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情緒與信賴程度對使用社會網絡行為及個人效益之影響:性別與涉入的干擾效果

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(1)INTERNATIONAL MASTER OF BUSINESS ADMINISTRATION NATIONAL UNIVERSITY OF KAOHSIUNG. Master Thesis. Effects of Emotion and Trust on Online Social Network Adoption toward Individual Benefits: Moderating Impacts of Gender and Involvement 情緒與信賴程度對使用社會網絡行為及個人效益之影響: 性別與涉入的干擾效果. Graduate Student: Yi-Jie Tsai Advisors: Dr. Chien-Hsing Wu Dr. Chian-Hsueng Chao. JULY 2014    .

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(3) Acknowledge First, my deepest respect and gratitude go to my parents, they support me and give me a nice life. Also, I am grateful to my families and my friends, they helped me to finish the data collections of this thesis. Second, I would like to acknowledge my advisor Professor Chien-Hsing Wu. His guiding, his teaching, and his thinking really make me learn a lot, not only the knowledge in academic but also the attitude in life. I am very glad that I can be his student. Meanwhile, thank Dr. Chian-Hsueng Chao, my co-advisor and also my tutor, he is a friendly teacher and treats me very well in NUK. Third, many thanks to Dean Yu-Hui Tao, Director I-Hsien Ting, lecturers of IMBA program: Dr. Yi-Kai Chen, Dr. Shao-Hsun Keng, Dr. David K. Wang, Dr. Ming-Jang Weng, Dr. Pao-Tiao Chuang, Dr. Chih-Min She, Dr. Yung-Kai Yang, and Dr. I-Hui Cheng, our IMBA assistant, and my classmates in NUK. With their help, I can grow up during this two years. Fourth, thank my committee members, Dr. Po-Chih Lee and Dr. Chuan-Chun Wu, for their comments and guidance in my oral defense. Especially, I would like to express gratitude to my college teachers, Dr. Chia-Chan Kao and Dr. Huei-Chu Cheng. With their greatly supports and suggestions, I went to NUK to continue my study. Finally, thank God always can be with me and help me to pass every difficult situations. I want to share this joyful feeling to every person whom I met in my life.. Joy Tsai Yi-Jie July 2014    .

(4) Effects of Emotion and Trust on Online Social Network Adoption toward Individual Benefits: Moderating Impacts of Gender and Involvement Advisors: Dr. Chien-Hsing Wu Dr. Chian-Hsueng Chao Department of Information Management National University of Kaohsiung Graduate Student: Yi-Jie Tsai International Master of Business Administration National University of Kaohsiung. Abstract For the past decade, the advanced development of Online Social Network (OSN) has demonstrated a considerable contribution to the industries and society. While literature presented research for concepts sharing, factors examining, and case studies with respect to the using willingness of OSN, it at the same time paid limited attention to the effects of positive emotion (PE), negative emotion (NE), and trust on OSN adoption toward individual benefits (IB). To address those issues in depth, the research thesis proposes and examines the research models that incorporate types of emotion and trust as the antecedents of OSN adoption to describe IB in PE and NE groups. A salient consideration is to examine the moderating effects of gender and involvement on the relationships between independent and dependent variables for both groups. Based on the analysis of 522 valid samples, research results show that (1) effects of PE and trust on OSN adoption toward IB are positive and significant. (2) PE group, attentive and active show significant effects on OSN adoption, respectively. (3) NE group, only ashamed presents a significant influence on OSN adoption. (4) moderators of PE group report that alert, attentive, and active are significant, indicating that female reveals significant effects while male reveals insignificant effects for both alert and attentive, and low involvement reveals significant effects for inspired and active while high involvement reveals significant effects for attentive and active. (5) moderators of NE group report that upset, ashamed, and afraid are significant, indicating that female reveals a significant effect for upset while male reveals a significant effect for ashamed, and high involvement shows significant effects for both ashamed and afraid. Discussion and implications are also addressed. Keywords: Online Social Network, Positive Emotion, Negative Emotion, Trust, Relationship, Information, Knowledge, Satisfaction, Gender, and Involvement.    .

(5) Table of Contents CHAPTER ONE INTRODUCTION ....................................................................................... 1  1.1 Background, Motivations and Objectives ..................................................................................... 1  1.2 Research procedure ....................................................................................................................... 3  1.3 Thesis Overview ........................................................................................................................... 5 . CHAPTER TWO LITERATURE REVIEW............................................................................ 6  2.1 Online Social Network .................................................................................................................. 6  2.1.1 Social Network Site .............................................................................................................................. 6  2.1.2 Online Social Network Adoption and Individual Benefits ................................................................... 9  2.1.2.1 Relationship maintenance and development...................................................................................... 9  2.1.2.2 Information and knowledge sharing ................................................................................................. 11  2.1.2.3 Use satisfaction ............................................................................................................................... 12  2.1.2.4 Technology Acceptance Model......................................................................................................... 14 . 2.2 Emotion and Trust ....................................................................................................................... 16  2.2.1 Emotions on IT Use ............................................................................................................................ 16  2.2.2 Positive Emotions and Negative Emotions ......................................................................................... 18  2.2.3 Trust .................................................................................................................................................... 20 . 2.3 Gender and Involvement ............................................................................................................. 23 . CHAPTER THREE RESEARCH METHOD........................................................................ 27  3.1 Research Models ......................................................................................................................... 27  3.1.1 Hypotheses of Model 1 (The Group of Positive Emotions)................................................................ 30  3.1.2 Hypotheses of Model 2 (The Group of Negative Emotions) .............................................................. 31 . 3.2 Population and Sampling Plan .................................................................................................... 32  3.3 Measurement ............................................................................................................................... 33  3.4 Data Analysis Techniques ........................................................................................................... 37 . CHAPTER FOUR DATA ANALYSIS AND RESULTS ....................................................... 38  4.1 Descriptive Statistics ................................................................................................................... 38  4.2 Reliability and Validity ............................................................................................................... 44  4.2.1 Reliability Analysis............................................................................................................................. 44  4.2.2 Factor Analysis ................................................................................................................................... 46  4.2.3 Model Fitting ...................................................................................................................................... 50 . 4.3 Path Analysis ............................................................................................................................... 53  4.3.1 Model 1 (The Group of Positive Emotions) ....................................................................................... 53  4.3.2 Model 2 (The Group of Negative Emotions) ...................................................................................... 58 . 4.4 Discussion and Implications ....................................................................................................... 63  4.4.1 Online Social Network Adoption and Individual Benefits ................................................................. 68  4.4.2 Trust .................................................................................................................................................... 70  4.4.3 Positive Emotions ............................................................................................................................... 71  4.4.4 Negative Emotions ............................................................................................................................. 73 . CHAPTER FIVE CONCLUSION ......................................................................................... 75  5.1 Research Findings ....................................................................................................................... 75  5.2 Research Suggestions.................................................................................................................. 77  5.3 Limitations and Future Research ................................................................................................ 78 . REFERENCES ......................................................................................................................... 79  APPENDIXES ......................................................................................................................... 85  Appendix A: Formal Research Questionnaire (in English) .............................................................................. 85  Appendix B: Formal Research Questionnaire (in Chinese) ............................................................................. 88 I   .

(6) List of Tables Table 2-1: The Studies of Social Capital on SNSs ................................................................... 13  Table 2-2: The Summary of Emotions Studies on IT Use ........................................................ 17  Table 2-3: I-PANAS-SF used in studies ................................................................................... 19  Table 3-1: Operational Definitions (I) ...................................................................................... 35  Table 3-2: Operational Definitions (II) .................................................................................... 36  Table 4-1: The Basic Information of Respondents (I) .............................................................. 40  Table 4-2: The Basic Information of Respondents (II) ............................................................ 41  Table 4-3: The Descriptive Statistics of All Variables .............................................................. 43  Table 4-4: Reliability Analysis and Results ............................................................................. 45  Table 4-5: Factor Analysis and Results (Positive Emotions) ................................................... 47  Table 4-6: Factor Analysis and Results (Negative Emotions).................................................. 48  Table 4-7: Factor Analysis and Results (Trust) ........................................................................ 48  Table 4-8: Factor Analysis and Results (OSN adoption) ......................................................... 49  Table 4-9: Factor Analysis and Results (Individual Benefits).................................................. 49  Table 4-10: The Summary of Reliability and Validity ............................................................. 51  Table 4-11: Correlation of All Constructs with AVE Validity .................................................. 52  Table 4-12: The Results of Path Analysis in Model 1 (I) ......................................................... 53  Table 4-13: The Results of Path Analysis in Model 1 (II)........................................................ 54  Table 4-14: The Path Results of Moderators in Model 1 (I) .................................................... 55  Table 4-15: The Path Results of Moderators in Model 1 (II) ................................................... 56  Table 4-16: The Results of Path Analysis in Model 2 (I) ......................................................... 58  Table 4-17: The Results of Path Analysis in Model 2 (II)........................................................ 59  Table 4-18: The Path Results of Moderators in Model 2 (I) .................................................... 60  Table 4-19: The Path Results of Moderators in Model 2 (II) ................................................... 61  Table 4-20: Hypotheses Testing of Model 1 (The Group of Positive Emotions) ..................... 66  Table 4-21: Hypotheses Testing of Model 2 (The Group of Negative Emotions) ................... 67  Table 4-22: The Summary of Path Analysis (OSN adoption to Individual Benefits) .............. 68  Table 4-23: The Summary of Path Analysis (Trust to OSN adoption)..................................... 70  Table 4-24: The Summary of Path Analysis (Positive Emotions to OSN adoption) ................ 71  Table 4-25: The Summary of Path Analysis (Negative Emotions to OSN adoption) .............. 73 . II   .

(7) List of Figures Figure 1-1: Research Flow Chart ............................................................................................... 4  Figure 2-1: Technology Acceptance Model ............................................................................. 14  Figure 2-2: The Unified Theory of Acceptance and Use of Technology Model ...................... 24  Figure 3-1: Research Model 1 (The Group of Positive Emotions) .......................................... 28  Figure 3-2: Research Model 2 (The Group of Negative Emotions) ......................................... 29  Figure 4-1: The Results of Path Analysis in Model 1 (I) ......................................................... 53  Figure 4-2: The Results of Path Analysis in Model 1 (II) ........................................................ 54  Figure 4-3: The Path Results of Moderators in Model 1 (I)..................................................... 55  Figure 4-4: The Path Results of Moderators in Model 1 (II) ................................................... 57  Figure 4-5: The Results of Path Analysis in Model 2 (I) ......................................................... 58  Figure 4-6: The Results of Path Analysis in Model 2 (II) ........................................................ 59  Figure 4-7: The Path Results of Moderators in Model 2 (I)..................................................... 60  Figure 4-8: The Path Results of Moderators in Model 2 (II) ................................................... 62  Figure 4-9: Hypotheses Testing of Model 1 (The Group of Positive Emotions) ..................... 64  Figure 4-10: Hypotheses Testing of Model 2 (The Group of Negative Emotions) .................. 65 . III   .

(8) CHAPTER ONE INTRODUCTION. 1.1 Background, Motivations and Objectives. The concept of Social Networks was introduced by Barnes (1954). For the past decade, the development of Online Social Network (OSN) has extended the notion of social networks on Web 2.0 network applications. Therefore, to emphasize this articulated social network as a critical organizing feature of these sites, researchers label them Social Network Sites (SNSs) (Donelan et al., 2010). For example, Facebook and Twitter are trends that are sweeping the world. Current studies have shown that OSN Adoption remains the mainstream of interaction research for now and near future in the SNSs filed, and also focused on research areas which are including SNSs’ applications and developments, usage behaviors and satisfactions, key factors of success, the effects on different traits or types of SNSs, friendship performances, networks management, and issues of online and offline connectivity and privacy, etc. (Ellison et al., 2007; Waters et al., 2009; Ganley and Lampe, 2009; Pfeil and Zaphiris, 2009; Roblyer et al., 2010; Kim et al., 2011; Lin and Lu, 2011).. Previous literature discussed factors and examined the use willingness of SNSs, IT use, and social capital (Ellison et al., 2007; Valenzuela et al., 2009; Shi et al., 2010; Beaudry et al., 2010; Kim et al., 2011). First, based on the Technology Acceptance Model (TAM), this study argues that behavioral intention is influenced by psychological status that mainly includes various types of emotion, such as inspired, upset, active, hostile, etc. Second, trust has been studied in many disciplines including sociology, psychology, economics, and computer science (Cook et al., 2005; Hughes et al., 2005; Huang, 2007; Maheswaran et al., 2007). And, there are literatures that illustrate the relationship between trust and OSN adoption in SNSs 1   .

(9) fields (Gross and Acquisti , 2005; George, 2006; Kornblum and Marklein, 2006; Dwyer et al., 2007; Jagatic et al. 2007). Third, Venkatesh et al. (2003) developed the Unified Theory of Acceptance and Use of Technology model to consolidate previous TAM related studies, and also explained how individual differences influence technology use. More specifically, the relationship between perceived usefulness, ease of use, and intention to use can be moderated by age, gender, and experience.. This study adopts the positive and negative emotional elements as the antecedents of OSN use, and assumed that trust can influence the using behavior on OSN. From references review of gender and involvement effects, this study also use these two variables to moderate the relationship between emotions, trust, OSN adoption, and individual benefits, to examine the different results in various reaction. Therefore, the research objectives of this study including that:. (1) To develop and examine research models that describes the effects of positive and negative emotions on OSN adoption toward individual benefits. (2) To develop and examine research models that describes the trust effect on OSN adoption toward individual benefits. (3) To examine the moderating effects of gender and involvement on the relationship between independent variables and dependent variables.. 2   .

(10) 1.2 Research procedure. The research procedure is shown in Figure 1-1. It covers steps as follows:. (1) Setting the research motivations and objectives of this study. (2) Reviewing literature that consists of independent variables, dependent variables, and the variables of moderating effects, which are positive emotions, negative emotions, trust, OSN adoption, individual benefits, gender, and involvement (3) Developing research models and questionnaires of this study. And data collection into two stages, which are the pre-test and the online survey from experienced users. (4) Utilizing software of statistics and structure equation model (SEM) to drive research results. Implications and discussion are also presented. (5) Providing conclusions, suggestions, and contributions, and limitation, and future research direction as well.. 3   .

(11) Setting Research Motivations and Research Objectives. Reviewing Literature and Formulating Research Hypotheses. Developing Research Method and Collecting Questionnaires. Analyzing Data and Discussing Analysis Results. Concluding this Research. Figure 1-1: Research Flow Chart. 4   .

(12) 1.3 Thesis Overview. There are five chapters of this study, and each chapter of them are presented in the following:. Chapter One Introduction: In this chapter, concludes the research background, research motivations, research objectives, research procedure, and the overview of this study.. Chapter Two Literature Review: In chapter two, it consists variables and moderating effects of this study. Discuss previous researches and references including positive and negative emotions from PANAS which is a testing schedule of psychology, trust, OSN adoption, and individual benefits. Also concludes the moderators: gender and involvement. In this chapter, the research hypotheses are proposed with those variables.. Chapter Three Research Method: Research methodology conducts research models, the sampling plan, operation definitions of questionnaire, and also presents the techniques of data analysis in this chapter.. Chapter Four Data analysis and Results: In this chapter, it presents the results of dada analysis and hypothesis testing, shows the descriptive statistics, the reliability and validity testing, the factor analysis, and path relationship of research models.. Chapter Five Conclusion: Summarizes the research results, illustrates the research findings and suggestions for the academic and businesses areas, and indicates future research of this study.. 5   .

(13) CHAPTER TWO LITERATURE REVIEW. In chapter two, there are three sections including 2.1 Online Social Network, 2.2 Emotions and Trust, and 2.3 Gender and Involvement. Those sections present the previous researches that relate with the variables of research models in this study, and also develop the hypotheses that can be examined in the following research steps.. 2.1 Online Social Network. The concept of social networks was introduced by Barnes (1954), who described them as connected graphs where nodes represented entities and edges. Nodes are individuals, groups, organizations, or government agencies; Edges are interactions, invitations, trades, values, etc. For the past decade, the emergence of online social network such as Myspace and Facebook has extended the notion of social networks in terms of their sizes (Golbeck, 2007). The public accessibility of OSN using mobile phones makes such platforms ubiquitous (Humphreys, 2008). Hanchard (2008) showed that user retention rates of social networks were as good as online banking at high nineties. Previous literatures have shown that social network remains the mainstream of interaction research for now and near future (Sherchan, 2013).. 2.1.1 Social Network Site. Social network site allows individuals to (1) construct a public or semi-public profile within a bounded system, (2) articulate a list of other users with whom they share a connection, and (3) view and traverse their list of connections and those made by others within the system; the nature and nomenclature of these connections may vary from site to site (Boyd and Ellison, 6   .

(14) 2008; Dutton, 2013). It is not only to allow users to meet the other strangers, but also individuals to articulate and make visible their social networks. In a large SNS, participants are not necessarily networking or looking to meet new people; instead, they are primarily communicating with people who are already a part of their extended social network (Boyd and Ellison, 2008). To emphasize this articulated social network as a critical organizing feature of these sites, researchers label them “social network sites” (Donelan et al., 2010).. Features of SNSs vary. For example, some have photo-sharing or video-sharing capabilities, and others have built-in blogging and instant messaging technology. Boyd and Ellison (2008) showed that there are mobile specific SNSs (e.g. Dodgeball), but some web-based SNSs also support limited mobile interactions (e.g. Facebook, MySpace, and Cyworld). While SNSs are often designed to be widely accessible, many attract homogeneous populations initially, so it is not uncommon to find groups using sites to segregate themselves by nationality, age, educational level, or other factors that typically segment society (Boyd and Ellison, 2008; Donelan et al., 2010; Dutton, 2013).. In 1997, the first recognizable social network site launched: SixDegrees.com, it allowed users to create profiles, list their Friends and surf the Friends lists; SixDegrees promoted itself as a tool to help people connect with and send messages to others. While SixDegrees attracted millions of users, it failed to become a sustainable business, and closed in 2000. Early adopters were already flocking to the Internet, but most did not have extended networks of friends who were online ((Boyd and Ellison, 2008; Donelan et al., 2010; Dutton, 2013).. From 2003, many new SNSs were introduced; most took the form of profile-centric sites, trying to replicate the early success of Friendster or target specific demographics. While socially-organized SNSs solicit broad audiences, professional sites such as LinkedIn and 7   .

(15) Visible Path focus on business people. Passion-centric SNSs like Dogster help strangers connect based on shared interests (Rheingold and Weeks, 2012). Care2 helps activists meet, Couchsurfing connects travelers to people with couches, and MyChurch joins Christian churches and their members. Furthermore, as the social media and user-generated content phenomena grew, websites focused on media sharing began implementing SNS features and becoming SNSs themselves; for examples: Flickr - photo sharing, Last.FM - music listening habits, and YouTube - video sharing ((Boyd and Ellison, 2008; Donelan et al., 2010; Dutton, 2013).. One of the popular SNSs, Facebook, was designed to support distinct college networks only, and began in early 2004 as a Harvard-only SNS; in September 2005, Facebook expanded to include high school students, professionals inside corporate networks, and eventually to everyone. Another feature that differentiates Facebook is the ability for outside developers to build “Applications” which allow users to personalize their profiles and perform other tasks, such as to compare movie preferences and to chart travel histories (Cassidy, 2006; Papacharissi, 2009; Raynes-Goldie, 2010; Mazman and Usluel, 2010).. The rise of SNSs indicates a shift in the organization of online communities (Boyd and Ellison, 2008). While websites dedicated to communities of interest still exist and prosper, SNSs are primarily to connect people, based mainly on interests sharing and relationship development (Donelan et al., 2010). Early public online communities such as Usenet and public discussion forums were structured by topics or according to topical hierarchies, but SNSs are structured as personal networks, with the individual at the center of their own community (Dutton, 2013). SNSs have introduced a new organizational framework for online social network, and explore a new research area.. 8   .

(16) 2.1.2 Online Social Network Adoption and Individual Benefits. Literature indicated that there are reasons (or benefits) for people to adopt social network, in this study, there are three sub-factors of individual benefits including 2.1.2.1 relationship maintenance and development, 2.1.2.2 information and knowledge sharing, and 2.1.2.3 use satisfaction. And hypotheses are also presented as follow.. 2.1.2.1 Relationship maintenance and development. In an online social network individuals are consciously able to construct an online representation of self, such as online dating profiles and online games (e.g. LoL- League of Legends, WoW- World of Warcraft, and StarCraft). To address the concept in more depth, the SNS has been developing an important research context for scholars to investigate processes of impression management, self-presentation, and relationship performance (Boyd and Ellison, 2008). The extent to which portraits are authentic or playful varies across sites; both social and technological forces shape user practices (Donelan et al., 2010). Skog (2005) found that the status feature on LunarStorm strongly influenced how people behaved and what they choose to reveal profiles that present one’s status as measured by activity (e.g. sending messages) and indicators of authenticity (e.g. using a real photo instead of a drawing).. Another aspect of self-presentation is the articulation of relationship links, which serve as identity markers for the profile owner. Donath (2007) noted that MySpace spammers leverage people’s willingness to connect to interesting people to find targets for their spam. Fono and Raynes-Goldie (2007) described users’ understandings regarding public displays of connections and how the Friending function can operate as a catalyst for social drama, in their examination of LiveJournal friendship. In listing user motivations for Friending, Boyd (2006) 9   .

(17) point out that friends on SNSs are not the same as friends in the everyday sense; instead, friends provide context by offering users an imagined audience to guide behavioral norms. Other work in this area has examined the use of Friendster Testimonials as self-presentational devices (Boyd and Heer, 2006) and the extent to which the attractiveness of one’s friends (as indicated by Facebook’s wall feature) impacts impression formation (Walther et al., 2008).. 10   .

(18) 2.1.2.2 Information and knowledge sharing. Many researchers use the terms, knowledge and information, interchangeably, although the term knowledge sharing is generally used more often than information sharing. However, researchers tend to use the term “information sharing” to refer to sharing with others that occurs in experimental studies in which participants are given lists of information, manuals, or programs (Wang and Noe, 2010). The Internet has been fostering the development of SNS that aims at facilitating collaboration by providing an environment for mutual sharing and interaction. A collaborative process in such an environment involves intensive online knowledge discovery and knowledge sharing between collaborators, such as knowledge consumers and knowledge contributors (Yang and Chen, 2008).. The emergent SNSs over the past decade have stimulated research interests by academia and practitioners. Zhang and Tanniru (2005) built an agent-based model for virtual learning communities, the results of a series of comparison experiments indicated that every member tends to be active in the initial stage. When the community reaches a reasonable size, each participant is important and function together to form a healthy and stable population. Wasko and Faraj (2005) found that knowledge sharing has been a motivation for participation in virtual communities. Prior studies have provided evidence demonstrating the importance of information and knowledge sharing in enhancing the performance, and provide mechanisms to support the information and knowledge sharing on OSN.. 11   .

(19) 2.1.2.3 Use satisfaction. As the number and types of social networking sites continue to grow and compete for users' attention, the question of how to make users satisfied with their use of social network becomes a critical issue. Satisfaction is defined as a pleasing experience with the social networking experience in terms of technology and social interaction. Wixom and Todd (2005) found that user satisfaction and intention to use technology is significantly affected when concurrently considering both the perceptions of the quality of the shared information as well as the quality of the technology. SNSs want members to use their sites, they at the same time want users to keep using, communicating and sharing information. In order for this to happen, users must be satisfied with their experience. Part of that experience involves not also the technology, but the interactivity or perceived interactivity associated with the site in terms of the message, personal relationships, social exchange and control. Satisfaction has been used in a number of research studies to examine a user's positive attitude toward website experiences (Szymanski and Hise, 2000; Dalcher and Shine, 2003; Wixom and Todd, 2005; Chiu et al., 2006).. Table 2-1 shows a review of literature (Ellison et al., 2007; Valenzuela et al., 2009; Shi et al., 2010; Beaudry et al., 2010; Kim et al., 2010), it has shown that factors have used to examine the use willingness of SNSs, IT use, and social capital which includes multidimensional construct: civic participation, political engagement, life satisfaction, and social trust, etc.. 12   .

(20) Table 2-1: The Studies of Social Capital on SNSs Authors. Impacts. Results. Ellison et al.. SNSs;. N= 286; Facebook was implicated to develop and maintain. (2007). Social capital. bridging social capital at college; Low satisfaction and low self-esteem gained in bridging social capital if used Facebook more intensely; Bonding social capital was significant to the intensity with students used Facebook; General internet use was significant to maintain social capital.. Valenzuela et al.. SNSs;. N=2603; Facebook use had a positive relationships with. (2009). Social capital. students’ life satisfaction, social trust, civic engagement, and political participation; There were positive and significant associations between Facebook variables and social capital.. Shi et al.. SNSs;. N=125; Both disconfirmations of maintaining offline. (2010). Social capital. contacts and entertainment had strong impact on satisfaction; The disconfirmation of information seeking influenced satisfaction less than above two factors.. Beaudry et al.. IT use;. N= 249; IT use was positively significant to information. (2010). Performance. (seeking and sharing), negotiation (with clients), and figure head (information with people).. Kim et al. (2010). SNSs;. N=589; The total results showed that use SNSs had high. Social capital. significant to seeking social support and seeking information; Attitude toward the SNSs was significantly related seeking friends in US, and also had a significant to seeking social support in Korea..  . 13   .

(21) 2.1.2.4 Technology Acceptance Model. According the Technology Acceptance Model (TAM) (Davis, 1989) (see Figure 2-1), two particular beliefs: perceived usefulness and perceived ease of use, were primary two elements for computer acceptance behaviors; TAM argued that computer usage was determined by behavioral intention to use, which was affected by the attitude toward ease of use and perceived usefulness toward use intention and actual use.. SOURCE: Davis (1989) . Figure 2-1: Technology Acceptance Model. The research thesis adopts the concept of TAM and regards that SNS adoption will be influencing the individual benefits and therefore the first hypothesis is formed as follow.. Model1. H1(abc): Online social network adoption is significantly related to individual benefits.. Model2. H6(abc): Online social network adoption is significantly related to individual benefits. (Individual benefits are relationship maintenance and development, information and 14 .  .

(22) knowledge sharing, and use satisfaction). Different from the TAM’s argument, the research thesis argues that behavioral intention is influenced by psychological status that mainly includes various types of emotion, such as inspired, upset, active, hostile, etc. While a review of literature has shown that factors have used to examine the use willingness of SNSs, IT use, and social capital (Ellison et al., 2007; Valenzuela et al., 2009; Shi et al., 2010; Beaudry et al., 2010; Kim et al., 2010), they at the same time paid a limited attention to the influence of emotion. Therefore, the research thesis regards the emotion as one of the antecedents that affects the SNS adoption toward individual benefits.. 15   .

(23) 2.2 Emotion and Trust. In this section, there are three parts: 2.2.1 Emotions on IT use, 2.2.2 Positive and Negative Emotions, and 2.2.3 Trust. Part 2.2.1 shows the applications about the general and specific emotions and using behaviors in the research area of information technology, part 2.2.2 presents the independent variables of this study including positive and negative emotions which are used on the medical area, and part 2.2.3 also consist of the independent variable: trust. The hypotheses are defined in the following.. 2.2.1 Emotions on IT Use. Emotions are a mental state that promote and help individual to organize behaviors and adjust the demands of the environment. Also, emotions influence behaviors or changes in action readiness (Bagozzi et al. 1999; Lazarus 1991). Beaudry (2010) studied the direct and indirect relationships between four emotions (excitement, happiness, anger, and anxiety) and IT use were studied through a survey of 249 bank account managers, pointed that emotions felt by users early in the implementation of a new IT have important effects on IT use, and also provides a complementary perspective to understanding acceptance and antecedents of IT use.. There are other references indicated the relationship between emotions and IT use in Table 2-2, this table summarizes the studies of information system that have examined emotions and how they relate to attitudes, beliefs, and IT use; and also presents those studies are grouped by period and by the type of emotions analyzed: system specific emotions that associated with a particular IT system, and general emotions related to IT or computers.. 16   .

(24) Table 2-2: The Summary of Emotions Studies on IT Use Authors. Types of Emotions. Results. Venkatesh. Anxiety: One’s apprehension, or even. Sample 1: 58 users (online help desk), Sample 2:. (2000). fear, when faced with the possibility of. 145 users (property management system), Sample. using computers. 3: 43 users (payroll application; Anxiety is. Enjoyment: The extent to which the. negatively related to perceived ease of use (T1: β=. activity of using a specific system is. -0.30***; T2: β= -0.26***; T3: β= -0.25***),. perceived to be enjoyable in its own. Enjoyment is positively related to perceived ease. right. of use (T1: ns; T2: β= 0.18*; T3: β= 0.24**),. Playfulness: The degree of spontaneity. Playfulness is positively related to perceived ease. in microcomputer interactions. of use (T1: β= 0.20***; T2: β= 0.16*; T3: ns). Bhattacherjee. Satisfaction: Users’ affect with. 122 online banking users; Satisfaction positively. (2001). (feelings about) prior (online banking). related to continuance intention (β= 0.567***). use Koufaris. Enjoyment: One of the emotion. 280 subjects (from online market research. (2002). components of flow which is the. company); Enjoyment is positively related to. holistic sensation that people feel when. one’s intention to return to an online shopping. they act with total involvement. website (β= 0.400**). Venkatesh et. Affect: One’s linking for a particular. Sample 1: 54 users (online meeting management),. al. (2003). behavior (computer use). Sample 2: 58 users (portfolio analysis), Sample 3:. Anxiety: The feelings of apprehension. 38 users accounting system); Affect is not. or anxiety that one experiences. significantly related to intention to use, Anxiety is negatively related to. intention to use (β= -0.15*). Cenfetelli. Positive emotions: Fondness,. 387 members of a marketing firm panel using a. (2004). happiness, joy, contentment. travel website; Positive emotions are positively. Negative emotions: Unhappiness,. related to perceived ease of use (β= 0.42*),. worry, anger, nervousness, regret,. Negative emotions are negatively related to. disgust, fear, anxiety, irritation. perceived ease of use (β= -0.65*). Kim et al.. Pleasure: The degree to which a user. 218 users of mobile Internet devices; Pleasure is. (2004). feels good or happy. positively related to attitude toward use (β=. Arousal: The degree to which a user. 0.37***), Arousal is positively related to attitude. feels excited or stimulated. toward use (β= 0.22**). Brown et al.. Anxiety: One’s level of fear of. 193 university students; Computer-mediated. (2004). apprehension associated with actual or. communication (CMC) anxiety is negatively. anticipated use of IT to communicate. related to attitude toward using a CMC tool (β=. with others. -0.58***). NOTE: *p < 0.05; **p < 0.01; ***p < 0.001; T1: initial training, T2: after 1 month, T3: after 3 months. 17   .

(25) 2.2.2 Positive Emotions and Negative Emotions. Human’s emotion is diverse. Watson et al. (1988) developed the Positive and Negative Affect Schedule (PANAS) using items from the positive emotions (PE) and negative emotions (NE) descriptor word clusters detailed by Zevon and Tellegen (1982). The 20-item PANAS with its 10-item PE are interested, excited, strong, enthusiastic, proud, alert, inspired, determined, attentive and active while NE has distressed, upset, guilty, scare, hostile, irritable, ashamed, nervous, jittery and afraid. This subscales has been validated in several settings inside and outside the United States, where it was developed, and has generally been shown to be reliable and consistently reflective of the lowly, albeit significantly, correlating dimensions of PA and NA (DePaoli & Sweeney, 2000; Melvin & Molloy, 2000).. In 2007, Thompson developed The International Positive and Negative Affect Schedule Short Form (I-PANAS-SF) from the full 20-item PANAS an internationally useable 10-item version that include PE: Alert, Inspired, Determined, Attentive, and Active; NE: Upset, Hostile, Ashamed, Nervous, and Afraid. This new measure schedule I-PANAS-SF, that (1) accounts for shortcomings highlighted above, (2) reflects items qualitatively assessed to be easy to understand and unambiguous in meaning across different populations of nonnative English speakers, (3) exhibits strong psychometric properties concerning reliability, cross-sample and temporal stability, and convergent and criterion-related validity, and (4) provides evidence of cross-national structural equivalence (Thompson, 2007).. I-PANAS-SF schedule also can applied in many different research areas to measure the positive and negative affect, those emotions can related the thinking and behavior, combine other effects and variables to analysis some results for the theory assumption. Here are some summary references about use I-PANAS-SF to measure the emotions, and applied in different 18   .

(26) research areas (see Table 2-3). From this table, it is found that the positive and negative emotions are extensively used to explore their impacts on performance in various domains, such as Educational psychology, social behavior, sport science, medicine, etc (Oliver et al., 2010; Wong et al., 2011; Felton and Jowett, 2013; Brogan and Hevey, 2013; Sanchez et al., 2014). Importantly, positive and negative emotions are the main categories to describe emotions.. Table 2-3: I-PANAS-SF used in studies Authors. Impacts. Results. Oliver et al.. Emotions;. n= 146; Informational self-talk was positively related with PE,. (2010). Self-talk;. about students’ study experiences; A negative experience or poor. Study. understanding was related higher anxiety and NE, when students. experience. used high levels of controlling of self-talk.. Wong et al.. Emotions;. n= 210; Dialectical beliefs were negatively related to PE Adherence. (2011). Subjective. to Asian Values was positively related to PE.. consciousness Felton and. Emotions;. n= 300; The associations between autonomy need and the. Jowett (2013). Behavior;. well-being and NE variables were significant; Competence need. Relationship. had highly significant between the social environment of coaching and athletes’ vitality, NE, and physical self-concept.. Brogan and. Emotions;. n= 57; Fruit and vegetable intake was negatively correlated with. Hevey (2013). Eating style. NE.; Higher NE was significantly positively associated with self-reported emotional eating; PE was significantly positively associated with restraint eating; BMI was significantly correlated with NE and PE.. Sanchez et al.. Emotions;. n= 25; Main effects were found for perceived exertion and heart. (2014). Exercise. rate, both increased during testing, and for affect: PE increased and. performance. NE decreased from pre-trial to post-trial.. NOTES: PE: Positive Emotions, NE: Negative Emotions. . 19   .

(27) 2.2.3 Trust. Trust has been studied in many disciplines including sociology, psychology, economics, and computer science (Cook et al., 2005; Hughes et al., 2005; Huang, 2007; Maheswaran et al., 2007). Each of these disciplines has defined and considered trust in using online social network from different perspectives, but their definitions may not be directly applicable to social networks. In general, trust is a measure of confidence that an entity or entities will behave in an expected manner, Sherchan et al. (2013) pointed that literature concerning trust can be categorized three criteria: (1) trust about information collection: attitudes, behaviors, and experiences; (2) trust about value assessment: graph, interaction, and hybrid; (3) trust about value dissemination: based recommendation and visualization models.. Previous studies about internet applications, trust has been studied from three different aspects: Web site content, Web application, and its services. Beatty et al. (2011) conducted a study of consumer trust on e-commerce Web sites, focusing on the organization of the Web site contents to ensure trustworthiness. Trust has also been widely studied in the area of service computing (Chang et al., 2006; Malik et al., 2009), where trust plays a major role in selecting the best services for a user. Wang and Vassileva (2007) presented a systematic review of various trust and reputation systems for Web service selection and propose a typology to classify them along three dimensions: centralized versus decentralized, persons/agents versus resources, and global versus personalized. Finally, Josang et al. (2007) published an important survey for Internet applications in which they provide an overview of existing and proposed systems that can be used to derive measures of trust and reputation for Internet transactions.. 20   .

(28) There are literatures that illustrate the relationship between trust and OSN adoption in SNSs fields. Acquisti and Gross (2006) argued that there is often disconnect between students’ desire to protect privacy and their behaviors. In analyzing trust on social network sites, Dwyer et al. (2007) argued that trust and usage goals may affect what people are willing to share. Another study examining security issues in SNSs, Jagatic et al. (2007) used freely accessible profile data from SNSs to craft a phishing scheme that appeared to originate from a friend on the network; their targets were much more likely to give away information to this friend than to a perceived stranger. Moreover, popular press coverage of SNSs has emphasized potential privacy concerns, primarily concerning the safety of younger users (George, 2006; Kornblum and Marklein, 2006).. This study review the definitions and measurements of trust from different disciplines that focus on online social networks. Accordingly, this study adopts the positive and negative emotional elements as the antecedents of OSN use, and also assumed that trust can influence the using behavior on OSN. Therefore, the study argues that the emotions and trust are the factors affecting use behavior of online social network. Hypotheses are then defined as follows.. Model1. H2(abcde): Positive emotions are significantly related to the online social network adoption. (Positive emotions are alert, inspired, determined, attentive, and active). Model1. H3: Trust are significantly related to the online social network adoption.. Model2. H7(abcde): Negative emotions are significantly related to the online social network adoption. (Negative emotions are upset, hostile, ashamed, nervous, and afraid). Model2. H8: Trust are significantly related to the online social network adoption. 21 .  .

(29) Despite that the research thesis regards the variables of emotions and trust are potential factors affecting OSN use, gender and involvement may moderate the causal relationships among variables. Therefore, the gender may cause different examination result with respect to the difference between male and female, and the involvement deals with the degree of depth that users adopt and have using experience on OSN. Next section 2.3 presents those two moderators with previous references that discussed about gender and involvement.. 22   .

(30) 2.3 Gender and Involvement. Venkatesh et al. (2003) developed Unified Theory of Acceptance and Use of Technology (UTAUT) model (see Figure 2-2) a comprehensive synthesis of prior technology acceptance research. UTAUT has four key constructs that influence behavioral intention to use a technology. Venkatesh et al. (2012) pointed four constructs of UTAUT with the research field of consumer behavior: (1) Performance expectancy is defined as the degree to which using a technology will provide benefits to consumers in performing certain activities. (2) Effort expectancy is the degree of ease associated with consumers’ use of technology. (3) Social influence is the extent to which consumers perceive that important others (e.g., family and friends) believe they should use a particular technology. And (4) facilitating conditions refer to consumers’ perceptions of the resources and support available to perform a behavior. According to UTAUT, performance expectancy, effort expectancy, and social influence are theorized to influence behavioral intention to use a technology, while behavioral intention and facilitating conditions determine technology use. Also, individual difference variables: age, gender, experience, and voluntariness of use are theorized to moderate various UTAUT relationships.. This research adapts moderators from UTAUT model, designs the moderating effects to measure the effects between human’s emotions, trust, the behavior of OSN adoption, and individual benefits, the moderators of this study are gender and involvement (also means experience in UTAUT). There are two parts of this sections including literatures reviews of gender and involvement as following.. First, literature indicates that male is more likely than female to adopt a new technology earlier (Dutton, et al., 1987; LaRose and Atkin, 1988; Jeffres and Atkin, 1996). More males 23   .

(31) used the Internet in its nascent years than females (Young, 1999). A recent report by Crunchies (2008) indicated that more women used the Internet than their male counterparts in the U.S. as of 2008 and the trend will continue in the near future. The current study proposes that there is a gender difference in using social networking site. Most users of SNSs are young individuals. SNSs are considered to play an active role in younger generation’s daily life (Lenhart, 2009). The relationship between the usage behavior and other factors such as gender and frequency has been studied in many researches that focused on young people’s online activities (Lenhart and Madden, 2007; Zywica and Danowski, 2008; Pempek et al., 2009).. SOURCE: Venkatesh et al. (2003). Figure 2-2: The Unified Theory of Acceptance and Use of Technology Model. Second, the original concept of involvement from social judgment theory was proposed by Sherif and Cantril (1947). They argued that ego-involvement was determined by internal factors such as motivations or emotional states by personal attitudes, and by human 24   .

(32) perception or interpretation of the external situations. There are many studies dealing with the involvement definition. For example, Zaichkowsky (1994) defined that the involvement is a motivational construct which partly relies on the antecedent factor of the person’s values and need. Involvement is also applied on the consumer behavior study; it shows how consumers process information and learn, and also form attitudes to make purchase decision. Moreover, the consequence of involvement may be relevant or interesting, and therefore may play a strong role in determining what is relevant or interesting to consumers (Hawkins and Mothersbaugh, 2009).. From those references review of gender and involvement effects, this study also use these two variables to moderate the relationship between emotions, trust, OSN adoption, and individual benefits, to examine the different results in various reaction. Therefore, hypothesis H4, H5, H9 and H10 are defined as follows:. Model1. H4: Gender has a significant moderating effect on H1, H2, and H3. H4a(123): Gender significantly influences the relationship between the online social network adoption and individual benefits. H4b(12345): Gender significantly influences the relationship between positive emotions and the online social network adoption. H4c: Gender significantly influences the relationship between trust and the online social network adoption.. Model1. H5: Involvement has a significant moderating effect on H1, H2, and H3. H5a(123): Involvement significantly influences the relationship between the online social network adoption and Individual benefits. H5b(12345): Involvement significantly influences the relationship between positive emotions and the online social network adoption. 25 .  .

(33) H5c: Involvement significantly influences the relationship between trust and the online social network adoption. (Individual benefits are relationship maintenance and development, information and knowledge sharing, and use satisfaction; Positive emotions are alert, inspired, determined, attentive, and active) Model2. H9: Gender has a significant moderating effect on H6, H7, and H8. H9a(123): Gender significantly influences the relationship between the online social network adoption and individual benefits. H9b(12345): Gender significantly influences the relationship between negative emotions and the online social network adoption. H9c: Gender significantly influences the relationship between trust and the online social network adoption.. Model2. H10: Involvement has a significant moderating effect on H6, H7, and H8. H10a(123): Involvement significantly influences the relationship between the online social network adoption and Individual benefits. H10b(12345): Involvement significantly influences the relationship between negative emotions and the online social network adoption. H10c: Involvement significantly influences the relationship between trust and the online social network adoption. (Individual benefits are relationship maintenance and development, information and knowledge sharing, and use satisfaction; Negative emotions are upset, hostile, ashamed, nervous, and afraid). 26   .

(34) CHAPTER THREE RESEARCH METHOD. Based on the literature review in chapter two, this study argues that positive emotions, negative emotions, and trust are the factors that affect online social network adoption toward individual benefits. It also examines the moderating impact of gender and involvement on the relationships between independent and independent variables. This chapter consists of four parts: the first part is research models; the second part is population and sampling plan; the third part is measurement; and the forth part is data analysis techniques.. 3.1 Research Models. According to hypothesis 1 to 10 defined in chapter two, the research models are illustrated in Figure 3-1 and Figure 3-2. Model 1 contains the five major components: (1) Positive Emotions (PE), (2) Trust, (3) Online Social Network (OSN) Adoption, (4) Individual Benefits (IB), (5) moderators that are Gender and Involvement. There are also five major components in Model 2 which are (1) Negative Emotions (NE), (2) Trust, (3) Online Social Network (OSN) Adoption, (4) Individual Benefits (IB), and (5) moderators include Gender and Involvement.. In this study, research models include three independent variables: (1) the sub-factors of PE are Alert, Inspired, Determined, Attentive, and Active. (2) NE has five sub-factors including Upset, Hostile, Ashamed, Nervous, and Afraid. (3) Trust. The dependent variables are OSN adoption, and IB: Relationship Maintenance and Development, Information and Knowledge Sharing, and Use Satisfaction. Figure 3-1 and 3-2 are research models, and there are ten major hypotheses are defined accordingly, they are presented as follow. 27   .

(35) SOURCE: This Study;. Figure 3-1: Research Model 1 (The Group of Positive Emotions). 28   .

(36) SOURCE: This Study. Figure 3-2: Research Model 2 (The Group of Negative Emotions). 29   .

(37) 3.1.1 Hypotheses of Model 1 (The Group of Positive Emotions) H1:. Online social network adoption is significantly related to individual benefits. H1a: H1b: H1c:. H2:. Online social network adoption is significantly related to the relationship maintenance and development. Online social network adoption is significantly related to the information/ knowledge sharing. Online social network adoption is significantly related to the use satisfaction.. Positive emotions are significantly related to the online social network adoption. H2a: H2b: H2c: H2d: H2e:. H3: H4:. Alert is significantly related to the online social network adoption. Inspired is significantly related to the online social network adoption. Determined is significantly related to the online social network adoption. Attentive is significantly related to the online social network adoption. Active is significantly related to the online social network adoption.. Trust are significantly related to the online social network adoption. Gender has a significant moderating effect on H1, H2, and H3. H4a:. Gender significantly influences the relationship between the online social network adoption and individual benefits.. H4a1:. Gender significantly influences the relationship between the online social network adoption and the relationship maintenance and development. Gender significantly influences the relationship between the online social network adoption and information/ knowledge sharing. Gender significantly influences the relationship between the online social network adoption and the use satisfaction.. H4a2: H4a3:. H4b:. Gender significantly influences the relationship between positive emotions and the online social network adoption.. H4b1: H4b2: H4b3:. Gender significantly influences the relationship between the alert and the online social network adoption. Gender significantly influences the relationship between the inspired and the online social network adoption. Gender significantly influences the relationship between the determined and the online social network adoption. Gender significantly influences the relationship between the attentive and the online social network adoption. Gender significantly influences the relationship between the active and the online social network adoption.. H4b4: H4b5:. H4c:. H5:. Gender significantly influences the relationship between trust and the online social network adoption.. Involvement has a significant moderating effect on H1, H2, and H3. H5a:. Involvement significantly influences the relationship between the online social network adoption and Individual benefits.. H5a1:. Involvement significantly influences the relationship between the online social network adoption and the relationship maintenance and development. Involvement significantly influences the relationship between the online social network adoption and information/ knowledge sharing. Involvement significantly influences the relationship between the online social network adoption and the use satisfaction.. H5a2: H5a3:. H5b:. Involvement significantly influences the relationship between positive emotions and the online social network adoption.. H5b1:. Involvement significantly influences the relationship between the alert and the online social network adoption. Involvement significantly influences the relationship between the inspired and the online social network adoption. Involvement significantly influences the relationship between the determined and the online social network adoption. Involvement significantly influences the relationship between the attentive and the online social network adoption. Involvement significantly influences the relationship between the active and the online social network adoption.. H5b2: H5b3: H5b4: H5b5:. H5c:. Involvement significantly influences the relationship between trust and the online social network adoption. 30 .  .

(38) 3.1.2 Hypotheses of Model 2 (The Group of Negative Emotions) H6:. Online social network adoption is significantly related to individual benefits. H6a: H6b: H6c:. H7:. Online social network adoption is significantly related to the relationship maintenance and development. Online social network adoption is significantly related to the information/ knowledge sharing. Online social network adoption is significantly related to use satisfaction.. Negative emotions are significantly related to the online social network adoption. H7a: H7b: H7c: H7d: H7e:. H8: H9:. Upset is significantly related to the online social network adoption. Hostile is significantly related to the online social network adoption. Ashamed is significantly related to the online social network adoption. Nervous is significantly related to the online social network adoption. Afraid is significantly related to the online social network adoption.. Trust are significantly related to the online social network adoption. Gender has a significant moderating effect on H6, H7, and H8. H9a:. Gender significantly influences the relationship between the online social network adoption and individual benefits.. H9a1:. Gender significantly influences the relationship between the online social network adoption and the relationship maintenance and development. Gender significantly influences the relationship between the online social network adoption and information/ knowledge sharing. Gender significantly influences the relationship between the online social network adoption and the use satisfaction.. H9a2: H9a3:. H9b:. Gender significantly influences the relationship between negative emotions and the online social network adoption.. H9b1: H9b2:. Gender significantly influences the relationship between the upset and the online social network adoption. Gender significantly influences the relationship between the hostile and the online social network adoption. Gender significantly influences the relationship between the ashamed and the online social network adoption. Gender significantly influences the relationship between the nervous and the online social network adoption. Gender significantly influences the relationship between the afraid and the online social network adoption.. H9b3: H9b4: H9b5:. H9c:. H10:. Gender significantly influences the relationship between trust and the online social network adoption.. Involvement has a significant moderating effect on H6, H7, and H8. H10a:. Involvement significantly influences the relationship between the online social network adoption and Individual benefits.. H10a1:. Involvement significantly influences the relationship between the online social network adoption and the relationship maintenance and development. Involvement significantly influences the relationship between the online social network adoption and information/ knowledge sharing. Involvement significantly influences the relationship between the online social network adoption and the use satisfaction.. H10a2: H10a3:. H10b:. Involvement significantly influences the relationship between negative emotions and the online social network adoption.. H10b1:. Involvement significantly influences the relationship between the upset and the online social network adoption. Involvement significantly influences the relationship between the hostile and the online social network adoption. Involvement significantly influences the relationship between the ashamed and the online social network adoption. Involvement significantly influences the relationship between the nervous and the online social network adoption. Involvement significantly influences the relationship between the afraid and the online social network adoption.. H10b2: H10b3: H10b4: H10b5:. H10c:. Involvement significantly influences the relationship between trust and the online social network adoption. 31 .  .

(39) 3.2 Population and Sampling Plan. The population in this study focuses on the people who are experienced in using online social network. From January 1 to 31 in 2014, the questionnaire was available in online community that included Facebook, Twitter, Google+, Line, WeChat, and PPT.. Regarding the population of this study, it was assumed that the sample error was 0.1 and significance level was set to be 95%, and the valid returned rate was 0.7. This implied that there were at least about 400 questionnaires returned to meet these requirements. To increase the response rate, it was announced that 20 of the respondents who returned valid questionnaires win a 100-TWD voucher each based on a lucky draw activity.. 32   .

(40) 3.3 Measurement. A questionnaire was designed as the data collection instrument (see Appendixes). Before the questionnaires were uploaded in the online communities, a series of interviews with 20 individuals and 4 professors in the research areas of psychology, social network, and information management, this pre-test was conducted to make the questionnaires more understandable and readable for the subjects. Then, the operational definitions for variables and their sub-factors for this study are presented in Table 3-1 and Table 3-2.. The questionnaire was designed with five major parts: (1) positive emotions (PE), (2) negative emotions (NE), (3) online social network adoption, (4) individual benefits (IB), and (5) moderators. First, thirty items were developed for two variables in positive and negative emotions (Watson et al., 1986; Thompson, 2007). For example, an item “I perceive that I am generally inspired by my daily life.” is used for the variable of positive emotions.. Second, the variable of trust were developed into three questions to test the trust degree on OSN (Acquisti and Gross, 2006; George, 2006; Kornblum and Marklein, 2006; Dwyer et al., 2007; Jagatic et al., 2007; Sherchan, 2013), for example, the item “I use online social network to help my work/study (Discussion, contact, seeking and sharing information, etc.)”.. Third, for online social network adoption, there were three items developed for subjects who perceive that they like to adopt OSN by considering the arguments of Boyd and Ellison (2008), Donelan et al. (2010), and Dutton (2013). For example, the item “I use online social network to help my work/study” is used for this variable.. Fourth, this study also added the variable of individual benefits (Szymanski and Hise, 2000; 33   .

(41) Dalcher and Shine, 2003; Wixom and Todd, 2005; Zhang and Tanniru, 2005; Wasko and Faraj, 2005; Chiu et al., 2006; Yang and Chen, 2008; Boyd and Ellison, 2008; Donelan et al., 2010; Wang and Noe, 2010; Dutton, 2013), and developed nine items based on this variable. For example, the item “Overall, I am satisfied with the use of online social network.” is used for use satisfaction of individual benefits.. Finally, eight items for moderators: gender and involvement were used according to Sherif and Cantril (1947), Dutton et al. (1987), LaRose and Atkin (1988), Zaichkowsky (1994), Jeffres and Atkin (1996), Young (1999), Venkatesh et al. (2003), Lenhart and Madden (2007), Crunchies (2008), Zywica and Danowski (2008), Lenhart (2009), Pempek et al. (2009), and Hawkins and Mothersbaugh (2009). Each variable was measured based on the Likert five-digit rating scale (from 1 to 5) using bipolar descriptors for each question.. The basic information included age and education level. There are 51 questions in total for variables that were included in the research model. The data analysis was divided into three parts: (1) descriptive statistics, (2) reliability and validity analysis, and (3) structure equation model using partial least-square technique for hypothesis testing.. 34   .

(42) Table 3-1: Operational Definitions (I) Constructs. Positive Emotions. Negative Emotions. Sub-factors. Operational Definitions. Alert. Subjects perceive that they are alert.. Inspired. Subjects perceive that they are inspired.. Determined. Subjects perceive that they are determined.. Attentive. Subjects perceive that they are attentive.. Active. Subjects perceive that they are active.. Upset. Subjects perceive that they are upset.. Hostile. Subjects perceive that they are hostile.. Ashamed. Subjects perceive that they are ashamed.. Nervous. Subjects perceive that they are nervous.. Afraid. Subjects perceive that they are afraid.. Source. Watson et al., (1986) and Thompson (2007).. Watson et al., (1986) and Thompson (2007).. Acquisti and Gross (2006), George The degree that subjects trust online social (2006), Kornblum and Marklein (2006),. Trust. Dwyer et al. (2007), Jagatic et al. (2007),. network.. and Sherchan (2013). Online Social. Subjects perceive that they are continuously Boyd and Ellison (2008), Donelan et al.. Network Adoption Relationship maintenance and development Individual benefits. to use the online social network.. (2010), and Dutton (2013).. Subjects perceive that they use the online. Boyd and Ellison (2008), Donelan et al.. social network to help their relationships.. (2010), and Dutton (2013).. Information and Subjects perceive that they use online social Zhang and Tanniru (2005), Wasko and knowledge. network to share information and. Faraj (2005), Yang and Chen (2008),. sharing. knowledge is beneficial.. and Wang and Noe (2010).. Use satisfaction. Subjects perceive that they are satisfied with the use of online social network.. Szymanski and Hise (2000), Dalcher and Shine (2003), Wixom and Todd (2005), and Chiu et al. (2006). Dutton et al. (1987), LaRose and Atkin (1988), Jeffres and Atkin (1996), Young. Gender. (1999), Lenhart and Madden, (2007),. Male and Female.. Crunchies (2008), Zywica and Danowski (2008), Lenhart (2009), Pempek et al. (2009).. Involvement. The degree that subjects experience the use of online social network.. (1994), Venkatesh et al. (2003), and Hawkins and Mothersbaugh (2009).. 35   . Sherif and Cantril (1947), Zaichkowsky.

(43) Table 3-2: Operational Definitions (II) Constructs Positive Emotions. Sub-factors Alert Inspired Determined. Attentive Active Negative Emotions. Upset Hostile. PE101. PE102. PE103. PE201. PE202. PE203. PE301. PE302. PE303. PE401. PE402. PE403. PE501. PE502. PE503. NE101. NE102. NE103. NE201. NE202.. Ashamed Nervous Afraid Trust. NE203. NE301. NE302. NE303. NE401. NE402. NE403. NE501. NE502. NE503. TRU1. TRU2. TRU3.. OSN Adoption. OSN1. OSN2.. Individual Benefits. Relationship Information Satisfaction. Gender Involvement. OSN3. IB101. IB102. IB103. IB201. IB202. IB203. IB301. IB302. IB303. GEN1. GEN2. INV.. Question Items I perceive that I am generally alert in my daily life. I perceive that I am generally alert in my working or studying time. Overall, I perceive that I am generally on alert. I perceive that I am generally inspired by my daily life. I perceive that I am generally inspired by my work or study. Overall, I perceive that I generally feel inspired. I perceive that I am generally determined to do things in my daily life. I perceive that I am generally determined to do things in my working or studying time. Overall, I perceive that I am generally a determined person. I perceive that I am generally attentive in my daily life. I perceive that I am generally attentive in my working or studying time. Overall, I perceive that I am generally attentive. I perceive that I am generally active in my daily life. I perceive that I am generally active in my working or studying time. Overall, I perceive that I am generally an active person. I perceive that I am generally upset about my daily life. I perceive that I am generally upset about my work or study. Overall, I perceive that I generally feel upset. I perceive that I am generally hostile to people or things in my daily life. I perceive that I am generally hostile to people or things in my working or studying time. Overall, I perceive that I generally feel hostile. I perceive that I am generally ashamed of myself in my daily life. I perceive that I am generally ashamed of myself in my working or studying time. Overall, I perceive that I generally feel ashamed. I perceive that I am generally nervous in my daily life. I perceive that I am generally nervous in my working or studying time. Overall, I perceive that I am generally a nervous person. I perceive that I generally feel afraid in my daily life. I perceive that I generally feel afraid in my working or studying time. Overall, I perceive that I generally feel afraid. How confident are you with the people you contact in online social network? (Users, friends, classmates, co-works…etc.) How confident are you with the contents you contact in online social network? (Information, comments, opinions…etc.) How confident are you with the privacy security of online social network? I use online social network to share things of my daily life. (Thinking, feeling, daily things, activities…etc.) I use online social network to help my work/study. (Discussion, contact, seeking and sharing information… etc.) Overall, I am generally a user of online social network. I maintain good relationship with users in online social network. I develop new relationship with users in online social network. Overall, I have good relationship with users in online social network. For my daily life, I feel information/knowledge helpful in online social network. For my work/study, I feel information/knowledge helpful in online social network Overall, I feel information/knowledge beneficial in online social network. For my daily life, I am satisfied with the use of online social network. For my work/study, I am satisfied with the use of online social network. Overall, I am satisfied with the use of online social network. Male Female How many years have you been in online social network?. NOTES: OSN: Online Social Network; Relationship: Relationship Maintenance and Development, Information: Information and Knowledge Sharing, Satisfaction: Use Satisfaction.. 36   .

(44) 3.4 Data Analysis Techniques. This study conducts descriptive statistics, reliability and validity analysis, and also used the Structure Equation Model (SEM) to examine the path relationship by using the software of statistical techniques: Excel 2013, SPSS 21.0, and SmartPLS 2.0. Frist step, this study conducted descriptive statistics to describe samples and examine the frequent distribution, mean, variation, and percentage distribution.. Second, to confirm the internal reliability was consistent, Cronbach’s alpha was used for the factors. A higher alpha coefficient indicates a stronger interrelationship of each item, and also presents a higher internal consistency.. In third step, using the exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to derive the actual composites for the research models as well as their reliability and validity confirmation.. Finally, this study tested the hypotheses and utilized the structural equation model (SEM) to derive the relationships among factors, and also disclosed the moderating effect of gender and involvement on the relationships between variables.. 37   .

數據

Figure 1-1: Research Flow Chart Setting Research Motivations
Table 2-1: The Studies of Social Capital on SNSs
Table 2-2: The Summary of Emotions Studies on IT Use
Table 2-3: I-PANAS-SF used in studies
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