線上遊戲玩家共識模式建構與驗證

Model Construction and Confirmation for Online Game Players’ Consensus

本研究有別與於傳統以語言為主的深度訪談，採用以圖像為訪談依據的隱喻抽取技術(Zaltman Metaphor Elicitation Technique,ZMET)來挖掘線上遊戲玩家內心的思維與想法，抽取出消費者心中的共同構念，建立共識地圖。也藉由因素分析篩選線上遊戲玩家構面及所涵蓋的構念，再運用結構方程模式建構共識模式，並對此模式進行二階驗證性因素分析，來確認此模式代表線上遊戲玩家的共識。研究結果獲得由27 個共同構念組成的共識地圖，並萃取出關係、成就、成長、安全及親和五個獨立需求構面來建構玩家的共識模式，再經執行二階驗證性因素分析後再給予必要的修正，修正結果顯示此模式具有良好的建構效度。此種由探索性分析轉為驗證性分析所建構的共識模式，可以確認是線上遊戲玩家共同思維的結構化架構。所建構的模式獲得23 個共同構念、5 項一階需求構面及2 項二階終結構念間的因果關係。此模式可以讓線上遊戲業者，作為分析線上遊戲玩家認知的有效憑藉，亦可透過分析結果重新擬訂行銷方案或進行產品改善，以達成符合顧客認同與需求的行銷策略或產品規劃。

Because the internet is more and more affordable and popular, the families with internet access increased to 160 million in 2005. Such increase also drives the internet entertainment to growth and creates a huge online game market. The earnings of global online games were estimated to measure from USD 3,400 million in 2005 to USD 13,000 million in 2011. Online game has become the star of interaction entertainment industry. Companies in the industry are exploring how to manage the pattern, the new market and the growth. Therefore, many researchers were done to find out the cognition and expectation of players in online games by traditional linguistically-based in-depth interviews. These researchers may not truly detect online game player’s thoughts, feelings and behaviors because many scientists thought most communication is non-verbal. It is important to add that nonverbal communication to determine weather customers literally mean what they say. Such discovery is significant to the researchers in marketing. This was also the motivation of this research for understanding online game player’s thoughts. In order to achieve a deeper understanding of the thoughts of online game players, this research used the Zaltman Metaphor Elicitation Technique (“ZMET”) instead of traditional linguistically-based in-depth interviews. According to this method, the participants were inquired and asked to link those pictures which they provided. The participants also had to explain the connection among pictures. The researcher would like to clearly understand the participant’s mind by nonverbal images. The real thoughts, feelings and behaviors could be collected under the method. The collected thoughts, feelings and behaviors were transformed to writing to find out the key constructs in online game players’ minds. Then each participant's mental model could be obtained. The different consumer mental models were utilized to assemble a Consensus Map by dominant constructs. Factor analysis was used to sort out the online game players’ dominant constructs. A structural equation model (“SEM”) was then used to build up the Consensus Model. Second-order confirmatory factor analysis was done to confirm that the SEM does indeed represent the online game players’ consensus. A Consensus Map of 27 dominant constructs was found and an SEM of 5 individual items, including relatedness, achievement, growth, safety and affiliation was derived through the research. After necessary modifications based on second-order confirmatory factor analysis, the adjusted SEM works well in terms of effectiveness. The model with 23 dominant constructs, 5 first-stage variables and 2 second-stage variables established through both exploratory analysis and confirmatory analysis is proved to be the institutional structure of online players’ common thoughts. Such a model is an effective tool to analyze online game players' cognition. The results of such analysis can be used to improve marketing and products to match customers’ cognition and meet their demands.