Factors influencing Attitude and Intension of Playing Online Computer Games: A Study of Thai Online Computer Gamers. Ake Choonhachatrachai Key words: Online Game, Consumer Behavior, Thailand, Game Industry Abstract Today, the online computer games have become one of the most popular leisure among teenagers. The online computer game industry has developed continuously and consistently in term of technology and marketing campaign. As such issues have been frequently raised in the society, some other particular issue such as social problem affected by playing online computer games still lacking. This study attempts to find out the attitude of teenagers toward playing online computer games. The theoretical model used in this study is Technology Acceptance Model (TAM). The research participants which are Thai teenagers were examined in order to find out their attitude toward the online computer games by basing on the factors like perceived usefulness, perceived enjoyment, and perceived ease of use. This study used quantitative method and deploys non-probability technique. The structure questionnaire was used as an instrument to gather the data. This study also identified the sampling frame by scoping down to undergraduate students in Bangkok (ages 1825). As this target respondents usually spends time playing online game at the internet café. Thus, the survey will be conducted on them by using convenience sample of 1825 year old undergraduate students who come to play online computer games at the internet café in Bangkok. This study examines factors adopted from Technology Acceptance Model (TAM) and the factors from conducting an exploratory study. This study gathering all of the factors together to see how they influence on the attitude and intension of online computer games players. Combining Technology Acceptance Model (TAM) with six additional variables, this study has provided both theoretical and managerial contribution. Global Markets (1999) estimated that the online user penetration rate has grown up to 39 per cent in non-US (worldwide) sector versus only 21 per cent in US online user. However, study about online usage still mostly done on American people context. Consequently, it is worthwhile for researchers to pay more attention to online consumers in Asia-Pacific countries e.g. Thailand where online games market continues to grow as local game providers have coordinated with Korean online game markets to provide new online games in Thailand such as the first major hit online game of Ragnarok Online (2002) gained 2.36 million subscribers worldwide (700,000 in Thailand), followed by MU Online (2003) that expect to attract 50,000 subscribers in Thailand (Bangkok Post Data Base, 2003). This paper focused on consumer’s attitude and intention toward using or playing online computer games. Such specific technology context is different from other type of internet usage in several aspects. Firstly, the nature of the product itself which considerably unique in many characteristics. Unlike other products selling on internet, online computer games are intangible and having less value compare to other types of products. While regular online consumers are concerned about disclosing their private and financial information (Park and Kim, 2003), online computer games consumers do have less concern on such issue as they can make a purchase without using credit card by make a payment through cell phone or pre-paid card (www.pangya.com). Secondly, online computer games also require consumers to spend much more time with computer than other internet shopping. The more playing time customers purchased the more time consuming they will have to spend on computer. Some people spend so much time online that they have not left their homes in more than two years (Castronova, 2005). Moreover, online computer games also provide different benefits to the customers as they offer imaginary world that enable people to act out their dreams (Jennings, 2006). So, it can be said that instead of serving consumer who have less leisure for store shopping, online computer games are serving those who want to spend their leisure on the computer screen. Result from this, the past researches that tried to explore the factors influencing the attitude of online users can be somewhat differ from the factors influencing the attitude of online computer games users. Moreover, researches involving online computer games to date focused mainly on one game only or asks subjects to respond based on viewing a particular game provided (Elliot and Fowell, 2000; Fogarty, 2000; Lohse and Spiller, 1998; Jarvenpaa and Todd, 1996-1997). Academically, this paper will be expected to contribute a new knowledge about consumer attitude toward the unique online product like online computer games and theoretically, this study applies modified TAM model by adding six more correlates variables namely appearance quality, game play, compatibility, trialability, self efficacy, and socialization agents to better suit with particular tested product. In managerial contribution, it will help e-tailers to develop effective strategies for online computer game products. The information from the finding will also help marketing managers to understand customer better and to effectively plan their marketing mixes. Literature review There are three theories that often used by researchers in studying the behavioral intention in technological products namely Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and the Diffusion of Innovation Theory. Most of these theories have been developed from the Theory of Reasoned Action originally proposed by Fishbein and Ajzen (1975). For the theory of planned behavior (TPB) (Azjen, 1985, 1991) is an extension of the theory of reasoned action (TRA) (Azjen and Fishbein, 1980), made necessary by the latter model’s inability to deal with behaviors over which individuals have incomplete volitional control. At the heart of TPB, and TRA, is the individual’s intention to perform a given behavior. For TRA and TPB, attitude toward the target behavior and subjective norms about engaging in the behavior are thought to influence intention, but TPB includes perceived behavior control engaging in the behavior as an additional factor influencing intention. According to TPB, an individual’s performance of a certain behavior is determined by his or her intent to perform that behavior. Another relevant theory of this study is diffusion of innovation theory. DOI theory sees innovations as being communicated through certain channels over time and within a particular social system (Rogers, 1995). Individuals are seen as processing different degrees of willingness to adopt innovations and thus it is generally observed that the portion of the population adopting an innovation is approximately normally distribution into segments leads to the segregation of individuals into the following five categories of individual innovativeness (from earliest to latest adopters): innovators, early adopters, early majority, late majority laggards (Rogers, 1995). The rate of adoption of innovations is impacted by five factors: relative advantage, compatibility, triability, observability, and complexity (Rogers, 1995). Anyway, this study will develop its constructs influencing attitude of online games purchasers by choosing Technology Acceptance Model (TAM) as model base. The reasons why TAM has been chosen as a model base for this study are TAM has been specially built for applications that deal with adoption of information technology and it is also easy to implement with less complications (Mathieson 1991; Davis, Bagozzi & Warshaw, 1989). The measurement scales used in TAM of perceived ease of use and perceived usefulness have also repeatedly been proven to have both high reliability and validity (Adam, Nelson & Todd, 1992). In addition, TAM was found to be the most popular theory used by most researchers for studying the behavioral intention to use technological products and services (Venkatesh & Davis, 2000). As a result, the Technology Acceptance Model (TAM) then is selected as a model used in this research and since this study will investigate the factors influencing online game player’s attitude and online game player’s intention toward online computer games, the conceptual framework from Technology Acceptance Model (TAM) will be applied (Figure 1). Figure 1: Technology Acceptance Model (TAM) Perceived Usefulness (U) Attitude toward Using (A) External Variables Perceived Ease of use (E) Behavioral Intention to use (BI) Actual System Use Source: Developed from Davis, Bagozzi & Warshaw (1989). However, with two variables provided in TAM, this study found from the literature review that there still several other external variable that seem to be interesting and useful for the product like online computer games. Result from this, the exploratory study has been conducted on college student age 18-25 that have experience playing online computer games for at least 50 hours. This believed to strengthen the sources of information found in the literature review. Along with perceived usefulness and perceived ease of use that come with TAM, literature review and exploratory study has provided six more variables in which combined to be eight variables as follow: - Perceived usefulness (PU): "The degree to which a person believes that using a particular system would enhance his or her job performance". (Davis, 1989) - Perceived ease-of-use (PEOU): "The degree to which a person believes that using a particular system would be free from effort". (Davis, 1989). - Appearance quality: Refer to attractiveness, organization, proper use of fonts, proper use of colours, and proper use of multimedia. (Aladwani, 2006) - Game play: A term most commonly used to rate, or score the quality of the experience had by gamer while playing a game. The term game play is often found in game reviews where a score is given based on player experiences during the interaction with game. (www.webopedia.com) - Trialability: The ability to sample the product without a major commitment. (Holak and Lehmann, 1990) - Internet self efficacy: The belief in one’s capabilities to organize and execute courses of internet actions required to produce given attainments. (Hsu, et al, 2004) - Compatibility: The ability of the consumer to use it in a way consistent with past behaviour. (Rogers, 1983) - Socialization agent: person or an organization that provides influence through frequent interaction with an individual, primacy over the individual, or control over rewards and punishments given to the individual (Brim, 1966) The above variables were used to test the attitude and intension of playing online computer games. The expectation of this modified TAM is to help understand the online computer gamers better. As it expected to contribute both theoretical and managerial implication, this study has hypothesized that attitude and intension toward online computer games can be influenced by all of the above factors as follow: Hypotheses H1. An online game player’s perceived usefulness has a positive impact on his/her attitude toward online computer games. H2. An online game player’s perceived ease of use has a positive impact on his/her attitude toward online computer games. H3. An online game player’s perceived ease of use has a positive impact on his/her perceived usefulness. H4. An online game player’s perceived usefulness has a positive impact on his/her intension to play online computer games. H5. An online game player’s attitude has a positive impact on his/her intension to play online computer games. H6. The appearance quality of online computer game has a positive impact on online game player’s attitude toward online computer games. H7. The appearance quality of online computer game has a positive impact on online game player’s intension to play online computer games. H8. An online game player’s perception of game play has positive impact on his/her attitude toward online computer games. H9. An online game player’s perception of game play has positive impact on his/her intension to play online computer games. H10. An online game player’s perception of compatibility has positive impact on his/her perceived usefulness. H11. An online game player’s perception of compatibility has positive impact on his/her attitude toward online computer games. H12. An online game player’s perception of compatibility has positive impact on his/her intension to play online computer games. H13. An online game player’s perception of trialability has positive impact on his/her attitude toward online computer games. H14. An online game player’s perception of trialability has positive impact on his/her intension to play online computer games. H15. An online game player’s internet self efficacy has positive impact on his/her attitude toward online computer games. H16. An online game player’s internet self efficacy has positive impact on his/her intension to play online computer games. H17. The socialization agent (peers) has positive impact on online game player’s attitude toward online computer games. H18. The socialization agent (peers) has positive impact on online game player’s intension to play online computer games. Method and methodology This study uses quantitative techniques. The research design of this study consisted of six stages which are exploratory research, research instrument construction, testing the research instruments, selection of participants and data collection methods, data editing and data analysis. The explanation of each stage is as follows: Stage 1 The Exploratory Research: This study has used the exploratory research as the first stage of the research process. By using the exploratory research, this study expects to better the understanding of online computer game player’s perception. Exploratory research is normally used as the first stage of a research process. It is conducted to identify and clarify problems (Zikmund, 1997). Zikmund (2003) also claimed that exploratory research can help researchers reach a better understanding of the extent of the research problem. Similarly, Sekaran (2000) stated that the exploratory study is conducted to clarify the nature of the research problems. The main objective of the exploratory research is to narrow the scope of the study and to discover the research problems in order to specify research objectives (Churchill and Iacobucci, 2002). However, the exploratory research does have some limitation as Zikmund (1997) stated that it cannot provide quantitative measurements, the interpretation is based on a research’s judgment and the sample is not representative of the population. Hence, the exploratory research was used as an initial stage for this study. Zikmund (1997) classified techniques for gaining clearer ideas of research problems into four basic categories: experience surveys, secondary data analysis, case study method and pilot study. Anyway, according to the appropriateness of this study, the exploratory research has adopted two techniques which are secondary data analysis and experience surveys. Stage 2 Research Instruments Construction: This research adopts the sample survey method. The data were gathered through a structured questionnaire using closed-end questions style including variables based on prior literature and exploratory work. The questions listed in the questionnaire were listed below: No. Questions Variables Sources (Authors) 1 Playing on-line computer games Attitude Cheong, J.H., and Park, give me good feeling. 2 I find playing on-line computer games give me new ideas and M.C. (2005) Attitude experiences. 3 To me, playing on-line computer Attitude games is not a waste of time. 4 5 The likelihood of my online Intension to computer games playing is high. play Something inside pushes me to Intension to go and play online computer play games. 6 7 Instead of going out shopping or Perceived Pikkarainen,T., partying, playing an online usefulness Pikkarainen, K.., computer games give me a better Karjaluoto, H., and use of time. Pahnila, S. (2004) I think that playing an online Perceived computer games is helpful to usefulness improve my computer skill in general. 8 I think that playing an online Perceived computer games help me explore usefulness to the modern technology. 9 10 I think that playing an online Perceived computer games is costly. usefulness I think that playing an online Perceived computer games give a sense of usefulness accomplishment. 11 I think that playing an online Perceived computer games is mentally usefulness challenging. 12 13 I think that playing an online Perceived computer game is addictive. usefulness I think access into online Perceived Cheong, J.H., and Park, computer games through internet ease of use M.C. (2005) is easy. 14 I think that learning to play online Perceived computer games through internet ease of use is easy to understand. 15 I think that the payment process Perceived of playing online computer games ease of use is easy. 16 I could explain the rules of how Perceived to play online computer games to ease of use a friend in a few minutes. 17 It is not necessarily easy to Perceived understand the rules of how to ease of use play online computer games. 18 Beautiful cartoon character in the Appearance online computer game’s website quality Aladwani, A.M. (2006) is important. 19 Beautiful background image of Appearance the online computer game’s quality website is important. 20 The use of proper color scheme in Appearance the online computer game’s quality website is important. 21 There is no time for yawning Gameplay when playing online computer Gagnon, K. (2007) games. 22 Most online computer games go Gameplay on and on. 23 Online computer games should be Gameplay difficult. 24 To play online computer games is D’Astous, A., and Gameplay like escaping from everything. 25 When I play online computer Gameplay games, I am totally focused. 26 Online computer games should be Gameplay easy. 27 When I play online computer Gameplay games, I feel that I am in another world. 28 When I play online computer Gameplay games, I may become so involved that I forgot everything. 29 Playing online computer games is Compatibility Park, Y, and Chen, J.V. compatible with all aspects of my (2007) regular computer use. 30 I think that playing online Compatibility computer games fits will with the way I like to spend time. 31 Before deciding on whether or Trialability not to play the online computer game, I would need to play it on a trail basis. 32 I would be permitted to play Trialability online computer games on a trail basis long enough to see what it can do. 33 I know where I can go to Trialability satisfactorily try out various features of online computer games. 34 I feel confident visiting a web site Internet self- Hsu, M.H., Chiu, C.M., by entering its address (URL) in and Ju, T.L. (2004) the browser. efficacy 35 I feel confident going backward Internet self and forward to previously visited efficacy web pages without being lost in the hyperspace (cyberspace). 36 37 38 39 40 I feel confident receiving e-mail Internet self messages. efficacy I feel confident sending e-mail Internet self messages. efficacy I feel confident downloading files Internet self and software. efficacy I feel confident installing an Internet self application or software. efficacy It bothers me when my friends do Socialization Dotson, M.J., and something I don’t know how to agent Hyatt, E.M. (2005) do. 41 42 43 It is important for me to fit in Socialization with my friends. agent I want to have the same activity Socialization as my friends. agent What my friends think is more Socialization important than what my parents agent think. The self administered questionnaires technique was selected as the data collection method. The strength of self administered questionnaires will help avoid or at least reduce the non-responses problem. A self administered questionnaire is employed to collect data since not only the researcher can collect all the completed responses within a short period of time, but any queries are answered immediately thereby reducing response errors (Cavana et al, 2001). Prior to the data collection method, 30 set of questionnaires has already been distributed to the sampling group as a pre-test process. Result from this, it expects to be able to assess the validity and refine the questionnaires. The questionnaires were distributed by the third party to the students on a convenience basis. All of the respondents have been given the outline of what the questionnaire is about and instruction on how to proceeds the questionnaire. Both outline and instruction will be presented to the respondents by both written and verbal explanation after three screening questions concerning age, educational background, and online computer game playing experience. Once the respondents complete the questionnaire, they will have to return it to the data collector. To have a sizeable sample size, a total of 400 questionnaires were distributed to potential respondents. The expected number of questionnaires return is 50%. Multiple-item scales are used to measure each component to enable testing for measurement error. All of the initial scales adopted were found to be reliable measures for their respective constructs as the Cronbach’s alphas exceed 0.80. (Please see appendix 7) All constructs are measured by interval scale in the form of a five points likert scale (1 = highly disagree to 7 = highly agree). Statistical Package of the Social Science (SPSS) will be used to in the part of data analysis. According to the research questions in this study that has already specify an explicit relationship between dependent variables namely online game player’s attitude and intension and independent variables namely perceived usefulness, perceived ease of use, appearance quality, game play, compatibility, trialability, internet self-efficacy and socialization agents (peers) as well as the purpose of the research questions that try to examine the simultaneous effects of independent variable on a dependent variable, this study has adopted the regression analysis to examine the influencing factors and adopt the correlation analysis to examine the relationship between two factors. Stage 3 Validity and Reliability of Research Instruments: In order to ensure the effectiveness of measures used in this study, the pre-test of research instruments was used to examine validity and reliability of each item in the questionnaire before conducting the real survey. The testing process is divided into two types which are the test of validity and the test of reliability. The Test of Validity After building the model, constructing research instruments and selecting the participants, it is necessary to assure that participants understand all of the questions in the research instrument. This is usually called the “validity” of the instrument (Nunnally, 1978). The Test of Reliability The reliability tests give information about consistency and stability through a series of research measure (Cronbach, 1965). Reliability can be tested in both quantitative and qualitative research (Cohen, Manion and Morrison, 2000). The reliability of measure refers to the extent that the measurement process is free from error (Garrett, 1966; Kinnear and Taylor, 1996). Reliability can be classified into two dimensions: stability and consistency (Sekaran, 2000). Stage 4 Selections of Participants and Data Collection Methods For the process of data collection, this study has used the sampling technique to recruit the participants. The terminology of “sampling” involves the process of choosing a small percentage of the whole population as its representatives (Zikmund, 1997). There are 2 main types of sampling techniques: First, probability technique and second, non-probability technique. For probability sampling all units in the population have the same chance of being chosen as part of the sample. For non-probability sampling the units do not have an equal chance of being chosen as part of the sample (Sekaran, 2000). This study deploys non-probability because there is no name list of Thai online gamer available. This study identified the sampling frame by scoping down to undergraduate students in Bangkok (ages 18-25). As this target respondents usually spends time playing online game at the internet café. Thus, the survey will be conducted on them by using convenience sample of 18-25 year old undergraduate students who come to play online computer games at the internet café in Bangkok. Carrier Market Development (2003) reported that there are 72 percent of people aged 15-19 play online games in the United States and 50 percent of people aged 15-24 play online games in Europe. In addition, the study by Gao (2004) pointed out that the appropriate sampling units that can be used as internet surfer population are those whose age is between 16-30. Thus, this target population considering as appropriate subjects for this research. However, to focus particularly on college students, it will also allow this study to be able to control the homogeneity of respondents’ attitude. Homogeneous respondents are desired for two reasons. First they permit more exact theoretical predictions than may be possible with a heterogeneous group (Cook and Campbell 1975). Secondly, heterogeneous respondents constitute a threat to statistical conclusion validity (Cook and Campbell 1975). The research participants will be approached in Bangkok because the research conducted by National Electric and Technology of Thailand (NETEC) in 2001 has shown that there are estimated about 3.5 million internet users in Thailand and 54 percent of internet user’s population is in Bangkok. Malhotra (1999) stated that determining the sample size is very complicated and involves several quantitative and qualitative considerations. These considerations include the importance of the decision, the nature of research, the number of variables, the nature of the analysis, sample size used in similar studies, incidence rates, completion rates and resource constraints (Malhotra, 1999). Quantitatively, a sample size of 200-500 persons is recommended to be sufficient for data analysis (Hair et al. 1998). The sample size in this study then set to be 400 undergraduate students aged between 18-25. Anyway, the possibility of getting back all 400 questionnaires from participants is not easy. Thus, this study has the expected number of returned questionnaires which is 50%. In this study, the questionnaires were distributed to the participants by the researcher’ assistants in front of the internet cafes nearby any university in Bangkok. The participants were approached right after they leave the internet café as this can assumedly indicate that they are the internet users. Anyway, to ensure that they are the right target participants, three screening questions concerning age, education background, and online game playing experience have also asked. Stage 5 Data Editing For the frequency procedure in this study, the Statistical Package for Social Sciences Windows version 10.0 (SPSS 10.0) was used to run all of the variables in order to ensure accuracy, consistency and reliability of the data during the data entry. Incomplete questionnaires were classified into two groups: the first group contained questionnaires in which more than twenty-five percent of variables were not completed (Sekaran, 2000). Questionnaires in this group were excluded from the data analysis. The second group included incomplete questionnaires in which the number of variables without response was less than twenty-five percent, these were identified as having missing values in the data entry for the SPSS programme (Kinnear and Taylor, 1996; Sekaran, 2000). Stage 6 Data Analysis As this study is quantitative research, both descriptive and inferential statistics were used to analyze the data collected from the questionnaire survey with the use of the Statistical Package for the Social Sciences, Window version 10.0 (SPSS 10.0). Survey Questionnaire Two major types of quantitative analysis techniques were chosen to analyze the data in this study which are Descriptive and Inferential Statistical Analysis. Descriptive statistics may be used to classify, review and explain the profile of all respondents (Cohen and Holiday, 1982). The use of descriptive statistics has found in many studies during the literature review stage of this study such as “Mobile internet acceptance in Korea” (Cheong and Park, 2005) and “Consumer acceptance of online banking: an extension of the technology acceptance model” (Pikkarainen et. al., 2004) . Moreover, the inferential statistical analysis has also been used in this study. Inferential statistics may be used to predict population parameters from respondents (sample) measures by using mathematical theories (Cohen and Holiday, 1982). To analyze data from a sample, choosing between parametric and non-parametric statistics must be considered. Parametric methods are the most commonly used techniques for testing hypotheses and can be used when exact population units are known (Cohen and Holiday, 1982). However, when it is difficult to make assumptions, when the population distribution is not normal, non-parametric methods are used to test hypotheses (Saengkaew, 2001). This may be called a “distribution free” process (Cohen and holiday, 1982) and is used when nominal or ordinal scales are used. For interval scales, they are converted to ordinal scales when non-parametric methods are applied (Saengkaew, 2001; Wechasarn, 2003). As the population that will be tested in this study expected to be not normal, therefore, non-parametric methods were initially considered to test the hypotheses of this study. Every questionnaire was distributed to the research participants by the third party, and all completed questionnaires have also been collected by the third party as well. Moreover, as this is an anonymous survey, no identification (names) of the participants is indicated in the report. The data will be aggregated and no specific reference to individual responses will be made. Before research participants will begin doing the questionnaire, a cover sheet for the survey questionnaire explaining the background and purpose of the research will be provided to them. This stage of the study is entirely voluntary so if research participants feel that the study was intrusive or they were reluctant to answer the questions, they could withdraw at any time of the process. The implication of the study Academically, this paper will be expected to contribute a new knowledge about consumer attitude toward the unique online product like online computer games and theoretically, this study applies modified TAM model by adding six more correlates variables namely appearance quality, game play, compatibility, trialability, self efficacy, and socialization agents to better suit with particular tested product. In managerial contribution, it will help e-tailers to develop effective strategies for online computer game products. The information from the finding will also help marketing managers to understand customer better and to effectively plan their marketing mixes. The limitation of the study Since, the behavior of consumer is changing overtime as well as product like online computer games which considered being in the category of technological advancement product. The existing study might not be valid when the time passed by. 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