Interpersonal Social Influence (isi)

From the above literature, it is clear that interpersonal social influence (ISI) is an important construct and have a significant impact on mobile commerce adoption. The smartphone users will adopt m-app for shopping based on their internal circles Yang (2012) recommended to investigate the influence of social factors (i.e. internal and external factors separately) on m-shopping adoption. This study will investigate the effect of ISI on behavioral intention towards m-shopping app adoption.

External Social Influence (Esi)

External influence refers to ‘‘External influence refers to mass media reports, expert opinions, and other non-personal information considered by adopters in making a “rational” acceptance decision”, (Bhattacherjee, 2000, p. 413). Boakye (2015) examined determinants of mobile data service adoption among USA consumer wherein he found ESI to have an indirect positive relationship with BI. Yul (2014) examined determinants of mobile fitness application adoption among smartphone users of USA gym users by using extended TAM approach, wherein external subjective norm had no significant effect on mobile fitness application adoption. Tran and Corner (2016) investigated the effect of mass media and social media on MBAD, wherein they found both to have no significance among New Zealand consumers. Lee et al (2010) found ESI to have a positive influence on online consumption among USA young consumers. The external social influence was found to have no significant relationship with technology adoption in studies of Hsu and Chiu (2004).

Recently in India mobile shopping app promotion is being done through the use of mass media from a large e-commerce players such as Flipkart, Snapdeal, and Amazon. Around $173.2 million dollars were spent on mobile ads in the year 2015 by the Indian e-commerce firms and it is considered as one of the most important part of marketing strategy among Indian online channel partners (e-marketer report, 2016). Indian digital marketing spending is predicted to cross $1.32 billion in the year 2020 (e-marketer report, 2016). Mobile advertising would increase from current 2-4 % to more than 15% by the year 2020 (Deloitte TMT India Predictions 2016 report). The promotion is being done through the use of “Big App Day” to promote the mobile shopping app. Myntra, a fashion e-retailer, has shut their website and totally transformed their business to mobile apps. From the above literature, it is clear that external social influence (ESI) is an important construct and lacks in context of mobile commerce studies. The smartphone users will adopt m-app for shopping based on external influence (i.e. influence through mass media and other non-personal information). Yang (2012) recommended to investigate the influence of social factors (i.e. internal and external factors separately) on m-shopping adoption. This study will investigate the effect of ESI on behavioral intention towards m-shopping app adoption.

Facilitating Conditions (FC)

Facilitating condition is defined as “consumers’ perceptions of the resources and support available to perform a behaviour” (Venkatesh et al., 2012, p. 159). Facilitating conditions is one of the important construct of mobile technology adoption studies (Venkatesh et al., 2012; Slade et al., 2014; Slade et al., 2013; Baabdullah et al., 2013; Shao et al., 2011; Yaseen and Al-Omoush, 2014) and was found to have positive influence on BI (Faria et al., 2014; Raman and Don, 2013; Unyolo, 2013; Hew et al., 2015; Yang, 2010; Venkatesh et al., 2012; Alwahaishi and Snásel, 2013). Faqih and Jaradat (2015) explored factors that affect MCA using TAM3 model among 425 Jordanian consumers wherein they found PEC to have a significant positive effect on PEOU, which in turn has a positive influence towards INT. Yee (2015) in his thesis examined factors that affect mobile e-book adoption among 260 university students of Malaysia using UTAUT2 model wherein he found FC to have no significant impact on BI. Hew et al (2015) examined determinants of m-app usage among 288 Malaysian consumers using UTAUT2 model wherein FC was found to have a significant positive impact on BI.

Mishra (2014) examined factors that affect acceptance of MCA, among 234 Indian consumers using TPB approach wherein he found PBC to have a significant positive impact on INT. Kit (2014) examined the influence of UTAUT2 constructs on m-app adoption among 300 Malaysian students wherein he found FC to have no major impact on BI. Faria et al (2014) investigated the factors that affect internet adoption through smartphone among 173 Brazilian smartphone users using UTAUT2 model wherein they found FC to have a significant positive impact on BI. Gitau and Nzuki (2014) conceptualized factors that determine m-commerce adoption among online users wherein they stated that perceived behavioural control will affect MCA. Zhong (2013) studied factors affecting mobile shopping satisfaction among 390 general Chinese consumers wherein Perceived behaviour control was found to have a significant positive relationship with mobile satisfaction. Alwahaishi and Snásel (2013) examined factors that affect ICT adoption among 238 KSA mobile users using UTAUT and Flow theory wherein they found FC to have a significant positive impact on BI. Chong (2013) examined factors that affect MCA, among 140 Chinese online users using UTAUT model wherein he found FC to have no significant effect on BI. Yang and Forney (2013) examined mediating effect of consumer technology anxiety in mobile shopping adoption among 400 USA mobile users by applying the UTAUT model wherein they found the effect of FC increase with a decrease in ANX towards m-shopping. Kim et al (2011) investigated the factors that affect MCA, among 1016 South Korean consumers wherein they found PBC to have a significant positive impact on INT. Yang (2010) examined factors affecting mobile shopping services adoption among 400 US online shopping consumers wherein FC was found to have a significant impact on mobile shopping adoption. Song (2009) explored factors affecting the purchase of music products through mobile commerce among 201 USA consumers using UTAUT as a base model wherein FC was found to have no significant impact on INT. Park et al (2007) explored the factors that affect MTA among 221 Chinese consumers using UTAUT wherein they found FC to have no significant impact on INT.