Empirical Investigation Of Influencing Factors Regarding Offshore Outsourcing Decision Of Application Maintenance

IEEE ACCESS(2021)

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摘要
Global Software Development (GSD) has been an emerging trend in the development of software globally, for the last two decades. Information Technology (IT) outsourcing includes application development, application maintenance, infrastructure management and business process outsourcing. Software maintenance aims to keep the IT system operational and to fulfill the client requirements. The maintenance is considered the longest phase of software life cycle that consumes about 60-70% of the total software budget. Maintenance of software is not only time consuming but also requires a significant human resources' ratio. Mostly, software acquisition and maintenance consume a big portion of the total IT budget. The current study aims to evaluate the findings of the systematic literature review and to derive a list of critical success factors regarding offshore outsourcing decision of application maintenance. Thus, an empirical study is performed to validate the influencing factors that were identified by using systematic literature review. These factors are further validated by 93 outsourcing experts from 30 different countries. The collected data through online survey is analyzed based on variables such as respondents experience level, respondents' locations (continents), experts' positions. Similarly, the data is analysed based on Chi square test (linear by linear association) and Spearman Rank Correlation. Additionally, the identified factors through survey and systematic literature review are ranked by two different methods. Consequently, a project assessment model is proposed, based on the critical success factors for the sourcing decision of application maintenance.
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关键词
Outsourcing, Maintenance engineering, Bibliographies, Systematics, Software, Industries, Information technology, Application maintenance, critical success factors, influencing factors, offshoring, ranking, sourcing decision, sourcing model
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