Power Brand Defense Up, My Friend! Stimulating Brand Defense through Digital Content Marketing

: Digital content marketing that increases consumers’ favorable behavior is of increasing interest to marketers. However, there is a lack of studies that examine the relative effect of digital content marketing on brand defense. Building on the theoretical lens of elaboration likelihood model, attachment theory, and source credibility theory, this experimental study examines the relative effect of two types of digital content marketing on brand defense, taking into consideration the mediation effect of behavioral engagement and the moderation effect of age generation. Based on 237 participants collected from a United States sample, the ﬁndings of this study revealed that user-generated content is a stronger predictor of brand defense and behavioral engagement compared to ﬁrm-generated content. Further, behavioral engagement served as a mediator variable between the digital content marketing types and brand defense. Signiﬁcant evidence has additionally been found between behavioral engagement and brand defense. Moreover, the ﬁndings of the moderation analysis illustrated that Generation Z is the most inﬂuenced by user-generated content, followed by Generations X and Y. Generation Y is the most inﬂuenced by ﬁrm-generated content, followed by Generations Z and X. This study adds empirical relevance to the growing literature of the importance of digital content marketing, behavioral engagement, and generation as well validates the effects of those constructs on brand defense.


Introduction
Nowadays, customers are increasingly switching to social networking sites such as Instagram, Facebook, or Twitter to participate in the stories concerning the brand or to articulate their behaviors and attitudes in favor of a brand. Within the digital era we are facing, customers' expectations have been transformed regarding brand interaction via the support of several social media platforms [1]. The content that has been created over social media becomes a primary technique and plays a significant role in customer interaction through effective content by forming it in an alluring style to sustain the customers' link to the brands [2]. By 2020, the number of US social networking site users was 223 million, where 38 million out of 199 million were Twitter users, making the US the leading country in the global Twitter penetration through other social networking sites. By 2025, the number of US social networking sites' visitors is forecasted to reach 243 million, whereas the number of global visitors by 2023 is forecasted to reach almost 3.43 billion [3].
Social media has been used by businesses to broadcast content related to the brand and inspiring customers' perception and their attitudes regarding brands [4]. Digital content marketing (DCM) has been shifted from focusing on related characteristics [5] and digital information value [6] to investigating its capability in marketing communications [7], turning from being business-focused to customer-focused through their participation

Research Framework
The Elaboration Likelihood Model (ELM), which has been considered as a part of the information process theories, posits that the message elaboration is essential in facilitating its impact on consumers over time [25]. ELM postulates that individuals might vary in their thinking level regarding the message, and the behavior that the message is calling for or defending may differ from low to high over an elaboration continuum [25]. Individuals may think a lot, a little, or even will not think about the message, and the thinking volume they engage in passes a long way to clarify how individuals will be convinced [29]. ELM is a persuasion model that illustrates how customers' attitudes will be affected by several sorts of decision-making [30] and have two persuasion routes, namely central and peripheral routes. The central route processes the information that is supposed to operate a great and long-term effect on the brand/product evaluation, whereas the peripheral one is processing the information that is assumed to be somewhat restricted [31]. If the individual chooses the central route, he/she will process the information cognitively, while under the condition of the peripheral route, the information will be processed emotionally without the need for much effort to evaluate a brand/product [32]. FGC is processed by the central route where the source of the message is less credible and reliable for the customers, and therefore, consumers revise the content wisely using rational thinking, while UGC is processed by the peripheral route where the source of the message is credible and reliable for customers [25]. The individual's cautious and serious examination of the genuine merits of the offered information leads to persuasion (e.g., brand defense). As a result, depending on the customer's chosen message source, the DCM's types influence on brand defense might be high or low. On the other hand, the study of [19] justified that the digital content that is characterized by functional and hedonic value will lead to customer engagement in the form of behavioral engagement which, in turn, will motivate customers to engage in voluntary behaviors (e.g., brand defense).

Digital Content Marketing
DCM has been identified as an inbound marketing tool-relationship marketingbetween the business or the brand and the customers [12]. DCM is defined as the process of "creating, distributing and sharing relevant, compelling and timely content to engage customers at the appropriate point in their buying consideration processes, such that it encourages them to convert to a business building outcome" [12] (p. 285). Two main types of marketing communications associated with social media are FGC and UGC, which are important types of DCM [22]. DCM might be disseminated over several digital platforms such as brands' websites, blogs, and other extra social media either from a business (FGC) or customer perspective (UGC) [33,34]. Within these platforms, customers' communications have been investigated through the brands' stimuli of the three types of digital content, which are owned, earned, and paid media [35]. UGC is theorized as the different media content forms generated by the end-user and made available for the whole public over the Internet [22,36]. It is distinguished as a truthful opinion and not controllable by the brand or the firm [37,38], where customers can allocate their creations regarding the brand either stories, likes, or comments, which makes UGC an authentic content source [39]. UGC is inspirational content due to its hedonic and utilitarian uses [40] and it is considered more trusted by customers than FGC because they imagine that UGC results from noncommercial benefits, is unbiased, and has both positive and negative experiences [41,42]. Therefore, it becomes a vital resource for customers regarding product information and evaluation [43]. Due to UGC, the communication became much easier either for the firms or the customers and, consequently, it helps firms to have a better understanding of customers' expectations [44], a new storytelling chance that benefits businesses or brands to help them foster a trusted nexus with customers [45], modify customer communication tools and strategies that expand customer-to-customer conversations influence within the marketplace [46], and build new types of competitive advantage and value [47].
On the other hand, [48] identified FGC as marketing communications launched by a firm on its formal social media pages, which aid to enhance the delivery of one-to-one nexuses with customers due to its nature as an official information channel. In terms of customer behavior, FGC can enhance both the transactional and the relational aspects of customer-firm interrelationships, as well as enhance customer profitability. Thus, it will help the customers who have long associations with the company and those who are digitally aware and prone on social media [49]. Regardless of the nature of FGC, it has the potential to inspire UGC; thus, organizations need to upgrade their fan pages with new posts regularly to capture customers' attention and invite them to create positive content Sustainability 2021, 13, 10266 4 of 17 related to their brands [50]. Persuasiveness and informativeness are two key features related to content [51]. Concerning UGC, informative and persuasive interactions might affect customers, whereas with FGC, persuasive communications might affect customers [52]. UGC affects consumers' behavior more than FGC does, owing to the notion that peer users are more credible and objective [53,54]. Hence, the attitudes towards UGC are positive since the content is more credible than FGC [42], which will lead to product or brand adoption more easily [55]. If UGC is going to be used in social media, it must be used in parallel with FGC, concerning its role in the success of the brand [56]. The joint existence of FGC vs. UGC generates exciting context since prospective customers have to route and make decisions concerning the information of both types of information [41,57].

Brand Defense
The brand defense has been identified as a voluntary behavior [58,59] that represents the strongest form of word-of-mouth and reflects the positive attributions in the customerbrand relationship that lead customers to defend a brand from criticism [60,61]. More precisely, it is a consumer behavior that stands up for, speaks on behalf of, defends, and prevents negative information about a brand, thereby protecting it [21,59]. The study of [59] considered it a major part of online brand advocacy, while it has been argued in the study of [60] as a behavior that goes beyond brand advocacy. It results from a high level of satisfaction with a brand that leads customers to support the brand by sharing positive experiences about it with others and, consequently, defend their thoughts about it [21,62]. It has also been connected with customer-brand attachment, where a high level of attachment with a brand leads consumers to defend it [63].

Digital Content Marketing and Brand Defense
The message source credibility is an imperative feature in its persuasiveness [64]. If the message has a greater credibility source, then it will result in a better attitude with regards to eWOM and UGC [65]. Source credibility theory [26] is connected with the strength of marketing communications' persuasive influences [32], where it stands for the degree with which a resource is viewed as having competence related to the communication issue and so can be relied on to provide an independent view of the situation [66]. Hence, message credibility is made up of two key elements: source trustworthiness and expertise, which are hypothesized to determine the persuasion's strength [67]. Expertise is extracted from subject knowledge and measures the degree to which a communicator is assumed to be an acceptable assertion source, whereas trustworthiness relates to the source's reliability [68]. Thus, if the customer is exposed to a message that is initiated from an extremely trustworthy source, then they will generate a better attitude than when they are exposed to a message that comes from less trustworthy sources [25].
DCM has been investigated as a predictor of customer engagement and the attitudes of the brand [9,19,67]. Since UGC is not powered by financial motivations, it is distinguished as more trustworthy than FGC [69]. On the contrary, FGC originated from an authorized and professional source that has more full and comprehensive information concerning the brand [32] which is, from the customers' perspective, less credible than UGC. Hence, FGC seems to be treated as an official message compared to UGC which originated from another customer where it is unproven and not from an official party [70]. When customers give more value to the expertise side of the message, FGC will build a stronger customer-brand relationship. When trustworthiness is more valued by customers, UGC will be the more effective tool to build a stronger customer-brand relationship. By extension, customers who are exposed to a message from a trustful source (e.g., UGC), most valued by them, might defend a brand more than when they are exposed to FGC. On the contrary, when customers are exposed to a message from an expert source (e.g., FGC), most valued by them, they may defend a brand more than when they are exposed to UGC. Thus, the following hypothesis is assumed: Hypothesis 1 (H1). User-generated content and firm-generated content differ in their effect on brand defense.

The Mediation Role of Behavioral Engagement
Any brand has assets, and having engaged customers is one of the most important ones, as they are considered a brand advocator [71,72]. Hence, brands absorb customers over DCM which is a type of value co-creation technique to raise their engagement [73,74]. The detailed FGC and UGC existence on social media gives an exclusive chance to notice customer-brand experiences and to try to interpret in which way they associate with value creation [75].
Customer engagement is theorized as a multidimensional construct for both purchase and non-purchase communications between potential and actual customers with a firm [76]. Ref. [77] (p. 254) identified customer engagement as "a customer's behavioral manifestations that have a brand or firm focus, beyond purchase, resulting from motivational drivers". While [78] (p. 3) distinguished customer engagement as the behavior, attitude, and attachment level between the customers and the business, Ref. [79] (p. 247) defined customer engagement as "a behavioral manifestation toward the brand or firm that goes beyond transactions". Based on previous studies, customer engagement is suggested to consist of three dimensions which integrate cognitive, emotional, and behavioral reactions [80,81]. The cognitive dimension is the processing of the customer's level of thought in a specific communication between the customer and the brand, whereas the emotional one is the customer's level of the positive influence of a brand within a specific interaction between the customer and the brand, and the behavioral one is the effort level that the customer spends on a brand in a specific communication between the customer and that brand [81]. Within the online communities, engagement is reflected from a behavioral perspective [76,81,82], resulting from cognitive engagement and/or emotional engagement, where the emotional one activates the growth of the next behavioral engagement [19]. From the behavioral standpoint, customer engagement concentrates on the behavioral indicators concerning a brand [82]. Behavioral brand engagement might facilitate the value of the nexus to be more noticeable for the customers [83].
To have the chance to engage in a traditional community, individuals need bonds that push them to do so [84], and the same exists within online communities to form online engagement where too many customers are searching for an emotional connection with their preferable brands [85]. Because of social media's superior importance, businesses now are significantly supporting their brands in a way that they can enhance their customer engagement [86].
Attachment theory [27] proposed that the emotional attachment level to an entity forecasts the nature of one's interactivity with that entity. Within the literature of marketing, attachment theory has been slightly applied to recognize the nexus and the way to tie consumers with brands [87][88][89]. Thus, to engage with a brand on a social media network, the customer must have an attachment sensation to that brand [84], and few scholars portrayed the attachment as the consumers' robust emotional bonds to some brands that prohibit them to switch to other brands and build stronger and long-term nexuses between customers and the brands [90,91]. There are three forms of attachment: social structure, bond, and identity attachment [92]. Within the online brand community, the individual's attachment is consisting of bond and identity-based attachment [93]. Bond attachment refers to long-term relationships, whereas identity refers to the incorporation of an object or entity (brand) into one's self-concept [84]. According to tourism and hospitality literature, eWOM is a positive benefit of customer engagement [94,95] and it is considered as an outcome of it [96,97].
Provided that brand defense is the strongest form of positive eWOM [60], if customers are stimulated by motivational drivers concerning a brand, they will engage with that brand and create voluntary involvement that goes further than purchasing from that brand [96]. As a result, brand defense is an outcome of customer engagement. Accordingly, and based on the theoretical lens of ELM and attachment theory, when customers are emotionally exposed to a credible message source (e.g., UGC), they will be more attached and engaged compared to the less credible ones (e.g., FGC). Hence, the customer will try to identify himself with others and defend that brand. All things considered, the following hypotheses are proposed: Hypothesis 2 (H2). User-generated content and firm-generated content differ in their effect on behavioral engagement.

Hypothesis 4 (H4).
Behavioral engagement mediates the relationship between DCM types and brand defense.

The Moderation Role of Generation
Generation is a market segmentation approach [98]. Based on the generational cohort theory, individuals might be split into segments regarding their ages [99]. Within each generational cohort, individuals can differentiate themselves by having comparable experiences, expectations, values, goals, skills, features, and lifestyles [100,101], where these individuals will remain reasonably constant throughout their lives [99].
Prior studies have tried to recognize the traits, values, and differences within this generational cohort [100,102]. Those traits and values differ from one generation to another [103]. They also stressed the significance of using generational cohorts to better understand the characteristics of customers in every segment [104]. To understand how every generation communicates with brand pages on social media and what drives them to connect with its content, it is important to focus on generational cohort segmentation [105]. Concerning consumer behavior, obvious variances among the generations have been found [105,106]. In a sequence to assess the moderation influence, three generations' (X vs. Y vs. Z) classifications have been counted to examine how these generational cohorts will moderate the nexus between the DCM, behavioral engagement, and brand defense. Based on the study of [107,108], classified generation is as follows: Generation X includes people who were born between 1965 and 1976, Generation Y includes people who were born between 1977 and 1994, and Generation Z comprises people who were born between 1995 and 2010. Generation Y has the greatest share among generation regarding social media users (28%), then Generation Z (21%), followed by Generation X (20%) [109].
The most important and active generation in the hospitality context is Generation Y [98] since they are characterized by digital knowledge [110]. Online communities and social media are a vital part of Generation Y's lives [111,112]. They pay more attention to DCM [113] and consider UGC more trustworthy than FGC in their final purchasing decision [114]. Generation X-ers are living the technological change, and they are capable to adapt these changes [115]. Within their interaction on social media, Generation X tends to be more responsible [116]. Generation Z is still new within the research exploring generational behavior [104]. They lived within electronic communication [117], so they are called the digital native generation [99]. They use social media more than any other generation, spending daily around 11 h interacting on social networking sites [99]. They value social media brand communication [118]. Generation Z is a robust volunteer and the greatest online content consumer, having powerful virtual bonding, being tech native, and playing a vital role in interacting with and defending the products or brands they have used [119]. Regarding digital channel usage, Gen Z is the most significant generation compared to the rest [120] By considering the different characteristics of each generation, we expect that the relative effect of DCM type on brand defense will vary among generations. Accordingly, we propose the following hypothesis: Hypothesis 5 (H5). Generation moderates the relationship between DCM types and brand defense. Based on the ELM framework and the theoretical lens of attachment theory [27] and source credibility theory [26], the conceptual model that combines the proposed hypotheses, in addition to age generation as a moderator, is presented in Figure 1.
pared to the rest [120] By considering the different characteristics of each generation, we expect that the relative effect of DCM type on brand defense will vary among generations. Accordingly, we propose the following hypothesis:

Hypothesis 5 (H5). Generation moderates the relationship between DCM types and brand defense.
Based on the ELM framework and the theoretical lens of attachment theory [27] and source credibility theory [26], the conceptual model that combines the proposed hypotheses, in addition to age generation as a moderator, is presented in Figure 1.

Experimental Design
This study implements a scenario-based experiments design. The scenario-based experiments design reduces biases caused by memory retrieval, rationalization tendencies, and inconsistency factors [121]. The stimuli and post-exposure survey were designed using SurveyMonkey in the English language. The first page includes the purpose of the study, the expected time to finish the survey, and contact information. This is followed by a written scenario. The scenario talks about a recent campaign of a fictitious coffee shop named Infinity Coffee. The reason why a fictitious name has been used is to eliminate the stereotype of the real brand [122]. The content of the scenario was as follows: "Through the days off in 2021, Infinity Coffee used off-white cups for hot drinks which are ordered by its customers within the United State. The firm invited its customers to create different sketches on their off-white cups, the final sketches of their cups will be posted on one of Infinity Coffee social media official accounts and implicate # OffwhiteCup in the caption; to help one student to gain a bachelor's degree tuition-free through the Infinity Coffee Achievement Plan". This is followed by either four posts generated by Infinity Coffee representing the FGC or four comments generated by customers representing UGC. A fictitious Twitter account has been used to show the content of FGC/UGC. Participants were randomly divided into two groups. The first group was exposed to the FGC, whereas the second group was exposed to the UGC. The content of the posts in the FGC case was that Infinity Coffee is going to provide a fund for one student to complete his/her bachelor's degree, whereas the content of UGC included followers' positive comments about the posts.

Experimental Design
This study implements a scenario-based experiments design. The scenario-based experiments design reduces biases caused by memory retrieval, rationalization tendencies, and inconsistency factors [121]. The stimuli and post-exposure survey were designed using SurveyMonkey in the English language. The first page includes the purpose of the study, the expected time to finish the survey, and contact information. This is followed by a written scenario. The scenario talks about a recent campaign of a fictitious coffee shop named Infinity Coffee. The reason why a fictitious name has been used is to eliminate the stereotype of the real brand [122]. The content of the scenario was as follows: "Through the days off in 2021, Infinity Coffee used off-white cups for hot drinks which are ordered by its customers within the United State. The firm invited its customers to create different sketches on their off-white cups, the final sketches of their cups will be posted on one of Infinity Coffee social media official accounts and implicate # OffwhiteCup in the caption; to help one student to gain a bachelor's degree tuition-free through the Infinity Coffee Achievement Plan". This is followed by either four posts generated by Infinity Coffee representing the FGC or four comments generated by customers representing UGC. A fictitious Twitter account has been used to show the content of FGC/UGC. Participants were randomly divided into two groups. The first group was exposed to the FGC, whereas the second group was exposed to the UGC. The content of the posts in the FGC case was that Infinity Coffee is going to provide a fund for one student to complete his/her bachelor's degree, whereas the content of UGC included followers' positive comments about the posts.

Pretest
In total, 44 participants from MTurk participated in the pretest. The responses of 5 participants were removed due to the attention check questions. The average age of participants was 39.43 and the majority were male (56.4%). The majority of participants were Caucasian (56.5%) followed by Hispanic/Latina (17.9%), then African American (15.4%), and the rest were Asian. Approximately 79.5% of participants were married and the majority had an undergraduate level degree (51.3%). The highest portion of participants earned an annual income of USD 40,000 to USD 59,999. Participants were exposed to either UGC or FGC and then asked about the degree of their agreement that the content they have seen represents a UGC/FGC on a 7-point Likert scale (1 = strongly disagree; 7 strongly agree). The findings revealed that the participants attributed UGC/FGC that they were Sustainability 2021, 13, 10266 8 of 17 exposed to according to the intended meaning (MUGC = 5.84, SD = 1.00; MFGC = 5.46, SD = 1.33).

Data Collection and Manipulation Check
A convenience sampling method was used in this study by recruiting 251 Amazon workers. Only workers who are located in USA were included in these experiments. Fifteen responses were excluded from the analysis for failing to pass the attention check questions [123], leaving a final sample of 237 participants. Participants who successfully responded to the survey and passed the attention check questions were given monetary reward (USD 0.5). Two attention check questions were used to ensure that the participants were really reading questions and answering accordingly. The first attention check question was "to what extent do you agree that the color of Apple could be blue", while the second attention question was asking the participants' age in two different formats ("How old are you?", "What is your birth year?") across the survey. The mismatched responses were removed taking into consideration one year as a margin error for the second attention check question. Further, the participants were informed at the first page of the survey that it included the attention check questions and they should pass them to be rewarded. Further, to increase the comprehensiveness of the collected data to represent USA citizens, none of the regions were excluded from the survey. The face validity of the survey was confirmed by three academicians who are specialized in digital marketing. To avoid the common method bias, the questions were asked randomly without attributing them to the variables they were measuring [124]. The brand defense was measured by adopting a six-item scale from the study of [21], while behavioral engagement was measured by adopting a three-item scale from the study of [28]. Items are detailed in Appendix A. The manipulation check of DCM types was also conducted in the main study by asking participants the degree to which they agree that the content that they have seen is UGC and FGC. Under the condition of UGC, participants rated UGC more than FGC (MUGC = 5.00, MFGC = 2.66). The result of a t-test reported a significant difference between both groups (t = 11.78, df = 240; p < 0.05). In planned contrast, participants rated FGC more than UGC (MFGC = 5.38, MUGC = 2.56) with statistically significant differences (t = 15.17, df = 230; p < 0.05). Thus, the manipulation of DCM types was successful.

Results
All the multi-scale items used to measure the constructs of the study reported a satisfactory level of reliability (α Brand defense = 0.94; α Behavioral engagement = 0.92) [125]. An independent t-test was used to examine H1 and H2. The result of Levene's test shows that the assumption of homogeneity of variance has been met (F = 0.65, p > 0.05). The result of the t-test revealed a statistically significant differential effect of UGC and FGC on brand defense (t = 2.59; p < 0.05). More precisely, UGC was a stronger predictor of brand defense than FGC (MUGC = 4.97, SD = 1.45; MFGC = 4.19, SD = 1.57). Thus, H1 is supported. Regarding the relative effect of DCM types on behavioral engagement, the result of the t-test revealed a statistically significant differential effect of UGC and FGC on behavioral engagement (t = 2.59; p < 0.05). More precisely, UGC was a stronger predictor of behavioral engagement than FGC (MUGC = 4.98, SD = 1.48; MFGC = 4.47, SD = 1.55). The result of Levene's test shows that the assumption of homogeneity of variance has been met (F = 0.84, p > 0.05). Thus, H2 is supported.
The result of the ANOVA test revealed a statistically significant effect of behavioral engagement on brand defenses (β = 0.62; p < 0.05), providing support for H3. The result of adjusted R2 revealed that behavioral engagement could explain 67% of the variance in brand defense. The 95% bias-corrected bootstrapped confidence interval (N = 5000) using Model 4 in PROCESS (version 3.5), developed by [126], has been used to examine the mediation effect of behavioral engagement in the relationship between DCM types and brand defense. Following prior studies, DCM types are coded as follows: UGC = 1 and FGC = 2. The findings of mediation analysis reported a significant indirect effect through  Figure 2 illustrates the direct and indirect effect of DCM types on brand defense through behavioral engagement. brand defense. The 95% bias-corrected bootstrapped confidence interval (N = 5000) using Model 4 in PROCESS (version 3.5), developed by [126], has been used to examine the mediation effect of behavioral engagement in the relationship between DCM types and brand defense. Following prior studies, DCM types are coded as follows: UGC = 1 and FGC = 2. The findings of mediation analysis reported a significant indirect effect through behavioral engagement β = −41.95% [−0.74-−0.10]. The direct effect of DCM types on brand defense reported β = −36.95% [−0.59-−0.13]. Thus, H4 is strongly supported. Figure 2 illustrates the direct and indirect effect of DCM types on brand defense through behavioral engagement.

Figure 2. Mediation analysis.
A two-way ANOVA test was conducted to examine the interaction effect of generation with DCM types on brand defense. The result showed that generation is a significant moderator between DCM type and brand defense (F (2216) = 9.44, p < 0.05). Therefore, H5 is supported. The interaction effect is plotted in Figure 3. The figure shows that under the condition of UGC, Generation Z was the most willing to defend a brand, followed by Generation X, and then Generation Y. Under the condition of FGC, Generation X was the last to defend a brand, preceded by Generation Z. Interestingly, the willingness of Generation Y to defend a brand under the FGC condition was the highest among other generations. The figure also shows that the greatest changes that occurred due to changes in the DCM types was in Generation X, followed by Generation Z, and then Generation Y. A two-way ANOVA test was conducted to examine the interaction effect of generation with DCM types on brand defense. The result showed that generation is a significant moderator between DCM type and brand defense (F (2216) = 9.44, p < 0.05). Therefore, H5 is supported. The interaction effect is plotted in Figure 3. The figure shows that under the condition of UGC, Generation Z was the most willing to defend a brand, followed by Generation X, and then Generation Y. Under the condition of FGC, Generation X was the last to defend a brand, preceded by Generation Z. Interestingly, the willingness of Generation Y to defend a brand under the FGC condition was the highest among other generations. The figure also shows that the greatest changes that occurred due to changes in the DCM types was in Generation X, followed by Generation Z, and then Generation Y.

Summary of Findings
The main issue to be addressed in this research was brand defense as an outcome o DCM and behavioral engagement, and the findings of this study confirmed the relativ effect of DCM types on brand defense. More precisely, customers who are exposed t UGC are more willing to defend a brand than the situation when they are exposed to FGC The findings also showed that the relative effect of DCM types on brand defense is med

Summary of Findings
The main issue to be addressed in this research was brand defense as an outcome of DCM and behavioral engagement, and the findings of this study confirmed the relative effect of DCM types on brand defense. More precisely, customers who are exposed to UGC are more willing to defend a brand than the situation when they are exposed to FGC. The findings also showed that the relative effect of DCM types on brand defense is mediated by behavioral engagement. As expected, the relative effect of DCM types on brand defense also differs according to generation.

Theoretical Contributions
The ELM and its empirical validation for brand defense in the hospitality sector make important contributions to the existing literature. From a theoretical approach, the ELM is built on the idea that individuals can follow two alternative routes for information processing (digital content marketing in this case): central or peripheral routes. By using this research framework, this investigation contributes to explaining why social media users process FGC using the central route and why they use the peripheral route for UGC [32]. According to the results of our experimental study, source credibility impacts consumers in the hospitality industry, in a way that UGC is a stronger predictor of brand defense compared to FGC. Consequently, this study connects ELM, source credibility theory, and attachment theory, providing an integrative framework to explain DCM's impact on behavioral engagement and brand defense. Our results show that when social media users feel emotionally connected with DCM, they show greater brand defense, and this occurs in the case of UGC, since its more inspirational [19] and is perceived as non-commercial, unbiased information [42,127]. Regarding customer engagement, attachment theory [27] shows how consumers tie to brands [88]. According to our results, DCM types also differ in their impact on behavioral engagement, since UGC can create tighter bonds and greater attachment with customers, favoring stronger links with behavioral engagement. This study adds to recent work on customer engagement [128,129], focusing on one of its dimensions and its impacts on brand defense. These empirical findings also complement existing literature on source credibility theory [26], since DCM types also differ in their degree of credibility. Since UGC is not driven by firms' motivations, consumers believe it is more trustworthy [69] than FGC, so users will be more favorable to exhibit greater brand defense. We also contribute to the existing literature by confirming that the relative effect of DCM types on brand defense is mediated by behavioral engagement. As the literature posits, positive e-WOM is one of the outcomes of customer engagement [96,97], so customers showing greater attachment to brands will exhibit greater behavioral engagement and this, in turn, will also contribute to increasing brand defense, which is the ultimate form of positive e-WOM [60,130]. Therefore, when users are exposed to UGC, they enter a virtuous circle when they show greater behavioral engagement which turns into brand defense, and this brand defense attitude creates positive e-WOM that favors further engagement and content creation.
This paper adds one more significant contribution which has not been properly addressed in the literature: the generational cohort theory. According to this theory, marketers should not target users as a whole, since age can affect not only interests and tastes, but also attitudes and shopping behaviors [131][132][133]. Our research shows that there are significant differences in the impact of DCM types on brand defense utilizing a moderation effect. More specifically, under the condition of UGC, Generation Z shows a stronger commitment to defend a brand, whereas under the condition of FGC, Generation X showed the least willingness for support. These results are consistent with previous literature [132,134,135] where Z-ers rely more on UGC, since they are more used to online environments and content creation, trusting user-generated content more. Interestingly, our research also shows that under the FGC condition, it is Generation Y and not Generation X that is the most likely to defend a brand. This could be because Generation Y is considered as the first digital natives [136] so they can process website information five times faster than previous generations [134]. However, they were born in a 1.0 digital environment, where UCG was scarce. Consequently, they grew up trusting company information as it was the only one available and they are less prone to create, share, and engage with user-generated content (compared to Z-ers), so they are more reflective when it comes to the credibility of the various kinds of information they find on the Internet [135].

Managerial Implications
This study aimed to analyze which type of DCM favors brand defense in the hospitality context and if that relationship was mediated by behavioral engagement and moderated by different generation cohorts. Following the idea that users are willing to engage more with UGC rather than content created by companies, the study compared how these DCM types affect users' behavioral intentions. The empirical findings show that UGC is more important in generating brand defense, and this effect is also mediated by behavioral engagement. After analyzing how DCM and behavioral intentions impact brand defense, we tested the moderating effect of the generational cohorts of users, showing that age is a determinant factor in committing with DCM content. The hospitality industry is a highly competitive sector, where lots of available alternatives can act as substitutes. Generation Z grew up with a coffee shop on every corner so they are looking for deeper emotional connections with brands compared to previous generations. Generation Z wants an experience together with their coffee and they also expect to align their purchases with ethical and sustainable behaviors. Consequently, transparency, honesty, and personal expectations and experiences are needed so that they engage with content. This is the reason why they prefer UGC, as users consider it neutral, non-commercial, and a reliable source of information they can process easily. Effective use of DCM can bring brands tangible benefits such as improved customer satisfaction, lower marketing expenditures, or higher customer reach [137]. If consumers share positive e-WOM about the coffee shop, its sustainable practices, or its community-based programs, this information is more credible for users than when it is generated by firms, turning into a stronger willingness to defend the brand.
Therefore, whether it is sustainability in general, local programs, or special initiatives, establishments need to work to communicate this transparently, taking advantage of new technologies to produce content that caters to customization (utilizing mobile apps or a newsletter subscription, for example) and convenience (by pre-ordering, taking advantage of online coupons and offers, or simply accommodating time tables and menus to different needs and preferences (organic, vegan, local food, and ethically responsible sourcing)). By using this communication style, coffee shops can enable users to use, reproduce, and modify original firm content or create new content based on consumer demands, which will favor behavioral engagement and, in turn, brand defense. Hospitality establishments in general and coffee shops in particular can incentivize customers' content creation by, for instance, creating iconic backgrounds to take photos while enjoying a drink, giving customers incentives for sharing content or creating reviews, reposting customers' photos thanking users, or even embedding user-generated content on coffee shops' websites or printed promotional materials.
This research also shows that Generation Y (millennials) show the strongest willingness to defend a brand under the FGC condition. This result is also very relevant for the hospitality industry since Y-ers are spending more on coffee compared to the previous year [138]. This generation cohort is also looking for healthier options, but they are more likely to drink specialty coffee. This means millennials are concerned with the coffee origin and its elaboration process when making a purchase decision. This information is more technical and cognitive, so users process it using a central route. This is the reason why they exhibit stronger brand defense under FGC. As a result, coffee shops and hospitality businesses should state very clearly that continual improvement means a rise in prices, but the final product quality compensates for this. One significant solution should be being as honest as possible when it comes to product description, elaboration techniques, and associated costs. All this detailed information, together with environmental friendliness, sustainability, and social responsibility, can make a difference when promoting (through behavioral intention) and defending a brand. Coffee shops can also contact food experts, bloggers, or gastro influencers to further develop the policies, practices, and menus of the establishments so that users have rich, detailed information when enjoying their specialties. By implementing clear and transparent FGC communications that trigger UGC creation, coffee shops and hospitality establishments can make the most of behavioral engagement and ultimately brand defense.

Limitations and Future Research Lines
Despite its contributions, this study is not free from limitations, which can create additional research opportunities First, we used a fictitious brand to conduct the experiments, trying not to condition participants on their behavioral responses. However, future studies should replicate this model with real brands to see if the same attitudes prevail, since customers with a high level of brand attachment could react differently. Secondly, we focused on one of the dimensions of customer engagement according to the literature to address DCM attributions and their impacts on brand defense. Future studies could improve the theoretical model by incorporating cognitive and emotional dimensions and measure their impact on brand defense. Further, the findings of this study are based on a United States sample collected through Mturk. Although well documented and supported in the literature, future studies should include field experimental design in which participants can interact with a specific coffee shop, and conduct comparative studies in different countries to check the robustness of results. Moreover, this study only considers the direct effect of generation as moderation on the relationship between DCM types and brand defense. However, future studies may also investigate moderation effects of generation on the relationship between DCM types and customer engagement and the moderated mediation effect of generation on the relationship between DCM types and brand defense through behavioral engagement, which was beyond the aim of this study. Finally, we measured brand defense as the ultimate positive voluntary behavior, but future studies could also build alternative brand defense constructs to study the effects of DCM on brand advocacy in general or brand defense in particular.

Data Availability Statement:
The data presented in this study are available on request from the corresponding author. [Brand] is one of the brands I usually use when I use [category].

Brand Defense
Defend the brand when others talk it down.
Stand up for the brand when others talk negatively about it.
Talk up the brand when others talk negatively about it.
Defend the brand if I hear someone speaking poorly about it.
Try to convince others to buy the brand.
Talk about the good points of this brand.