What Predicts Commercial Bank Leaders’ Intention to Use Mobile Commerce?: The Roles of Leadership Behaviors, Resistance to Change, and Technology Acceptance Model

What Predicts Commercial Bank Leaders’ Intention to Use Mobile Commerce?: The Roles of Leadership Behaviors, Resistance to Change, and Technology Acceptance Model

Maddy Halbach (Howard County Public Schools, USA) and Tao Gong (University of Maryland Eastern Shore, USA)
Copyright: © 2011 |Pages: 19
DOI: 10.4018/jeco.2011070101
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Abstract

The purpose of this study was to investigate the roles leadership behaviors have on technology acceptance models, focusing on bank leaders’ intention to use mobile-commerce. The study included responses from 101 senior-level managers working at FDIC-insured commercial banks in the United States. Three instruments including Kouzes and Posner’s (1987) leadership practice inventory (LPI), Wu and Wang’s (2005) mobile commerce technology acceptance model (MC-TAM), and Oreg’s (2003) resistance to change model (RTC) were employed. A correlation analysis revealed that two transformational leadership behaviors—model the way and enabling others to act—positively relate to behavioral intent to use mobile commerce. A regression analysis found that perceived compatibility, perceived usefulness, and perceived ease of use are positively related to the behavioral intent to use m-Commerce. However, the authors found that the RTC and LPI model cannot predict the willingness to use m-Commerce.
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Introduction

Banking and financial sectors have recently been impacted by the economic downturn and disruption to credit markets. This has forced banks to reduce costs and attempt to operate more efficiently to increase profits in a depressed market. Research has shown that the implementation of new information technology (IT) platforms and products can assist with these issues (Casolaro & Gobbi, 2007). The banking industry is one of the leaders in implementing new technologies because of how the industry has grown and adapted to governmental regulations, competition, and market demand. According to Roster (2009), the banking industry has already spent $558.4 billion globally on information technology (IT) systems, with the annual growth rate expecting to be 3.7 percent.

The banking industry was heavily regulated from the 1950s through the 1970s until governmental regulatory changes between 1979 and 1994 allowed banks to expand their physical presence across state lines (Polski, 2000). Deregulation also allowed new “entrants such as GE Capital, [and] Ford finance” (Holland & Westwood, 2001, p. 53) to enter the market, causing a decline in profitability for banks and forcing them to become more competitive through increased efficiency obtained by relying heavily on technology. By the late 1980s IT became a very apparent strategic necessity for banks (Berger, 2003; Brady & Targett, 1995; Davamanirajan, Mukhopadhyay, & Kriebel, 2002), causing the commercial banking industry to spend $11.6 billion on IT by 1988, and it has since continuously spent heavily in this area (Bielski, 2007).

Through technology the banking industry reduced the cost of daily operations by 1.3 to 2 percent (Casolaro & Gobbi, 2007). A study by Hayes and Thompson (2000) found a 7-to-9 percent increase in productivity through the use of automatic teller machines (ATMs) instead of human tellers, while Holden and El-Bannany (2004) documented that ATMs reduced the cost of each teller transaction from $1.04 to 27 cents.

The banking industry began investing in Internet-based financial transactions and products during the early 1990s, with CitiBank being the first bank to register its domain for a Web site in 1991. By 1996 banks began to include transactional banking services (Yadav, Prabhu, & Chandy, 2007). Since 1996 electronic banking (e-banking) and online banking has become the norm in the banking industry, and it has enabled banks to offer products more conveniently to customers (Daks, 2008). E-banking is defined by a variety of technological platforms including: Internet banking, telephone banking, and TV-based banking (Lustsik, 2004). Products on these platforms include: direct deposits, ATM cards, debit cards, preauthorized debits, automatic phone systems, computer banking, smart cards, and prepaid cards. These products reduce the cost of human-based processing for banks even more (Anguelov, Hilgert, & Hogarth, 2004).

Mobile commerce (or m-commerce) is currently one of the marketplace’s latest technological platforms (Marcus, 2010). It is defined as “the exchange or buying and selling of commodities, services, or information on the Internet through the use of mobile handheld devices” (Hu, Lee, & Yeh, 2004, pp. 1-2). Bielski (2007) states the convergence of “previously delivered [electronic products] on discrete end-user-devices” (p. 45), will have a direct impact on the banking industry, and he cites mobile banking as one of these new end-user devices. Mobile banking allows customers to access their accounts from a cell phone or other hand-held device (Daks, 2008), and according to Valentine (2011), is expected to have widespread use within the next 6 years. Mobile banking could also reduce the cost of banking transactions even more than previously stated (“ClairMail powers retail banking”, 2006; “Product focus”, 2006; Siddhartha, Rik, & Sanjay, 2011).

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