Implementing Fuzzy AHP and FUCOM to evaluate critical success factors for sustained academic quality assurance and ABET accreditation

Abstract

The Accreditation Board for Engineering and Technology (ABET) accredits the tertiary education programs in the areas of applied and natural science, computing, engineering, and engineering technology. ABET offers accreditation in the United States and other regions in the world that lack such entities such as Gulf Cooperative Counties (GCC). Though ABET accreditation is voluntary, graduates of the ABET-accredited programs are considered equivalent in knowledge, behaviors, and attitude with global standards. The process of ABET accreditation takes months or years depending upon the gap with readiness and resources. The objective of this study is to compile and prioritize the list of critical success factors (CSFs) to commit resources optimally for sustained academic quality assurance and ABET accreditation. The triangulation research designed has been employed. Firstly, the observation of the ABET accreditation process of multiple programs at King Khalid University (KKU) helped in identifying 11 CSFs in three categories namely Program design and execution, Quality culture and excellence, and Institutional infrastructure and support. Further, these CSFs have been explored in the literature in the area of ABET accreditation. Finally, the research employs a fuzzy analytical hierarchy process (Fuzzy AHP) and full consistency method (FUCOM) to rank the relative importance of these CSFs and their dimensions for sustained academic quality assurance and ABET accreditation. The incorporation of these CSFs will help institutions in the GCC and other regions to get their academic programs ABET-accredited in an optimal manner.

D Numbers – Fucom – Fuzzy Rafsi Model for Selecting the Group of Construction Machines for Enabling Mobility

“…The FUCOM (Full Consistency Method) method is intended for determining the weight coefficients of the evaluation criteria. The method was first presented by Pamučar et al [36]; since then it has been applied in a large number of papers for solving various problems, such as: ▪ landfill site selection, together with the CODAS method [37], ▪ assessment of critical success factors for continuous academic quality assurance and accreditation, in the model with fuzzy AHP method [38], ▪ evaluation of the provisional sizing process in the clothing industry, with the fuzzy PIPRECIA method [39], ▪ selection of the best solution for business balance of the passenger railway operator, as a part of the validation test with the fuzzy AHP method [40], ▪ determination of macro location for railway network, in the model with the fuzzy TOPSIS method [41], ▪ selection of a distribution channel, in combination with the MARCOS method [42], ▪ solving the case study in the rubber glove industry, used in a hybrid model with the VIKOR method [43], ▪ for the purpose of assessing human resources, on which the overall efficiency of the enterprise depends, together with the MARCOS method [44], ▪ mineral potential mapping in greenfields, in the model with the MOORA and MOOSRA method [45], ▪ selection of vehicles with automatic guidance (AGVs), in combination with the R-ROV (Rough Range of Value) method [46], ▪ improvement of service quality measurement in the hybrid Delphi-FUCOM-SERVQUAL model [47], ▪ selection of a terrain vehicle for equipping military units, through the validation test of the AHP-DEA model, with the BWM method [48], ▪ selection of a sustainable supplier in a construction company, with the COPRAS method, while for the validation of the results the ARAS, WASPAS, SAW and MABAC methods were used in combination with rough numbers [49], ▪ evaluation of the sustainable performance of suppliers, with the MAIRCA method [50], ▪ selection of a location for a textile manufacturing facility, in combination with the GIS [51], and, ▪ selection of a fighter aircraft, with the ARAS method [52]. In addition to the classic FUCOM method, a fuzzified version of this method was used for solving practical problems, such as:…”

Operation mode selection of NIMBY facility Public Private Partnership projects

“…It enables rationally expressing the judgments of a decision-maker with a minimal number of comparisons [ 51 ]. Ahmad Naim (2020) [ 52 ] compared FUCOM and BWM and concluded that BWM has less pair-wise Verbs and leads to FUCOM more reliable solution. The author claimed that FUCOM offers better consistency, reduced pair-wise comparisons, and flexibility of measurement scale.…”

A comparative analysis of the principal component analysis and entropy weight methods to establish the indexing measurement

“…The AHP method was used as the most common subjective method to determine the weights of the criteria/constructs in management problems [ 21 , 22 ]. They assigned weights to the responses with the decision-makers choice [ 23 ].…”