A probabilistic model for predicting service level adherence of application support projects

Srijith Sreenivasan and Manimaran Sundaram

International Journal of Productivity and Quality Management, 2018, vol. 25, issue 3, 305-330

Abstract: Application support projects are those which maintain the operations of software in production environment. Service level adherence is a key outcome metric which monitors the contractual compliance of these projects with customers. This paper discusses an approach to develop a prediction model using process factors impacting service level adherence. These factors are derived from the processes and sub-processes having a logical relationship with the outcome. A total of 23 factors were considered initially for modelling, of which six were found to be statistically significant. The model, developed using regression and Monte Carlo simulation, is validated in an actual industrial project to ensure its accuracy. The model can be used in application support projects to arrive at timely decisions for suitable mid-course corrections to control service level adherence.

Keywords: application support; software maintenance; service level adherence; SLA; prediction model; regression analysis; Monte Carlo simulation; model validation. (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=95648 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpqma:v:25:y:2018:i:3:p:305-330

Access Statistics for this article

More articles in International Journal of Productivity and Quality Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().