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研究生：	Karen Rocío Castellanos Gossmann Karen Rocío Castellanos Gossmann
論文名稱：	The Role of Culture in the Acceptance of Online Social Networks’ for Organizational Staffing Activities by HR Practitioners The Role of Culture in the Acceptance of Online Social Networks’ for Organizational Staffing Activities by HR Practitioners
指導教授：	葉俶禎 Yeh, Chu-Chen
學位類別：	碩士 Master
系所名稱：	國際人力資源發展研究所 Graduate Institute of International Human Resource Developmemt
論文出版年：	2013
畢業學年度：	101
語文別：	英文
論文頁數：	102
英文關鍵詞：	Online social networks, TAM, culture, HR practitioner
論文種類：	學術論文
相關次數：	點閱：96 下載：24
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This research was based on the Technology Acceptance Model (TAM), which theorized on how perception of a system’s usefulness, ease of use and other’s influence affect the intention to use a system. The system in question is online social networks. The role of culture as a moderator was studied. The effect of perceived usefulness, perceived ease of use, and subjective norms on HR practitioners’ behavioral intention to use online social networks in their staffing activities were studied, with Hofstede´s dimensions of culture as moderators. HR practitioners in Taiwan, India, Spain and Guatemala were the target sample of this study. Contact information was gathered through company websites or through the researcher’s online and personal social networks. Respondents were asked to complete an online questionnaire to assess both their espoused cultural values and their perception toward online social networks for staffing activities. A total of 101 valid responses were collected for data analysis. Partial least square structural equation modeling techniques were used to test study hypotheses. Results indicated that, as hypothesized, the TAM model was effective in explaining HR practitioners’ behavioral intention to use online social networks for staffing activities. In addition, uncertainty avoidance was found to moderate the relationship between perceived usefulness as well as perceived ease of use and behavioral intention. Power distance also was found to moderate the relationship between subjective norms and behavioral intention. On the contrary, espoused masculinity/femininity and individualism/collectivism values were not found to moderate any of the relationships hypothesized.

TABLE OF CONTENTS
Abstract    I
Table of Contents…………………………………………………………………………  II
List of Tables    IV
List of Figures    VI
CHAPTER I  INTRODUCTION    1
Background of the Study    1
Statement of the Problem    2
Rationale    3
Purpose    4
Research Questions    5
Scope of the Study    6
Contribution of the Study    6
Definition of Terms    7
CHAPTER II  LITERATURE REVIEW    9
A New Technology: The Online Social Networks    9
Social Networks and HR    10
The Technology Acceptance Model    13
The Cultural Construct    17
Technology Acceptance and Culture    20
Development of Hypotheses    21
CHAPTER III  METHODOLOGY    29
Research Framework    29
Hypotheses    30
Research Procedure    32
Research Design    33
Sample Setting    34
Measurement    34
TAM    34
Culture    36
Data Collection    39
Sample Profile    40
Data Analysis Procedure    42
CHAPTER IV  DATA ANALYSIS AND RESULTS    61
Correlation Analysis    61
Model Testing in PLS    64
CHAPTER V  CONCLUSIONS AND DISCUSSIONS    81
Conclusions    81
Discussion    83
Research Implications    84
Practical Implications    85
Limitations    86
Future Research Suggestions    88
REFERENCES    91
APPENDIX:  QUESTIONNAIRE    97












LIST OF TABLES
Table 2.1    TAM Moderators…………………………………………….....................16
Table 3.1    Hofstede’s five dimensions of culture and its given scores….....................34
Table 3.2    TAM Questionnaire Scales………………………………………….…….35
Table 3.3    Culture Questionnaire Scales………………………………………….......37
Table 3.4    Descriptive Statistics of the sample (N=101)……….……….....................41
Table 3.5    Rotated Component Matrix TAM……………………….………………...45
Table 3.6    Rotated Component Matrix Hofstede’s Cultural Dimensions……..……...46
Table 3.7    Original CFA results: evidence of opposite loadings on BI………………48
Table 3.8    Descriptive Statistics, Factor Loadings, Composite Reliability,
AVE and Items of Studied Construct BI1……...........................................50
Table 3.9    Descriptive Statistics, Factor Loadings, Composite Reliability, AVE and Items of Studied Construct BI1……………...............................................52
Table 3.10    Factor Loading and Cross-Loadings among the variables BI1…...…........55
Table 3.11    Factor Loading and Cross-Loadings among the variables BI2…...…........56
Table 3.12    Cronbach’s Alpha…………...……………………………………..……...58
Table 3.13    Overview of AVE and Discriminant Validity Testing Among the Constructs BI1………………………………………………………………………...59
Table 4.1    Means, Standard Deviations and Correlation Coefficients…...…………..63
Table 4.2    Path Coefficients, T-statistics for Hypothesis 1 to 3 BI1………..………..65
Table 4.3    Path Coefficients, T-statistics for Hypothesis 1 to 3 BI2………..………..65
Table 4.4    Path Coefficients, T-statistics for Hypothesis 4 Model BI1…………........66
Table 4.5    Path Coefficients, T-statistics for Hypothesis 4 Model BI2…………........66
Table 4.6    Path Coefficients, T-statistics for Hypothesis 5a Model BI1…..……........67
Table 4.7    Path Coefficients, T-statistics for Hypothesis 5a Model BI2…..……........68
Table 4.8    Path Coefficients, T-statistics for Hypothesis 5b Model BI1………..........69
Table 4.9    Path Coefficients, T-statistics for Hypothesis 5b Model BI2………..........69
Table 4.10    Path Coefficients, T-statistics for Hypothesis 5c Model BI1…,…….........70
Table 4.11    Path Coefficients, T-statistics for Hypothesis 5c Model BI2…,…….........70
Table 4.12    Path Coefficients, T-statistics for Hypothesis 6 Model BI1…………........71
Table 4.13    Path Coefficients, T-statistics for Hypothesis 6 Model BI2…………........72
Table 4.14    Path Coefficients, T-statistics for Hypothesis 7a Model BI1…..……........73
Table 4.15    Path Coefficients, T-statistics for Hypothesis 7a Model BI2…..……........73
Table 4.16    Path Coefficients, T-statistics for Hypothesis 7b Model BI1…..……........74
Table 4.17    Path Coefficients, T-statistics for Hypothesis 7b Model BI2…..……........74
Table 4.18    Path Coefficients, T-statistics for Hypothesis 7c Model BI1…..……........75
Table 4.19    Path Coefficients, T-statistics for Hypothesis 7c Model BI2…..……........76
Table 4.20    Hypotheses Testing Results Summary……………………………………..77



LIST OF FIGURES
Figure 3.1    Research Framework……………………………………………………..29
Figure 3.2    Research Procedure…………………………………………...………….33
Figure 4.1    Hypothesis 1-3 Model BI1…………………………………...…………..65
Figure 4.2    Hypothesis 1-3 Model BI2…………………………………...…………..65
Figure 4.3    Hypothesis 4 Model BI1……………………………………...…….…….67
Figure 4.4    Hypothesis 4 Model BI2……………………………………...…….…….67
Figure 4.5    Hypothesis 5a Model BI1…..………………………………...…….…….68
Figure 4.6    Hypothesis 5a Model BI2…..………………………………...…….…….68
Figure 4.7    Hypothesis 5b Model BI1…..………………………………...…….…….69
Figure 4.8    Hypothesis 5b Model BI2…..………………………………...…….…….69
Figure 4.9    Hypothesis 5c Model BI1…..………………………………...…….…….71
Figure 4.10    Hypothesis 5c Model BI2…..………………………………...…….…….71
Figure 4.11    Hypothesis 6 Model BI1……………………………………...…….…….72
Figure 4.12    Hypothesis 6 Model BI2……………………………………...…….…….72
Figure 4.13    Hypothesis 7a Model BI1…..………………………………...…….…….73
Figure 4.14    Hypothesis 7a Model BI2…..………………………………...…….…….73
Figure 4.15    Hypothesis 7b Model BI1…..………………………………...…….…….75
Figure 4.16    Hypothesis 7b Model BI2…..………………………………...…….…….75
Figure 4.17    Hypothesis 7c Model BI1…..………………………………...…….…….76
Figure 4.18    Hypothesis 7c Model BI2…..………………………………...…….…….76
Figure 4.19    Hypotheses Testing Summary Model BI1……………………………….79
Figure 4.20    Hypotheses Testing Summary Model BI2……………………………….79

                                

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