Organizations have been spending an increasing amount on IT, and their budgets have continued to rise, even in the face of potential economic downturns. However, fears about economic conditions and increasing competition create the pressure to cut costs, which requires organizations to measure and examine the benefits and costs of technology. Naturally, organizations are interested in knowing the return on these investments. The effects of IT are often indirect and influenced by human, organizational, and environmental factors. Thus, the measurement of IS success is both difficult and elusive. A plethora of utilitarian ISs are used in organizations, such as decision support systems, computer-mediated communications, HISs, e-commerce, knowledge management systems, as well as a number of others (Kanaracus, 2008; S. Petter, DeLone, & McLean, 2008).
The literature review in this section presents the DeLone & McLean success model and the important factors for the success of IT application in any sector. Moreover, this section describes the relationship between acceptance and success by discussing relevant studies. To measure the success of various IT, organizations have been moving beyond traditional financial measures. In an effort to understand the tangible and intangible benefits of their ISs better, organizations have turned to methods such as balanced scorecards (R. S. Kaplan & Norton, 1996) and benchmarking (P.B. Seddon, Graeser, & Willcocks, 2002). Researchers have created models for success (Ballantine et al., 1996; W.H. DeLone & McLean, 1992; Peter B Seddon, 1997), which emphasize the need for better and more consistent success metrics.
According to Petter et al. (2008), researchers have derived a number of models to explain what makes some ITs “successful” (S. Petter, et al., 2008). TAM, which was created by Davis (1989), uses the TRA to explain why some ISs are more readily accepted by users than others (Fred D Davis, 1989; Fishbein, 1975). However, acceptance is not equivalent to success, although the acceptance of an IT is a necessary precursor to success. Early attempts to define the success of IT were ill defined because of the complex, interdependent, and multi-dimensional nature of IT success. To address this problem, DeLone and McLean (1992) performed a review of research published from 1981 to 1987 and created a taxonomy of IT success based on this review.
DeLone and McLean (1992) identified six variables or components of IS success: system quality, information quality, use, user satisfaction, individual impact, and organizational impact. These six variables are interdependent. Figure 2.3 shows this original IS success model (W.H. DeLone & McLean, 1992).
Figure 2.3: DeLone & McLean IS success model (1992)
Shortly after the publication of the DeLone & McLean success model, IS researchers began to propose modifications to this model. Accepting the call of the authors for “further development and validation”, Seddon and Kiew (1996) studied a portion of the IS success model (i.e., system quality, information quality, use, and user satisfaction) (P.B. Seddon & Kiew, 1996). In their evaluation, they modified the construct and use because they “conjectured that the underlying success construct that researchers have been trying to tap is Usefulness, not Use.” The concept of usefulness by Seddon and Kiew is equivalent to the idea of perceived usefulness in the TAM (1989) (F.D. Davis, Bagozzi, & Warshaw, 1989). They argued that, for voluntary systems, use is an appropriate measure; however, if system use is mandatory, usefulness is a better measure of IS success than use. DeLone & McLean (2003) responded that, even in mandatory systems, the considerable variability of use can still exist and, therefore, use deserves to be retained as a variable.
Since the introduction of the DeLone & McLean model in 1992, a number of studies have empirically tested and validated relationships within the model (Rai, Lang, & Welker, 2002), and discussed its practical applications (Bossen, Jensen, & Udsen, 2013; Goodhue & Thompson, 1995; Peter B Seddon, 1997). According to the study by Seddon (1997), the DeLone & McLean success model was confusing in its original form, partly because both process and variance models were combined within the same
framework (Peter B Seddon, 1997). In the years that followed, several modifications were proposed to develop the DeLone & McLean model (1992). It was applied in different fields such as knowledge management (Jennex, Olfman, Panthawi, & Park, 1998; Kulkarni, Ravindran, & Freeze, 2007), e-commerce (William H Delone & Mclean, 2004) and healthcare IT (Bossen, et al., 2013; Pai & Huang, 2011; Van Der Meijden, Tange, Troost, & Hasman, 2003). DeLone and McLean (2003) reviewed empirical studies that had been performed during the years since 1992 and revised the original model accordingly; the updated 2003 model proposes that IS success includes seven dimensions: information quality, system quality, service quality, use, intention to use, user satisfaction, and net benefits. Figure 2.4. Shows the Delone & McLean update model (2003).
Figure 2.4: DeLone and McLean model (2003)
This updated IS success model integrated this recommendation (Pitt, Watson, & Kavan, 1995) to include service quality as a construct. Another update to the model addressed the criticism that an IS can affect levels other than the individual and organizational levels. Given that IS success affects workgroups, industries, and even societies (B. L. Myers, Kappelman, & Prybutok, 1997; P.B. Seddon, Staples, Patnayakuni, & Bowtell, 1999), DeLone and McLean replaced the variables, individual impact, and organizational impact with net benefits, thereby accounting for benefits at multiple
levels of analysis. The constructs of the updated DeLone & McLean IS success model are as follows:
1) System Quality: Performance of the IS in terms of reliability, convenience, ease of use, functionality, and other system metrics (William H. Delone & McLean, 2003; S. Petter, et al., 2008; Stacie Petter & McLean, 2009).
2) Information Quality: Characteristics of the output offered by the IS, such as accuracy, timeliness, and completeness (William H. Delone & McLean, 2003; S. Petter, et al., 2008; Stacie Petter & McLean, 2009).
3) Service Quality: Support of users by the IS department, often measured by the responsiveness, reliability, and empathy of the support organization (S. Petter, et al., 2008; Pitt, et al., 1995).
4) Intention to Use: Expected future consumption of an IS or its output (Stacie Petter & McLean, 2009).
5) Use: Consumption of an IS or its output described in terms of actual or self- reported usage
6) User satisfaction: Approval or likeability of an IS and its output (William H Delone & Mclean, 2004; Ives, Olson, & Baroudi, 1983; Stacie Petter & McLean, 2009).
7) Net benefits: The effect of an IS on an individual, group, organization, industry, society, etc., which is often measured in terms of organizational performance, perceived usefulness, and effect on work practices (Stacie Petter & McLean, 2009).
The literature review in this section covers the factors of IS success in different fields. An important way of measuring IS success is how much the system is accepted and used by users. The Delone & McLean model (2003) provides significant factors that indicate the acceptance and success of a technology. Reflecting on this debate, the
Delone & McLean (2003) model clarified the Use construct. They note that, “Use must precede ‘user satisfaction’ in a process sense, but positive experience with ‘use’ will lead to greater ‘user satisfaction’ in a causal sense.” According to the authors, given the variability of IS and their contexts, measuring the Intention to Use (an attitude) may be more appropriate than measuring Use (a behaviour). They went on to state that if Intention to Use was a measure, then increased User Satisfaction would lead to a higher Intention to Use, which would subsequently affect Use. This resulted in the addition of Intention to Use in the updated model.