Chapter II- Literature Review
3.3 Research Hypotheses
Base on the purpose of the study and the designed research framework, the following hypotheses are generated to be tested:
1). Test whether there are differences between gamers with different “demographic variables” and attractiveness of different game design elements:
Hypothesis 1-1 H0: Gamers with different “gender” and attractiveness of different game design elements have no significant relationship.
Hypothesis 1-1-6 H0: Gamers with different “gender” and attractiveness of game design element -“interaction” have no significant relationship.
Hypothesis 1-1-5 H0: Gamers with different “gender” and attractiveness of game design element -“control” have no significant relationship.
Hypothesis 1-1-4 H0: Gamers with different “gender” and attractiveness of game design element -“character settings” have no significant relationship.
Hypothesis 1-1-2 H0: Gamers with different “gender” and attractiveness of game design element -“ visual presentation” have no significant relationship.
Hypothesis 1-1-3 H0: Gamers with different “gender” and attractiveness of game design element -“sound & music” have no significant relationship.
Hypothesis 1-1-1 H0: Gamers with different “gender” and attractiveness of game design element -“story” have no significant relationship.
Hypothesis 1-2 H0: Gamers with different “age” and attractiveness of different game design elements have no significant relationship.
Hypothesis 1-3 H0: Gamers with different “monthly income” and attractiveness of different game design elements have no significant relationship.
Hypothesis 1-2-6 H0: Gamers with different “age” and attractiveness of game design element -“interaction” have no significant relationship.
Hypothesis 1-3-1 H0: Gamers with different “monthly income” and attractiveness of game design element -“story” have no significant relationship.
Hypothesis 1-3-2 H0: Gamers with different “monthly income” and attractiveness of game design element -“visual presentation” have no significant relationship.
Hypothesis 1-3-3 H0: Gamers with different “monthly income” and attractiveness of game design element -“sound & music” have no significant relationship.
Hypothesis 1-3-4 H0: Gamers with different “monthly income” and attractiveness of game design element -“character settings” have no significant relationship.
Hypothesis 1-3-5 H0: Gamers with different “monthly income” and attractiveness of game design element -“control” have no significant relationship.
Hypothesis 1-3-6 H0: Gamers with different “monthly income” and attractiveness of game design element -“interaction” have no significant relationship.
Hypothesis 1-2-2 H0: Gamers with different “age” and attractiveness of game design element -“visual presentation” have no significant relationship.
Hypothesis 1-2-3 H0: Gamers with different “age” and attractiveness of game design element -“sound & music” have no significant relationship.
Hypothesis 1-2-4 H0: Gamers with different “age” and attractiveness of game design element -“character settings” have no significant relationship.
Hypothesis 1-2-5 H0: Gamers with different “age” and attractiveness of game design element -“control” have no significant relationship.
Hypothesis 1-2-1 H0: Gamers with different “age” and attractiveness of game design element -“story” have no significant relationship.
2). Test whether there are differences between gamers with different “demographic variables” and gamer satisfaction towards the game:
Hypothesis 2 H0: Gamers with different “demographic variables” and the gamer satisfaction towards the game have no significant relationship.
3). Test whether there are differences between gamers with different “demographic variables” and the gamer loyalty:
Hypothesis 3 H0: Gamers with different “demographic variables” and gamer loyalty towards the game have no significant relationship.
Hypothesis 2-2 H0: Gamers with different “age” and the gamer satisfaction towards the game have no significant relationship.
Hypothesis 2-3 H0: Gamers with different “monthly income” and the gamer satisfaction towards the game have no significant relationship.
Hypothesis 3-1 H0: Gamers with different “gender” and gamer loyalty towards the game have no significant relationship.
Hypothesis 3-2 H0: Gamers with different “age” and gamer loyalty towards the game have no significant relationship.
Hypothesis 3-3 H0: Gamers with different “monthly income” and gamer loyalty towards the game have no significant relationship.
Hypothesis 2-1 H0: Gamers with different “gender” and the gamer satisfaction towards the game have no significant relationship.
4). Test whether there are differences between attractiveness of different game design elements and gamer satisfaction towards the game:
Hypothesis 4 H0: Attractiveness of different game design elements and gamer satisfaction towards the game have no significant relationship.
Hypothesis 4-4 H0: Attractiveness of game design element - “character settings” and gamer satisfaction towards the game have no significant relationship.
Hypothesis 4-5 H0: Attractiveness of game design element - “control” and gamer satisfaction towards the game have no significant relationship.
Hypothesis 4-6 H0: Attractiveness of game design element - “interaction” and gamer satisfaction towards the game have no significant relationship.
Hypothesis 4-3 H0: Attractiveness of game design element - “sound & music” and gamer satisfaction towards the game have no significant relationship.
Hypothesis 4-2 H0: Attractiveness of game design element - “visual presentation” and gamer satisfaction towards the game have no significant relationship.
Hypothesis 4-1 H0: Attractiveness of game design element - “story” and gamer satisfaction towards the game have no significant relationship.
5). Test whether there are differences between gamer satisfaction and gamer loyalty towards the game:
Hypothesis 5 H0: Gamer satisfaction towards the game and gamer loyalty has no significant relationship.
3.4 Questionnaire Design
This study’s questionnaire design process includes two main stages:
1. Pre-test
The initial design and pre-testing of the questionnaire is developed first to test whether the wordings and contents are understandable and clear for the subjects.
Through 50 online gamers as the pre-test subjects, their opinions and suggestions were taken into account; and after making several adjustments, the final official questionnaire is developed.
2. Official Questionnaire
This questionnaire survey is divided into four main sections- perceived quality on attractiveness of game design elements, gamer satisfaction, gamer loyalty, and demographic variables. Section one through three will be using Likert five point scale, from 1 “strongly disagree” to 5 “strongly agree” (Table 3-3, 3-4 & 3-5).
Section 1: Attractiveness of attractiveness of game design element variables:
Table 3-3 Questionnaire Attractiveness of Game Design Element Variables Variable Type Name of Variable Scales of
Measurement storyline that clearly explains the plot of the game.
2. The game offers a rich and intriguing story content.
3. The events in the game are consistent with one another.
4. The characters show development throughout the progress of the game.
5. The game is expandable with lots of side stories &
quests to accomplish.
Visual Presentation
1. The game delivers amazing style of visual arts.
2. The character module design in the game is unique and consistent.
3. The background design in the game is consistent.
4. The equipments (armors &
weapons) in the game have unique artistic designs that are visually appealing.
5. The actions and
expressions of the characters are designed with great detail.
Sound & Music
1. The background musics in the game make me feel comfortable.
2. The musics in the game are chosen appropriately to fit the style of the game.
3. The sound effects in the game allows me to enjoy the gaming atmosphere more.
4. The sound effects and the background musics sync smoothly with one another.
Character Setting
1. There are many job
classes/races to choose from in the game.
2. There are many techniques/
maigcs available to use in the game.
3. The sets of equipments (weapons and armors) each job class/race can wear are clearly different from one another.
4. The job classes/races are balanced in a way that no one class/race is superior to another.
Control
conveniently team up with other players for questing in the game.
2. The players can
conveniently communicate with other players in the game.
3. The players can
conveniently make in-game transactions with other players in the game.
4. I am meet new friends easily in the game.
Section 2: Overall gamer satisfaction & gamer loyalty.
Table 3-4 Questionnaire Customer Satisfaction & Loyalty Variables Variable Type Name of Variable Scales of
Measurement
1. Overall, playing this free-to-play MMORPG satisfies me.
2. I am satisfied by the overall quality of the game.
3. The contents of the game fit my needs for gaming.
Loyalty
1. I feel a strong sense of belonging towards the game.
2. I feel uneasy whenever I discontinue playing the game.
3. I will continue playing this game.
4. I will recommend my friends to join me in playing the game.
Section 3: Personal information (demographic data)
Table 3-5 Questionnaire Demographic Variables Variable Type Name of Variable Scales of
Measurement
Questionnaire Content
Moderating Variable
Gender Nominal Scale 1. Male
2. Female
Age Ordinal Scale
1. Below 16 2. 17 ~ 23 3. 24 ~ 30 4. 31 ~ 37 5. 38 ~ 44 6. Above 45
Monthly Income (in NT dollars)
Ordinal Scale
1. Less than $10,000 2. $10,001 ~ $20,000 3. $30,001 ~ $30,000 4. $30,001 ~ $40,000 5. $40,001 ~ $50,000 6. More than $50,001
3.5 Sampling Design
The sampling process of this study is based on the following steps:
1. Defining population
This study’s primary objects are online gamers, and the population of the study is then defined as the Taipei’s graduate students who have some experience in playing F2P MMORPGs. Since various studies provide very different findings on the age profile of the gamers, an estimation from the past studies will be used, and players ages 17~23 will be the core mass of players, while stretching the figure to approximately age 44 to cover about 90% of players (GameSpot Audience Profile Study, June 2008; IDC, 2008).
2. Confirming the sampling framework
The sampling framework uses members of Taipei’s various graduate students to participate in the questionnaire survey. The questionnaire surveys are sent out via email to the students currently participating in graduate studies and the link to the questionnaire survey (which is produced by an online survey maker- my3Q) is disclosed within the mails for the subjects to respond to the survey. Using this kind of sampling method means the samples are not completely randomly selected, which also means the representativeness of the sample might be biased. However, since the purpose of the research is to study the gamers’ behavior and how perceived attractiveness of game design element on part of the gamers will affect their game loyalty level, selecting the samples from those who have actually played online games is still appropriate (since they must have experienced it themselves to give more accurate opinions) and should have a above average level of representativeness.
3. Choosing the sampling method
Due to the size of the population, and also limited by time, human & financial resources, this study will use systematic sampling method. Since the questionnaire survey is done on partly on the internet and partly by face-to-face, part of the entered answers are automatically stored and filed, this automation process not only reduces the potential human errors, but can also reduce cost and time of the research. In addition, by performing a portion of the survey online removes the need for excessive printing
hard copies of the questionnaires, which not only saves cost, but saves the environment at the same time.
4. Deciding on sample size
The decision on the sampling size is based on the principles Roscoe (1975) proposed:
1). A reasonable sampling size should be between 30 ~ 500 samples to be appropriate.
2). When samples are divided into sub-sample groups, each sub-sample groups need to have at least 30 samples.
3). In performing a multivariate study, number of samples need to be 10 times or more the size of research variables to be appropriate.
This study uses systematic sampling method to focus the study group to those who have actually played a F2P MMORPG before, and then uses random sampling ratio technique to estimate the minimum sample size for the study. This method randomly selects n samples from the N parent population. The chance of occurrence of error which the variance between ratio of the sample with a particular characteristic and the parent ratio p cannot be over an acceptable error limit d must not be smaller than 1 - α.
And this can be represented by the equation as follows:
pˆ
pˆ p d
1
P ··········· (1)
Where: = sampling ratio, p = parent population ratio, d = level of acceptance of error, and 1 - α = degree of reliability.
pˆ
Then the size of the sample is big enough, the allocation of p can use normal distribution to come close to the actual value. Thus, using the above equation (1), we can get the minimum sample size, as shown in the following equation:
Where: n = sample size, N = parent population
When the parent population is very large, (2) can be simplified as:
)
Since p is unknown, the p(1- p) in the above equation acts as an increasing function, and since 0 therefore getting the maximum value of p(1- p) of ¼. Hence our equation will now look like this:
As described above, with the level of acceptance of error is d = 0.05 and with level of significance of α = 0.05 (95% level of confidence), our sample size n = 384.16.
Therefore, 385 will be the number of effective questionnaires retrieved for the samples to be representative.
5. Selecting sampling units
The questionnaire utilizes the online survey maker my3Q as the basis to produce the questionnaire survey. With a time frame of three weeks (from August 20th to September 10th of 2009 to distribute the surveys by means of e-mailing and link posting to various graduate students who have at least some experience in playing F2P MMORPGs in Taipei with help of classmates and friends. Also from September 15th to 30th of 2009, hard copies of the questionnaire survey were handed out to students.
6. Collecting Sample data
Since part of the survey questionnaire will be completed by the participants online via e-mails and links provided to the my3Q website, the sample data collection process is simplified since the input data are already stored on the website automatically as soon as they complete them
7. Assessing the sampling result:
The number of questionnaires retrieved is 406 copies. After the initial selection process, 12 copies are deemed to be invalid or incomplete, making the total number of valid questionnaires to 394 copies. The following provides an insight on the statistical distribution of the collected samples.
Gender
Frequency Percent Valid Percent
Cumulative Percent
Male 299 75.9 75.9 75.9
Female 95 24.1 24.1 100.0
Valid
Total 394 100.0 100.0
Age
Frequency Percent Valid Percent
Cumulative Percent
17~23 211 53.6 53.6 53.6
24~30 150 38.1 38.1 91.6
31~37 26 6.6 6.6 98.2
38~44 5 1.3 1.3 99.5
Above 45 2 .5 .5 100.0
Valid
Total 394 100.0 100.0
Monthly Income ($NT)
Frequency Percent Valid Percent
Cumulative Percent
Less than $10,000 283 71.8 71.8 71.8
$10,001~$20,000 96 24.4 24.4 96.2
$20,001~$30,000 13 3.3 3.3 99.5
$30,001~$40,000 2 .5 .5 100.0
Valid
Total 394 100.0 100.0
3.6 Data Processing and Analysis Method
The study uses SPSS17.0 statistical software as the study analysis tool- it is used to store coded data, perform statistical analysis, and produce statistical results.
The analysis framework of the study is shown below:
Gamer Loyalty Gamer Satisfaction Attractiveness of Game Design Elements:
1. Story
2. Visual Presentation 3. Sound & Music 4. Character Settings 5. Control
6. Interaction
Demographic Variables
Regression Analysis Factor Analysis
t-test ANOVA t-test ANOVA
Regression Analysis t-test ANOVA
Figure 3-2 Data Analysis Framework
The study’s data collection method includes both by means of retrieval of information from my3Q website where the online respondents filled out the survey and by the casual human collection method to collect the hard copy surveys. Therefore, in processing the data, there are two steps to be taken care of- human editing and computer processing:
Here are the descriptions of the statistical methods used in this study:
(1). Descriptive Statistics:
Using descriptive statistics to interpret the collected sample data can give a certain level of understanding towards research subjects’ sampling structure and basic characteristics. The demographic variables include: gender, age, and average monthly income (in NTD).
(2). Factor Analysis:
Used to produce and simplify the variables from the initial number of variables, and to explain the biggest variances in the initial data. This study uses the analysis on variables of design elements, and extracts the more important elements, at the same time, drops the less important ones to shrink down the number of variable dimensions.
Another use for this analysis is that not only it can shrink down the number of variables to conduct the research, but also that new variables can be generated from the old ones.
(3). One-way ANOVA Analysis:
This is used to test whether the single factors under different groups have significant relationship in their means. This research uses ANOVA to examine whether there are significant relationship between different demographic variables towards attractiveness of game design elements, gamer satisfaction, and gamer loyalty.
(4). Tukey’s HSD Test:
The Tucky’s Honestly Significant relationship (HSD) test is a post event analysis, single-step multiple comparison procedure used to find which means are significantly different (at α = 0.05 significance level) from one another. When significant is achieved during ANOVA test, the Tukey HSD post event analysis is used to compare the significance level between the means of different groups.
(5). Regression Analysis:
The regression analysis can be used to analyze one or more dependent and independent variables and their relationships. This study uses regression analysis to
analyze the influence the attractiveness of game design element dimension has on customer satisfaction.
(6). Cronbach α Coefficient:
Mainly to test the reliability of this study- testing if the attractiveness of game design elements’ different dimensions are consistent internally. The higher the number, it means the items’ relatedness are higher, meaning higher consistency, which translates to higher reliability.
3.7 Reliability and Validity Analysis
This section will provide a description on the reliability and the validity towards the study’s content.
3.7.1 Reliability
Reliability is the credibility of the measurement tools; accuracy and precision will be taken into account, which implies for stability and consistency considerations.
1. Stability: The reliability relating to stability consists of two main types: the test-retest reliability and the alternate form reliability. The former means in different times, measurements are repeated on the same group of samples, and the two results are compared to get the correlation coefficient. The latter means if a testing tool has two alternate forms, based on the score gained by the same group of objects, the correlation coefficient is calculated to get the alternate form reliability.
2. Consistency: In measuring attitudes, if certain item is used to measure the same attitude, then the items should be consistent among one another, meaning there is internal homogeneity. There are three types of measurements measuring consistency- split-half reliability, Kuder-Richardson reliability, and score reliability.
Most researches uses the Cronbach’s alpha coefficient as the consistency measurement of internal items of questionnaires, and this study will also use this method to test the extent of consistency of the answers on the questionnaires. According to Roberts and Wortzel, the alpha coefficient between 0.7 and 0.98 reflects high reliability.
And if it is less than 0.35, then the researcher should give up on the variable(s) and look for other variable(s) to use.
3.7.2 Validity
Validity means the extent of correctness of the variables. It refers to the extent that the tests or other measurement instruments are capable of measuring characteristics or functions that the researchers want to measure. Achieving a high score on validity means the results of the tests show more real characteristics in the variables the examiner is trying to measure. Validity coefficients of intrinsic validity are just the square root of the reliability coefficient. The American Psychological Association (APA) published a book titled “The Standards for Educational and Psychological Testing”
in 1974 which generalized the testing of validity into the following three types:
1. Content Validity: Checking the operationalization against the relevant content domain for the construct. It can test the appropriateness of content validity by according to a set of processes of a measurement tool.
2. Criterion-Related Validity: Checking the performance of the operationalization against some criterion.
3. Construct Validity: Testing the level validity of some theoretical concept or trait, normally based on some concept as basis of building a constructed correlation.
The level of accuracy is then based on the accuracy of the theory itself.
The variables examined in the study are based mainly from scholars with tested theoretical concepts, and the construction and presentation of the questionnaire survey is assisted by advising professor, students, and various papers, theses, and journal articles on the subject matter. Thus, the goal is to enhance the level of
The variables examined in the study are based mainly from scholars with tested theoretical concepts, and the construction and presentation of the questionnaire survey is assisted by advising professor, students, and various papers, theses, and journal articles on the subject matter. Thus, the goal is to enhance the level of