Keywords

1 Introduction

Along with the rapid growth of the Internet, online information search has become a prevalent Internet activity. The Internet is by definition an interactive medium (Rust and Varki 1996). Despite the potential for interactivity provided by the Internet, little attention has been paid to how interactivity might be more fully utilized (Johnson et al. 2006).

Drawing upon the affordances of digital representation of self in ACG website, participants assume the role of social actor in order to problem solve and achieve goals. The social dynamics in ACG website have led to the emergence of a broad range of sociocultural norms and artifacts, social structures and hierarchies, as well as social roles that impact users’ behavior. However, little is known regarding how social behavior emerges within these environments and what factors contribute to such behavior.

ACG products and services are seldom routine purchases (Lee and You 2014). Choices of ACG products usually involve considerable emotional significance and perceived cost risk for the individual. Prior studies investigate factors that affect consumer preferences in online shopping websites. And, seldom distinguish between pre-purchase and post-purchase experiences and tend to focus on post-purchase assessment only. Therefore, this study aimed at the Internet users’ searching behavior, and further probed into users’ socialness of websites satisfaction.

2 Literature Review

2.1 Web Interactivity

Srinivasan et al. (2002, p. 42) operationalize interactivity as the availability and effectiveness of customer support tools on a website, and the degree to which two-way communication with customers is facilitated. Perceived interactivity is measured by user evaluations of the interactivity of the evaluated website using the Measures of Perceived Interactivity (MPI) based on previous researches.

Lee (2005) identified (1) user control, (2) responsiveness, (3) personalization, and (4) connectedness as important components to interactivity in a mobile commerce setting has particular relevance to the current work. We adopt these three components: user control, responsiveness, connectedness, to fit on the website environment. User control refers to the user’s ability to control the information display and content. Responsiveness refers to the site as being able to respond to user queries. Finally, perceived connectedness refers to whether customers share experiences regarding products or services offered with other visitors to the mobile site.

2.2 Consequence of Perceived Interactivity

Users visit websites not only for information, but also for entertainment. Utilitarian performance results from user visiting a site out of necessity rather than for recreation; therefore, this aspect of performance is judged according to whether the particular purpose is accomplished (Davis et al. 1992; Venkatesh 2000).

The hedonic aspect of Web performance is the evaluation of a website based on the assessment by users regarding the amount of fun, playfulness, and pleasure they experience or anticipate from the site. It reflects a website’s entertainment value derived from its sensory attributes, from which users obtain consummatory affective gratification (Batra and Ahtola 1990).

Thus the hypothesis formulate as follow:

Hypothesis 1a. Higher levels of user perceived interactivity will have positive evaluate on perceived utilitarian. Hypothesis 1b. Higher levels of user perceived interactivity will have positive evaluate on perceived hedonic.

Hypothesis 2a. Higher levels of user perceived utilitarian will have positive evaluate on perceived satisfaction. Hypothesis 2b. Higher levels of user perceived hedonic will have positive evaluate on perceived satisfaction.

2.3 Socialness

While B2C Internet sales continue to increase, the rate of increase in online sales is slowing. Bhatnager et al. (2000) argued that positive attitudes toward and acceptance of e-commerce may be inhibited by a lack of product ‘touch’. Jahng et al. (2007) pointed out lack of interaction with a representative from the organization may be the reason, too. Wakefield et al. (2011) found that if websites infused with cues that express familiarity, helpfulness and intelligence (for example) generate a social response from users of the site can leading to greater enjoyment of the website.

Prior research has demonstrated that virtual environments are designed to promote social interaction. Moon (2000) defined social response as people tend to treat computers as social actors even when they know that machines do not possess feelings, intentions, selves, or human motivations. In this study we utilize Moon’s concept of attraction (likeable, friendly, kind, helpful), reciprocity (socially appropriate sequence), intimacy to measure socialness in website interaction. Hypothesis 1c. Higher levels of user perceived interactivity will have positive evaluate on perceived socialness. Hypothesis 2c. Higher levels of user perceived socialness will have positive evaluate on perceived satisfaction.

2.4 Website Satisfaction

Satisfaction is a post-consumption evaluation based on the comparison between the expected value in the pre-consumption stage and the perceived post-consumption value after the purchase or after the use of services or products (Oliver 1981; Ravald and Gröroos 1996). This is especially true for companies selling goods and services on their websites. Customers must be satisfied with their experience with the website or they will not return. Barnes and Vidgen (2002) argues that socialness has a strong association with satisfaction¸ but how about it for ACG users on entertainment information still not clear. Hypothesis 1d. Higher levels of user perceived interactivity will have positive evaluate on perceived satisfaction.

2.5 Internet Users’ Searching Behavior

Product information seeking often is portrayed as a critical early stage in the consumer buying process (Haubl and Trifts 2000).

Novak et al. (2003) drawing nine distinctions between goal-directed and experiential behavior is particularly important in online environments, because the experiential process is, for many individuals, as or even more important than the final instrumental result. Thus we propose hypothesis 1: goal-directed and experiential users have different online searching experience on the same ACG portal site. Hypothesis 3. Goal-directed and experiential users have differences online searching experience on ACG portal site.

3 Method

3.1 Measures

To test the hypothesis, three popular ACG portal sites ranked by alexa were selected in Taiwan. A pilot test was conducted with 148 undergraduate students from vocational universities of north Taiwan. Additionally, the interviewees’ compeers who confirmed to the characteristics of cosplay groups were invited to participate in the questionnaire investigation. Two groups of goal-directed (score ≤ 21) and experiential (score ≥ 27) were differentiated with their reports score of six questions, the sample size of goal-directed is 65 the other one is 83. They all visited three selected ACG websites before.

To analyze the relationship among these variables and examine the fitness of the conceptualized framework, this study conducts Structural Equation Modeling (SEM). The questionnaire is designed in Likert 7 point scale and adjusted according to the pilot test. Participants are asked to fill in the questionnaire and indicate their current situation for each variable item (1 = strong disagreement and 7 = strong agreement).

3.2 Model Evaluation and Modification

Based on literature reviewed, a structural equation modeling was conducted to evaluate the fit of the research model (Fig. 1).

Fig. 1.
figure 1

Research model

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4 Item Purification

Some of the measurement items may not be relevant to the scale, hence a “purification” process is needed to identify the effective items by eliminating the relationship between the individual item and the entire scale. The coefficient alpha and the item-to-total correlation for each item were computed, then the items whose item-to-total correlations were low and whose removal increased the coefficient alpha were deleted. In addition, squared multiple correlation for each item, the multiple R2 from the regression analysis with the very item as the dependent variable and all other items as independent variables, was also computed to determine if the item should be deleted due to its low value. Thus, the internal consistency of the set of items was examined.

5 Result

After item purification by pilot test, the questionnaire is proposed as Table 1.

Table 1. Questionnaire for survey
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