Novel Multiperspective Hiring Framework for the Selection of Software Programmer Applicants Based on AHP and Group TOPSIS Techniques

The selection of software programmer applicants based on multiperspective evaluation criteria (grade point average (GPA) and soft skills of the applicants) is needed instead of an interview because an interview does not necessarily lead to hiring the best candidate amongst the applicants. The selection of a suitable software programmer is considered a challenging task owing to the following factors: (1) data variation, (2) multiple evaluation criteria and (3) criterion importance. A general framework for the selection of the best software programmer applicants is not available in the existing literature. The present study aims to propose a novel multiperspective hiring framework based on multicriteria analysis to select the best software programmer amongst several applicants. A decision matrix (DM) is constructed for the selection of the best programmer applicants according to multiple criteria, namely, structured programming, object-oriented programming, data structure, database system and courseware engineering. Each criterion includes two parameters, namely, GPA and soft skills, and these criteria cross over with programmer applicants as alternatives. The standard and expert opinion of the Software Engineering Body of Knowledge is used to distribute the criteria in the DM. The two commonly used techniques of multicriteria decision-making are analytic hierarchy process (AHP) for weighing the criteria and technique for order performance by similarity to ideal solution (TOPSIS) for ranking the alternatives (programmer applicants). The data used in this study include 60 software engineering students who graduated in 2016 from Universiti Pendidikan Sultan Idris. Results show that integrating multilayer analytic hierarchy process (MLAHP) and group TOPSIS are effective for solving applicant selection problems. Group TOPSIS uses different contexts — internal and external aggregation — and indicates similar results. Objective validation is used for the ranking of the results, which are equally divided into four parts. Furthermore, the applicants are systematically ranked. This study benefits application software, system software and computer programming tool companies by providing a method that improves software quality whilst reducing time and cost in the selection process.