Assessing call centers’ success: A validation of the DeLone and Mclean model for information system

• Published in: Egyptian informatics journal Vol. 14; no. 2; pp. 99 - 108
• Main Authors: Baraka, Hesham A., Baraka, Hoda A., EL-Gamily, Islam H.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.07.2013
• Subjects: Call centers indicators; Call centers system (CCS); Composite indicators; DeLone and McLean; Information systems evaluation; Composite indicators; Call centers system (CCS); DeLone and McLean; Information systems evaluation; Call centers indicators
• ISSN: 1110-8665; 2090-4754
• DOI: 10.1016/j.eij.2013.03.001

Business process outsourcing (BPO) is becoming one of the most growing industries in 21st Century and a significant workforce in the global economy. Revolution in telecommunications, free trade agreements, and cultural behavior in a number of developing countries paved the way for the growth of BPO industry. Technology based BPO services are those services provided by Call centers, services that vary from receiving simple phone calls, to marketing services, sales services, and up to remote diagnosis and technical support services. This paper introduces a model to evaluate the performance of call centers based on the Delone and McLean Information Systems success model. A number of indicators are identified to track the call center’s performance. Mapping of the proposed indicators to the six dimensions of the D&M model is presented. A Weighted Call Center Performance Index is proposed to assess the call center performance; the index is used to analyze the effect of the identified indicators. Policy-Weighted approach was used to assume the weights with an analysis of different weights for each dimension. The analysis of the different weights cases gave priority to the User satisfaction and net Benefits dimension as the two outcomes from the system. For the input dimensions, higher priority was given to the system quality and the service quality dimension. Call centers decision makers can use the tool to tune the different weights in order to reach the objectives set by the organization. Multiple linear regression analysis was used in order to provide a linear formula for the User Satisfaction dimension and the Net Benefits dimension in order to be able to forecast the values for these two dimensions as function of the other dimensions