Fuzzy Supplier Selection Strategies in Supply Chain Management

Supplier selection is a major strategy for manufacture to run the production process smoothly in supply chain network. Supplier categorization, selection and performance evaluation are decisions of strategic importance to companies. Global competition, mass customization, high customer expectations and harsh economic conditions are forcing companies to rely on external suppliers to contribute a larger portion of parts, materials, and assemblies to finished products and to manage a growing number of processes and functions that were once controlled internally. Thus supplier performance evaluation is very important to choose the right supplier for the right product for supply chain management. In this paper a fuzzy supplier selection algorithm (FSSA) is implemented to rank the technically efficient vendors according to both predetermined performance criteria and additional product-related performance criteria. Investigation of the properties of the best supplier alternative by ranking the fuzzy indices allow to develop an algorithm which is based on calculating fuzzy suitability indices for the efficient supplier alternatives and validity is illustrated through an example problem

Strategic Sourcing and Supplier Selection in the U.S. Textile— Apparel—Retail Supply Network

This research investigates the key causal linkages in supply chain management—the impact of strategic sourcing and supplier selection on firm performance in the U.S. textile–apparel–retail supply network. A conceptual framework was developed and the empirical survey-based research methodology was used to gather data from the U.S. textile–apparel–retail complex. The data collection resulted in 181 responses, representing a 38.2% response rate. Structural equation modeling was used to assess the research model and test the research hypotheses. The research findings support that strategic sourcing has a significant and positive effect on business performance, and supplier selection has a significant and positive effect on the firm’s ability to gain competitive advantages. The research concludes with implications, limitations, and directions for future research

Proactive and reactive supply chain strategies for risk mitigation

The pandemic has forever changed the way our industry evaluates material supply risks. In this presentation, we share two case studies of proactive and reactive supply risk mitigation efforts. Proactive: Pre-pandemic, in early 2019, we had the opportunity to perform supplier selection for a new single-use facility. The team’s remit for assembly design: modular and able to be dual sourced. This remit reflected the facility’s plan to be flexible and supplier agnostic. Using the three-legged stool model, the team vetted suppliers based on their strengths in procurement, quality and technology. The suppliers were scored based on this cross function criteria: Strategic Business Continuity Operational Delivery Average Lead Time From RFP Quality and Regulatory Compliance Global Supplier/ Ability to Manufacture at \u3e1 Site Modular designs Control over sub-components This process enabled us to understand the cost of a strong supplier and partner, as opposed to the traditional RFP model of selecting the lowest cost supplier. Using this cross-functional, proactive approach to design and supplier selection, the team benefited from the selection of strong suppliers and designs that had identified alternate sources. Reactive: Pre-pandemic, the idea of using expired materials in a GMP process seemed outlandish. As the reality of the supply crisis set it, our team encountered a scenario where needed material would expire prior to the planned run, and additional materials would not be delivered in time. By partnering with our supplier, we were able to develop a joint justification for shelf-life extension of the single-use assembly. This strategy has evolved into a report which can be leveraged across our internal network to extend shelf-life of single-use assemblies. The key takeaway, we must continue to think outside of the box as an industry and innovate new strategies for supply risk mitigation, by proactively planning and being flexible enough to react to new scenarios

Assessing and Selecting Sustainable and Resilient Suppliers in Agri-Food Supply Chains Using Artificial Intelligence: A Short Review

[EN] The supplier evaluation and selection process is critical to increase the sustainability and resilience of the agri-food supply chain. Therefore, in this sector, it is necessary to consider sustainability and resilience criteria in the supplier evaluation and selection process. The use of arti¿cial intelligence techniques allows managing of a lot of information and the reduction of uncertainty for decision making. The objective of this article is to analyze articles that address the selection of suppliers in agrifood supply chains that pursue to increase their sustainability and resilience by using arti¿cial intelligence techniques to analyze the techniques and criteria used and draw conclusions.Authors of this publication acknowledge the contribution of the Project 691249, RUC-APS "Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems" (www.ruc-aps.eu), funded by the European Union under their funding scheme H2020-MSCA-RISE-2015.Zavala-Alcívar, A.; Verdecho Sáez, MJ.; Alfaro Saiz, JJ. (2020). Assessing and Selecting Sustainable and Resilient Suppliers in Agri-Food Supply Chains Using Artificial Intelligence: A Short Review. IFIP Advances in Information and Communication Technology. 598:501-510. https://doi.org/10.1007/978-3-030-62412-5_41S501510598Brandenburg, M., Govindan, K., Sarkis, J., Seuring, S.: Quantitative models for sustainable supply chain management: developments and directions. Eur. J. Oper. Res. 233, 299–312 (2014)Ocampo, L.A., Abad, G.K.M., Cabusas, K.G.L., Padon, M.L.A., Sevilla, N.C.: Recent approaches to supplier selection: a review of literature within 2006–2016. Int. J. Integr. Supply Manage. 12, 22–68 (2018)Valipour, S., Safaei, A.: A resilience approach for supplier selection: using Fuzzy analytic network process and grey VIKOR techniques. J. Clean. Prod. 161, 431–451 (2017)Amindoust, A.: A resilient-sustainable based supplier selection model using a hybrid intelligent method. Comput. Ind. Eng. 126, 122–135 (2018)Zavala-Alcívar, A., Verdecho, M.-J., Alfaro-Saiz, J.-J.: A conceptual framework to manage resilience and increase sustainability in the supply chain. Sustainability 12(16), 6300 (2020)Villalobos, J.R., Soto-Silva, W.E., González-Araya, M.C., González-Ramirez, R.G.: Research directions in technology development to support real-time decisions of fresh produce logistics: A review and research agenda. Comput. Electron. Agric. 167, 105092 (2019)Ristono, A., Santoso, P.B., Tama, I.P.: A literature review of design of criteria for supplier selection. J. Ind. Eng. Manage. 11, 680–696 (2018)Torres-Ruiz, A., Ravindran, A.R.: Multiple criteria framework for the sustainability risk assessment of a supplier portfolio. J. Clean. Prod. 172, 4478–4493 (2018)Setak, M., Sharifi, S., Alimohammadian, A.: Supplier selection and order allocation models in supply chain management: a review. World Appl. Sci. J. 18, 55–72 (2012)Ravindran, A.R., Warsing, D.P.: Supplier selection models and methods. In: Supply Chain Engineering: Models and Applications. Taylor and Francis Group, Boca Raton, Florida (2013)De Boer, L., Labro, E., Morlacchi, P.: A review of methods supporting supplier selection. Eur. J. Purch. Supply Manage. 7, 75–89 (2011)De Felice, F., Deldoost, M.H., Faizollahi, M., Petrillo, A.: Performance measurement model for the supplier selection based on AHP. Int. J. Eng. Bus. Manag. 7, 1–13 (2015)Zimmer, K., Fröhling, M., Schultmann, F.: Sustainable supplier management – a review of models supporting sustainable supplier selection, monitoring and development. Int. J. Prod. Res. 54, 1412–1442 (2016)Christopher, M., Peck, H.: Building the resilient supply chain. Int. J. Logist. Manag. 15, 1–14 (2014)Ali, A., Mahfouz, A., Arisha, A.: Analysing supply chain resilience: integrating the constructs in a concept mapping framework via a systematic literature review. Supply Chain Manage. 22, 16–39 (2017)Verdecho, M., Alarcón-Valero, F., Pérez-Perales, D., et al.: A methodology to select suppliers to increase sustainability within supply chains. Cent. Eur. J. Oper. Res. (2020). https://doi.org/10.1007/s10100-019-00668-3Rabelo, L., Bhide, S., Gutierrez, E.: Artificial Intelligence: Advances in Research and Applications. Nova Science Publishers, Inc., Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL, United States (2017)Denyer, D., Tranfield, D.: Producing a systematic review. In: The Sage Handbook of Organizational Research Methods. SAGE Publications Ltd., pp. 671–689 (2019)Chen, Y.-J.: Structured methodology for supplier selection and evaluation in a supply chain. Inf. Sci. (Ny) 181, 1651–1670 (2011)Hamdi, F., Ghorbel, A., Masmoudi, F., Dupont, L.: Optimization of a supply portfolio in the context of supply chain risk management: literature review. J. Intell. Manuf. 29(4), 763–788 (2015). https://doi.org/10.1007/s10845-015-1128-3Kumar, V., Srinivasan, S., Das, S.: Optimal solution for supplier selection based on SMART fuzzy case base approach. In: 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems. SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems. ISIS 2014, Institute of Electrical and Electronics Engineers Inc., Department of Computer Science, IISJ Yokohama, Tokai Chiba, Japan, pp. 386–391 (2014)Jahani, A., Murad, M.A.A., bin Sulaiman, M.N., Selamat, M.H.: An agent-based supplier selection framework: Fuzzy case-based reasoning perspective. Strateg. Outsourcing 8, 180–205 (2015)Wang, Q.: Hybrid knowledge-based flexible supplier selection. In: 8th International Conference on Management of e-Commerce and e-Government. ICMeCG 2014. Institute of Electrical and Electronics Engineers Inc., Department of Information Management, Shanghai Finance University, Shanghai, China, pp. 235–239 (2014)Bai, C., Sarkis, J.: Green supplier development: analytical evaluation using rough set theory. J. Clean. Prod. 18, 1200–1210 (2010)Bai, C., Sarkis, J.: Integrating sustainability into supplier selection with grey system and rough set methodologies. Int. J. Prod. Econ. 124, 252–264 (2010)Guo, F., Lu, Q.: Partner selection optimization model of agricultural enterprises in supply chain. Adv. J. Food Sci. Technol. 5, 1285–1291 (2013)Azadnia, A.H., Saman, M.Z.M., Wong, K.Y.: Sustainable supplier selection and order lot-sizing: an integrated multi-objective decision-making process. Int. J. Prod. Res. 53, 383–408 (2015)Miranda-Ackerman, M.A., Azzaro-Pantel, C., Aguilar-Lasserre, A.A.: A green supply chain network design framework for the processed food industry: application to the orange juice agrofood cluster. Comput. Ind. Eng. 109, 369–389 (2017)Hajikhani, A., Khalilzadeh, M., Sadjadi, S.J.: A fuzzy multi-objective multi-product supplier selection and order-allocation problem in supply chain under coverage and price considerations: an urban agricultural case study. Sci. Iran. 25, 431–449 (2018)Zhang, H., Cui, Y.: A model combining a Bayesian network with a modified genetic algorithm for green supplier selection. Simulation 95, 1165–1183 (2019)Yadav, S., Garg, D., Luthra, S.: Selection of third-party logistics services for internet of things-based agriculture supply chain management. Int. J. Logist. Syst. Manage. 35, 204–230 (2020)Yazdani, M., Wang, Z.X., Chan, F.T.S.: A decision support model based on the combined structure of DEMATEL, QFD and fuzzy values. Soft. Comput. 24(16), 12449–12468 (2020). https://doi.org/10.1007/s00500-020-04685-2Zhang, H., Feng, H., Cui, Y., Wang, Y.: A fuzzy Bayesian network model for quality control in O2O e-commerce. Int. J. Comput. Commun. Control 15(1), (2020). article number 1003. https://doi.org/10.15837/ijccc.2020.1.3783Amiri, S.A.H.S., Zahedi, A., Kazemi, M., Soroor, J., Hajiaghaei-Keshteli, M.: Determination of the optimal sales level of perishable goods in a two-echelon supply chain network. Comput. Ind. Eng. 139, 106156 (2020)Roy, S., et al.: A framework for sustainable supplier selection with transportation criteria. Int. J. Sustain. Eng. 13(2), 77–92 (2020)Parkouhi, S.V., Ghadikolaei, A.S., Lajimi, H.F.: Resilient supplier selection and segmentation in grey environment. J. Clean. Prod. 207, 1123–1137 (2019)Camarinha-Matos, L.M., Afsarmanesh, H., Galeano, N., Molina, A.: Collaborative networked organizations – concepts and practice in manufacturing enterprises. Comput. Ind. Eng. 57, 46–60 (2009)Lezoche, M., Panetto, H., Kacprzyk, J., Hernandez, J., Díaz, M.A.: Agri-food 4.0: a survey of the supply chains and technologies for the future agriculture. Comput. Ind. 117, 103187 (2020)Alikhani, R., Torabi, S., Altay, N.: Strategic supplier selection under sustainability and risk criteria. Int. J. Prod. Econ. 208, 69–82 (2019

A methodology to select suppliers to increase sustainability within supply chains

[EN] Sustainability practice within supply chains remains in an early development phase. Enterprises still need tools that support the integration of sustainability strategy into their activity, and to align their sustainability strategy with the supplier selection process. This paper proposes a methodology using a multi-criteria technique to support supplier selection decisions by taking two groups of inputs that integrate sustainability performance: supply chain performance and supplier assessment criteria. With the proposed methodology, organisations will have a tool to select suppliers based on their development towards sustainability and on their alignment with the supply chain strategy towards sustainability. The methodology is applied to an agri-food supply chain to assess sustainability in the supplier selection process.The authors of this publication acknowledge the contribution of Project GV/2017/065 'Development of a decision support tool for the management and improvement of sustainability in supply chains', funded by the Regional Valencian Government. Also, the authors acknowledge Project 691249, RUC-APS: Enhancing and implementing knowledge-based ICT solutions within high risk and uncertain conditions for agriculture production systems (www.ruc-aps.eu), funded by the European Union according to funding scheme H2020-MSCA-RISE-2015.Verdecho Sáez, MJ.; Alarcón Valero, F.; Pérez Perales, D.; Alfaro Saiz, JJ.; Rodríguez Rodríguez, R. (2021). A methodology to select suppliers to increase sustainability within supply chains. Central European Journal of Operations Research. 29:1231-1251. https://doi.org/10.1007/s10100-019-00668-3S1231125129Agarwal G, Vijayvargy L (2012) Green supplier assessment in environmentally responsive supply chains through analytical network process. In: Proceedings international multiconference of engineers and computer scientists, Hong KongAgeron B, Gunasekaran A, Spalanzani A (2012) Sustainable supply management: an empirical study. Int J Prod Econ 140(1):168–182Akarte MM, Surendra NV, Ravi B, Rangaraj N (2001) Web based casting supplier evaluation using analytical hierarchy process. J Oper Res Soc 52:511–522Alfaro Saiz JJ, Rodríguez R, Ortiz Bas A, Verdecho MJ (2010) An information architecture for a performance management framework by collaborating SMEs. Comput Ind 61:676–685Alfaro JJ, Ortiz A, Rodríguez R (2007) Performance measurement system for enterprise networks. Int J Prod Perform Manag 56(4):305–334Awasthi A, Govindan K, Gold S (2018) Multi-tier sustainable global supplier selection using a fuzzy AHP-VIKOR based approach. Int J Prod Econ 195:106–117Azadnia AH, Ghadimi P, Zameri M, Saman M, Wong KY, Heavey C (2013) An integrated approach for sustainable supplier selection using fuzzy logic and fuzzy AHP. Appl Mech Mater 315:206–221Azimifard A, Moosavirad SH, Ariafar S (2018) Selecting sustainable supplier countries for Iran’s steel industry at three levels by using AHP and TOPSIS methods. Resour Pol 57:30–44Bai C, Sarkis J (2010) Integrating sustainability into supplier selection with grey system and rough set methodologies. Int J Prod Econ 124:252–264Bhagwat R, Sharma MK (2007) Performance measurement of supply chain management: a balanced scorecard approach. Comput Ind Eng 53(1):43–62Bititci US, Mendibil K, Martinez V, Albores P (2005) Measuring and managing performance in extended enterprises. Int J Oper Prod Manag 25(4):333–353Brewer PC, Speh TW (2000) Using the balanced scorecard to measure supply chain performance. J Bus Logist 21(1):75–93Bullinger HJ, Kühner M, Hoof AV (2002) Analysing supply chain performance using a balanced measurement method. Int J Prod Res 40(15):3533–3543Chan FTS (2003) Interactive selection model for supplier selection process: an analytical hierarchy process approach. Int J Prod Res 41(15):3549–3579De Boer L, Labro E, Morlacchi P (2001) A review of methods supporting supplier selection. Eur J Purch Supply Manag 7(2):75–89Degraeve Z, Labro E, Roodhooft F (2000) An evaluation of supplier selection methods from a total cost of ownership perspective. Eur J Oper Res 125(1):34–58Dobos I, Vörösmarty G (2014) Green supplier selection and evaluation using DEA-type composite indicators. Int J of Prod Econ 157(11):273–278Dou Y, Sarkis J (2010) A joint location and outsourcing sustainability analysis for a strategic offshoring decision. Int J Prod Res 48(2):567–592Dyllick T, Hockerts K (2002) Beyond the business case for corporate sustainability. Bus Strategy Environ 11:130–141Falatoonitoosi E, Leman Z, Sorooshian S (2013) Modeling for green supply chain evaluation. Math Probl Eng 2013:1–9Farzad T, Rasid OM, Aidy A, Rosnah MY, Alireza E (2008) AHP approach for supplier evaluation and selection in a steel manufacturing company. JIEM 1(2):54–76Ferreira LMDF, Silva C, Garrido Azevedo S (2016) An environmental balanced scorecard for supply chain performance measurement (Env_BSC_4_SCPM). Benchmark Int J 23(6):1398–1422Figge F, Hahn T, Schaltegger S, Wagner M (2002) The sustainability balanced scorecard: linking sustainability management to business strategy. Bus Strat Env 11:269–284Folan P, Browne J (2005) Development of an extended enterprise performance measurement system. Prod Plan Control 16(6):531–544Freeman J, Chen T (2015) Green supplier selection using an AHP-entropy-TOPSIS framework. Supply Chain Manag 20:327–340Genovese A, Koh L, Bruno G, Esposito E (2013) Greener supplier selection: state of the art and some empirical evidence. Int J Prod Res 51(10):2868–2886Ghodsypour SH, O’Brien C (1998) A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming. Int J Prod Econ 56–57:199–212Glock CH, Grosse EH, Ries JM (2017) Decision support models for supplier development: systematic literature review and research agenda. Int J Prod Econ 194:246–260Govindan K, Khodaverdi R, Jafarian A (2013) A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach. J Clean Prod 47:345–354Govindan K, Rajendran S, Sarkis J, Murugesan P (2015) Multi criteria decision making approaches for green supplier evaluation and selection: a literature review. J Clean Prod 98:66–83Gunasekaran A, Patel C, Tirtiroglu E (2001) Performance measures and metrics in a supply chain environment. Int J Oper Prod Manag 21(1/2):71–87Ho W, Xu X, Dey PK (2010) Multi-criteria decision making approaches for supplier evaluation and selection: a literature review. Eur J Oper Res 202:16–24Hsu CW, Hu AH (2009) Applying hazardous substance management to supplier selection using analytic network process. J Clean Prod 17(2):255–264Hsu CW, Kuo TC, Chen SH, Hu AH (2013) Using DEMATEL to develop a carbon management model of supplier selection in green supply chain management. J Clean Prod 56:164–172Huan SH, Sheoran SK, Wang G (2004) A review and analysis of supply chain operations reference (SCOR) model. Supply Chain Manag Int J 9(9):23–29Hutchins M, Sutherland JH (2008) An exploration of measures of social sustainability and their application to supply chain decisions. J Clean Prod 16(15):1688–1698Igarashi M, Boer L, Magerholm Fet A (2013) What is required for greener supplier selection? A literature review and conceptual model development. J Purch Supply Manag 19(4):247–263Jimenez-Jimenez D, Martínez-Costa M, Sanchez Rodriguez C (2019) The mediating role of supply chain collaboration on the relationship between information technology and innovation. J Knowl Manag 23(3):548–567Kaplan RS, Norton DP (1992) The balanced scorecard: measures that drive performance. Harvard Bus Rev 70(1):71–79Luthra S, Govindan K, Kannan D, Kumar Mangla S, Prakash Garg C (2017) An integrated framework for sustainable supplier selection and evaluation in supply chains. J Clean Prod 140:1686–1698Maestrini V, Luzzini D, Maccarrone P, Caniato F (2017) Supply chain performance measurement systems: a systematic review and research agenda. Int J Prod Econ 183A:299–315Masella C, Rangone A (2000) A contingent approach to the design of vendor selection systems for different types of co-operative customer/supplier relationships. Int J Oper Prod Manag 20(1):70–84Miller GA (1956) The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol Rev 63:81–97Mohammed A, Harris I, Govindan K (2019) A hybrid MCDM-FMOO approach for sustainable supplier selection and order allocation. Int J Prod Econ 217:171–184Motevali-Haghighi S, Torabi SA, Ghasemi R (2016) An integrated approach for performance evaluation in sustainable supply chain networks (with a case study). J Clean Prod 137:579–597Nawaz W, Koç M (2018) Development of a systematic framework for sustainability management of organizations. J Clean Prod 171:1255–1274Nie X (2013) Green suppliers selecting based on analytic hierarchy process for biotechnology industry. In: Zhong Z (ed) Proceedings of the international conference on information engineering and applications. Springer, London, pp 253–260Nielsen IE, Banaeian N, Golińska P, Mobli H, Omid M (2014) Green supplier selection criteria: from a literature review to a flexible framework for determination of suitable criteria. In: Golinska P (ed) Logistics operations, supply chain management and sustainability. Springer, Cham, pp 79–99Noci G (1997) Designing ‘green’ vendor rating systems for the assessment of a supplier’s environmental performance. Eur J Purch Supply Manag 3(2):103–114Petersen KJ, Handfield RB, Ragatz GL (2005) Supplier integration into new product development: coordinating product, process and supply chain design. J Oper Manag 23:371–388Pishchulov G, Trautrims A, Chesney T, Gold S, Schwab L (2019) The voting analytic hierarchy process revisited: a revised method with application to sustainable supplier selection. Int J Prod Econ 211:166–179Popovic T, Kraslawski A, Barbosa-Póvoa A, Carvalho A (2017) Quantitative indicators for social sustainability assessment of society and product responsibility aspects in supply chains. J Int Stud 10(4):9–36Qorri A, Mujki Z, Kraslawski A (2018) A conceptual framework for measuring sustainability performance of supply chains. J Clean Prod 189:570–584Reefke H, Trocchi M (2013) Balanced scorecard for sustainable supply chains: design and development guidelines. Int J Prod Perform Manag 62(8):805–826Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, New YorkSaaty RW (1987) The analytic hierarchy process: what it is and how it is used. Math Model 9(3–5):161–176Saaty TL (2008) Decision making with the analytic hierarchy process. Int J Serv Sci 1(1):83–98Saaty TL, Ozdemir MS (2003) Why the magic number seven plus or minus two. Math Comput Model 38(3–4):233–244Seuring S, Müller M (2008) From a literature review to a conceptual framework for sustainable supply chain management. J Clean Prod 16:1699–1710Shaik M, Abdul-Kader W (2011) Green supplier selection generic framework: a multi-attribute utility theory approach. Int J Sustain Eng 4(1):37–56Shi P, Yan B, Shi S, Ke C (2015) A decision support system to select suppliers for a sustainable supply chain based on a systematic DEA approach. Inf Technol Manag 16(1):39–49Superdecisions (2018) Tutorial on hierarchical decision models. Creative Decisions Foundation. https://www.superdecisions.com/sd_resources/v28_man03.pdf. Accessed 7 Jan 2018Thakkar J, Kanda A, Deshmukh S (2009) Supply chain performance measurement framework for small and medium scale enterprises. Benchmark Int J 16(5):702–723Theißen S, Spinler S (2014) Strategic analysis of manufacturer–supplier partnerships: an ANP model for collaborative CO2 reduction management. Eur J Oper Res 233(2):383–397Tseng ML, Lim M, Wong WP (2015) Sustainable supply chain management: a closed-loop network hierarchical approach. Ind Manag Data Syst 115(3):436–461Uysal F (2012) An integrated model for sustainable performance measurement in supply chain. Proc Soc Behav Sci 62:689–694Valenzuela L, Maturana S (2016) Designing a three-dimensional performance measurement system (SMD3D) for the wine industry: a Chilean example. Agric Syst 142:112–121Verdecho MJ, Alfaro-Saiz JJ, Rodriguez-Rodriguez R, Ortiz-Bas A (2012) A multi-criteria approach for managing inter-enterprise collaborative relationships. Omega 40:249–263Virender P, Jayant A (2014) A green supplier selection model for an agriculture-machinery industry. Int J Appl Eng Res 9(5):597–605Weber CA, Current JR, Benton WC (1991) Vendor selection criteria and methods. Eur J Oper Res 50(1):2–18Xu L, Kumar DT, Madan Shankar K, Kannan D, Chen G (2013) Analyzing criteria and sub-criteria for the corporate social responsibility-based supplier selection process using AHP. Int J Adv Manuf Technol 68(1–4):907–916Xu Z, Qin J, Liu J, Martínez L (2019) Sustainable supplier selection based on AHP Sort II in interval type-2 fuzzy environment. Inf Sci 483:273–293Zaklad A, McKnight R, Kosansky A, Piermarini J (2004) The social side of the supply chain. Ind Eng 36(2):40–44Zhe S, Wong NT, Lee LH (2013) Using data envelopment analysis for supplier evaluation with environmental considerations. In: International systems conference, OrlandoZimmer K, Fröhling M, Schultmann F (2016) Sustainable supplier management: a review of models supporting sustainable supplier selection, monitoring and development. Int J Prod Res 54(5):1412–144

A supplier selection strategy within the Malaysian telecommunications industry

The telecommunication industry in Malaysia has grown rapidly over the last 15 years, with effective supply chain management becoming increasing important within the sector. A multitude of providers and part owned Malaysian government companies, vendors and suppliers are involved in generating and creating value-adding products and services within this sector (across wireless, wireline, broadband business and consumer lines of business). This paper describes key challenges facing a major telecoms service provider in Malaysia with regards to drivers involved in the overall procurement and supplier selection with regards to components of performance management, decision-making, selection techniques, quality and cost management, procurement policy and procurement ethics. This paper further focuses on defining and detailing research currently being undertaken to develop a framework for identifying supplier selection drivers that are inherent within the sector and suggests a research approach to investigate and develop strategies for supplier selection for the telecommunications industry in Malaysia

Supplier Portfolio Selection and Optimum Volume Allocation: A Knowledge Based Method

Selection of suppliers and allocation of optimum volumes to suppliers is a strategic business decision. This paper presents a decision support method for supplier selection and the optimal allocation of volumes in a supplier portfolio. The requirements for the method were gathered during a case study that was conducted within the logistics unit of Shell Chemicals Europe. The proposed method is based on the classical view by Sprague and Carlson of sequence and interaction of the different phases of decision making in a decision support system and supports Kraljic’s portfolio approach for supplier management. This method aims to help the managers in making decisions on the allocation of volumes to suppliers while simultaneously trying to satisfy conflicting objectives of improvement in benefit and reduction in risk. A mathematical model to struc-ture the problem is presented, knowledge elicited from the managers is used to parameterize the mathemati-cal model and a multi-objective, hierarchical optimization procedure produces ‘trade-off’ outputs. The man-agers can also conduct interactive post optimization ‘what-if’ analysi

Improving sustainability performance through supplier relationship management in the tobacco industry

Purpose: The purpose of this study is to explore how tobacco manufacturing companies can improve their sustainability performance via effective supplier relationship management (SRM). Design/methodology/approach: This study has adopted a single case study of an international tobacco company. The primary data involved semi-structured interviews with participants from the case company who are familiar with sustainable SRM in the tobacco industry and are engaging in various techniques to improve sustainability performance. Findings: The drivers for sustainable SRM commonly identified in literature are observable within the case company. There is also clear evidence of integrating sustainability in its SRM processes. However, the perception of sustainability as a requirement to meet stringent regulations limits its scope and drive in pursuing sustainable SRM. It has also limited supplier sustainability evaluation and performance metrics. Furthermore, the findings of this paper reinforce the importance of a procurement team’s ability to work with other functional teams in implementing sustainable SRM. The findings also contribute to the emerging literature on the impact of sustainability on supplier segmentation and multi-tier supplier management. Research limitations/implications: This study provides insight into the varying SRM methods used in the tobacco industry to ensure compliance and improve sustainability performance. However, further research is required to explore the generalisability of the findings of this study derived from a single case study. Originality/value: The tobacco industry is an under-researched industry, particularly in terms of sustainable operations and supply chain management practices. The findings of this study seem to be relevant to those comparable industries with stringent regulations as well

An assessment of supply chain and innovation management practices in the manufacturing industries in Turkey

This paper aims at assessing the supply chain and innovation management in the manufacturing industries in Turkey on an empirical basis. The assessments presented are based on parts of the data and information collected through the execution of the Competitive Strategies and Best Practices Benchmarking Questionnaire in 82 companies from four sectors of the manufacturing industries in Turkey. Results of these sectoral benchmarking studies reported elsewhere indicate the need of adopting product differentiation particularly through more knowledge intensive products as the dominant competitive strategy and also the need for improvement in various areas of supply chain as well as innovation management. In this paper, these issues are analysed through the survey results and some conclusions are drawn. Several policy measures applicable in near future are suggested for improving the areas found in need of improvement