探討線上網路遊戲網路沉浸及成癮與使用者行為之關係

Abstract

網際網路相關科技發展至今，已讓我們的生活產生許多變化，網際網路不再只是簡單的查詢紀錄工具，還用來當作是溝通學習的資訊媒介，也進行著各種不同的休閒娛樂活動，特別是網路線上遊戲。台灣線上遊戲的試場規模從2001年的 17.1 億元到2009年的 113 億，預估2010年的市場規模可望達126億元，十年間的市場規模已成長了七倍之多。本論文主要藉由網路成癮（Internet Addiction）與沉浸理論（Flow Theory)，從線上遊戲玩家出發，區隔出不同類型玩家，探究他們在在人口統計變數與使用行為上有何差別。

本研究參考Lemmens等人於荷蘭所發表的網路遊戲成癮量表面向為主，2003年陳玉慧發展出的中文網路成癮量表為輔並結合 Hoffman 等人的沈浸模型設計問卷，接著採問卷調查法進行資料收集，透過網站總計回收 307 份有效問卷。透過網路成癮的顯著性、耐受性、戒斷症、心情轉換、重複、衝突、問題等七個構面與沉浸模型的專注、操控/技巧、探索行為、時間感扭曲、遠距臨場感、互動性、涉入等七個構面與遊戲，共十四個構面進行因素分析，萃取出全心投入、紓解情緒、操控樂趣、簡易操作、喜好變化、自我認知等六個因素，再進行集群分析，分出滿足成就族、喜好新鮮族、遊戲依賴族三個族群。並針對人口統計變數、網路使用行為進行外部一致性分析。

結果顯示，在使用年資上，有七成的網路線上遊戲依賴族的遊戲資歷為三年以上，網路遊戲的依賴度較高，使用年資越長。在每月平均消費上，隨著族群對網路遊戲依賴使用的強度，花費的金額也呈現遞增的現象，但整體而言，八成玩家的消費皆在五百元以下，推估可能是因為免費的網路線上遊戲更能使人無負擔的使用，進而較容易產生成癮與沉浸的現象。不同族群每天在網路線上遊戲上所花費的時間也有明顯的不同，隨著族群對網路遊戲依賴使用強度的增加，花費時間也呈現遞增的現象。

The internet is not only for searching, the media of communication but also for various entertainment such as online game. In 2001 the market size of Taiwan online game is 1.71 billion, in 2009 the market size is 11.3 billion, there is estimation for market size in 2010 is expected to reach 12.6 billion. During the decade the market has grown seven times.

This paper examines the online gamers’ level of addiction and immersion experience. In this paper, Flow Theory is used to categorize and to understand the different types of players by using chisquare. The questionnaires were designed by adopting from the scale that Lemmens published in 2009 and Hoffman et al.’s Flow Model. The method used to collect our data was through surveying. A total of 307 valid questionnaires were collected through the web site. According to the Internet Addiction, there are seven dimensions that were analyzed: tolerance, withdrawal, relapse, conflict, salience, problems, and mood modification. Moreover according to Flow Model, there are seven dimensions that were analyzed: attention, control/skill, exploring behavior, disoriented to time, disoriented to distance, interaction, and invasion. These fourteen dimensions totally were analyzed and were categorized into six major subjects. Next the use of cluster analysis, separated into three groups, And For demographic variables, Internet use behavior analysis to conduct the external consistency.

The result shows that the gamer that have high reliable on online games would have great experience and spent much time and money on online game.