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Article

Exploring Enablers of Contagious Content for Dining Blogs: An Integrated Approach by Using Content Analysis and Interpretive Structural Modeling

by
Kuo-Chien Chang
1,
Yi-Sung Cheng
2,*,
Shih-Ming Hu
3 and
Nien-Te Kuo
4
1
Department of Leisure and Recreation Management, Chihlee University of Technology, New Taipei City 22050, Taiwan
2
School of Marketing, Entrepreneurship, Sport Management, and Hospitality and Tourism Management, Western Carolina University, Cullowhee, NC 28723, USA
3
Department of Management and Hotel, Resort, and Hospitality Management, Southern Utah University, Cedar City, UT 84720, USA
4
Department of Travel Management, National Kaohsiung University of Hospitality and Tourism, Kaohsiung City 81271, Taiwan
*
Author to whom correspondence should be addressed.
J. Theor. Appl. Electron. Commer. Res. 2023, 18(1), 668-688; https://doi.org/10.3390/jtaer18010034
Submission received: 24 January 2023 / Revised: 11 March 2023 / Accepted: 16 March 2023 / Published: 20 March 2023
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Abstract

:
Blogs remain a popular and reliable form of online communication. As the number of dining blogs continues to rise, competition is increasingly fierce. Thus, it is important to not only draw the attention of users but to also secure followers. To increase reader loyalty, bloggers must consider blog marketing from a blog reader’s perspective. Although previous studies have explored how blog narratives influence consumer behaviors, few studies have focused on exploring the enablers of contagious content for dining blogs from a blog reader’s perspective. Creating contagious content helps to achieve the maximum benefits from blog marketing. Therefore, this study identifies the enablers of contagious blogs and models their interrelationships to aid dining bloggers in framing a consistently popular blog. Based on Berger’s six principles—social currency (S), triggers (T), emotion (E), public (P), practical value (P), and stories (S) (STEPPS)—13 main factors were first compiled through a literature review. Qualitative content analysis was then applied to extract the 31 enablers related to the main factors within the context of dining blogs. In order to identify the hierarchical relationships among the extracted enablers, this study applied interpretive structural modeling (ISM). Based on the results of ISM, cross-impact matrix multiplication applied to classification (MICMAC) describes the driving and dependence behaviors of the enablers. The results of ISM and MICMAC show areas of priority on which dining bloggers should focus to create contagious content. The most important areas include emotional stimulation, storytelling, and gamification. Finally, the theoretical and managerial implications of the findings were provided.

1. Introduction

With the rising popularity of digital communication and social networks, marketing strategies have necessarily evolved, with subsequent effects on content creation [1]. The main force driving this evolution is inbound marketing on online platforms [2]. Inbound marketing focuses on creating memorable content that consumers then share with their social groups. It utilizes a multichannel approach to implement content sharing; within this approach, the priorities are the development of blog content and the promotion of social media interactions [3]. A blog is a webpage that is frequently updated with new content. Over the years, blogs have remained a popular form of online communication [4,5,6]. They are also considered more reliable than other online platforms, ranking among the top-five “most trustworthy” sources according to Technorati Media’s [7] Digital Influence Report. Statistics collected in 2020 indicated that 77% of internet users habitually read blogs, spending on average 37 s on each post [8]. A survey conducted by the PIXNET Digital Media Corporation [9] revealed that dining-related topics are one of the largest and most popular blog categories among readers in Taiwan.
As the number of dining blogs continues to rise, it is important to consider blog marketing from the perspective of a blog reader. The noisier that online platforms become, the more important it is to not only draw the attention of users but also hold it. This means that blog readers need to be sufficiently affected by the content of the blog to return to the site and hopefully become loyal followers [10]. Reader loyalty not only guarantees the success of the blog itself, but it is an important influencer of purchase decisions [11]. Thus, although previous studies have explored blog narratives that influence consumer behaviors (e.g., [12,13,14]), few studies have focused on exploring enablers of contagious content from a blog reader’s perspective.
Creating contagious content helps to achieve the maximum benefits from blog marketing. In his book Contagious: Why Things Catch On, Berger [15] proposed six principles for creating contagious content: social currency (S), triggers (T), emotion (E), public (P), practical value (P), and stories (S) (STEPPS). These principles can be applied to ensure that the content of a blog is talked about, shared, and imitated. In the present study, STEPPS was used as an initial framework to extract the main influencing factors from relevant literature. Qualitative content analysis of semi-structured interviews [16] regarding the main factors was then applied to identify enablers within the context of dining blogs.
Once these enablers were identified, the present study sought to determine the hierarchical structure among them from the perspective of a blog reader. The number of variables as well as the complexity and uncertainty regarding their structural relationships made this problem a good match for interpretive structural modeling (ISM) [17]. Accordingly, this study integrated qualitative content analysis with the quantitative approach of ISM to explore the research questions. Note that this kind of mixed-method approach is increasingly popular in practical empirical research [18,19]. To fill gaps in existing research, the following two research objectives were proposed:
(1)
Based on the STEPPS principles, this study explored enablers of contagious content for dining blogs using qualitative content analysis.
(2)
Based on the obtained enablers, this study identified the hierarchical structure of the enablers from a user perspective using ISM.
The remainder of the paper is organized as follows. First, relevant literature is reviewed. Second, the research methodology is presented including the collection and processing of data. The results, as well as their theoretical and practical implications, are then discussed. Conclusions, limitations, and a discussion of directions for future research are outlined in the final section.

2. Literature Review

2.1. Blogs

Web 2.0 applications enable users to create and share their own content online. This era of technological development not only nurtures communication and social interaction but also allows users to co-create experiences [20]. Users become familiar with certain blogs as they return to read each new post. It is also possible to comment on the posts and for the blogger to reply to user comments. In this way, strong interpersonal relationships develop between the blogger and their readers [21]. Much research has been conducted within the field of tourism and hospitality blogging, particularly in terms of characteristics and content (e.g., [12,13,21,22]). Indeed, most extant studies provide a rich source of information on “what occurs in blogs.” However, as suggested by Kwok and Yu [23], research into the information preferred by blog readers would enable managers to craft messages tailored to their target market, thereby increasing engagement. This approach necessitates investigating the mechanisms underlying the creation of contagious content. Findings on this topic would offer dining bloggers a concrete direction for content creation, thereby helping to achieve the effect of inbound marketing.

2.2. STEPPS Principles and Theoretical Main Factors

To develop a preliminary framework for dining blogging, the theoretical main factors in the literature were identified and classified them according to the STEPPS principles, as follows:
Social Currency (S): Berger [15] described that being able to share original products or ideas grants consumers a type of social currency, thereby increasing their social status. Social currency includes six distinct dimensions [24]. Three dimensions of social currency (i.e., conversation, advocacy, and information) describe the exchange of products and brand information and thus can be grouped together under information sharing. The other three dimensions of social currency are utility, affiliation, and identity. These represent the provision of insider information (e.g., limited timing on special offers). Berger [15] further proposed that gamification can be applied to motivate viewers to share content internally. Thus, incentive-based games can be regarded as a third type of promotional activity aimed at entertaining and retaining consumers, accelerating repurchase, and contributing to in-store engagement [25].
Triggers (T): Berger [15] suggested utilizing different stimuli to encourage consumers to talk about a product, idea, or concept. A trigger is defined as a stimulus that generates a specific association with the brand and creates a word-of-mouth (WOM) effect. According to Aaker [26], brand associations represent types of brand assets and liabilities that include anything “linked” to a brand. This includes preferences, uniqueness, and benefits of the brand [27]. Iyer and Griffin [28] proposed that WOM communication plays a key role in buyer behavior decisions. For a time-sensitive product, immediate WOM is important. For example, Christmas turkey relies on immediate WOM. Most other products as well as the promotion of creativity require continuous WOM [15].
Emotion (E): Berger [15] proposed that rather than emphasizing features or facts, social media content should focus on the underlying emotions that motivate people to act. In all types of advertising, emotional appeals are key to eliciting a response from the consumer [29]. Particularly within the context of eating out, invoking emotion is a highly effective strategy, as the nature of this kind of consumer experience is inherently hedonic [30]. Thus, emotional stimulation is a key aspect of this principle. In addition, Rai and Nayak [31] suggested that establishing emotionally committed consumers in hospitality marketing is especially important, as the hospitality sector relies on the creation of personalized service experiences. Loyal consumers also tend to want to share their experiences of a brand, allowing their emotions to stimulate other consumers [32]. This tendency is even more apparent in service processes. This phenomenon is termed emotional contagion.
Public (P): Berger [15] proposed that making something more observable makes it easier to imitate. Social media influencers (SMIs) are independent third parties who endorse services/products to their sizeable followings on social networks [33]. They usually gain these followers through the sharing of intimate details regarding their personal lives. This sharing takes several forms, including text, videos, images, location check-ins, and hashtags. Homophily is the tendency for communities to attract users of similar interests and opinions [34]. If a social media influencer with many social media followers provides a social media post about a product, a higher number of social media users is expected to react to that post [35]. A community such as TripAdvisor attracts a diverse community of travelers, which means that the layer of homophily between different users is likely to be low. Online blogging has been linked to higher engagement by consumers. This engagement is seen as a form of expressing one’s self-identity through making recommendations based on personal experience [36]. This phenomenon is termed social identity. Favorable performance outcomes reflect the compliance of target consumers. If, for example, consumers imitate the lifestyle or fashion choices of an SMI, they are also likely to spread positive WOM regarding the products/services recommended by the SMI. Thus, social identity is enacted through behavioral residue, that is, clues or evidence after the behavior is completed. This creates a cycle of continuous exposure.
Practical value (P): Berger [15] proposed that people share information that they believe to be practically valuable to others. Therefore, consumers judge the overall quality and/or advantages of a product to determine its perceived value [37]. A common practice is to promote special prices, adopting a strategy of percentage discounts for low-priced products and a reduction in the number of high-priced products. Therefore, special promotion is an important factor that conveys the meaning of practical value. In addition, social media (e.g., blogs) is used to seek information [38] and allows users to build connections with others and with content [39]. Social media platforms have become a phenomenon of cultural significance because for many users, it represents their primary source of information about the world as well as a vehicle for social connection [40,41]. The latter is profoundly affected by the type of content shared and how often it is shared. Thus, solving problems is another important factor that conveys practical value.
Stories (S): Berger [15] proposed that people do not think in terms of information. Rather, they think in terms of narratives. When the focus rests on the story, information comes along for the ride. The work of Bury [42] supports the idea that storytelling is the foundation of human communication. This concept has been exploited by researchers and practitioners in consumer psychology, marketing, and sociology [43]. Zhong et al. [44] proposed that studies on storytelling often take the viewpoint of commercial entities and discuss how stories can be used to build a strong brand image. Story packaging is an important factor in this perspective. When using stories as a means of marketing, the pragmatic approach is to create a “Trojan Horse”; that is, a touching or vivid and interesting story can disguise products or ideas if they are successfully integrated into the story plot. Thus, story spread is another important factor.

2.3. Interpretive Structural Modeling (ISM)

The evaluation of quality systems is complex and subjective [45]. Thus, the ISM approach was designed to collect expert views and hold panel discussions to investigate the connections between elements in the system [46]. ISM is a recognized methodology for generating solutions to complex problems, identifying and understanding the direct and indirect relationships between specific elements, and analyzing the influence between elements [47]. It creates a structural relationship diagram that visualizes the interrelationships among elements [48].
ISM, analytical hierarchy process (AHP), analytic network process (ANP), and decision-making trial and evaluation laboratory (DEMATEL) are sophisticated multi-criteria decision-making (MCDM) techniques used in various research fields [49]. Although each of these methods has its own advantages and disadvantages, ISM is superior in the following aspects to ANP and AHP [50,51]. First, ISM involves a set of criteria which is interconnected rather than the loose network suggested by ANP or the strict discipline of hierarchy in AHP. Second, ISM addresses the complexities of practical challenges while ANP focuses exclusively on nonlinear problems and AHP fails as complexity increases. Third, ISM generates the “leads to” relationships among the criteria while ANP only considers interdependencies. Fourth, ISM has a higher ability for capturing dynamic complexity compared to ANP and AHP. Although both ISM and DEMATEL express causal relationships among several decision variables [52], DEMATEL is based on digraphs, which separates involved factors into cause and effect groups [53], while ISM creates a structural model that simply identifies relationships without the need to determine the degree of influence [54]. As suggested by Al-Muftah et al. [55], ISM is the most suitable methodology if a study aims to visually represent the variables and their associations with each other within the individual stages.
The theoretical main factors in terms of STEPPS are listed in Table 1. Although previous scholars have provided valuable evidence for discussing blog content, the STEPPS principles have rarely been the focus of empirical research on dining blogs. Thus, using a mixed-method approach, this study contributes to extracting factors related to dining blogging. The research model is presented in Figure 1.

3. Methodology

3.1. Mixed-Method Approach

Mixed-method approaches combine the advantages of both qualitative (QUAL) and quantitative (QUAN) methods to explore patterns in collected data. It allows for a deeper analysis while preserving the independence of individual components, thereby increasing the validity of the findings [56]. In this study, the exploratory sequential mixed method was applied, which leans equally on both types of data [57]. Integration of the two allows for an analysis more valuable than the sum of its parts [58].
First, the relevant main factors were obtained by reviewing the literature and then extracted enablers from semi-structured interviews. Next, the data analysis software (MAXQDA) was applied to transcribe the interview sessions [59]. Qualitative content analysis is “a method for systematically describing the meaning of qualitative material” [60] (p. 1). Consequently, ISM was implemented to analyze the relationships between the enablers using hierarchical diagrams. In complex systems, the relationships between different types of vocabulary can be transformed from abstract fragments into concrete hierarchical diagrams.

3.2. Data Collection

Data collection in the first stage was performed through semi-structured interviews. For qualitative approaches, interviewing subjects using a set of open-ended questions offers some structure while allowing new topics to emerge. This type of dialogue provides a container in which it becomes possible to determine how the discourse of wider society can function as a lens through which the subjects interpret their own realities [61]. A set of interview questions were drafted based on the factors presented in Table 1 and recruited participants by posting on social media platforms. Interested users were asked to contact the researcher to participate in the study. Criteria included availability in Taipei for interviewing and experience reading dining blogs. To confirm their knowledge of dining blogs, the participants were asked to write down the most popular dining blogs. If a participant could not list at least 3–5 dining blogs, he/she was not considered for joining the interview. Fifteen participants were selected [62]. They first completed a survey to collect their demographic information, and then were interviewed separately for 30 to 60 min. This data collection period ran from September 2021 to January 2022. Two interviewers were present at each interview: one led the interview while the other took notes. Once the recorded interviews were transcribed, content analysis was performed to obtain a list of enablers [59].
The questionnaire used in the second stage of data collection was designed based the obtained enablers using a seven-point Likert scale. A total of 100 participants were recruited from social media websites to join this survey [63]. For ISM analysis, another 10 dining-blog readers were recruited in the third stage to conduct the focus groups. Further details and results on these stages are presented below. Accordingly, a gift card of $30 was given to participants who joined the interviews, and those who complete the questionnaire survey were eligible for the gift drawing.

3.3. Data Processing

MAXQDA Analytics Pro software was applied for content analysis. It has been recommended that sufficient reliability demands an upper limit of 30–40 codes [64]. The data was coded both deductively and inductively, beginning with codes extracted from relevant literature [65]. These codes were then modified by the researchers based on the interview transcripts.

3.4. Application of ISM to Clarify Structural Relationships

ISM creates a structure based on the relationships among factors [66]. These relationships are determined by the judgment of the focus group. The group’s identification and interpretation of the element set and contextual relationships enable formulation of the adjacency matrix based on pairwise comparison of the factors [63].
The procedure of ISM is therefore as follows [63]: Step 1: identify the enabler set; Step 2: construct the adjacency matrix; Step 3: generate the reachability matrix in which the transitivity rule implies that if X affects Y and Y affects Z, then X necessarily affects Z; Step 4: analyze the reachability matrix; and Step 5: draw the ISM interrelationship diagram.

4. Results

4.1. Participant Profiles

Of the 15 interview participants, all were between 30 and 50 years old, had bachelor’s degrees, and 60% were male. Of the 92 valid questionnaires obtained for the second stage (of a distributed 100), the majority of respondents were between 18 and 44 years old, had bachelor’s degrees, and 47.8% were male. In the focus groups, all 10 participants were between 30 and 50 years old, had bachelor’s degrees, and 50% were male.

4.2. Results of Content Analysis

The data collected during the interviews were transcribed and then applied to MAXQDA 2020. The researchers then read each transcript to manually code the data. The interviews revealed that emotional stimulation and contagion responses were similar and often occurred together for consumers. This phenomenon also occurred for the story package and spread interview results. Thus, the emotional stimulation and contagion results were combined, along with the story packaging and communication results. Finally, two coders evaluated a stratified random sample (10–25%) to examine intercoder reliability [64]. A kappa statistic of 0.82 that is greater than 0.75 is an acceptable target [67]. As a result, 31 enablers were produced. These are presented in Figure 2 and Table 2.

4.3. Results of Reliability Analysis and Ranking of Enablers

The high reliability was confirmed for the results of the second stage with a Cronbach’s alpha of 0.847. Descriptive statistics for the 31 enablers are presented in Table 2. Liu et al. [63] suggested that a mean value of more than 4 indicates criticality. Twenty-three of the enablers (74%) were therefore considered critical as they presented mean values of more than 5. This indicates that most of the enablers are important and should serve as reference for dining bloggers. The top-five enablers were as follows: special gifts, attractive pictures, continue to have specific offers, impressive, and share personal experience.

4.4. ISM Procedure

In the first step of building ISM, ISM was used to determine what kinds of relationships exist among the 31 enablers. To clarify the contextual relationships, Nilashi et al. [68] suggested using focus groups to collect data. Mandal and Deshmukh [69] mentioned that when judging the relationship between two factors, if there are five participants in total, at least four people must agree on the relationship. That is, when the disagreement rate was lower than 20% (20% = 1/5), the relationship was established. Therefore, two enablers are recorded as “1” for those which are related and “0” for those which are not.

4.5. Development of Adjacency Matrix

In the second step of ISM, an adjacency matrix is created to illustrate the relationships among the obtained enablers, where aij is the adjacency value of factors i to j (i = 1, 2, …, n; j = 1, 2, …, n). Direct relationships are determined by responses to the following question: “Does factor i have an impact on j?” Three conditions govern the construction of an adjacency matrix [63]: (1) for aij, if i has an impact on j, aij = 1; if not, aij = 0 and vice versa; (2) if there exist strong mutual effects between i and j, then aij and aji equal 1, and if the degree of influence varies, then the one with the larger effect equals 1 and one with the smaller effect equals 0; (3) if i = j, then aij = aji = 0. The adjacency matrix developed for this study is presented in Appendix A.

4.6. Generation of Reachability Matrix

In the third step of ISM, a reachability matrix represents the degree to which nodes influence each other, either directly or indirectly [63]. As shown in Figure 3, matrix R can be sequentially calculated as follows based on Boolean rules: (V + E) ≠ (V + E)2 ≠ (V + E)3 ≠ … ≠ (V + E)r = (V + E)r+1 = R, where R = (V + E)r is the reachability matrix of adjacency matrix A. As illustrated in Appendix B, driving power represents the degree to which enablers drive a particular issue and dependence power represents the degree to which an enabler is driven by other enablers [70].

4.7. Partitioning of Layers

In the fourth step of ISM, the final reachability matrix is separated into different layers in order to extract the reachability and antecedent sets [71]. If the reachability and antecedent sets for an enabler are identical, this enabler remains at the first layer and the remaining enablers move to the next layers for classification [72]. In the following iterations, the enablers are partitioned as shown in Table 3.

4.8. Drawing ISM Interrelationships Diagram

In the fifth step of ISM, partitioning resulted in a rearrangement of the reachability matrix into a five-layer hierarchy. As shown in Figure 4, the enablers in the rectangular box indicate that there is an interrelationship between the enablers. The enablers on the top layer are F2, F3, F11, F12, F22, F27, F28, and F31. The enablers on the second layer are F7, F13, and F29. The enablers on the third layer are F1, F4, F5, F6, F8, F9, F14, F15, F21, F23, F24, F25, and F26. The enablers on the fourth layer are F10 and F30. The enablers on the bottom are F16, F17, F18, F19, and F20. Although ISM offers a detailed representation of the relationships existing among the enablers, it does not measure their driving and dependence power. This limitation can be overcome through integration with MICMAC [73].

4.9. MICMAC Analysis

The MICMAC analysis was used to assess the ability to influence and dependency [74]. MICMAC offers a visual representation of the driving and dependence power of each factor. The four quadrants of a MICMAC graph are termed as follows: independent, linkage, autonomous, and dependent [71]. According to the last row and column of the reachability matrix (see Appendix B), the driving power diagram is plotted (see Figure 5), and the enablers and relationships between them are determined using the MICMAC analysis technique [72].

5. Discussion and Conclusions

Most past studies on blogging have been based on surveys of existing blog content (e.g., [13,36,74,75,76]). This fails to explore the mechanisms underlying the creation of contagious content to achieve inbound marketing. Thus, Berger’s [15] STEPPS principles were applied to compile 31 enablers of contagious dining blog content. ISM-MICMAC were then applied to elucidate the interaction among the extracted factors and constructed a hierarchical framework [77]. The ISM method was utilized to determine the interrelationships between the identified enablers, and MICMAC analysis was used to finalize the connection among the enablers, including their driving and dependent powers.
In ISM, bottom-layer enablers represent causes while top-layer enablers represent effects. Therefore, the bottom five enablers are the most fundamental stimuli attracting dining blog readers. The 15 enablers located in the third and fourth layers present a more functional perspective of dining blogs. These are influenced by the five fundamental enablers and also exert an influence on the top layer, thereby connecting the layers of the model. The enablers located at the first and second layers indicate more emotionally oriented thinking. This suggests that with the help of the lower layers, when blog readers like and agree with dining blog content they will engage in more social behaviors, share it with others, or turn it into a topic of discussion that can realize the ultimate goal of inbound marketing.
MICMAC analysis categorized enablers F10, F16, F17, F18, F19, F20, and F30 into quadrant IV. This indicates their influential role. These are usually the most fundamental enablers affecting a blog reader’s views of blog content. Strong driving power is key to independent enablers [78]. The enablers F1, F4, F5, F6, F8, F14, F1, F21, F23, F24, F25, and F26 were categorized into quadrant III. This quadrant indicates instability, which means these enablers can influence those in other quadrants as well as generate their own feedback [78]. Therefore, dining bloggers need to think about which practices are more in line with the content that they need when writing their blogs. The enablers F2, F3, F7, F11, F12, F13, F22, F27, F28, F29, and F31 were categorized into quadrant II. These are at the top layer of the ISM and reflect the final achievements of creating contagious dining blogs. The enabler F9 was categorized into quadrant I, which means that it does not have much influence on obtaining the attention of blog readers and maintains a weak relationship with other enablers [79]. This is probably because blog readers are not yet willing to use gamification applications to pursue a sense of accomplishment and would rather earn real rewards (F8). Therefore, this represents an area which dining bloggers can strengthen in the future. MICMAC analysis successfully identified areas of priority on which bloggers should focus in order to create contagious dining blogs.

5.1. Theoretical Implications

This study used a mixed-method approach (qualitative content analysis and ISM) to investigate how to create contagious dining content from the perspective of blog readers. Figure 4 shows that in Layer 5, blog users first notice affective enablers. Then, in Layers 3 and 4, users note what functional content the blog provides. This can be described as a cognitive aspect. Finally, Layers 1 and 2 indicate that blog readers respond to the dining blog, which can be described as behaviors. Therefore, the results of this study echo the affective, cognitive, and behavioral (ACB) model. The ACB model describes a predictable sequence from the affective to cognitive to behavioral dimensions.
In the ACB model, the affective dimension refers to the feelings and emotions that make an individual react and allow them to decide how to respond to the current situation; the cognitive dimension is based on the beliefs and values that a person has, which are related to what they have learned in the experiences of their life; the behavioral dimension focuses on the behavior and intentions of an individual facing a situation and needing to act [80].
Based on the results of Figure 4 and the ACB model, the theoretical relationships among the 31 enablers were categorized, as shown in Figure 6. The five enablers of Layer 5 (F16, F17, F18, F19, and F20) can be interpreted as perceived affective quality, which is a precursor to cognitive beliefs and behavioral intentions [81]. The enabler of Layer 4 (F10) incorporates gamification mechanisms into dining blog designs, which exploit the natural human tendency towards playfulness [82]. The enabler of Layer 4 (F30) produces a special significance that engages blog readers [83]. The enabler of Layer 3 (F9) focuses on achievement. Achievement goals are cognitive representations that guide behavior towards a future goal [84]. The enablers of Layer 3 (F1, F4, F5, F6, F8, F14, F15, F21, F23, F24, F25, and F26) represent perceived value, which are blog readers’ subjective impressions of the perceived benefits and losses of a good or service [85]. The enablers of Layer 2 (F7, F13, and F29) represent information sharing, which refers to sharing one’s information with others and the embedding of the notion of “willingness to share” [86]. The enablers of Layer 1 (F2, F3, F11, F12, F22, F27, F28, and F31) satisfy social needs, which means that users meet and talk to others to gain peer support and a sense of community [87].
Once these enablers were categorized, the proposed relationships among them were further discussed. The relationship between perceived affective quality and gamification was termed R1. The aesthetic experience and pleasure of website users are important when integrating gamification mechanisms into the design of a website [82]. Therefore, an attractive and trustworthy website design makes blog readers likely to use gamification mechanisms on the site [81]. Consequently, perceived affective quality can positively affect intention to use gamification mechanisms in the context of dining blogs.
The relationship between perceived affective quality and engagement was termed R2. Compared to logical concern, affective concern may have a more significant impact on a customer’s desire for a product or attachment to a service provider [88]. For example, tourists who are unfamiliar with a destination gain impressions and information about hotels by visiting mobile apps [89]. Sari and Alversia [90] proposed that consumer affection influences their intention to use and engage a mobile application. Therefore, perceived affective quality positively influences engagement with a dining blog.
The relationships among gamification, achievement, and sharing are termed R3 and R5. Gamification constructs gameplay by defining an achievement that is experienced as non-gameful—for example, getting an achievement badge for completing a task [91]. When a game in a dining blog gives a user more to achieve, it also makes them more willing to share it with others. Therefore, achievement mediates the relationship between gamification and sharing.
The relationships among engagement, perceived value, and socializing are termed R4 and R6. Dovaliene et al. [92] suggested that behavioral engagement and emotional engagement have significant impacts on perceived value in the context of mobile apps. Further, because virtual socializing has become a lifestyle staple for many [93], it can be inferred that the more engaged a blog reader is and the higher the perceived value of the blog is, the more that socializing behavior will increase. Therefore, perceived value mediates the relationship between engagement and socializing. The relationship between sharing and socializing is termed R7. Savolainen [94] proposed that information sharing represents a form of social exchange; that is, when blog readers see information as useful and share it with others, they are engaging in a form of socializing.
The above inferences represent only a preliminary study of the relationships among the enablers of contagious content. These provide a useful basis for future research.

5.2. Practical Implications

As dining blogs become more popular, so too does the importance of invoking emotional responses from blog readers (e.g., F18, F19, and F20). This pattern is consistent with the findings of previous research on blogs. For example, Tsaur et al. [13] examined travel blogs from the perspective of a user and identified the following characteristics of successful content: interesting, fun, fresh, and enjoyable. In addition to attracting new blog readers, it is necessary to tell stories that generate special meaning (e.g., F30), as this has the important effect of generating WOM in hospitality services [95]. To remain memorable, storytelling blogs should create messages with a distinctive style and pleasing visual effects [96]. Furthermore, blog readers hope that reading dining blogs can provide practical benefits (e.g., F1, F25, and F26). These emotional and cognitive stimulations will likely engender responses such as thinking of special people (F13), sharing personal experiences (F7), maintaining community relationships (F27), and becoming a topic of discussion (F31).
Finally, as shown in Figure 4, this study found that when the games in blog posts feel fresh and interesting to readers (F10), they are shared with special people for the sense of accomplishment (F9) or to engender an impressive image (F29) and finally achieve the purpose of social communication (e.g., F27 and F31). Although fresh and interesting gamification (F10) is another direction that can be developed in blog posts, MICMAC results indicated that using games to obtain a sense of accomplishment (F9) lacks strong driving and dependent power. Nevertheless, as gamification applications become increasingly popular among younger consumers, dining bloggers may consider leveraging the sense of accomplishment to establish new trends in dining blogs because gamification could be applied to encourage engagement and enhance value creation [97,98].
A blog provides information on any topic, and sometimes many topics [99], and seeking information is an important reason for reading blogs [100]. However, in the current age of information explosion, the sheer volume of information is forcing people to navigate the web in a much faster way. The magical number (7 ± 2) of immediate memory [101] suggests that categorizing information in meaningful units (chunks) increases the amount of recalled information and immediate memory span. Larson and Czerwinski [102] argued that short-term memory limitations play an important role in users’ ability to learn and remember the structure of a website. Sheng [103] suggested that the appropriate organization of information on the interface makes it more comprehensible and that too many elements will increase the time needed to understand the site. Suppawittaya and Yasri [104] also supported the idea of delivering information in chunks. Accordingly, the 31 enablers identified in this study need to be ‘chunked’ in the design of the dining blog so that these messages can circulate more efficiently.

5.3. Research Limitations

Despite its valuable contributions, this study is subject to limitations. First, the 31 enablers selected according to Berger’s [15] principles may not represent a comprehensive list. Other factors may exist which are relevant to the field of dining blogging. Second, the participants were only recruited from Taiwan; the generalizability of our results could therefore be improved by interviewing blog readers from other regions. A larger sample size would also contribute to generalizability.

5.4. Directions for Future Research

Although the relationships among the enablers of dining blogs were identified, further research could utilize these enablers as the basis for the development of a scale incorporating other outcome variables (e.g., satisfaction and behavioral intentions) to examine the quality of dining blogs. Moreover, because the ISM is built with data-driven analysis, the procedure to obtain an adjacency matrix is objective and consistent [105]. Thus, in order to find the real correlation between X and Y, partial correlation coefficient analysis could be applied to quantify the direct correlation between any two variables [106]. Future research could develop a structural adjacent matrix according to the partial correlation coefficient matrix, which can find the relationship between variables, avoid the influence of irrelevant variables and of irrelevant variables, and remove the influence of subjective factors [105].

Author Contributions

Conceptualization, K.-C.C.; methodology, K.-C.C.; software, K.-C.C.; validation, K.-C.C.; formal analysis, K.-C.C.; investigation, K.-C.C.; resources, N.-T.K.; data curation, K.-C.C.; writing—original draft preparation, K.-C.C.; writing—review and editing, K.-C.C. and Y.-S.C.; visualization, K.-C.C. and Y.-S.C.; supervision, S.-M.H.; project administration, S.-M.H. and N.-T.K.; funding acquisition, K.-C.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Ministry of Science and Technology of Taiwan, Republic of China, under Grant MOST 110-2410-H-263-005.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data are available on request due to restrictions.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

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Figure A1. Adjacency matrix for the enablers. Note: See Table 2 for enabler names.
Figure A1. Adjacency matrix for the enablers. Note: See Table 2 for enabler names.
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Appendix B

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Figure A2. Reachability matrix of enablers. Note: See Table 2 for enabler names; De.P. = Dependence power; Dr.P. = Driving power; * = Incorporating the “rule of transitivity”.
Figure A2. Reachability matrix of enablers. Note: See Table 2 for enabler names; De.P. = Dependence power; Dr.P. = Driving power; * = Incorporating the “rule of transitivity”.
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Figure 1. The originality of the research model.
Figure 1. The originality of the research model.
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Figure 2. Enablers identified in the content analysis.
Figure 2. Enablers identified in the content analysis.
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Figure 3. The matrixes V, E, and R.
Figure 3. The matrixes V, E, and R.
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Figure 4. Interpretive structural modeling framework of enablers.
Figure 4. Interpretive structural modeling framework of enablers.
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Figure 5. MICMAC analysis for enablers. Note. See Table 2 for enablers names.
Figure 5. MICMAC analysis for enablers. Note. See Table 2 for enablers names.
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Figure 6. Proposed theoretical relationships of the 31 enablers.
Figure 6. Proposed theoretical relationships of the 31 enablers.
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Table
Table 1. Examples of mapping interview questions in the dining blog context.
Table 1. Examples of mapping interview questions in the dining blog context.
Interview QuestionsSTEPPS PrinciplesTheoretical Main Factors
When you browse dining blog articles on the internet, why do you usually share the information in the articles with others?Social currencyInformation sharing
Description: This refers to the primary intent of consumers when sharing blog post content with others.
When you browse dining blog articles on the internet, do you consider whether the content of the article offers insider information? Provide insider information
Description: This means that consumers feel that the information provided in the blog posts is current and offers insider knowledge.
When you browse dining blog articles on the internet, do you think why the games would make you want to engage?Incentive-based games
Description: This means consumers’ intention to participate in the game in the blog post.
When you browse dining blog articles on the internet, what do you think the content of the article usually conjures up for you?TriggersGenerate a specific association
Description: This means that the consumer has a specific association with the content of the article.
When you browse dining blog articles on the internet, what are the usual reasons for the word-of-mouth effect of article content?WOM effect
Description: This means that consumers will pass on the content of the article by word of mouth.
When you browse dining blog articles on the internet, what do you think are the most common reasons for the content of articles to trigger your emotions?EmotionEmotional stimulation
Description: This means that the content of the article will cause consumer emotions.
When you browse dining blog articles on the internet, what do you think are the most common reasons for the content of articles to trigger your emotional contagion?Emotional contagion
Description: This means that the content of the article will cause consumers’ emotions to become infectious.
When you browse dining blog articles on the internet, what do you think are the reasons for why the things discussed in the article are imitated?PublicSocial identity
Description: This means that consumers imitate or follow what is said in blog posts.
When you browse dining blog articles on the internet, what do you think is the reason the content of the article will continue to be forwarded?Continuous exposure
Description: This means that the content of blog posts is constantly being forwarded by consumers.
When you browse dining blog articles on the internet, what promotional messages do you think would be of interest to you from the article?Practical valueSpecial promotion
Description: This means that the content of the blogpost is the most interesting promotional message to consumers.
When you browse dining blog articles on the internet, what are your considerations for sharing content to help others solve their problems?Solving problems
Description: This refers to the consideration that consumers share blog post content to solve others’ problems.
When you browse dining blog articles on the internet, what do you think are the benefits of using storytelling as a way of helping to package the content of an article?StoriesStory packaging
Description: This refers to the impact that blog posts have on consumers when they are packaged in stories.
When you browse dining blog articles on the internet, what do you think are the benefits of using storytelling as a way of helping to deliver the content of an article?Story spread
Description: This refers to the impact that blog posts have through the dissemination of stories.
Table
Table 2. Scores and ranking of the enablers.
Table 2. Scores and ranking of the enablers.
Main FactorsEnablersMeanStandard DeviationRankVerification
Information sharingF1. Share special dining information5.0431.30122Pass
F2. Invite others to try a new restaurant4.9781.31724Pass
F3. Understand others dining experience5.0981.27619Pass
F4. Internet reviews are good5.2171.17511Pass
Provide insider informationF5. Share limited-time dining information4.8041.17029Pass
F6. Share the latest dining news5.1631.18914Pass
F7. Share personal experience5.3261.2055Pass
Incentive-based gamesF8. Games can earn real rewards4.7071.37931Pass
F9. Games impart a sense of accomplishment4.9671.23526Pass
F10. Games feel fresh and interesting5.0111.33023Pass
Generate a specific associationF11. Thinking of special scenes4.9351.12727Pass
F12. Thinking of festivals or special days5.0871.12620Pass
F13. Thinking of special people4.8801.10828Pass
WOM effectF14. High exposure5.2751.2487Pass
F15. Good value for money5.3081.1226Pass
F16. Attractive pictures5.3851.1332Pass
F17. Experts/online celebrities’ recommendation5.2531.0918Pass
Emotional stimulation & contagionF18. Feel very happy5.0551.11921Pass
F19. Feel very surprised5.1211.23716Pass
F20. Feel very interested5.2311.12610Pass
Social identityF21. Follow the trending topics5.1871.20113Pass
F22. Reduce purchase risk4.8021.10830Pass
Continuous exposureF23. Interesting marketing techniques5.1321.12715Pass
F24. Continue to have specific offers5.3411.1173Pass
Special promotionF25. Special gifts5.4071.0541Pass
F26. Multiple preferential payment methods5.1211.12416Pass
Solving problemsF27. Maintain community relationships4.9781.18324Pass
F28. Provide useful information5.1981.17612Pass
Story package &
spread 		F29. Impressive5.3411.0983Pass
F30. Produce special meaning5.1211.04216Pass
F31. Become a topic of discussion5.2530.9618Pass
Table
Table 3. Layer partition of reachability matrix of enablers.
Table 3. Layer partition of reachability matrix of enablers.
EnablersReachabilityAntecedent SetIntersection SetLayer
F22.11.12.27.311.2.4.5.6.7.8.9.10.11.12.13.14.15.16.17.
18.19.20.21.23.24.25.26.27.29.30.31		2.11.12.27.31I
F33.221.3.4.5.6.7.8.9.10.13.14.15.16.17.
18.19.20.21.22.23.24.25.26.30		3.22I
F112.11.12.27.311.2.4.5.6.7.8.9.10.11.12.13.14.15.16.17.
18.19.20.21.23.24.25.26.27.29.30.31		2.11.12.27.31I
F122.11.12.27.311.2.4.5.6.7.8.9.10.11.12.13.14.15.16.17.
18.19.20.21.23.24.25.26.27.29.30.31		2.11.12.27.31I
F223.221.3.4.5.6.7.8.9.10.13.14.15.16.17.
18.19.20.21.22.23.24.25.26.30		3.22I
F272.11.12.27.311.2.4.5.6.7.8.9.10.11.12.13.14.15.16.17.
18.19.20.21.23.24.25.26.27.29.30.31		2.11.12.27.31I
F28281.4.5.6.8.9.10.14.15.16.17.18.19.
20.21.23.24.25.26.28.29.30		28I
F312.11.12.27.311.2.4.5.6.7.8.9.10.11.12.13.14.15.16.17.
18.19.20.21.23.24.25.26.27.29.30.31		2.11.12.27.31I
F771.4.5.6.7.8.10.14.15.16.17.18.
19.20.21.23.24.25.26.30		7II
F13131.4.5.6.8.9.10.13.14.15.16.17.
18.19.20.21.23.24.25.26.30		13II
F29291.4.5.6.8.9.10.14.15.16.17.18.
19.20.21.23.24.25.26.29.30		29II
F11.4.5.6.8.14.15.21.
23.24.25.26		1.4.5.6.8.10.14.15.16.17.18.
19.20.21.23.24.25.26.30		1.4.5.6.8.14.15.21.
23.24.25.26		III
F41.4.5.6.8.14.15.21.
23.24.25.26		1.4.5.6.8.10.14.15.16.17.18.
19.20.21.23.24.25.26.30		1.4.5.6.8.14.15.21.
23.24.25.26		III
F51.4.5.6.8.14.15.21.
23.24.25.26		1.4.5.6.8.10.14.15.16.17.18.
19.20.21.23.24.25.26.30		1.4.5.6.8.14.15.21.
23.24.25.26		III
F61.4.5.6.8.14.15.21.
23.24.25.26		1.4.5.6.8.10.14.15.16.17.18.
19.20.21.23.24.25.26.30		1.4.5.6.8.14.15.21.
23.24.25.26		III
F81.4.5.6.8.14.15.21.
23.24.25.26		1.4.5.6.8.10.14.15.16.17.18.
19.20.21.23.24.25.26.30		1.4.5.6.8.14.15.21.
23.24.25.26		III
F999.10.16.18.209III
F141.4.5.6.8.14.15.21
.23.24.25.26		1.4.5.6.8.10.14.15.16.17.18.
19.20.21.23.24.25.26.30		1.4.5.6.8.14.15.21.
23.24.25.26		III
F151.4.5.6.8.14.15.21.
23.24.25.26		1.4.5.6.8.10.14.15.16.17.18.
19.20.21.23.24.25.26.30		1.4.5.6.8.14.15.21.
23.24.25.26		III
F211.4.5.6.8.14.15.21.
23.24.25.26		1.4.5.6.8.10.14.15.16.17.18.
19.20.21.23.24.25.26.30		1.4.5.6.8.14.15.21.
23.24.25.26		III
F231.4.5.6.8.14.15.21.
23.24.25.26		1.4.5.6.8.10.14.15.16.17.18.
19.20.21.23.24.25.26.30		1.4.5.6.8.14.15.21.
23.24.25.26		III
F241.4.5.6.8.14.15.21.
23.24.25.26		1.4.5.6.8.10.14.15.16.17.18.
19.20.21.23.24.25.26.30		1.4.5.6.8.14.15.21.
23.24.25.26		III
F251.4.5.6.8.14.15.21.
23.24.25.26		1.4.5.6.8.10.14.15.16.17.18.
19.20.21.23.24.25.26.30		1.4.5.6.8.14.15.21.
23.24.25.26		III
F2614.5.6.8.14.15.21.
23.24.25.26		1.4.5.6.8.10.14.15.16.17.18.
19.20.21.23.24.25.26.30		14.5.6.8.14.15.21.
23.24.25.26		III
F101010.16.18.2010IV
F303016.17.18.19.20.3030IV
F1616.1816.1816.18V
F17171717V
F1816.1816.1816.18V
F19191919V
F20202020V
Note: See Table 2 for enabler names.
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Chang, K.-C.; Cheng, Y.-S.; Hu, S.-M.; Kuo, N.-T. Exploring Enablers of Contagious Content for Dining Blogs: An Integrated Approach by Using Content Analysis and Interpretive Structural Modeling. J. Theor. Appl. Electron. Commer. Res. 2023, 18, 668-688. https://doi.org/10.3390/jtaer18010034

AMA Style

Chang K-C, Cheng Y-S, Hu S-M, Kuo N-T. Exploring Enablers of Contagious Content for Dining Blogs: An Integrated Approach by Using Content Analysis and Interpretive Structural Modeling. Journal of Theoretical and Applied Electronic Commerce Research. 2023; 18(1):668-688. https://doi.org/10.3390/jtaer18010034

Chicago/Turabian Style

Chang, Kuo-Chien, Yi-Sung Cheng, Shih-Ming Hu, and Nien-Te Kuo. 2023. "Exploring Enablers of Contagious Content for Dining Blogs: An Integrated Approach by Using Content Analysis and Interpretive Structural Modeling" Journal of Theoretical and Applied Electronic Commerce Research 18, no. 1: 668-688. https://doi.org/10.3390/jtaer18010034

APA Style

Chang, K. -C., Cheng, Y. -S., Hu, S. -M., & Kuo, N. -T. (2023). Exploring Enablers of Contagious Content for Dining Blogs: An Integrated Approach by Using Content Analysis and Interpretive Structural Modeling. Journal of Theoretical and Applied Electronic Commerce Research, 18(1), 668-688. https://doi.org/10.3390/jtaer18010034

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