The effect of user experience in online games on word of mouth: A pleasure-arousal-dominance (PAD) model perspective

Accepted Manuscript The effect of user experience in online games on word of mouth: A pleasurearousal-dominance (PAD) model perspective

Minxue Huang, Rizwan Ali, Junyun Liao PII:

S0747-5632(17)30327-8

DOI:

10.1016/j.chb.2017.05.015

Reference:

CHB 4974

To appear in:

Computers in Human Behavior

Received Date:

26 December 2016

Revised Date:

26 March 2017

Accepted Date:

09 May 2017

Please cite this article as: Minxue Huang, Rizwan Ali, Junyun Liao, The effect of user experience in online games on word of mouth: A pleasure-arousal-dominance (PAD) model perspective, Computers in Human Behavior (2017), doi: 10.1016/j.chb.2017.05.015

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT

Highlights: 

User experience leads to WOM by evoking pleasure, arousal, and dominance



Dominance was the most prominent and significant mediator in the relationship between user experience and WOM.



Tenure moderates the effects of user experience on pleasure, arousal, and dominance



Managers could promote the diffusion of online games by enhancing user experience.

ACCEPTED MANUSCRIPT

The effect of user experience in online games on word of mouth: A pleasure-arousal-dominance (PAD) model perspective

Minxue Huang1 Professor, Economics and Management School of Wuhan University Address: Economics and Management School of Wuhan University, Wuhan 430072, China E-mail: [email protected]

Rizwan Ali2 Ph.D. student, Economics and Management School of Wuhan University Address: Economics and Management School of Wuhan University, Wuhan 430072, China E-mail: [email protected] Tel:86-13476244139

Junyun Liao3(corresponding author) Ph.D. student, Economics and Management School of Wuhan University Address: Economics and Management School of Wuhan University, Wuhan 430072, China E-mail: [email protected] Tel:86-02768753149

Word count: 258 Abstract Online games are now a prosperous industry. Despite the popularity of online games, game developers confront the short life cycle of online games. To tackle this significant challenge, game developers utilize the power of word of mouth (WOM) to diffuse games quickly. However, what influences WOM intention in the context of online games remains unexplored. To address this gap, this study investigates the manner in which three types of experiences, namely, functional, hedonic, and social, influence WOM. Drawing from the pleasure–arousal–dominance model, the authors propose that user experience leads to WOM by evoking pleasure, arousal, and dominance. Using the survey data collected from online game players, our study reveals that user experience significantly affects consumer intention to spread WOM. Theoretical and managerial implications are discussed. Acknowledgments The authors thank seminar participants of Research Center for Marketing Engineering and Innovation of China for their helpful suggestions. This research was supported by the National Natural Science Foundation of China under Grant 71372127 and 71672132.

ACCEPTED MANUSCRIPT

1

The effect of user experience in online games on word of mouth: A pleasure-arousal-dominance (PAD) model perspective

Abstract: Online games are now a prosperous industry. Despite the popularity of online games, game developers confront the short life cycle of online games. To tackle this significant challenge, game developers utilize the power of word of mouth (WOM) to diffuse games quickly. However, what influences WOM intention in the context of online games remains unexplored. To address this gap, this study investigates the manner in which three types of experiences, namely, functional, hedonic, and social, influence WOM. Drawing from the pleasure–arousal–dominance model, the authors propose that user experience leads to WOM by evoking pleasure, arousal, and dominance. Using the survey data collected from online game players, our study reveals that user experience significantly affects consumer intention to spread WOM. Theoretical and managerial implications are discussed. Keywords: Functional experience, Hedonic experience, Social experience, Emotions, Word-of-mouth 1 Introduction As the second most popular activity among internet users today, playing online games has expanded globally (Lenhart, 2008). Despite the popularity of online games, game developers face a significant challenge, that is, the short life cycle of their product. The estimated life is roughly six months. Therefore, game developers are driven to rapidly disseminate information about new games before consumers lose interest. Word of mouth (WOM) is a very powerful marketing strategy to make products popular among target audience (Godes & Mayzlin, 2004). WOM communication allows online game players to share their experiences and feelings with others and invite new players. WOM on experienced product shared by forum members is likely considered trustworthy because these members are fellow consumers without interest in firms and products so they do not benefit from marketing the product. More importantly, WOM of products can be transmitted rapidly among networks of consumers. Online games are experienceoriented products, and their success greatly depends on how consumers feel toward and experience them. For a long time, previous research extensively examined flow experience as an important factor for user engagement in game (Choi & Kim, 2004; Takatalo, Kawai, Kaistinen, Nyman, & Häkkinen, 2011). A study on MMORPG examined the relationship between brand image and online WOM through the mediation effect of brand trust. The study suggested that game developers should create a good brand image to gain positive WOM by online game players (Liao, 2012). Opinion seekers spread more negative WOM than opinion leaders in response to system failure of social network games (Sun, Youn, Wu, & Kuntaraporn, 2006). Therefore, avoiding negative WOM is another important consideration. Fast-growing internet technology enhances electronic WOM in a one-to-many relationship and provide online forums where game

ACCEPTED MANUSCRIPT

2

players share experiences and exchange views. In line with this research stream, how user experience in online games affects user intention to spread WOM should be investigated. Building on the pleasure–arousal–dominance (PAD) model (Mehrabian & Russell, 1974), we intend to investigate how the functional, hedonic and social experiences of online game users influence WOM through emotions. This research primarily aims to test the mechanism through which user experience evokes emotions, which in turn, persuade emotionally laden players to disseminate WOM among their circle of friends. We assume that functional and social experiences positively influence three dimensions of emotions (i.e., pleasure, arousal, and dominance). Pleasure, arousal, and dominance also positively affect WOM. The authors also investigated the moderating role of players’ tenure, a critical consumer characteristic in the context of online games on the intention to spread WOM. Using survey for data collection and obtained 356 valid samples, we tested our hypotheses. Our findings show that functional and social experiences significantly activate the emotions of players and lead to the spread of WOM. 2 Literature review 2.1 User experience in online games Children participate in MMORPG communities, and this participation motivates them to purchase tools and accessories to use in online games (Hota, Hota, Derbaix, & Derbaix, 2016). User-game engagement is crucial to retain players. Two cognitive elements, namely, game familiarity and complexity, exert significant individual and joint effects on user-game engagement (Li, Jiang, Tan, & Wei, 2014). A study examined the relationship among virtual atmospheric cues, emotions, and WOM, and the results indicated that pleasure is vital emotional state to spread WOM in males and females (Loureiro & Ribeiro, 2014). An empirical study investigated arousal of visitors’ emotions while experiencing death- and suffering-related sites, and the findings suggested that negative emotions can exert long-term behavior effects (Nawijn & Fricke, 2015). Given that online games are experience products, consumers mainly derive value from their experience in online game. Consumers experience great enjoyment when playing online games. Playing online games increases self-esteem, competence, and wellbeing of consumers (Rau, Peng, & Yang, 2006). Recent decades have witnessed an increasing number of users immersing themselves in online games. To explain such immersion, Csikszentmihalyi (1975) provided the construct flow, which refers to the state of an optimal experience in which players fully engage in action. The flow state is characterized by distorted sense of time, feeling of control, clarity of goals, and loss of self-consciousness (Trevino & Webster, 1992). Flow experience occurs when one’s skills match the challenges. The role of flow is widely acknowledged. Extensive studies examined the antecedents and outcomes of the optimal experience in online games (Sánchez, Vela, Simarro, & Padilla-Zea, 2012). Prior studies indicated that factors, such as novelty, skills, challenges, specialized player, and recreational specialization, enhance flow experience (Wöran & Arnberger, 2012; Wu, Scott, & Yang, 2013). Takatalo et al. (2011) studied 3D

ACCEPTED MANUSCRIPT

3

stereo scope display, and they found that medium stereo elicits high sense of presence and flow experience. Specialized players are more likely to enjoy flow experience and show evidence of game addiction than inexperienced players (Wu et al., 2013). Regarding the outcomes of flow experience, players tend to play online games continuously if they have good experience while playing (Choi and Kim, 2004). Recent research notes the positive effect of flow experience on repurchase intention and willingness to pay premium price (WTP). Table 1 summarizes the literature. Table 1. Empirical Research on the Antecedents and Consequences of Game Players’ Optimal Experience Related Studies

Choi and Kim

Theoretical Foundation

Flow Theory

(2004)

Antecedents of Flow

Outcomes of Flow

Experience

Experience

Personal interaction and

Flow experience motivates

social interaction leads to

users to continue playing

flow experience.

online games.

Takatalo et al.

Presence–Involvement–

Moderate level of stereo

(2011)

Flow Framework

separation enhances user

________

experience by increasing the sense of presence among the users. Skoric and Kwan

Social Capital Theory　

(2011)

Game experience is related ________

to online bonding social capital.

Wu, Scott, and

Recreation Specialization

User specialization increase

Flow experience increases

Yang (2013)

Framework

flow experience.

game addiction.

Wan and Chiou

Flow Theory and

(2006)

Humanistic Need Theory

Flow state is not ______

psychological mechanism of player addiction.

Weibel et al. (2008)

Flow Theory

Type of opponent influences flow experience

Current Study

Pleasure–Arousal– Dominance Model

________

________ Word of Mouth

Although flow construct greatly advances knowledge on user immersion in online games, this construct does not capture specific dimensions of user experience in online

ACCEPTED MANUSCRIPT

4

games. The literature on online games demonstrates that user experience in the online context is a multidimensional construct (Takatalo et al., 2011). Studies on virtual communities to which online games belong provide evidence that customer experience is a multidimensional construct in the context of online communities. Nambisan and Watt (2011) show four components of customer experience in online product communities, namely, pragmatic, hedonic, sociability, and usability dimensions. In pragmatic dimension, customers found useful and valuable experiences, which help them achieve goals. In hedonic dimension, customers experience pleasure and excitement by interacting with online community. Sociability dimension reflects the friendliness and openness among community members. Usability dimension captures the ability of customer to participate in online community easily without any distraction. In line with Nambisan and Watt, the current study investigates the effects the dimensions of user experience (functional, hedonic, and social) on emotions and explore whether emotional players exhibit intention to spread WOM. Functional experience in online games is the utilitarian value users experience from interactions in online games (Nambisan & Watt, 2011). Functional experience relates to the utilitarian aspect of user experience in games. Online games are highly interactive systems, and players engage in different functional experiences while playing. Role playing, sociability, quest fulfillment, reward system, graphics, and sounds are appealing functions of video games (Holt & Kleiber, 2009). Hedonic experience refers to customers’ high level of involved interaction with products that provide them with fun and excitement (Mummalaneni, 2005). Social experience in online games is the value users derive from the interactions with others in the online games (Nambisan & Watt, 2011). If people effectively and successfully communicate with others, then they feel good, and they will be motivated to communicate again to enjoy the same feeling. WOM communication pertains to unofficial communication among consumers about a product, brand, or organization (Buttle, 1998). Although emotions are believed to influence consumer behaviors, few studies examined the effect of user experience on WOM. Given the significance of the role of WOM for diffusing online games, the lack of research attention is surprising. Drawing on the PAD model, we examine the effects of user experience on WOM intention to address the research gap 2.2 Pleasure–arousal–dominance model The PAD model is initially proposed to adequately capture the emotional states of individuals. Russell and Mehrabian (1977) claimed that pleasure is a mood state that ranges from extreme pain or unhappiness to extreme happiness or ecstasy. Arousal refers to one’s degree of excitement, alert, and stimulate. Dominance is the extent to which one feels he or she can control events rather than be controlled by events. The PAD model assumes that stimuli affect the three main emotions of individuals and thus influence the experience of users with the environment. The PAD model is in line with the widely accepted stimuli–organism–response (S-O-R) paradigm; the model is usually used to explain the influence of stimuli on people’s intentions and behaviors. Hsieh et al. (2014) used the PAD model to examine consumer response to website atmospherics (e.g., taskrelevant cues), and they found that pleasure, arousal, and dominance mediate the effect of website atmospherics on purchase intention. Vanwesenbeeck, Ponnet, & Walrave (2016)

ACCEPTED MANUSCRIPT

5

proposed a model on the basis of PAD dimensions and revealed that persuasion knowledge is influenced by game flow, which is affected by emotions (i.e., self-reported pleasure, arousal, and dominance). These emotional responses affect consumer behaviors, including buying products and staying in or escaping from a setting (Eroglu, Machleit, & Davis, 2001). Graa & Dani-el Kebir (2012) used the PAD model in the retail environment and investigated the mediation effect of customer emotions (pleasure, arousal, and dominance) on the relationship between situational factors and impulse buying behavior. Drawing on the PAD model, a study on retail environment revealed the effect of ambient scent on the emotional and behavioral responses of consumers (Davies, Kooijman, & Ward, 2003). Heussler, Frank, & Meyer (2009) examined the relationship between price increase and perception toward price fairness, which is moderated by emotions. Correspondingly, emotions are measured by adopting the PAD scale of Mehrabian & Russell (1974). The effects of emotional responses are usually examined in the online retail setting, and, thus, knowledge on its effects is limited in the context of online games. By contrast, the PAD model seems highly relevant to the concern of online game developers regarding game design. The virtual physical and social contexts can greatly influence the emotional responses of gamers. Therefore, in this study, we use the PAD model to investigate the effect of user experience on WOM intention. 3 Research Hypotheses 3.1 Functional experience and PAD Online game function, especially easiness, is a great value for players (Kim, Choi, Kim, & Liu, 2015). Advancement is a popular function of online games. If a player reaches a goal, then he/she advances to the next level. Advancement in games motivates players to continue playing (Yee, 2006). Online games are highly interactive systems, and their main goal is to exploit user emotions and provide entertainment (Voida & Greenberg, 2012). These functions of online games can produce continuous pleasure for players (Hsu, Wen, & Wu, 2009). Good functional experience make gamers excited about games. In online games, users may be motivated by the atmosphere within games (Barry, 2009). For example, 3D games with medium-level stereo sound provide good experience to players compared with 2D games with very high or very low stereo sound. Functional experiences also make users easily control their roles in games, leading to a high level of dominance. Online games contain challenges that urge players to acquire specialized skills for using game tools to advance to the next stage. Highly skilled players enjoy flow experience for a long time, whereas lowly skilled players enjoy flow experience frequently but only for a short period (Wu, Scott, & Yang, 2013). Virtual atmospheric cues are categorized into three parts, namely, design, layout, and information, which allow users to experience easiness when navigating a website with respect to goal achievement (Dennis, Merrilees, Manganari, Siomkos, & Vrechopoulos, 2009). Virtual atmospheric cues are goal oriented and positively affect emotions, such as pleasure and arousal (Davis, Wang, & Lindridge, 2008; Koo & Ju, 2010). Many games incorporate randomness and uncertainty to evoke player emotions, such as surprise (Owen, 2005).

ACCEPTED MANUSCRIPT

6

Using the above discussion as basis, we assume that functional experiences can affect emotions. H1a: Functional experience positively affects pleasure. H1b: Functional experience positively affects arousal. H1c: Functional experience positively affects dominance. 3.2 Hedonic experience and PAD Hedonic experience includes multiple senses, fantasy, and emotions. Senses comprise smell, touch, hearing, and sight. Fantasy reflects the imagination of consumers that is unrestricted by reality. There are several types of emotions, like active, calm, alive, peaceful, cheerful, warmhearted, delighted, stimulated, and excited. Pleasure is one of the three dimensions of the PAD model. Pleasure and arousal differs largely from hedonic experience. According to the literature, pleasure is a feeling that ranges from extreme pain to extreme happiness; arousal refers to one’s degree of excitement and stimulates (Mehrabian & Russell, 1974), which are internal to consumers. By contrast, hedonic experience comes from external context (Otto & Ritchie, 1996). The pleasure of consumers is strongly stimulated by hedonic experiences (Dhar & Wertenbroch, 2000; Holbrook & Hirschman, 1982). Hedonic products significantly influence emotional responses during product trial as well as attitude formation and future utilization (Menon & Kahn, 2002). Goulding (2000) stated that a museum environment generates emotions in visitors and affects behavioral intention. Bougie, Pieters, & Zeelenberg (2003) claimed that customers may experience anger when they experience poor services unlike when they experience good services. Digital games influence a player’s emotions (Poels & Dewitte, 2006) and provide pleasure (Phillips, Rolls, Rouse, & Griffiths, 1995). In an online game, the hedonic experience of players occurs when they continuously adapt to the new environment of the advance stages of the game. Repeated hedonic consumption experience brings pleasure to players (Nicolao, Irwin, & Goodman, 2009). Positive experiences explain the conception of flow, where people are fully under the control of environment. Video games often lead players to a flow state (Gur\uau, 2008; Wan & Chiou, 2006). Thus, we assume the following hypotheses: H2a: Hedonic experience positively affects pleasure. H2b: Hedonic experience positively affects arousal. H2c: Hedonic experience positively affects dominance. 3.3 Social experience and PAD People join social media to meet like-minded friends and pass information to one another (Ridings & Gefen, 2004). Social environment, particularly close ties, influences one’s emotional regulation and depression. In a social context, two persons can affect the emotions of each other (Butler & Randall, 2013). Particular relationships, such as lovers, friends, and family, are related to interpersonal emotions; people in relationships can

ACCEPTED MANUSCRIPT

7

affect one another’s emotions (Dixon-Gordon, Bernecker, & Christensen, 2015). To overcome big challenges in online games, players usually play in company and motivate each other, subsequently arousing collective emotions or feelings (Sánchez et al., 2012). Interaction among online gamers develops social capital and enhances the players’ commitment with their community. Online games provide a virtual space to players, where they can interact with one another, and this interaction may lead to optimal experience (Churchill & Bly, 1999a, 1999b). Effective and pleasant social interactions among online game players can result in optimal experience, which causes players to enter a flow state (Choi & Kim, 2004). In this context, we assume the following hypotheses: H3a: Social experience influences pleasure. H3b: Social experience influences arousal. H3c: Social experience influences dominance. 3.4 PAD and WOM Considerable research investigated the relationship between emotions and intentional behavior (White, 2010); Derbaix & Vanhamme, 2003; Zeelenberg & Pieters, 2004). Pleasure may increase the willingness of consumers to share their experience with others. A study on virtual environment (Loureiro & Ribeiro (2014) revealed that compared with arousal and dominance, pleasure exerts the most significant effect on positive WOM. Pleasure indirectly influences WOM through satisfaction (Miniero, Rurale, & Addis, 2014). High arousal emotions strongly influence the intention to spread WOM because consumers intend to restore stable mood state by talking to others (Ladhari, 2007). Positive emotions tend to produce WOM. Thus, we believe that dominance, which is a positive mood, can increase the WOM intention of users (White & Yu, 2005). Based on the evidence of the above scenario, we assume that emotions influence WOM. H4a: Pleasure positively affects WOM. H4b: Arousal positively affects WOM. H4c: Dominance positively affects WOM. 3.5 Moderating Effect of Tenure Tenure refers to how long a user has played a game. In the current scenario, beginners (just joined the game) of an online game have short tenure. They are emotional and actively interact with other players to establish connections and learn, and share game skills. As their playing time increases, players gain game expertise and they focus on advancing to the next level of a game (Shen, Monge, & Williams, 2014). A hierarchy of emotions and cognitions preexists based on the emotion-cognition model; emotions develop first in the exposure of websites, and these emotions subsequently influence cognition (Richard & Chebat, 2016; Zajonc & Markus, 1982). Beginners of the online game feel more emotions in the initial stage of game but with the passage of time they get

ACCEPTED MANUSCRIPT

8

expertise, feel fewer emotions and use more cognition to achieve the advance stages. Not all players enjoy social experience; some people join the group in online games, but most of the players do not join the group (Shen et al., 2014). Tenure is positively related with counterproductive behavior, role performance, and core-task behavior (Ng & Feldman, 2010). Users with long tenure are usually experts and they are accustomed to a game and feel fewer emotions. By contrast, users with shorter tenure tend to get excited about the game and feel more emotions. Thus, we offer the following hypotheses: H5: The effect of functional experience on (a) pleasure, (b) arousal, and (c) dominance is stronger for shorter tenure users than longer tenure users. H6: The effect of hedonic experience on (a) pleasure, (b) arousal, and (c) dominance is stronger for shorter tenure users than longer tenure users. H7: The effect of social experience on (a) pleasure, (b) arousal, and (c) dominance is stronger for shorter tenure users than longer tenure users. 3.6 Mediation effect of PAD This hypothesis is based on S-O-R model recommended by Mehrabian & Russell (1974). A stimulus is the first component of S-O-R model which refers to user experience in online games like functional, hedonic, and social experience. Organism, the second component of model expresses the emotions of pleasure, arousal, and dominance that people experience while playing online games. Response component refers to WOM that players spread in their social circle. According to the S-O-R model, we propose that the emotional states of pleasure, arousal, and dominance may mediate the effect of user experience on WOM intention. Shoppers’ emotions often conceptualized in retail studies with different aspects (Dailey, 2004; Eroglu, Machleit, & Davis, 2003). Past research has abundantly investigated the atmospheric cues in the traditional retail settings (Hausman & Siekpe, 2009). In the current research S-O-R model suggests that the stimuli (user experience) affect emotions of online gamers and their behaviors as well. Loureiro & Ribeiro (2014) examined emotions as a mediator in the relationship of online atmospheric cues and WOM; they suggested that pleasure is the most effective mediator to transmit WOM. Perceptions toward price-related unfairness create negative emotions, which subsequently generate negative WOM (Mayer & Avila, 2006). When consumer experience is unfavorable, negative feelings are generated, and negative WOM is spread (Loureiro & Ribeiro, 2014). Eroglu, Machleit, & Davis (2001, 2003) used S-O-R model in online store setting and found that low task related cues influence the pleasure and arousal, which in turn affects the consumers’ behavior of online store customers. Koo & Ju (2010) adopted S-O-R framework in online store setting and revealed that online atmospherics (colors, links and graphics) have impact on pleasure and arousal, which in turn leads to the intentional behavior. Finally, dominance is also an important emotional state that may be a good mediator in the relationship between user experience and WOM in the context of online games. Graa & Dani-el Kebir (2012) tested the role of PAD in the relationship between situational factors of physical retail environment and impulse buying behavior and found that dominance played a significant mediation role between them. In the light of the S-O-R model and the literature discussed, we can assume the following hypothesis:

ACCEPTED MANUSCRIPT

9

H8: Pleasure mediates the effect of (a) functional experience (b) hedonic experience (c) and social experience on WOM. H9: Arousal mediates the effect of (a) functional experience (b) hedonic experience (c) and social experience on WOM. H10: Dominance mediates the effect of (a) functional experience (b) hedonic experience and (c) social experience on WOM.

Online Game User Experience

Short and LongTenure

Functional Experience

Emotional Dimensions Pleasure Intentional Behavior

Hedonic Experience

Arousal

Social Experience

Dominance

WOM

Fig 1. Research Model

4 Methodology and data analysis 4.1 Participants and procedures The survey has been conducted for two months July and august 2015. The samples were those who have online games experience for last three months. Respondents were approached in the big city of Pakistan. The response rate was 71% (356 valid questionnaires out of 500). The survey was distributed among volunteers who had experiences in playing online games. The demographic and socio-economic profiles of the sample indicated 75% males and 25% females. A major portion (54%) of the sample was between the 18 and 23 years old, and 34% of the respondents were between 24 and 30 years old. The mean age of the online game players was within the range of 23 to 24 years old. The mean tenure of online gamers was 2.35 years (S.D=1.183). From the respondents, 44% completed bachelor degrees and 39% completed the master or above degree. Among the respondents, 26% have been playing online games from the last three years or more. 4.2 Measure

ACCEPTED MANUSCRIPT

10

The authors used a survey to check the introduced hypotheses. The survey consisted of three parts. The first section evaluated participants’ interest and orientation toward playing online games like their favorite game, tenure, and purpose. The second part asked participants’ online game user experience in terms of user’s functional, hedonic, and social experiences. Participants’ were asked about their emotions like pleasure, arousal, and dominance while playing online games. A 5-point likert scale used to measure the items in part two. The last part of the survey was related to participants’ personal information, such as gender, age, and qualification. 4.2.1 User experience The measurement items of functional, hedonic, and social experiences are adapted from Nambisan & Watt (2011). The scale measures different dimensions of functional experience, such as user-friendly interface, graphics, music, etc. The scale measures hedonic experience, including feelings and satisfaction of a player. The social experience is measured by asking their social circle, communication with other players, and being praised by others. Functional experience (Cronbach’s α=0.70), hedonic experience (Cronbach’s α=0.74), and social experience (Cronbach’s α=0.86) demonstrated acceptable reliability. 4.2.2 PAD Items of pleasure, arousal, and dominance are adapted from Mehrabian & Russell (1974). The instruments evaluated happiness, excitement, and control of virtual environment of online game players. Higher score on pleasure, arousal, and dominance represented highly emotional laden players. Pleasure (Cronbach’s α=0.85), arousal (Cronbach’s α=0.84), and dominance (Cronbach’s α=0.76) showed acceptable reliability. 4.2.3 WOM Brown et al. (2005) measured WOM, and this scale was used in the current study. The scale measured different dimensions of WOM, such as recommendation, sharing experiences with others, and encouraging others to play the game. High score on WOM demonstrated high advocacy about the game by online game players. The WOM dimension demonstrated good reliability (Cronbach’s α=0.84). 5. Results 5.1 Descriptive statistics The demographic and gaming profiles of the respondents are shown in Table 2. Table 2. Demographic Characteristics of Participants Profile

Category

%age

ACCEPTED MANUSCRIPT Male

75%

Female

25%

Under18

6%

18-23

54%

24-30

34%

Over 30

6%

High School or Below

14%

Intermediate

3%

Undergraduate

44%

Master or Above

39%

1 Year or Less

33%

<1 and < 2 years

26%

<2 and < 3 years

15%

3 years and above

26%

11

Gender

Age

Education

Tenure

5.2 Measurement model A two-step approach is used to analyze data (Anderson & Gerbing, 1988). To test measurement reliability, composite reliability and Cronbach’s alphas were calculated. Average variance extracted (AVE) and factor loading were checked to assess the discriminate and convergent validity. After verifying the measurement model, relevant structural equation model (SEM) was examined to find the relationship among the constructs. SPSS 19.0, Smart PLS 2.0, and AMOS 17.0.2 software packages were applied for statistical analysis. First, a measurement model was predicted by CFA. All latent constructs were loaded by their relevant measurement items and constructs permitted for correlation analysis (Anderson & Gerbing, 1988). Composite reliability and Cronbach’s alpha were calculated to check reliability of the instruments. Seven constructs are employed in the research. Alpha values for all components fell in the range of 0.70 to 0.86. Table 3 shows alpha values of all the constructs that fulfill the minimum requirement of 0.70. Values of composite reliability exceed the standard value of 0.70, ranging from 0.82 to 0.93. In this study, the instrument is now reliable for measurement of latent construct. Standardized factor loading of all items ranged from 0.72 to 0.93, which are significant at 0.01 level of significance. However, one item, with value of 0.62, which is acceptable. Overall all the values satisfied convergent validity. All values of AVE fell in the range of 0.54 to 0.86, which was above the minimum criterion of 0.50, which showed that maximum variance is interpreted with constructs (Fornell & Larcker, 1981). To test discriminant validity, values of AVE were compared with squared correlations between

ACCEPTED MANUSCRIPT

12

paired constructs, and represented discriminant validity. In summary, the research instrument indicates high validity and reliability for the function of latent construct. Table 3.Confirmatory Factor Analysis Constructs Functional Experience

Items

SFL

I play this online game due to its graphics, background music, etc.

0.62

I think this online game is simple and user friendly

0.72

I think this online game gives me better user experience

0.81

In general, while playing this online game I feel it works well

0.76

When I play this online game, I feel good

0.89

Playing this game makes me feel very satisfied

0.89

Playing this online game can make it easier for me to get socially accepted by others

0.73

Playing this online game to expand my social circle

0.85

Playing this online game can let me communicate with others more smoothly

0.85

Playing this online game can let me win the praise of others

0.77

Playing this online game to makes me feel more confident in social interactions.

0.81

I feel joyful after playing the game

0.89

I feel pleasure after playing the game

0.88

I feel gratified after playing the game

0.86

When I play this online game, I think it's very exciting

0.93

When I play this online game, I feel very excited

0.93

This game is better to use, I can control the game

0.87

In this game, I have the right to control

0.87

I would like to recommend this network game to others

0.88

Cronbach's α= .84

I would like to share this experience with others

0.89

CR= 0.90

I would like to encourage others to play with me

0.85

Cronbach's α= .70 CR= 0.82 AVE= 0.54 Hedonic Experience Cronbach's α= .74 CR= 0.88 AVE= 0.79

Social Experience Cronbach’s α=0. 86 CR= 0.90 AVE= 0.65

Pleasure Cronbach's α= 0.85 CR= 0.91 AVE= 0.76

Arousal Cronbach's α= .84 CR= 0.93 AVE= 0.86

Dominance Cronbach's α= .76 CR= 0.86 AVE= 0.76

WOM

AVE= 0.76

Overall Model Fit: χ2(356) = 771.80, χ2/df = 2.168, p <0.01; CFI = 0.94 ;NFI = 0.91, RMSEA = 0.05

Chi-square test and several fit indices were run to estimate the fitness of model for confirmatory factor analysis. Chi-square goodness of fit was 771.80. The root mean square error of approximation was 0.05. The comparative fit index (CFI) was 0.94, which is above than standard value recommended by Bentler (1990). Normed fit index (NFI) was 0.91. The statistical results indicated the overall fitness of the models was satisfactory.

ACCEPTED MANUSCRIPT

13

Table 4. Correlations Matrix Variable

1

2

3

4

　

5

6

7

1- Functional Experience

0.73

2- Hedonic Experience

0.66**

0.88

3- Social Experience

0.49**

0.51**

0.81

4- Pleasure

0.57**

0.68**

0.44**

0.87

5- Arousal

0.53**

0.65**

0.43**

0.66**

0.93

6- Dominance

0.59**

0.57**

0.42**

0.52**

0.56**

0.87

7- WOM

0.58**

0.59**

0.49**

0.52**

0.52**

0.54**

0.87

Mean

3.71

3.75

3.29

3.77

3.85

3.72

3.79

SD

0.78

0.87

0.95

0.84

0.94

0.91

0.93

　

　

　

　

　

　

　

　

　

　

　

　

　

　

　

　

　

　

　 　

Note: n= 356, Bold figures on the diagonal are the square roots of the AVE for constructs. Correlation is significant at the 0.01 level

5.3 Structural equation model The parameter estimates revealed that functional experience influenced pleasure (b = 0.23, t = 3.78), arousal (b = 0.17, t = 2.73), and dominance (b = 0.37, t = 5.33) positively and significantly as shown in the mediation effect of table 5. Thus, H1a, H1b, and H1c were supported. Hedonic experience exerted the highest effect on pleasure (b = 0.48, t = 8.54) compared with arousal (b = 0.49, t = 8.06) and dominance (b = 0.26, t = 3.77). The parameter estimates revealed that hedonic experience influenced all three mediators positively and significantly. Thus, H2a, H2b, and H2c were supported. The parameter estimates indicated that social experience influenced pleasure (b = 0.09, t = 1.91), arousal (t = 0.10, t = 1.94), and dominance (b = 0.11, t = 2.04) significantly. Thus, H3a, H3b, and H3c were supported.

Table 5. Model Estimation Moderation Effect Main Effect

Mediation Effect

Short Tenure

Long Tenure

(n=208)

(n=148)

Hypothesized Path t path coef

t path coef

value

t path coef

value

t path coef

value

value

FE -> WOM

0.32

5.83

0.20

5.14

0.20

3.87

0.25

3.79

HE -> WOM

0.28

4.57

0.29

6.91

0.26

4.79

0.30

4.10

SE -> WOM

0.19

3.76

0.07

2.85

0.09

2.34

0.06

1.33

PL -> WOM

0.23

3.62

0.17

2.31

0.38

3.27

AR -> WOM

0.20

2.76

0.24

2.88

0.07

0.52

DM -> WOM

0.32

5.77

0.33

5.20

0.30

3.33

FE -> PL

0.23

3.78

0.20

2.67

0.27

2.72

FE -> AR

0.17

2.73

0.24

2.97

0.10

1.01

ACCEPTED MANUSCRIPT

14

FE -> DM

0.37

5.33

0.33

3.78

0.46

4.62

HE -> PL

0.48

8.54

0.51

7.23

0.45

4.63

HE -> AR

0.49

8.06

0.40

5.11

0.61

6.12

HE -> DM

0.26

3.77

0.24

2.65

0.28

2.72

SE -> PL

0.09

1.91

0.06

0.91

0.12

1.65

SE -> AR

0.10

1.94

0.15

2.28

0.03

0.34

0.11

2.04

0.13

1.85

0.03

0.39

SE -> DM

　

　

Notes: FE = Functional experience, HE = Hedonic experience, SE = Social experience, PL = Pleasure, AR = Arousal, DM= Dominance, WOM = Word of Mouth.

The relationship between pleasure and WOM is significant (b = 0.23, t = 3.62). Arousal also significantly (b = 0.20, t = 2.76) affects WOM. Parameter estimates reveal that dominance exerts a positive and significant influence on WOM (b = 0.32, t =5.77). Thus, H4a, H4b, and H4c are supported. Short tenure exerted slightly low effect (b = 0.20, t = 2.67) compared with long tenure (b = 0.27, t = 2.72) on the relationship between functional experience and pleasure. Therefore, 5a is rejected. Functional experience exerted significant effect (b =0.24, t = 2.97) on arousal in the short tenure group but insignificant effect (b = 0.10, t = 1.01) in the long tenure. Therefore, H5b is accepted. The effect of short tenure (b = 0.33, t = 3.78) is slightly weaker but significant compared with the effect of long tenure (b = 0.46, t = 4.62) in the relationship between functional experience and dominance. This result reverses our supposition, and thus, H5c is rejected. Short tenure strengthened the relationship (b =0.51, t = 7.23) and long tenure weakened the relationship (b = 0.45, t = 4.63) between hedonic experience and pleasure. Short tenure weakened the relationship (b = 0.40, t = 5.11) and long tenure strengthened the relationship (b = 0.61, t = 6.12) between hedonic experience and arousal. Short tenure weakened the relationship (b = 0.24, t = 2.65) and long tenure strengthened the relationship (b = 0.28, t = 2.72) between hedonic experience and dominance. Thus, H6a was accepted, but H6b and H6c were rejected. Social experience did not show significant effect (b = 0.06, t = 0.91) on pleasure in the short tenure group also exerted insignificant effect (b = 0.12, t = 1.65) in long tenure. This result affirmed prior research, as group activities do not prevail during the early stages of the game (Ducheneaut et al., 2006). Thus, H7a is unsupported. Relationship between social experience and arousal is strong (b = 0.15, t = 2.28) in the short tenure group, but this relationship is insignificant (b = 0.03, t = 0.34) in long tenure, and thus, H7b is accepted. Short tenure strengthened the relationship (b = 0.13, t = 1.85) between social experience and dominance, whereas long tenure weakened the relationship (b = 0.03, t = 0.39) between social experience and dominance, and thus, H7c supported. 5.4 Mediating role of emotional response between online game user experience and WOM

ACCEPTED MANUSCRIPT

15

Functional experience influence the WOM (b =0.32, t =5.83) positively and significantly without mediation effect as shown in the main effect of table 5. There was a positive and significant direct relationship (b =0.28, p =4.57) between hedonic experience and WOM. Direct effect of social experience on WOM was positive and significant (b =0.19, t =3.76). After introducing mediator, relationship strength between user experience and WOM gets change as shown in the table 6. The authors used sobel test to check the significance of mediator and found that pleasure had significant mediation effect (z =1.75, p =0.07) between the relationship of functional experience and WOM. Pleasure also had significant mediation effect (z =3.49, p =0.00) in the relationship between hedonic experience and WOM. Pleasure had insignificant mediation effect (z =1.41, p =0.15) between social experience and WOM. Thus pleasure had partial mediation effect between the relationships of user experience and WOM. Arousal had insignificant mediation effect (z =0.84, p =0.40) between functional experience and WOM. Mediation effect of arousal (z =2.68, p =0.00) was positive and significant in the relationship between hedonic experience and WOM. Arousal had insignificant mediation effect (z =1.37, p =0.16) in the relationship between social experience and WOM. Therefore arousal had weak mediation effect in the relationship between user experience and WOM. Dominance had positive and significant mediation effect (z =3.56, p =0.00) in the relationship between functional experience and WOM. Mediation effect of dominance was positive and significant (z =3.22, p =0.00) in the relationship between hedonic experience and WOM. Dominance had significant mediation effect (z =1.81, p =0.06) in the relationship between social experience and WOM as well. Overall dominance was the most prominent and significant mediator in the relationship between user experience and WOM. Table 6. Sobel Tests (Z) Hypothesis

Predictor

Mediator

Outcome

Z value

p value

Status

H8a

Functional Experience

Pleasure

WOM

1.75*

0.07

Accepted

H8b

Hedonic Experience

Pleasure

WOM

3.49***

0.00

Accepted

H8c

Social Experience

Pleasure

WOM

1.41

0.15

Rejected

H9a

Functional Experience

Arousal

WOM

0.84

0.40

Rejected

H9b

Hedonic Experience

Arousal

WOM

2.68***

0.00

Accepted

H9c

Social Experience

Arousal

WOM

1.37

0.16

Rejected

H10a

Functional Experience

Dominance

WOM

3.56***

0.00

Accepted

H10b

Hedonic Experience

Dominance

WOM

3.22***

0.00

Accepted

H10c

Social Experience

Dominance

WOM

1.81*

0.06

Accepted

Note: Sobel test examine whether pleasure, arousal, and dominance mediate the relationships presented. Note: *p <0.1; **p <0.05; ***p <0.01

6 Discussion Emotions have been extensively investigated in different fields, such as the pleasure state of emotions evoked by store environment (Brengman, Willems, & Joye,

ACCEPTED MANUSCRIPT

16

2012). Virtual atmospheric cues influence emotions, and emotionally laden customers spread WOM (Loureiro & Ribeiro, 2014). A hotel setting significantly affects emotions of guests, and steps of the service environment like check-in, services required, and check-out etc. are vital in hotel strategy (Brunner-Sperdin & Peters, 2009). Prior studies on online games paid much attention to antecedents and outcomes of flow experiences. As such, user experience is usually seen as a single-dimensional construct, but recent studies indicated that user experience is a multidimensional construct. Thus, investigating the effects of specific dimensions of user experience is important. Past research intended to engage players with the game for a long time to generate revenue. However, few studies investigated the relationship between the online game user experience and WOM, specifically, the manner in which online game user experience influences WOM through emotions. To address these gaps, our research explores how user experience in online game activates the player’s emotions and how emotions lead to behavior in terms of WOM. Specifically, we draw a conceptual framework on the grounds of the PAD model. We collected the data from 356 online game users to test our hypotheses. Our results showed that functional, hedonic, and social experiences all significantly influenced the WOM. Specifically, emotions had considerable mediation effect on the relationship between user experience and WOM. According to our findings, functional experience exerts positive and significant effect on pleasure and dominance, which is consistent with the findings of Davis et al. (2008). Online games have many operators and tools that help players to accomplish the goal and advance to the next stage. Good usage of tools gives players pleasure and dominance. As per findings of the current study, hedonic experience positively and significantly affects all dimensions of emotions (pleasure, arousal, and dominance). Our results confirmed the findings of Wan & Chiou (2006), as well as that of Nicolao et al. (2009). Social experience positively and significantly influences all dimensions of emotions (pleasure, arousal, and dominance). Our findings are consistent with Sánchez, Vela, Simarro, & Padilla-Zea (2012), Choi & Kim (2004), and Churchill & Bly (1999b). Our results revealed that social experience has strong positive and significant effect on WOM but to some extent our findings are different from the prior research of Rezaei & Ghodsi (2014).When players are playing in teams, they appreciate each other on good usage of tools, and show gratefulness via comments and sending emoticons, such as thumbs. These messages elicit happiness and excitement from players, who then become fully involved in the game. As per our findings, dominance compared with pleasure and arousal had stronger effect on the WOM. This finding is different from the previous research, such as Loureiro & Ribeiro (2014), who cited pleasure as the most significant effect on positive WOM. Dominance is the best mediator in the relationship between user experience and WOM. Tenure is a good moderator in the relationship between user experience and emotions. This hypothesis supported the emotion-to-cognition model presented by Zajonc & Markus (1982). Moreover, our findings are consistent with Richard & Chebat (2016). Players belonging to short tenure (initial players) have less specialization, but are more emotionally laden and actively interact with other players to make connection. Consequently, initial players actively enhance their social circle, information sharing, and learn new techniques and skills. By contrast, players who belong to long tenure are skilled and specialized, but are more cognitive and less emotional, as they have passed the initial

ACCEPTED MANUSCRIPT

17

phase of emotions and are more familiar with the game. Our findings are consistent with prior research that beginners make connections enthusiastically, but these connections diminish in the later stages (Shen et al., 2014).

6.1 Theoretical contribution Our research contributes to literature in several ways. First, we extend prior research by investigating the relationship of user experiences in online game and WOM. While WOM is critical for diffusion of online games, research is insufficient on factors that influence online gamer intention to spread WOM. In this paper, we investigated the relationship between user experience and WOM. More importantly, user experience is a complex and multidimensional construct, and prior research usually considered experience as a single-dimensional construct. This limitation is unable to identify dimensions that affect WOM. Thus, this study examined the effect of functional, hedonic, and social experiences in a general framework. Our study can advance the knowledge on the relationship between user experience and WOM. Second, we used the PAD model to explain why user experience affects WOM. The PAD model is usually adopted to explain the effect of stimuli on consumer behavior, and recently is widely used in the context of retailing. Our study uses this model in the context of online games and finds that the three emotion responses are very important mediators in the relationship between user experience and WOM. Thus, our study generalizes the application of the PAD model. Third, the current study extends the knowledge of online gamer segment. Our results showed that users with different tenures paid various levels of attention to functional, hedonic, and social experiences. This result implied that users who play online games are not homogeneous but rather heterogeneous. 6.2 Managerial implication This study provides online game developers with several important implications. First, this study indicated that developers should pay attention to the factors influencing intention to spread WOM of games. Previously, online game developers only gave heavy attention to the time consumers spend in online games. However, given the short life cycle of online games, managers must learn to utilize the power of WOM to spread online games quickly. Second, our study indicates creating good user experience is very critical. Thus, when developing games, managers should incorporate functional, hedonic, and social experiences in the game. For instance, developers should design convenient communication tools to facilitate user social experience. Third, online game developers should monitor the emotional response of users when they play games. Our results showed that positive emotional state would positively affect WOM intention of users. In other words, developers would find value in knowing the sentiment of consumers and addressing factors that may destroy positive mood of users. 6.3 Limitations and future research

ACCEPTED MANUSCRIPT

18

Our study has several limitations that suggest future studies. First, we examined functional, hedonic, and social experiences in the context of online games. Future research can investigate experiences apart from functional, hedonic, and social types. Second, our research investigated the effect of user experience in online games on WOM. Future research can investigate other variables, such as willingness to continue to play and to pay premium price. Third, current research only investigated the role of tenure of user plays in the relationship between user experience and emotional responses. Future studies can investigate other consumer characteristics that may moderate the effect of user experience on emotional responses. These future endeavors can provide online game developers with useful suggestions. References: Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423. Bougie, R., Pieters, R. & Zeelenberg, M. (2003). Angry customers don’t come back, they get back: The experience and behavioral implications of anger and dissatisfaction in services. Journal of the Academy of Marketing Science, 31(4), 377–393. Barry, S. R. (2009). Fixing My Gaze: A Scientist’s Journey Into Seeing in Three Dimensions. Brown, T. J., Barry, T. E., Dacin, P. A., & Gunst, R. F. (2005). Spreading the Word: Investigating Antecedents of Consumers’ Positive Word-of-Mouth Intentions and Behaviors in a Retailing Context. Journal of the Academy of Marketing Science, 33(2), 123–138. Butler, E. A., & Randall, A. K. (2013). Emotional coregulation in close relationships. Emotion Review, 5(2), 202–210. Buttle, F. A. (1998). Word of mouth: understanding and managing referral marketing. Journal of Strategic Marketing, 6(3), 241–254. Brengman, M., Willems, K. & Joye, Y. (2012). The impact of in-store greenery on customers. Psychology \& Marketing, 29(11), 807–821. Brunner-Sperdin, A. & Peters, M. (2009). What influences guests’ emotions? The case of high-quality hotels. International Journal of Tourism Research, 11(2), 171–183. Choi, D., & Kim, J. (2004). Why People Continue to Play Online Games: In Search of Critical Design Factors to Increase Customer Loyalty to Online Contents. CyberPsychology & Behavior, 7(1), 11–24. Csikszentmihalyi, M. (1975). Play and intrinsic rewards. Journal of Humanistic Psychology, 15(3), 41–63. Choi, D. & Kim, J. (2004). Why people continue to play online games: in search of critical design factors to increase customer loyalty to online contents. Cyberpsychology & behavior : the impact of the Internet, multimedia and virtual reality on behavior and society, 7(1), 11–24. Churchill, E. F. & Bly, S. (1999a). Virtual Environments at Work: ongoing use of MUDs in the Workplace. ACM SIGSOFT Software Engineering Notes (Vol. 24, pp. 99–108).

ACCEPTED MANUSCRIPT

19

Churchill, E. F. & Bly, S. (1999b). It’s all in the words: supporting work activites with lightweight tools. Proceedings of the international ACM SIGGROUP conference on Supporting group work (pp. 40–49). Derbaix, C., & Vanhamme, J. (2003). Inducing word-of-mouth by eliciting surprise – a pilot investigation. Journal of Economic Psychology, 24(1), 99–116. Dixon-Gordon, K. L., Bernecker, S. L., & Christensen, K. (2015). Recent innovations in the field of interpersonal emotion regulation. Current Opinion in Psychology, 3, 36–42. Davies, B. J., Kooijman, D. & Ward, P. (2003). The sweet smell of success: olfaction in retailing. Journal of Marketing Management, 19(5-6), 611–627. Dailey, L. (2004). Navigational web atmospherics: Explaining the influence of restrictive navigation cues. Journal of Business Research, 57(7), 795–803. Davis, L., Wang, S. & Lindridge, A. (2008). Culture influences on emotional responses to on-line store atmospheric cues. Journal of Business Research, 61(8), 806–812. Dennis, C., Merrilees, B., Manganari, E. E., Siomkos, G. J. & Vrechopoulos, A. P. (2009). Store atmosphere in web retailing. European Journal of Marketing, 43(9/10), 1140–1153. Dhar, R. & Wertenbroch, K. (2000). Consumer choice between hedonic and utilitarian goods. Journal of marketing research, 37(1), 60–71. Eroglu, S. A., Machleit, K. A., & Davis, L. M. (2001). Atmospheric qualities of online retailing: A conceptual model and implications. Journal of Business Research, 54(2), 177–184. Eroglu, S. A., Machleit, K. A. & Davis, L. M. (2003). Empirical testing of a model of online store atmospherics and shopper responses. Psychology & Marketing, 20(2), 139–150. Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. Graa, A. & Dani-el Kebir, M. (2012). Application of stimulus & response model to impulse buying behavior of Algerian consumers. Serbian Journal of Management, 7(1), 53–64. Godes, D., & Mayzlin, D. (2004). Using Online Conversations to Study Word-of-Mouth Communication. Marketing Science, 23(4), 545–560. Goulding, C. (2000). The museum environment and the visitor experience. European Journal of marketing, 34(3/4), 261–278. Graa, A. & Dani-el Kebir, M. (2012). Application of stimulus \& response model to impulse buying behavior of Algerian consumers. Serbian Journal of Management, 7(1), 53–64. Gur\uau, C. (2008). The Influence of advergames on players’ behaviour: an experimental study. Electronic Markets, 18(2), 106–116. Hausman, A. V. & Siekpe, J. S. (2009). The effect of web interface features on consumer online purchase intentions. Journal of Business Research, 62(1), 5–13. Hirschman, E. C., & Holbrook, M. B. (1982). Hedonic Consumption: Emerging Concepts, Methods and Propositions. Journal of Marketing, 46(3), 92–101.

ACCEPTED MANUSCRIPT

20

Holt, N. A., & Kleiber, D. A. (2009). The Sirens’ Song of Multiplayer Online Games. Children, Youth and Environments, 19(1), 223–244. Hsieh, J.-K., Hsieh, Y.-C., Chiu, H.-C., & Yang, Y.-R. (2014). Customer Response to Web Site Atmospherics: Task-relevant Cues, Situational Involvement and PAD. Journal of Interactive Marketing, 28(3), 225–236. Hsu, S. H., Wen, M.-H., & Wu, M.-C. (2009). Exploring user experiences as predictors of MMORPG addiction. Computers & Education, 53(3), 990–999. Heussler, T., Frank, H. & Meyer, F. (2009). Moderating effects of emotion on the perceived fairness of price increases. NA-Advances in Consumer Research Volume 36. Holbrook, M. B. & Hirschman, E. C. (1982). The experiential aspects of consumption: Consumer fantasies, feelings, and fun. Journal of consumer research, 9(2), 132–140. Hota, M., Hota, M., Derbaix, M. & Derbaix, M. (2016). A real child in a virtual world: Exploring whether children’s participation in MMORPGs transforms them into virtual retail shoppers. International Journal of Retail \& Distribution Management, 44(11), 1132–1148. Koo, D.-M. & Ju, S.-H. (2010). The interactional effects of atmospherics and perceptual curiosity on emotions and online shopping intention. Computers in Human Behavior, 26(3), 377–388. Kim, S. J., Choi, Y. K., Kim, K. H., & Liu, H. (2015). Country of origin and brand image influences on perceptions of online game quality. Journal of Consumer Behaviour, 14(6), 389–398. Ladhari, R. (2007). The effect of consumption emotions on satisfaction and word-ofmouth communications. Psychology and Marketing, 24(12), 1085–1108. Lenhart, A. (2008). Teens, Video Games, and Civics: Teens’ Gaming Experiences Are Diverse and Include Significant Social Interaction and Civic Engagement. Pew Internet & American Life Project. Li, M., Jiang, Q., Tan, C.-H. & Wei, K.-K. (2014). Enhancing user-game engagement through software gaming elements. Journal of Management Information Systems, 30(4), 115–150. Liao, C.-S. (2012). SELF-CONSTRUAL, PERSONALIZATION, USER EXPERIENCE, AND WILLINGNESS TO USE CODESIGN FOR ONLINE GAMES. Information, Communication \& Society, 15(9), 1298–1322. Loureiro, S. M. C. & Ribeiro, L. (2014). Virtual atmosphere: The effect of pleasure, arousal, and delight on word-of-mouth. Journal of Promotion Management, 20(4), 452–469. Mayer, V. F. & Avila, M. G. (2006). Percepções de injustiça em aumentos de preços de serviços: um estudo experimental sobre dependência do consumidor, relevância do serviço, emoções e intenções de comportamento. ENCONTRO NACIONAL DOS PROGRAMAS DE PÓS-GRADUAÇÃO EM ADMINISTRAÇÃO, 30. Mehrabian, A. & Russell, J. A. (1974). An approach to environmental psychology. the MIT Press. Miniero, G., Rurale, A. & Addis, M. (2014). Effects of Arousal, Dominance, and Their Interaction on Pleasure in a Cultural Environment. Psychology \& Marketing, 31(8), 628–634.

ACCEPTED MANUSCRIPT

21

Mummalaneni, V. (2005). An empirical investigation of Web site characteristics, consumer emotional states and on-line shopping behaviors. Journal of Business Research, 58(4), 526–532. M, P. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246. Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology (Vol. xii). Cambridge, MA, US: Menon, S., & Kahn, B. (2002). Cross-category effects of induced arousal and pleasure on the internet shopping experience. Journal of Retailing, 78(1), 31–40. Nambisan, P. & Watt, J. H. (2011). Managing customer experiences in online product communities. Journal of Business Research, 64(8), 889–895. Nawijn, J. & Fricke, M.-C. (2015). Visitor emotions and behavioral intentions: The case of concentration camp memorial Neuengamme. International Journal of Tourism Research, 17(3), 221–228. Nicolao, L., Irwin, J. R. & Goodman, J. K. (2009). Happiness for sale: do experiential purchases make consumers happier than material purchases? Journal of Consumer Research, 36(2), 188–198. Nambisan, P., & Watt, J. H. (2011). Managing customer experiences in online product communities. Journal of Business Research, 64(8), 889–895. Ng, T. W. H., & Feldman, D. C. (2010). Organizational tenure and job performance. Otto, J. E. & Ritchie, J. B. (1996). The service experience in tourism. Tourism management, 17(3), 165–174. Owen, M. (2005). An anatomy of games. Discussion paper produced by Futurelab, Bristol. Phillips, C. A., Rolls, S., Rouse, A., & Griffiths, M. D. (1995). Home video game playing in schoolchildren: a study of incidence and patterns of play. Journal of Adolescence, 18(6), 687–691. Poels, K., & Dewitte, S. (2006). How to Capture the Heart? Reviewing 20 Years of Emotion Measurement in Advertising. Journal of Advertising Research, 46(1), 18–37. Rau, P.-L. P., Peng, S.-Y., & Yang, C.-C. (2006). Time Distortion for Expert and Novice Online Game Players. CyberPsychology & Behavior, 9(4), 396–403. Richard, M.-O. & Chebat, J.-C. (2016). Modeling online consumer behavior: Preeminence of emotions and moderating influences of need for cognition and optimal stimulation level. Journal of Business Research, 69(2), 541–553. Rezaei, S., & Ghodsi, S. S. (2014). Does value matters in playing online game? An empirical study among massively multiplayer online role-playing games (MMORPGs). Computers in Human Behavior, 35, 252–266. Ridings, C. M., & Gefen, D. (2004). Virtual Community Attraction: Why People Hang Out Online. Journal of Computer-Mediated Communication, 10(1), 00–00. Russell, J. A., & Mehrabian, A. (1977). Evidence for a three-factor theory of emotions. Journal of Research in Personality, 11(3), 273–294. Sánchez, J. L. G., Vela, F. L. G., Simarro, F. M., & Padilla-Zea, N. (2012). Playability: analysing user experience in video games. Behaviour & Information Technology, 31(10), 1033–1054.

ACCEPTED MANUSCRIPT

22

Shen, C., Monge, P., & Williams, D. (2014). The evolution of social ties online: A longitudinal study in a massively multiplayer online game. Journal of the Association for Information Science and Technology, 65(10), 2127–2137. Sun, T., Youn, S., Wu, G. & Kuntaraporn, M. (2006). Online Word-of-Mouth (or Mouse): An Exploration of Its Antecedents and Consequences. Journal of Computer-Mediated Communication, 11(4), 1104–1127. Takatalo, J., Kawai, T., Kaistinen, J., Nyman, G., & Häkkinen, J. (2011). User Experience in 3D Stereoscopic Games. Media Psychology, 14(4), 387–414. Trevino, L. K., & Webster, J. (1992). Flow in computer-mediated communication: Electronic mail and voice mail evaluation and impacts. Communication Research, 19(5), 539–573. Voida, A., & Greenberg, S. (2012). Console gaming across generations: exploring intergenerational interactions in collocated console gaming. Universal Access in the Information Society, 11(1), 45–56. Vanwesenbeeck, I., Ponnet, K. & Walrave, M. (2016). Go with the flow: How children’s persuasion knowledge is associated with their state of flow and emotions during advergame play. Journal of Consumer Behaviour, 15(1), 38–47. White, C., & Yu, Y. (2005). Satisfaction emotions and consumer behavioral intentions. Journal of Services Marketing, 19(6), 411–420. Wan, C.-S. & Chiou, W.-B. (2006). Psychological motives and online games addiction: Atest of flow theory and humanistic needs theory for taiwanese adolescents. CyberPsychology \& Behavior, 9(3), 317–324. White, C. J. (2010). The impact of emotions on service quality, satisfaction, and positive word-of-mouth intentions over time. Journal of Marketing Management, 26(5-6), 381– 394. Wu, T.-C., Scott, D. & Yang, C.-C. (2013). Advanced or addicted? Exploring the relationship of recreation specialization to flow experiences and online game addiction. Leisure Sciences, 35(3), 203–217. Wöran, B., & Arnberger, A. (2012). Exploring Relationships Between Recreation Specialization, Restorative Environments and Mountain Hikers’ Flow Experience. Leisure Sciences, 34(2), 95–114. Wu, T.-C. (Emily), Scott, D., & Yang, C.-C. (2013). Advanced or Addicted? Exploring the Relationship of Recreation Specialization to Flow Experiences and Online Game Addiction. Leisure Sciences, 35(3), 203–217. Yee, N. (2006). Motivations for Play in Online Games. CyberPsychology & Behavior, 9(6), 772–775. Zeelenberg, M., & Pieters, R. (2004). Beyond valence in customer dissatisfaction: A review and new findings on behavioral responses to regret and disappointment in failed services. Journal of Business Research, 57(4), 445–455. Zajonc, R. B. & Markus, H. (1982). Affective and cognitive factors in preferences. Journal of consumer research, 9(2), 123–131.