Abstract
The phenomenon of Global Software Development (GSD) has attracted the interest of businesses all over the world. It brings together partners from various national and corporate cultures to develop applications with numerous advantages, including access to a vast labor pool, cost savings, and round the clock growth. GSD, on the other hand, is technologically and organizationally diverse and poses a number of obstacles for the development team, such as geographical distance, cultural differences, communication and language barriers. Global services are provided by selecting one of the suitable global delivery options, i.e., the onshore model, nearshore model or offshore model. Experts typically choose one of the models based on the nature of the project and the needs of the customer. However, the vendors and clients lack an adequate decision support system that can assist them in making suitable sourcing decisions. Therefore, the current study presents a Multi-Criteria Decision Making (MCDM) model for offshore outsourcing decisions of application maintenance. To achieve our target, two systematic literature reviews were conducted that explored a list of 15 influencing factors. The identified factors were further evaluated in the outsourcing industry by performing an empirical study that resulted in a list of 10 critical success factors. We propose a sourcing framework based on the critical success factors that can assist decision makers in adopting a suitable sourcing strategy for the offshore outsourcing of application maintenance. In order to further enhance the decision-making process, the MCDM model is developed based on the Analytic Hierarchy Process (AHP). The MCDM model is evaluated with three case studies in highly reputable international companies, including IBM Stockholm, Sweden, Vattenfall AB, Stockholm, Sweden and a London based company in the United Kingdom. The outcomes of these case studies are further reviewed and validated by the outsourcing specialists in other firms. The proposed model is used as a decision support system that determines the ranking of sourcing alternatives and suggests the most suitable option for application maintenance offshoring.