To comment or not? The role of brand-related content type on social media

Abstract

In recent years, social media platforms have transformed into dynamic spaces for brand-consumer interaction, with commenting emerging as a strategic tool for brands to connect with their audience. This research study aims to examine what types of incentives trigger customers’ engagement in terms of commenting on different brand-related content types on social media. A total of 415 questionnaires were analyzed and a structural equation modeling approach was used to investigate the relationships among communal, self-interest, and reward incentives as independent variables and intentions to comment on commercial, personal opinion, and lifestyle brand-related content on social media as dependent variables. The results reveal that communal and reward incentives positively influence intentions to engage in commenting on commercial, personal opinion, and lifestyle content, whereas self-interest incentives negatively influence intentions to engage in commenting on the three types of analyzed brand-related content on social media. The paper focuses specifically on intentions to comment on different types of brand-related social media content rather than on contributing activities in general. The present study fills the research gaps, concerning the lack of analysis of the influence of different incentives on intentions to comment on different brand-related content types on social media.

Keywords:

• Brands
• content management
• social media
• end users
• consumer behavior
• co-creation

JEL CODES:

• M31
• M37

1. Introduction

Social media usage is an everyday activity of many people worldwide, reaching 3.6 billion users in 2020 with a projection to increase to 4.41 billion in 2025 (Statista, 2022). Customers are becoming important collaborators and contributors in brand communication activities (Li et al., 2021), making brands’ presence on social media ineffective unless it motivates social media users to engage with brands’ content (Weinberg & Pehlivan, 2011). By using social media, consumers exchange brand experiences and opinions among them thus influencing their purchase decisions (Yesiloglu et al., 2021). Therefore, brands need to understand customer engagement to attract new customers and facilitate customer loyalty (Cao et al., 2021).

Research on customer engagement in the social media context has been emerging recently (Dolan et al., 2019), lagging the remarkable practical development (Hollebeek & Macky, 2019). Additionally, there is a lack of consensus on its understanding and definition, and therefore a significant fragmentation of the research streams is evident (Syrdal & Briggs, 2018). After the initial conceptualization of the construct (as a psychological and/or behavioral) (Hollebeek, 2011; Van Doorn et al., 2010) and further operationalization development (Hollebeek et al., 2014; Schivinski et al., 2016), empirical validation of the conceptual models comprising customer engagement and its antecedents and consequences has been emerging (Srivastava & Sivaramakrishnan, 2021). Yet, there is a lack of empirical studies that focus on engagement behavior with brand-related social media content aside from research on customer engagement, in general (Yesiloglu et al., 2021). Based on this research gap, this study focuses on analyzing customer engagement with brand-related social media content, operationalizing it as a behavioral construct (Schivinski et al., 2016). Having in mind the suggestion of Syrdal and Briggs (2018) that the branded content rather than the brand itself is the focal object of engagement on social media, this study comprises different types of content in analyzing customer engagement and its underlying motives.

When referring to the type of brand-related content, only a few studies analyzed it in the context of social media customer engagement, applying different categorizations (Dolan et al., 2019; Fu et al., 2017; Pletikosa Cvijikj & Michahelles, 2013; Shahbaznezhad et al., 2021; Tafesse, 2015). The present study analyzes customer engagement by referring to commercial, personal opinion, and lifestyle affairs messages as different types of brand-related content, as suggested in the study of Fu et al. (2017). The assumption is that customer engagement behavior on social media varies depending on brand-related content type (Shahbaznezhad et al., 2021).

The present study strives to enhance understanding of commenting on brand-related social media content, as a distinct engaging activity. We conceptualize commenting as a contributing activity within the consumers’ online brand-related activities (COBRAs) framework (Muntinga et al., 2011) which proposes three levels of brand-related activities, i.e., consuming, contributing, and creating. Consumption involves customers watching, listening, and reading content; contributing refers to participation in social interactions with liking, sharing, or commenting on content created by others, and lastly, creating involves customers posting their own content for self-expression and self-actualization (Heinonen, 2011; Muntinga et al., 2011).

Although most of the previous studies analyzed contributing activities in general (Buzeta et al., 2020; Dolan et al., 2019; Piehler et al., 2019; Yesiloglu et al., 2021), we assume that a more profound understanding could be achieved if focusing on a specific activity. As suggested by Syrdal and Briggs (2018), there is a vast difference in social media interactive behaviors and their underlying motivations, thus recommending each to be analyzed separately. Namely, although liking, commenting, and sharing are all contributing activities that are analyzed as active forms of moderate level of engagement (Muntinga et al., 2011), there is a distinction among them. So, sharing and commenting require a higher level of effort (Swani & Labrecque, 2020) and are more reflective processes while liking is reflexively done (Swani et al., 2017). Beyond this, commenting includes co-creation activities, e.g., writing comments, engaging in conversation, etc. (Muntinga et al., 2011; Yesiloglu et al., 2021) and when commenting on brand-related content, customers contribute to brand value, exchanging their persuasion and social capital (Li et al., 2021).

In the recent studies of customer engagement (Hollebeek et al., 2019; Li et al., 2021) it is evident the acceptance of service-dominant (S-D) logic of interactivity and co-creation (Vargo & Lusch, 2008, 2016), emphasizing the active role of customers in creating value. Different levels of companies’ inputs in terms of social media engagement initiatives are expected to result in different levels of customers’ social media interactivity (Harmeling et al., 2017) with a focus on enticing active engagement from customers (Buzeta et al., 2020). Therefore, an important question to address is what drives customers’ engagement behavior on social media?

The present study combines Uses and Gratifications (U&G) (Katz, 1959; Katz et al., 1973) and Self-Determination Theory (SDT) (Deci & Ryan, 1985) in explaining what drives customers’ intentions to contribute by commenting on brand-related content on social media, focusing on three types of incentives, i.e., communal (socializing), self-interest (personal) and reward (remuneration) incentives. According to U&G, people actively choose the media and the content they are exposed to, which in turn satisfies their needs (Katz et al., 1973) while according to SDT, the satisfaction of relatedness, competence, and autonomy as psychological needs are essential for arising intrinsic motivation of individuals and self-regulation of extrinsic motivations (Deci & Ryan, 2000).

Based on all the above, the contribution of the present study is severalfold: first, it focuses on customer engagement behavior on social media, a context that still needs to be researched (Yesiloglu et al., 2021). Additionally, this study applies the perspective of customer engagement with brand-related content rather than engagement with the brand in general (as suggested by Syrdal & Briggs, 2018), analyzing three types of content (commercial, personal opinion, and lifestyle). When considering the type of engagement activity, we apply the recommendation of Syrdal and Briggs (2018) to concentrate on a specific activity, focusing on commenting as a contributing activity that is active, reflective, and co-creative. At the same time, based on U&G and SDT we address three types of incentives (communal, self-interest, and reward) which motivate customers’ engagement with different levels of intensity and in different directions. Comprising all the aspects elaborated above, a conceptual model is proposed, and hypotheses are developed which are further empirically tested, applying structural equation modeling (SEM).

2. Literature review

Customer engagement behavior is defined as ‘the customers’ behavioral manifestation toward a brand or firm, beyond purchase, resulting from motivational drivers’ (Van Doorn et al., 2010, p. 253).

Despite the wide research base that focuses on customer engagement (Azar et al., 2016; Buzeta et al., 2020; Cao et al., 2021; Dolan et al., 2016; 2019; Muntinga et al., 2011; Piehler et al., 2019; Schivinski et al., 2016; Yesiloglu et al., 2021) there is still lack of scientific research that focuses only on commenting on brand-related social media content as a specific contributing activity (Syrdal & Briggs, 2018). Aside from liking which is a ‘one-click’ action, commenting requires additional effort and more cognitive resources, thus establishing a two-way interaction and deeper connection between sender and receiver (Swani & Labrecque, 2020). Commenting on posts allows social media users to network and interact with brands and peers (Cao et al., 2021) and to post their opinions, knowledge, experience, and concerns (Hollebeek et al., 2017; Swani & Labrecque, 2020). Beyond social relations, commenting is also driven by self-presentation in terms of expressing and signaling credibility and competence (Swani & Labrecque, 2020).

Most of the previous studies on drivers of customer engagement on social media apply the U&G theory (Azar et al., 2016; Buzeta et al., 2020; Dolan et al., 2016; 2019; Fu et al., 2017; Heinonen, 2011; Muntinga et al., 2011; Palamidovska-Sterjadovska & Ciunova-Shuleska, 2020; Piehler et al., 2019) that focuses on consumers’ motives to use different technology and media and the outcome from those motives. Recent studies identify information, entertainment, social interaction, and remuneration as four U&G motivations influencing COBRAs (Buzeta et al., 2020; Piehler et al., 2019). De Vries et al. (2017) propose a motivation continuum from intrinsic to extrinsic, highlighting entertainment, self-expression, socializing, and remuneration as major drivers of contributing activities on brand-related social media content. However, some studies challenge this, indicating that entertainment is not a significant motivation for contributing (Buzeta et al., 2020; Piehler et al., 2019; Vale & Fernandes, 2018), and commenting on brand-related social media posts (Khan, 2017). Therefore, we focus on three, both intrinsic and extrinsic, motivations (self-interest, socializing, and remuneration) relying on U&G and SDT. Both theories apply a user-centric perspective in understanding how and why people use media, having in mind the complexity and diversity of the drivers. So, based on the U&G (Katz et al., 1973), it is assumed that people are active and goal-oriented in choosing specific media, and gratification of one’s needs has a prominent role in this process. Additionally, SDT suggests that in a social environment that supports the satisfaction of three basic psychological needs, i.e., relatedness, competence, and autonomy, a higher level of engagement is expected (Adams et al., 2017). So, we study communal and self-interest incentives as intrinsic motives that entice commenting on brand-related social media content when an individual feels related to others and competent to express her/his opinions and experiences (Deci et al., 2013). At the same time, commenting as an engagement activity is autonomous since individuals ‘experience choice and volition in their action, and perceive themselves to be the origin of their actions’ (Adams et al., 2017, p. 49). Aside from intrinsic motives, we also analyze reward incentives as fully extrinsic (De Vries et al., 2017) which proves to drive contributing on brand-related social media content (Azar et al., 2016; Buzeta et al., 2020; Dolan et al., 2016; 2019; Piehler et al., 2019). Although extrinsically motivated, customers who comment on the reward-related posts still perform a free-choice behaviour, thus satisfying the need for autonomy. Aligned with Ryan and Deci (2000) assumption that motivations based on a higher level of autonomy lead to more demanding actions, as engaging in commenting is, we investigate how intrinsic (communal and self-interest) and extrinsic (remuneration) motivations influence customers’ intentions to comment on brand-related social media posts, integrating perspectives from UGT and SDT in a social media context.

Albeit emerging research focuses on motives that drive customer engagement on brand-related social media content, there is a lack of studies with a focus on different content types. Pletikosa Cvijikj and Michahelles (2013) suggested that both rational and remunerative content increase the number of comments. Contrary to these findings, Dolan et al. (2019) empirically demonstrated that rational, remunerative, and entertaining content is not related to comments, although they proved the relationship with likes, as a more passive engagement activity. Tafesse (2015) empirically proved the relationship between entertaining content and shares and likes, but the study did not consider the relationship with comments. Luarn et al. (2015) found that social and entertainment posts exhibited a significantly higher number of comments compared to information and remuneration posts.

To analyze the role of content type on customers’ intentions to comment we relied on the research of Fu et al. (2017), thus referring to commercial, personal opinion, and lifestyle brand-related content.

2.1. Hypotheses development

Communal incentives: Social interaction motivation refers to various media gratifications that are related to other people (Muntinga et al., 2011). People use social media for social interaction (Hennig-Thurau et al., 2004), and to satisfy the need to belong to a group (Cheung & Lee, 2012). Socializing with others as a moderately autonomous motivation (De Vries et al., 2017) and the desire to support others (Syrdal & Briggs, 2018), drive people to contribute to brand-related content on social media (De Vries et al., 2017; Ellison et al., 2007; Yesiloglu et al., 2021). Namely, the communication motive (socializing) has a significant influence on the frequency of contributing to brand-related posts on social media (Yesiloglu et al., 2021), and social interaction positively affects these activities (Piehler et al., 2019). According to De Vries et al. (2017), socializing with others motivates social media users to engage in brand-related contributing activities rather than in creating activities. Based on all the above and given that commenting is one of the contributing activities significantly influenced by brand-related content types (Luarn et al., 2015), we suggest the following hypotheses:

H1: Communal incentives have a positive influence on intentions to comment on brand-related personal opinion messages on social media.

H2: Communal incentives have a positive influence on intentions to comment on brand-related lifestyle messages on social media.

Self-interest incentives: Personal identity motivation refers to ‘media gratifications that are related to the self’ (Muntinga et al., 2011, p.20). Consumers engage in eWoM behavior driven by self-enhancement reasons (Hennig-Thurau et al., 2004; Sabermajidi et al., 2020), self-expression motivation (Pasternak et al., 2017), as well as motivation to enhance their reputation as experts (Cheung & Lee, 2012). According to Pasternak et al. (2017), consumers’ self-identity determines the consumers’ willingness to actively participate in social media-based brand communities. Additionally, social media users engage with brand-related content to present and add depth to their desired identity (Muntinga et al., 2011; Swani & Labrecque, 2020), to maintain or enhance their self-image (Syrdal & Briggs, 2018), for self-enhancement (Dolan et al., 2019; Swani et al., 2017) and self-interest motivations (Fu et al., 2017). According to Swani et al. (2017) the possibility of expressing an opinion motivates social media users to engage in writing a comment on a brand-related post. Qin (2020) empirically proved that consumers with higher self-identity motivations tended to develop greater intentions to contribute to brand-related content on social media. Moreover, based on the findings that people’s contributing activities on social media (Dolan et al., 2019; Fu et al., 2017; Pletikosa Cvijikj & Michahelles, 2013; Tafesse, 2015), and commenting activities in particular (Luarn et al., 2015) depend on the content types, and considering previously explained, we assumed that self-interest incentives influence intentions to comment on different types of brand-related content, thus proposing the following hypotheses:

H3: Self-interest incentives have a positive influence on intentions to comment on brand-related commercial messages on social media.

H4: Self-interest incentives have a positive influence on intentions to comment on brand-related personal opinion messages on social media.

H5: Self-interest incentives have a positive influence on intentions to comment on brand-related lifestyle messages on social media.

Reward incentives: Remuneration motivation refers to the motivation to receive rewards and economic incentives such as discounts, promotions, and free products (Azar et al., 2016; Fu et al., 2017) as well as vouchers, coupons, and other rewards and advantages from the brand page (Hennig-Thurau et al., 2004; Piehler et al., 2019). Remuneration motivation plays an important role in customer engagement in the social media context (Azar et al., 2016; Muntinga et al., 2011) and economic incentives are the primary motivations for eWOM behavior (Hennig-Thurau et al., 2004). If social media users expect social media brand pages to gratify the need for remuneration, they are more likely to engage with the page and content shared (De Silva, 2019). In addition, remuneration is the main driver of contributing to brand-related social media posts (Buzeta et al., 2020; De Vries et al., 2017; Vale & Fernandes, 2018) exerting a stronger influence on contributing to brand-related posts on profile-based platforms where users can be asked to comment, to obtain a reward (eg. Facebook and Instagram) than on content-based platforms (eg. Reddit and Youtube) (Buzeta et al., 2020). Moreover, Piehler et al. (2019) confirmed that remuneration motivation has a positive effect on contributing behaviors on social media. Previous research studies also proved that commenting is driven by remuneration content (Luarn et al., 2015; Piehler et al., 2019; Pletikosa Cvijikj & Michahelles, 2013). Concerning previously discussed, and having in mind that rewards and economic incentives on social media often require people to contribute (e.g., comment) to different types of posts, we propose the last three hypotheses:

H6: Reward incentives have a positive influence on intentions to comment on brand-related commercial messages on social media.

H7: Reward incentives have a positive influence on intentions to comment on brand-related personal opinion messages on social media.

H8: Reward incentives have a positive influence on intentions to comment on brand-related lifestyle messages on social media.

3. Methodology

A self-administered online questionnaire served as the data collection instrument for this study. Besides demographic (gender, age, education level, income) and social media usage data (social media platform and frequency of social media use), the questionnaire consisted of nine items for measuring incentives, three for each type (communal, self-interest, and reward incentives) and 12 items for measuring intentions to comment on different brand-related content type, i.e., four items for each type (commercial, personal opinion and lifestyle content). All measurement items referring to communal, self-interest, and reward incentives were assessed using a seven-point Likert scale from 1 = strongly disagree to 7 = strongly agree and were operationalized based on the study of Fu et al. (2017) and Azar et al. (2016). Measurement items referring to intentions to comment on commercial, personal opinion, and lifestyle type of content were assessed using a five-point Likert scale from 1 = strongly disagree to 5 = strongly agree and they were operationalized based on the study of Fu et al. (2017), Muntinga et al. (2011) and Schivinski et al. (2016). The items were initially translated from English to Macedonian and then back-translated by native English speakers for accuracy. Following this, the final version underwent pre-testing on nine respondents to identify and address any clarity-related modifications.

Out of 422 social media users surveyed, after data screening, 415 responses were analyzed. The sample comprised 66.51% women and 33.49% men, mostly undergraduate students (81.45%), with 33.01% having a monthly household income of 25,001 to 40,000 den. (1 euro = 61.5 den). Most of the respondents (74.15%) mostly used Instagram, followed by Facebook and other social media platforms. Around a third of the respondents (29.16%) spent over two hours daily on social media. The surveyed age group ranged from 18 to 56 years, with 83.13% between 18 and 24 years, with largest participation from 22-year-olds (33.25%).

The sample size of 415 respondents meets the rule of thumb with at least 5 observations per variable (Hair et al., 2006; 2018). The sample size has a sampling error of ±4.81%, at a 95% confidence level for the case of maximum uncertainty. Post hoc power analysis was performed with G*Power (Version 3.1.9.7) software (Faul et al., 2007) to ensure that acceptable statistical power (≥80%) was achieved to fully explain significant findings (Cohen, 1988). The results confirmed that our study included a sufficient sample size with a statistical power of 100% (from the post hoc test) for three predictors at a 95% confidence level.

3.1. Common method bias

Having in mind the common method bias (CMB) issue, we undertook some ex-ante measures during instrument design and data collection, as suggested by Chang et al. (2010) and Podsakoff et al. (2003). Namely, the questionnaire had three sections with randomized questions/items orders in each section. Additionally, different question and scale types were applied, as well as different scale endpoints, thus diminishing the anchor effects (Frederick & Mochon, 2012). Respondents were assured of research confidentiality and anonymity during questionnaire administration.

Further, ex-post statistical analyses were performed to evaluate the CMB risk. First, the assessment of the correlation matrix indicated that all the coefficients were below 0.90, suggesting that common method bias is not an issue in this study (Bagozzi et al., 1991). Additionally, Harman’s test suggested that there is no dominant factor since the single un-rotated factor solution of all the variables is 39.39% which is less than 50% of the shared variance, as suggested by Fuller et al. (2016). This also suggested that there is no common method bias detected in the analyzed model.

4. Results

The research model (Figure 1) was analyzed using the structural equation modeling (SEM) technique and AMOS software version 20.0 following a two-stage procedure for evaluation, as suggested by Anderson and Gerbing (1988). First, confirmatory factor analysis (CFA) was performed to assess the measurement model. Secondly, the SEM technique was used to examine the underlying relationships in the model and hypotheses developed.

Figure 1. Conceptual model.

Source: Authors’ design.

4.1. Measurement model

The reliability of the proposed scales was tested by calculating Cronbach’s alpha. The results confirmed that the overall reliability of the scale was above 0.70 (from 0.78 to 0.89), indicating that the theoretically developed scales can be considered reliable.

The performed CFA confirmed that the model fits the data well (RMR = 0.08, GFI = 0.96, AGFI = 0.94, NFI = 0.97, CFI = 0.99, RMSEA = 0.04, PCLOSE= 0.98).

Next, the internal consistency of the constructs was assessed based on the standardized loadings of construct items and construct reliability. The standardized loadings of the items in all constructs are significant and range from 0.72 to 0.91, indicating that the items are a strong reflection of their respective constructs (see Table 1). Composite reliability (CR) values computed from the squared sum of factor loadings and the sum of error variance terms (Hair et al., 2006) range from 0.79 to 0.89, exceeding the threshold value of 0.70, thus demonstrating adequate construct reliability (see Table 1).

Table 1. Measurement model evaluation.

Construct name and measurement items	Λ
Communal incentives (α = 0.872)
‘I interact with brands on social network sites to…’
Have group fun with friends	0.91
Keep in touch with friends	0.85
Self-interest incentives (α = 0.783)
‘I interact with brands on social network sites to…’
Gain a sense of achievement	0.76
Express self	0.85
Reward incentives (α = 0.804)
‘I interact with brands on social network sites to…’
Access discounts and promotions	0.77
Access free products	0.87
Intentions to comment on commercial messages (α = 0.882)
‘I intend to comment on posts/photos/videos related to…’
New product information	0.84
Promotion activities	0.80
Industrial news	0.83
CSR events	0.76
Intentions to comment on personal opinions (α = 0.872)
‘I intend to comment on posts/photos/videos related to…’
Other people’s experiences about low service quality store	0.80
Other people’s experience of buying a low-quality product	0.72
Critical arguments (news or articles with critical opinions)	0.90
Intentions to comment on lifestyle affairs (α = 0.890)
‘I intend to comment on…’
Inspiring articles	0.86
Popular music and movies	0.86
Posts related to practical wisdom	0.84

Note(s). All loadings are significant at confidence level p < 0.001.

Source: Authors’ calculations.

To test for construct validity, we checked for convergent validity and discriminant validity. The convergent validity for all reflective measures was evaluated using average variance extracted (AVE). AVE values ranged from 0.65 to 0.73 (AVE should be higher than 0.50) indicating adequate convergent validity (Fornell & Larcker, 1981). Discriminant validity was established using the Fornell-Larcker criterion (Fornell & Larcker, 1981) as the square root of AVE is higher than the correlation of the corresponding latent variables, indicating that all the constructs explain more information through their items than through their inter-relationships. Therefore, adequate reliability, as well as convergent and discriminant validity of the model were confirmed (see Table 2).

Table 2. Convergent and discriminant validity.

			Square root of AVE's in diagonal cells
	CR	AVE	POC	CI	SII	RI	CC	LSC
Personal opinion content (POC)	0.85	0.66	0.81
Communal incentives (CI)	0.87	0.78	0.30	0.88
Self-interest incentives (SII)	0.79	0.65	0.33	0.64	0.81
Reward incentives (RI)	0.81	0.68	0.36	0.46	0.70	0.82
Commercial content (CC)	0.88	0.65	0.56	0.34	0.51	0.61	0.81
Lifestyle content (LSC)	0.89	0.73	0.69	0.28	0.35	0.48	0.71	0.86

Source: Authors’ calculations.

4.2. Structural model

Having assessed the measurement model, the structural model was examined. The model fit indices indicated a quite acceptable level (RMR = 0.11, GFI = 0.94, AGFI = 0.91, NFI= 0.95, CFI = 0.97, RMSEA = 0.06, PCLOSE = 0.09).

The results of the analyzed relationships among the latent constructs are presented in Table 3, offering support for all of them. Six of the regression paths are significant at p < 0.001, one regression path is significant at p < 0.01, and one is significant at p ≤ 0.05. Interestingly, intentions to comment on commercial content, personal opinion content, and lifestyle content were found to be negatively influenced by the self-interest incentives meaning that the higher self-interest incentives, the lower intentions to comment on the analyzed brand-related content. All the other relationships are positive.

Table 3. Structural model estimation.

			Estimates
H1: Communal incentives	→	Personal opinion content	0.15**
H2: Communal incentives	→	Lifestyle content	0.11*
H3: Self-interest incentives	→	Commercial content	−0.98***
H4: Self-interest incentives	→	Personal opinion content	−1.26***
H5: Self-interest incentives	→	Lifestyle content	−1.72***
H6: Reward incentives	→	Commercial content	1.63***
H7: Reward incentives	→	Personal opinion content	1.57***
H8: Reward incentives	→	Lifestyle content	2.22***

Note(s). The presented estimates are standardized and they are significant at ***p < 0.001; **p < 0.01; *p ≤ 0.05.

Source: Authors’ calculations.

The standardized regression coefficients in three structural relationships exceed the bounds of (-1, 1). Deegan (1978) explained that the standardized regression coefficient may exceed these bounds if there are two or more predictors that are correlated, positively or negatively. Jöreskog (1999) likewise provided a rationale for the regression coefficients greater than one.

Further, the relationship between reward incentives and intentions to comment on brand-related lifestyle messages (2.22***) is significant, positive and the strongest, followed by the relationship between reward incentives and intentions to comment on brand-related commercial content (1.63***) and the relationship between reward incentives and intentions to comment on brand-related personal opinion content (1.57***), providing support for H8, H7, and H6 respectively.

Self-interest incentives are inversely related to intentions to comment on brand-related lifestyle content (−1.72***), intentions to comment on personal opinion content (−1.26***), and intentions to comment on commercial content (−0.98***), indicating that the intentions to comment on different brand-related content are lower when self-interest motives are higher. Although these three relationships are also strong and significant, the negative relationship suggests rejecting H5, H4, and H3, respectively.

Additionally, there is a significant and positive relationship between communal incentives and intentions to comment on brand-related personal opinion messages (0.15**), supporting H1 at p < 0.01. The hypothesis referring to the positive relationship between communal incentives and intentions to comment on lifestyle brand-related messages (0.11*), i.e., H2 was confirmed too, given the significant influence of communal incentives on intentions to comment on lifestyle brand-related content (p ≤ 0.05).

The R² of intentions to comment on brand-related lifestyle content, on brand-related personal opinion content, and on brand-related commercial content is 0.85, 0.54, and 0.68, respectively, demonstrating that the three types of incentives explain a considerable amount of the variance in intentions to comment on three types of brand-related message and that the model is a good fit for the data.

5. Discussion

The results demonstrate the significant impact of all three types of incentives on intentions to comment on proposed brand-related content types but with different intensities and directions. Namely, reward incentives have a positive and the strongest effect on intentions to comment on three types of brand-related content compared to other types of incentives. In other words, the higher the reward incentives the higher the intentions to comment on lifestyle content, followed by personal opinion and commercial messages. This is in line with the results presented in the previous studies where a reward (remuneration) is proved to be an important extrinsic motivator of brand-related engagement on social media (Buzeta et al., 2020; De Vries et al., 2017; Piehler et al., 2019; Pletikosa Cvijikj & Michahelles, 2013; Vale & Fernandes, 2018; Yesiloglu et al., 2021).

The influence of communal incentives on intentions to comment on two types of brand-related content (personal opinion content and lifestyle content) is significant and positive. This corresponds to past research suggesting that socializing on social media prompts users to engage in brand-related activities (De Vries et al., 2017; Ellison et al., 2007; Syrdal & Briggs, 2018; Yesiloglu et al., 2021). However, the influence of communal incentives is the lowest compared to other types of incentives on intentions to comment on personal opinion and lifestyle brand-related content on social media. The self-interest incentives have a significant influence on the intentions to comment on three types of brand-related social media content. This aligns with previous research indicating that individuals’ involvement on social media platforms is inked to the individual’s desired identity (Muntinga et al., 2011; Qin, 2020; Swani & Labrecque, 2020), self-image (Syrdal & Briggs, 2018), self-enhancement (Dolan et al., 2019; Swani et al., 2017), self-interest (Fu et al., 2017) and possibility for self-expression (Swani et al., 2017). However, the results showed that this influence is negative, which means that social media users have lower intentions to comment on brand-related content if the self-interest motivation (interest in self-presentation) is higher. This is in line with the study of Ciunova-Shuleska et al. (2022) which empirically proved that self-interest incentives are negatively related to intentions to like brand-related content, complementing the suggestion of De Vries et al. (2017) that social media users are prone to engage in creating rather than in contributing activities when focused on self-presentation and self-expression.

Regarding the content types, it could be concluded that customers’ intention to comment on brand-related commercial content is determined mostly by reward incentives, whereas self-interest incentives inhibit customers from commenting on commercial content on social media. Customers are likely to comment on brand-related personal opinion content driven by reward incentives and followed by communal incentives. On the other side, self-interest motivations reduce customers’ intentions to comment on brand-related personal opinion content on social media. The results of this research study not only confirmed the initial findings about the role of different incentives on intentions to comment but also revealed additional insights related to the content type that significantly contribute to the overall comprehension of the subject (Luarn et al., 2015; Pletikosa Cvijikj & Michahelles, 2013).

5.1. Theoretical contribution

Even though the interest in researching the link between customers’ motivations and responses to content on social media (Buzeta et al., 2020; De Vries et al., 2017; Muntinga et al., 2011; Piehler et al., 2019; Yesiloglu et al., 2021) has been continually increasing, the research studies regarding the influence of different incentives on specific contributing activity are quite limited. In fact, to the extent of our knowledge, this is the first research study that focuses specifically on analyzing the influence of incentives on intentions to comment on brand-related posts on social media. Previous limited research studies have focused on investigating the impact of incentives on contributing activities on brand-related social media content in general (Azar et al., 2016; Buzeta et al., 2020; De Vries et al., 2017; Dolan et al., 2016; 2019; Muntinga et al., 2011; Palamidovska-Sterjadovska & Ciunova-Shuleska, 2020; Piehler et al., 2019; Yesiloglu et al., 2021). In addition, this paper has a pivotal role in investigating the intensity and direction of the influence of three types of incentives on customers’ intentions to comment on three different brand-related content types on social media.

Our results confirmed the relationships between reward incentives/self-interest incentives and intentions to comment on commercial/personal opinion/lifestyle content and the relationships between communal incentives and intentions to comment on personal opinion/lifestyle brand-related content on social media. All the analyzed relationships are positive except the relationships between self-interest incentives and intentions to comment on commercial/personal opinion/lifestyle content that are significant, but inverse, meaning that the customers motivated by self-interest have lower intentions to comment on social media. Namely, by commenting on brand-related content on social media, customers indirectly interact with the general public, and thus, their comments on brand-related posts can be subject to criticism from different people that might damage their image on social media. Therefore, the so-called fear of negative evaluation and reticence (Keaten & Kelly, 2000) could inhibit social media users’ responses such as commenting on brand-related content on social media. Additionally, there are plenty of reasons why social media users decide to self-censor and not to post content on social media, such as the reason to protect their own and others’ privacy (Lampinen et al., 2011), as well as to avoid regrets or mitigate their negative effects (Wang et al., 2011). According to Lampinen et al. (2011) deciding not to post content either for maintaining a personally acceptable impression of themselves or for the benefit of others, is one of the preventive strategies for protecting social media users’ desired image.

However, on the other side, the results confirmed the positive influence of communal incentives on intentions to comment on lifestyle and personal opinion content. Customers intend to comment on this kind of content, driven by the need for a sense of connectedness and belonging (Buzeta et al., 2020; Cheung & Lee, 2012). Also, the results indicated the positive impact of reward incentives on intentions to comment on commercial, personal opinion, and lifestyle brand-related content on social media suggesting that rewards are a significant predictor of intentions to comment on different types of brand-related content. This is in line with the findings that people expect and want to receive some kind of compensation (coupons, discounts, vouchers, free products, etc.) for their effort, i.e., engagement in commenting on brand-related content on social media (Hennig-Thurau et al., 2004; Muntinga et al., 2011).

5.2. Managerial implications

Regarding the business/managerial practice, the results of this study may help social media marketing managers in at least five ways.

First, this study empirically demonstrates that social media marketing managers need to excel in developing different types of content and should have a good knowledge of different targets in terms of what drives them to comment on social media.

Second, to boost comments on posts, social media managers should consider rewarding their audience, as reward incentives have the strongest positive impact on intentions to comment on various brand-related posts compared to other types of incentives.

Third, to engage social media users with strong communal incentives, a social marketing manager should transparently handle and address posts/photos/videos expressing users’ concerns about service and product quality, or shopping experiences related to the brand as users with strong communal incentives prefer commenting on brand-related content reflecting personal opinions and experiences instead of commenting on brand-related lifestyle content.

Fourth, to enhance customer engagement, social media managers should avoid targeting those with high self-interest incentives, as the results show a negative relationship with intentions to comment on different types of content. Instead, social media managers should focus on users with low self-interest (who do not use social media for self-presentation), as they are more likely to comment on brand-related content, particularly lifestyle, followed by personal opinion, and commercial content.

Fifth, social media managers should produce lifestyle brand-related content, such as interesting photos, videos, inspiring articles, popular music, and movies, to engage users motivated by reward incentives, as it is more likely to generate comments compared to commercial and personal opinion content.

6. Study limitations and Further research

Despite the valuable outcomes, this study is subject to several limitations. First, the use of a purposive sample considerably reduces the possibility of making broader generalizations from the results. Additionally, future research could quantify actual commenting activities, exploring the number of comments on different types of brand-related posts. Also, investigating intentions to comment within specific industries and the level of brand loyalty would add depth to future research. Lastly, exploring social capital as a moderating variable in the incentives-intentions to comment relationship and conducting text and topic analyses of comments on different types of brand-related content on social media would contribute valuable insights.

Note

Based on the national laws, an ethical approval is not required for this study since it is a non-interventional study (a survey is applied).

Disclosure statement

No potential conflict of interest was reported by the author(s).