Evaluating Green and Resilient Supplier Performance: AHP-Fuzzy Topsis Decision-Making Approach

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1 Evaluatng Green and Reslent Suppler Performance: AHP-Fuzzy Topss Decson-Makng Approach Ahmed Mohammed, Irna Harrs, Anthony Soroka, Nam Mohamed and Tm Ramjaun Cardff Busness School, Cardff Unversty, Aberconway Buldng, Colum Dr, CF10 3EU, Cardff, U.K. Keywords: Abstract: Suppler Selecton, Green Development, Supply Chan Reslence. Ths paper presents an approach for evaluatng and rankng supplers wth respect to ther tradtonal, green and reslence (TGR) characterstcs. A set of crtera/sub-crtera were dentfed wthn a unfed framework and ther relatve mportance weghted usng the analytcal herarchy process (AHP) algorthm. In addton, the supplers were evaluated and ranked based on ther performance towards the dentfed TGR crtera usng the fuzzy technque for order of preference by smlarty to deal soluton (FTOPSIS) algorthm. The applcablty and effectveness of the proposed approach was proved through a real case study by revealng a comparatvely meanngful rankng of supplers. The study provdes a noteworthy ad to management who understand the necessty of buldng supply chan reslence whle concurrently pursung go green responsbltes. 1 INTRODUCTION The suppler selecton decson-makng process represents a key actvty n supply chan management snce purchasng expenses exceed ffty percent of all frms costs (Mohammed et al., 2017a). Suppler selecton refers to a mult-crtera decson-makng problem n evaluatng supplers performance wth respect to several crtera n order to purchase materals from the most approprate source. Despte the mportance of prce, other evaluaton crtera should be consdered such as relable delvery, whch wll ultmately effect productvty and effcency wthn a producton envronment and therefore overall costs. Dckson (1966) hghlghted 23 parameters that can be used by decson-makers to assess supplers, Ha and Krshnan (2008) updated these and suggested several addtonal crtera. Nevertheless, the most prevalent tradtonal busness crtera are qualty, cost, and delvery. Popular green crtera nclude: envronmental management systems, resource consumpton, eco-desgn and waste management. Further suppler selecton crtera can be found n Weber et al. (1991); Govndan et al. (2015); and Assaou et al. (2007). Presently, there are ever ncreasng responsbltes placed on companes to consder the envronmental mpact of ther supply chan actvtes (Mohammed et al., 2017b and 2015; Konur et al., 2016). Green supply chan management s the actvty of purchasng, producng, marketng and performng varous packagng and logstcal actvtes that takes nto account envronmental mplcatons (Mohamemd et al., 2017c). However, supplers tend to represent nevtable sources of external rsk (Rajesh and Rav, 2015). Purchasng managers may consder tradtonal and more recently green crtera when assessng supplers whle neglectng reslence (Kannan et al., 2015). Reslence s the capablty of the system to effcently adapt an expected dsruptons and back to ts normal process, s a vtal aspect of any supply chan management (Torab et al., 2015). Followng an earthquake n Japan (2011), Apple was unable to produce the Pad 2 due to lack of flash memory and super-thn battery (BBC News, 18 Mar 2011) caused by an unantcpated dsrupton to the supply chan. Ths partcular event also nterrupted the automotve sector and retal supply chans n the UK (Hall, 16 Apr 2010). Recently, hurrcane Sandy led to massve dsruptons n US supply chans (Torab et al., 2015; Burnson, 30 Oct 2012). To protect ther busness, purchasng managers should nclude reslence n to ther decson-makng crtera (Torab et al., 2015). Reslence crtera s represented by a suppler s capablty to cope wth rsk and unexpected events more effcently and quckly than other supplers. The current work consders reslence crtera dentfed 209 Mohammed, A., Harrs, I., Soroka, A., Mohamed, N. and Ramjaun, T. Evaluatng Green and Reslent Suppler Performance: AHP-Fuzzy Topss Decson-Makng Approach. DOI: / In Proceedngs of the 7th Internatonal Conference on Operatons Research and Enterprse Systems (ICORES 2018), pages ISBN: Copyrght 2018 by SCITEPRESS Scence and Technology Publcatons, Lda. All rghts reserved

2 ICORES th Internatonal Conference on Operatons Research and Enterprse Systems and analysed by Purvs et al. (2016). The latter proposed a framework for the development and mplementaton of a reslent supply chan strategy, whch llustrates the relevance of varous management paradgms. The authors consdered four pllars (enablers) as key factors to mprove supply chan reslence: redundancy, aglty, leanness and flexblty (RALF). However, vsblty was suggested as an essental reslence crteron by the purchasng manager for our case study. Snce addtonal crtera, such as envronmental sustanablty and reslence are paramount to buldng a successful and compettve supply chan, suppler selecton complexty has ncreased. A novel approach s requred, whch ncorporates three man crtera: tradtonal busness, green and reslence. Despte the sgnfcant quantty of research already conducted around these topcs, the vast majorty of current lterature consders the green and reslence aspects of suppler selecton ndependently. Ths paper addresses the knowledge gap by proposng a unfed suppler selecton approach that consders tradtonal, green and reslence crtera smultaneously. The evaluaton crtera were dentfed from the lterature and based on dscussons wth the purchasng manager from our case study. The development of ths approach can be detaled nto three phases. In phase one, the man tradtonal, green and reslence crtera and ther sub-crtera were dentfed n a unfed framework. Phase two, AHP was used to ntegrate judgments from a decson maker wth the purpose of determnng the weghts of the crtera and sub-crtera. In the thrd phase, FTOPSIS was appled to evaluate and rank supplers based on ther TGR performance. The robustness of the proposed approach s valdated wthn a case study for a manufacturng company and the work contrbuted to provdng a framework for the suppler selecton strategy, whch ncorporates tradtonal, green and reslence crtera. 2 LITERATURE REVIEW Prevous studes on suppler selecton consder tradtonal crtera to be more extensve than the less establshed, green suppler selecton (Govndan et al., 2015; Amndoust et al., 2012). Most Recently, Govndan et al. (2015) revewed publshed research from 1997 to 2011 on MCDM and mathematcal modellng used for green suppler selecton problems. Shen et al. (2013) proposed a fuzzy approach for evaluatng the green supplers. Büyüközkan and Çfç (2010) developed a fuzzy analytc network process (ANP)-based approach wthn a mult-person decson makng scheme under ncomplete preference relatonshps. Kuo and Ln (2011) proposed an ntegrated approach usng ANP and DEA for green suppler evaluaton. Akman (2015) suggested a twostep suppler-assessment framework to evaluate green supplers. Kannan et al. (2015) nvestgated a green suppler selecton problem n a plastc company usng a fuzzy axomatc desgn approach. Govndan and Svakumar (2016) developed an ntegrated multcrtera decson-makng and mult-objectve lnear programmng approach as an ad to select the best green suppler. Songa et al. (2017) proposed an ntegrated approach for evaluatng supplers wth respect to economc, green and socal crtera usng the mert of parwse comparson method n determnng relatve mportance, the strength of decson makng tral and evaluaton laboratory (DEMATEL) n manpulatng the complex and ntertwned problems wth fewer data, and the rough number's advantage n flexbly dealng wth vague nformaton. Supply chan management ncludes a varety of complex actvtes subject to dsruptons caused by unexpected ncdents. Improvng supply chan reslence s crucal for managng potental dsruptons (Torab et al., 2015). The revewed lterature showed that research studes usng quanttatve approaches to solve reslent suppler problem are lmted. Mtra et al. (2009) and Sawk (2013) dentfed several pllars and crtera that should be consdered for selectng reslent supplers. Haldar et al. (2014) developed a fuzzy MCDM approach for suppler selecton consderng the mportance degrees of specfc attrbutes as lngustc varables formulated by trangular and trapezodal fuzzy numbers. Torab et al. (2015) proposed a fuzzy stochastc b-objectve optmzaton model to solve a suppler selecton and order allocaton problem to mprove the supply chan reslence under operatonal and dsrupton rsks. Sahu et al. (2016) proposed a suppler evaluaton decson support system usng the VIKOR method consderng general and reslency crtera. Pramank et al. (2016) presented a fuzzy MCDM approach as an ad to developng a reslent suppler selecton actvty. Klb and Martel (2012) formulated a mxed nteger programmng model for handlng suppler selecton and order allocaton problem. Sawk (2013) desgned a mxed-nteger programmng model to solve a suppler selecton problem n a supply chan under dsrupton rsks. 210

3 Evaluatng Green and Reslent Suppler Performance: AHP-Fuzzy Topss Decson-Makng Approach 3 DEVELOPED GREEN AND RESILIENT SUPPLIER SELECTION APPROACH A laboratory nstrumentaton Orgnal Equpment Manufacturer wants to develop a reslent suppler selecton approach for evaluatng ther current supplers n order to plan for unexpected events. Addtonally, the company s keen to take ownershp of ther envronmental responsbltes. Ths research supports the company s requrements through development of a suppler selecton approach to facltate evaluaton and rankng of supplers based on ther performance wth respect to tradtonal, green and reslence crtera. Fgure 1 shows the herarchcal suppler selecton framework developed for ths task. The tradtonal sub-crtera nclude: cost, qualty, delvery relablty, performance hstory, turnover, lead tme, and operatng capacty. The green subcrtera nclude: envronmental management system, waste management and envronment related certfcate. The reslence sub-crtera nclude: flexblty, leanness, aglty robustness and vsblty (FLARV). AHP used lngustc expert assessment to determne the mportance weght for each crtera and sub-crtera. FTOPSIS was then adapted towards evaluatng supplers based on ther performance towards the crtera shown n Fgure 1. Subsequently, the rankng order of supplers was determned based on evaluaton derved from FTOPSIS. 3.1 AHP AHP s a mult-crtera decson makng algorthm, developed for consderng both qualtatve and quanttatve aspects of evaluaton (Saaty, 1977). It attempts to reduce complex decsons to a seres of parwse comparsons and then reveals the fnal weghts. In ths work, AHP was appled for determnng the mportance weght for each TGR crtera and sub-crtera. Table 1 shows the evaluaton scale n terms of lngustc varables that were used to perform parwse comparsons among TGR crtera and sub-crtera. Decson makers need to gve ther opnon about the mportance of every crtera and sub-crtera. AHP was mplemented as follows: Fgure 1: Crtera and sub-crtera for the tradtonal, green and reslent suppler selecton. 1. Use a decson maker s preference to buld a parwse comparson matrx (A) usng the evaluaton scale shown n Table 1: 1 a1,2 a1, j a2,1 1 a2, j A ; 1, 2, 3,..., I; j 1, 2, 3,..., J a,1 a,2 1 (1) where I refers to the number of supplers and J refers to the number of crtera. 2. Sum each column of A as follows: Column S a jj j, (2) 3. Buld the normalsed decson matrx (R) by dvdng each value n matrx A by the sum of ts column: A R Column (3) S 4. Determne the weght w j of each crteron by calculatng the average of ts weght wth respect to other crtera: 211

4 ICORES th Internatonal Conference on Operatons Research and Enterprse Systems Table 1: Evaluaton scale n lngustc varables. Scale Lngustc Varable 1 Equally mportant (EI) 3 Weakly mportant (WI) 5 Strongly more mportant (SMI) 7 Very strongly mportant (VSI) 9 Extremely mportant (EI) w I Fuzzy TOPSIS rows J (4) Hwang and Yoon (1981) developed TOPSIS to select an alternatve based on ts dstance to the deal soluton and the negatve deal soluton. FTOPSIS s an extenson of TOPSIS developed by Chen (2006) to handle the uncertanty n the lngustc assessment. In ths work, after determnng the mportance weght for each green and reslent crtera and sub-crtera, Fuzzy TOPSIS was appled to evaluate and rank supplers wth respect to ther TGR performance. It s noteworthy to menton that fuzzy TOPSIS was used rather TOPSIS to cope wth uncertan evaluaton of some supplers. Table 2 presents the lngustc varables and the correspondent trangular fuzzy numbers that were used to rank the alternatves consderng each crteron. Decson makers need to gve ther opnons about the performance of every suppler based on TGR crtera. FTOPSIS was mplemented as follows: Eq. (6) s used to normalse the fuzzy decson matrx to get the normalsed decson matrx ( R ): where r j R rj nxm aj nj mj,, m m m j j j (5) (6) The weghts of the crtera (w j ) obtaned from the AHP approach need to be multpled by the elements of the normalsed decson matrx ( R ) to form the weghted normalsed decson matrx ( V ). V v j nxm where v j s obtaned usng the followng equaton: vj rj x wj (7) (8) The fuzzy postve and negatve deal solutons are determned usng Eqs. 9 and 10, respectvely (Roy et al., 2004).,,..., n A v1 v2 v,,..., n A v1 v2 v (9) (10) The dstance of suppler I from the fuzzy postve deal soluton ( d ) and the fuzzy negatve deal soluton ( d ) are calculated as follows: where d dv vj, v j ; jn d dv vj, v j ; v j and j jn (11) v are fuzzy postve and negatve deal ponts for crteron j, respectvely. Based on d and d, the fuzzy closeness coeffcent (CC) for each suppler s then determned usng Eq. 12. The suppler wth the hghest CC (vares between 0 and 1) s selected as the best green and reslent suppler. CC d d d (12) Table 2: Lngustc varables and ther TFN used for evaluatng and rankng supplers. Lngustc varable Trangular fuzzy number Very low (VL) (1, 1, 3) Low (L) (1, 3, 5) Medum (M) (3, 5, 7) Hgh (H) (5, 7, 9) Very hgh (VH) (7, 9, 9) 212

5 Evaluatng Green and Reslent Suppler Performance: AHP-Fuzzy Topss Decson-Makng Approach 4 APPLICATION: A REAL CASE STUDY In To valdate the applcablty and effectveness of the developed methodology, t was appled wth a manufacturng company (Company A, henceforth) that desgn and produce thermal desorpton and tmeof-flght mass spectrometry nstrumentaton n the UK. Ther products are used for a varety of applcatons such as: envronmental montorng, detecton of chemcal warfare agents, qualty control & safety of food products, aroma proflng and envronmental forenscs. Company A ams to develop a purchasng strategy that helps n evaluatng ther current suppler wth respect to green and reslence performance n addton to the tradtonal busness crtera such as cost and qualty. Company A am to meet ther growth target by 2020, however, current and projected turnover have not been revealed upon the company s request. Our novel approach to suppler selecton has been appled n ths case study to help the purchasng manager: (1) develop a unfed TGR purchasng strategy and (2) evaluate ther current supply chan reslence n term of supplers performance towards the prevously defned TGR crtera (Fgure 1). The purchasng manager (PM) was nvted to select a number of supplers to valdate the proposed approach n evaluatng ther performance towards the dentfed crtera llustrated n Fgure 1. The PM has more than 18 years procurement experence. Two deep dscussons (each about 2 hours) were held to explan, dscuss and evaluate the TGR crtera, sub crtera and fve supplers (S) performance. In the frst step, AHP was mplemented to determne the mportance weght for each TGR crtera and sub-crtera. Thus, the PM was nvted to perform a parwse comparson among TGR crtera and sub-crtera usng the lngustc varables presented n Table 1. A par-wse comparson matrx was bult va the correspondence scale evaluaton (refer to Table 1) as shown n Table 3. Eqs.1-4 were then appled to determne the mportance weghts of each crtera and sub-crtera whch are presented n Table 4. Accordng to the calculatons shown n Table 4, the weght of tradtonal crtera s ; the weght of green crtera s ; and the weght of reslence crtera s The reslence crtera obtaned the hghest weght followed by the tradtonal and then green pllar. Thus, the reslence crtera are deemed to be the most mportant compared wth the other tradtonal and green crtera. The PM confrmed that the company s current strategy was to buld a reslent supply chan rather Table 3: Decson matrx among TGR crtera. TGR crtera Tradtonal Green Reslence Tradtonal 1 9 1/5 Green 1/9 1 1/9 Reslence than selectng supplers accordng to performance towards tradtonal crtera such as costs and qualty. After determnng the mportance for each TGR crteron, fuzzy TOPSIS was mplemented to obtan the rankng order of supplers based on ther TGR performance. The PM was nvted for another ntervew to evaluate the performance of selected supplers wth respect to each sub-crteron usng the evaluaton scale presented n Table 2. Table 5 shows the lngustc evoluton of supplers towards ther TGR performance. Fuzzy TOPSIS was appled usng Eqs 5-12 to determne the matrx of normalzed and weghted normalzed trangular fuzzy numbers n addton to the postve deal soluton ( D ) and the negatve deal soluton ( D ). The closeness coeffcent (CC) for each suppler s determned by the obtaned dstances usng Eq. 12. Table 6 shows the performance evaluaton and rank of supplers wth respect to each TGR crteron, whch s represented graphcally, Fgure 2. Accordng to the obtaned results, S 2 revealed the hghest TGR performance wth a closeness coeffcent of Comparng wth the other supplers the closeness coeffcent of S 4 ( ), S 2 ( ), S 5 ( ) and S 3 ( ) were respectvely n rank after S 1. 5 CONCLUSIONS Ths work presents a unfed tradtonal busness, green and reslent suppler selecton approach. The framework was developed by dentfyng tradtonal, green and reslence crtera and sub-crtera. Two steps were followed to evaluate and rank supplers. Frstly, AHP was appled to determne the mportance weght of each crteron and sub-crteron based on the lngustc evaluaton of a purchasng manager. The AHP results ndcate that the reslence crtera are deemed the most mportant for company A, followed by tradtonal and green, respectvely. Secondly, fuzzy TOPSIS was appled to reveal the order rankng of supplers based on ther TGR performance wth respect to the mportance weght of each crteron and sub-crteron. Based on the obtaned supplers performance, we recommended that company A works wth some of ther supplers (e.g. S 3 and S 5 ) to mprove ther reslence. The results 213

6 ICORES th Internatonal Conference on Operatons Research and Enterprse Systems Table 4: Weghts of TGR crtera and sub-crtera obtaned by AHP. Crtera IW Rankng Sub-crtera IW Rankng Tradtonal TC TC TC TC TC TC TC Green GC GC GC Reslence RC RC RC RC RC Table 5: Evaluaton of supplers towards ther tradtonal, green and reslence performance. Crtera Sub-crtera S l S 2 S 3 S 4 S 5 Tradtonal TC1 H H M M M TC2 M M M M M TC3 M M M M M TC4 VL L M M M TC5 H L M L L TC6 M M M M M TC7 H M M M M Green GC1 M M M M M GC2 M M M M M GC3 M M M M M Reslence RC1 M M M H L RC2 H H M M L RC3 M M M L L RC4 H M L H L RC5 L L L M L Table 6: Closeness coeffcent and dstances from the postve deal/negatve deal solutons related to supplers. S 1 S 2 S 3 S 4 S 5 D D CC rank Fgure 2: A graphcal comparson of supplers closeness coeffcent performance wth respect to TGR crtera ndvdually. 214

7 Evaluatng Green and Reslent Suppler Performance: AHP-Fuzzy Topss Decson-Makng Approach demonstrate the applcablty of the novel approach n assstng the purchasng manager at company A to produce a green and reslent purchasng strategy through suppler evaluaton. The developed methodology can be appled to other companes as a tool to measure the healthness of ther supply chan n terms of reslence and green performance. Furthermore, t medates the uncertanty n experts opnons through the use of fuzzy evaluaton. Ongong work ncludes the ncorporaton of socal crtera to those already studed here. Fnally, the authors are developng a mult-objectve optmzaton model to help decson makers n solvng order allocaton problem wth respect to TGR performance of supplers. REFERENCES Akman, G., Evaluatng supplers to nclude green suppler development programs va fuzzy c-means and VIKOR methods. Comput. Ind. Eng. 86, BBC News, 18 Mar Japan dsaster: Supply shortages n three months. BBC News. (accessed ). Bng, X., Bloemhof-Ruwaard, J., Chaabane, A., van der Vorst, J., Global reverse supply chan redesgn for household plastc waste under the emsson tradng scheme. J. Clean. Prod. 103, Assaou, N., Haouar, M., Hassn, E., Suppler selecton and order lot szng modelng: a revew. Com. Oper. Res. 34, Burnson, P., 30 October Naton s Supply Chans Dsrupted by Hurrcane Sandy. Logstcs Management. (accessed ). Büyüközkan and Çfç, 2010 G. Büyüközkan, G. Çfç. Evaluaton of the green supply chan management practces: a fuzzy ANP approach. Producton Plannng & Control, Frst (2010), pp Chen, C.T., Ln, C.T., Huang, S.F., A fuzzy approach for suppler evaluaton and selecton n supply chan management. Int. J. Prod. Econ. 102, Dckson, G., An analyss of vendor selecton systems and decsons, J. Purch. 2(1), Govndan, K., Rajendran, S., Sarks, J., Murugesan, P., Mult crtera decson makng approaches for green suppler evaluaton and selecton: a lterature revew. J. Clean. Prod. 98, Govndan, K., Svakumar, R., Green suppler selecton and order allocaton n a low-carbon paper ndustry: ntegrated mult-crtera heterogeneous decson makng and mult-objectve lnear programmng approaches. Ann. Oper. Res. 238, Ha, S.H., Krshnan, R., A hybrd approach to suppler selecton for the mantenance of a compettve supply chan. Expe. Sys. wth Appl. 34, Haldar, A., Ray, A., Banerjee, D., Ghosh, S., Res- lent suppler selecton under a fuzzy envronment. Int. J. Manage. Sc. Eng. Manage. 9 (2), Hall, J., 16 Apr Volcanc Ash Cloud Leaves Shops Facng Shortages of Frut, Vegetables and Medcne. The Daly Telegraph. Hwang, C.L, Yoon, K., Multple attrbute decson makng: methods and applcatons. New York: Sprnger-Verlag. Kannan, D., Govndan, K., Rajendran, S., Fuzzy axomatc desgn approach based green suppler selecton: a case study from sngapore. J. Clean. Prod. 96, Klb, W.; Martel, A. Scenaro-based Supply Chan Network rsk modelng. Eur. J. Oper. Res. 2012, 223, Konur, D., Campbell, J.F., Monfared, J.A., Economc and envronmental consderatons n a stochastc nventory control model wth order splttng under dfferent delvery schedules among supplers. Omega, 71, Kuo, R.J., Y.J. Ln. Suppler selecton usng analytc network process and data envelopment analyss. Internatonal. Journal of Producton Research (2011), pp. 1-12Frst. Mtra, K.; Gud, R.D.; Patwardhan, S.C.; Sardar, G. Towards reslent supply chans: Uncertanty analyss usng fuzzy mathematcal programmng. Chem. Eng. Res. Des. 2009, 87, Mohammed A. and Wang Q Integrty of an RFIDenabled HMSC Network. Proceedngs of the Thrd Internatonal Conference on Dgtal Enterprse and Informaton Systems, Shenzhen, Chna, 2015a, Mohammed A. and Wang Q. and L X. 2017a. Developng a meat supply chan network desgn usng a multobjectve possblstc programmng approach. Brtsh Food Journal, 119, 3, Mohammed, A. and Wang, Q., 2017b. The fuzzy multobjectve dstrbuton planner for a green meat supply chan. Internatonal J. Pro Eco., 184, Mohammed, A., Wang, Q., Alyahya, S. and Bnnette, N. 2017c. Desgn and optmzaton of an RFID-enabled automated warehousng system under uncertantes: A mult-crteron fuzzy programmng approach. The Internatonal Journal of Advanced Manufacturng Technology. 91 (5), Pramank, D., Subhash, N., Haldar, A., Mondal, S.C., Naskar, S.N., Ray. A., Reslent suppler selecton usng AHP-TOPSIS-QFD under a fuzzy envronment. Internatonal Journal of Management Scence and Engneerng Management, 12 (1), Purvs, L., Spall, S., Nam, M. and Spegler, V Developng a reslent supply chan strategy durng boom and bust, Producton Plannng & Control, 27:7-8, Rajesh, R.; Rav, V. Suppler selecton n reslent supply chans: A grey relatonal analyss approach. J. Clean. Prod. 2015, 86, Saaty, T. L. (1977). A scalng method for prortes n herarchcal structures. Journal of Mathematcal Psychology, 15(3),

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