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研究生：	寇兒 Cole, Patience Salla
論文名稱：	A Cross-level Examination of Factors that Make Players Become Popular:The Case of National Basketball Association A Cross-level Examination of Factors that Make Players Become Popular:The Case of National Basketball Association
指導教授：	林豪傑 Lin, Hao-Chieh
學位類別：	碩士 Master
系所名稱：	管理學院 - 國際經營管理研究所碩士班 Institute of International Management (IIMBA--Master)
論文出版年：	2011
畢業學年度：	99
語文別：	英文
論文頁數：	58
外文關鍵詞：	Clutch, Highlight, Player Efficiency Rating (PER), Team performances, National Basketball Association (NBA)
相關次數：	點閱：63 下載：0
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This research paper investigated which factors of a National Basketball Association leads a player to become popular. Factors that lead a player to become popular are stated in this research as Clutch factor, Highlight factor, Player Efficiency rating (PER), and high level moderator Team Performance. This paper measure individual level which are the three hypothesis (Clutch factor (H1), Highlight factor (H2), Player Efficiency rating (PER) (H3) and Control variable which are (Age, Year, Position, Conference, GameBack, player’s country of origin, and Teams Cities) Group level which is high level moderator Team Performance (H4) by using Hierarchical Linear Modeling (HLM) to utilize the eight year season and thirty teams of the National Basketball Association (NBA).
The result revealed the entire four hypotheses including the control variables to be highly significant to the depended variable Popularity.

ACKNOWLEDGEMENTS	I
ABSTRACT	III
TABLE OF CONTENTS	IV
LIST OF TABLES	VII
LIST OF FIGURES	VIII
CHAPTER ONE INTRODUCTION	1
1.1 Research Background and Motives.	1
1.2 Research Purposes.	2
1.2.1 Conceptual Model.	3
1.2.2 Definition of Variables.	3
1.2.3 Research Gap I Clutch Factors.	4
1.2.4 Research Gap II Player Efficiency Rating PER.	5
1.3 Why this Research Exploit National Basketball Association (NBA) Data.	6
1.4 Research Structure.	7
CHAPTER TWO LITERATURE REVIEW	8
2.1 Theoretical Background: Human Capital Theory.	8
2.2 Definitions for Relevant Research Variables.	10
2.2.1 Popularity.	10
2.2.2 Clutch Factor.	10
2.2.3 Highlight Factor.	12
2.2.4 Players Efficiency Rating (PER).	15
2.2.5 Team Performance as a Higher-level Moderator.	17
2.3 Developments of Research Hypotheses.	19
2.3.1 Relationships between Clutch Factor and Popularity.	19
2.3.2 Relationships between Highlight Factor and Popularity.	19
2.3.3 Relationships between Player Efficiency Rating (PER) and Popularity.	20
2.3.4 Relationships between Team Performance as a Higher-level Moderator and Popularity.	21
CHAPTER THREE RESEARCH DESIGN AND METHODOLOGY	23
3.1 Research Model.	23
3.2 Description of Sample.	24
3.3 Summary of Hypotheses.	24
3.4 Measures and Definitions of Variables.	25
3.5 Control Variables.	25
3.5.1 Age.	26
3.5.2 Position.	26
3.5.3 Conference.	26
3.5.4 Game Back.	27
3.5.5 Year.	27
3.5.6 Player’s countries of origin.	28
3.6 Method of Analysis.	28
3.6.1 Descriptive Statistics.	28
3.6.2 Pearson Correlation Analysis.	29
3.6.3 Multilevel Analysis.	29
CHAPTER FOUR RESEARCH RESULTS	30
4.1 Descriptive Analysis.	30
4.2 Mean, Standard Deviations, and Pearson Correlation.	33
4.3 Dataset explanation of how it is being used in HLM software.	35
4.3.1 Individual Level.	35
4.3.2 Group Level: Cross level Interaction.	36
4.3.3 Dataset Description.	36
4.4 HLM Result for Dependent Variable: Popularity.	42
4.4.1 Null Model Result.	44
4.4.2 Individual-Level Result.	44
4.4.3 Moderator Level.	44
4.4.4 Cross-Level Interaction.	45
4.4.5 Summary of Hypothesis Results.	45
4.4.6 Summary of Control Variables Result.	46
CHAPTER FIVE CONCLUSION AND SUGGESTION	47
5.1 Discussion.	47
5.1.1 Theoretical Implications.	47
5.1.2 Managerial Implications.	49
5.2 Limitations and Future Directions.	50
REFERENCES	52
APPENDIX 1	55
APPENDIX 2	58
 
LIST OF TABLES
Table 2-1 Hollinger Stats-Player Efficiency Rating-Qualified Players	16
Table 3-1 Definitions of Variables and Proxies	25
Table 4-1 Descriptive Analysis	31
Table 4-2 NBA Basketball Teams	37
Table 4-6 Hierarchical Linear Modeling (HLM) Result for Popularity	43
Table 4-7 Summary of Hypotheses Test	45
Table 4-8 Summary of Control Variables tested.	46

 
LIST OF FIGURES

Figure 1-1. Conceptual model	3
Figure 2-1. Pictures of slam dunk, block, and assist of how it has been done by players	12
Figure 3-1. Framework of constructs, hypotheses and control variables	23
Figure 4-1. Mean, standard deviations, and Pearson correlation	34
Figure 4-2. Individual level	35
Figure 4-3. Moderator level	36
Figure 4-4. Cross-level interaction	36
Figure 4-5. NBA teams and cities part 1	37
Figure 4-6. NBA teams and cities part 2	38
Figure 4-7. NBA player’s country of origin part 1	38
Figure 4-8. NBA player’s country of origin part 2	39
Figure 4-9. Player’s  teamcode	41

                                    

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