Counter-strike players' network gaming center preference

A new phenomenon that has been flooding the consumer industry these past years is the rising of network games specifically Counter-Strike. There is a need to study the factors affecting consumer decision-making from the perspective of the marketing application in order to relate to influential facto...

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Bibliographic Details
Main Authors: De Jesus, Maria Paula A., Rey, Karen A.
Format: text
Language:English
Published: Animo Repository 2002
Subjects:
Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/4174
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Institution: De La Salle University
Language: English
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Summary:A new phenomenon that has been flooding the consumer industry these past years is the rising of network games specifically Counter-Strike. There is a need to study the factors affecting consumer decision-making from the perspective of the marketing application in order to relate to influential factors in Network Gaming Center preference. A descriptive study was pursued to describe what constitutes consumers' decision-making in their patronizing behavior regarding purchase, use and disposal of products and services. Purposive sampling was done to obtain the respondents: 69 Counter-Strike players who were categorized according to frequency and duration of the purchase, use and disposal of Counter-Strike as a network game. The study employed survey questionnaire measuring the factors involving the consumption of Counter-Strike in a Network Gaming Center. The study focused on seven (7) specific influential factors: accessibility, crowd, design, mood, price. PC quality, and temperature. Raw scores were computed and quantitatively analyzed. Results show that Counter-Strike players are mostly externally influenced. The researchers also found out that the seven (7) influential factors could be hierarchically measured - PC quality, price, accessibility, crowd, mood, temperature, and design. Within the seven (7) influential factors and the other significant factors given by the Counter-Strike players, a typical Counter-Strike player was concluded. A new model was constructed to specifically and firmly anchor the results that the researchers have gathered.