Organization of the dissertation

The dissertation is organized as the following order. Chapter 2 explores blog acceptance behaviors from the perspectives of technology acceptance and media choice factors, describing why bloggers accept and use blog. We addressed a proposed model from the literature review, and an online field survey was conducted to verify this model. Chapter 3 designs an empirical study of blog application. We employ blogs as interactive learning tools for communities of practice in higher education. Three hypotheses were suggested to verify the effects of interactive blogging in empirical setting. A quasi-experiment was conducted to assess the effects of interactive blogging on student attitudes towards peer interaction, learning motivation, and academic achievements. The implication and recommendation are provided at the end of each chapter.

Chapter 2.

Blog acceptance and usage: From the perspectives of technology acceptance and media choice factors

2.1. Research background

Blogs, or weblogs, have been experiencing a rapid growth rate in recent years. Blogs are easy to use and possess interactive features, attracting wide use leading them to be regarded as communication media in web-based information technology (Du and Wagner 2006). However, they differ from other websites in two ways. First, websites tend to have static or rarely changing content. Blogs, on the other hand, are dynamic and are developed to facilitate and accommodate frequent changes in content, particularly by giving readers the opportunity to comment on the primary messages that appear on them (Kim 2005). In most instances, readers will be able to place their contributions on social media such as blogs without requiring authorization. Therefore, fully two-way online communication is made possible (Wright 2006, Kaplan and Haenlein 2010). A second difference is the user empowerment characterized by the ease with which content can be placed on blogs (Du and Wagner 2006).

The creator of the message prepares the content without having to be familiar with special coding and uploads the message to blogs by clicking on the “Publish” button. Therefore, blogs can be considered as easy to use communication media in web-based information technology.

Over the previous two decades, the technology acceptance model (TAM) (Davis 1989, Davis et al. 1989), has been widely used to explain and predict the acceptance behaviors of information systems (e.g. Adams et al. 1992, Agarwal and Karahanna 2000, Karahanna et al.

2006, Venkatesh et al. 2008). The TAM suggests that both perception usefulness and ease of use are key determinants of the adoption of user technology. Although TAM is a well

established model, many studies have extended TAM with other constructs in various web-based information technologies, such as trust in online shopping (Gefen et al. 2003), playfulness in WWW context (Moon and Kim 2001), perceived risk in online transactions (Pavlou 2003), perceived enjoyment in internet-based learning (Lee et al. 2005), and social influence in online gaming (Hsu and Lu 2004). Blogs have been an emerging web-based information technology (Boulos and Wheeler 2007); hence, TAM could be applied to explain and predict the acceptance behaviors of blog. Therefore, our study extends TAM with some other constructs to investigate blog acceptance behaviors.

Blogs are not only web-based information technology, but also media (Kim 2005, Yates 2008, Kaplan and Haenlein 2010). Yates et al. (2008) addressed the genre model (Yates and Orlikowski 1992) to evaluate media usage, including blogs as a form of media. Kaplan and Haenlein (2010) provided a classification of social media according to media richness and self-presentation, and included blogs. Media have been conceptualized as transmission conduits (Axley 1984) or channels (Fisher 1978) through which information can be conveyed.

Media vary in their capacity to convey information, which can influence individual/organizational media choices (e. g. Daft et al. 1987, Carlson and Zmud 1999).

Several media choice theories have been developed to study individual/organizational communication, including media richness (Daft and Lengel 1984, Rice 1992), critical mass (Markus 1987), social influence (Fulk 1993, Schmitz and Fulk 1991), and media experience (Sitkin et al. 1992). Consequently, the purpose of this study is to incorporate the perspectives of technology acceptance and media choice factors to investigate blog acceptance behavior.

Therefore, this study may lead to a better understanding of how the two structures influence blog acceptance behavior. This study applied a structure equation model and conducted an online field survey to investigate the empirical strength of the relationships in the proposed model.

2.2. Literature review

2.2.1. Blog

Weblogs, or blogs, are defined as “frequently modified web pages in which dated entries are listed in reverse chronological sequence” (Herring et al. 2005). The original blogs were used mostly for web pages with links to other sites or blogs of interest, providing blogger commentary for added value (Blood 2002). After mid-1999, when free and easy-to-use blogging software (e.g. Pitas, Blogger, and Groksoup) was released, the nature of blogs changed with numerous blogs becoming more like personal websites containing diverse types of content posted in reverse chronological order. According to Winer (www.scripting.com), a blogging pioneer, blogs have four characteristics: they are personalized, web-based, community-supported, and automated (meaning easy-to-use). Herring (2005) presented the results of the content analysis of 203 randomly-selected weblogs, and proposed that blogs have the following characteristics: they are frequently updated, have reverse chronological order, a personal journal, an asymmetrical exchange, and hyperlinks. Blogs made it feasible for the communication process to be much larger, less technical, with a higher number of users. Therefore, blogs create a platform for dialogues between bloggers and readers. Through conversations initiated by bloggers and engaged in by readers, blog platforms build a solid base of shared experiences and mutual relationships.

Blogs are often viewed as similar to other media such as e-mail, bulletin board systems, and web pages. Blogs are a form of internet media (Kim 2005) and the social media equivalent of personal web pages, coming in a multitude of different variations, from personal diaries describing the author’s life to summaries of all relevant information in one specific field (Kaplan and Haenlein 2010). In the previous few years, blogs have become an increasingly popular form of communication on websites, and have been adopted by users for several

applications in domains such as journalism (Hall and Bavison 2007), business (Tikkanen et al.

2009), and education (Chang et al. 2008). For example, teachers use blogs as a tool for encouraging interaction between students to facilitate learning (Chang et al. 2008). Corporate established blogs act as marketing channels for engaging existing and potential customers (Tikkanen et al. 2009). Two famous business examples include Jonathan Schwartz, CEO of Sun Micro-systems, who maintains a personal blog to improve the transparency of his company, and the automotive giant General Motors. Blogs have become popular social media for facilitating interaction in a variety of specific fields. In addition, blogs are web-based information technology (Du and Wagner 2006). Blog acceptance behaviors can be explained in part by TAM. Consequently, this study will discuss blog acceptance behavior from the perspectives of technology acceptance and media choice.

2.2.2. Technology acceptance model (TAM)

TAM, adapted from the Theory of Reasoned Action (TRA) (Fishbein and Ajzen 1975) and originally proposed by Davis (1986), has become a widely accepted model in the field of information systems to explain and predict an individual’s acceptance of IT (Lee et al. 2004).

TRA suggests that an individual’s behavior is determined by his or her intention to perform the behavior, which in turn is determined by the individual’s attitude concerning the behavior.

TAM is based on TRA’s belief-attitude-intention relationship to explain an individual’s IT acceptance behaviors.

TAM assumes that an individual’s attitude toward use affect behavioral intentions, and an individual’s attitude toward using IT, is determined by two beliefs: perceived usefulness (PU) and perceived ease-of-use (PEOU) (Davis 1989). Davis defined PU as “the degree to which a person believes that using a particular system would enhance his or her job performance”, and PEOU as “the degree to which a person believes that using a particular system would be

free of effort”. Furthermore, PEOU is a determinant of PU because, ceteris paribus, users consider IT more useful when it is requires less effort. Also, there is the belief that PU affects an individual’s behavioral intentions. Furthermore, both beliefs are influenced by external variables, such as development process, system characteristics, and social influences. Figure 2.1 shows the TAM model.

Figure 2.1. The technology acceptance model

Based on TAM, numerous studies have extended the TAM with other constructs to enhance the understanding of an individual’s IT acceptance behavior in a specific context. For example, Gefen et al. (2003) proposed trust as an extended variable of TAM for online shopping acceptance research. Agarwal and Karahanna (2000) addressed cognitive absorption as a structure reflecting an individual’s intrinsic belief in WWW acceptance. Cheng et al.

(2006) extended the TAM with playfulness and risk to explain consumer acceptance of the internet as a channel of distribution. Moreover, other studies have shown that TAM is a robust model of technology acceptance behavior. The TAM has been successfully applied to predict technology acceptance behavior, across time (Venkatesh 2000, 2008), across settings (Vance et al. 2008, Straub et al. 1997), and across samples (Taylor and Todd 1995). The TAM has

not only been applied in job related IT acceptance (e.g. Gefen and Straub 1997, Lederer et al.

2000, Hernandez et al. 2008), but also revised in other IT applications such as entertainment (Hsu and Lu 2004), online consumer behavior (Koufaris 2003, Kwon et al. 2007, Shin 2009), and media technology (Lederer et al. 2000). Since blogs are not only an IT application, but also media, this research attempts to extend TAM using media choice factors to understand an individual’s IT blog acceptance behaviors.

Although the TAM has been widely applied in MIS research, many limitations of the TAM also were discussed (Venkatesh and Davis 2000, Agarwal and Karahanna 2000, Agarwal and Karahanna 2000, Karahanna and Straub 1999). Lee et al. (2003) investigated many TAM studies in a couple of decades and summarized its limitations as follows: The most commonly reported limitation is self-reported use, although 36 studies relied mainly on self-reported use, assuming that self-reported use successfully reflects actual usage. The second limitation is the generalization problem, examining only one information system with a homogeneous group of subjects performing a single task at a single point of time. Other suggested limitations of TAM studies included student samples, a single subject (or restricted subjects), a one-time cross sectional study, single measurement scales, self-selection bias of the subjects.

Consequently, follow-up IT acceptance studies which apply TAM would avoid the limitations.

2.2.3. Media choice factors

Media have been conceptualized as transmission conduits (Axley 1984) or channels (Fisher 1978) through which information can be conveyed. Moreover, some researchers have considered the capacity of different media to convey data (Daft and Lengel 1984, Sitkin et al.

1992), while others have focused on the capacity of different media to convey symbolic meaning (Feldman and March 1981, Trevino et al. 1987). From the different perspectives of media, several interrelated theories and studies have examined a variety of contingencies that affect which media are chosen and how effective choices are likely to be. Several media

choice theories have been developed to study individual/organizational communication, and how to affect individual/organizational media attitudes, behavioral intentions, and usage behaviors (Carlson & Zmud, 1994; Fulk et al., 1995; Webster, 1998; Cameron & Webster, 2005). Webster (1998) summarized the prior literature and outlined the media choice factors, including media richness (Daft and Lengel 1984, 1986, Daft et al. 1987, Rice 1992), critical mass (Markus 1987, Oliver 1988), social influence (Fulk 1993, Schmitz and Fulk 1991), individual characteristic --- media experience (Sitkin et al. 1992), situational factors (Trevino et al 1987, Rice 1992), and media symbolism (Trevino et al. 1990). This study selects media richness, critical mass, social influence, and media experience, which are suited to the context of a blog, while excluding situational factors and medium symbolism. The situational factors were excluded because blogs are a web-based application, that it is not limited by the distance between communication partners. Media symbolism was also excluded because a blog’s symbolism is not clear. Media choice factors are introduced in the following sections.

2.2.3.1. Media richness

Media richness theory (MRT), introduced by Daft and Lengel (1984), suggests that the use of communication media in an organization is a rational process that achieves a match between the information processing tasks and the media capacities. Daft and Lengel (1986) defined media richness as the capacity of media to evolve shared meaning, overcome different frames of reference, and clarify ambiguous issues to change understanding in a timely manner.

Media richness could be measured by four criteria sets (Daft and Lengel 1986), including (1) capacity for immediate feedback, (2) multiple information cues, (3) personalization, and (4) language verity. MRT proposed that an organization processes information to reduce uncertainty and equivocality (Daft and Lengel 1986). The uncertainty was defined as the difference between the amount of information required to perform the task and the amount of

information already possessed by the organization (Galbraith 1977). The equivocality means that multiple and conflicting interpretations of an organizational situation exist (Weick, 1979).

Moreover, organizations can facilitate the amount of information to reduce uncertainty and the richness of information to reduce equivocality (Daft and Lengel 1986).

Rich media are thought to be best when communication is ambiguous. A richer medium can be seen as equally useful for unambiguous tasks as for ambiguous ones (Schmitz and Fluk, 1991). The capacity of process information is as diverse as the different communication media.

Schmitz and Fulk (1991) ranked the order of media richness as face-to-face, telephone, e-mail, personal written text (letters, memos), formal written text (documents), and formal numeric text. Face-to-face communication would be the richest medium because it provides maximum immediate feedback, multiple cues via body language and tone of voice, and the message context is expressed in natural language.

Many blogs offer communication tools for supporting interactions with others, and the most distinctive characteristic are comments and “Trackback” (Miura and Yamashita 2007), a reverse hyperlink tracking the referrer weblogs. Blogs are usually managed by one author only, but readers can leave a comment on posted entries and authors can answer it with another comment or by posting a subsequent or revised entry (Kaplan and Haenlein 2010).

Therefore, blogs provide the capacity for feedback through readers’ comments, which are managed by the author, allowing the author to maintain his own personal requirements. Also, the blog readers can maintain their personal requirements through “Trackback”. Moreover, multiple information cues are present on blogs, because the majority of blogs provide multimedia capability (such as pictures, music, and emoticons) to very different cues more than just text content with the same click-and-post ease (Du and Wagner 2006). Consequently, the media richness of blogs can be measured by the set of media richness criteria provided by Daft and Lengel, and blogs fall somewhere on the media richness scale.

Numerous studies have been conducted using the MRT to investigate media selection and usage behavior (e.g. Dennis and Kinney 1998, Carlson and Zmud 1999, Trevino et al.

2000, Lim and Benbasat 2000, Cameron & Webster, 2005). Trevino (2000), for example, found that general attitudes toward different media (including e-mail, fax, letters, and face-to-face meeting) were influenced by perceived media richness. Moreover, new media attitudes were also influenced by person/technology interaction factors. Dennis and Kinney (1997) tested the media richness in computer-mediated and video communication to exam the effect of cues, feedback, and task equivocality. Therefore, media richness was proposed as the factor that reflected the acceptance behaviors of blog. In this study, we used the four criteria (immediate feedback, multiple information cues, personalization and language verity) defined by Daft and Lengel to measure the media richness of blogs.

2.2.3.2. Critical mass

Critical mass refers to “the idea that some threshold of participants or actions has to be crossed before a social movement explodes into being” (Oliver et al. 1985). This definition suggests that critical mass is the basis for producing collective actions. Blog acceptance requires the participation and collective actions from all individuals whose activities are affected by the technology. Markus (1987) indicated that “even individuals who would prefer to use interactive media may not really perceive these media to be viable options in the absence of universal access”. Moreover, Markus and Connolly (1990) showed that interactive media might fail without securing a critical mass of users for the technology. Hence, the success of blog acceptance is not only dependent on an individual’s use of blogs, but on other responses to this use. If few people are willing to contribute to the blog, it will not be effectively used. Furthermore, from the network externality perspective, critical mass refers to the effect that the value of technology to a user increases with the number of people who

adopt it (Nault and Dexter 1994, Wang and Seidmann 1995).For example, the more people who use e-mail, the more valuable e-mail is to each user. Online social networks work in the same way, with sites like Twitter and Facebook being more useful as more users join.

Applying network externality perspective, Luo and Strong (2000) pointed out that the users may develop a perceived critical mass through interaction with others. The perception of critical mass is rapidly strengthened as more people participate in network activities.

Consequently, achieving a “critical mass” of users has been recognized as the key for successful media acceptance (Markus and Connolly 1990, Grudin 1994, Lim et al. 2003, Cameron & Webster, 2005; Slyke et al. 2007). Therefore, critical mass was proposed as the factor that reflected blog acceptance behaviors.

2.2.3.3. Media experience

Media experience, representing individual use, skills, and comfort with the media (King and Xia 1997), plays an important role in influencing user attitudes and can facilitate or constrain choices and general use (Sitkin et al. 1992, King and Xia 1997). Some individuals may have little or no experience or skill with media and as a result have negative attitudes toward it and/or may avoid using it (Webster 1998). Schmitz and Fulk (1991) indicated that expertise in using new media facilitates choice and use. Moreover, human behavior is more about self-interest, and efficiency oriented than rationality motivated (Williams 1985). But human behavior is also experience based. If individuals are uncomfortable or unfamiliar using a new medium, and view learning to use a new medium as more time consuming and inefficient than traditional media, they will choose a familiar medium rather than a rationally efficient medium (King and Xia 1997).

Carlson and Zmud (1994) indicated that media choice is determined by the fit of the perceived media richness and the perceived information richness. These perceptions are built

upon previous experience with the media in addition to the objective view of media characteristics. Experience enables the development of familiarity, expertise, and comfort with the media, which in turn enables users to improve his attitude toward using the media, and to facilitate appropriate media choice. For example, because individuals have high levels of expertise and familiarity with face-to-face communication, they would naturally and instinctively prefer this medium over other unfamiliar ones. This argument is consistent with the study by Schmitz and Fulk (1991), which found face-to-face communication to be the richest medium. Empirical studies (Schmitz and Fulk 1991, Webster 1998) provided confirmation of positive relationships between media attitudes and media experience.

Accordingly, media experience was proposed as the factor that best reflected blog acceptance behaviors.

2.2.3.4. Social influence

Fulk et al. (1991) presented the social influence model of technology usage to explain media choices. They suggested that social influences such as work group norms, and coworker and supervisor attitudes and behaviors can influence individual/organizational media attitudes, use and choice. According to social influence theory, it is proposed that media perceptions vary and are, at least in part, socially constructed. In addition, based on the theory of reasoned action, an individual’s behavioral intentions are influenced by subjective norms as well as attitude. Innovation diffusion research also suggests that user adoption decisions are influenced by a social system that goes beyond an individual’s decision style and the characteristics of the IT (Valente 1996).

The effect of social influences on media choices has been empirically supported in a number of studies (Schmitz and Fulk 1991, Fulk 1993, Kraut et al. 1998, Gu and Higa 2009).

Fulk et al. (1991), for example, found that attitudes and e-mail usage were affected by social influences from coworkers, supervisors, and networks. Kraut et al. (1998) found that people

used a particular system (e.g. video telephone) more when more people in general were using it. Gu and Higa (2009) indicated that social influence was identified as the most important factor for the primary medium selection in multiple media usage settings, followed by a rational factor and environment factor. As empirical examples, Facebook and Twitter are

used a particular system (e.g. video telephone) more when more people in general were using it. Gu and Higa (2009) indicated that social influence was identified as the most important factor for the primary medium selection in multiple media usage settings, followed by a rational factor and environment factor. As empirical examples, Facebook and Twitter are