Assessing information systems success: a respecification of the DeLone and McLean model to integrating the perceived quality

  • Received October 12, 2017;
    Accepted November 1, 2017;
    Published March 22, 2018
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/ppm.16(1).2018.34
  • Article Info
    Volume 16 2018, Issue #1, pp. 348-360
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DeLone and McLean (1992) model of information systems success has received much attention amongst researchers. This study aimed to respecify and validate the DeLone and McLean model (2003) by proposing a social exchange theory for underlying changes in the direction of perceived quality and adding perceived value variables suggested by Wang (2008). The purpose of this study was to obtain a better understanding of information system of the user perception when using organization’s information systems. Therefore, a model for testing the information systems success was formed.
The primary data used in this study were collected from 102 respondents who apply accounting software in their companies (end-user computing). Companies that were used as samples in this study were the ones that created or developed accounting software by themselves. 27 questionnaires were obtained by mail survey accompanied with a contact-person approach.
All of the hypotheses tested were found to be significantly supported. The model provided strong support for the relationships between perceived quality, perceived value, user satisfaction, and net benefits. Information and system quality has been shown as a proxy that affects service quality. Information quality, system quality, and service quality cause the formation of perceived value and, then, this perceived value will affect user satisfaction and net benefits. The characteristics of information systems are an important aspect that researchers should concern when testing the information systems success.

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    • Figure 1. DeLone and McLean (2003) updated IS success model
    • Figure 2. The research model of e-commerce systems success
    • Figure 3. The research model
    • Table 1. Value of factor loading the observed variable
    • Table 2. AVE and communality
    • Table 3. Root of AVE and latent variable correlation
    • Table 4. Hypotheses testing results