Innovative Applications of O.R.Capturing and prioritizing students’ requirements for course design by embedding Fuzzy-AHP and linear programming in QFD
Section snippets
Introduction and motivation
Quality Function Deployment (QFD) is employed towards the direction of developing and delivering flawless services based on customer requirements. QFD driven by the “voice of the customer” provides a detailed structured process, utilizing a series of planning matrices – Houses of Quality (HOQ) (Cohen, 1995) for service providers to interpret customer requirements into palpable service features and communicate quality throughout the organization assuring customer satisfaction whilst maintaining
Quality in higher education
The primary role of higher education institutions is to generate, enhance, preserve and disseminate knowledge (Clarke, Hough, & Stewart, 1984). However, higher education not only facilitates the acquisition of the desired professional qualifications through a strict study process but also fosters the intellectual development of students, influencing their lives in the long run (Norris, 1978). In line with industry principles, it has been suggested that the ultimate goal of higher education
Integrating LP-GW-Fuzzy AHP into QFD
Reported limitations of QFD (Andronikidis et al., 2009, Bouchereau and Rowlands, 2000) prompted the need for improvements by incorporating other analytical tools such as the Analytic Hierarchy Process (AHP). Specifically, QFD is a planning and development support method, powerful in designing high-quality services (Mazur, 2008). On the other hand, AHP is a versatile and widely used decision making method (Ho, 2008, Madu and Georgantzas, 1991, Shahin and Mahbod, 2007, Zhou et al., 2006) that can
Developing the framework
In this study, we focus on expectations and preferences of a particular customer type in higher education, namely, undergraduate business students. First and fourth-year university students of business administration were asked to express their preference on the expected learning outcomes in selected courses. The objective was to identify desirable learning outcomes based on what students expect to learn, understand, and be able to do by the end of a course and to prioritize learning outcomes
Sensitivity analysis and discussion
The QFD-LP-GW-Fuzzy AHP produced the prioritization and importance weights of the learning outcomes appearing in the first row of Table 5. Specifically, “Key transferable skills” was the learning outcome with the highest preference with a percentage priority of 31.67%. The second learning outcome in ranking is “Practical-based Knowledge”, with a percentage priority of 30.98%. “Generic Academic skills”, follows with a percentage priority of 26.02% and finally, “Theory-based Knowledge” was found
Concluding remarks
This work proposed a framework for interpreting and prioritizing customer preferences in the context of higher education. Limited cognitive processes, incomplete information and finite amount of time, prevent decision-makers from adequately scrutinize all the factors in a complex decision-making process. The interpretation and prioritization of important but ill-defined customer requirements are essential steps in order to take further actions to improve the quality of an offered service.
Acknowledgements
This research has been co-financed by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF) – Research Funding Program: Heracleitus II. Investing in knowledge society through the European Social Fund.
References (110)
- et al.
Applied data envelopment analysis
European Journal of Operational Research
(1991) Fuzzy hierarchical analysis
Fuzzy sets and systems
(1985)- et al.
Quality function deployment: A literature review
European Journal of Operational Research
(2002) - et al.
A systematic approach to quality function deployment with a full illustrative example
The International Journal of Management Science
(2005) - et al.
Development of a strategic plan for an academic Department through the use of Quality Function Deployment
Computers and Industrial Engineering
(1993) - et al.
Fuzzy linear programming models for NPD using a four-phase QFD activity process based on the means-end chain concept
European Journal of Operational Research
(2010) - et al.
An evaluation approach to engineering design in QFD processes using fuzzy goal programming models
European Journal of Operational Research
(2006) Evaluating weapon systems using fuzzy arithmetic operations
Fuzzy Sets and Systems
(1996)- et al.
A parametric representation of fuzzy numbers and their arithmetic operators
Fuzzy Sets and Systems
(1997) Integrated analytic hierarchy process and its applications – A literature review
European Journal of Operational Research
(2008)