03_Bojana Jovanovic:tipska.qxd 25 Bojana Jovanović1, Boris Delibašić2 1Iritel a.d. Belgrade, Serbia 2 University of Belgrade, Faculty of organizational sciences, Serbia Application of integrated QFD and fuzzy AHP approach in selection of suppliers UDC: 005.311.12:519.8 ; 658.7:621.3.04 DOI: 10.7595/management.fon.2014.0018 1. Introduction and literature review Limited business resources and a fierce market competition require quality management which considers stakeholders’ needs. For every production company important stakeholders are suppliers of components embedded in the final product. The selection of suppliers of product components plays a very important role in the realization of the production process. Supplier selection is a multi-criteria decision-making problem which often consists of qualitative metrics. Many authors presented different approaches in supplier selec- tion. Variants of the integrated QFD (quality function deployment) methods (Ju & Hwang, 2004) have been used in selecting and ranking suppliers. For example, a supplier selection methodology based on QFD and data mining technique has been proposed (Ni et al., 2007). Many researchers have proposed the introduc- tion of fuzzy numbers in the QFD approach for the supplier selection process (Bevilacqua et al., 2006). Gencer & Gurpinar (2007) proposed a model for usage of an analytic network process (ANP) in supplier se- lection. & (2009) published a paper about the Internet service provider selection, using fuzzy numbers in combination with the QFD method. Kilincci & Onal (2011) presented one supplier selection problem of a washing machine company in Turkey that used a fuzzy analytic hierarchy process (AHP) methodology. Zouggari & Benyoucef (2012) presented an approach for the supplier selection problem, using the fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) technique. Many papers present separated integrated fuzzy AHP and fuzzy QFD approaches, but there are only sev- eral papers which present integrated QFD and fuzzy AHP approaches as one technique. To the best of our knowledge, no selection of suppliers of electronic components using integrated QFD and fuzzy AHP ap- proaches has been published up to now. One integrated QFD and fuzzy AHP approach and its application is presented in this paper. This is the first application of QFD and fuzzy AHP in a Serbian company. The de- tailed algorithm of application of the proposed approach is given in Chapter 3. The proposed approach allows for an integration of requirements of different stakeholders in decision mak- ing about the supplier selection. A pilot research is conducted in one company which is a manufacturer of electronic devices. Management 2014/72 Supplier selection is a widely considered issue in the field of management, especially in quality management. In this paper, in the selection of suppliers of electronic components we used the integrated QFD and fuzzy AHP approaches. The QFD method is used as a tool for translating stakeholder needs into evaluating criteria for suppliers. The fuzzy AHP approach is used as a tool for prioritizing stakeholders, stakeholders’ requirements, evaluating criteria and, finally, for prioritizing suppliers. The paper showcases a case study of implementation of the integrated QFD and fuzzy AHP approaches in the selection of the electronic components supplier in one Serbian company that produces electronic devices. Also presented is the algorithm of implementation of the proposed approach. To the best of our knowledge, this is the first implementation of the proposed approach in a Serbian company. Keywords: QFD; fuzzy AHP; fuzzy numbers; supplier selection; stakeholders. The reminder of the paper will be organized as follows. In Chapter 2, the QFD method, the fuzzy QFD method and the fuzzy AHP approach, with their applications in available literature are described. In Chapter 3, the implemented integrated QDF and fuzzy AHP approaches are described and necessary guidelines for its practical implementation are given. In Chapter 4, a case study of implementation of the integrated QFD and fuzzy AHP approach in the selection of the electronic components supplier in one Serbian company that pro- duces electronic devices are showcased. In Chapter 5, the result analysis, conclusions and future research proposals are described. 2. QFD, fuzzy and AHP approaches The QFD method originated in 1972 in Japan, as a methodology for improving products quality in Japan- ese firms (Hauser & Clausing, 1988). One of the benefits of the QFD method is that it takes into considera- tion the stakeholders’ needs (Akao, 1990). The process of QFD involves the construction of one or more interlinked matrices, ‘‘Houses of Quality’’ (HoQs). During the QFD process, the determination of the impor- tance weights of stakeholders’ requirements is an essential step ( & , 2003). Some authors have integrated QFD with other methods. Chen & Ngai (2008) proposed a fuzzy-QFD approach. Lee et al. (2008) integrated the Kano model with the Fuzzy mode into the matrix of the QFD. Delice & Zülal (2009) combined the QFD with an integer linear programming model and the Kano model. Liang (2010) developed an approach of a fuzzy-QFD. Another variant for the integration of the QFD model is the AHP technique. There have been huge efforts to integrate AHP with QFD in order to identify the priority of customer requirements (Chuang, 2001; Bhattacharya et al., 2005). In recent years, the QFD has been used in different areas. Karsak et al. (2002) used the QFD for product planning. Luo et al. (2008) used the QFD method for components selection. Chaudhuria & Bhattacharyya (2009) linked the QFD with the Conjoint Analysis to determine technical char- acteristics. Chen (2009) integrated the QFD with the process management in product design improvement. Deros et al. (2009) proposed a QFD method for measuring the service quality characteristics. Chuang at al. (2009) used the QFD method to provide the market trends, competitive and operational strategies. Zadeh (1965) introduced the fuzzy set theory to deal with the uncertainty. The motivation for the use of words or sentences rather than numbers is that linguistic characterizations are less specific than numerical ones (Zadeh, 1973). The fuzzy logic allows for decision-making with estimated values under incomplete infor- mation. The integrated fuzzy QFD approach is used in many different areas, for example, in ensuring relia- bility in supply chain management (Sohn & Choi, 2001), in evaluation in building industry (Yang et al., 2003), in an industrial company which supplies motors for electronic appliance companies (Erol & Ferrell, 2003), in ranking the strategic actions of the Iran mobile cellular telecommunications (Khademi-Zare et al., 2010), in routing of shipping investment decisions in crude oil tanker market (Celik et al., 2009), in environmental considerations (Kuo et al., 2009), in acquiring enterprise software selection requirements (Sen & Baracli, 2010), in characterizing customers’ rating of extra virgin olive oil (Bevilacqua et al., 2012), as a decision sup- port model for licensor selection (Wang et al., 2012). The analytic hierarchy process (AHP) has been developed by Saaty (1977, 1980). The methodology trades- off among various qualitative and quantitative factors with a scale called Saaty‘s ninepoint scale (Saaty, 1980, 1988, 2008). In the research of literature, it is observed that the focus has been on the applications of the in- tegrated AHP rather than the stand-alone AHP. The methods and techniques which are commonly combined with the AHP include mathematical programming, quality function deployment (QFD), meta-heuristics, the SWOT analysis, and the data envelopment analysis (DEA) (, 2008). The fuzzy AHP approach is implemented in many different business areas, such as a strategic analysis of healthcare service quality (Buyukozkan et al., 2011), in shipping registry selection in the Turkish maritime industry (Celik et al., 2009), in prioritization of at- tributes in target planning for automotive product development (Nepal et al., 2010), in evaluating environmental sustainability from the perspective of the “Secured by Design” scheme (Larimian et al., 2013), in work safety evaluation and early warning rating of hot and humid environments (Zheng et al., 2012), in the evaluation of recreational fishing (Gao & Hailu, 2012), in risk assessment of implementing green initiatives in the fashion supply chain (Wang et al., 2012), in multi-criteria supplier segmentation (Rezaei & Ortt, 2013), in the strategic analysis of electronic service quality in healthcare industry (Buyukozkan & Cifci, 2012), in timetable evaluation (Isaai et al., 2011), in managing intellectual capital assets and an application to the ICT service industry (Cal- abrese et al., 2013), in prioritizing customer requirements in QFD (Kwong & Bai, 2006). Ho et al. (2012) pre- sented an integrated QFD and fuzzy AHP approach and its application in strategic logistics outsourcing. 26 2014/72Management 3. Integrated QFD and fuzzy AHP approach The integrated QFD and fuzzy AHP approach which is implemented in this paper includes three “Houses of Quality” (HOQs), including HOQ1 which links company stakeholders with their requirements, HoQ2 which relates stakeholder requirements to suppliers evaluating criteria, and HoQ3 which benchmarks alternative suppliers with respect to various criteria. Each pairwise comparison result in an AHP matrix or HoQ is a fuzzy number which possesses the characteristics of a triangular fuzzy membership function (Ho et al., 2012). In the case study in this paper, the integrated QFD and fuzzy AHP approach, proposed by Ho et al. (2012) and Calabrese et al., (2013) is used. We adopted a triangular fuzzy conversation scale proposed by Chang (1996), given in Table 1. For defuzzification, we used the central deffuzification method. Table 1: Triangular fuzzy conversation scale (Chang, 1996) The numbers used in the comparison scale (given in Table 1) have the following meanings: - 1 – JUST EQUAL –Both subjects have the same significance - 2 – EQUALLY IMPORTANT – Subject on the left side of the scale is equally important as the subject on the right-hand scale - 3 – WEAKLY MORE IMPORTANT - Subject on the left side of the scale is weakly more important than the subject on the right-hand scale - 4 – MODERATERLY MORE IMPORTANT - Subject on the left side of the scale is moderately more im- portant than the subject on the right-hand scale - 5 – STRONGLY MORE IMPORTANT - Subject on the left side of the scale is strongly more important than the subject on the right-hand scale - 6 – EXTREMELY MORE IMPORTANT - Subject on the left side of the scale is extremely more important than the subject on the right-hand scale Prior to the implementation of the method, AHP questionnaires were prepared. We made a pilot research, using the created AHP questionnaires, with answers in fuzzy numbers. We had four groups of AHP ques- tionnaires (for prioritization of stakeholder importance, for prioritization of stakeholder requirements, for pri- oritization of evaluating criteria and for prioritization of alternative suppliers). For computing priorities on the basis of questionnaires, a fuzzy AHP is used. All priorities are prescribed in three HoQs. In the first step, the management team establishes the importance of stakeholders in decision-making. After that, each of the stakeholders completed one questionnaire which determined the priority of the stakeholder requirements. Afterwards, a team comprised of stakeholders completed one questionnaire, which determined the priority of the criteria for the evaluation of suppliers. And finally, again, the same team consisting of stakeholders, completed one questionnaire, which evaluates suppliers in respect of all criteria. In Figure 1 the algorithm of the implemented approach is given. 27 Management 2014/72 Linguistic scale Triangular fuzzy conversation scale Triangular fuzzy reciprocal scale JUST EQUAL (1) (1, 1, 1) (1, 1, 1) EQUALLY important (2) (1/2, 1, 3/2) (2/3, 1, 2) WEAKLY MORE important (3) (1, 3/2, 2) (1/2, 2/3, 1) MODERATERLY MORE important (4) (3/2, 2, 5/2) (2/5, 1/2, 2/3) STRONGLY MORE important (5) (2, 5/2, 3) (1/3, 2/5, 1/2) EXTREMELY MORE important (6) (5/2, 3, 7/2) (2/7, 1/3, 2/5) Figure 1: Algorithm of integrated QFD and fuzzy AHP approach 4. Case study of implementation of integrated QFD and fuzzy AHP approach on selection of electronic components supplier The company that is the subject of our case study is one Serbian enterprise that produces electronic devices and has its own research and development institute. The company‘s main business activities are: research & development, design, manufacturing, engineering, consulting, maintenance, technical and customer train- ing. The company is paying great attention to the selection and evaluation of suppliers of electronic com- ponents. In accordance with the implemented and certified quality management system, the company has to evaluate potential suppliers. The integrated QFD and fuzzy AHP method allows the company to include stakeholder requirements in the process of evaluation and selection of suppliers. One possible method for evaluation and selection of suppliers of electronic components is proposed. Stakeholders who influence the selection of suppliers are: procurement manager, marketing manager, prod- uct development manager and production manager. The structure of the AHP model is given in Figure 2. Identified requirements of stakeholders (conducted brainstorming sessions): • Appropriate delivery conditions • Possession of certified management systems • Guarantees for the execution of delivery and services within the warranty period The authors Ho et al. (2012) used the following criteria in evaluating suppliers of third-party logistics serv- ices: cost, delivery, flexibility, quality, technology and risk. Supplier selection attributes according to Ha & Kr- ishnan (2008) framework are the following: after sales service, geographical location, product appearance, 28 2014/72Management amount of past business, impression, production facilities and capacity, attitude, Just-In-Time capability, quality, catalogue technology, labour relations, reciprocal arrangements, communication system, maintain- ability, reputation and position in industry, delivery, management and organization, response to customer re- quest, ease-of-use, operational controls, technical capability, e-commerce capability, packaging ability, technical support, environmentally friendly products, performance history, training aids, financial position, price, warranties and claims. Identified criteria for evaluation of suppliers, in accordance with the require- ments of stakeholders (conducted brainstorming sessions) are the following: • Delivery conditions: delivery time, price, distance of supplier, adaption to customer needs (emergency supplies, smaller lots, etc.), discounts (quantity, loyal customers, etc.). • Management systems: courtesy of staff, packaging and transport conditions, previous customer ex- perience, experience in communication with staff, number of certified management systems. • Warranties: financial stability, complaints procedure, warranty period. Figure 2: Fuzzy AHP model: goal, criteria, sub-criteria and alternatives All results obtained in the research are systematizes in three HoQs, shown in Table 2, Table 3 and Table 4. The first HoQ (HoQ1) represents the stakeholders involved in the selection of suppliers of electronic com- ponents, their importance in the process of selection of suppliers and stakeholder requirements. The HoQ1 allow us to compute the importance of each stakeholder‘s requirements, which will then be used in the HoQ2. Table 2: HoQ1 – Stakeholders and stakeholder‘s requirements 29 Management 2014/72 HOQ1 Im p o rt a n ce o f st a ke h o ld e r A p p ro p ri a te d e liv e ry co n d iti o n s P o ss e ss io n o f ce rt ifi e d m a n a g e m e n t sy st e m s G u a ra n te e s fo r th e e xe cu tio n o f d e liv e ry a n d se rv ic e s w ith in t h e w a rr a n ty p e ri o d Procurement manager 0.349 0.319 0.361 0,319 Marketing manager 0.206 0.298 0.431 0,27 Product development manager 0.222 0.319 0.361 0,319 Production manager 0.222 0.42 0.289 0,289 IMPORTANCE OF STAKEHOLDER REQUIREMENTS: 0.3367 0.3591 0.3019 The second HoQ (HoQ2) represents the stakeholder requirements, defined at the brainstorming session, their importance for each stakeholder and the criteria for the evaluation of suppliers (defined at the brain- storming session). The HoQ2 allow us to compute the importance of each evaluating criteria, which will be used in the next HoQ3. Table 3: HoQ2 – Stakeholder‘s requirements and evaluating criteria The third HoQ (HoQ3) represents evaluating criteria, their importance in the evaluation of suppliers, and the suppliers which will be evaluated. The HoQ3 allow us to compute the importance of each supplier. Table 4: HoQ3 – Evaluating criteria and suppliers 30 2014/72Management HoQ2 Im p o rt an ce o f st ak e h o ld e rs ’ re q u ir e m e n ts D e liv e ry t im e P ri ce D is ta n ce o f su p p lie r A d ap ta tio n t o cu st o m e r n e e d s D is co u n ts C o u rt e sy o f s ta ff P ac ka g in g a n d tr an sp o rt co n d iti o n s P re vi o u s cu st o m e r e xp e ri e n ce E xp e ri e n ce in co m m u n ic at io n w ith s ta ff N u m b e r o f ce rt ifi e d m an ag e m e n t sy st e m s F in an ci al s ta b ili ty C o m p la in ts p ro ce d u re W ar ra n ty p e ri o d Appropriate delivery conditions 0 .3 3 7 0 .1 9 5 0 .2 4 1 0 .1 5 8 0 .1 7 4 0 .2 3 3 Possession of certified management systems 0 .3 5 9 0 .1 5 6 0 .2 2 6 0 .2 3 6 0 .2 0 .1 8 2 Guarantees for the execution of delivery and services within the warranty period 0 .3 0 2 0 .2 6 1 0 .3 6 9 0 ,3 6 9 IMPORTANCE OF EVALUATING CRITERIA: 0 .0 6 6 0 .0 8 1 0 .0 5 3 0 .0 5 9 0 .0 7 8 0 .0 5 6 0 .0 8 1 0 .0 8 5 0 .0 7 2 0 .0 6 5 0 .0 7 9 0 .1 1 1 0 .1 1 1 HoQ3 Im p o rt a n ce o f e va lu a tin g cr ite ri a S u p p lie r 1 S u p p lie r 2 S u p p lie r 3 Delivery time 0.066 0.421 0.29 0,29 Price 0.081 0.302 0.315 0,384 Distance of supplier 0.053 0.37 0.37 0,261 Adaptation to customer needs 0.059 0.37 0.261 0,37 Discounts 0.079 0.261 0.37 0,37 Courtesy of staff 0.056 0.333 0.333 0,333 Packaging and transport conditions 0.081 0.34 0.321 0,34 Previous customer experience 0.085 0.37 0.261 0,37 Experience in communication with staff 0.072 0.368 0.341 0,291 Number of certified management systems 0.065 0.228 0.393 0,379 Financial stability 0.079 0.333 0.333 0,333 Complaints procedure 0.111 0.37 0.261 0,37 Warranty period 0.111 0.333 0.333 0,333 IMPORTANCE OF SUPPLIERS: 0.3376 0.3181 0.3427 After determining all relationship importance, the importance rating of each supplier was computed in the HoQ3 as shown in Table 4. According to the HoQ3, the performance of the supplier 3 is the best, followed by supplier 1 and supplier 2. Alternatively, the performance of suppliers can be evaluated with respect to groups of evaluation criteria (delivery conditions, management systems and warranties). Result analysis and conclusions In this section, we will benchmark alternative suppliers with respect to groups of evaluating criteria. Each group of criteria will be analyzed to understand which supplier is the best in respect of each group of crite- ria. Values of importance of suppliers given in Table 5, Table 6 and Table 7 have been normalized. The first group of criteria is “delivery conditions”, in which there are five criteria as shown in Table 5. Supplier 3 per- forms the best in this category because it has discounts for customers, is adaptive to customer needs and offers a competitive price. However, this does not apply to the two criteria, which will lead to a low level of satisfaction because of lengthy delivery time and a large distance of the supplier from the company. Table 5: Importance of suppliers with respect to group of criteria: delivery conditions The second group of criteria is “management systems”, in which there are five criteria as shown in Table 6. Supplier 3 performs the best in this category because it has courteous staff, good packaging and transport conditions and previous customers have good experience with this supplier. However, this does not apply to the two criteria, which will lead to a low level of satisfaction because of bad experience in communication with the staff (inefficiency in communication) and a smaller number of certified management systems in comparison with supplier 2. Table 6: Importance of suppliers with respect to group of criteria: management systems The third group of criteria is “warranties”, in which there are three criteria as shown in Table 7. Supplier 3 and supplier 2 perform the best in this category because they are financially stable (as other suppliers), have a short and simple procedure for complaints and offer a warranty as other suppliers. 31 Management 2014/72 Importance of evaluating criteria Supplier 1 Supplier 2 Supplier 3 Delivery time 0.066 0.421 0.29 0,29 Price 0.081 0.302 0.315 0,384 Distance of supplier 0.053 0.37 0.37 0,261 Adaption to customer needs 0.059 0.37 0.261 0,37 Discounts 0.079 0.261 0.37 0,37 IMPORTANCE OF SUPPLIERS: 0.11431 0.10889 0.115137 Importance of evaluating criteria Supplier 1 Supplier 2 Supplier 3 Courtesy of staff 0.056 0.333 0.333 0,333 Packaging and transport conditions 0.081 0.34 0.321 0,34 Previous customer experience 0.085 0.37 0.261 0,37 Experience in communication with staff 0.072 0.368 0.341 0,291 Number of certified management systems 0.065 0.228 0.393 0,379 IMPORTANCE OF SUPPLIERS: 0.11895 0.11693 0.123225 Table 7: Importance of suppliers with respect to group of criteria: warranties This paper used an integrated QFD and fuzzy AHP approach to measure the performance of suppliers of elec- tronic components, embedded in electronic devices. A case study was presented to demonstrate how this ap- proach can be implemented in the selection of electronic component suppliers. The integrated fuzzy AHP and QFD approach was used to translate the stakeholders’ requirements into 13 evaluation criteria which were used to benchmark the suppliers and to determine the importance and weightings in the HoQs. The integrated ap- proach involves a team of people representing various departments that have a say in the selection of electronic component suppliers: procurements, marketing, product development and production. After the implementation of the proposed approach, we can conclude that the company should select supplier 3, because it has courte- ous staff, good packaging and transport conditions, previous customers have good experience with this supplier, the supplier grants discounts for customers, it is adaptive to customer needs and has competitive prices, a fi- nancial stability, a short and simple procedure for complaints and grants warranty as other suppliers. The detail algorithm of application of the proposed approach is shown in Figure 1, which allows for the reproducibility of the conducted research. The other benefit of this paper is that this is the first application of QFD and fuzzy AHP in a Serbian company. Since this is pilot research, a small sample of respondents is used, and this is the main disadvantage of this paper. A larger sample of respondents would make the findings of our paper more reliable. REFERENCES [1] Akao, Y. (1990). 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Application of a trapezoidal fuzzy AHP method for work safety evaluation and early warning rating of hot and humid environments, Safety Science 50, 228–239, DOI: 10.1016/j.ssci.2011.08.042 [53] , A., , L. (2012). Simulation based fuzzy TOPSIS approach for group multi-criteria supplier selection problem, , , Pages 507–519, DOI: 10.1016/j.engappai.2011.10.012 ACKNOWLEDGMENT This paper is part of a project supported by the Ministry of Education, Science and Technological Develop- ment of the Republic of Serbia, under the title TR 32016 - Innovative electronic components and systems based on inorganic and organic technologies, embedded in goods and consumer products. Receieved: May 2013. Accepted : June 2014. 34 2014/72Management 35 Management 2014/72 About the Author Bojana Jovanović Iritel a.d. Belgrade, Batajnicki put 23, Serbia Bojana.jovanovic.123@gmail.com Bojana Jovanović is a PhD candidate at the Faculty of organizational sciences, Department of Management, University of Belgrade. The author works as a research associate at the Institute for telecommunications and electronics Iritel a.d. Belgrade, as a lecturer at the Education center Institution and as a consultant at various projects for CE marking of products. Boris Delibašić University of Belgrade, Faculty of organizational sciences, Serbia boris.delibasic@fon.bg.ac.rs Boris Delibašić is profesor at the Faculty of Organizational Sciences, University of Belgrade. He obtained his PhD in 2007 in Business Decision-Making. His main research areas are decision support Systems, business intelligence, data mining, and decision theory.