Appliction of Anlyticl Hierrchy Process (AHP) Technique To Evlute nd Selecting Suppliers in n Effective Supply Chin Shhroodi 1*, Kmbiz, Industril Mngement Deprtment, Islmic Azd University (Rsht Brnch), Rsht Irn. Kermtpnh, Amin, student of Business Mngement, Islmic Azd University (Rsht Brnch), Rsht Irn. Amini, shbnm, student of Business Mngement, Islmic Azd University (Rsht Brnch), Rsht Irn. Shiri, Elnz, student of Business Mngement, Islmic Azd University (Rsht Brnch), Rsht Irn. Syyd Hghighi, Kmyr, student of Business Mngement, Islmic Azd University (Rsht Brnch), Rsht Irn. Njibzdeh, Mohmmd, student of Business Mngement, Islmic Azd University (Rsht Brnch), Rsht Irn Abstrct With incresingly competitive globl world mrkets, compnies re under intense pressure to find wys to cut production nd mteril costs to survive nd sustin their competitive position in their respective mrkets. Since qulified supplier is key element nd good resource for buyer in reducing such costs, evlution nd election of the potentil suppliers hs become n importnt component of supply chin mngement. Most supplier selection models consider the buyer s viewpoint nd mximize only the buyer s profit. This does not necessrily led to n optiml sitution for ll the members of supply chin. This pper dels with brief review of the literture regrding AHP technique nd its relevncy to its ppliction in supplier selection process. Supplier selection is complicted process. This process needs evlution of multiple criteri nd vrious constrints ssocited with them. After nlysis of the results we found tht for mnufcturing firms, supplier relibility, product qulity nd supplier experience re the top three supplier selection problems tht needs to be tken up on priority for effective vendor selection. Keywords: supply chin mngement; Supplier selection; multi ttributive decision mking (MADM); Anlytic Hierrchy Process (AHP) Introduction In tody s globl mrketplce chrcterized by globliztion, incresing customers vlue expecttions, expnding regultory complince, globl economic crisis, nd intense competitive pressure, to thrive nd survive mnufcturing firms must select nd mintin core suppliers. Thus, supplier selection nd evlution represents one of the significnt roles of purchsing nd supply mngement functions(chen nd Hung, 2006) Weber et l. (1991) ttest tht it is impossible to successfully produce low cost, high qulity products without stisfctory selection nd mintennce of 1
competent group of suppliers Crr nd Smeltzer (1999) note tht "the purpose of strtegic purchsing [nd supply mngement] is to direct ll purchsing ctivities towrd opportunities consistent with the firm s cpbilities to chieve its long-term gols. Indeed, becuse purchsing nd supply mngement cn ply prominent role in firm s strtegic plnning, supply chin mngement, nd profitbility. Supplier selection is one of the key decisions to be mde in the strtegic plnning of supply chins tht hs fr-reching implictions in the subsequent stges of plnning nd implementtion of the supply chin strtegies. In trditionl/forwrd supply chin, the problem of supplier selection is not new. First publictions on supplier selection in trditionl forwrd supply chins bck to the erly 1960s (Wng, G., Hung, S. H. nd Dismukes, 2004) trditionlly, in supply chin literture, the supplier selection problem is treted s n optimiztion problem tht requires formulting single objective function. However, not ll supplier selection criteri cn be quntified, becuse of which, only few quntittive criteri re included in the problem formultion. AHP mkes the selection process very trnsprent. It lso revels the reltive merits of lterntive solutions for Multi Criteri Decision Mking (MCDM) problem. (Drke, P.R., 1998). AHP pproch is subjective methodology (Cheng nd Li, 2001); informtion nd the priority weights of elements my be obtined from decision-mker of the compny using direct questioning or questionnire method. It is generlly greed in the literture tht the following mkes the supplier selection decision mking process difficult nd/or complicted (de Boer, 1998, Murlidhrn et.l. 2001).Supplier selection process represents complex problem nd thus multi-ttribute decision mking (MADM) problem. MADM such s the nlytic hierrchy process (AHP) model is n importnt technique tht hs been used successfully in supplier selection nd evlution Therefore,. this pper uses the AHP model developed by Sty (1980) for supplier selection nd evlution in mnufcturing firms in which the gol being pursued hs multiple, often conflicting ttributes. The remining portion of this pper is orgnized s follows. Section 2 presents brief bckground on dvntges nd disdvntges of using AHP method. Section 3 presents n bbrevited review of relevnt literture on the pproches used in supplier selection nd evlution. Section 4 provides the reserch methodology, including dt collection nd nlysis. Section 5 discusses the reserch findings s well s limited discussion on the sensitivity nlysis. Finlly, the conclusions nd mngeril implictions re presented in section 6. Advntges nd Disdvntges of Using AHP Method: One dvntge of AHP is tht it illustrtes how possible chnges in priority t upper levels hve n effect on the priority of criteri t lower levels. Moreover, it provides the buyer with n overview of criteri, their function t the lower levels nd gols s t the higher levels. A further dvntge of AHP is its stbility nd flexibility regrding chnges within nd dditions to the hierrchy. In ddition, the method is ble to rnk criteri ccording to the needs of the buyer which lso leds to more precise decisions concerning supplier selection. The min dvntge of AHP is tht the buyer is ble to get good picture of the supplier s performnce by using the hierrchy of the criteri nd evluting the suppliers (Omkrprsd nd Kumr, 2006). However, AHP lso hs some wek points. One of these is the complexity of this method which mkes it implementtion quite inconvenient. Moreover, if more thn one person is working on this method, different opinions bout the weight of ech criterion cn complicte mtters. AHP lso 2
requires dt bsed on experience, knowledge nd judgment which re subjective for ech decisionmker. A further disdvntge of this method is tht it does not consider risks nd uncertinties regrding the supplier s performnces (Yusuff et l., 2001). The strength of the AHP method lies in its bility to structure complex, multi-person, multi-ttribute, nd multi-period problems hierrchiclly nd it is simple to use nd to understnd. It necessittes the construction of hierrchy of ttributes, sub-ttributes, lterntives nd so on, which fcilittes communiction of the problem nd the recommended solutions. In ddition, the AHP method provides unique mens of quntifying judgmentl consistency. The issues of supplier selection hve ttrcted the interest of reserchers since the 1960s, nd reserch studies in this re hve incresed. A study ws conducted to determine wht criteri were used in the selection of firm s supplier. Most of these criteri during tht time were quntittive. During tht time the reserchers did not give ttention to qulittive criteri which hd lower level rnking for the evlution nd the selection of suppliers. Method for decision-mking to mesure qulittive criteri such s AHP, Fuzzy etc. ws used to select suppliers. Nowdys, qulittive methods received more ttention in decision-mking models for selecting the suppliers. Consequently, the reserchers will focus on qulittive criteri in the future rther thn combintion of both qulittive nd quntittive criteri with existing methods such s AHP. Nowdys, AHP nd Fuzzy AHP s two precise methods for supplier selection decision- mking re believed to be useful for mngers due to their simplicity in use. Yet gin, it is proven tht AHP work well in mking decision for mny types of compnies tht involves different types of suppliers. Bsed on bove review, it would be not irrtionl to suggest tht the supplier selection issues need further ttention in order to hrmonies the combintion of qulittive nd quntittive criteri to develop the best decision-mking models for the selection of the best suppliers. Literture Review Ghodsypour nd O Brien (1988) noted tht supplier selection models could be broken down into single source nd multiple source models. In single source models, one supplier is ble to respond to buyer s demnd. In multiple source models, the lloction problem is considered to be the sme s the selection problem. Rnking techniques re usully pplied to single source models, but in multiple source models mthemticl progrmming models re developed (Degreve nd Roodhooft, 2000). Further developed multi-period, multi-item, multi-vendor mixed- integer progrmming model bsed on the TCO, to determine n optiml ordering nd inventory policy nd jointly to decide on the best combintion of suppliers their model covers the totl cost. Incurred, including the purchsing cost, the ordering cost, the trnsporttion costs nd so forth. Ghodsypour nd O Brien (1988) developed decision support system tht combined the nlyticl hierrchy process with liner progrmming. They first presented single objective mixedinteger nonliner progrmming model to minimize totl cost. In tht model, they considered qulity s constrint, nd then developed multi-objective model with one of its objectives to mximize the orders qulity. Hong et l. (2005) developed mixed integer progrmming model to select right suppliers nd mximize revenue while stisfying the customer needs. They considered chnges in suppliers cpbilities nd customer requirements over the horizon of the problem. In their model, the suppliers which stisfy mny prts of the idel procurement condition re selected more often thn other suppliers. Bsnet nd Leung (2005) developed model to combine lot-sizing with supplier selection problem. They considered multi-period inventory lot-sizing scenrio where multiple products could be sourced from set of selected suppliers in ech cycle. The objective function consists of 3
purchsing price, inventory holding cost nd trnsction cost for minimiztion nd n enumertive serch lgorithm ws proposed to solve the problem. Kirytopolos et l (2008) utilized nlytic network process pproch for the selection nd evlution of suppliers. The supplier selection criteri considered in their study included cost, service, supplier s profile, qulity, risk, nd other. This pper contributes to the existing strem of reserch by integrting regultory complince into supplier's selection process in production industril firm supply chin. Supplier selection literture is endowed with vrious kinds of methodology, including multi-criteri decision-mking techniques or decision support systems (e.g., AHP), conceptul ppers, empiricl reserch, simultion techniques, mong mny others. Strem of reserch tht hve pplied AHP methodology in supplier selection include (e.g., Brbrosoglu nd Tzgc 1997; Bhutt nd Huq 2002; Chn 2003; Onesime et.l. 2004). Methodology Problem of selection of vendor hs been delt with by using questionnire bsed study. A structured questionnire ws frmed nd ll the criteri re rted by the professionl of vrious fields. The frmework dopted for this study is s shown in figure1. The foundtion of the Anlytic Hierrchy Process (AHP) is set of xioms tht crefully delimits the scope of the problem environment (Sty 1986). It is bsed on the well- defined mthemticl structure of consistent mtrices nd their ssocited eigenvector s bility to generte true or pproximte weights, Sty (1980, 1994). The AHP methodology compres criteri, or lterntives with respect to criterion, in nturl, pir wise mode. To do so, the AHP uses fundmentl scle of bsolute numbers tht hs been proven in prctice nd vlidted by physicl nd decision problem experiments it converts individul preferences into rtio. Scle weights tht cn be combined into liner dditive weight for ech lterntive. The resultnt cn be used to compre nd rnk the lterntives nd, hence, ssist the decision mker in mking choice. It is powerful opertionl reserch methodology useful in structuring complex multi-criterion problems or decisions in mny fields such s logistics nd supply chin mngement, mrketing engineering, eduction, nd economics. Merits ssocited with AHP include its relince on esily derived expert judgment dt, bility to reconcile differences (inconsistencies) in expert judgments nd perceptions, nd the existence of Expert Choice Softwre tht implements the AHP. 4
Model Development AHP for Supplier Selection Supplier Selection cn help mnufcturing firms to contin cost ssocited with the bottom line. It entils the determintion of quntittive nd qulittive fctors impertive for selecting the best possible suppliers (Chn, 2003). The following steps ssocited with AHP method for decision mking re used: (1) Clerly define the decision problem nd determine its gol. (2) Structure the hierrchy from top through the intermedite levels to the lowest level. In Figure 2, the gol of the problem is locted t level 1. Level 2 houses the mjor ttributes. Finlly, the lterntives re locted t the lst level of the hierrchy. The supplier selection criteri nd lterntive suppliers re identified below. Figure2. The Hierrchicl Structure for mnufcturing firm For supplier selection process nd evlution, mnufcturing firms hve primrily considered criteri such s qulity, service, cost, flexibility, reputtion, nd finncil stbility (e.g. Srkis nd Tlluri 2002; Verm nd Pullmn 1998; Hirkubo nd Kublin, 1998). However the current reserch considered qulity of product, trnsporttion ese nd cost, relibility of vendor, price of product, experience of the supplier, led time to evlute ech of the four suppliers. 5
Figure 3.Criteri nd Abbrevitions Used S.N Criteri Abbrevition used 1 Trnsporttion ese nd cost TC 2 3 Experience of the supplier Led time ES LT 4 Relibility of the supplier RS Eigenvlue nd Eigenvector Price of product PP 5 Sty (1990) recommended tht the mximum eigenvlue, λ mx, cn be determined s Qulity of product QP 6 In AHP, multiple pirwise comprisons re bsed on stndrdized comprison scle of nine levels. Let C= {Cj j=1, 2... n} be the set of criteri. The result of the evlution mtrix in which every element ij (i, j=1, 2... n) is the quotient of weights of the criteri, s shown: A 11 21 n1 12 22 n2 1n 2n nn, 11 1, ji 1 ij, ij 0. (1) Eigenvlue nd Eigenvector Sty (1990) recommended tht the mximum eigenvlue, λ mx, cn be determined s: /W. (2) λ mx = ij Wj i j=1 Where λ mx is the principl or mximum eigenvlue of positive rel vlues in judgment mtrix, W j is the weight of j th fctor, nd W i is the weight of i th fctor. If A represents consistency mtrix, eigenvector X cn be determined s Consistency Test 6 (A - λ mx I)X = 0 (3) Both AHP nd Expert Choice Softwre does not impose on the mnufcturing firms to be perfectly consistent, rther consistency test is performed to exmine the extent of consistency s well s ech
judgment once the priorities re determined. Sty (1990) recommended using consistency index (CI) nd consistency rtion (CR) to check for the consistency ssocited with the comprison mtrix. A mtrix is ssumed to be consistent if nd only if ij * jk = jk i jk (for ll i, j, nd k). When positive reciprocl mtrix of order n is consistent, the principl eigenvlue possesses the vlue n. Conversely, when it is inconsistent,the principl eigenvlue is greter thn n nd its difference will serve s mesure of CI. Therefore, to scertin tht the priority of elements is consistent, the mximum eigenvector or reltive weights/λ mx cn be determined. Specificlly, CI for ech mtrix order n is determined by using (3): CI = (λ mx - n)/n - 1 (4) Where n is the mtrix size or the number of items tht re being compred in the mtrix. Bsed on (3), the consistency rtio (CR) cn be determined s: CR = CI/RI = [(λ mx - n)/n - 1]/RI. (5) Where RI represents verge consistency index over number of rndom entries of sme order reciprocl mtrices shown in Tble 1. CR is cceptble, if it is not greter thn 0.10. If it is greter thn 0.10, the judgment mtrix will be considered inconsistent. To rectify the judgment mtrix tht is inconsistent, decision-mkers judgments should be reviewed nd improved. However, Byun (2001) suggested tht.20 might still be cceptble. Tble.1 The Reference Vlues of RI for Different Numbers of n n 2 3 4 5 6 7 8 9 10 RI 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49 Dt Collection nd Anlysis A survey questionnire pproch ws used for gthering reltionl dt to ssess the order of importnce of the supplier selection criteri. Thus, from the hierrchy tree, we developed questionnire to enble pirwise comprisons between ll the selection criteri t ech level in the hierrchy. The pirwise comprison process elicits qulittive judgments tht indicte the strength of group of decision mkers preference in specific comprison ccording to Sty s 1-9 scle. A group of purchsing nd supply chin mngers ws requested to respond to severl pirwise comprisons where two ctegories t time were compred with respect to the gol. The result of the survey questionnire technique ws then used s input for the AHP. The mtrix of pirwise comprisons of the criteri or ttributes given by the mnufcturing firms in the cse study is shown in Tble 2. The judgments re entered utilizing Sty s pirwise comprison preference scle explined in step 3. 7
Tbles 3-8 show the judgments of group of decision mkers regrding the reltive importnce of the suppliers A, B, C, nd D with respect to qulity of product, trnsporttion, ese nd cost, relibility of supplier, price of product, experience of the supplier, led time. 8
9
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Results nd Discussions The priorities obtined from the group decision mkers judgments re depicted in Figure 3. It shows tht is relibility of supplier the best supplier selection criterion, followed by qulity of product, experience of the supplier, led time, trnsporttion ese nd cost, price of product. Thus, suggesting tht the decision mkers in the cse of mnufcturing firms should integrte the preceding criteri into supplier selection decision. The inconsistency or referred to s CR is 0.07 < 0.10 reported by the Expert Choice Softwre. This implies tht the group decision mkers (purchsing nd supply chin mngers ) evlution is consistent. 11
Conclusions nd Implictions AHP pproch helps decision mkers to rnk lterntive suppliers bsed on the decision mkers subjective judgments regrding the importnce of the ttributes. The role of supplier selection process nd evlution hs become more thn ever impertive for supply chin performnce. Supplier selection process nd evlution represents one of the key ctivities tht orgniztions must integrte into their core strtegic decisions. Selecting nd evluting the right suppliers is the quintessentil spect of strtegic purchsing nd supply chin mngement tht cn ffect mnufcturing firms. The primry objectives of supplier selection nd evlution include reducing costs, ttining rel-time delivery, ensuring world-clss qulity, mitigting risks, nd receiving better services. References Brbrosoglu, G., Yzgc, T., 1997.An ppliction of the nlytic hierrchy process to the Supplier selection problem. Production nd Inventory Mngement Journl8 (1), 14 21 Bsnet, C. nd Leung, J.M.Y. (2005), Inventory lot-sizing with supplier selection. Computers nd Opertions Reserch 32, 1-14 Chn, F. T. S., Chn, H. K., Ip, R. W., nd Lu, H. C. W. (2007). A Decision Support System for Supplier Selection in the Airline Industry, Journl of Engineering Mnufcture, 221Prt B, 742-758. Chn, F. T. S. (2003). Interctive Selection Model for Supplier Selection Process: An Anlyticl hierrchy Process Approch, Interntionl Journl Production Reserch, Volume 14, Number 15, 3549-3579. Chen-Tung, C. nd Ching-Torng, L. (2006). A fuzzy pproch for supplier evlution nd selection in 12
supply chin mngement. Production Economics, 102:289-301 Degreve, Z. nd Roodhooft, F.(2000), A mthemticl progrming pproch for procurement using ctivity bsed costing. Journl of Business Finnce & Accounting 27(1-2), 69-98. Crr, A. S. nd Smeltzer, L. R. (1999). The reltionship of Strtegic Purchsing to Supply Chin mngement. Europen Journl of Purchsing nd Supply Mngement, Volume 5, 43-51. Drke, P.R., 1998, Using the Anlyticl Hierrchy Process in Engineering Eduction, Interntionl Journl of Engineering Eduction, Vol. 14, No3, nd PP. 191-196. Ellrm, L.M. (Fll 1990). "The Supplier Selection Decision in Strtegic Prtnership," Journl of Purchsing nd Mterils Mngement, Volume 26, Number 4, pp. 8-14. Ghodsypour, S. H. nd O Brien, C. (1998). A decision support system for supplier selection using n integrted nlytic hierrchy process nd liner progrming, Interntionl Journl of Production Economics, Volume 56-57, 199-122. Hirkubo, N. nd Kublin, M. (1998). The reltive importnce of supplier selection criteri: The cse of electronic components, Interntionl Journl of Purchsing &Mterils Mngement, Volume 34, Number 2, 19-24. Kirytopoulos, K., Leopoulos, V., nd Voulgridou, D. (2008). Supplier Selection in industries: An Anlytic Network Process Approch: An Interntionl Journl, Volume 15, Number 4, 494-516. Kumr, M., Vrtb, P., nd Shnkrc, R. (2003). A fuzzy gol progrmming pproch for vendor selection problem in supply chin. Computers nd Industril Engineering Volume 46, 69-85. Murlidhrn, C., Annthrmn, N. Deshmukh, S. G., 2001, Vendor Rting in purchsing Scenrio: A Confidence Intervl Approch. Interntionl Journl of Opertions nd Production Mngement, 21(10): PP. 1306-1325. Omkrprsd, S.V. nd Kumr, S. (2006).Anlytic hierrchy process: n overview of ppliction. EJOR, 169:1-29. Sty, T.L. (1980). The Anlytic Hierrchy Process. New York: McGrw-Hll. Sty, T. L. (1990). How to Mke Decision: The Anlytic Hierrchy Process, Europen Journl of Opertionl Reserch, Volume 48, 9-26. Srkis, J. nd Tlluri, S. (2002). A Model for Strtegic Supplier Selection, Journl of Supply Chin Mngement, Volume 38, Number 1, 18-28. Sty, T. L. (2000). Fundmentls of decision mking nd priority theory with the nlytic hierrchy process. Pittsburgh, PA: RWS Publictions. Wng, G., Hung, S. H. nd Dismukes, J. P., Product-driven supply chin selection using integrted multi-criteri decision-mking methodology, Interntionl Journl of Production Economics, 91, 1-15, 2004. Weber, C. A., Current, J. R. nd Benton, W. C. (1991). Vendor selection criteri nd methods. 13
Europen Journl of Opertionl Reserch, Volume 50, 2-18. Weber, C. A. nd Ellrm, L. M. Supplier Selection using Multi-Objective Progrmming: A Decision Support System Approch, Interntionl Journl of Physicl Distribution nd Logistics Mngement, (23:2), 1992, pp. 3-14. Wilson, E. J. (1994). The reltive importnce of supplier selection criteri: A review nd updte, Interntionl Journl of Purchsing & Mterils Mngement, Volume 30, Number 3, 35-41. Yusuff, R.D. nd Poh Yee, K. (2001). A preliminry study on the potentil use of the nlyticl hierrchicl process (AHP) to predict dvnced mnufcturing technology (AMT) implementtion. Robotics nd Computer Integrted Mnufcturing. 17:421-427. 14