社群媒體平台之內容發展策略分析 - 政大學術集成

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(1)國立政治大學商學院資訊管理學系碩士學位論文. 論文題目：社群媒體平台之內容發展策略分析 Understanding Content Development on Social Network Sites. 指導教授：尚孝純博士研究生：莊英杰中華民國 104 年 9 月.

(2) 致謝研究所兩年，最大的成就莫過於論文的完成，同時也宣告告別人生最後一個學生的階段。撰寫論文的過程當中，有各種的挫折，曾經也一度想要放棄，經過許多貴人的幫助與鼓勵，激勵我完成研究論文，在此我由衷感謝許多幫助我的各位。首先，感謝提供給我最大鼓勵與開導的指導教授尚孝純老師，從一開始建議題目的方向，困難時給我的指引，遇到挫折時給我的鼓勵，這都是一路上支持我的動力，以至於能夠順利完成論文，除了學術上面的教導之外，同時也很關心我的生活狀況，真的非常感謝老師。第二位要感謝俞鈞學長，提供本篇研究的研究素材，以及實務上社群媒體應用的寶貴意見，讓我除了學術上的研究，更能夠了解實際狀況，並且不厭其煩的與我討論，以及建言，著實讓我學習到很多。最後感謝我最好的同學劉漢徽，一路上都互相支持互相打氣，而且也幫忙我許多事情，從來都沒有計較誰做得多誰做得少，而是盡可能的幫助對方，這份真摯的友情，讓我非常感動。在此感謝大家的支持與鼓勵，讓我能夠順利完成論文。. 2.

(3) Understanding Content Development on Social Network Sites Abstract The number of enterprises that use social network sites (SNS) has increased dramatically in recent decades. Companies consider SNS to be another channel for increasing brand and product exposure and acquiring or retaining customers. Many companies attempt to leverage social networks by providing various forms of content to attract views and interact with customers. How to reach and attract the maximum number of customers remains a significant question for all types of businesses. Managing content development involves various dimensions, including determining what to present to viewers, what type of content customers prefer, and when the appropriate time is to post new content. To enhance the understanding of content strategy, this study aims to address ways to stimulate customer engagement by developing SNS content. Based on the use and gratification framework, this study focuses on the spectrum of strategies for satisfying users through content development. By employing a review of academic research and practical cases, this study identifies factors that can influence the intensity of content popularity and users’ behavior on SNS. The four components of content development are vividness, interactivity, richness, and emotiveness. This study tests the level of influence of each factor using data from brand fan pages of famous magazines. Through the research, we not only find that the interactivity and emotiveness factors would positively affect customer engagement but also verify that the intensity of customer engagement on the brand fans page is beneficial to companies. The findings can improve companies’ understanding of the attributes of quality content and how to stimulate customer engagement on SNS.. Keywords: Social networks, content strategy, customer engagement, use and gratification.. 3.

(4) 摘要近年來，使用社群網站的公司數量急遽的增加，公司視社群網站為是另外一種渠道，可增加產品的曝光，並且獲取新客戶與維繫現有客戶。因此，許多公司企圖藉由多種形式與特色的內容去吸引觀看以及與客戶互動，以發揮社群網站的最大效用。然而，如何去吸引到最多客戶仍就是一個未解的謎題。管理內容發展包含許多不同的面向，包括呈現的內容、什麼樣的類別能受到顧客喜愛，以及決定最適當的時間發布，為了加強對於內容策略的了解，本篇研究提出一些方法，藉由發展社群網站內容刺激顧客參與。根據使用與滿足理論框架，本篇研究專注於透過內容發展來滿足顧客。藉由學術文獻上的參考與實際案例分析，本研究識別出幾個重要的元素，最能夠去影響內容人氣的程度，分別是生動、互動、豐富、情緒。本篇研究使用知名雜誌內容中我們所提到的四個重要元素，測驗其帶來的影響程度。透過本研究，我們不僅發現互動與情緒元素可以對於顧客參與帶來正向的影響，並且也證實顧客參與於粉絲專頁上，對於公司而言是有利益的。這些發現可以改善公司對於內容特色上的了解，以及知道如何有效去刺激顧客參與於社群網站。. 關鍵詞：社群網站、內容策略、顧客參與、使用與滿足理論. 4.

(5) Contents Abstract ............................................................................................................................................................. 3 Tables................................................................................................................................................................. 6 1. Introduction: .................................................................................................................................................. 7 2. Literature review ........................................................................................................................................... 8 2.1 Use and Gratification Theory....................................................................................................................8 2.2 Resonance ................................................................................................................................................9 2.3 Customer Engagement .............................................................................................................................9 2.3 Influence of content features on customer engagement ......................................................................10 3. Methodology ............................................................................................................................................... 13 3.1 Research Design .....................................................................................................................................13 3.2 Research Processes: ...............................................................................................................................15 3.3 Method ...................................................................................................................................................16 3.4 Research variables ..................................................................................................................................17 3.5 Data collection and analysis ...................................................................................................................19 4. Research Results and Analysis ..................................................................................................................... 19 4.1 Structure model analysis: .......................................................................................................................19 4.2 Discussions and implications: .................................................................................................................21 5. Conclusion and Recommendations ............................................................................................................. 23 5.1 Research limitations and future .............................................................................................................23 5.2 Research Implication ..............................................................................................................................23 5.3 Summary.................................................................................................................................................24 Reference ........................................................................................................................................................ 25. 5.

(6) Tables Table 1. Description of samples ...................................................................................................................16 Table 2. Comparison of two tests .................................................................................................................16 Table 3. Definition of research variables ......................................................................................................17 Table 4. Research variables and definitions .................................................................................................18 Table 5. Description of sample resource ......................................................................................................19 Table 6. Demographic Information of Respondents ....................................................................................19 Table 7. Results of research model 1 ...........................................................................................................20 Table 8. Results of research model 2 ...........................................................................................................21. 6.

(7) 1. Introduction: Social network sites (SNS) have significantly changed not only the way in which people exchange information and interact with each other but also the channel of communication between customers and companies (Hennig-Thurau et al., 2010). Enterprises use Facebook fan pages and microblogging systems to post articles and messages that solicit customer feedback and enhance customer engagement (Sabine et al., 2012). Due to the attributes of interactivity between customers and companies, SNS create another channel to help companies gather useful information that can increase profits, including customer opinions on products and services and opportunities to develop new products and satisfy customer needs (Verhoef & Lemon, 2013). According to studies of SNS (Bagozzi & Dholakia, 2006), brand fan pages tend to generate loyalty and commitment to the brand, and fans are even likely to become advocates for the products, brands, or a company (Sashi, 2012). To support customer acquisition and retention, companies invest in social media to interact and maintain close relationships with customers (SAS HBR, 2010). Michaelidou (2011) examined why companies construct brand fan pages and create content on social network sites (SNS). She found that companies were using SNS to attract new customers (91%), to cultivate relationships with customers (86%), to increase awareness of their brand (82%), to publicize the brand online (73%), and to receive feedback (46%). Several previous studies (Nair, 2011; Fennis, 2010) have focused on how to attract visitors and address customers. Most companies construct their brand fan pages to share product-related content with their customers and to attract new customers. Research on brand ranking (F.A.V.E 50, 2013), which followed the trends in volume of content and customer engagement among the top 50 US retail brands on Facebook from 2011 to 2013, found that as the company content increases, customer engagement increases. Thus, companies are spending more money on SNS to publicize their content. To support customer engagement and interactions on fan pages, companies must encourage discussion and play the role of moderator (Godes et al., 2005). Companies can publish relevant content to reach and connect with their customers (Graber, 1989). If customers engage the company through the brand fan page, they may share content with their friends, which creates word-of-mouth publicity about the brand. Thus, content is the key element necessary to stimulating customers’ attention, and can take a variety of forms, such as informational, functional, and entertainment. For instance, Jahn and Kunz (2012) demonstrated that content that includes functional value will positively influence customers’ 7.

(8) usage intensity on and satisfaction from brand fan pages. Customers using the brand fan pages want to learn about products, services, and other practical information. Another study found that informational content is the key to stimulating customers to engage in the brand fan pages (Cvijikj, 2013). Hedonic value is another driver of customer engagement, and content that is considered fun, entertaining, and exciting satisfies customers (Madupu & Cooley, 2010). Contents of brand fan pages with high perceived hedonic value could lead customers to log on to the fan page more frequently (Jahn & Kunz, 2012). Customers who are satisfied with brand fan page content tend to spread the word about content without any reinforcement or costs because people enjoy sharing content with their peers (Agresta & Bough, 2011; Madupu & Cooley, 2008; Fournier & Avery, 2011). Therefore, content stimulates interaction. In sum, because content plays an important role in SNS, companies should recognize customer interests and develop a strategy for providing content that is aligned with the company’s goals (Bottles & Sherlock, 2011; Phan, 2011). Given the variety of opinions that exist about content development on SNS and multi-media communication, this study aims to provide a deep understanding of the contextual and substantial features that drive customer intention to engage on social networks.. 2. Literature review 2.1 Use and Gratification Theory Use and gratification (U&G) theory is one of most frequently applied theories on SNS research because it explains how people can have different media use patterns as a result of different gratification needs and goals (Katz, 1959; Austria, 2010). Most consumer needs can be divided into three categories: content gratification focused completely on content provided by media, relationship gratification based on social interactions with others, and self-presentation gratification based on individuals’ need to express themselves. Shao (2008) used U&G theory to examine why people use SNS to understand how behavior relates to content. The author defined three behaviors: consuming, participating, and producing. Producing is an act of self-expression and self-actualization, both of which can satisfy self-presentation gratification. This type of user would publish their own content to construct their personal identity. Another type of user would participate by interacting with the content to achieve social relationship gratification. The remaining users do not produce content or participate, but they consume content to attain content gratification. The author asserts that SNS are so popular because they enable users to easily achieve their purposes. Therefore, we can understand the significance of content on SNS because, regardless of the different purposes for using the sites, the uses are closely related to the contents. 8.

(9) Furthermore, interactive behavior on SNS can include commenting on published content, “liking” content to support its perspective, and sharing content with friends. According to the studies, interacting with the contents is participating behavior; this behavior can help people seek information and entertainment through SNS. For instance, “posting a comment” can help people understand the content; “rating” can help people find the most popular video, content, or product; and “sharing with others” can directly spread the content. Thus, participating not only enriches the content and attracts other people but also helps facilitate brand fan pages (Shao, 2008; Sashi, 2012). Therefore, successful content is adapted by customers and stimulates the previously mentioned behaviors. Content gratification includes functional value and hedonic value (Hirschman & Holbrook, 1982). Customers can attain functional value because they can access helpful, functional, practical, and useful content. Customers may also obtain hedonic value by accessing fun, entertaining, and exciting content (Carlson, 2014). Jahn and Kunz (2012) indicated that valuable content, which includes hedonic and functional characteristics, is one of the most important drivers for attracting users to brand fan pages. Focusing on content gratification, this study examines specific characteristics of content development that may affect customer engagement. 2.2 Resonance Social media such as Facebook, Titter, Instagram, and Youtube provide free platform to enable users interacting with others, discussing with hot topics, and getting favorable information. There are many different using pattern on social media; however, most of people would like to discuss and share message with others when they are interested in a topic. These behavior can be consider as the phenomenon of resonance (Gruhl et al., 2004). In social media, the easiest way to evaluate intensity of resonance are liking, commenting, and sharing the content. Companies should figure out what is the best strategy to stimulate resonance for exposing their product or brand. 2.3 Customer Engagement Customers who use SNS engage in many different behaviors, such as participating in online discussions, commenting, searching for information, and contributing to opinion polls. These behaviors can be considered customer engagement if they are related to a firm (van Doorn et al., 2010). Verhoef et al. (2010) defined customer engagement as a behavior that is expressed toward a brand or firm that goes beyond transactions, including all customer-to-firm interaction and customer-to-customer communication about the brand. The behavior may have both positive and negative consequences, including trust, satisfaction, commitment and loyalty (Brodie et al., 2011; van Doorn et al., 2010). Thus, customer engagement 9.

(10) is occasionally used to represent the highest form of loyalty (Bowden, 2009). Several studies (Jahn & Kunz 2012; Johanna & Veronica, 2012) have verified that customer engagement positively affects loyalty and purchases. Customer engagement includes all types of communication through brand fan pages, blogging and other social media (van Doorn et al., 2010). Consequently, various factors are used to measure customer engagement, such as the frequency of visits to brand fan pages, liking content, commenting, and news reading (Johanna & Veronica 2012). In general, most studies analyze content liking and commenting behavior to evaluate the popularity of particular content (Lisette de Vries et al. 2012; Ferran & Jasmina, 2014). In addition to these two dependent variables, we consider the number of shares to be another dependent variable because sharing is defined as highly intense agreement. Each of these actions potentially promotes content (Ferran & Jasmina, 2014). 2.3 Influence of content features on customer engagement Vividness Visual aesthetics are considered to be a factor that strongly affects user’s satisfaction with a product or system (Green & Jordan, 2001). Moreover, numerous studies have indicated that visual aesthetics can influence perceptions of usability, trust, fun, and enjoyment and the intention of a revisit (Phillips & Chaparro, 2009; Mahlke, 2002; Mathwick et al., 2001). Eysenck (1941) asserted that aesthetics of an object depend on two factors: simplicity and complexity. Numerous studies have defined visual complexity as the perceptual dimension of quantity of objects, clutter, openness symmetry, organization, and variety of colors (Michailidou et al., 2008; Nadkarni & Gupta, 2007). However, Birkhoff (1933) indicated that complexity deters the effect of the aesthetics of an object. Similarly, many studies have found that visual complexity negatively influences aesthetic perceptions; lower complexity is perceived to be more aesthetic than higher complexity (Michailidou et al., 2008; Pandir & Knight, 2006). Moshagen and Thielsch (2013) suggested that vividness is related to dynamics, variety, visual richness, creativity, interest, and novelty and that it is closely related to visual complexity (Moshagen & Thielsch, 2010; Hekkert et al., 2003). Berlyne (1971) asserted that complexity and novelty are the factors that determine the arousal potential of a stimulus. If a stimulus is simple, it results in a low arousal and a negative aesthetic perception. Therefore, vividness can counteract low arousal by provoking interest and tension (Hekkert & van Wieringen, 1990; Hekkert et al., 2003). Thus we hypothesize that 10.

(11) H1. The greater the vividness is, the higher the resonance will be: H1A: The greater the vividness is, the higher the likes will be. H1B: The greater the vividness is, the higher the comments will be: H1C: The greater the vividness is, the higher the shares will be: Interactivity The method used to enhance the salience of content is interactivity (Lisette de Vries et al., 2012). Blattberg and Deighton (1991) explained that interactivity enables an individual to directly communicate with a company regardless of time and distance. Moreover, Steuer (1992) defined interactivity as “the degree to which users can join in modifying the form and content of a mediated environment in real time.” Each type of content contains different degrees of interactivity. For instance, content using only text has a low degree of interactivity. Conversely, content with links enabled for users is more interactive (Fortin & Dholakia, 2005). Moreover, using questions is considered a high degree of interactivity because it solicits user responses to the content (Lisette de Vries et al., 2012). Lisette de Vries et al. (2012) indicated that content with a high level of interactivity is significant and positively related to the number of likes and comments. Cvijikj (2013) also supported these results by finding that interactivity has strong effects on customer engagement. Thus, we hypothesize that H2. The more the interactivity exists, the higher the resonance will be: H2A: The more interactivity exists, the higher likes will be H2B: The more interactivity exists, the higher comments will be H2C: The more interactivity exists, the higher shares will be Richness The degree of richness is considered to be the vividness of online content (Lisette de Vries et al., 2012; Ferran & Jasmina, 2014). Buraj and Lee (2013) indicated that rich information on business websites can enable companies to effectively communicate with customers about their products and services. Balasubramanian et al. (2003) also found that those companies with high-quality information on their websites helped their customer achieve greater satisfaction. Indeed, Jahn and Kunz (2012) asserted that the content with higher functional value plays an important role in encouraging people to spend their time on the brand fan pages because people would search for utilitarian information to satisfy their functional gratification. A previous study verified that richness information would enhance positive attitudes toward a website (Ferran & Jasmina, 2014).. 11.

(12) Thus, we hypothesize that H3. The more richness there is, the higher the resonance will be: H3A: The more richness there is, the higher the likes will be: H3B: The more richness there is, the higher the comments will be: H3C: The more richness there is, the higher the shares will be: Emotiveness Emotion plays an important role in the success of mobile communication, which enriches both inter-personal and inter-group relationships (Iyer & Leach, 2008). Collins Dictionary (2011) defines an emotion as a feeling such as happiness, love, fear, anger, or hatred. Emotive expression can be used as a stimulus to strengthen the understanding of communication between message senders and receivers (Kwon et al., 2011). Emotion not only enriches communication but also helps build trust in the negotiation process through content, sentence structure, and style (Scissors et al., 2009). Emotive expression can pour emotive experience into a linguistic structure, which can help people understand an event (Pennebaker et al., 1997). Emotion can be expressed in text in many ways, such as signs, capital letters, exclamation marks, and wording. These tactics can convey different meanings to different individuals (Moriarty, 1994). Jiang (2004) used different intensities of emotive expression to examine customers’ advertising recall rate, attitude toward advertising, attitude toward products, and intention to purchase. The results show that declarative expression led to greater advertising recall, whereas interrogative expression led to better attitude toward advertisements. Other researchers have found that emotional expression results in more positive reactions (Page et al., 1990) and higher recall levels (Choi & Thorson, 1983). Thus, we hypothesize that H4. The greater the emotiveness in communications, the higher resonance will be: H4A: The greater the emotiveness in communications, the higher likes will be H4B: The greater the emotiveness in communications, the higher comments will be H4C: The greater the emotiveness in communications, the higher shares will be Customer Engagement Customer engagement is defined as “an intimate long-term relationship with customer”. This is very beneficial if companies have intensity of customer engagement. Companies want to exchange the relation with customer from short to long-term and cursory to intimate, because customer engagement may effectively affect brand commitment, word of mouth, and purchase; hence, companies spend much time to develop strategy and tool for increasing customer engagement 12.

(13) (Sashi, 2012). Since social media is easy to spread product information and gather people, companies would like to know if the content with high resonance would stimulate customer engagement. Thus, we hypothesize that The more resonance there is, the higher the customer engagement will be: H5A: The more likes there are, the higher the customer engagement will be. H5B: The more comments there are, the higher the customer engagement will be. H5C: The more shares there are, the higher the customer engagement will be. Contents in social media have diversity style and features, which may attract user to engage on brand fans page, but not actually increase customer engagement; hence, this study also try to figure out if the content’s factors would directly affect customer engagement. Thus, we hypothesize that H6A: The greater the vividness is, the higher the customer engagement will be. H6B: The greater the interactivity is, the higher the customer engagement will be. H6C: The greater the richness is, the higher the customer engagement will be. H6D: The greater the emotiveness is, the higher the customer engagement will be.. 3. Methodology 3.1 Research Design This study adapted quantitative analysis method to conduct research. To explore the relation between variables and validate the hypothesis, this study adapted partial least squares (PLS) to help validate. In the other hand, to determine whether different intensities of content components affect customer engagement, we collected data from brand fan pages and analyzed their effect on customer engagement. Figures 1 and 2 depict our research model. We used diverse dimensions of content components as research variables to explore their influence on customer engagement and verified whether resonance would affect customer engagement.. 13.

(14) Figure 1. Conceptual Depiction of Research Model 1. Figure 2. Conceptual Depiction of Research Model 2. First, we collected the contents from the brand fan pages of Marie Claire Taiwan, There are three reasons why collected the contents from Marie Claire. First, Marie Claire is an international magazine, which includes various topics, and it attracts different kinds of customers engage in their brand fans page. Second, due to our senior who works in Marie Claire, this study is more understood empirical situation, and attained useful advice from him. Last, the value of customer engagement should be used the benefits and performances of companies to evaluate, which is credential and can’t attain from external. Moreover, with our senior help, this study can be verified the hypothesis by the data and doesn’t leak any business secret. Therefore, it is very helpful to this. 14.

(15) study for collecting data from Marie Claire to conduct research on examining impact of content on social media. In this study, our data came from two ways, in the questionnaires part, adopting NVivo software, which is a powerful application for qualitative analysis and provides many tools. One of NVivo’ tools is similar to the web crawler, which can download the data from any brand fans page. Besides, our senior also provides business performance data to evaluate the impact of factors in our study. After collecting the data, we inserted the data into a database and constructed a website that would assist us in inviting interviewees to judge the intensity of diverse dimensions. After the first test was finished, we adjusted the number of posts that would be judged by the interviewees and conducted a second test. We compared the tests results to find their common attribute and filtered invalid samples of the second test to be used as research data, which was analyzed by SmartPLS to examine our research model. 3.2 Research Processes: Step1. Collect one thousand posts from Marie Claire Taiwan for use as material in our questionnaires Step2. Input the posts into our database and construct a website that would help us give questionnaires to interviewees. See Figure 3. Figure 3. Questionnaires from the website.. 15.

(16) Step 3. In the first test, we distributed 1,000 posts to 20 interviewees, so each interviewee had to answer fifty posts about their intension of dimension. Step 4 Based on feedback from interviewees, we adjusted the number of posts in each interview. Thus, we redistributed the posts to each interviewee who has twenty-five post and totally have forty interviewee to reduce their workload. Step 5. After two runs of tests, the table below shows the results. Table 1. Description of samples Test. Interviewee. Reviewed Posts. Sample. Valid sample. 1 2. 20 40. 50 25. 1000 1000. 859 941. Step 6. We classified the intension of dimension from a number into a level. Our principle of classification is shown below: 1-2 point → Low level 3-5 point → Middle level 5+ point → High level We compared the results of each of the same posts in the two tests, as shown below. Table 2. Comparison of two tests Common result. Samples. More than 1 Completely same. 412 50. Step 7. The valid samples (941) from the second test were considered our research sample and were used to examine our research model with SmartPLS. 3.3 Method This study explores the relationships between content development and resonance behavior and how that finally affects customer engagement. We downloaded relevant data from brand fan pages and interviewed fan page members. We then applied Netnography as our research method because it 16.

(17) tends to push the researcher to participate in virtual communities and become one of the members, which can help the researcher thoroughly observe the community’s activities and effects. 3.4 Research variables Because we aimed to examine what factors can stimulate resonance behavior and affect customer engagement, we constructed a series of processes to verify our findings. We combined the concepts of content strategy, customer engagement, and customer intention into our research model. Table 3 specifies each variable in the content. Table 3. Definition of research variables Level. Low. Medium. High. Vividness. Number of elements is less than 3.. Number of elements is more than 3 and less than or equal to 5.. Number of elements is more than 5.. Interactivity. Share a link to their website. Give a question or quiz to stimulate fans to respond. Host an activity or contest to persuade fans to do something. Richness. Promote the event, activity, and spaces. Share personal experience. Have sufficient and. or practical methods. detailed information. Emotiveness Declarative: Obviously expresses the content so people can easily understand the purpose of the content. Interrogative: Imperative & Emotive: Uses interrogative method Expresses with strong to catch people’s attention emotion or commands and stimulate consideration. Content Elements: Tag, link, picture, emoticons, sufficient sign, title.. 17.

(18) Example of elements:. To evaluate the popularity of content, we recorded the number of likes and comments, which indicates that the content is successful and influential because customers take the time to express their opinion of the popularity of the content. Both variables have been used extensively to study SNS (Cvijikj, 2013; Lisette de Vries et al., 2012). A high number of likes indicates that the content is interesting and accepted. Similarly, sharing can be considered to demonstrate high intensity of agreement with the content, as customers share content with their friends. Therefore, we used these variables to judge the intensity of content popularity (Ferran, 2014). In addition, we used the redirect-click-through-rate to examine whether the resonance behavior would affect customer engagement; thus, customer engagement was also one of our research variables. Table 4. Research variables and definitions Research Variables. Description. Likes Comments Shares customer engagement. Number of likes Number of comments Number of shares Number of redirect-click-through-rates. 18.

(19) 3.5 Data collection and analysis We focused on Marie Claire Taiwan brand fan pages because they contain various topics, such as fashion, celebrities, and beauty. The brand provides such diverse contexts that they can reach different customer demographics. All details are displayed in Table 5. Table 5. Description of sample resource Brand fan pages. Description. Number of fans. Marie Claire Taiwan. A monthly women’s magazine based on the French version. 378,327. that focuses on health, beauty, and fashion. We chose Facebook as a research platform because it is the largest and most frequently used SNS in the world. Its platform enables customers and companies to easily communicate with each other. Customers who use Facebook exhibit many different behaviors that can help us evaluate the intensity of content popularity. Many other studies have used Facebook to examine customer engagement (Dholakia, 2004; Hansen, 2011). Most of interviewee are teenage, because the interviewee are the person who spend much time on social media and notice regarding fashion and celebrity, which is related to our brand fans page, so this study invite many college to conduct questionnaires. Table 6 are more detail information. Table 6. Demographic Information of Respondents (N = 40) Measure. Items. Frequency. Percent. Gender. Male Female High School & Below College Graduate < 21 21–30 >30. 14 26 0 11 29 0 39 1. 35% 65% 0 27.5% 72.5% 0 97.5% 2.5%. Education. Age. 4. Research Results and Analysis 4.1 Structure model analysis: To examine our research model, we applied PLS (Partial least squares) as the method of analysis. In this research, we used SmartPLS to help us analyze R2 (R-squared) and Path Coefficient to validate our research hypothesis. 19.

(20) Using the PLS algorithm attained an explanation for the variance in advertisement performance (R2 =34%), which is qualified because an R2 value larger than 33% can be considered a medium explained ability. Moreover, using the Bootstrapping method to calculate the path coefficient, we found that there were several paths that reached significance levels (t > 1.96, p<0.05). The relations among each factors are detailed below. Figure 4. Results of research model 1. Table 7. Results of research model 1 Hypothesis. β. Path. P Values. Result. H1A. Vividness -> Like. 0.057. 0.167. H1B. Vividness -> Comment. 0.063. 0.09. Support. H1C. Vividness -> Share. -0.069. 0.088. Support. H2A. Interactivity -> Like. -0.054. 0.115. H2B. Interactivity -> Comment. 0.011. 0.677. H2C. Interactivity -> Share. 0.083. 0.005. Support. H3A. Richness -> Like. 0.064. 0.089. Support. H3B. Richness -> Comment. -0.097. 0.022. H3C. Richness -> Share. -0.032. 0.415. H4A. Emotiveness -> Like. 0.092. 0.01. Support. H4B. Emotiveness -> Comment. 0.073. 0.008. Support. H4C. Emotiveness -> Share. 0.006. 0.856. H5A. Like -> Link. 0.414. 0. H5B. Comment -> Link. -0.039. 0.759. H5C. Share -> Link. 0.336. 0. 20. Support Support.

(21) Figure 5. Results of research model 2. Table 8. Results of research model 2 Hypothesis. β. Path. H6A. Vividness -> Link. H6B. Interactivity -> Link. H6C. Richness -> Link. H6D. Emotiveness -> Link. P Values. Result. -0.096. 0.008. 0.034. 0.346. -0.105. 0. 0.076. 0.021 Support. 4.2 Discussions and implications: Based on the results, we obtained several findings. At first, we expected that when we used content with various elements, which is considered vivid, we could hold the customers’ attention and induce increased resonance and even customer engagement behavior. However, the analytic results do not show the consequence that we expected; thus, vividness is not a significant influence factor on on number of likes and shares, but just only does on number of comments. Ferran (2013) indicated that content with images receives a higher number of likes and comments than does content with videos or links; he thus asserted that images are easier than videos to invoke customers’ feeling and opinions to react in few seconds. Hence, we fail to support H1A and H1C, but support H1B. Although U&G theory asserts that one of the reasons why people use social media is to obtain 21.

(22) information, the results show that content with deep and rich information does positively affect only the number of likes (β=0.064, p<0.10). In addition, richness negatively affected the number of comments (β=-0.097, p<0.01); thus, we assume that content with rich information may effectively specify and automatically answer the question in customers’ mind, thereby reducing the intention of commenting. Interactivity is not a significant factor regarding likes (β=-0.054, p>0.05) or comments (β=0.011, p>0.05). These results show that the intensity of interactivity does not positively affect the number of likes and comments. Cvijikj (2013) also supported this perspective and even negative relationships, though we found a positive correlation among interactivity and the frequency of shares (β=0.083, p<0.01), thus supporting H3C. Because most brand fan pages would like to host an activity or contest to induce their users to interact with the brand and receive prizes for increasing exposure, sharing the post is considered part of the activity, and number of shares will thus increase throughout the activity. We found that emotiveness positively affects the number of likes (β=0.092, p<0.01) and the number of comments (β=0.073, p<0.01), which supports H4A and H4B. Emotions are useful in computermediated communication because communication with emotions can enrich the communication itself and convey the sender’s emotions or feelings (Derks et al., 2008). Hence, we can understand that content with strong emotion would increase interactivity with users. Regarding resonance, we can see that the numbers of likes (β=0.414, p<0.001) and shares (β=0.336, p<0.001) have a strongly positive correlation with customer engagement. The act of liking can be considered an intensity agreement and inclination, which is closely related to satisfaction. We know that when a customer is intensely satisfied, the possibility of a revisit or a repurchase increases; hence, engaged customers are not only satisfied with the brand but plan to keep using it and following it in the future (Smith, 2013). In contrast, due to the attributes of social media, when a company receives likes and comments from customers, the posts will appear in the customer’s dynamic profile and be seen by their friends, which effectively increases the possibility of the post be seen and clicked (Williams et al., 2012) and results in the more direct sharing of the posts on their profile, thereby supporting H5A and H5C. However, the number of comments (β=-0.097, p > 0.05) is not a significant influence factor on customer engagement, so we fail to support H5B. Finally, in exploring the relationship between dimensions and customer engagement, we have some important findings. First, the results showed that vividness negatively impacted customer engagement (β=-0.096, p <0.001); this was not our expectation, so we assume that a possible cause of the negative relationship may be the use of too many elements in a limited space, which would annoy and interfere with the customer reading information, thereby and reducing their intention. As we know from collecting data from business magazine brands, having so much content with rich 22.

(23) information related to products may be a reason for the reduction in the customers’ intention to click a link because studies have shown that customers generally have negative attitudes toward advertising. However, emotiveness can positively affect customer engagement (β=0.076, p <0.01), thereby supporting H6D. For instance, using the interrogative method can increase the customer’s curiosity, and the imperative method can attract the customer’s attention, so these are both effective methods for inducing the customer to go to a particular website.. 5. Conclusion and Recommendations 5.1 Research limitations and future After much effort, we reached our research goals and contributed to the literature, but there are still a few limitations. First, the intensity of vividness is defined by the number of elements being included in the content, but there are many different ways to judge; for example, color is mostly intuitive and evocative, and it has been researched empirically. However, there is no effective tool for evaluating color; thus, if we can develop the ability to create evaluation criteria and thereby find an important relationship between color and customer engagement, we can provide stronger contributions. Second, although we have examined the intensity of rich information and attain its results, there are still several variables that may influence the consequence, such as the information resource, acceptor of information, and type of information. Two studies have classified contents into information and entertainment and examine, but they had adverse consequence against each other. However, if entertainment really can receive plenty of reactions, what type of entertainment would get the best effort, e.g., fashion, celebrities, music or movies? To sum up, exploring customer engagement with social media still has meaning and value that are worthy of examining in the future. 5.2 Research Implication Our research findings reveal significant implications to the academic and business area. We thoroughly studied and examined academic theory and research, which include customer engagement and Use & Gratification theory; in addition, because we found that interactivity factors and emotiveness can positively affect customer engagement, brand managers can use this evidence to adjust their content strategy to attract their audience and enhance the relationship between them and their customers. Moreover, because we have verified the value of customer engagement, companies can refer to our research to consider whether they are making a suitable investment in social media and are appropriately evaluating its value. Thus, our research can provide further insight and be of value to someone who tends to conduct research or use social media. 23.

(24) 5.3 Summary Social media strategy for business is still a critical issue in academic and empirical arenas, and there are different portfolios for different purposes. We explored the common methods of verifying and analyzing the effects of social media use in practice. The results showed that interactivity, richness, and emotiveness have a positive impact on resonance and customer engagement but that a few factors negatively impact customer engagement. Following technical trends and the behavior of people, social media has become the thing that most deeply influences our life and that brings huge opportunity and value to companies; hence, companies would like to spend a lot of money and invest in research that effectively retrieves benefits from it. However, many obstacles and difficulties remain. To address these problems and provide further insight, we conducted our research and contributed our findings. First, we analyze and verify that some dimensions, which are commonly used in content, effectively influence the behavior of customer engagement. Second, we specify that the frequency of customer engagement behavior (likes, comments, and shares) is meaningful and valuable to the company. This finding eliminates any doubts that companies might have about investing in social media. Third, examining the analytic results revealed that different factors have different effects and meaning. Companies and researchers can refer to our research to create their own strategy or conduct further research on using different dimension effects.. 24.

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