Activity system of the Business Model

Our work is related to omni-channel studies that investigate consumer behav-ior between the online and offline channels in the financial services and retailing contexts.

3.2.1. Online Banking Adoption in Omni-channel Financial Services

The explosive evolution of online banking in the last decade has spurred re-searchers to examine customer channel preferences and banking behavior before and after adopting the new channel. Hitt and Frei (2002) explore the demograph-ical differences between online banking users and traditional channel users and find that customers in the former group are more profitable and have higher reten-tion. Xue et al. (2007) incorporate channel usage and find that higher consumer efficiency in the online channel results in greater banking profitability. Xue et al.

(2011) further investigate the drivers of online banking adoption and point to

47 higher transaction demand, consumer efficiency and local penetration as the pri-mary motivations. They also find that customers significantly increased their banking activities, acquired more products and conducted more transactions after adopting online banking.

Campbell and Frei (2009) focus on customer channel preferences after online banking adoption and identify substitution effects of online banking on self-service channels, including automated teller machines (ATMs) and voice response units (VRUs), and augmentation effects on human-service channels, including branches and call centers. They suggest that substitution is most likely to happen between channels offering a similar mix of services, such as online banking and self-service channels. On the other hand, the improved financial controls after online banking adoption will improve customers’ willingness to access all the available service channels and, consequently, increase the transaction volumes through other channels. Hernando and Nieto (2006) support this finding through their firm-level analysis and find that banks use online banking as a complement instead of a substitute for physical branches.

3.2.2. Relationship between Online and Offline Channels in Omni-channel Retailing

The phenomenon of omni-channel retailing has received significant academic attention due to the availability of retail data and the relatively better channel inte-gration. Studies in this context focus on quantifying the pressure on physical stores with the introduction of the online channel. Deleersnyder et al. (2002) ex-plore newspaper data and suggest that the general concerns about cannibalization with online channel implementation are overstated. Similarly, Biyalogorsky et al.

(2003) analyze data from Tower Records and conclude that the addition of the

48 online channel did not significantly substitute sales away from offline channels, but contributed to amplifying the share of purchase overall. Ansari et al. (2008) also supports this positive effect of online channel usage on merchant sales. The underlying reasons for this effect involve the small overlap between online chan-nel users and physical store visitors, as well as more active interactions between customers and retailers through the added online channel. Thus, transactions through physical stores are less likely to be substituted away but are more likely to have synergistic growth with the introduction of the online channel.

Several papers discuss the impact of physical store entries on customer chan-nel preferences. They consistently find that the presence of a physical retail store increases store sales (Avery et al. 2012; Bell et al. 2015; and Kumar et al. 2014), due to the reduced transaction costs (e.g., transportation cost, time cost, uncertain-ty, etc.) and increased accessibility to the physical facilities. However, the prior literature does not offer clear results about the impact of physical store entry on the online channel. Some papers suggest that the large online disutility cost and decreased distance to offline stores will shape customers’ choice to switch from the online channel to physical stores after store entries. For example, Forman et al.

(2009) study sales of online and physical book stores and find that when a physi-cal store opened lophysi-cally, customers substituted away from online purchasing. Oth-er studies empirically identify increased online purchases aftOth-er physical store en-tries (Avery et al. 2012; Bell et al. 2015, Kumar et al. 2014). They suggest that higher exposure to retail stores reduces the customers’ risks of purchasing online by providing them a physical place for product evaluation and after-sale trouble resolution. It also strengthens brand awareness and customer loyalty, which might transfer to other channels as a halo effect (Jacoby et al. 1984; Keller 1993; Kwon

49 et al. 2009).

The prior research generally starts with the online channel and looks at its im-pact on customer channel choices and other behavior. But studies that focus on physical facility networks are not sufficient. Although some papers in the retailing context investigate the physical store entries, their results on how customers be-have after the opening of a local store are unclear. Plus, none of the prior research analyzes the effects of store closures, which is also important because banks and retailers are closing their physical stores more aggressively than they are opening new ones. Moreover, consumer behavior in omni-channel financial services may be largely different from that in the retail setting, due to the more complex chan-nel system and the lower level of chanchan-nel integration for products and services.

Thus, our work aims to complement the existing literature by exploring customers’

omni-channel usage, as well as account opening and closing behavior after physi-cal facility network changes occur.