The Role of Viral Marketing in Social Media on Brand Recognition and Preference

Viral marketing is one of the most effective and imperative marketing strategies. The prominence of digital technology and social media has elevated the importance of viral marketing campaigns by increasing their cost efficiency and enabling them to reach targeted audiences rapidly. This study aimed to examine the influence of viral marketing strategies on brand recognition and brand preference by developing a framework for the effectiveness of viral marketing (7I’s) in social media contexts and testing the associations among the 7I’s, brand recognition and brand preference. A quantitative research method with a structured questionnaire as the research tool was employed to collect data from a total of 286 respondents in Thailand. Structural equation modelling (SEM) was utilized to test the proposed hypotheses. The results showed that effective viral marketing relates positively to brand recognition (b = 0.440) and preference (b = 0.298). The mediation analysis also revealed that brand recognition partially mediates the relationship between effective viral marketing and brand preference. In terms of the moderating effects, the results indicated a stronger influence for effective viral marketing on brand preference among younger respondents (b = 0.336) than among older respondents (b = 0.278). This research makes a significant contribution to the existing literature by validating a theory-driven framework based on the novel concept of the 7I’s and its potential effect on customers’ brand perceptions.


2-Literature Review
Viral marketing is the electronic form of word-of-mouth marketing, which encompasses news, environment and information [14]. While Grewal and Chahar (2013) demonstrated that word-of-mouth communication is generally performed offline, viral marketing combines internet technology and word-of-mouth tactics [15]. The characteristics of viral marketing are typically associated with the use of social media applications. However, Sohnet et al. (2013) suggested that viral marketing is not limited to a single medium of transmission [16]. Customer-to-customer exchangewhether societal or informational-is the result of the proliferation of broadband access, social media platforms, customer communities, status update services, wikis, blogs and video-sharing sites; thus, viral marketing now spreads at the speed of thought [17,18]. This facilitates social interaction opportunities, enabling communication among multiple people.
Previous studies have demonstrated that viral marketing greatly affects consumer decisions. Stonedahl et al. (2010) opined that viral marketing is more powerful than traditional marketing because consumers now rely heavily on word of mouth and discussions about a product to inform their purchase decisions [19]. According to Kaplan and Haenlein (2011), companies are increasingly aware of the growth in customer-to-customer interactions or viral marketing [20]. This growth can be attributed to the following factors. First, viral marketing allows companies to more efficiently promote their products or services and enhance brand awareness [21]. Viral marketing is less costly than other forms of marketing and advertising campaigns [8]. At the same time, however, it represents a significant investment in a company's strategy for building brand equity and thus enables a brand to distinguish itself from competing brands and products and creates a sustainable competitive advantage [22]. Second, viral marketing is considered more credible than marketer-initiated communications because viral messages are perceived as unbiased and 'coming from people like me' [23,24]. The concept of viral marketing, which, unlike paid testimonials and mass advertising campaigns, encourages the recipient to forward the message voluntarily, is consistent with this perception [21]. The information that consumers share usually stems from their personal experiences and thus impacts others' attitudes and resonates better than any particular information created by advertising companies and corporate marketing departments [25].
Numerous consumer decisions occur in a social environment. Bickart and Schindler (2001) and East et al. (2008) stated that personal interactions exert a greater influence over consumer choices than do personal selling, print advertisement or radio advertisement [26,27]. Pescher et al. (2014) supported this idea by emphasising that the core difference between a viral advertisement and a television advertisement is that consumers seek out and enjoy viral advertisements and thus willingly sending them to others [28]. As early as 1979, Davis et al. (1979) offered an example of the service industry's dependence on word-of-mouth advertising [29,30]. As they explained, intangibles, e.g. aftersale services, cannot be gauged before consumption. Hence, customers can only rely on word of mouth. Studies show that viral marketing is helpful for both new and existing brands. Viral marketing plays an important role in converting and retaining recipients as new users and enhancing brand penetration and loyalty [15]. The successful introduction of a new product is important for a firm's long-term performance [31]. Studies show that compared with traditional advertising, viral marketing can generate higher levels of consumer awareness and intentions of adopting a new product. Typically, the aim of viral marketing is to build the brand, which begins with the company composing electronic content, such as a mini-site or video [32]. López and Sicilia (2013) demonstrated that a firm should start new product communications with word-of-mouth marketing and then continue with traditional advertising [33]. Prins and Verhoef's (2007) study supported this assertion, finding that the higher the volume of word-of-mouth interactions, the faster consumers adapted to the new product [31]. Viral marketing has benefits for established products as well. Digital technology presents opportunities for building relationships-whether among peers or between marketers and customers [34,35]. Blazevic et al. (2013) stated that customers influence not only each other's behaviours but also each other's attitudes by exchanging information about their experiences [36]. Thus, a company can improve its image based on consumers' positive perceptions of its message [37]. It is also important to note that positive word of mouth critically increases customers' purchasing intentions and reduces companies' promotional expenditures [38]. Indeed, marketers do not pay users of the Internet to propagate their information. Because users' decisions to forward information are entirely voluntary, however, it is essential for companies to understand the reasons behind these decisions [32]. Despite the rich literature on the effects and implementation of viral marketing strategies, no research has yet been conducted to investigate the characteristics of effective viral marketing [39,38]. To manage viral marketing effectively, it is crucial both to explore consumers' motivations for posting online word-of-mouth messages and to measure the effectiveness of viral marketing campaigns [11,40].
Based on a review of the literature, this paper identifies seven characteristics-the 7I's-of effective word-of-mouth marketing campaigns: Invisibility (IN), Identity (ID), Innovation (IO), Insight (IS), Instantaneity (IT), Integration (IE) and Interactivity (IR). Figure 1 outlines the proposed 7I's framework while the sections below detail the literature supporting each characteristic. Invisibility: Grewal and Chahar (2013) suggested that consumers perceive content dominated by branding elements as too commercial, and therefore, they tend not to pass it on. Marketers can avoid these negative consumer perceptions and reactions by balancing the branding element with the quality of the content [15]. Consumers tend to favour messages in which the marketer's involvement is 'invisible' and the source is deemed credible. Accordingly, the study by Dobele et al. (2005) found that consumers tend not to share content directly from businesses [21]. Rather, for consumers, sharing information via social networks is about personal connections with friends and family. Furthermore, the results indicated that branding elements lower the credibility of the content in viral marketing messages and sometimes cause negative consumer perceptions to emerge. Previous research on social networking supports this result by showing that customers loathe to forward messages that violate social networking's innate qualities of trust and socialisation [41]. In this context, online influencers play an important role. Rather than appearing as the 'agents', marketers should be deemed as knowledgeable helpers in social networking [42]. Under such circumstances, the likelihood of consumers forwarding messages increases considerably. Therefore, they tend to obtain information from friends and other personal contacts [43]. This is because consumers are overwhelmed by the number of advertising messages they receive and thus actively avoid them [44].
Identity: In recent years, consumers have increasingly defined their personalities by sharing online content with their friends and family. Consumers engage with messages in viral marketing because they wish to align themselves with the content [38]. In other words, they might decide to share a message or even become a brand advocate because they anticipate that such actions will produce a positive impact on their own image or status. Jalilvand and Samiei (2012) reported that viral marketing considerably affects brand image and indirectly increases consumers' intentions to Invisibility Identity Interactivity Integration Instantaneity Insight Innovation 7I's -Effectiveness of viral marketing purchase a product or service [38]. To promote these positive effects, the study explained, marketers must know what consumers are saying about themselves when sharing messages. Whether they resonate with consumers' humour, fashion sense, tech-savviness or social contributions, effective messages must be clear and consistent with consumers' identities. Ho and Dempsey (2010) showed further those consumers are willing to stand out from others [32]. Consistent with this study, sharing viral content allows consumers to differentiate themselves and demonstrate their status among their friends. Grewal and Chahar (2013) supported this assertion by suggesting that viral content should integrate the brand with the story, whether directly or indirectly, and ensure that consumers are aware of the content-brand connection [15].
Innovation: After opening a message, individuals may simply move on or begin to engage with the content and process the information. Following the latter decision, they may decide to share the message. Exploratory research has demonstrated that consumers tend to prefer messages that utilise genuinely new and interesting forms of communication. As indicated by Southgate et al. (2010), the distinctiveness of an ad is an important factor in determining whether it will become a successful communication tool. Studying 102 video ads released in the United Kingdom, the authors suggested that a video advertising campaign's creative details correlate with the campaign's popularity [45]. Ibeh et al. (2005) refer to the distinctiveness that leads an audience to engage with viral marketing campaigns as unique messages, functionality and content [46]. The content of successful viral marketing campaigns might, for example, be exceptionally funny or outstanding enough in some other way to depart from the status quo and thus surprise consumers [15]. According to Dobele et al. (2005), successful viral marketing campaigns must disseminate an engaging, imaginative, entertaining and intriguing message [21].
Insight: The process of data analysis has identified many different types of viral marketing. Respondents stress that they share not just the content of viral marketing but also the feelings the content creates. They are, moreover, more willing to share an interesting story that is relevant to their lives rather than a list of product attributes. Marketers should thus consider whether the content matches an individual's insight-and if it matches, how it matches. In other words, the idea of the content should be relevant to the target audience. Accordingly, the respondents from the study of Grewal and Chahar (2013) were more willing to open and share viral marketing messages when they could relate to those messages in a positive way and the message exhibited great personal relevance [15]. Furthermore, Kotler and Keller (2018) recommended that viral marketing messages highlight some type of benefit or encouragement to engage with consumers [47]. They stated that both rational appeals and emotional appeals could comprise the message. While a rational appeal encourages purchase willingness by presenting product attributes, an emotional appeal can elicit consumers' positive emotions towards engagement. Indeed, Berger and Milkman (2012) suggested that people share useful content that is rich in information as well as positive content that elicits emotions. They also found that content that is funny, touching, surprising, interesting or even strange is more likely to be shared [48].
Instantaneity: Consumers are more likely to notice a viral marketing campaign if it reminds them of something that is currently popular. For example, Ferguson (2008) found that successful viral marketing campaigns capitalise on the human desire to appear trendy and in the know [17]. Consumers desire opportunities to tell their connections about novel products and thus garner attention, prestige and status through new product knowledge, experiences or ownership [14]. Celebrities may play an important role in spreading brands' messages as well. The respondents in the study of Southgate et al. (2010) demonstrated the importance of the presenter's credibility to the success of viral marketing campaigns [45]. Wu and Wang (2011) found that credible celebrities vouching for products incline consumer attitudes towards those products and thus render viral marketing campaigns-and, in turn, the brand-in a positive light. They further indicate that credibility increases when celebrities are considered more trustworthy and attractive. Trustworthiness refers to the professional knowledge the presenter has about the brand that makes the audience confident in the presenter. Attractiveness refers to the presenter's physical traits or status that could attract consumers to engage with viral marketing campaigns [49].
Integration: Viral marketing messages function as a gateway to connect brands with consumers through other channels. In fact, the most successful viral marketing campaigns impel audiences to do more than merely open and read the messages; in addition, the audiences of successful campaigns tend to engage subsequently with the brand via other channels. Hence, viral marketing campaigns achieve their full potential when synergised with other tools of marketing communication [14]. For instance, above-the-line work can be used to enhance the impact of viral marketing. As marketers construct their viral marketing campaigns, they must think about consumers holistically and consider their social interactions in the context of other consumer touch points with the brand. According to Baird and Parasnis (2011), if the customer is known in one channel, he or she must also be known in other channels. This means that viral marketing campaigns should not be used in isolation. Rather, they must be thoughtfully integrated with other channels [50].
Interactivity: Besides constructing the right message, viral marketers must also consider the level of interaction between the message and the targeted consumers. According to Fisher (2009), marketers can utilise the interaction rate as a metric when planning an effective campaign [51]. When the respondents featured in Fisher's research were asked how they interact with brands after being exposed to viral marketing messages, they listed 'Purchasing products and services' and 'Reading reviews and product rankings' as their top two activities [51]. This suggests that consumers require not just more interactions but more intimate interactions with a company. When consumers trust a brand and engage with it emotionally via viral marketing content, these interactions, in turn, facilitate the development of a holistic experience. The foremost step in the relationship chain leading to cross-and up-selling and enhanced customer lifetime value, customer identification is essential to promote the required high level of interaction [17]. Marketers already employ various methods to promote customer identification-for example, enlisting customers in opt-in plans, gathering e-mail addresses or tracking offer redemptions. Abrantes et al. (2013) found that consumers tend to share negative experiences with friends through social networks [52]. If marketers possess the ability to interact and communicate proactively with consumers, firms can capitalise upon those interactions to counter the effects of negative comments. Thus, a successful viral marketing campaign must be interactive. Several studies have recommended that marketers regard interactions with consumers as a vital opportunity to receive feedback by monitoring the information exchanged in social communities, e.g. Twitter, Facebook and LinkedIn. Marketers must, moreover, address this feedback proactively, especially when the feedback is negative [52,53].

3-Conceptual Framework and Hypotheses Development
This research aims to investigate the impact of viral marketing strategies on customers' purchasing behaviours and intentions in social media contexts. To this end, the study proposes the 7I's framework for effective viral marketing. To test the moderation effects of generational differences on the links among the 7I's, brand recognition and brand preference, the proposed model also includes the respondents' ages. Figure 1 illustrates the proposed research framework.

Figure 2. Conceptual framework of this study.
To examine the associations among the 7I's, brand recognition (BR) and brand preference (BP) with generational differences as a moderator, the study tests the following hypotheses: Hypothesis 5: Generational differences among consumers (younger vs older) moderate the positive effect of the 7I's of effective viral marketing on brand preference such that the effect is stronger among younger respondents than among older respondents.

4-1-Research Design and Data Collection
This study employed a quantitative method with an online survey questionnaire to examine the proposed research hypotheses and test the suggested model. The survey questions asked respondents to convey their perceptions of viral marketing strategies, campaigns or advertising they had recently experienced through social media. Structural equation modelling (SEM) via AMOS 22.0 was used to analyse the data, which were gathered via a purposive sampling technique. Anderson and Gerbing (1988) suggested at least 150 participants as an adequate sample size [54]; however, Bentler and Chou (1987) and Kline (2011) recommended that SEM analyses include at least 200 participants-or at least five cases per parameter for uncomplicated SEM models [55,56]. Because this study contained 27 observables variables, the minimum sample size was 27×5=135. After gathering and filtering the data for analysis, 286 valid surveys were collected, exceeding the minimum sample size. Figure 3 presents the research methodology in a flowchart.

4-2-Questionnaire Development
The questionnaire comprised two sections: (1) basic information related to respondents' behavioural and demographic aspects and (2) the measurement items. A five-point Likert scale ranging from strongly agree (5) to strongly disagree (1) was used for the measurement items. In the suggested model, the independent variable-the 7I'sconsisted of seven sub-elements: Invisibility, Identity, Innovation, Insight, Instantaneity, Integration and Interactivity, which were calculated with 21 items. Brand recognition was calculated with three items adapted from Alhaddad (2015) [57]. Brand preference was assessed via three items adapted from Ebrahim et al. (2016) [58]. Table 1 illustrates the constructs and measurement scales.

IS3
Viral marketing messages from this brand contain positive thoughts, and the message shows great personal relevance.
Instantaneity IT1 Viral marketing messages from this brand remind me of something that is currently the talk of the town.

IT2
Viral marketing messages from this brand tap into my desire to appear trendy and in the know.

IT3
The celebrity representing this brand's viral marketing messages possesses trustworthiness and attractiveness.
Integration IE1 Viral marketing messages from this brand synchronise with the brand in other channels afterward.

IE2
Viral marketing campaigns from this brand thoughtfully integrate with other channels.

IE3
I can easily link these viral marketing messages with the brand's other communication content and messages.
Interactivity IR1 Viral marketing messages from this brand allow me to read other audiences' reviews or comments.

IR2
Viral marketing messages from this brand allow me to write any review or provide product rankings.

IR3
Viral marketing messages from this brand allow me to purchase products or services after the exposure.

BR1
I am aware of the particular brand using effective viral marketing messages.

BR2
I can distinguish this brand from other brands using viral marketing messages.

BR3
I usually remember this brand name from among all of the circulating viral marketing messages.
Brand preference

BP1
I like this brand better than others.

BP2
This brand is my preferred brand over others.

BP3
When it comes to making a purchase, this brand is my first preference.

5-1-Sample Profile
The data were acquired from an online questionnaire, which social media users in Thailand were invited to complete. After being asked to recall their most recent encounters with viral marketing messages via social media, respondents completed the questionnaire, which allowed them to express their views of those messages. Two hundred eighty-six valid questionnaires were submitted for analysis. Descriptive statistics in SPSS were employed to analyse the respondents' demographic characteristics. Table 2 reveals that 53.36% of the participants were female while 46.64% were male. Most respondents ranged in age from 18 to 25 years (30.85%), and 52.52% were undergraduates who spent more than 4 hours (48.5%) on social media daily.

5-2-Measurement Model
To assess the correlations between the constructs and their retained items, confirmatory factor analysis (CFA) was employed. The estimation included an overall goodness-of-fit test as well as separate tests for significance to assess the presumed relations among the variables. To assess the correlations between the constructs and their retained items, pooled confirmatory factor analysis (CFA) was employed. Following Awang's (2015) suggestion, the latent constructs of IN, ID, IO, IS, IT, IE and IR (second-order constructs of the 7I's) were pooled together with the BR and BP constructs [59]. Table 3 illustrates our measurement model's items and constructs.  Table 3, Cronbach's α, which measures the model variables' reliability, was between 0.897-0.925 for every construct and its respective subscales; these values, which exceeded the 0.7 threshold, verified the constructs' internal consistency. Moreover, the constructs' discriminant and convergent validities were gauged. To evaluate the convergent validity, three indices were employed: factor loading values and composite reliability (CR) values exceeded the 0.7 threshold, and average variance extracted (AVE) values exceeded the 0.5 threshold [60]. Discriminant validity helps in differentiating one construct from the other. In this study, every construct's discriminant validity was confirmed by ensuring that the AVE's square root was greater than the association between that construct and the others. Overall, the tests of discriminant and convergent validity revealed satisfactory levels, which implied that for a structural model assessment, the research constructs had a suitable fit, and the model was adequate for further analysis.

5-3-Structural Model and Hypotheses Testing
The hypotheses tests were utilised to evaluate the structural model. IBM AMOS software (version 22) provided a path analysis for investigating the causal model. The model's goodness-of-fit indicators were as follows: root mean square error of approximation (RMSEA) = 0.049; comparative fit index (CFI) = 0.938; Tucker Lewis index (TLI) = 0.943; normal fit index (NFI) = 0.942; goodness-of-fit index (GFI) = 0.935; df = 314; chi-square = 732.293; and minimum discrepancy per degree of freedom (CMIN/df) = 2.332. These indicators fell within the cutoff values, suggesting a good model fit. Table 4 illustrates the hypotheses test results that indicate the significance of the variables' relationships. The regression results indicated that the 7I's have a significant positive effect on brand preference (SE = 0.071; β = 0.298; p < 0.001; supporting H1) and brand recognition (SE = 0.09; β = 0.440; p < 0.001; supporting H2). The structural equation modelling results also illustrated that brand recognition has a significant positive influence on brand preference (SE = 0.07; β = 0.653; p < 0.001; supporting H3).
To test the potential mediating effect of brand recognition on the relationship between the 7I's and brand preference, a bootstrapping technique was utilised. The outcome of the mediation analysis with bootstrapping illustrated that the 7I's have a direct effect on brand recognition (0.298; p < 0.001; 95% CI [0.171, 0.422]) and a considerable indirect effect on brand preference through brand recognition (0.287; p < 0.001; 95% CI [0.197, 0.389]), confirming partial mediation. Table 5 illustrates the outcomes of the mediation analysis with bootstrapping. To test H5, multi-group moderation tests were conducted to explore the variation effect of the antecedent variable (the 7I's) on the dependent variables (brand recognition and preference). For these tests, the respondents were divided into two groups (younger and older). The younger group, which included 167 respondents, was defined as those who were 35 years of age or younger. Meanwhile, the older group included the 119 respondents who were older than 35.
To test the categorical moderation hypothesis, we used AMOS to produce critical ratios for the differences in regression weights between groups of generational difference (younger and older). Gaskin and Lim (2018) recommended a statistical tools package for testing multi-group moderation effects that uses regression weights and critical ratios for difference parameters [61]. The relevant models were analysed separately for these categorical groups and cross-checked with their respective regression weights and critical ratios for group differences (Table 6) via the statistical tools package [61]. According to Table 6, the 7I's significantly and positively enhanced brand preference in both the younger (β = 0.336, p < 0.001) and older (β = 0.278, p < 0.001) groups. However, the 7I's effects on brand preference were more prominent in the younger group. Therefore, H5 is supported.
The results of the structural equation modelling analysis provide additional insight into the impacts of viral marketing initiatives on targeted audiences' brand recognition and preference. Our findings confirm previous studies by Mustikasari & Widaningsih (2018) and Nguyen & Nguyen (2020) that effective viral marketing initiatives have a positive direct impact on targeted audiences' brand recognition [62,63]. Therefore, marketers and businesses should adopt the 7I's concept to ensure that they are creating appropriate content for effective viral marketing campaigns. Marketers and businesses should also exploit social media platforms as the main medium for viral campaigns; indeed, the speed and ease with which audiences can share content via such platforms places social media among the most effective tools for businesses [64]. Additionally, the results reveal that effective viral marketing campaigns can significantly and positively affect targeted audiences' brand preference. This finding is consistent with Liu and Wang (2019) and Arici and Arici (2021), who reported that viral marketing influences customer-based brand equity and purchase intention. Consequently, if an individual interacts with viral marketing campaigns, his or her BP is likely to increase, which, subsequently, increases the possibility that the individual will purchase the advertised brands, products or services [65,66].
Furthermore, the results of the moderation effect testing between the older and younger groups reveal that the effect of viral marketing campaigns on brand preference is stronger among younger than older audiences. This finding aligns with Libert (2014), who noted that people in different age groups respond differently to similar viral marketing campaigns [67]. Therefore, marketers and enterprises must account for certain demographic factors, such as age, before executing viral marketing campaigns. The content of viral marketing messages must be customised and sent only after demographic or psychographic segmentation.

6-Conclusion
The penetration of digital technology and internet infrastructure into consumers' lives during the past decade has changed the very nature of online advertising. Marketers now recognise-and must capitalise on-new opportunities to accelerate the spread of marketing messages through customer-to-customer interactions, or viral marketing. Viral marketing departs from traditional word-of-mouth marketing in its reliance on the agility of digital resources, including mobile phones and the Internet [15]. As mentioned previously, viral marketing is more beneficial for companies than traditional above-the-line media due to the lower levels of investment (cost) involved in devising viral marketing campaigns and the potential of such campaigns to reach larger audiences [21]. Although, theoretically, marketers can thus derive key advantages from viral marketing, the major disadvantage of such campaigns is the relative lack of control they allow marketers to exert over the message and its distribution [13]. While we anticipate significant growth of viral marketing in the future, the results of viral marketing initiatives can be costly for marketers if audiences perceive messages negatively. Companies should be aware of this risk because even high brand equity can be significantly diluted by negative messages [10]. To date, only limited research has examined the elements of successful viral marketing campaigns. The present research works to close this gap by providing guidelines for creating effective viral marketing campaigns. This study has important implications for marketers to achieve their communication goals efficiently and effectively. Based on the present study's findings, seven factors (the 7I's) influence successful viral marketing through social media: Identity, Innovation, Insight, Instantaneity, Integration, Interactivity and Invisibility. While many marketers fixate on the size of the audiences that their viral messages can reach (Index), this study finds that effective viral marketing through the 7I's framework has a significant positive effect on brand recognition and preference. The results of the moderating effect testing also reveal that the impact of viral marketing on brand preference is greater among younger participants than older participants. Our findings thus provide insights for both academics and practitioners, suggesting that successful viral marketing campaigns depend significantly on the quality of the content (Influential). By understanding the 7I's framework of successful viral marketing campaigns in social media contexts, companies can more accurately predict which viral marketing approach will become widely successful and why.

6-1-Limitations and Future Research
The proposed 7I's framework for successful viral marketing provides practitioners and researchers with an overview of different contexts from which to further explore or challenge the framework derived. Despite this study's theoretical and practical contributions, it also entails limitations. Because its results depend on a self-administered questionnaire and respondents' perceptions, the most significant limitation of this research is the generalisability of its findings. The limitation of data collection to respondents in Thailand further restricts the study's generalisability and requires additional research in other countries with different cultures to capture the effects of cultural differences.

7-1-Author Contributions
W.P. conceptualized and participated study design, coordinated data collection, carried out the initial analyses, drafted the initial manuscript, and read and approved the manuscript. S.T. participated in study design, guided the methodology coordinated and supervised data collection and analyses, reviewed and edited manuscript. Both authors read and approved the manuscript as submitted and agree to be accountable for all aspects of the work.

7-2-Data Availability Statement
The data presented in this study are available on request from the corresponding author.

7-3-Funding
The authors received no financial support for the research, authorship, and/or publication of this article.

7-4-Conflicts of Interest
The authors declare that there is no conflict of interests regarding the publication of this manuscript. In addition, the ethical issues, including plagiarism, informed consent, misconduct, data fabrication and/or falsification, double publication and/or submission, and redundancies have been completely observed by the authors.