§ 瀏覽學位論文書目資料
  
系統識別號 U0002-1807201311440600
DOI 10.6846/TKU.2013.00671
論文名稱(中文) 建構手機玩線上遊戲之動機與阻礙量表
論文名稱(英文) Developing the scales to measure the motivation and constraint of playing mobile online game
第三語言論文名稱
校院名稱 淡江大學
系所名稱(中文) 管理科學學系碩士班
系所名稱(英文) Master's Program, Department of Management Sciences
外國學位學校名稱
外國學位學院名稱
外國學位研究所名稱
學年度 101
學期 2
出版年 102
研究生(中文) 張育萍
研究生(英文) Yu-Ping Chang
學號 600620149
學位類別 碩士
語言別 英文
第二語言別
口試日期 2013-06-26
論文頁數 83頁
口試委員 指導教授 - 陳水蓮(slchen@mail.tku.edu.tw)
委員 - 康信鴻(hhkang@mail.ncku.edu.tw)
委員 - 陳怡妃(enfa@seed.net.tw)
關鍵字(中) 手機
線上遊戲
探索性因素分析(EFA)
動機
阻礙
科技接受與使用整合理論(UTAUT)
關鍵字(英) Mobile phone
online game
exploratory factor analysis (EFA)
motivation
constraint
the Unified Theory of Acceptance and Use of Technology (UTAUT)
第三語言關鍵字
學科別分類
中文摘要
本研究的主要目的是建構手機玩線上遊戲之動機與阻礙量表。首先,透過探索性因素分析(EFA),萃取出四個動機因子:逃避、知覺關鍵多數、社會影響與績效預期;而在休閒阻礙的部分,則萃取出六個因子,分別如下:社會阻礙、時間阻礙、身體阻礙、績效阻礙、心理阻礙及轉換障礙。第二,本研究根據探索性因素分析的結果(EFA),將科技接受與使用整合理論(UTAUT)的四個構面(社會影響、績效預期、付出預期、促進條件)與逃避、知覺關鍵多數做為使用手機玩線上遊戲的休閒動機,而研究結果顯示逃避、知覺關鍵多數、社會影響、績效預期及付出預期對手機玩線上遊戲的態度有顯著的正向影響;知覺阻礙與轉換障礙則是使用手機玩線上遊戲的休閒阻礙,本研究結果也發現使用手機玩線上遊戲的態度會被社會阻礙、時間阻礙、績效阻礙、心理阻礙及轉換障礙影響。此外,無論是動機還是阻礙,手機玩線上遊戲的態度都會正向影響行為意圖。最後,本研究提出理論意涵、管理意涵與未來可研究方向做為手機遊戲業者及後續研究者參考。
英文摘要
The purpose of this study was to develop scales to measure “motivation” and “constraint” for playing online games using mobile phones. First, this thesis reveals four motivation factors based on exploratory factor analysis (EFA): escapism, performance expectancy, perceived critical mass, and social influence. EFA also extracted six leisure constraints: social, time, physical, performance, psychological, and switching barriers. Second, based on the EFA results, this study used four constructs of the Unified Theory of Acceptance and Use of Technology (UTAUT) model and two other constructs (escapism and perceived critical mass) as leisure motivations for using mobile phones to play online games. Next, the study reveals that escapism, perceived critical mass, performance expectancy, effort expectancy, and social influence all strongly affect attitudes toward playing online games using mobile phones. Perceived constraint and switching barriers are leisure constraints for playing online games through mobile phones according to the EFA results, whereas social, time, performance, psychological, and switching barriers are constraints that affect attitudes towards using mobile phones to play online games. Furthermore, user attitudes affect behavioral intention positively for both motivation and constraint. Finally, the thesis presents theoretical and managerial implications and several directions for future research.
第三語言摘要
論文目次
Table of Contents
Chapter1 Introduction	1
1.1 Overview	1
1.2 Research Process	4
Chapter2 Literature Review and Research Hypotheses	7
2.1 Leisure Motivation	7
2.2 Escapism	8
2.3 Perceived Critical Mass	8
2.4 The Unified Theory of Acceptance and Use of Technology	9
2.4.1 Social Influence	11
2.4.2 Performance Expectancy	11
2.4.3 Effort Expectancy	12
2.4.4 Facilitating Conditions	13
2.5 Leisure Constraint	13
2.6 Perceived Constraint	14
2.7 Switching Barriers	15
2.8 The Relationship between Escapism and Attitude	16
2.9 The Relationship between Perceived Critical Mass and Attitude	16
2.10 The Relationship between Social Influence and Attitude	17
2.11 The Relationship between Performance Expectancy and Attitude	17
2.12 The Relationship between Effort Expectancy and Attitude	18
2.13 The Relationship between Facilitating Conditions and Attitude	19
2.14 The Relationship between Attitude and Behavioral Intention	19
2.15 The Relationship between Social Constraint and Attitude	20
2.16 The Relationship between Time Constraint and Attitude	21
2.17 The Relationship between Physical Constraint and Attitude	21
2.18 The Relationship between Performance Constraint and Attitude	21
2.19 The Relationship between Psychological Constraint and Attitude	22
2.20 The Relationship between Switching Barriers and Attitude	22
Chapter3 Research Method	24
3.1 Conceptual Research Framework	24
3.2 Measurement Development	25
3.3 Questionnaire Design, Pre-testing	27
3.4 Sampling and Data Collection	28
3.5 Data Analysis Method	29
3.5.1 Descriptive Statistics	29
3.5.2 Exploratory Factor Analysis (EFA)	30
3.5.3 Reliability and Validity Analysis	31
3.5.4 Structural Equation Model (SEM)	32
Chapter4 Data Analysis and Results	33
4.1 Respondents Profiles	33
4.1.1 First Wave (EFA)	33
4.1.2 Second Wave (CFA, SEM)	35
4.2 Exploratory Factor Analysis (EFA) Results	38
4.2.1 Kaiser-Meyer-Olkin (KMO) and Bartlett’s Test of Sphericity	38
4.2.2 Communality	39
4.2.3 Model Fit	43
4.2.4 Validity Analysis	44
4.3 Measurement Model Results	46
4.3.1 CFA and Model Fit	46
4.3.2 Reliability Analysis	47
4.3.3 Validity Analysis	50
4.4 Structural Model Results	51
4.4.1 Overall Model Validation	51
4.4.2 Structural Equation Model Evaluate Hypothesis Test	52
Chapter5 Conclusions	56
5.1 Research Discussion	56
5.1.1 EFA Results Discussion	56
5.1.2 CFA and SEM Results Discussion	56
5.2 Theoretical Implication	60
5.3 Managerial Implication	62
5.4 Limitations and Future Research	63
Reference	64
Appendix	74
1. 第一波問卷(動機)	74
2. 第一波問卷(阻礙)	76
3. 第二波問卷(動機)	79
4. 第二波問卷(阻礙)	81 
List of Tables
Table 3-1 Corresponding Literature Sources of the Measure Items	27
Table 4-1 Frequency and Percentage of the Demographic Variables for Motivation (EFA)	34
Table 4-2 Frequency and Percentage of the Demographic Variables for Constraint (EFA)	35
Table 4-3 Frequency and Percentage of the Demographic Variables for Motivation (CFA, SEM)	36
Table 4-4 Frequency and Percentage of the Demographic Variables for Constraint (CFA, SEM)	37
Table 4-5 KMO and Bartlett’s test of EFA for Motivation	38
Table 4-6 KMO and Bartlett’s test of EFA for Constraint	39
Table 4-7 Varimax rotated loading matrix for motivation	39
Table 4-8 EFA factor analysis for motivation	40
Table 4-9 Varimax rotated loading matrix for constraint	41
Table 4-10 EFA factor analysis for constraint	42
Table 4-11 CFA model fits of EFA for motivation	43
Table 4-12 CFA model fits of EFA for constraint	43
Table 4-13 Measurement properties of EFA for motivation	44
Table 4-14 Chi-Square Difference Results for motivation	44
Table 4-15 Measurement properties of EFA for motivation	45
Table 4-16 Chi-Square Difference Results for constraint	46
Table 4-17 CFA model fits for motivation	46
Table 4-18 CFA model fits for constraint	47
Table 4-19 Measurement properties for motivation	48
Table 4-20 Measurement properties for constraint	49
Table 4-21 Chi-Square Difference Results for motivation	50
Table 4-22 Chi-Square Difference Results for constraint	51
Table 4-23 Goodness-of-fit measures of the structural model for motivation	52
Table 4-24 Goodness-of-fit measures of the structural model for constraint	52
Table 4-25 The results of the structural equation model for motivation	54
Table 4-26 The results of the structural equation model for constraint	55
Table 5-1 Hypotheses Results of Motivation	58
Table 5-2 Hypotheses Results of Constraint	60

 
List of Figures
Figure 1-1 Research Process	6
Figure 3-1 Research Framework of Motivation	24
Figure 3-2 Research Framework of Constraint	25
Figure 4-1 Structural equation model of hypotheses testing result for motivation	53
Figure 4-2 Structural equation model of hypotheses testing result for constraint	55
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