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Influence of Facebook game players' behavior on flow and purchase intention.

Use of the social media website Facebook has become increasingly prevalent worldwide, with over 1.1 billion users as of January 2013, of whom 13,303,940 reside in Taiwan (Checkfacebook, 2013; Quan, 2013). Many previous researchers have focused on users' purchase intention toward online games, including factors such as game design and demographics (Kim, Park, Kim, Moon, & Chun, 2002). According to Kim et al., differences in game design and demographics may reflect differences in purchase intention, and an understanding of player purchase intention can benefit the developer's revenue. But how do game developers make users like a game sufficiently well to increase their purchase intention? Previous researchers demonstrate that the flow experience significantly impacts players, because flow sways human behavior (Csikszentmihalyi, 1975, 1990); in fact, players are often willing to pay a high price to maintain the optimal flow experience.

Hence, we also investigated how flow influences purchase intention. Bichler, Field, and Werthner (2001) claim that charging different consumers varying prices for similar transactions is accomplished by exploiting differences in consumer estimates or price perception. Following the above-mentioned researchers' results, in our study we explored the way in which players' flow relates to four factors: sociality, interactivity, challenge, and novelty. In addition, we examined how flow and price perception influence purchase intention. Thus, we formed the following research questions:

1. Do sociality, interactivity, challenge, and novelty influence flow?

2. Does flow influence purchase intention?

3. Does price perception influence purchase intention in Facebook game stores?

Theoretical Background and Hypotheses


According to Schutz (1966), human social interaction is founded on purposeful, mutual exchanges between two or more people. Moreover, interpersonal activities can result in either psychological closeness or distancing (Shi, 1996). In a gaming scenario, players garner a sense of individuality in relation to the other players, and also gain a sense of achievement by playing well and receiving compliments from the other players. Thus, according to the research cited above, sociality is operationally defined as players' recognition of their social position through interpersonal interactions while they are playing Facebook games.


Interactivity is affected by the degree of players' involvement in changing form and content within mediated environments (Steuer, 1992). Communicative strategizing is then based on past interactions (Garrison, 1993). Both communicators and audiences provide responses or fulfill each other's communication needs. Thus, according to the research cited above, interactivity is operationally defined as the degree of social cohesion provided by interactions on Facebook and in online games.


Online game players are faced with the challenge of competition from other players during a game (Fabricatore, Nussbaum, & Rosas, 2002), including situations in which players must seek information online (Skadberg & Kimmel, 2004). Thus, according to the research cited above, challenge is operationally defined as the overcoming of perceived difficulties, including competition from other players, in Facebook games, which provides a sense of accomplishment.


Trevino and Webster (1992) included cognitive curiosity when defining the concept of novelty during computer use. In this study, novelty is operationally defined as the unexpected, unusual, and rare events that one experiences when playing Facebook games.

Flow Theory

After observing numerous individuals, including athletes and chess players, Csikszentmihalyi (1975) advanced the concept of flow, which is used to describe the experience of a person so completely immersed in an activity that material changes in the environment go unnoticed. Being "in the flow" brings tremendous joy and is often pursued at a high cost (Csikszentmihalyi, 1975, 1990). Flow is an enjoyable, exploratory state (Trevino & Webster, 1992) and, as an optimal experience, both in work and leisure (Choi & Kim, 2004), flow provides a holistic experience of total immersion (Ha, Yoon, & Choi, 2007). Furthermore, online game players may be persuaded to purchase commodities through online transactions. Thus, based on the research cited above, flow is operationally defined as players' experiencing complete immersion in the enjoyment of games, inducing willingness to pay a high price for the experience of optimal and heightened concentration.

Price Perception

Price perception is the consumer's evaluation of the worth of a product or service, translated and assessed through personal and psychological filters (Kashyap & Bojanic, 2000). Thus price perception is operationally defined as a player's personal and psychological filtering of the cost and worth of products available in Facebook game stores.

Purchase Intention

Purchase intention is the probability that, after being exposed to advertising, a consumer will purchase a product (Dodds, Monroe, & Grewal, 1991). Thus, purchase intention is operationally defined as the behavioral tendency of players to pay for products available in Facebook game stores.


Figure 1 illustrates the conceptual scheme we employed in the present study. To maintain an optimal experience, players are often willing to pay a high price to maintain flow (Csikszentmihalyi, 1975, 1990). As Facebook games are typically free, how does the absence of a price influence players and, consequently, their online store purchase intention? On the basis of our literature review, Hypotheses 1-4 were formulated. As the amount spent on other purchases during an online transaction increases, the probability of consumers buying an extra item that they did not originally intend to purchase also increases (Csikszentmihalyi, 1975, 1990). The proposed positive relationship between flow and purchase intention is presented as Hypothesis 5. Online game stores are an emerging form of online commerce. Delaying price comparisons essentially implies reintroducing search costs. This can usually be done by charging consumers different prices for similar transactions, accomplished by exploiting differences in consumer estimates (Bichler et al., 2001). On the other hand, price differences are focused on the operation of a socially acceptable activity: in this case, Internet usage. However, the key factor influencing purchase is price. As Facebook games are built on models similar to emergent online games, in this study we investigated whether or not players' price perception of Facebook game store commodities affects their purchase intention. Previous researchers have indicated a positive relationship between price perception and purchase intention, which provides the basis for Hypothesis 6.

In summary, based on the results of the literature reviewed and the research model in Figure 1, we formulated the following hypotheses:

Hypothesis 1: There will be a positive relationship between sociality and flow.

Hypothesis 2: There will be a positive relationship between interactivity and flow.

Hypothesis 3: There will be a positive relationship between challenge and flow.

Hypothesis 4: There will be a positive relationship between novelty and flow.

Hypothesis 5: There will be a positive relationship between flow and purchase intention.

Hypothesis 6: There will be a positive relationship between price perception and purchase intention.


Participants and Questionnaire

We designed the questionnaire for this study by consulting past literature with an emphasis on a research scenario focused on Facebook games. Adjustments were made to the questionnaire after consulting with experts in the field of information management from National United University and National Taipei University and viewing the results of a pilot study. We developed a questionnaire using MySurvey ( Participants were 194 Facebook game players selected using convenience sampling through an online questionnaire tool. Of the respondents, 41.2% were male and 58.8% were female; 13.4% were aged under 19 years old, 83.5% were 20 to 29 years old, and 3.1% were 30 to 39 years old. In terms of the degree of exposure to Facebook games, 10.30% had been playing for less than 3 months, 3.61% for 3-6 months, 6.70% for 6-12 months, 30.93% for 1-2 years, 27.84% for 2-3 years, and 20.62% for more than 3 years. With regard to time devoted to playing each day, 56.7% spent less than 30 minutes, 18.6% spent between 30 minutes and 1 hour, 12.9% spent 1-2 hours, 4.6% spent 2-3 hours, 3.1% spent 3-4 hours, 1.5% spent 4-5 hours, and 2.6% spent more than 5 hours.

Data Analysis

We employed SPSS for descriptive statistical analysis, SmartPLS version 2.0 to conduct confirmatory factor analysis (CFA) to assess reliability and discriminant validity, and structural equation modeling to test the research hypotheses.

Reliability. We measured reliability using the average variance extracted (AVE) and combinatorial reliability (CR). A CR of at least 0.6 and an AVE above 0.5 denote a high level of reliability. Purchase intention had an AVE of .9013 and the CR was .9648. Challenge had an AVE of .5218 and the CR was .8934. Flow had an AVE of .7194 and the CR was .8838. Interactivity had an AVE of .7439 and the CR was .9355. Novelty had an AVE of .6329 and the CR was .9111. Price perception had an AVE of .7654 and the CR was .8669. Sociality had an AVE of .6208 and the CR was .9075. These results indicate a high level of reliability for all factors. The reliability measures for purchase intention, challenge and accomplishment, flow, novelty, price perception, and sociality and identity (see Table 1) also indicate a high level of reliability.

Validity. In terms of convergent validity, when the square root of the AVE of a concept is higher than the coefficients of that and other concepts, the measurement of that concept can be considered to have greater discriminant validity. The comparison matrix of the square root of AVE levels and other correlational coefficients are shown in Table 2. The square roots of the AVE level of each concept were higher than those of the coefficients of that concept and other concepts, indicating high validity for purchase intention, challenge and sense of accomplishment, flow, interactivity, novelty, price perception, and sociality and identity. Thus, all factors exhibited good reliability and convergent validity.


The results of our research are presented in Figure 2. They explain 48% of the variance in flow and 58.2% of the variance in purchase intention. Flow has significant positive relationships with interactivity, challenge, and novelty; thus, Hypotheses 2, 3, and 4 were supported. There is a significant positive relationship between flow and price perception in that flow positively affects purchase intention; thus, Hypotheses 5 and 6 were supported. However, sociality does not affect flow; thus, Hypothesis 1 was not supported. In addition, interactivity, challenge, and novelty are significantly affected by flow; while flow and price perception are significantly affected by purchase intention.


Certainly, Facebook game designers want users to be satisfied with their products, to increase users' flow experience and purchase intention. Thus, flow experience and the other factors we investigated in this study, including interactivity, challenge, and novelty, could play an important role in the economic success of Facebook games.

In most of the studies presented in the literature review, sociality was not significantly related to flow because it has been operationally defined as players' recognition of their social position through interpersonal interactions during Facebook games. However, based on our results sociality exhibited no significant influence because, in contrast with other online games that require teams, most Facebook games are played solo. Consequently, relevant factors of sociality (e.g., interactions with other players and expanding one's circle of friends) did not significantly influence Facebook game flow.

First, our results revealed that interactivity, challenge, and novelty influenced players' flow in Facebook games, and flow and price perception influenced players' purchase intention for Facebook games.

Second, our results demonstrated that flow has a significant impact on player behaviors, such as purchase intention. This finding is similar to those of the above-mentioned studies and supports Csikszentmihalyi's (1975, 1990) findings regarding flow maintenance. In accordance with the reviewed literature, in our study we found that game designers want to increase users' flow experience to facilitate increased purchase intention.

Last, our results indicate that the price perception of products influences Facebook game players' purchase intention. These results support the work of Kashyap and Bojanic (2000) in the definition and analysis of price perception as the consumer's evaluation of the work of a product, translated or assessed through personal and psychological filters. Differences in product price influence willingness to buy games by exploiting differences in consumer estimates of prices. In other words, if the price perception is unreasonable, it reduces, or even eliminates, the possibility of users buying the product.

Our findings suggest certain implications for Facebook management. To increase players' flow or immersion in games, designers should focus on interactivity, challenge, and novelty. In addition, games' difficulty, interactivity, and originality can further enhance players' flow experience. Regarding interactivity, management should improve game interfaces and simplify operational procedures. The survey we conducted in this study showed that most users spent an average of 1 hour per day playing Facebook games; therefore, simplifying game content favors users who play games for a limited period. At the same time, players should perceive the game as challenging within that limited period to maintain a high level of interest. One example is the Happy Farm game, in which players can steal other players' harvests. Furthermore, novelty is a characteristic that increases the players' likelihood of continuing to play the game (Trevino & Webster, 1992); thus, game themes should be constantly updated, thereby producing surprising, pleasurable new elements. For instance, during Christmas, players typically anticipate updates that incorporate Christmas-related elements. In addition, players have certain perceptions of the price of game products, and those who perceive that a product is worth purchasing or have experienced a certain level of game flow may be willing to purchase the product. Therefore, game features that assist players in completing game challenges or advancing through the game increase their purchase intention.

Directions for Future Research

Persuading players of free Facebook games to purchase a game is difficult. Therefore, Facebook management should enhance price perception to increase players' purchase intention. To achieve this, game companies should focus on price perception as well as interactivity, challenge, and novelty, which enhance players' flow experience. Further, most players in our study spent 1 hour per day playing Facebook game, so designers have a short time in which to attract players, increase flow, and increase purchase intention. To increase and extend the scope of this study, future researchers could explore how best to attract players and enhance their purchase intention.


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Hua-Jung Liu and Yih-Chearng Shiue

National Central University

Hua-Jung Liu and Yih-Chearng Shiue, Department of Information Management, National Central University.

Correspondence concerning this article should be addressed to: Hua-Jung Liu, Department of Information Management, National Central University, No. 300 Jhongda Road, Jhongli City, Taoyuan County 32001, Taiwan, ROC. Email:

Table 1. Reliability Analysis

Concept               AVE     CR     Cronbach's     Test results

Purchase intention   .9013   .9648   .9450
Challenge            .5218   .8934   .8651
Flow                 .7194   .8838   .7980
Interactivity        .7439   .9355   .9139        High reliability
Novelty              .6329   .9111   .8823
Price perception     .7654   .8669   .6991
Sociality            .6208   .9075   .8778

Table 2. Matrix of the Correlational Coefficients Between Factors

[square root of (AVE)]     PI         C         F         I

PI                       (.9494)
C                        .4142     (.7224)
F                        .4310     .5887     (.8482)
I                        .3491     .7059     .6447     (.8625)
N                        .3450     .6666     .6019     .6930
P                        .7526     .4099     .4200     .3312
S                        .3809     .6296     .5522     .7882

[square root of (AVE)]      N         P         S

N                        (.7956)
P                        .3202     (.8634)
S                        .5435     .3755     (.7879)

Note. PI = Purchase intention; C = Challenge; F = Flow; I =
Interactivity; N = Novelty; P = Price Perception; S = Sociality.
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Author:Liu, Hua-Jung; Shiue, Yih-Chearng
Publication:Social Behavior and Personality: An International Journal
Geographic Code:1USA
Date:Feb 1, 2014
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