Keywords

1 Introduction

Demographics keep changing globally, and recently aging society has become a key issue. Taiwan has been an aging society since 1993 - in Taiwan, citizens aged between 45 and 65 are defined as middle and old aged by Employment Service Act [1].

Technology improves rapidly, and mobile devices are now a part of our life. For instance, smartphone and tablet both change our life dramatically. In Taiwan, more than 60 % of people own a mobile device. They use the device to make phone calls, take photos, chat with friends, and play games. Mobile devices now are also key instruments for information communication and entertainments [2]. Moreover, choices for digital games are increasing as well. Mobile devices also boost developments of mobile games that utilize multiple technologies, such as touch screen and gyroscope that create a new way of gaming. People can interact with friends, and buy virtual items to make game progressing easier.

Before maturity of mobile devices’ developments, there are relatively fewer middle and old aged players. However, without specific gaming platform, recent survey shows number of players older than 45 increase significantly compared to 2013 [3]. It’s assumed that as mobile devices become more popular, number of middle and old aged people use mobile games for entertainment also increase. Huang’s report [4] mentions that when playing mobile games, middle and old aged players prefer to purchase virtual items for achievements or self-assurance.

In summary, this study focuses on middle and old aged players’ purchase intention for virtual items in mobile games. In questionnaires all ages are surveyed, and results lay groundwork for future interview questionnaire design. Companies may utilize the result to design games and campaigns that encourage players to purchase virtual items.

2 Literature Review

2.1 Middle and Old Aged Player

Taiwan has officially been an aging society since 1993. According to Employment Service Act, Ministry of Justice, middle and old aged are citizens aged between 45 and 65 [1]. In digital era, middle and old aged may face digital disorders, including psychological disorder, physiological disorder, societal disorder, and lack of experience. However, due to recent mobile devices and mobile games craze, middle and old aged treat mobile games as a new way of entertainment. They can interact with relatives and friends, or purchase in game virtual items for self assurance [4, 5].

2.2 Mobile Game and Virtual Items

Mobile Game. As technology improves, communication and game industries gradually move into same mobile game industry. Mobile games utilize mobile devices with wireless connectivity, and they can be played anytime [6]. Take smartphone as an example, Lin, Chen & Kuo [7] state that smartphone integrates several technologies, including touch screen and sensors, and users can operate intuitively and create new ways of gaming. Lin [8] points out that smartphones revolutionize mobile games; touch screen enables user to operate intuitively; sensors including gyroscope, G-sensor, and GPS, allow players to feel presence and receive feedbacks.

Virtual Items. Players spend money for gaming, such as prepaid card or membership, and spend time and efforts to accumulate in game assets, including avatar or virtual currency. These items are collectively known as virtual assets [9]. Virtual items for mobile games are purchased mainly in two channels: people may buy prepaid card in convenient store and save amounts as in game currency; also, people may directly buy virtual currency in game store with credit cards.

2.3 Flow Experience Theory

Csikszentmihalyi [10] proposes flow theory that is also known as flow experience. The theory integrates motivation, individual factors, and subjective experience. When skills and challenges achieve equilibrium, individual enter the flow channel (Fig. 1).

Fig. 1.
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2013 & 2014 Yahoo 2014 Yahoo! game White Paper, players’ age comparison

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Csikszentmihalyi [11] summarizes that there are eight characteristics when individual enters flow channel: clear goals and immediate feedbacks, balance between challenges and skills, actions and awareness merge, concentration on the task, a sense of potential control, loss of self-consciousness, altered sense of time, and experience becomes autotelic. Based on past literatures, this study classifies flow experiences into two states (flow level): partial flow state, and complete flow state.

2.4 Game Motivation

Game motivation affects players’ behavior to participate games. Characteristics of players’ game motivation are studied for player participation increase [12]. Lepper & Malone [13] categorizes game motivation into individual motivation and interpersonal motivation; individual motivation includes challenge, curiosity, control, and fantasy; interpersonal motivation includes competition, cooperation, and recognition. Based on past studies, Tsai [14] categorizes motivation of mobile games participation into entertainment, curiosity, self-assurance, social interaction, and attribution avoidance. Summarized from past literatures, this study categorizes game motivation into five types: challenges and curiosity, cooperation and social interaction, competition and self-assurance, fantasy, and entertainment.

2.5 Game Playability

Playability derives from the concept of usability; when usability is adopted in game environment, game designer identifies it as playability. Clanton [15] classifies game playability into three sections: game interface, game mechanics, and game play. For mobile games, Korhonen and Koivsto [16] classify it as game usability, mobility, and gameplay. Based on past literatures, this study classifies playability as four types: usability, mobility, artistry, and sociability.

2.6 Satisfaction and Purchase Intention

Woodside, Frey and Daly [17] point out that customer satisfaction is the overall behavior after purchases and reflects customers’ fondness of the product. Cronin & Taylor [18] state that satisfaction is a key factor for customer’s decision to repurchase. Kotler [19] states that if customers are very satisfied with the product or service, their purchase intention is also higher. They will repurchase relevant product or service, and inform others benefits of the product or service.

3 Method

This study adopts quantitative method, and the survey is conduct for players of all ages. Only people with mobile games experience can be qualified for survey subjects. The survey is conducted through internet questionnaires with 15 days duration, and 1,283 replies are received. After 148 invalid replies are removed, final effective sample size is 1,035 and effective response rate is 80.6 %. Afterward, analytical software, SPSS 20, is used to conduct analysis, including reliability, correlation, regression, and variance. Based on analysis results, players’ views of all age can be understood, including perspectives of participation motivation, playability for mobile games, satisfaction impact due to flow level, and purchase intention of virtual items. Results inferred above can be adopted for questionnaire improvement and used for future individual interview of middle and old aged players.

4 Analysis and Discussion

Participants. The number of total effective survey subjects is 1,035 players. Based on Erikson’s stages of development [20], Employment Service Act [1], and studies of Lin [21], this study categorizes subjects into four groups by ages (Fig. 3), (A) 239 teenagers aged between 13 and 18, 23 %; (B) 591 youths aged between 19 and 30, 57 %; (C) 133 middle-aged aged between 31 and 44, 13 %; (D) 72 old-aged aged between 45 and 65, 7 %.

Fig. 2.
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Flow theory model

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Fig. 3.
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Participants’ age in this study

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Reliability Analysis. This analysis focuses on consistency of each dimension for mobile games, including participation motivation, playability, flow level, and purchase intention. When Cronbach’s α is higher, internal consistency and correlation are also higher, which is insightful for reliability of each dimension. In this study, Cronbach’s α of each dimension is larger than .70 (Table 1). After removing items, Cronbach’s α is still mostly larger than .70. Therefore it’s concluded that questionnaire hold good reliability, and survey subjects’ views are consistent.

Table 1. Reliability analysis in this study
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Correlation Analysis. This study aims to understand correlation of game motivation, flow level, purchase intention, as well as game playability, flow level, and purchase intention; thus Pearson correlation coefficient analysis is conducted. According to results (Tables 2 and 3), coefficient of game motivation and flow level is .555, which shows they are moderately correlated; coefficient of game motivation and purchase intention is .328, which shows they are modestly correlated; coefficient of game playability and flow level is .572, which shows they are moderately correlated; coefficient of game playability and purchase intention is .187, which shows they are modestly correlated; coefficient of flow level and purchase intention is .239, which shows they are modestly correlated.

Table 2. Correlation Analysis of game motivation, flow level and purchase intention in this study
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Table 3. Correlation Analysis of game playability, flow level and purchase intention in this study
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Analysis results infer that game motivation and flow level, as well as game playability and flow level, are moderately correlated. This means the higher players’ participation motivation, and game provide varieties for playability, the better players are in flow channel; although game motivation and purchase intention, as well as game playability and purchase intention, are modestly correlated, different game motivation or game playability may produce different purchase intention of virtual items. Flow level and purchase intention are modestly correlated, so that players in flow channel are not correlated to purchase intention. Additional game features may be needed to increase purchase intention when players are in flow channel and increase their correlation.

Regression Analysis. This study conducts multiple regressions for all effective samples. Purchase intention of virtual items is dependent variable; dimensions of game motivation and game playability are independent variables; flow level is the intervening variable. Results of correlation are shown in Tables 4 and 5.

Table 4. Regression analysis of game motivation, purchase intention and flow level in this study
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Table 5. Regression analysis of game playability, purchase intention and flow level in this study
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According to Table 4, it can be inferred that each dimensions of game motivation affects flow level (A1) positively and significantly, so the survey subject will achieve flow channel for all game motivations. For each dimension of game motivation and purchase intention (A2), only competition and self-assurance affect it positively and significantly, and entertainment affects it negatively and significantly. This denotes survey subject may seek self-assurance by succeeding in competition. Using virtual items will increase chance of succeeding, therefore purchase intention for virtual items increase as well. However survey subject will not increase purchase intention of virtual items because of entertainment - mobile games are only a recreation of life. If flow level is intervening variable (A3) of game motivation to purchase intention, flow level affects purchase intention positively and significantly. When affected by flow level, competition and self-assurance affects purchase intention positively and significantly; entertainment affects purchase intention negatively and significantly. Summarized from A1 to A3, it’s clear that whether flow level is intervening variable, competition and self-assurance and entertainment affects purchase intention significantly. Therefore this study concludes that albeit flow level does not hold significant mediating effect for competition, self-assurance, and entertainment, it does indirectly increase flow level and increase purchase intention.

Moreover, according to Table 5, it can be inferred that each dimension of game playability affect flow level (B1) positively and significantly so survey subjects achieve flow channel for all game playability. Each dimensions of game playability affect purchase intention (B2) and mobility negatively and significantly; it affects artistry and sociability positively and significantly. This denotes survey player will not increase purchase intention if virtual items can be purchased anytime and anywhere. On the contrary, if artistry design is favorable, such as avatar, scenario, and visual effects, they are more likely to increase purchase intention of virtual items. If games also provide social interaction, and achievements can be accomplished by interactions such as chatting, cooperation, or competition, this will also increase purchase intention for virtual items. If flow level is intervening variable (B3) for game playability to purchase intention, flow level affects purchase intention positively and significantly. Affected by flow level, mobility affects purchase intention negatively and significantly. It affects artistry and sociability positively and significantly. Summarized from B1 to B3, whether flow level is intervening variable or not, mobility, artistry and sociability affect purchase intention positively and significantly. Therefore this study concludes that albeit flow level does not hold significant mediating effect for mobility, artistry and sociability of game playability, it does increase purchase intention by indirectly increasing flow level.

Variance Analysis. This study categorizes survey subjects into four groups: (A) teenagers aged between 13 and 18, (B) youths aged between 19 and 30, (C) middle-aged aged between 31 and 44, (D) old-aged aged between 45 and 65. Each group is analyzed to check if each dimension holds significant difference with one-way ANOVA. Moreover, Scheffé Method is used to understand difference among each group. Analysis result (Table 2) shows that overall gaming motivation achieves level of significance (p=.004*); group A and B are more significant than group D. Game playability achieves level of significance (p=.000***); group A, B, and C are more significant than group D. Game mobility also re achieves aches level of significance (p=.000**); group B and C are more significant than group D. Therefore, younger groups (A, B & C) are more significant than group D in game motivation or game playability. This study concludes that players in group A, B, and C are grown up during matured digital gaming era. Overall participation motivation is high due to increasing number of mobile devices, as well as craze of mobile games, Their game perspective for mobile games is also more significant than group D, especially game mobility. This study concludes that younger groups (A, B & C) tend to accept mobile games that can be played anytime, anywhere. Old group (D) holds no significant difference in each dimension. This may be due to the sample size is fewer than younger groups’, and old group (D) may be new to video game and lack of gaming experience. Therefore there are significant difference of game motivation and game playability among younger and old groups (Table 6).

Table 6. Variance Analysis in this study
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5 Conclusion

As digital technology advances, smart mobile devices have become part of our life, and mobile games are now popular entertainments. This study discovers that albeit there is big sample size difference among groups, youth group aged between 19 and 30 contains the most players, and there are relatively fewer players with age over 45. However according to survey in 2014, players aged over 45 have already accounted for 14 % of all players; albeit this study only focus on mobile games on smart devices, players aged over 45 still accounts for 7 % of all players. This infers that number of players aged over 45 gradually increase. Past reviews [4] also denote that middle and old aged players prefer to buy virtual items to achieve objectives and self assurance and posses huge potentials for mobile game industry. It will be beneficial for companies if behaviors of middle and old aged players are studied in depth. Moreover, regression analysis results show that if companies increase competition and self-assurance of game motivation, as well as artistry and sociability of game playability, players will be in higher flow level and increase purchase intention of virtual items. They can share those topics with friends, and increase self assurance due to their game skills. On the contrary, increasing entertainment will decrease purchase intention, because some players only view mobile games as a recreation and do not pay for virtual items. In variance analysis, younger players have more significant difference than middle and old aged players. This is due to two reasons: the difference of sample sizes, and middle and old aged players may be lack of gaming experience. Finally, based on these data, companies can design games that attract players to increase purchase intention of virtual items, and increase market share for middle and old aged players. They may design campaigns for players of all ages to increase their desire to purchase virtual items, increase company profit, and please those players.

6 Future Work

Some areas in this study can be improved. Firstly, there is big difference in sampling size among each age group that cause incomplete analysis result. It’s recommended that future researchers should keep each group similarly sized. Also, number of video games can be shortlisted to increase accuracy of survey results.

Secondly, interviews are needed to understand middle and old aged players in depth. To design suitable interview questionnaire, results in this study can be utilized. Interviews should be based on motivation and playability, as well as flow theory that affects purchase intention of virtual items. Interviews can provide players’ first hand data that reflect their ideas. They are also helpful for mobile games companies to design contents that attract players to purchase virtual items; players can also enhance abilities in game by purchasing virtual items. Both companies and player acquire benefits from each other and achieve a win-win situation.