Does value matters in playing online game? An empirical study among massively multiplayer online role-playing games (MMORPGs)

Computers in Human Behavior 35 (2014) 252–266

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Computers in Human Behavior journal homepage: www.elsevier.com/locate/comphumbeh

Does value matters in playing online game? An empirical study among massively multiplayer online role-playing games (MMORPGs) Sajad Rezaei a,⇑, Seyedeh Sheyda Ghodsi b a b

International Business School (IBS), Universiti Teknologi Malaysia (UTM), International Campus, Kuala Lumpur, Malaysia Graduate School of Management (GSM), Multimedia University (MMU), Cyberjaya Campus, Malaysia

a r t i c l e

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Article history: Available online 27 March 2014 Keywords: PERVAL framework Repurchase intention (RI) Willingness to pay a premium price (WTP) Word-of-mouth (WOM) Massively multiplayer online role-playing games (MMORPGs)

a b s t r a c t A few study examined the impact of value and aspects of behavioral intention in virtual environment. The aim of this study is to examine the impact of emotional value (VE), social value (VS), price-value for money (VP), performance-quality value (VQ) and repurchase intention (RI), willingness to pay a premium price (WTP) and word of mouth (WOM) among massively multiplayer online role-playing games (MMORPGs). A total of 228 valid questionnaires were collected from cybercafé customers in Klang Valley-Malaysia. Structural equation modeling (SEM) was employed using partial least squares (PLS) analysis to assess measurement and structural model for reflective construct. Our result reveals that there is a positive relationship between VP and RI, VQ and RI while there is no positive relationship between VE and RI, VS and RI. VE, VP and VQ value positively impact WOM but VS does not. VE and VP have positive while VQ and VS did not explain WTP. This study contributes to literature on the new phenomena of online game and is considered as few studies in examining value in Second Life setting. The practical and social implications of study are discussed along with research limitation and implication. Ó 2014 Elsevier Ltd. All rights reserved.

1. Introduction Online game attracts researchers for its novel application and positive/negative impact on society and has received much attention from academics to policy makers, sociologist, psychologist, education and recently information drivers systems in exploring human behavior and attitudes towards games played on the internet. Some reasons make this phenomenon still unique to discover. While digital games clearly provide highly engaging activities but the nature of this engagements and activities are not well understood (Boyle, Connolly, Hainey, & Boyle, 2012). According to Davis and Lang (2012), there is not much empirical evidence to support existing theories in the users’ consumption of games. The question of what factors can contributes to game player’s intention and retention to play online games is significantly critical for academician and practitioners alike. Previous studies of online games have tended to focus on the more negative effects such as game addiction, increased aggression and problematic use of the Internet for online game players (Connolly, Boyle, MacArthur, Hainey, & Boyle, 2012; Koo, 2009) despite games might have a positive influence on users specifically and entire society in general. Likewise, the ⇑ Corresponding author. Tel.: +6032180 5023; fax: +60 362429161. E-mail addresses: [email protected], [email protected] (S. Rezaei), [email protected] (S.S. Ghodsi). http://dx.doi.org/10.1016/j.chb.2014.03.002 0747-5632/Ó 2014 Elsevier Ltd. All rights reserved.

popularity of massively multiplayer online role-playing games (MMORPGs) makes it critically important to investigate how they elicit impact on gamers’ lives (Zhong, 2011). It is important to understand how to design a successful MMORPG that can satisfy the target users (Ang, Zaphiris, & Mahmood, 2007; Lo & Wen, 2010; Zhong, 2011) and retain those players (Hou, Chern, Chen, & Chen, 2011). Because of vital differences between conventional game and MMORPGs, it is not clear in what context current understanding of the interaction between game players can be generalized (Collins, Freeman, & Chamarro-Premuzic, 2012). Unlike networked games with limited numbers of players and conventional offline computer games, MMORPGs are not only software applications as they are usually seen as a space with complicated dynamics of social interactions among users (Ang et al., 2007). Furthermore, despite the fact that delivering superior value is a key for businesses to create core competitive advantages (Chang, Ku, & Fu, 2012; Davis & Hodges, 2012; Davis & Lang, 2012; Grace & Weaven, 2011; Koo, 2009; Parasuraman, 1997; Shobeiri, Laroche, & Mazaheri, 2013; Tseng, 2011) but understanding of value creation and value remains missing and few studies have been examined on game and value paradigm (Grönroos & Voima, 2012) specifically in MMORPGs market (Li, Shi, & Wang, 2011). Most of the previous theories and models on value are adopted, validated and examine in areas other than game. Surprisingly, few studies have examined causal relationship and impact of emotional values

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(VE), social value (VS), price-value for money (VP), and performance-quality value (VQ) on repurchase intention (RI), willingness to pay a premium price (WTP) and word-of-mouth (WOM). As a marketing practice, game marketing was neglected in a research focus for decades. Games have long been neglected by academia and researchers as an distinct field of research with games being understood as a sub category of other research fields such as films, digital texts and interactive media (Davis & Lang, 2012). Accordingly, the measurement approaches of online game players’ interaction with a game is becoming a critical challenge for industry marketing and considered as an important key for future industry sustainability (Tony, Richard, & Paul, 2009). More specifically, less is known about how customer experiences on online game would be from their consumption which might be interpreted into customer ‘‘value perception components’’ (Iyanna, Bosangit, & Mohd-Any, 2012). Thus, the multidimensional influences of motivational aspects of entertainment and leisure technologies were relatively neglected in previous related studies. Research in examining factors influencing individual customer’s value remains inadequate in general and among online game players specifically (Davis & Hodges, 2012; Wu & Liang, 2009). The internet has changed all marketing concepts especially in the game sectors in which the internet is alerting relationship marketing activities, from its initial database orientation collaborative relationships with customers (Maklan & Klaus, 2011). As a research agenda, perceived value has attracted significant attention from marketing scholars in general and some argue that the study of perceived value has dominated mostly on the services literature (Karjaluoto, Jayawardhena, Leppäniemi, & Pihlström, 2012) and has been shown to be a predictor of consumer behavior, decision making process and a source of competitive advantage. It is not well understood how value is constructed from a customer value creation perspective (Gummerus & Pihlström, 2011). In addition, technology brought high expectations for customers and challenged new value created by organizations. Stetina, Kothgassner, Lehenbauer, and Kryspin-Exner (2011) found that MMORPG users experience more problematic gaming behavior compared to other virtual games players. This issue brought a practical implication in the MMORPGs industry. Specifically, this study aims to examine dimensions of perceived value proposed by Sweeney and Soutar (2001) to investigate RI, WTP and WOM among MMORPGs. Some studies validate the PERVAL framework but still there is not conclusive evidence on the concept of value. The empirical studies are rare in measuring PERVAL in regards to online game player’s behavioral intention. Therefore, the aim of this study is to examine the relationship between VE, VS, and VP, VQ and RI, WTP, WOM among MMORPGs in Malaysia. 1.1. Online game and MMORPGs Technology and specifically internet advancement has changed the behavior of businesses in creating value for their target customers. With the rapid development of computer hardware and software, the first commercial digital game appeared on the market in 1971, although it did not achieve wide acceptance, as computers were seen as primarily tools for work (Chang et al., 2012). As the computers and online games market grew rapidly many people especially children and youth spend critical amounts of time playing online games (Boyle, Connolly, & Hainey, 2011; González-González, Toledo-Delgado, Collazos-Ordoñez, & González-Sánchez, 2014; van Reijmersdal, Jansz, Peters, & van Noort, 2013). In addition, studies shows that the number of adults playing one of the most recent and popular types of video games called MMORPGs has grown exponentially in recent years (Billieux et al., 2013). The Internet based network games used a website as a customer’s interface and mostly are played on several computers

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in different methods simultaneously. Online games refer to ‘‘games that are played over the Internet using PCs and game consoles’’ (Papagiannidis, Bourlakis, & Li, 2008, p. 611) and are one sort and a category of entertainment which is oriented based on information technology adoption (Hsu & Lu, 2004). Computer and online gaming can be a sort of creative activity in which many games warrant a special type of concentration as well as a type of interaction in which the gamer helps to create various narratives by directly affecting the plot (Kim, Kim, Shim, Im, & Shon, 2013) and considered as a ‘‘multimillion-pound business’’ and there is a growing interest in using games as a vehicle for teaching and learning, interaction with computers permeates our lives both at work and play (Tony et al., 2009). The initial usage of MMORPG goes back to the 1970s. Online multiplayer gaming approach started, when people played games called ‘‘Multi User Dungeons (MUDs)’’ on the Advanced Research Projects Agency Network (ARPANET) back in the mid-1970s (Daniel & Daniel, 2012, chap. 41). MMORPGs attract a growing number of participants as MMORPGs permit individual users to interact with each other concurrently within a science fiction world full of genre-based fantasy (Ang et al., 2007; Lan-Ying & Ying-Jiun, 2011) and currently this industry is growing rapidly (Daniel & Daniel, 2012, chap. 41; Hou et al., 2011; Lo & Wen, 2010). MMORPGs are known ‘‘where multiple geographically users interact with each other in real time’’ (Ang et al., 2007) in which they are interested to play online game within a competition. Barnes and Pressey (2013) and Papagiannidis et al. (2008) refer to MMORPGs as Second Life in which ‘‘users can be whoever they want to be and do whatever they want to without many of the various constraints of the physical world’’ such as World of Warcraft, Lineage, Sociolotron, and EverQuest. Although, Shelton (2010) discuss that Second Life is different from other MMORPGs because users in Second Life do not play. Moreover, MMORPGs is ‘‘special kind of online game which allows hundreds or thousands of geographically distributed players to simultaneously play games on the internet’’ (Zhong, 2011, p. 2353) and are a type of computer games featured by a very large number of players interacting with each other in a determined online game’’ (Merrick, Isaacs, Barlow, & Gu, 2013). It mainly brings mass online players into a single game play. MMORPGs are modern games that offer a persistent 3D virtual world to support thousands of players to playing together on the Internet or PCs (Lo & Wen, 2010). Thus, MMORPGs brought a significant role in online consumer’s interactions within game industries. 2. Literature review and hypotheses development 2.1. Consumer’s behavioral intention There are several approach and elements of consumer’s behavioral intention proposed by literature in different discipline. Zeithaml, Berry, and Parasuraman (1996) distinct dimensions of behavioral intention including loyalty to company, propensity to switch, willingness to pay more, external and internal response to problem. Gruen, Osmonbekov, and Czaplewski (2006) measured loyalty intention by RI and WOM. Sirohi, McLaughlin, and Wittink (1998) measured store loyalty intentions by intent to continue shopping, intent to increase purchases and intent to recommend the store. This study constructs behavioral intention of MMORPGs by RI, WOM and WTP. 2.1.1. Repurchase intention (RI) RI has been distinct as a component of customer’s behavioral intention (Oliver & Berger, 1979; Rezaei & Amin, 2013) and is theoretically designated a consequence of perceived value (Tsai, 2005)

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which a few study conducted into purchase behavior in virtual world context (Guo & Barnes, 2011). ‘‘Repeat purchase intention refers to the subjective probability that a customer will continue to purchase a product from the same online seller’’ (Chiu, Wang, Fang, & Huang, 2014, p.89). RI defined (Hellier, Geursen, Carr, & Rickard, 2003, p. 1764) ‘‘as the individual’s judgments about buying again a designated service from the same company, taking into account his or her current situation and likely circumstances’’ while ‘‘re-patronage intentions reflect the likelihood that a customer will shop at a retail store again’’ (Jones, Reynolds, & Arnold, 2006, p. 976) and ‘‘is an apparent motivational state of consumers to repeat a buying behavior of a branded product’’ (Tsai, 2005, p. 282). Many literatures claim that because of cost matters, the retaining of business’s customers have less cost compared with acquiring new customers (Chen & Chen, 2010). In fact, customer’s re-patronage intention has an important effect on company’s survival in the long run. It has been argue that customer must shop four times at an online store before the store can make profit from that customer (Chiu et al., 2014). Customer’s loyalty offers advantages such as WTP, positive WOM recommendations, declining marketing and operating costs, and low likelihood of switching to competitors (Kim, Lee, & Kim, 2012). Although, long term customer’s loyalty remains an elusive dream for many businesses (Karjaluoto et al., 2012) and most of the MMORPGs are switching to another brand and type of game because of unknown reasons. 2.1.2. Willingness to pay a premium price (WTP) Customer’s willingness to pay a premium price (WTP) is one of the important characteristic of a successful business. As the Internet can be differentiated from traditional brick-and-mortar retailers in numerous ways; willingness to purchase could be an important distinguishing factor (Smith & Sivakumar, 2004). ‘‘Brand loyalty refers to the willingness to pay more for a brand because of perceived unique values in the brand that no alternative can provide’’ (Ferns & Walls, 2012). Most literatures have evaluated WTP in a different contexts, for example, the role of customer’s WTP in consumer contamination, consumer impatience and consumer satisfaction (Ligas & Chaudhuri, 2012). WTP drives organizational core strategy and is the core vehicle which has been used in questionnaires; and contingent valuation methods and approaches become one of the popular methods to evaluate environmental values (Andersson & Carlbäck, 2009). Accordingly, a higher willingness to pay a premium price shows that the game has enough value for game players. Therefore, there is evidence which concludes that consumers’ stated willingness to pay would translate into actual purchasing intention (Ligas & Chaudhuri, 2012). Moreover, in today’s competitive retailing, it is not always simply a matter of whether buyers are willing to pay for a particular brand but rather whether they are willing to pay more for some items at one retail over another retail because of some surplus or perception of value offered by the higher priced store (Ligas & Chaudhuri, 2012). 2.1.3. Word of mouth (WOM) The significant development of information technology adoption has brought a new concept in marketing literatures which is electronic word of mouth or ‘‘word of mouse’’ (WOM). In fact, rapid development of intent and technology adoption has changed and enhance the way in which information is transformed thorough societies which make differences from WOM in online compared with WOM in traditional markets (Duan, Gu, & Whinston, 2008). WOM recommendation as a marketing tool also called viral marketing which is a new marketing method and approach that uses electronic communications in the online area (e.g. email) to trigger brand messages throughout a vast network of consumer markets (Li, Lin, & Lai, 2010). WOM is a critically important topic among both marketing researchers and practitioners alike (Cheung &

Thadani, 2012; Dierkes, Bichler, & Krishnan, 2011; Duan et al., 2008; Lee, Kim, & Kim, 2012) because it is not only increases marketing messages but also changes consumer information processing (Wang, Yu, & Wei, 2012) and important factor in building long term relationship with customers. WOM has a distinct definition in online and electronic context and conceptualized as consumer’s post-purchase evaluation (Swan & Oliver, 1989) which refers to ‘‘marketing techniques that utilize the customers’ social networks; to increase brand awareness via self-replication and message diffusion’’ (Li et al., 2010, pp. 294– 304). According to Dierkes et al. (2011), WOM refers to the informal communication between customers about a certain brand, product or service. Negative WOM is defined ‘‘as interpersonal communication concerning an organization and/or its products or services that denigrates the object of the communication’’ (White, Breazeale, & Collier, 2012, pp. 250–261). WOM researches have also shown that negative WOM is more influential than a positive WOM which indicates that the influence WOM could vary across WOM valence and users’ intention (Gu, Tang, & Whinston, 2013). The positive WOM increase market share of company and relatively negative WOM would destroy the market share of certain retails. Traditionally, WOM communications have been proven to influence pre-purchase decision and post-purchase product perception (Purnawirawan, De Pelsmacker, & Dens, 2012). Therefore, planning, implementing and achieving organizational goals are not successfully achieved with ignoring the strength of WOM. 2.2. The concept of perceived value The concept of value discussed initially in economic literature followed by strategic and marketing literature; has continued to receive extensive research interest in the present century (Chen & Quester, 2007; Sweeney & Soutar, 2001), and the concepts emerged as the defining business issue of the 1990s (SánchezFernández & Iniesta-Bonillo, 2007). Identifying values in the minds of consumers are critical in explaining consumer behavior (Sweeney, Soutar, & Johnson, 1997) in choose to enter for a certain brand (Bevan & Murphy, 2001). Value is argued to be the most ‘‘ill-defined’’, and relatively elusive concept in management and service marketing (Grönroos & Voima, 2012) and there is lack of consensus definition for value in literatures. According to Gummerus and Pihlström (2011), even in the more mature offline literature, there is still little conclusion on how to best conceptualize ‘‘customer value’’. There are several definitions proposed for this construct. Woodruff (1997, p. 142) defined customer value as ‘‘a customer’s perceived preference for and evaluation of those product attributes, attribute performances, and consequences arising from use that facilitate (or block) achieving the customer’s goals and purposes in use situations’’. ‘‘Value is the consumer’s total assessment and evaluation of the total utility of a product which is based on perceptions of what is received and what is given’’ (Zeithaml, 1988, p. 14). Researches in assessing value operationalized the value construct based on the ‘‘give-versus-get’’ trade-off concept; and measured it with indicators such as meeting quality and price requirements’’; ‘‘fair price’’, ‘‘good value’’; ‘‘value for money’’ (Lin, Sher, & Shih, 2005), thus, it described as ‘‘a trade-off between customer sacrifice and the benefits received in return’’ (Beldona, So, & Morrison, 2006, pp. 65–80) and defined as the ‘‘subjective evaluation of the product attributes; performance and the consequences of using that product’’ (Grace & Weaven, 2011, pp. 366–380). According to value theories, value is considered as either a unitdimensional (cognition-based perception) or as a multidimensional perception that combines cognitive and emotive aspects of consumption of consumers. Value is considered as a multi-dimensional variable and has long been recognized in many intensive researches (Karjaluoto et al., 2012). On the other hand, measuring

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perceived value as a multidimensional construct has more implications and is suitable for researches; because multidimensional value affects consumer’s behavioral intentions more positively for repeaters than for first-timers (Kim et al., 2012). The unidimensional aspect of value has been criticized for its degree of measuring value differently and the traditional (cognitive and utilitarian) approach but the multidimensional approach releases a richer conception of the complexity of consumers’ perceptions of value (Sánchez-Fernández & Iniesta-Bonillo, 2009). Therefore, the PERVAL framework has a functional value component (functional value and value for money) and also includes other value dimensions (social value, epistemic value and emotional value) (Williams & Soutar, 2009). Generally, value has been measured by different type of measurements which is based on the nature of concept of value itself. Uni-dimensional and multi-dimensional measurements are general concepts through which several theories and scales have been developed accordingly. In this study, the focus is on utilitarian and hedonic value which has been a base for typology of value. In the next section, PERVAL framework scale (Sweeney & Soutar, 2001) which has been developed based on typology of consumer value (Holbrook, 1994; Holbrook, Chestnut, Oliva, & Greenleaf, 1984) is discussed.

2.3. PERVAL framework As discussed, there are different theories, models and scales in regard to the value concept. Mathwick, Malhotra, and Rigdon (2001) develop experiential value scale including elements such as playfulness, aesthetics, customers return on investment and service excellence. Sheth, Newman, and Gross (1991) multidimensional approach to value which include social, emotional, functional, epistemic and conditional value factors. Richins and Dawson (1992) developed the 18-item Material Values Scale (MVS) that consists of three consumer values success, centrality, and happiness. In this study, to examine perceived value, PERVAL scale (Sweeney & Soutar, 2001) used to examine the impact of value on MMORPGs. Initially, the PERVAL scale was designed to investigate: what consumption values affect purchase attitude and consumers behavior in consumer goods sectors (Grace & Weaven, 2011). Thus, online game player’s attitudes towards MMORPGs would be examined by applying PERVAL scale. PERVAL has several potential implications and applications which can serve as a theoretical base and framework for future empirical research (Sweeney & Soutar, 2001) while still there is not conclusive evidence on the concept of value specifically PERVAL framework. The empirical studies are rare in assessing PERVAL in regard to online game player’s attitudes, intention and behavioral intention. PERVAL has been generally accepted as one of the best approach to empirically determine perceived values from consumer’s point of view (Chi & Kilduff, 2011). PERVAL determines the perceptions of value from understanding of emotion, social, price and quality dimensions. On the other hand, PERVAL framework examines and incorporates physiological and psychological dimensions of value which are necessary to ‘‘discern the complex nature of perceived value’’ (Grace & Weaven, 2011; Williams & Soutar, 2009). To understand the issue of brand selection and consumers decision making process, the results indicate that the four-factor models (Quality, Price, Emotion, and Social) fit better than the three-factor; one-factor or null model (Lee, Trail, Kwon, & Anderson, 2011). One particularly important aspect of experiential consumption (perceived value) concerns is: its emotional components which is a dimension of PERVAL framework (Holbrook et al., 1984) and marketing involved with competition and price (Cox & Alderson, 1948). This study measures perceived value from four perspective based on PERVAL which was developed by Sweeney and Soutar (2001).

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Therefore, VE, VS, and VP, VQ (PERVAL) are elements propose to influence behavioral intention (RI, WTP and WOM) of MMORPGs. 2.3.1. Emotional value (VE) Emotion (feeling or affect) are intransigent to the retail service provision and aroused during patronage or consumption (Grace & O’Cass, 2005) which occurs in the post-purchase period (Westbrook & Oliver, 1991). This study argues that there is a positive relationship between emotional aspect of value and customers’ behavioral intention (RI, WOM and WTP). Consumption emotion is different from affective phenomenon of mood on the basis of emotion’s relatively greater psychological urgency, motivational potency, and situational specificity (Westbrook & Oliver, 1991). VE, in another words, is defined as ‘‘the utility derived from the feelings or affective states that a product generates’’ (Sweeney & Soutar, 2001, p. 211) and is ‘‘a kind of consumer knowledge inextricably which link to perceptions of uncertainty and risk’’ (Grace & Weaven, 2011). The game players are playing games mostly based on their emotional attraction. When a product or service arouses feelings or affect, VE are acquired and perceived (Gummerus & Pihlström, 2011; Karjaluoto et al., 2012). The perceived VE might be positive or negative and depending on the type of game and the initial perception of customers, the values are different. Various aspects of MMORPGs lead to positive feelings and strong attachment between players (Campello de Souza, de Lima e Silva, & Roazzi, 2010). Thus, the perceptions of value towards games are mostly affected by emotions and feelings. 2.3.1.1. VE, RI, WOM and WTP. Consumer values are beliefs that guide consumers’ behavior when purchasing products or services (Lee et al., 2011) which might influence MMORPGs. VE could be more obviously related to objects that need more interactions like playing games. Emotions influence shopping value (Stoel, Wickliffe, & Lee, 2004), re-patronage intention (Grace & O’Cass, 2005) and that VE is a key factor influencing purchase intention toward a brand (Kumar, Lee, & Kim, 2009). Consumers’ emotional response positively influence intention to purchase (Sierra, Jillapalli, & Badrinarayanan, 2013). In practice, to purchase a product or service, consumers need to evaluate the product, gather information, communicate with sellers and essentially evaluate the value of the product (Wan, Nakayama, & Sutcliffe, 2012). Sánchez, Callarisa, Rodríguez, and Moliner (2006) argue that VE influence perceive purchase value. Consumers’ product evaluations are not only assessment of price and quality, but feelings and emotion also affect consumption decisions (Hwang & Ok, 2013). According to Bailey, Gremler, and McCollough (2001), emotions and feelings influence and impact customer satisfaction. Thus, we hypothesize as below: H1. There is a positive relationship between VE and RI. Relational aspect of emotion on WOM has not been investigated by literatures (Söderlund & Rosengren, 2007) despite WOM is a consequence of emotional responses to consumption (Jones et al., 2006). In the online game markets, the community of game players is increasing in popularity because of social entertainment. WOM reflects one of the most influential and important sources of information transfer by customers which are clearly useful and profitable for companies (Khare, Labrecque, & Asare, 2011). In fact, the results from literature indicate that positive WOM would benefit popular products more than niche products and negative WOM would destroy niche products more (Gu et al., 2013). Previous related studies declared that purchase decisions and intention of customers are largely affected by the product comments and reviews provided by individual customers than the firm’s own advertisements and marketing activities. Thus, we hypothesize:

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H2. There is a positive relationship between VE and WOM. Emotions and human feelings affect customer’s attitudes and behaviors about certain objects and process of shopping in market. Research showed that customer’s perceived value is a predictor toward purchase intention, search behavior and repeat purchase in different retail settings (Grace & Weaven, 2011). Customer loyalty is described as a customer’s repeat visitation or repeat purchase behavior while including the emotional commitment or expression of a favorable attitude toward the service provider (Yoo & Bai, 2013). Willingness to buy and pay at the highest price (premium price) in online game context is one of important issues, which is mostly because it affects other people and game players’ emotions. The higher the perceived VE the higher the price they are willing to pay and positive WOM (Pihlström & Brush, 2008). Value was hypothesizes as a factor that impact willingness to purchase a product (Grewal, Krishnan, Baker, & Borin, 1998; Sweeney et al., 1997). Willingness to purchase influenced by one’s emotional state (Mano, 1999) and positively influences post-recovery satisfaction of users (Kuo & Wu, 2012). H3. There is a positive relationship between VE and WTP. 2.3.2. Price/Value (VP) Gallarza, Gil-Saura, and Holbrook (2011) recommended that future research should investigate the relationship between price and value perception to validate the relationship between constructs. Price is considered as a relevant component of factors which affect consumer behavioral intention although as a component of marketing strategy in online game markets has not been investigated. The utilitarian value of prices comparisons refer to a consumer’s increased perception of comparable products or service prices across different channels (Noble, Griffith, & Weinberger, 2005). Literatures declare that monetary value and economic value are principal dimensions of the perceived value (Tseng & Chiang, 2013). VP defined as ‘‘the utility derived from the product due to the reduction of its perceived short term and longer term costs’’ (Sweeney & Soutar, 2001, p. 211). PV and total perceived value are mostly related to online business activities which shape the behavior intention of individual users and customers. Researchers have shown that perception about price is assumed to be determined by counteracting quality perceptions and market economy; and the results of this trade-off give rise to value perceptions of certain brand (Oh, 2003). Grace and Weaven (2011) argued that money and price are significantly and positively related to behavioral intention of customers. Offering the product can be considered as having two main elemental characteristics; firstly, its value to the customers and second, its price (Anderson, Thomson, & Wynstra, 2000). Thus, price is a component of marketing strategy that always comes with value. 2.3.2.1. VP, RI, WOM and WTP. VP influence consumer decision making process and purchase intention (Lu & Hsiao, 2010; Tseng & Chiang, 2013). Literatures have elaborated on the relationship between price component and perception of value in the mind of customers as well as between price factors and customer’s loyalty (Grewal, Iyer, Krishnan, & Sharma, 2003) but research on this relationships are rare in online game and specifically MMORPGs. Price and price image influence consumer’s purchase decisions (Hamilton & Chernev, 2013) and price utility has a positive effect on the intention to purchase digital items (Kim, Gupta, & Koh, 2011) such as MMORPGs. In tourism context (Sánchez et al., 2006) argue that VP influence perceived value of the purchase. Stoel et al. (2004) hypothesize that expenditure of money in the mall has a negative influence on utilitarian and hedonic shopping value. Perceived value could be an assessment of product where the individual

compares the benefits and sacrifices in the aspect of emotion (Sánchez et al., 2006). Accordingly, consumers depend on price as a quality signal which influence purchase intention (Zeithaml, 1988). Thus, in this study, the perceived price as value would be examined in online game markets, specifically among MMORPGs. Therefore, we hypothesize as below: H4. There is a positive relationship between VP and RI. As the internet makes it easier to compare prices and therefore useful for buyers to get a product with a lower cost, monetary savings and value is important for online users (Chiu et al., 2014). Price-related monetary value reveal a low price compared to the alternatives or perceptions of good value for money (Karjaluoto et al., 2012). In addition, evaluation of product and comparison of the expenses with the accrued quality would be determined by price especially in the online game context. Researchers have shown that perception about price is assumed to be determined by counteracting the quality perceptions, a market economy; and the results of this trade-off give rise to value perceptions of a certain brand (Oh, 2003). Consumer’s perceived value as an identical economic, value and a price or as a sum of money depends differently on their consumer’s characteristics, price presentation, the consumer context and monetary form characteristics (Raghubir, 2006). Thus, we hypothesize as below: H5. There is a positive relationship between VP and WOM. Perceived value for money influences consumer’s willingness to buy (Sweeney, Soutar, & Johnson, 1999), RI (Pihlström & Brush, 2008) and loyalty toward an business (Parasuraman & Grewal, 2000). Grace and O’Cass (2005) argue that perceived value for money will have a significant positive effect on re-patronage intentions. The higher the monetary value users perceive by individuals bring the higher the price they intent to willing to pay (Pihlström & Brush, 2008). The subject of achieving premium prices in the market have clear implications for marketing managers since such a strategic advantage would lead to more profits in comparison with other competitors (Ligas & Chaudhuri, 2012). Most of the online game players are highly potentially motivated to pay premium prices. For many, monetary value is critically important for describing how online game users perceive the value of game items (Park & Lee, 2011). H6. There is a positive relationship between VP and WTP.

2.3.3. Performance/quality value (VQ) According to the previous related studies, as a final result of the spread of the cognitive approach is the main benefit component concepts (quality) and the main sacrifice component (price) have been related to the important determinants of perceived value (Sánchez-Fernández & Iniesta-Bonillo, 2009). Quality has a direct impact on consumers’ behavioral intention in shaping purchase intention, WOM and mostly leads to WTP. In literatures, VQ is considered as a functional value and defined as ‘‘the utility derived from the perceived quality and expected performance of the product’’ (Sweeney & Soutar, 2001, p. 211) which in this study argue that influence on RI, WOM and WTP. When the expectation of customers are compared with the results of what they received, it shows that the perceived quality is a cognitive construct (Sánchez et al., 2006) a construct that results from post-purchase evaluation of performance and quality of product would reflect the value of purchase and experienced service. Moreover, in the game context, the higher the perception about quality of product results, the higher the perception about value ability of certain MMORPGs. There are several strategies which companies and their marketing

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managers deploy in relation to effectiveness of those strategies on companies’ consumers decision process and quality and performance. Most of the company’s efforts in enhancing performance and quality of products will usually lead to innovation and invention through organization. Therefore, we argue that VQ has a direct impact on consumers’ behavioral intention in shaping purchase intention, WOM and mostly leads to WTP among MMORPGs. 2.3.3.1. VQ, RI, WOM and WTP. Consumer perception of performance and quality influences purchase intention (Hollebeek, 2013; Lu & Hsiao, 2010). San Martín and Herrero (2012) argue that the performance expectancy in the use of the websites positively affects the online purchase intention. Functional quality has a positive effect on the intention to purchase digital items (Kim et al., 2011) and perceive quality influence on brand selection and purchase intention (Kumar et al., 2009). Moreover, values and the perceived features, dimensions, and attributes of a product elicit consumptive behaviors (Lee et al., 2011). Accordingly, MMORPGs perception of performance and quality determine the perception of quality and repurchase intention. MMORPGs would be more interested in continues playing if they perceived VQ. Therefore we hypothesize:

257

line games possess high attraction to individuals using the Internet for social stimulation (Lan-Ying & Ying-Jiun, 2011). Social value is defined as ‘‘the utility derived from the product’s ability to enhance self-concept’’ (Sweeney & Soutar, 2001, p. 211). A social community or society is considered as a main factor linking individuals, with almost similar goals, objectives and interests in the imaginary world (Lo & Wen, 2010). VS in online banking, online retailing, service performance, ticketing are essentially different from online game because it is the online game (MMORPGs) that needs more interaction in nature (Ching, Fan-Chen, Ye-Sho, & Soushan, 2012). There is an important impact of sharing knowledge, idea, perceptions and information about almost every type of information in the virtual world. The marketers are providing a promotional strategy to enhance the online game activities and develop several weaknesses of the game which were not distinct other than by working with online game players. Social interaction is a key construct which leads online game players to be more interactive, engaged and is important in determining online game vendors success (Lin & Lin, 2011). Markets and marketing has been recognized as closely related to social welfare through all society and consumer wellbeing (Shultz & Holbrook, 2009). Thus, VS and sociality is an important component of value which is proposed to influence behavioral intention of MMORPGs.

H7. There is a positive relationship between VQ and RI. The VQ drives consumer decision making in the online market for specific MMORPGs, buying process and positive WOM. Previous related studies declare that purchase decisions and intention of customers are largely affected by the product comments and reviews provided by somebody who we can trust rather than the firm’s own advertisements (Li et al., 2010). In an organization setting, (Hartline & Jones, 1996) argue that performance influence overall service quality value and behavioral intention such as WOM recommendation. In MMORPGs context, communicate with other game players by typing their messages or by using the game’s instant messaging facility (Papagiannidis et al., 2008). Thus, the strength of WOM highly affects the performance of MMORPGs, both providers and customers’ behavioral intention which might be influenced by perception of game’s performance and quality. Thus, we hypothesize as below: H8. There is a positive relationship between VQ and WOM. Performance and quality play a significant role in determining consumers in the online game market especially in MMORPGs industry and WTP. In the technology and information products, the users are willing to pay for a new product with new, better and savvy performance. Quality of product design is recognized as the most important determinant of sales success (Mowe, Fang, & Scott, 2010). In the technology and information products such as MMORPGs, the users are willing to pay for a new product with new, better and savvy performance. The expectation of quality and perceived value are highly related to behavioral intention of consumers in the consumer markets. Most of the customers are paying a higher price for the sake of performance which is considered as a driver of consumers in the MMORPG markets. Thus, we hypothesize as below: H9. There is a positive relationship between VQ and WTP. 2.3.4. Social value (VS) VS is considered as ‘‘the utility derived from a product’s ability to enhance the social self-concepts’’ (Jamal, Othman, & Muhammad, 2011, pp. 5–15) and affects behavioral intention which lead to brands choice by MMORPGs in the decision making process. On-

2.3.4.1. VS, RI, WOM, WTP. Social interaction and social bonding plays a critical role in repeat purchase behavior due to the increasing social interaction capability provided by online businesses (Chiu et al., 2014) can be one of the most important factors for motivating people to play games (Hsu, Wen, & Wu, 2009). San Martín and Herrero (2012) argue that the social influence regarding the use of the websites of rural accommodation positively affects the online purchase intention and (Sánchez et al., 2006) propose that VS influence purchase value. Social relationship support and social self-image expression has a positive effect on the intention to purchase digital items (Kim et al., 2011). Internet games reflect high absorption of users who are using the internet for social provocation, thus, online games become a main channel for players to anonymously and instantly communicate, socialize, share experience, and relatively form virtual societies (Kwoting, Yu-Chih, & Tung-Lin, 2009). Given that an online game is both an information technology and the channel through which users communicate with others in technology-based and flow-based antecedents, cyber-space and pursue entertainment, it should influence the decision to adopt online game (Liu, Ja-Chul, Yung-Ho, & Sang-Chul, 2012) and influence MMORPGs. Thus, VS could influence behavioral intentions of MMORPGs hypothesize as below: H10. There is a positive relationship between VS and RI. Participants in online games can interact with other game players unidentified and instantly and also even form interpersonal relation or manage virtual communities (Lan-Ying & Ying-Jiun, 2011). WOM volume, captures the underlying dispersion of WOM within and across online communities, thus, studies show that WOM volume predicts future product sales (Gu et al., 2013). Most online users are using Web 2.0 tools such as consumer’s review sites, online discussion forums, weblogs, and social network sites to communicate their ideas, opinions and exchange product information (Cheung & Thadani, 2012). Active electronic WOM participation can be evoked in how consumers see themselves in relation to other users and members in their online brand communities (Lee et al., 2012). Thus, negative and positive MMORPG’s WOM can be explicitly important to continue or discontinue online game activates.

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H11. There is a positive relationship between VS and WOM. MMORPGs entail a series of interaction and relationship that often lead to improved social skills and activity in real life (Campello de Souza et al., 2010). It has been noted that personal interaction could be enhanced by providing suitable goals, operators, and also feedback and would be developed by using internet in the communication networking (Liu et al., 2012) which is different from traditional channels (Ching et al., 2012) in boosting WTP. When willingness to purchase is high, therefore, individuals would be more likely to refer individuals to a particular site trough society; more likely to shop at a particular site; and more likely to buy gifts for others (Smith & Sivakumar, 2004). On the other hand, when an individual player plays at a specific price, then he or she can drag other users to play and buy the online game, thus, VS has occurred in this point. According to WTP, values increase because people dealing with hypothetical buying decisions, which is different from people buying in a real situation (Van Loo, Caputo, Nayga, Meullenet, & Ricke, 2011).

Table 1 Demographic profile of respondents. Profile

Category

%

1

Age

18–24 25–34 35–44 Not specified

64.9 28.9 5.3 0.9

2

Gender

Male Female

66.7 33.3

3

Race

Malay Chinese Indian Others

42.5 41.7 13.6 2.2

4

Educational background

Doctorate/PHD Master Bachelor/advanced diploma Diploma Not specified

7.0 12.7 26.8 43.9 9.6

5

Occupation

Professionals (Engineer) Senior Employee level Student Executive Others

2.2 8.8 20.6 53.1 11.8 3.55

6

Income (Monthly)

Below RM1,000* RM2100 to RM3000 RM3100 to RM4000 Above RM4000

57.0 29.4 12.7 0.9

H12. There is a positive relationship between VS and WTP.

3. Method 3.1. Data collection approach

RM1000 = USD312.11.

The primary data were collected using paper-and-pencil method among MMORPGs in Malaysia. To be more specific, the target population of study was cybercafé customers in Klang Valley, Malaysia. In Malaysia, with advancement and Multimedia Super Corridor (MSC), the country is stepping toward development and expansion of business and ICT sectors. Prior to main data collection, a per-test (N = 23) was conducted to ensure that questionnaire is free of any mistake in term of wording and design, with cross sectional data collection approach in actual study. Before respondents proceed with rating the questionnaire, we ensure that they have experience in MMORPG. In this regards, the initial page of survey designed to explain the objective of research and importantly described MMORPGs concept to respondents including some of MMORPG examples. Therefore, those online game players who have had experience with MMORPGs were entitled to respond to questionnaire. Moreover, in the questionnaire (Section A), respondents were asked about demographic variables such as age, gender, race, educational background, occupation and income (see Table 1). Table 1 depicts demographic profile of respondents. To determine the appropriate sample size, power analysis (Chin, 2010) based on the portion of the model with the largest number of predictor with minimal recommendations range from 30 to 100 cases was used. Moreover, proposed by Gefen, Straub, and Boudreau (2000) at least 10 times the number of items in the most complex construct rule of thumb used in this study to set the sample size. From paper-and-pencil method, total of 260 sets of questionnaires were distributed among MMORPGs players in cybercafé in Klang Valley, Malaysia. 232 questionnaires were returned back and out of the 232 questionnaires received, some of them were not usable; only 228 respondents’ responded to the questionnaires properly. Thus, we obtained rate of 87.92%. In section B which is the main section of the questionnaire, the factors that affect online game player’s behavioral intention was translated into several questions (the measurement scales are presented Appendix A). The measurement in section B is the 6 and 7 point Likert scale with the scale format which asks target population to indicate the extent to which they agree or disagree with a series of mental belief or behavioral belief statements about a given object. 5 items were

adopted to measure VE, 4 items to measure VS, 4 items to measure VQ, 4 items to measure VP adopted from Sweeney and Soutar (2001). To measure RI items were adopted from previous studies (Aron & Jamie, 2010; Chao-Min, Chen-Chi, Hsiang-Lan, & Yu-Hui, 2009; Liu & Li, 2011; Park & Lee, 2011), 4 items to measure WTP (Srinivasan, Anderson, & Ponnavolu, 2002; Suwelack, Hogreve, & Hoyer, 2011) and 4 items to measure WOM (Srinivasan et al., 2002). 3.2. Dealing with missing values For researchers in the social and behavioral sciences missing data are an issue (Schafer & Olsen, 1998). Before data were analyze, expectation maximization algorithm (Little, 1988) used to impute missing values and handle missing values by means of SPSS software (Version 19). The Expectation Maximization method is an iterative processing which all other variables relevant to the construct of interest are used to predict the values of the missing variables (Graham, Hofer, Donaldson, MacKinnon, & Schafer, 1997). The Expectation Maximization analysis in SPSS generates Little’s MCAR (Missing Completely At Random) v2 statistic which show that the missing data assumed to be missing at random. Thus, we run expectation maximization procedure to impute missing values and handle missing values problem. 3.3. Common method bias Common method bias may exist due to the single survey method in data collection form target population (MacKenzie & Podsakoff, 2012; Podsakoff, MacKenzie, Jeong-Yeon, & Podsakoff, 2003; Zheng, Zhao, & Stylianou, 2012). Most researchers agree that common method variance (i.e., variance that is attributable to the measurement method rather than to the constructs the measures represent) is a potential problem in behavioral research (Podsakoff et al., 2003). This study addressed common method variance with potential threat by following guideline proposed by Podsakoff et al.

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(2003). At the design stage: common scale anchors are avoided by using 6 anchors and 7 anchors for endogenous construct and exogenous constructs. At the data analysis stage three statistical techniques the Harman’s one-factor test, in the partial correlation procedures, the structural model marker-variable technique were conducted. Thus, our statistical result shows that common method variance is not a concern in this study.

Table 2 Measurements model. Construct

Item

Outer loadings

AVEa

CRb

CAc

Repurchase Intention (RI)

RI1 RI2 RI3 RI4

0.738 0.848 0.841 0.817

0.660

0.886

0.827

Emotional Value (VE)

VE1 VE2 VE3 VE4 VE5

0.842 0.836 0.840 0.836 0.839

0.703

0.922

0.895

Price-Value For Money (VP)

VP1 VP2 VP3 VP4

0.838 0.879 0.870 0.861

0.743

0.921

0.885

Performance-Quality Value (VQ)

VQ1 VQ2 VQ3 VQ4

0.920 0.945 0.901 0.912

0.846

0.956

0.939

Social Value (VS)

VS1 VS2 VS3 VS4

0.865 0.893 0.899 0.870

0.778

0.933

0.905

Word-of-mouth (WOM)

WOM1 WOM2 WOM3 WOM4

0.866 0.862 0.880 0.860

0.752

0.924

0.890

Willingness to pay a premium Price (WTP)

WTP1 WTP2 WTP3 WTP4

0.885 0.901 0.896 0.848

0.779

0.934

0.905

3.4. Assessment of measurements and structural model The structural equation modeling (SEM) was employed using partial least squares (PLS) analysis to assess measurement and structural model for reflective construct. PLS-SEM or partial least squares path modeling has enjoyed increasing popularity in recent years (Becker, Klein, & Wetzels, 2012). We employed PLS-SEM to analyze the data by applying SmartPLS software (Ringle, Wende, & Will, 2005). PLS-SEM is, however, advantageous compared to covariance based structural equation modeling when analyzing predictive research models that are in the stages of theory development (Gimbert, Bisbe, & Mendoza, 2010). According to Hair, Ringle, and Sarstedt (2011), reasons for using PLS-SEM is ‘‘if the the aim of study is to predict a phenomena (behavior) rather than conformation’’. Hence, PLS-SEM recognized as an appropriate method to conduct the statistical analysis in this study. The common approach in reporting SEM result is to present them in two steps (Chin, 2010): first is to focus on the reliability and validity of the item measures and second structural model (Hair et al., 2013). Reflective measurement models’ validity assessment focuses on convergent validity and discriminant validity Hair 2011 are discussed. According to Hair et al. (2011) and Hair, Hult, Ringle, and Sarstedt (2013), internal consistency reliability (composite reliability should be higher than 0.70), indicator reliability (indicator loadings should be higher than 0.70) and convergent validity (average variance extracted (AVE) should be higher than 0.50) deployed to assess measurement items using PLS algorithm procedure. Moreover, discriminant validity was assesses according to Fornell and Larcker (1981) criterion. Before assessing the structural model we examine the structural model for collinearity. Followed by Hair et al. (2013) to assess structural model we performed bootstrapping (5000 resample) to assess the path coefficients’ significance and to assess predictive relevance we also performed blindfolding to obtain cross-validated redundancy measures for each construct. Moreover, the level of the R2 values, the f2 effect size, and the predictive relevance (Q2 and the q2 effect size) were assessing in line with structural model.

4. Results 4.1. Assessing measurement model To evaluate reflectively measured models, we examine the outer loadings, composite reliability (CR), average variance extracted (AVE = convergent validity) and discriminant validity. Table 2 shows the outer loadings, CR, AVE, Cronbach’s alpha for reflective constructs. As shown in Table 2, all outer loadings for items are above 0.738 which are above the minimum threshold value of 0.70. In addition, all reflective constructs have high levels of internal consistency reliability as demonstrated by the above composite reliability values. In addition, the AVE values (convergent validity) are well above the minimum required level of 0.50, thus, demonstrating convergent validity for all constructs. Furthermore, to assess the discrimination between constructs, the results depicted in Table 3 indicate that discriminant validity between all the constructs

a Average variance extracted (AVE) = (summation of the square of the factor loadings)/{(summation of the square of the factor loadings) + (summation of the error variances)}. b Composite reliability (CR) = (square of the summation of the factor loadings)/ {(square of the summation of the factor loadings) + (square of the summation of the error variances)}. c CA: Cronbachs Alpha.

Table 3 Discriminate validity. Construct

RI

VE

VP

VQ

VS

WOM

WTP

RI VE VP VQ VS WOM WTP

0.812a 0.338 0.323 0.399 0.311 0.462 0.335

0.839 0.630 0.508 0.632 0.396 0.369

0.862 0.304 0.368 0.377 0.330

0.920 0.697 0.347 0.272

0.882 0.317 0.308

0.867 0.515

0.883

a

The diagonals represent the square root of AVE and the off-diagonals represent the correlation.

confirmed. The off-diagonal values matrix are the correlations between the latent constructs. Comparing the loadings across the columns in the Table 4 indicates that an indicator’s loadings on its own construct are in all cases higher than all of its cross loadings with other constructs. Thus, the results indicate there is discriminant validity between all the constructs based on the cross loadings criterion. 4.2. Assessing structural model Once the construct measures have been confirmed as reliable and valid we proceed to assess the structural model which involve examining the model’s predictive capabilities and the relationships

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Table 4 Cross loading. Construct a

RI1 RI2 RI3 RI4 VE1 VE2 VE3 VE4 VE5 VP1 VP2 VP3 VP4 VQ1 VQ2 VQ3 VQ4 VS1 VS2 VS3 VS4 WOM1 WOM2 WOM3 WOM4 WTP1 WTP2 WTP3 WTP4 a

RI

VE

VP

VQ

VS

WOM

WTP

0.738 0.848 0.841 0.817 0.544 0.452 0.450 0.469 0.512 0.452 0.488 0.489 0.527 0.570 0.599 0.527 0.621 0.518 0.524 0.442 0.484 0.612 0.536 0.594 0.609 0.472 0.513 0.524 0.536

0.401 0.469 0.487 0.522 0.842 0.836 0.840 0.836 0.839 0.757 0.697 0.622 0.663 0.624 0.663 0.657 0.678 0.682 0.657 0.707 0.756 0.537 0.498 0.560 0.582 0.535 0.547 0.552 0.509

0.441 0.420 0.447 0.534 0.597 0.693 0.668 0.696 0.680 0.838 0.879 0.870 0.861 0.493 0.497 0.488 0.548 0.462 0.511 0.549 0.616 0.546 0.472 0.528 0.576 0.516 0.503 0.508 0.504

0.446 0.543 0.542 0.517 0.682 0.596 0.539 0.609 0.552 0.562 0.487 0.419 0.438 0.920 0.945 0.901 0.912 0.808 0.748 0.700 0.691 0.497 0.482 0.510 0.550 0.465 0.450 0.500 0.424

0.387 0.469 0.488 0.463 0.708 0.691 0.646 0.645 0.640 0.571 0.536 0.469 0.520 0.719 0.762 0.770 0.819 0.865 0.893 0.899 0.870 0.484 0.449 0.486 0.526 0.511 0.472 0.506 0.471

0.481 0.558 0.549 0.611 0.551 0.513 0.505 0.538 0.528 0.514 0.499 0.544 0.558 0.529 0.552 0.533 0.553 0.482 0.480 0.513 0.509 0.866 0.862 0.880 0.860 0.625 0.633 0.636 0.642

0.394 0.511 0.460 0.507 0.557 0.509 0.464 0.522 0.487 0.499 0.487 0.468 0.525 0.472 0.488 0.438 0.515 0.456 0.476 0.493 0.532 0.673 0.606 0.604 0.607 0.885 0.901 0.896 0.848

Bold values are loadings for items which are above the recommended value of

0.5.

between the constructs (J.F. Hair et al., 2013). Table 5 depicts the hypothesis testing. Before assessing the structural model we examine the structural model for collinearity issue and our result shows that all VIF values are clearly below the threshold of 5. Accordingly, we assess significance and relevance of the structural model relationships by applying the PLS-SEM algorithm which estimates are obtained for the structural model relationships (the path coefficients) and represent the hypothesized relationships between the constructs and bootstrapping procedure to examine their significance with 5000 resample (Hair et al., 2013). As shown in Table 5, hypothesis 1, hypothesis 9, hypothesis 10, hypothesis 11, hypothesis 12 were not supported while hypothesis 2, hypothesis 3, hypothesis 4, hypothesis 5, hypothesis 6,

hypothesis 7, hypothesis 8 supported. Referring to path coefficients in Table 5, VP is more important followed by VQ in determining RI. The VS is not a predictor toward explaining RI, WTP and WOM. In addition, the relationship between VE with WTP and WOM supported while RI not supported. In fact, our results support the positive relationship between VE with WOM and WTP while our result does not support positive relationship between VE and RI. Accordingly, VP is positively related to WOM, WTP and RI while social value is not supported. Finally, the relationship between VQ with RI and WOM were supported but our result does not support VQ with WTP. In the other hand, our result reveal that there is a positive relationship between VP and RI, VQ and RI while there is no positive relationship between VE, VS and RI. VE, VP and VQ can be used to predict WOM but VS is not important. VE and VP can be use while PQ and VS cannot be used in predicting WTP. In the PLS algorithm procedure, the R2 values of the endogenous latent variables can be interpreted. The R2 value of RI (0.470), WOM (0.413) and WTP (0.475) can consider as moderate. Fig. 1 shows these findings from structural point of view. In addition to evaluating the size of the R2 values of all endogenous constructs, the f 2 effect size measures the change in the R2 value when a specified exogenous construct is omitted from the model. Depicted in Table 7, f2 and q2 are compared against path coefficient. Moreover, blindfolding procedure used to obtain predictive relevance (Q2). For SEM models, Q2 values larger than zero for a specific reflective endogenous latent variable indicate the path model’s predictive relevance for a construct. When blindfolding performed for all endogenous latent constructs in the model they all have Q2 values considerably above zero which indicates the model has medium (RI: Q2 = 0.294; WOM: Q2 = 0.3220) large (WTP: Q2 = 0.355) predictive relevance for all construct (see Table 6).

5. Discussion Value perception is considered as a core business driver in successful businesses. Many researchers have focused on the measurements and scale for consumer value but because of the needs, wants and demand of individual buyers are shifting over time and depending very much on the current situation in the market, it is necessary to constantly assess value within specific contexts (Davis & Hodges, 2012) such as MMORPGs. Sánchez et al. (2006) deployed the PERVAL framework to examine experiential perceived value of the purchase of a tourism product and found

Table 5 Hypothesis testing. Hypothesis

Path

Standard error

t-Statistics

Decision

H1 H2 H3

VE ? RI VE ? WOM VE ? WTP

0.051 0.183 0.211

0.128 0.102 0.114

0.399 1.788* 1.855*

Not supported Supported Supported

H4 H5 H6

VP ? RI VP ? WOM VP ? WTP

0.303 0.319 0.264

0.099 0.093 0.114

3.074*** 3.424*** 2.312**

Supported Supported Supported

H7 H8 H9

VQ ? RI VQ ? WOM VQ ? WTP

0.494 0.318 0.117

0.098 0.080 0.105

5.036*** 3.969*** 1.108

Supported Supported Not supported

H10 H11 H12

VS ? RI VS ? WOM VS ? WTP

0.079 0.042 0.129

0.114 0.100 0.169

0.700 0.421 0.763

Not supported Not supported Not supported

Notes: Critical t-values. Two-tailed test are 1.65 (significance level = 10%). ** 1.96 (significance level = 5%). *** 2.58 (significance level = 1%). *

Path coefficients

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Fig. 1. Structural model.

Table 6 Results of R2 and Q2. Endogenous construct

R2

Q2

RI WOM WTP

0.470 0.475 0.413

0.294 0.355 0.322

studies, few studies examined the impact of perceived value of behavioral intention among Malaysian online game players. Thus, this study contributes to literature on the new phenomena of online game which is the MMORPGs. 5.1. Managerial implication and recommendation

that PERVAL is sufficiently constructed in predicting post-purchase evaluation of products because of its multidimensional power of variables which is almost consistent with our results. Yang and Jolly (2009) argued that four sub-values of PERVAL are relevant psychological dimensions driving buyers’ behavioral intentions to use mobile data services. This study is among the few study that aim to determine the relationship between VE, VS, VP, VQ and behavioral intention (RI, WTP and WOM) among MMORPGs which is a step toward understanding consumer’s behavior in Second Life. In addition, this study explored into determining the four (4) aspects of perceived value as proposed by Sweeney and Soutar (2001). The research contributes to the understanding of MMORPGs in globally and specifically in Malaysia – a country that not much known about MMORPGs. Based on previous related

Based on online game player’s preferences and value perception, business and organizations from profit to non-profit sectors are deploying online game applications in their business activities. In addition, the online game providers are looking into the preference of their users which is rapidly changing (Park & Lee, 2011). This study contributes to the improvement of online game industry – MMORPGs. Our findings reveal that online game players are highly influenced by the type of value. Marketing managers should deliver value to consumers in the online game market by emphasizing on the emotional aspect of value. This is because online game players are mostly affected by emotional features of game. MMORPGs are mostly looking for emotional and feeling of gaming. Therefore, online game designers should look into the feeling impact of value which determines behavioral intention of online

Table 7 Path coefficients, f2 and q2. Research construct

VE VP VQ VS a

Path coefficients.

RI

WOM

WTP

PCa

f2

q2

PC*

f2

q2

PC*

f2

q2

0.051 0.303 0.494 0.079

0.012 0.160 0.243 0.053

0.001 0.109 0.203 0.027

0.183 0.319 0.318 0.042

0.100 0.158 0.157 0.034

0.019 0.120 0.109 0.015

0.211 0.264 0.117 0.129

0.109 0.010 0.044 0.041

0.056 0.034 0.012 0.096

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game players. Companies should realize that the value customers place on technology as part of the shopping process is the benefit of recent innovations in customer interface technology (Burke, 2002). Most of the value dimensions could be transferred by technology enhancement in the online game industry. Moreover, the rapid developments of World Wide Web has not only strengthened the material, contents, shapes and formats of various online games, but also caused dramatic growth for the gaming industry (Lin & Lin, 2011). Generally acknowledged, game developers and designers have not completely implemented all of the characters of the games because of limitation of development resources like human resources and money with the time-to-market pressure of the product (Lo & Wen, 2010). Therefore, to be more sufficient, the area of online game needs more attention. This study reveals that online game players are not influenced by the social aspect of value. The social value is important because the nature of MMORPGs is interaction through online game channels. To enhance interaction as a social aspect of value, managers should realize the importance of social media channels. Most of the online game players are looking into the sociality of online game interactions with their peers around the world. Moreover, this implies that developing and improving of other types of online game may depend on the social aspect of the game. VP is found to be important for online game players in Malaysia. This is consistent with previous study in online and offline marketing. Most of the consumers in the consumer markets are highly influenced by price incentives and promotions. In addition, online game players in Malaysia are looking for a more valuable price. The implication of this finding is for marketers in the pricing strategy. Price strategy will influence the rate of return on MMORPGs. Thus, marketers must evaluate the influence of marketing online game in the aspect of value of price. Finally, marketers in online game markets should realize the importance of performance and quality of product for marketing implications. Few studies have examined the relationship between performance and quality as aspect of value in examining MMORPGs. In addition, this study reveals that there is a positive relationship between VQ and behavioral intention of MMORPGs. Thus, there would be a managerial implication toward understanding and explaining quality on the behavior of online game players. MMORPGs marketers should enhance the performance of quality in regards to perceived value dimensions.

5.2. Social implication This study discussed the positive impact of online game players among a specific type of digital game which is known as MMORPGs. Based on the research findings, the MMORPG expansion have positive impact on societies. Two factors are important in these arguments which are VS and VP. In addition, VE and VP assumed to be relevant to online game designers. Firstly, social value in this study was not found as a predictor toward behavioral intention of digital game players. The social value is important because of the stimulating social interaction among massive users. The interaction among online game users would possibly lead to knowledge sharing, emotion sharing and information acquiring among users. In fact, in this study, online game players value the sociality of online game. Thus, societies should encourage users to use and play online game with the nature of sociability compared to other types of online game categories which usually leads to isolate game addiction. The second important aspect of value in this study is price or VP. In this study, 57.0% of the respondents stated that their

monthly income was less than RM1000.00 (Approximately USD312.00). This indicates that most of the low income families prefer to play digital games rather than physical games. Most of the online game players cannot find a better alternative than internet games in cybercafés in which the price is much lower than other entertainment activities. Thus, VP is determining online game players’ behavioral intention (RI, WOM, and WTP). The internet and computer game industry has become a fruitful industry for investors to invest. The online game industry has dramatically expanded during the past years both from market size and the population of people who are using the game through online. This is occurring because online game is not solely playing a game; the application of online game could be used in the learning process, and improving skills about certain activities. Most of the businesses are realizing the positive impact of online game on marketing activities in different ways. From the industry and business point of view, online games help other businesses to promote and advertise their product via online game which has been validated as a new channel toward advertising activities (Tony et al., 2009). Thus, the online game industry and its product has been developed, assessed and targeted for different prospective businesses through human society (Merrick et al., 2013). In today’s societies, online game has become a dominant activity among the youth compared to traditional games. Thus, the popularity of online game is significantly increasing around the globe (Daniel & Daniel, 2012, chap. 41). A huge number of children, youth and adolescents are willing to spend for online game activities with sociability in nature. Therefore, online game market has important implications in research and practice. Marketing on the Internet has advantages compared with traditional media because of higher speed, lower costs, and externality effects specifically among youth which are capable to use the Internet for different purposes. As shown in Table 1 and 649% of MMORPGs were age between 18–24 and 28.9% were age 25–34. Most of the companies are looking into internet capability as a competitive advantage. Web site interactivity receives extensive attention in the marketing literature and creates numerous opportunities for marketers to persuade online consumers (van Noort, Voorveld, & van Reijmersdal, 2012). Thus, the virtual world opens a new topic for research and creates new opportunities for stockholders. The virtual world depends very much on internet development which relatively enhances the attractiveness of online game markets. The rapid growth of online game markets which are using internet as communication is fascinating and associated with traditional channels (Keng & Ting, 2009). Therefore, the virtual world is providing a place for people to interact and communicate with each other.

5.3. Research limitations and future directions This study has some limitations which propose some areas for future research. Firstly, this study examined MMORPGs. Future studies should compare MMORPGs and other types of online game player’s behavioral intention. Secondly, this study did not examine the relationship between value and game addiction, thus, future research should examine the relationship between perceived value and the act of addiction among online game users with an assessment of value perception. Finally, this study examined all age categories of MMORPGs. Future researchers should examine the savviest online game players which are mainly the generation Yers.

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Appendix A. Questionnaires items

Appendix A. (continued)

Research construct

Scale

Source

1

Quality Value (VQ)a

VQ1 Online gamec has consistent quality VQ2 Online game is well made VQ3 Online game has an acceptable standard of quality VQ4 Online game would perform consistently

Sweeney and Soutar (2001)

2

Social Value (VS)a

VS1 Online game would help me to feel acceptable VS2 Online games would improve the way I am perceived VS3 Online game would make a good impression on other people VS4 Online game would give its owner social approval

Sweeney and Soutar (2001)

3

Emotional Value (VE)a

VE1 Online game is one that I would enjoy VE2 Online game would make me want to use it VE3 Online game is one that I would feel relaxed about using VE4 Online game would make me feel good VE5 Online game would give me pleasure

Sweeney and Soutar (2001)

VP1 Online game is reasonably priced VP2 Online game offers value for money VP3 Online game is a good product for the price VP4 Online game would be economical

Sweeney and Soutar (2001)

RI1 If I could, I would like to continue using the web site for purchasing online

Chao-Min et al. (2009), Aron and Jamie (2010), Park and Lee (2011) and Liu and Li (2011)

4

Price Value (VP)a

Research construct

Repurchase Intention (RI)b

Source

game RI2 I intend to continue purchasing online game in the future RI3 I seldom consider switching to another related website RI4 I believe I will play online games in the future

a b c

5

Scale

6

Willingness to pay a premium price (WTP)a

WTP1 For this online game I would be willing to pay a higher price WTP2 I would still buy the online game even if the seller increases the price WTP3 I will continue to do business with this website if its prices increase somewhat WTP4 I will pay a higher price at this website relative to the competition for the same benefit

Srinivasan et al. (2002) and Suwelack et al. (2011)

7

Word-ofmouth (WOM)a

WOM1 I say positive things about this online game website to other people WOM2 I recommend this online game website to anyone who seeks my advice WOM3 I encourage friends to do business with this online game website WOM4 I do not hesitate to refer my acquaintances to this online game website

Srinivasan et al. (2002)

7-Point scales anchored by ‘‘strongly disagree’’ to ‘‘strongly agree’’. 6-Point scales anchored by ‘‘strongly disagree’’ to ‘‘strongly agree’’. Massively multiplayer online role-playing games (MMORPGs).

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