the pertest indicate that participants’ recognition of emotional and cognitive message types was successful (see Table 2). When the peripheral route stimulus was shown the results revealed that (M peripheral route = 5.55; M central route = 2.96) (SD peripheral route = 1.30; SD central route = 1.64). On the other hand, when the central route stimulus was presented, the measurements resulted in (M central route = 5.98; M peripheral route = 2.67) (SD central route = 1.25; SD peripheral route = 1.55). The mean results of the peripheral route (M = 5.55) and the central route (M = 5.98) are both significantly greater than the median value of 4. The t-test scores show significance in both message types (t (44) = 5.93; p < 0.05 for peripheral route; and t (28) = 6.43; p < 0.05 for central route). Thus, the stimuli of the advertising messages in the pre-test were successfully manipulated which makes it effective to be used in the main experiment.

Table 1: Demographic profile of the sample












Prefer not to say




Gen X



Gen Y



Gen Z



Facebook membership

“Less than 6 months”



“6 months to one year”



“One to two years”



“More than two years”



Facebook usage frequency

“I have never tried Facebook”



“I have used Facebook before, but I am not currently using it”



“I use Facebook at least once a year”



“I use Facebook at least once a month”



“I use Facebook at least once a week”



“I use Facebook daily”



Average time spent on Facebook

“Less than 30 minutes”



“30 minutes to one hour”



“More than one hour”


Figure 2: Scenarios
Table 2: Means and standard deviation of the pilot study: manipulation check

Central route

Peripheral route










Std. deviation






t (28) = 6.43; p < 0.05

t (44) = 5.93; p < 0.05

Note: PR = Peripheral route; CR = Central route

Measurement reliability

The Cronbach's α value was analyzed to ensure the measurement items’ reliability. Personal relevance (involvement) reported reliability score of (α = 0.84); the three-customer engagement behaviors were as follow: consuming (α= 0.90); contributing (α = 0.88); and creating (α = 0.84). The values of all constructs were greater than the acceptable value of 0.70 (Nunnally, 1978); thus, the internal consistency of the model is confirmed to be reliable.

Main experiment results

The first hypothesis (H1) was tested by using t-test statistics to determine the significant difference between the effect of cognitive and emotional advertising messages on the three dimensions of consumer engagement. Comparing the impacts of the peripheral route and central route message types on consuming, the results reported that the groups exposed to cognitive appeal expressed higher consuming behavior (M central route = 5.59; SD = 1.33) than those in the emotional appeal type (M peripheral route = 4.07; SD = 1.70). At 95% confidence interval (CI), the t-test showed statistical significance (t (200) = -6.82; p < 0.001). The results for the engagement behavior of contributing revealed similar significant findings to the ones in consuming, at 95% CI, (t (200) = -6.24; p < 0.001). Participants that saw the central route message will contribute more to an SNS post (M central route = 4.93; SD = 1.66) than subjects in the peripheral route condition (M peripheral route = 3.44; SD = 1.67). As for the last dimension, the t-test scores for the CEB type of creating confirms with the first two types (consuming and contributing) that users engaged more with the cognitive appeal. This is proven through the significant difference between the two copy ads (M central route = 5.13; SD = 1.52) and (M peripheral route = 3.40; SD = 1.65), were t (200) = -7.60; p < 0.001. The overall results of all three types combined together show that central route messages resulted in higher mean (M central route = 5.22; SD = 1.37) as compared to the peripheral route (M peripheral route = 3.64; SD peripheral route = 1.51), and the t-test scores were (t (200) = -7.60; p < 0.001), at 95% CI. Therefore, the findings support hypothesis 1 (see Table 3 and Table 4).

To analyze the second hypothesis (H2) a t-test was conducted (see Tables 3 & 4). The results indicated a significant difference in involvement levels between those who were exposed to the different copy ads (t (200) = -4.41; p < 0.001). In particular, subjects who used the central route to process the message were more involved (M central route = 4.82; SD central route = 1.42) than those who emotionally processed the information in the copy ad (M peripheral route = 3.84; SD peripheral route = 1.63). Thus, these results confirm hypothesis 2.

Table 3: Group statistics results for H1 & H2

Message Type


Std. Deviation

Std. Error

Customer Engagement

Peripheral route




Central route





Peripheral route




Central route





Peripheral route




Central route





Peripheral route




Central route




Personal relevance

Peripheral route




Central route




Table 4: Independent samples test results for H1 & H2







Customer Engagement



< 0.001






< 0.001






< 0.001






< 0.001



Personal relevance



< 0.001



Table 5: The indirect effect of personal relevance





Personal relevance (involvement)





The mediating role of personal relevance (involvement

This research hypothesized that the interaction effects between advertising messages and customer engagement would indirectly affect customer engagement through personal relevance (involvement). Hypotheses 3 was examined using PROCESS macro (Version 3.5), developed by Hayes (2013). The mediating role of personal relevance was tested through the bootstrap tests of the indirect effect, and a bias-corrected 95% bootstrapped confidence interval (N = 5000) was estimated. As shown in Table 5, the indirect mediating effect of involvement was (β = 0.6145, not including zero values at the 95% CI, the Boot Lower CI limit (BootLLCI) = 0.33, and the Boot Upper CI limit (BootULCI) = 0.9320). In other words, the level of personal relevance customers’ feels when processing advertisements on social media mediates their engagement behaviors, thus, hypothesis 3 is fully supported.

The moderating effect of generations

In examining H4 by using PROCESS, the results reported a significant interaction effect between message types and customer engagement (β = 0.8913, p < 0.05). The interaction effect is plotted in Figure 4, which shows that generation Z’s engagement levels are higher at the central route message type as opposed to the peripheral route where engagement is at its lowest. The results from generation X reported similar findings to generation Z, the users engaged more with central route content than the peripheral route. On the other hand, generation Y reported contrasting results than those seen in Gen Z and X. Gen Yers exhibited higher customer engagement with the peripheral route message type. Hence, hypothesis 4 is supported. Figure 4 illustrates the interaction effect of generations.

Summary of the study

Drawing on the theoretical lens from the Elaboration Likelihood Model (ELM) proposed by Petty and Cacioppo (1986)Petty et al. (1986), this research developed an experimental model to examine the cause-and-effect relationship of two social media advertising message types; peripheral route and central route, and to investigate the mediating role of personal relevance and moderating effect of generations. Giving the inconsistent findings in literature as to which message type generates higher customer engagement levels (Tafesse et al., 2018), the findings of the study revealed that people engaged more with the central route message stimuli.
Figure 3: The interaction effect of generations

These posts trigger the reader’s cognitive thinking, motivating them to view pictures or videos, comment or write reviews, and share and publish blogs about the brand. Additionally, the study shows how a person’s generation influence the level of engagement; in particular, those from generation Z and X showed higher engagement with cognitive appeal as compared to generation Y. Further, the results demonstrate that involvement indirectly impacts the effect of emotional and cognitive copy ads on SMEB.

Theoretical contributions

Several studies have explored customer engagement drivers (Dolan et al., 2019; Hollebeek et al., 2014; Moran et al., 2019; Tafesse et al., 2018). However, the emergence of this research is still new and requires more research (Rosado-Pinto et al., 2020) as there are inconsistencies in the previous literature regarding the treatment of consumer engagement on digital platforms (Pentina et al., 2018). To bridge the gap in the literature, the study is the first to examine the effect of the two message appeals on COBRA, to investigate how generations engage with these copy ads, and how customer involvement explains the impact of the independent variable on customer engagement behavior. Thus, the findings of this research provide substantial insights into consumer engagement and social media literature in several ways. Firstly, the results clarify the different impacts of cognitive and emotional types of copy ads on passive and active COBRA levels, which are consuming, contributing, and creating. Cognitive messages are found to be significantly more effective than emotional messages in generating higher engagement levels from all three behavioral dimensions. These findings align with the results reported byDolan et al. (2019) andLee et al. (2016) that the central route or informativeness outperformed the peripheral route. Additionally, this study extends the social media literature by adopting the new emerging COBRA’s three behavioral dimensions (Cheung et al., 2021; Muntinga et al., 2011; Schivinski et al., 2016), and hence, the study answers important questions such as which message stimuli engage users more.

Furthermore, the mediating effect of personal relevance in the relationship between advertising messages and customer engagement is still under-researched in the marketing literature. Involvement has been identified as an antecedent of engagement that indirectly affects CEB (Rosado-Pinto et al., 2020). Although several studies have explored the role of involvement as a moderator (Limbu et al., 2012; Petty et al., 1983; Wu et al., 2011), however, little attention has been given to its impact as an antecedent that mediates the effect of social media posts on users’ engagement (Barreto et al., 2019). Moreover, Barreto and Ramalho urged the need for research to test the mediating effect of involvement. Therefore, the results of this research shed light on this matter and deepen knowledge of the marketing literature. The findings show that central and peripheral route messages differ in their impact on involvement significantly. In addition, the results indicate that cognitive copy ads have a more significant impact in contrast to copies that use emotional appeal. The study also identified the mediating role of involvement; this means that the stimulus (advertising messages) affects customer engagement through its influence on personal relevance (involvement).

Finally, the study contributes to the literature by clarifying the moderation effect of generations on CE. There are no previous studies that attempted to uncover the interaction relationship of generations X, Y, and Z between message strategies and engagement. The majority of the prior research focused on either X and Y or one of them (Ambrose et al., 2020; Bento et al., 2018; Heinze, 2010). In their paper, Bento et al. (2018), compared Generation X and Y’s brand engagement behavior on social media and suggested that brands must create different types of content when targeting people from these generations. They also highlighted that it is important that the posts prepared to target Gen Yers contain emotional stimuli or present information such as new offers, discounts, and special prices. On the other hand, limited research has investigated the behavior of Gen Zers on social media platforms, as well as there are no previous studies that attempted to uncover the interaction relationship of generations X, Y, and Z between message strategies and engagement. To fill this gap in the literature, the results of this study showed that generation moderated the impact of cognitive and emotional messages on CE. Additionally, the findings provided an understanding of which generations engaged more with which message type, Figure 4, illustrated that both generation Z and X engaged more with the central route while members of generation Y engaged with the peripheral route.

Managerial contributions

The current study provides marketers with managerial implications to guide them when developing message strategies for their social media advertisements. The most important point to note is that marketers can use copy ads that trigger the central route of information processing, or in other words, the cognitive thinking of the readers, thereby increasing customers’ engagement levels on social media platforms. First, the findings revealed that cognitive appeal resulted in higher engagement levels as compared to emotional appeal. Therefore, social media marketers should focus on creating copy ads content that triggers users’ cognitive thinking by presenting product-related information such as specific features, benefits, and prices. Contrasting, copy ads that trigger emotional cues such as humor resulted in lesser customer engagement. Using the cognition persuasion tactic will lead to increasing passive (consuming) and active (contributing and creating) engagement levels on SNS. Managers can also measure their marketing campaigns’ effectiveness with the three behavioral engagement levels based on the extent users view, like, comment, share, write feedback, and create blogs about the brand. Moreover, advertisers could use these findings to help them decide what type of information to present not only on the post’s copy ad but visual creative such as image or video. For example, marketers can add price, location, or other important features related to the product or service on the post’s images.

Second, the results demonstrated the mediating role of involvement on the relationship between the message stimuli and engagement. Marketers should develop advertising strategies by carefully considering the level of involvement consumers hold toward the product or service and how message types, particularly cognitive appeal, increase consumers’ engagement through personal relevance. As B Barreto et al. (2019) highlighted, there is no fixed strategy that all brands can follow to market their products. However, the findings suggest that informative content tends to generate higher engagement levels when involvement levels are high, and hence, implementing this content strategy will lead to favorable results for managers and brands. Third, the research provides insights into how engagement levels differ in people from generation X, Y, and Z when shown cognitive or emotional messages. Social media sites allow advertisers to set up ad settings to target customers based on their age and other demographical aspects, and thereby marketers must understand which message type would result in more engagement on which segment of the target audience. Marketers should consider the significant moderation role of generations when creating their advertisements and adopt the most effective copy ad that will appeal to people from the targeted generation. This study helps practitioners by identifying which message type to use when creating marketing campaigns. The results of this research showed that Gen Xers and Zers engaged more in advertising messages that offer product-related information such as price and features than the humorous copy ad. On the contrarily, Gen Yers showed more engagement with the humorous content. Therefore, social media marketers could achieve better results and successful campaigns by applying these tactics and strategies.

Research limitations and future research directions

This research contributes to the marketing literature by identifying consumers’ engagement responses to advertising stimuli (cognitive vs. emotional) messages on Facebook. Nevertheless, some limitations must be taken into consideration to provide direction for future research. The first major limitation of this study is that the sample size of generation X is relatively small for generalizations. To correct this limitation and to obtain more valid results is by collecting a greater number of participants from this generation segment. The second one is that the experimental design in this study used a Facebook post-stimulus from a fictitious Café that focused on promoting a single product (coffee drinks). Future research using a wider product or service category will contribute with interesting theoretical and practical findings regarding how customers on social media platforms engage with the brand’s content. In addition, researchers may study the impact of advertising messages on different SNS such as Instagram and Twitter. Third, it is worthwhile to replicate the study using actual advertising stimuli and real-world data to obtain the findings; this will improve the external and uncontrolled limitations of this research’s results such as ensuring that all data collected will be from users who are actively using Facebook or have used it before. Also, a self-administered survey lacks the actual Facebook experience and some crucial factors unaccounted for, such as the exact audience size of the brands and Facebook’s algorithm that affects how and when posts are shown to users (Lee et al., 2013; Moran et al., 2019).

Forth, other factors beyond the two ELM routes were not included in this study. In this research, the peripheral route focused only on the humorous aspect, while product features and prices were presented for the central route. The peripheral message type content can include other dimensions that scholars can investigate, such as triggering positive or negative emotions like entertainment or guilt. Further research can also extend this study’s work by testing the different techniques used in copy ads, such as the copy’s length and the usage of calls to action (e.g., buy now, shop online, learn more, etc.). Fifth, the sample Facebook post in this study used a still-image creative. In the future, scholars could test the model of this research using other media types such as videos. Recent studies argued that using videos in advertisements can result in more favorable behaviors than when a single photo ad is used (Lee et al., 2016; Sung & Cho, 2012). Sixth, while the present research focused on online brand-related activities as a response to the advertising stimuli, it is recommended to examine alternative outcomes such as EWOM, online purchase behavior, and brand awareness. Finally, the moderated-mediation effect of generations and personal relevance is not taken into account in this study; this relationship is worth exploring to strengthen this research model. Overall, these future research directions offer abundant opportunities to extend the literature and practice in the social media context.

Funding statement

The author received no financial support for the research, authorship, and/or publication of this article.



Msallati, A., (2021) . Investigating the Nexus Between the Types of Advertising Messages and Customer Engagement: Do Customer Involvement and Generations Matter? . Journal of Innovations in Digital Marketing , 2 (1) 1-18 ,