The development of online games is becoming popular and is flourishing. The game companies continue to launch new ideas and innovative games, such as World of Warcraft, Legend of League, Hearthstone
and so on. Players can interact or compete with other players in their virtual avatars in online games [1
]. In recent years, massively multiplayer online games (MMOGs) have been attractive and players around the world have become highly attached to them. Players can build their own team with friends or people from all sides and play against other players’ teams [3
With the rapid development of information technology (IT) and artificial intelligence (AI), knowledge sharing and knowledge transfer in the network are getting faster and farther. The emerging technology such as AI can help companies discover, categorize, and share knowledge that contains valuable big data [4
]. More specifically, AI can aid to transform big data into useful information and required knowledge required for companies to develop correct marketing and decision-making for sales strategies [5
]. Therefore, the companies expect AI can help in customization, user personalization, product innovation, and reinforced marketing performance and readiness. On the other hand, people who have similar traits or interests gather in the virtual space of the internet. There are many kinds of discussion platforms. For example, online discussion forum (e.g., Mobile 01, PTT), social networking sites (e.g., Facebook), or online game discussion platforms (e.g., Bahamut, Gamebase, and online discussion space of game companies). Players share game information, exchange game experience, and use cyberspace to convey their thoughts and feedback about the games, which is similar to face-to-face communication between people in the real world. In general, this behavior is a kind of consumer engagement. Consequently, companies should use these emerging digital technologies to understand consumers’ thought and to provide appropriate products or services to them.
With the advancements of IT and changes in time, the marketing strategy of enterprises needs to make substantial adjustments to satisfy consumers’ needs. Consumers become more proactive and have the courage to express their opinions, ideas, and even complaints. Accordingly, companies must pay more attention to the voices of consumers than before and fulfill the needs of different consumers for the products of companies.
The traditional marketing strategy has been redefined under the rapid changes of time and technological advancements. Consumers are no longer passive, but they are more energetic in expressing their ideas, suggestions, and complaints. Consumer engagement hence has a considerable influence on the relationships between enterprises and consumers. Consequently, companies have responsibilities to listen carefully to the advice of consumers and to satisfy the needs of various consumers.
With the emergence of digital technology and the popularity of the Internet, surfing the Internet is becoming a part of personal life so that consumers can conveniently express their opinions. As reported by the International Telecommunications Union in 2017, the percentage of individuals using the Internet in Taiwan is 92.78%, indicating that there are over 21.86 million people who had experience in using the Internet in Taiwan. In this investigation, the first top three countries/regions are Kuwait, Bermuda, as well as Iceland, and Taiwan is ranked 21st among 229 countries/regions. In East Asia, Taiwan is only behind the Republic of Korea. Another investigation proposed by Market Intelligence and Consulting Institute (MIC) of Taiwan in 2018 indicates that the most popular Internet services include video streaming, social media, instant messaging, online game, and online shopping. The usage of social media accounts for 80.6%; hence, it can be seen that online interactive mechanisms such as social networking sites have profoundly affected people’s daily lives and become an important tool for interpersonal interaction. This investigation further illustrated that consumers prefer to express opinions in social media as well as online discussion communities, and about 89.1% of consumers are influenced by electronic word-of-mouth when they make purchasing decisions. If companies can understand the consumer’s perception of the products as well as services through social media, they can use consumer engagement behavior to help the improvement of their products and services to better meet the needs of consumers. By doing so, the sales revenue and market share will be increased.
Game players (consumers) can quickly and conveniently interact with other players and game operators (companies) through various community discussion spaces, online forums, and other communication channels. The game companies themselves can also use these channels to effectively interact with players and establish a good interactive relationship [8
] to improve their games and reinforce the competitive advantage of firms. In the prior research of consumer engagement, scholars found that consumers were involved in the process of services or products to a certain degree. For example, consumers might mention their preferences so that the service providers can devote to meet consumers’ needs. From the consumer’s point of view, consumer engagement creates value for the consumer, and antecedent research also found that consumer engagement can increase the productivity of the organization and enhance the value of the consumer relationship [9
]. However, related research in consumer engagement in the online game scenario is limited.
Additionally, researchers who studied online games mainly analyzed the motivation and feelings for playing online games as well as engagement behaviors in online gaming communities [10
], whereas another research path focused on the negative effects of online game, such as game addiction [13
], time distortion [14
], menticide [15
], and cheating behaviors in online gaming communities [17
]. Nevertheless, antecedent research has rarely taken the positive effects of the online game into consideration [19
]; therefore, this study will adopt the perspective of online game players’ consumer engagement behavior. Moreover, the analysis unit of this research is used as an individual perspective to analyze whether online game players have social identity and consumer engagement behavior through their virtual experience (social presence and telepresence).
Taken together, when investigating consumer engagement in the online game, it is necessary to ponder not only the impact of virtual presence but also how the different kinds of social identity influence consumer engagement consecutively under the perspective of the team. As a result, this research takes social presence, telepresence, social identity as research themes to discuss the effect of consumer engagement.
The remainder of this study is organized as follows. The next section reviews the literature on consumer engagement, social presence, telepresence, cognitive social identity, and affective social identity. The research framework and hypotheses are later proposed depending on prior literature. The characterization of the constructed measures and data collection process is described in Section 3
. Next, the data analysis results are illustrated. Ultimately, the practical implications and suggestions for future research are presented.
The core theme of this study is to analyze the causal relationship between social presence, telepresence, cognitive social identity, emotional social identity, and consumer engagement behavior in the online gaming communities as well as verify the overall fitness of the research model; hence, structural equation modeling (SEM) is used. SEM is a statistical technique used to verify the suitability of a theoretical model, which can simultaneously estimate the measurement indicators and potential variables in the model, not only to estimate the measurement error of the indicator variable in the measurement process but also to evaluate the reliability and validity.
SEM includes measurement model and structure model. Measurement mode analysis is used to illustrate the relationship between potential constructs and measured variables and to measure the reliability and validity. The structural model analysis illustrates the causal relationship of potential constructs and calculates the amount of explanatory and unexplained variation [75
4.1. Measurement Model
IBM SPSS Amos 21.0 was used to conduct confirmatory factor analysis (CFA) to examine the measurement model. The whole model fit was evaluated by eight common goodness-of-fit indexes: the ratio of chi-square to degrees of freedom (chi-square/df), goodness of fit index (GFI), adjusted goodness of fit index (AGFI), non-normalized fit index (NNFI), comparative fit index (CFI), incremental fit index (IFI), relative fit index (RFI), and root mean square error of approximation (RMSEA). The results of these indexes, together with their recommended values for the overall model fit, are shown in Table 2
. All the model-fit indexes surpassed recommended cut-off value suggested by antecedent studies [76
], therefore, reporting that the measurement model illustrated a good model fit with the data gathered (chi-square/df = 2.064, GFI = 0.926, AGFI = 0.894, NNFI = 0.966, CFI = 0.973, IFI = 0.973, RFI = 0.936, RMSEA = 0.056). Accordingly, the further analyses could be executed to assess the psychometric features of the measurement model such as individual item reliability, convergent validity, and discriminant validity.
As indicated in Table 3
, the test of individual item reliability was evaluated by using factor loading, which should exceed 0.70 [76
]. Convergent validity was assessed via composite reliability (CR) and average variance (AVE). As shown in Table 3
, the CR of all constructs surpasses 0.8, obviously higher than the cut-off level of 0.70. Meanwhile, the AVE of all constructs are also greater than the recommended value of 0.5 [77
], indicating the adequacy of individual item reliability and convergent validity of the measurement model [76
]. To examine discriminant validity, the comparisons of correlations between constructs with the square roots of AVE of each construct [78
] were proceeded to verify it. As reported in Table 4
, the correlations between constructs were lower than the square roots of AVE, meaning discriminant validity is confirmed. Taken together, the measurement model illustrated sufficient reliability, convergent validity, and discriminant validity.
4.2. Common Method Bias
Because the data were self-reported and collected from a single source, this study conducted the Harman’s one-factor test to evaluate common method bias [79
]. Four factors with eigenvalues greater than 1.0 (ranging from 1.34 to 8.09) emerged from the un-rotated factor solution with the principal component method. The total percentage of variance accounting for these four components is 74.32. In the meantime, the analysis results also indicate that the first component accounts for less than 50% of the total variance. Additionally, this study further conducted single-factor model to examine the effect of common method bias. The single-factor model led to X2
(135) = 2396.337, compared with the measurement model X2
(120) = 247.693, the measurement model is obviously superior to the single-factor model [80
]. According to the results of these two analyses, the common method bias was not a problem in this study.
4.3. Structural Model
In the part of the structural model, the model fit was also examined and reported in Table X. The results indicate that all seven indexes for structural model (chi-square/df = 2.639, GFI = 0.902, AGFI = 0.868, NNFI = 0.947, CFI = 0.956, IFI = 0.957, RFI = 0.918, RMSEA = 0.070) attained the acceptable level and suggested a good model fit, meaning that the structural model is appropriate for advanced statistical analysis in terms of hypotheses testing.
The results of hypotheses testing, path coefficients, t values, and SMC values are described in Figure 2
. As expected, all the hypothesized relationships are supported. Social presence and telepresence both had significant positive effects on cognitive social identity and affective social identity (γ = 0.378, p
< 0.001; γ = 0.651, p
< 0.001; γ = 0.337, p
< 0.05; γ = 0.148, p
< 0.05, respectively). Cognitive social identity and affective social identity both had significantly positive influences on psychological engagement (γ = 0.364, p
< 0.001; γ = 0.418, p
< 0.001, respectively). Finally, psychological engagement demonstrated significantly positive effect in affecting behavioral engagement (γ = 0.637, p
< 0.001). Overall, the research model explains 34.9% of the variance in cognitive social identity, 51.7% in affective social identity, 42.7% in psychological engagement, and 40.5% in behavioral engagement.
It is notable that the direct and total effects of cognitive social identity and affective social identity on psychological engagement were 0.364 and 0.418, respectively. Affective social identity demonstrated stronger direct and total effects on psychological engagement than cognitive social identity. Among the influences of virtual experience (social presence and telepresence) on cognitive social identity and affective social identity, the results indicate that social presence had stronger effects on cognitive social identity and affective social identity. Taken together, the summarized results are shown in Table 5
Despite the flourishing growth in the online game market, limited studies have explored the interaction of related constructs in the online game and online gaming communities, including virtual experience (social presence and telepresence), social identity factors (cognitive social identity and affective social identity), as well as consumer engagement (psychological engagement and behavioral engagement). This research is devoted to filling the knowledge gap by establishing and verifying a theoretical framework of consumer engagement behaviors in online gaming communities that were found in the current literature on virtual experience, social identity, and consumer engagement. This research framework seized the multi-dimensional and the bilateral dependent essence of constructs determining the behaviors of online gaming communities. The empirical findings suggest that social presence, telepresence, cognitive social identity, affective social identity, psychological engagement, and behavioral engagement are valid measures of online gaming communities. All the hypotheses between the six success constructs are supported by the analytical results.
As reported by the results, several valuable implications can be addressed. In keeping with the proposed framework, psychological and behavioral engagement are more effective constructs of online gaming communities than the other four constructs. Psychological and behavioral engagement should be encouraged while the formation of social presence, telepresence, cognitive social identity, and affective social identity are well managed. Therefore, game companies ought to pay much attention to the advancement of virtual experience, social identity formation, and consumer engagement processes. For the purpose of increasing consumer engagement behavior of game players, the online game developers should not only provide a better online discussion space where game players can freely express their ideas and suggestions about the game but also encourage game players and game developers to have deeper reciprocal interactions and extensive opinion exchanges. By doing so, the game itself and game developers could continuously absorb the valuable advice as well as improve their products, thus building a bonding relationship. A successful game developer must be open-minded to accept the criticism and learn modestly from the suggestions from game players.
Cognitive social identity and affective social identity partially mediate the effects of social presence and telepresence on psychological engagement and behavioral engagement. Cognitive social identity and affective social identity continue to be essential determinants of psychological engagement and behavioral engagement. The findings also indicate that social presence has stronger direct and total effects on behavioral engagement via cognitive social identity, affective social identity, and psychological engagement (see Table 5
), suggesting the importance of social presence in promoting affective social identity and of psychological engagement in strengthening behavioral engagement.
Prior studies have proposed that psychological engagement has a positive effect on behavioral engagement [67
]; however, they did not further examine the mediating effect of psychological engagement or its antecedent constructs. Accordingly, the mediating analysis is further conducted. To validate the mediating role of psychological engagement, this study followed the guidelines of Zhao et al. [81
]. The result of mediating analysis is shown in Table 6
. According to Zhao et al. [81
], the statistical significance of indirect effects should be firstly verified, which means that the indirect effects of cognitive social identity and affective social identity on behavioral engagement via psychological engagement are both significant at p
< 0.05, and zero is not included in the 95% confidence interval. This study subsequently validates the significance of direct effects of cognitive social identity and affective social identity on behavioral engagement, with the mediator (psychological engagement) controlled to testify the type of mediation.
As reported by Table 6
, psychological engagement completely mediates the relationship between cognitive social identity and behavioral engagement as well as between affective social identity and behavioral engagement. The results indicate that the indirect-only relationships of cognitive social identity, affective social identity, and behavioral engagement exist, meaning that psychological engagement is fully mediated by the relationship between cognitive social identity and behavioral engagement as well as by the relationship between affective social identity and behavioral engagement. This means that consumer engagement is a sequential process, and behavioral engagement cannot independently exist without psychological engagement.
The empirical findings indicate the significance of a multi-dimensional way of evaluating online gaming communities. Scholars can gain from this framework by taking it as the fundamental basis to establish comprehensive measures of online gaming communities, investigate inter-relationships between the proposed success constructs, and contrast different frameworks of online gaming communities. The empirical results also stimulate game companies to take measures of social presence, telepresence, cognitive social identity, affective social identity, psychological engagement, as well as behavioral engagement into consideration when they design and evaluate a brand-new online game.
7.1. Theoretical Implications
An important contribution of this research is the development a consumer engagement model of online gaming communities that goes beyond the concept of community continuance intention. As far as we know, this research is the first study to investigate virtual experience and social identity driving consumer engagement. This research theoretically revealed the relationships between virtual experience attributes, social identity characteristics, psychological engagement, and behavioral engagement and verified them empirically based on the context of online gaming communities.
The results of this research offer new insights into consumer engagement literature by exploring its antecedents in online gaming communities. Although previous studies explored consumer engagement in a mobile travel app and in the purchase of digital goods in an online game [68
], no prior study has identified its antecedent factors under the scenario of online gaming communities. This research advances this knowledge basis by empirically identifying the two kinds of virtual experience as antecedents driving consumer engagement in online gaming communities. Furthermore, this research advances to prove that consumer engagement is a consecutive process and behavioral engagement cannot independently exist without psychological engagement.
7.2. Managerial Implications
This research provides some evidence to echo practitioners. Blizzard Entertainment is one of the biggest game companies in the world. In 2018, Blizzard launched a new game, Diablo Immortal, which is the first mobile game since Diablo, released to the game market in 1996. The game’s promotional video received 250,000 dislikes less than one day since the chair game designer, Wyatt Cheng, announced the game on the annual festivity, BlizzCon 2018. For example, a hardcore fan of Blizzard, Dontinquire, said that he was very disappointed about this game and that this game should be cancelled. Moreover, many fans use the hashtags #NotMyDiablo on social media and some Blizzard fan propose a petition on the social welfare petition website Change.org to express their anger and ask Blizzard to cancel this game. Their statement is as follows: “Blizzard does not care about the community anymore. This is an outrage and a spit on the face of the Diablo community. Sign this petition to show them how disappointed we are and hopefully help wake them up to see that they have lost sight of what their core fan base desires.” Most of the fans criticize the playability, in-app purchase mechanism, the limitation of the mobile phone, the similarity with another game (i.e., Land of Glory), user interface (UI), and user experience (UX).
One year later, Blizzard announced that they will release a new PC game, Diablo IV, in the near future. In the meantime, the president of Blizzard, J. Allen Brack, said that he thought they did a poor job when they announced Diablo: Immortal. Additionally, Brack admitted that they did not communicate well with the players. He also said that they did not properly explain to their core fans that they did not want to abandon the PC platforms or switch to home consoles and mobile games.
From the example of Blizzard, we can conclude that the players’ virtual experience in online games facilitates social identity formation in online gaming communities. When players feel strongly identified with the game and the game companies, they have strong and vigorous motivations to engage in online gaming communities psychologically. When events such as the one involving Diablo Immortal happen, the players present behavioral engagement, such as calling for support online and becoming cohesive to demand that the game company take some action in response to the players’ requests and expectations.
Taken together, this research not only provides theoretical contribution to academic research but also offers powerful evidence to remind game companies must always take players’ thought and feedback as their first priority. This study emboldens future researchers to continue investigating and validating the scenario in online gaming communities and provides more useful suggestions to practitioners.