## 3 Proposed Method
### AHP Technique for MCDM Problem  
The final and third phase of our proposed research method was the development of an MCDM model based on the AHP technique. By considering multiple criteria for taking a decision, this type of decision making is called MCDM. The primary purpose of MCDM is to rank the alternatives and, consequently, to select the most appropriate alternative by applying certain techniques along with considering specific criteria. MCDM has a variety of applications in different fields, such as engineering, management and economics. MCDM is divided mainly into two classes, which are Multi-Attribute Decision Making (MADM) and Multi Objective Decision Making (MODM). MADM consists of discrete factors as well as a limited number of alternatives, whereas MODM has continuous variables as well as alternatives, which are unlimited. In the literature, the terms MADM and MCDM are used interchangeably. Over the past years, several MCDM techniques have been proposed by researchers, namely TOPSIS, GDM (Gray Decision Making), ELECTRE (Elimination and Choice Expression Reality), SWARA (Step Wise Weight Assessment Ratio Analysis), AHP and ANP (Analytic Network Process) [48; 49]. [PERSON] and [PERSON] [50] discussed that, despite the extensive use of MCDM methodologies, the primary approaches, such as AHP, TOPSIS, ELECTRE, PROMETHEE, and their combinations have been criticized because of an issue known as the rank reversal problem. Rank reversal is defined as when a new option is introduced to a set or one of the existing alternative is deleted, the order of the alternatives in that set changes. [PERSON] [51] introduced the merging of the TOPSIS and PROMETHEE II methods with the characteristic objects method, which is resistant to the rank reversal problem. The characteristic objects method needs a massive number of pair comparisons, which grows exponentially in proportion to the number of criteria applied. AHP is one of the most important methods of MCDM and was developed by [PERSON] in the 1970s. This is an accurate and precise method for the variables ranking and their prioritization. Similarly, it is a flexible decision making technique that can be used easily. AHP uses a hierarchical structure to present a complex problem and make it simple by splitting it into sub problems. One of the most important features of AHP is that it organizes both the intangible and tangible variables in a systematic manner and offers a structured and comparatively simple solution to the multi-criteria decision making problems. This approach is well suited to fields where intuition, logic and irrationality are present in relation to risk and uncertainty. The problem may include significant social, political,  
Figure 2: Designations of respondents and their experience levels. economic and technical amounts, as well as a variety of goals, criteria and alternatives. This method is used for assigning weights/scores to criteria and alternatives. In the current study, weights were assigned to influencing factors and the sourcing alternatives. For the purpose of pairwise comparison, the scale used to provide preferences to criteria as well as alternatives is given in Table 2[52; 53; 54]. The current study aimed to compute the relative priorities/weights of influencing factors as well as to rank the available alternatives. Therefore, the classical AHP was the most suitable technique to calculate weights of the influencing factors and to rank the available sourcing models. Further, AHP has been used by other researchers in the same domain to solve the multi-criteria decision making problems, such as [55; 56; 57]. The selection of an effective and most appropriate model for the offshore outsourcing decision of application maintenance depends on various criteria, which were derived by using SLR and validated by performing empirical study, namely the employee skills, cost, poor communication, legal requirements, infrastructure, maturity level, frequent requirement changes, domain knowledge, language barrier and project management.