2.4. Previous studies on mobile commerce in a Vietnam and international context
2.4.3. Individual difference variables in mobile commerce research and
Personality refers to an individual’s unique internal traits (Walczuch and Lundgren, 2004). Previous studies have introduced a wide range of personality traits that affect consumer behavior (Parks-Leduc et al., 2015). Among them, the Big Five is a very popular and widely accepted paradigm (Barrick, Mount and Judge, 2001, Costa and McCrae, 1992). Accordingly, it is argued that personality traits include five factors: extraversion, agreeableness, openness to new experience, conscientiousness, and neuroticism. Adopting Big Five personality traits paradigm, Walczuch and Lundgren (2004) discuss and test the impact five factors on trust while Devaraj et al.
(2008) investigate the influence of these five factors on the acceptance of a collaborative technology and Junglas et al. (2008) find agreeableness, extraversion, emotional stability, openness to experience, and conscientiousness have effects on the adoption of location-based services.
Personal innovativeness refers to the tendency of an individual to try out new things, products or services. Previous studies have demonstrated that individual difference in innovativeness has a strong and positive effect on information technology and information system adoption (Agarwal and Prasad, 1998, Citrin et al., 2000, Zhang et al., 2012). This is because innovative individuals are more likely to positive perceptions of innovations and thus, are more likely to have the intention to use new technology and commerce (Lu, 2014, Lu et al., 2005). Personal innovativeness is widely used in literature to predict the adoption of a wide range of innovative technologies, including Internet banking (Aldás-Manzano, Lassala-Navarré, Ruiz- Mafé and Sanz-Blas, 2009a, Aldás-Manzano, Ruiz-Mafe and Sanz-Blas, 2009b),
mobile services (Kuo and Yen, 2009, Zarmpou, Saprikis, Markos and Vlachopoulou, 2012) such as mobile payment (Kim, Mirusmonov and Lee, 2010a) and mobile marketing (Bauer, Reichardt, Barnes and Neumann, 2005) and wireless Internet services (Lu et al., 2005). For example, Limayem, Khalifa and Frini (2000) prove that personal innovativeness is positively related to the adoption of Internet shopping while Citrin et al. (2000) find that this variable has a positive association with Internet shopping. In the domain of mobile commerce, personal innovativeness is also extensively use to explain intention to use mobile commerce (Aldás-Manzano et al., 2009a, Aldás-Manzano et al., 2009b)
Propensity to trust refers to the general willingness to trust others while trust is considered as “the willingness of a party to be vulnerable to the actions of another party based on the expectation that the others will perform a particular action important to the trustor, irrespective of the ability to monitor or control that other party” (Mayer, Davis and Schoorman, 1995, p. 712). Mayer et al. (1995) argue that individuals trustworthiness of others is a function of their beliefs in the ability (i.e., knowledge, skills, and competencies), benevolence (i.e., the trustor believes the trustee will act in the best interest of trustor), and integrity (i.e., the trustor perceives the trustee as acting according to acceptable principles). Previous studies have demonstrated that propensity to trust is a key factor that effecting consumer behavior in an online context (Bianchi and Andrews, 2012, Lin, Wang, Wang and Lu, 2013, Luo et al., 2010, Zhou and Lu, 2011).
Also, prior studies also examine the impact of affinity, and compatibility (Aldás- Manzano et al., 2009b), individual playfulness and optimum stimulation level (Mahatanankoon, 2007). In summary, individual difference variables are promising factors determining consumer behavior in an online context. However, the role of consideration of future consequences is largely ignored in this context, generating an uncomprehensive picture of how these variables are related to online behavior.
According to Joireman and King (2016), there were over 125 studies that have adopted CFC to explain a wide range of behavior in different domains such as health
behavior, financial decision-making, work behavior, ethical decision-making in organizational contexts and environmental decision-making. Also, the integration of consideration of future consequences into proposed research models in increasing, indicating that this variable is an interesting factor that has an important role in explaining and predicting individual behavior (Olsen and Tuu, 2017, Pozolotina and Olsen, 2019)
Health behavior is one of the most heavily studied areas within the consideration of future consequences context. For example, healthy consumption studies have demonstrated that individuals with level of CFC to are more likely to perform healthy behavior such as eating healthy and avoiding smoking and consuming alcohol (Adams and Nettle, 2009, Beenstock, Adams and White, 2011, Rappange, Brouwer and van Exel, 2009, Strathman et al., 1994). Also, in this area, individuals who are high in CFC have a tendency to perform preventive actions to prevent negative consequences such as exercise (Joireman et al., 2012) to get better sleep (Peters, Joireman and Ridgway, 2005). Besides, they are more likely to get H1N1 vaccine uptake (Nan and Kim, 2014) and accept human papillomavirus vaccination for their daughter (Morison, Cozzolino and Orbell, 2010). They are also more concerned about preventing past illnesses from reoccurring (Sirois, 2004) and managing blood sugar by taking insulin (Louch, Dalkin, Bodansky and Conner, 2013). Finally, previous studies have also demonstrated that CFC is related to physical and mental health as well as subjective well-being outcomes. For example, individuals with high CFC have lower body mass indexes (Adams and Nettle, 2009). Also, those high CFC predict higher satisfaction with life (Azizli, Atkinson, Baughman and Giammarco, 2015) and higher positive affect and optimism (Geers, Wellman, Seligman, Wuyek and Neff, 2010).
In the financial decision-making domain, individuals with a higher level of CFC are less likely to buy impulsively (Joireman, Sprott and Spangenberg, 2005) and compulsively (Joireman et al., 2010). Also, they have a lower level of temporal discounting (Joireman et al., 2008), problematic gambling (Toplak, Liu, Macpherson, Toneatto and Stanovich, 2007) or credit card debt (Joireman et al., 2010). Work-related
behavior is an interesting domain that recently adopts CFC in explaining behavior. In particular, Graso and Probst (2012) have demonstrated that individuals with higher level of CFC have tendency to prioritize quality of work over quantity of work while Probst, Graso, Estrada and Greer (2013) have shown that those high in CFC have higher motivation for safety-related behaviors, which in turn leads to fewer on-the-job injuries. Past studies have also demonstrated a link between CFC and pro- environmental decisions (Milfont, Wilson and Diniz, 2012). Individuals with a higher level of CFC are more likely to conduct recycle behaviors (Strathman et al., 1994), participate in pro-environmental political actions (Carmi and Arnon, 2014). Those high in CFC also have a tendency to value and postulate concern about the environment (Arnocky et al., 2013)
In summary, although a large amount of studies has adopted CFC to explain a wide range of behavior in different areas, there exists a lack of studies linking CFC with consumer behavior in a mobile commerce context. This study, therefore, aims at filling the gap by discussing and testing the role of CFC in explaining continuance intention to use mobile commerce.