Application Maintenance Offshoring Using HCI Based Framework and Simple Multi Attribute Rating Technique (SMART)

Over the last two decades, the rapid expansion of the Internet has prompted a growing number of enterprises to deploy their work globally. Companies are increasingly reliant on software systems, which need ongoing modification, maintenance, and upgrades. The maintenance phase consumes approximately...

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Veröffentlicht in:IEEE access 2023, Vol.11, p.107068-107084
Hauptverfasser: Rahman, Hanif Ur, Alzayed, Asaad, Mohmand, Muhammad Ismail, Albarrak, Abdullah M., Qasem, Sultan Noman
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Sprache:eng
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Zusammenfassung:Over the last two decades, the rapid expansion of the Internet has prompted a growing number of enterprises to deploy their work globally. Companies are increasingly reliant on software systems, which need ongoing modification, maintenance, and upgrades. The maintenance phase consumes approximately 80% of the total software budget. Hence, companies have been eagerly looking for offshore outsourcing of these software systems. Choosing the best sourcing model for software maintenance projects remains elusive and challenging due to a variety of technological, social, and political factors. This study aims to analyze application maintenance offshoring related factors and addresses its decision-making process. To achieve the study objectives, factors of two datasets are analyzed based on standard deviation, mean and mean error. The Critical Success Factors (CSFs) are examined thoroughly to explore their impact on decision-making process. Additionally, the study proposes a sourcing framework based on CSFs that uses the Human Computer Interaction (HCI) principles. This framework assists clients and vendors to evaluate the projects prior to offshoring decisions. To enhance decision-making process, a case study is conducted in the Information Technology (IT) industry and the Simple Multi Attribute Rating Technique (SMART) is applied. As the results show, SMART ranks the available options and helps in making effective offshoring decisions.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2023.3320941