Introduction survey and how these appear to be influencing

Introduction

 

 

The
research article “An Investigation of the Diffusion of Online Games in Taiwan:
An Application of Roger’s Diffusion of Innovation Theory” investigates the
diffusion of online games in Taiwan based on Roger Diffusion of Innovation
Theory.

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For
the purpose of the assignment, one had to use the knowledge about diffusion of
innovations as well as the given information in the research text to address
four different issues. First, the methodological approach, the main findings,
the characteristics of the participants and how these characteristics influence
innovative behavior. Second, the significance of the usage of Rogers’ DOI model
to examine the diffusion of online games in Taiwan and a critical analysis of
the theory.

Third,
the effect of demographic and socio-economic factors of the participators and
how these have influenced the outcome and the application of the study. Also how
these biases can be solved. Last, the creation and conduction of a future
research study, regarding the attributes which influence the diffusion of an
innovation.

 

 

 

 

 

 

(a)  Start
by providing a synthesis of the methodological approach used in the research
article and the main findings. Include in your overview of the findings, a description
of the characteristics of the participants in the research survey and how these
appear to be influencing innovative behavior.

 

Methodology is defined
as the structure of methods and principles for carrying out research (Collins Dictionary,
2018). It is important so readers know how the data is gathered, to show the
reliability of the study and that certain methods were chosen right and to
demonstrate that the methods fit with the aims of the research study (Research
Guide, 2018).

 

The
methodological approach starts with a literature review regarding the history
of online games, a status quo of online games research and the explanation of different
models of the diffusion of innovation theory (Cheng, Kao & Lin, 2004). After
the literature review, the authors planned and conducted the survey. They
started with designing and pre-testing of the questionnaire followed by
sampling and the data collection. For the data analysis the statistics program
SPSS was used. By the usage of the cluster analysis, the present diffusion
stages of online games and the participators adoption behaviors in terms of online
games and general products were investigated.

 

The
survey includes answers of Taiwanese residents between the age of 13-50,
younger or older people were excluded for assumption of the lack of maturity or
the lack of knowledge about online games. (Cheng, Kao & Lin, 2004). A
university background is the most stated educational degree (46.6%) followed by
a senior high school/ junior college degree. Furthermore, the largest group of
participants’ occupation is “student” (38.6%). More than half of the
participants are female, although the majority of online gamers are male. The
characteristics of the participants influence their innovative behavior. Moreover,
students could be more innovative because of their educational degree, in fact
Kimberly and Evanisko (1981) stated that a higher educational degree of an
individual results in a more open behavior towards innovation.

 

 The authors of the research article found out,
that Rogers’ diffusion of innovation theory in principle can be utilized to
explain the personalities of online gamers. In fact, the results imply that the
diffusion of online games in Taiwan reached a level of 38.6%. Concerning Rogers
graph of the diffusion of the innovation, currently the diffusion reached the
early majority stage.

 

Moreover, the findings show that
online game innovators hold the latest games information, obtain knowledge of
newest trends, purchase the latest games versions even without knowledge about
them, are the earliest gamers and play more types of games more often than the
other groups. The analysis of the participators’ characteristics and behaviors
also follow Roger’s theory about communication behaviors (credit, social
travel, business travel, making friends) and the personality values (sympathy,
curiosity, abstract concepts, control of future, education, new technology,
effective methods). In both categories the innovators obtain higher scores
compared to the early adopters and early majority. For this reason, online game
innovators value credit more, travel more and prefer “making friends” more than
the early adopters and the early majority. Online game innovators have more
sympathy, curiosity, can handle abstract concepts, better control their future,
place more value in education, adopt new technologies easier and use effective
methods to complete a job more often.

 

The
findings of the socioeconomic statuses are contrary with Roger’s diffusion of innovations
theory. Hence, young people with lower disposable income and a lower degree of
education are forming the group of the online game innovators. In addition, the study shows that the
group of innovators reached the highest percentages regarding information
sources (internal and external) as well as information spreading. They are
followed by the early adopters and the early majority. Additionally, innovators
are more likely to be change agents or opinion leaders. The authors of the
journal article also concludes that there is no connection between
participators’ adoption behaviors towards online games and products in general.

 

 

(b)  Discuss
the significance of using Rogers’ model to investigate the diffusion of online
gaming in Taiwan. Your answer should include a critical analysis of Rogers’
diffusion of innovation theory.

 

Rogers’ diffusion
of innovation theory can be applied successfully in various fields and gained a
lot of attention (Cheng,
Kao & Lin, 2004). The framework is extensively used to describe the
adoption and diffusion of an innovation (Sahin, 2006). Moreover, it has been
enhanced by Rogers’ and his team since the invention in 1962 until 2003 and can
be used at macro and micro level as well as for tangible and intangible
innovations (Dibra, 2015). It was used as a theoretical framework in more than
5000 studies in different fields, so one can say it’s a reliable theory (Dibra,
2015).

 

The diffusion of the innovation is defined as ‘the process by which an
innovation is communicated through certain channels over time among the members
of a social system’ (Rogers, E. M., 1983). The consequence would be the
adoption of a new technology, idea, behaviour or product by people in a social
system (LaMorte, 2016). Moreover, it implies that a person does something
different than before, which occurs as a process rather than a one-time action (LaMorte,
2016). Rogers identifies the five different groups of adopters as innovators, early
adopters, early majority, late majority and laggards from which some are more
likely to adopt a behaviour than others (Rogers, E. M., 1983). Innovators are
venturesome and eager to try new ideas, early adopter are receptive to new
ideas and already know that change is necessary (Rogers, E. M., 1983). The early
majority requires evidence to adopt a new idea or innovation, the late majority
is more sceptical and in need of a confirmation of the usefulness of an
innovation by the majority of the population (Rogers, E. M., 1983). Laggards are
even more sceptical than the late majority, they are very traditional and hard
to convince (Rogers, E. M., 1983). These groups show different characteristics
when it comes to the adoption of an innovation (Rogers, E. M., 1983). If one
wants to support an innovation, it is important to know the characteristics of
the target population (LaMorte, 2016). Addressing the right people at the
current stage of adoption, promotes the diffusion of an innovation (Rogers, E.

M., 1983).

 

 If one applies this definition to the research
article, there are clear overlaps. The innovation of the online games in
Taiwan, is communicated through different channels (i.e. direct communication
through travels), over time among Taiwanese residents. As Cheng, Kao and Lin
(2004) mention in their article, it can portray organisations and individuals. Hence,
it’s suitable to investigate the diffusion of online gaming of Taiwanese
residents individually and as a group. Furthermore, the authors conclude that
Rogers’ theory generally can be used on the prediction of personalities of
online gamers in Taiwan.

 

Although the
results of the research article show that the theory can be applied to describe
the diffusion of online games, there emerged some criticism to the usage of
Rogers’ theory in the literature. For example, a persons’ resources or the
social support to adopt an innovation are not reflected in Rogers’ DOI (Diffusion
of Innovations) model or in the research article. Additionally, questions about
the completeness of the list of attributes and the applicability for all technological
innovations arose (Lyyinen & Damsgaard, 2001). The authors Lyyinen and
Damsgaard questioned if all technological innovations can be measured by the
same attributes. It could be helpful to add various attributes for different
fields of study.  Moreover, the data
reflects that in this case the innovation of electronic data interchange (EDI)
was not spread through mass media or peer networks, like mentioned in Rogers’
DOI theory, but through actors like the government (Lyyinen, Damsgaard, 2001).

 

The Diffusion of
Innovations is just a framework which has weaknesses and can’t be fully applied
to every field of research. For example, with some technological innovations
like the EDI, it’s difficult to differentiate between the different stages of
the theory (Lyyinen, Damsgaard, 2001).

 

To better understand the current adoption rate in the Taiwanese
population, it would be helpful to apply Rogers theory over several years to
see if and how changes in the adoption rate evolve.

 

 

 

(c)  
As part of the methodology, the
researchers collected 350 questionnaires from respondents aged between 13 and
50 years; most of these were students possessing a university degree. To what
extent do you consider that the demographics and socio-economic background of
the participants in the study might have affected the outcomes of the study and
their applicability to understand the diffusion of related innovations? How
would you overcome these biases if designing a study of your own?

 

The demographics and socio-economic factors of a population include age,
sex, education, income, marital status, occupation, religion, birth rate, death
rate, average size of a family, average age at marriage and other aspects (Business
Dictionary, 2018).

 

The participants
of the study are quite young, have a relatively high income, more than of half
of them possess a university or master degree, and almost 40% posed as
occupation ‘student’. As mentioned in the literature, these characteristics all
strongly support the innovativeness of the participants (Tellis, Yin and Bell,
2009). Tellis, Yin and Bell (2009) defined the ‘profile of a global innovator
across countries as one who is more likely to be wealthy, young, mobile,
educated, and male’, they found five demographic variables (age, income,
mobility, education and gender) which influence a person’s innovativeness.

 

In other words,
the questioned group of participants is more innovative and more likely to
adopt innovative products or services. These findings could implicate a more
positive status of the adoption rate of online games in Taiwan. If compared to
a representative selection of participants, the diffusion rate could be lower
than described in survey.

 

In addition, the adoption
rate would probably be much lower, if the study would include all ages. Despite
the balanced allocation of participants in the categories, the range of ages
only reaches 13-50 years. These range doesn’t represent the whole population in
Taiwan.

 

Sampling describes ‘the process of
selecting a representative group from the population under study'(McLeod,
2014). To overcome these biases in one’s own study, it could be better to
include all ages, to have a more realistic view of the diffusion of online
games. It would improve the quality of a new study, if a representative
selection of the population in Taiwan would be questioned. The distribution of
factors like age, income, education and occupation play an important role towards
the results of a survey. Thus, the sampling of a future study is important.

 

 

 

 

·      
 

 

(d)  The
article suggests that further research could focus on the perceived attributes
of online games and how these might influence diffusion. Explain how you would
take these suggestions further in a research study of your own.

 

First of all,
it’s important to have a clear structure, if one wants to carry out a research
study. The University of Southern California suggests a structure divided in
the parts introduction, background and significance, literature review,
research design and methods, preliminary suppositions and implications and
conclusion and citations (Research Guide, 2018). The structure of a future
research study would be built on these points.

           

Rogers DOI theory
includes five characteristics which specify how the consumer reacts to an
innovation (Roger, E. M., 1983). The characteristics consist of the relative
advantage, compatibility, complexity, trialability and observability (Roger, E.

M., 1983). The relative advantage is the perceived improvement from one
innovation to the other it’s replacing (Roger, E. M., 1983). Compatibility
describes the extent to which an innovation is perceived as fitting with
existing values, past experiences and needs of possible adopters (Roger, E. M.,
1983). Trialability explains in what way an innovation can be tested (Roger, E.

M., 1983). Observability describes how far the results of an innovation are
visible to others (Roger, E. M., 1983). These attributes of an innovation allow
one to determine the current and the future adoption of an innovation and how
adopters respond to it (Roger, E. M., 1983).

 

Further research should investigate how gamers perceive the
innovativeness of online games as a modern entertainment device regarding the
attributes of innovativeness. The future study should include an experiment and
questionnaire with questions about the perception of these five attributes.

Different types of gamers (regarding the time they play per week) should be
questioned to have a variety of opinions. Each gamer should play the game for a
set amount of time and rate it afterwards. For rating the attributes, one could
use a Likert scale. After rating the attributes of each game, the different
games can be compared in terms of the influence towards diffusion and
innovativeness. Therefore, it could be possible to find attributes which have a
stronger impact on the innovativeness of online games than others. Regarding
the attributes, the results could indicate which attributes an online game
should have to speed up the diffusion.

 

 

Conclusion

           

           

The assignment discusses
the survey and analysis as methodological
approach. Furthermore, the main findings of the current status of the diffusion
of online games in the Taiwanese population. The characteristics including the educational
level might have influenced the innovativeness of the participants and their willingness
to adopt the innovation. A better sampling method could prevent an impact on
the results in a future study. The author of this assignment concludes that
Rogers’ DOI Theory is appropriate to describe the diffusion of online games in
Taiwan. Additionally, criticism of the usage of Rogers’ Diffusion of Innovation
Theory to investigate the current status of the diffusion of online games is
mentioned. At the end, a research study based on the attributes of an
innovation is planned to investigate more on the influence of the diffusion of online
games. 

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