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
24
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
25
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.
26
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)
27
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.