Selection of Academic Staff Using the Fuzzy Analytic Hierarchy Process (fahp): a Pilot Study;

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Date

2012

Authors

Erkan, Turan Erman

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Open Access Color

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Industrial Engineering
(1998)
Industrial Engineering is a field of engineering that develops and applies methods and techniques to design, implement, develop and improve systems comprising of humans, materials, machines, energy and funding. Our department was founded in 1998, and since then, has graduated hundreds of individuals who may compete nationally and internationally into professional life. Accredited by MÜDEK in 2014, our student-centered education continues. In addition to acquiring the knowledge necessary for every Industrial engineer, our students are able to gain professional experience in their desired fields of expertise with a wide array of elective courses, such as E-commerce and ERP, Reliability, Tabulation, or Industrial Engineering Applications in the Energy Sector. With dissertation projects fictionalized on solving real problems at real companies, our students gain experience in the sector, and a wide network of contacts. Our education is supported with ERASMUS programs. With the scientific studies of our competent academic staff published in internationally-renowned magazines, our department ranks with the bests among other universities. IESC, one of the most active student networks at our university, continues to organize extensive, and productive events every year.

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Abstract

Evaluating candidates' suitability for a selection of academic staff is an important tool for Human Resources Management (HRM) to select the most suitable candidates for required posts. There are various methods regarding the selection of staff in the field. As there are increasing improvements in the field of education, universities around the world demand high quality and professional academic staffs. The present paper examines a fuzzy Analytic Hierarchy Process (FAHP) for selecting the most suitable academic staff, where five candidates under ten different sub-criteria are evaluated and prioritised. The FAHP method adopted here uses Triangular Fuzzy Numbers (TFN). The inability of AHP to deal with the impression and subjectiveness in the pair-wise comparison process has been improved in the FAHP. Instead of a crisp value, the FAHP generates a range of values to incorporate the decision-makers uncertainty. Also, a real case study is presented.

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Keywords

Academic Staff Selection, Fuzzy Analytic Hierarchy Process (FAHP), Human Resources Management (HRM), Multi-Criteria Decision-Making (MCDM)

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Fields of Science

Citation

65

WoS Q

Q4

Scopus Q

Q3

Source

Tehnicki Vjesnik

Volume

19

Issue

4

Start Page

923

End Page

929

URI

https://hdl.handle.net/20.500.14411/9340

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Scopus