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Using enterprise architecture and technology adoption models to predict application usage
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.ORCID iD: 0000-0002-6590-6634
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2012 (English)In: Journal of Systems and Software, ISSN 0164-1212, Vol. 85, no 8, 1953-1967 p.Article in journal (Refereed) Published
Abstract [en]

Application usage is an important parameter to consider in application portfolio management. This paper presents an enterprise architecture analysis framework which can be used to assess application usage. The framework, in the form of an architecture metamodel, incorporates variables from the previously published Technology Acceptance Model (TAM) and the Task-Technology Fit (TTF) model. The paper describes how the metamodel has been tailored for a specific domain, viz, industry maintenance management. The metamodel was tested in the maintenance management domain through a survey with 55 respondents at five companies. Data collected in the survey showed that the domain-specific metamodel is able to explain variations in maintenance management application usage. Integrating the TAM and TTF variables with an architecture metamodel allows architects to reuse research results smoothly, thereby aiding them in producing good application portfolio decision-support.

Place, publisher, year, edition, pages
2012. Vol. 85, no 8, 1953-1967 p.
Keyword [en]
Enterprise architecture, Architecture analysis, Technology Acceptance Model, Task-Technology Fit, Maintenance management, Computerized Maintenance Management Systems, Metamodel, Application portfolio management
National Category
Computer Systems Software Engineering
URN: urn:nbn:se:kth:diva-98916DOI: 10.1016/j.jss.2012.02.035ISI: 000305109300018ScopusID: 2-s2.0-84861346426OAI: diva2:540940
QC 20120712Available from: 2012-07-12 Created: 2012-07-05 Last updated: 2012-09-12Bibliographically approved
In thesis
1. Enterprise Architecture for Information System Analysis: Modeling and assessing data accuracy, availability, performance and application usage
Open this publication in new window or tab >>Enterprise Architecture for Information System Analysis: Modeling and assessing data accuracy, availability, performance and application usage
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Decisions concerning IT systems are often made without adequate decision-support. This has led to unnecessary IT costs and failures to realize business benefits. The present thesis presents a framework for analysis of four information systems properties relevant to IT decision-making. The work is founded on enterprise architecture, a model-based IT and business management discipline. Based on the existing ArchiMate framework, a new enterprise architecture framework has been developed and implemented in a software tool. The framework supports modeling and analysis of data accuracy, service performance, service availability and application usage. To analyze data accuracy, data flows are modeled, the service availability analysis uses fault tree analysis, the performance analysis employs queuing networks and the application usage analysis combines the Technology Acceptance Model and Task-Technology Fit model. The accuracy of the framework's estimates was empirically tested. Data accuracy and service performance were evaluated in studies at the same power utility. Service availability was tested in multiple studies at banks and power utilities. Data was collected through interviews with system development or maintenance staff. The application usage model was tested in the maintenance management domain. Here, data was collected by means of a survey answered by 55 respondents from three power utilities, one manufacturing company and one nuclear power plant. The service availability studies provided estimates that were accurate within a few hours of logged yearly downtime. The data accuracy estimate was correct within a percentage point when compared to a sample of data objects. Deviations for four out of five service performance estimates were within 15 % from measured values. The application usage analysis explained a high degree of variation in application usage when applied to the maintenance management domain. During the studies of data accuracy, service performance and service availability, records were kept concerning the required modeling and analysis effort. The estimates were obtained with a total effort of about 20 man-hours per estimate. In summary the framework should be useful for IT decision-makers requiring fairly accurate, but not too expensive, estimates of the four properties.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2012. xiii, 41 p.
Trita-EE, ISSN 1653-5146 ; 2012:035
Enterprise Architecture, Metamodeling, Decision-making, Data Accuracy, Service Availability, Service Performance, Technology Acceptance Model, Task Technology Fit
National Category
Information Systems
urn:nbn:se:kth:diva-101494 (URN)978-91-7501-444-9 (ISBN)
Public defence
2012-09-17, F3, Lindstedtsvägen 26, KTH, Stockholm, 10:00 (English)

QC 20120912

Available from: 2012-09-12 Created: 2012-08-29 Last updated: 2013-01-28Bibliographically approved

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Närman, PerHolm, HannesHöök, DavidHoneth, NicholasJohnson, Pontus
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