PME I J http://polipapers.upv.es/index.php/IJPME International Journal of Production Management and Engineering Received: 2021-12-03 Accepted: 2022-06-27 Sustainable and Agile Manufacturing Outsourcing Partner Selection: a literature review Mohammad Akhtar Galgotias University, Greater Noida, U.P., 203201, India. * mk71b@yahoo.com, mohammad.akhtar@galgotiasuniversity.edu.in Abstract: Outsourcing to third party to manage non-core activities helps the firm to focus on core activities. Manufacturing firms are outsourcing product development, manufacturing, logistics, customer care etc. to enhance production capacity and flexibility, and to reduce operational costs, which in turn can improve profitability and competitive advantage of the enterprise. Sustainability in operations and supply chain is gaining momentum due to increased global environmental concern, pressures from consumers and communities, and enforced regulations. Volatile and uncertain business environment necessitates the adoption of agility and flexibility to effectively manage manufacturing and supply chain. Globalisation has made the market very competitive and hence manufacturing firms are adopting manufacturing outsourcing to third parties. Selecting a sustainable and agile manufacturing outsourcing partner (MPS) is crucial as it will improve sustainability, efficiency, and effectiveness of the supply chain and competitive advantage to the firm. Detailed literature review on sustainable and agile manufacturing outsourcing partner selection has been carried out from EBSCO data base and Goggle scholar. Selection criteria used are classified into agile, operational, economic, environmental and social. The techniques use are mostly multi criteria decision making methods (MCDM) while few have adopted programming techniques. Discussion, implication and the scope of future work is also provided. Key words: Manufacturing outsourcing partner selection, Contract manufacturer selection, Outsourcing partner selection, Manufacturing outsourcing criteria, Multi criteria decision making. 1. Introduction Supply chain starts with procurement of raw materials, storage, inventory control, to transportation, and distribution of finished goods to customers to meet their demand. Outsourcing establishes a contract with an outside party to manage its non-core work in order to efficiency improvement, cost reduction, increase profits and to focus on core activities. Outsourcing has become an important business approach to manufacture products more efficiently by a contract manufacturer to gain competitive advantages. Logistics, finance, accounting, legal services, marketing and customer care are already outsourced to external service providers. New technologies, globalization and increasing demand from end-users provide extra scope for outsourcing activities (Yang et al., 2007). Ineffective outsourcing may lead to loss of core capabilities and competencies, and may cause to business failure (Wang and Yang, 2007). To attain effective manufacturing outsourcing, manufacturing outsourcing partner selection (MPS) or contract manufacturer selection (CMS) is essential. MPS affects upstream, downstream and reverse supply To cite this article: Akhtar, M. (2022). Sustainable and Agile Manufacturing Outsourcing Partner Selection: a literature review. International Journal of Production Management and Engineering, 10(2), 143-158. https://doi.org/10.4995/ijpme.2022.16807 https://doi.org/10.4995/ijpme.2022.16807 Int. J. Prod. Manag. Eng. (2022) 10(2), 143-158Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International 143 http://creativecommons.org/licenses/by-nc-nd/4.0/ chain operations, hence both qualitative and quantitative factors need to be examined carefully. With the increased global environmental awareness and pressure, firms’ decision-makers should consider environmental perspective in all commercial activities (Afred and Adam, 2009). Sustainable supply chain will improve environmental efficiency and social responsibility, meet stakeholder requirements and enhance firm competitiveness and profit (Gualandris et al., 2014). Environmental factors in product design, material purchasing, and supply network design have become important (Hervani et al., 2005; Sarkis, 2005). Manufacturing outsourcing partner selection (MPS) directly affects the sustainable initiatives implementation. For successful sustainable business practices, companies need to consider economic, environmental, and social sustainable criteria for outsourcing partners performances evaluation (Govindan et al., 2013). Companies should share their capabilities and resources with outsourcing partners in areas of green and technological innovations, environmental management systems, social responsibilities and sustainable initiatives (Luthra et al., 2017). Agile supply chain is needed to efficiently and effectively respond to volatile business environment (Christopher, 2000). To achieve necessary levels of SC agility, it is essential to align supply partners with firm operations to improve efficiency (Wu and Barnes, 2011). Therefore, a sustainable and agile (susgile) supply chain is desired to meet the sustainability obligation and business volatility. Manufacturing outsourcing partner selection process (MPS) involves several criteria, number of outsourcing partners and multiple decision makers (DM) and it is said to be a multi-criteria group decision making (MCDM) problem. A structured approach should be adopted to select the right criteria, and technique to assess and select the manufacturing outsourcing partner (MP) or contract manufacturer (CM). In the literature, many selection criteria and techniques including MCDM have been applied by various researchers for MPS. Research questions has been framed that should be addressed in the literature review. RQ1. What are the operational criteria used for manufacturing outsourcing partner selection? RQ2. What are the economic, environmental and social sustainable criteria used for manufacturing outsourcing partner selection? RQ3. What are the agile criteria used for manufacturing outsourcing partner selection? RQ4. What are the techniques used for the assessment and ranking of manufacturing outsourcing partners? The paper is organised in following sections. Section two presents the detailed review of the literature; section three provides the findings and discussion, and section four offers the conclusion and scope for future work. 2. Review of Literature To undertake literature review, guidelines provided by Denyer and Tranfield (2009) have been adopted, which help researchers to formulate a research question and define the boundaries of a literature review. The literature review is carried out by searching the word ‘manufacturing outsourcing partner selection’, ‘manufacturing outsourcing provider selection’, ‘contract manufacturer selection’, ‘manufacturing outsourcing’, ‘contract manufacturing’, ‘strategic outsourcing partner’, ‘strategic outsourcing provider’ ‘vendor selection’, ‘triple bottom line sustainability’, ‘agile criteria’, ‘sustainable criteria’, ‘economic criteria’, ‘environmental criteria’, and ‘social criteria’ in EBSCO database and Google scholar. Outsourcing is the process where an external company takes the responsibility of certain activities and processes through a contract with the company (Yang et al. 2007). Outsourcing reduces operating costs and improve competitiveness of a firm. Outsourcing manufacturing activities to MP or CM decreases operational cost, increases the flexibility of production capability and improves the profit. It is therefore, crucial for a company to select appropriate MP. Supply chain managers have incorporated sustainability in manufacturing outsourcing partnership which improved firm’s competitiveness (Govindan et al. 2013; Luthra et al. 2017). Suppliers and vendors selection affects supply chain operations and performances which is evident from the significant number of studies found in the literature (Malviya et al., 2018). Right supplier selection reduces purchasing costs, improves end- user’s satisfaction, and competitiveness in the market (Onut et al., 2009), while wrong supplier selection can negatively impact the operational and Int. J. Prod. Manag. Eng. (2022) 10(2), 143-158 Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Akhtar 144 http://creativecommons.org/licenses/by-nc-nd/4.0/ financial performance of the firm (Bhattacharya and Singh, 2019). Selection right supplier is an important part of sustainable supply chain (Sen et al., 2018) and key concern for business firms (Seuring, 2013; Grimm et al., 2014). It is challenging for many firms to adopt a dependable approach for supplier selection (Ortiz-Barrios et al., 2017; Sen et al., 2018) that can enhance cost savings, delivery, quality, flexibility, service level (Govindan et al., 2013), and innovation (Nair et al., 2015). Ebrahimipour et al. (2016) suggested product characteristics, finished products reliability and product life cycle to choose the right vendor and suppliers for manufacturing firms. Process of supplier selection is to select the right criteria and right technique (Büyüközkan and Göçer, 2019). Fan et al. (2020) studied battery outsourcing for electric vehicle manufacturers considering battery production cost, electric vehicle manufacturing and assembly cost, government subsidy. Helo et al. (2021) designed Cloud Ecosystem for cloud-based collaborative manufacturing portals for sheet metal manufacturing companies. Lahiri et al. (2022) carried out meta-analysis to examine the effect of industrial nature of activity (manufacturing vs. services), value chain activity (core vs. non-core), and provider’s location (domestic vs. international) in sourcing on firm performance and found that effect is stronger for non-core and international outsourcing equally for manufacturing and service outsourcing. 2.1. Criteria for Manufacturing Outsourcing Partner Evaluation It is crucial for decision-makers to identify effective evaluation criteria, as well as assess outsourcing partner’s feasibility and compatibility prior to outsourcing. A number of evaluation criteria for MPS have been used in the literature. Mummalaneni et al. (1996) adopted price, quality, on-time delivery, responsiveness, expertise, and supplier relationship. Ho et al. (2010) suggested price, quality and delivery. Liou et al. (2012) considered cost (flexibility in billing, cost saving), quality (on-time rate, customers’ satisfactions, knowledge skills), risk (management control loss, labor union, information security), and compatibility (information sharing, flexibility, relationship) criteria outsourcing provider selection in a Taiwanese airline. Garg and Sharma (2020) adopted economic factors (service delivery and access, firm performance and reputation, resources capacity, financial capacity, outsourcing benefits, technical ability, and communication), environmental factors (green certification and accreditation, emission and pollution minimization, green purchasing and designing, green manufacturing and marketing, waste minimization, green practices, green packaging, energy efficiency, cleaner technology, and reverse logistics), and social factors (working conditions, health and safety, employee rights and fair wages, women specific issues, employee and community equity, social welfare, community connection and support, ethical and transparent practices) for sustainable outsourcing partner selection in Indian electronics company. Chen and Hung (2010) used service criteria such as on-time delivery, process capacity, experience, response to changes, and reputation; financial criteria such as services cost, long-term viability, and finacial stability; quality criteria such as product quality, processes for quality control, and program for continuous improvement; compliance criteria such as goods manufacturing practices compliance, environmental health and safety, intellectual property infringement; and culture criteria such as lasting and mutually profitable relationships, interaction ability for MPS in pharmaceutical R&D. For sustainable supplier and vendor selection, Ulutas et al. (2016) used cost, supplier production capacity, financial position, order requirement, sectoral price compliance, percentage defective, percentage late delivered, volume flexibility, technological capability reputation, and communication issues. Luthra et al. (2017) adopted product price, quality, delivery & service of product, transportation cost, product profit, lead time, production capacity, flexibility, green manufacturing, waste management, green product design, green purchasing, green packing and labeling, technological and financial capability, green management, green research and innovation, pollution prevention, environment management systems, environmental costs, environmental competencies, employees interests and rights, occupational health and safety, stakeholders rights, and information disclosure. Fallahpour et al. (2017) considered cost (material cost, after-sales service cost, freight cost), delivery & service (on-time delivery, lead time, after- sales service, flexibility, complaint resolution time), quality (internal quality audit process, abnormal quality handling capability, rejection rate), flexibility (delivery time flexibility, ordering flexibility, discount flexibility) criteria. Song et al. (2017) adopted ten criteria; cost, quality, delivery, Int. J. Prod. Manag. Eng. (2022) 10(2), 143-158Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Sustainable and Agile Manufacturing Outsourcing Partner Selection: a literature review 145 http://creativecommons.org/licenses/by-nc-nd/4.0/ resource consumption, eco-design, recycling, environmental management system, occupational safety and health, rights and welfare of employees, and community training and development. Awasthi et al. (2018) adopted five sustainable criteria; economic, quality, environment, social, and global risk. Cheraghalipour and Farsad (2018) used three main criteria of economic (delivery, quality, loyalty, cost, service, financial situation, technology), environmental (product performance, environmental commitment, environmental pollution, greenhouse gas, environmental management), and social (working hours, worker safety and health, freedom of association and wages, social commitment, social management). Arabsheybani et al. (2018) used delivery, quality, green supply chain, suppliers of the supplier, environmental management system (EMS), worker safety and health, worker safety cost, worker dismissal, and employee interests & rights criteria. Sinha and Anand (2018) adopted criteria such as cost, delivery reliability, quality, technology capability, green product, financial situation, pollution control, environmental management system, green image, health & safety contractual, social responsibility management, local community and stakeholder influence. Vasiljević et al. (2018) considered price, delivery, quality, environmental and social criteria that help organizations in achieving long- term economic sustainability, ecological stability, and market position. Sen et al. (2018) proposed price, on-time delivery, quality, flexibility, service, production facility, financial capability, innovation, green design, green product, resource consumption, waste, recycling, EMS, work safety, stakeholders’ rights, and information disclosure. For agile contract manufacturer selection, Adali and Isik (2017) adopted product cost, on-time delivery, production capacity, equipment, material quality, geographic location and reliability criteria, Hu and Yu (2015) considered cost, delivery, quality, and flexibility. Supply chain agility studies have been conducted across industries; manufacturing (Blome et al., 2013; Um, 2017; Al-Shboul, 2017; Kim and Chai, 2017); auto components (Dubey et al., 2018); fashion and textiles (Ngai et al., 2011; Chan et al., 2017); electronics (Tse et al., 2016; Wu et al., 2017); telecommunications (Collin and Lorenzin, 2006), and oil and gas (Yusuf et al., 2014). In Moroccan manufacturing companies, Barhmi (2019) studied the supply chain agility and resilience effect on the supply chain performance. 2.2. Technique for Manufacturing Outsourcing Partner Selection Manufacturing outsourcing partner selection involves multiple inter-related criteria, alternatives and decision makers and hence complex process. In the literature, various techniques including MCDM have been applied for MPS by various scholars. Vendor selection for outsourcing in Taiwanese semiconductor company, Lin et al. (2010) applied Analytic network process (ANP) method. Parthiban et al. (2012) adopted fuzzy SWOT and DEA for vendor selection. Liou et al. (2012) adopted integrated DEMATEL, fuzzy preference programming and ANP method to select outsourcing provider in a Taiwanese airline. For outsourcing provider selection, Hsu et al. (2013) applied DANP and GRA method. Festel et al. (2014) proposed an action research-based selection of strategic outsourcing partner in a global pharmaceutical manufacturing company. Hu and Yu (2015) proposed an integrated voting method and the goal programming (GP) model for electronic contract manufacturer selection. For vendor selection in the steel industry, Kar (2015) adopted Delphi and fuzzy AHP method. Rezaeisaray et al. (2016) utilized DEMATEL-fuzzy ANP-DEA to select outsourcing supplier in pipe manufacturing company. Adali and Isik (2017) applied CRITIC and Multi-attribute utility theory (MAUT) methods for CMS. Momeni and Vandchali (2017) proposed a Data envelopment analysis (DEA) model using evidential reasoning (ER) algorithm for strategic outsourcing in an Iranian software company. Ji et al. (2018) proposed neutrosophic linguistic sets based MABAC–ELECTRE method for outsourcing provider selection. Büyüközkan and Göçer (2019) proposed pythagorean fuzzy AHP and COPRAS for digital supply chain partner selection. Song (2019) adopted AHP for selection of outsourcing partner in Korean pharmaceutical R&D. Fei et al. (2019) presented Dempster–Shafer evidence theory (DS theory) and VIKOR for supplier selection. Ghorabaee et al. (2017) applied interval type-2 fuzzy CRITIC– WASPAS for selection of third party logistics provider. Rostamzadeh et al. (2018) proposed FCRITIC and FTOPSIS method, while Abdel-Basset and Mohamed (2020) applied a plithogenic CRITIC and TOPSIS model for managing sustainable supply chain risk. Awasthi and Kannan (2016) proposed nominal group technique and fuzzy VIKOR for green supplier development program. Chen et al. (2019) designed a model based on capability index and manufacturing time performance index for outsourcing partner selection. Percin (2019) adopted Int. J. Prod. Manag. Eng. (2022) 10(2), 143-158 Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Akhtar 146 http://creativecommons.org/licenses/by-nc-nd/4.0/ FSWARA and fuzzy axiomatic design method for selecting outsourcing provider in Turkish chemical manufacturing company. Liaw et al. (2020) proposed DEMATEL-CRITIC method for criteria weight and classifiable TOPSIS to classify green manufacturing outsourcing providers in Taiwanese multinational machine tool manufacturing firm. For Malaysian manufacturing SMEs, Zulkiffli and Padlee (2021) used confirmatory factor analysis to study sustainable outsourcing impact on the competitive capabilities and business performance. Yazdani et al. (2021) assessed outsourcing risk using triangular fuzzy hesitant sets, Failure mode and effect analysis (FMEA) and Combined compromise solution (CoCoSo) in Iranian chemical company. Singh and Sarkar (2021) applied integrated AHP and VIKOR method for sustainable contract manufacturer selection in automotive industry. Akhtar et al. (2021) applied stochastic fuzzy TOPSIS to select sustainable vendor in the Indian petroleum refining sector. Haoues et al. (2021) presented genetic algorithm techniques under reliability maintenance constraint to minimize total cost for inhouse and outsourced manufacturing maintenance. Teerasoponpong and Sopadang (2022) applied genetic algorithm and artificial neural network (ANN) for sourcing and inventory management, which reduced raw materials purchasing cost, order interval and on-hand inventory cost in medium-sized food company. For sustainable supplier and vendor evaluation, Dobos and Vörösmarty (2014) utilized DEA with the common weights analysis (CWA) method; Bai and Sarkis (2014) adopted rough set theory based DEA; Zarbakhshnia and Jaghdani (2018) adopted two-stage DEA; Mohammed et al. (2018) proposed hybrid AHP and TOPSIS; Sivakumar et al. (2015) used AHP and Taguchi loss functions; Trapp and Sarkis (2016) applied Integer programming technique; Luthra et al. (2017) applied integrated AHP and VIKOR; and Cheraghalipour and Farsad (2018) used BWM, MILP, and Revised multi-choice goal programming. Garg and Sharma (2020) adopted integrated BWM-VIKOR method for selection of sustainable outsourcing partner in an Indian electronics company. For agile supplier and vendor selection, Hasan et al. (2008) adopted DEA and ANP methods; Luo et al. (2009) proposed a radial basis function based ANN; Alimardani et al. (2014) demonstrated hybrid DEMATEL, ANP and TOPSIS application; and Beikkhakhian et al. (2015) applied ISM for agile selection criteria and integrated TOPSIS-AHP method for vendor ranking. Lee et al. (2015) used FAHP and FTOPSIS for agile supplier selection and studied the impact of agility criterion and order allocation strategy on business performance. Matawale et al. (2016) presented fuzzy multi-level (FML) approach for selecting agile supplier and compared the result with FTOPSIS and FMOORA. Goker (2021) applied intuitionistic fuzzy cognitive map and COPRAS method for agile outsourcing provider selection in Turkish white goods industry. Fuzzy variant of MCDM methods have also been reported by many researchers in the literature. Chen and Hung (2010) adopted FAHP and FTOPSIS method for selecting outsourcing manufacturing partner for pharmaceutical R&D. Akhavan et al. (2015) applied fuzzy quantitative strategic planning matrix-based SWOT for strategic alliance planning; F-ARAS, F-COPRAS, F-TOPSIS, and F-MOORA for strategic outsourcing partner evaluation in an Iranian car manufacturer company. For supplier selection with triple bottom line sustainability, Wang et al. (2019) proposed fuzzy AHP and TOPSIS in Vietnamese garment industry. Dos Santos et al. (2019) adopted Shanon Entropy and FTOPSIS in the furniture industry. For sustainable supplier selection, Zhou et al. (2016) utilized Type-2 multi-objective DEA; Fallahpour et al. (2017) proposed FAHP and FTOPSIS; Paydar et al. (2017) and Arabsheybani et al. (2018) utilized integrated F-MOORA and failure mode and effects analysis (FMEA); Awasthi et al. (2018) proposed FAHP and FVIKOR; and Mohammed et al. (2018) adopted FAHP, FTOPSIS and multi-objective programming model. Rabbani et al. (2019) presented interval-valued fuzzy group decision model-based reference point systems with fuzzy possibilistic statistical concepts. 3. Findings and Discussion Based on the literature review, discussions on the findings are summarized under following headings. 3.1. Distribution of Articles Journal Wise Though large number of articles are published on supplier selection but few articles related to manufacturing outsourcing partner selection are available in the literature. The manufacturing outsourcing partner selection with sustainability consideration are rarest. The manufacturing outsourcing partner selection articles published in Int. J. Prod. Manag. Eng. (2022) 10(2), 143-158Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Sustainable and Agile Manufacturing Outsourcing Partner Selection: a literature review 147 http://creativecommons.org/licenses/by-nc-nd/4.0/ journals are listed Table 1. Most of the articles are published once in any journal. 3.2. Distribution of Articles Year wise The number of articles published year wise from 2010 to 2021 are 18 as shown in Figure 1. The highest number of articles published are 3 in years 2019 and 2020. Figure 1. Manufacturing Outsourcing Partner Selection Articles Publication Year Wise 3.3. Selection Criteria From the literature review, important criteria for manufacturing outsourcing partner selection are operational, agile, and economic, environmental and social sustainable criteria as displayed in Table 2. The operational criteria are process and production capacity, product quality, on-time delivery, response to customer needs, and Technological ability. The agile criteria are production capability & flexibility, service level, lead time minimisation, delivery flexibility, sourcing flexibility, multi-skilled & flexible workforce, collaboration with partners for innovation & capacity enhancement, and customer driven innovation. The economic criteria are product price, resource consumption, and financial stability. The environmental sustainability criteria are green product, green manufacturing process, green R&D, and environmental management system. The social sustainability criteria are worker’s wages and welfare, worker’s occupational health & safety, and social welfare & community development. Most of the papers cover operational, economic and agile criteria. Latest trend is to include environmental and social sustainability criteria in selection process. 3.4. Evaluation Methods Techniques used for outsourcing partner selection in the literature are shown in Table 3 and 4. For criteria weight determination AHP, ANP, CRITIC, SWARA, BWM, MABAC, Cognitive map and fuzzy variant, and voting method have been used. For outsourcing partner evaluation and selection, MCDM methods such as AHP, TOPSIS, ANP, MAUT, ELECTRE, VIKOR, COPRAS, GRA, and fuzzy variant have been adopted. Other methods such as goal programming (Hu and Table 1. Manufacturing Outsourcing Partner Selection Articles publication in Journals. S. No. Journal Name Year No. of Publication 1 International Journal of Production Research 2010 1 2 Expert System with Applications 2010 1 3 Expert System with Applications 2013 1 4 Journal of Business Chemistry 2014 1 5 Technological and Economic Development of Economy 2015 1 6 Resources Policy 2015 1 7 Omega 2016 1 8 Journal of Modelling in Management, 2016 1 9 European Journal of Multidisciplinary Studies 2017 1 10 Computers & Industrial Engineering 2018 1 11 Journal of Manufacturing Technology Management 2019 1 12 International Journal of Reliability, Quality and Safety Engineering 2019 1 13 Journal of Pharmaceutical Innovation 2019 1 14 International Transactions in Operational Research 2020 1 15 Symmetry 2020 1 16 Environment, Development and Sustainability 2020 1 17 International Journal of Industrial and System Engineering 2021 1 18 Soft Computing 2021 1 Int. J. Prod. Manag. Eng. (2022) 10(2), 143-158 Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Akhtar 148 http://creativecommons.org/licenses/by-nc-nd/4.0/ (Table 2 continues in the next page) Table 2. Important Criteria for Sustainable and Agile Manufacturing Outsourcing Partner Evaluation from the literature. Criteria type Criteria Benefit/ Non- Benefit Description References O pe ra tio na l p er fo rm an ce c ri te ri a Process and production capacity Benefit Production and process capacity Chen and Hung (2010), Ulutas et al. (2016), Luthra et al. (2017), Adali and Isik (2017) Product Quality Benefit Product quality and reliability Liou et al. (2012), Chen and Hung (2010), Mummalaneni et al. (1996), Ho et al. (2010), Ulutas et al. (2016), Awasthi et al. (2018), Cheraghalipour and Farsad (2018), Gören (2018), Sinha and Anand (2018), Arabsheybani et al. (2018), Song et al. (2017), Luthra et al. (2017), Fallahpour et al. (2017), Hu and Yu (2015), Adali and Isik (2017). On-time delivery Benefit On time delivery to customers Garg and Sharma (2020), Chen and Hung (2010), Mummalaneni et al. (1996), Ulutas et al. (2016), Luthra et al. (2017), Fallahpour et al. (2017 Fallahpour et al. (2017), Song et al. (2017), Cheraghalipour and Farsad (2018), Arabsheybani et al. (2018), Sinha and Anand (2018), Vasiljević et al. (2018), Adali and Isik (2017), Hu and Yu (2015) Response to customer needs Benefit Responsiveness and order fulfilment Mummalaneni et al. (1996), Chen and Hung (2010). Technological ability Benefit Technology and technical ability Garg and Sharma (2020), Ulutas et al. (2016), Luthra et al. (2017), Cheraghalipour and Farsad (2018), Sinha and Anand (2018) A gi le P er fo rm an ce c ri te ri a Production flexibility and capability Benefit Production ability for variety of products to meet customer’s demand. Chen and Hung (2010), Ulutas et al. (2016), Awasthi et al. (2018), Gören (2018), Luthra et al. (2017), Fallahpour et al. (2017), Hu and Yu (2015), Adali and Isik (2017). Service level Benefit Providing service without stockout situation Garg and Sharma (2018), Chen and Hung (2010), Bhutta and Huq (2002), Ulutas et al. (2016), Awasthi et al. (2018), Cheraghalipour and Farsad (2018), Fallahpour et al. (2017). Lead time Benefit Lead time and variability minimisation Liou et al. (2012), Gören (2018), Luthra et al. (2017), Fallahpour et al. (2017). Delivery flexibility Benefit The ability to exploit various dimensions of delivery Garg and Sharma (2018), Chen and Hung (2010), Mummalaneni et al. (1996), Ho et al. (2010), Ulutas et al. (2016), Awasthi et al. (2018), Cheraghalipour and Farsad (2018), Sinha and Anand (2018), Arabsheybani et al. (2018), Song et al. (2017), Luthra et al. (2017), Fallahpour et al. (2017), Hu and Yu (2015), Adali and Isik (2017). Sourcing flexibility Benefit The availability of range of sourcing options Garg and Sharma (2018), Chen and Hung (2010), Luthra et al. (2017), Hu and Yu (2015). Multi-skilled and flexible workforce Benefit Multi-skilled workforce will provide flexibility in scheduling workers Liou et al. (2012), Chen and Hung (2010), Mummalaneni et al. (1996), Ulutas et al. (2016). Collaboration with partners Benefit Collaboration with suppliers will enhance innovation and capability Garg and Sharma (2018), Liou et al. (2012), Chen and Hung (2010), Mummalaneni et al. (1996), Ulutas et al. (2016), Gören (2018), Sinha and Anand (2018), Cheraghalipour and Farsad (2018), Arabsheybani et al. (2018), Luthra et al. (2017), Awasthi et al. (2018). Customer driven innovation Benefit Customer need based innovation Liou et al. (2012), Mummalaneni et al. (1996), Sinha and Anand (2018). Int. J. Prod. Manag. Eng. (2022) 10(2), 143-158Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Sustainable and Agile Manufacturing Outsourcing Partner Selection: a literature review 149 http://creativecommons.org/licenses/by-nc-nd/4.0/ Yu, 2016) and genetic algorithm (Haoues et al., 2021) have also been used in few cases. DEMATEL (Hsu et al., 2013; Rezaeisaray et al., 2016; Wu et al., 2017; Liaw et al., 2020) and ISM (Beikkhakhian et al., 2015) are used to show interrelationship among criteria. There is no clear trend on usage of any particular method. However, integrated fuzzy models have been used by majority researchers and among them fuzzy AHP and fuzzy TOPSIS are two most frequently used methods: Chen and Hund (2010), Liaw et al. (2020), Beikkhakhian et al. (2015), Lee et al. (2015), Singh and Sarkar (2021). There is no justification given for using a particular MCDM method in any of the papers. Fuzzy theory and its variant (Intuitionistic fuzzy sets, Neutrosophic linguistic sets), and Grey theory have been applied to deal with imprecision and ambiguity in decision makers’ judgments. Most of the papers have used integrated models. It has been observed that AHP or fuzzy AHP is highly used for evaluation while DEMATEL is used to find the inter- relationship among the criteria. Criteria type Criteria Benefit/ Non- Benefit Description References E co no m ic p er fo rm an ce c ri te ri a Product Price Non- benefit Product price Garg and Sharma (2018), Liou et al. (2012), Mummalaneni et al. (1996), Chen and Hung (2010), Ho et al. (2010), Ulutas et al. (2016), Gören (2018), Luthra et al. (2017), Fallahpour et al. (2017), Song et al. (2017), Arabsheybani et al. (2018), Hu and Yu (2015), Cheraghalipour and Farsad (2018), Adali and Isik (2017), Awasthi et al. (2018), Sinha and Anand (2018). Resource consumption Non- benefit Resource consumption in production process Luthra et al. (2017), Song et al. (2017). Financial stability Benefit Financial position and stability Garg and Sharma (2020), Chen and Hung (2010), Ulutas et al. (2016), Sinha and Anand (2018), Cheraghalipour and Farsad (2018). E nv ir on m en ta l P er fo rm an ce c ri te ri a Green Product Benefit Product requiring less physical resources and low environmental impacts Garg and Sharma (2018), Awasthi et al. (2018), Gören (2018), Sinha and Anand (2018), Song et al. (2017), Arabsheybani et al. (2018), Luthra et al. (2017), Cheraghalipour and Farsad (2018). Green Manufacturing Process Benefit Manufacturing process that minimise waste, pollution, and energy use. Garg and Sharma (2018), Awasthi et al. (2018), Sinha and Anand (2018), Gören (2018), Luthra et al. (2017), Arabsheybani et al. (2018), Song et al. (2017), Cheraghalipour and Farsad (2018). Green R & D Benefit Environmental sustainability in research and development Garg and Sharma (2018), Awasthi et al. (2018), Luthra et al. (2017). Sinha and Anand (2018), Cheraghalipour and Farsad (2018), Arabsheybani et al. (2018). Environmental Management System (EMS) Benefit Environmental planning, implementation, monitoring and controlling Garg and Sharma (2018), Chen and Hung (2010), Gören (2018), Sinha and Anand (2018), Arabsheybani et al. (2018), Song et al. (2017), Luthra et al. (2017), Awasthi et al. (2018), Cheraghalipour and Farsad (2018). So ci al P er fo rm an ce c ri te ri a Worker’s Wages and Welfare Benefit Workers’ wages and welfare at supplier’s firm Garg and Sharma (2018), Liou et al. (2012), Arabsheybani et al. (2018), Luthra et al. (2017), Song et al. (2017), Cheraghalipour and Farsad (2018). Worker’s Occupational health and safety Benefit Workers’ occupational health and safety at suppliers’ firm Garg and Sharma (2018), Luthra et al. (2017). Cheraghalipour and Farsad (2018), Gören (2018), Sinha and Anand (2018), Arabsheybani et al. (2018), Song et al. (2017). Social welfare and community development Benefit Social welfare and community development Garg and Sharma (2020), Luthra et al. (2017), Song et al. (2017), Cheraghalipour and Farsad (2018), Sinha and Anand (2018), Vasiljević et al. (2018) (Table 2 continues from the previous page) Int. J. Prod. Manag. Eng. (2022) 10(2), 143-158 Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Akhtar 150 http://creativecommons.org/licenses/by-nc-nd/4.0/ Based on literature review study, a proposed framework of manufacturing outsourcing partner selection based on five dimensions such as Operational, agile, economic, environmental and social sustainability is shown in Figure 2. The proposed model takes into consideration operational/ technical, agile as well as triple bottom line sustainability aspects. Table 3. Techniques for Sustainable and Agile Outsourcing Partner Selection in the literature. Author (s) Methodology and Techniques Adopted Issues Addressed Chen and Hung (2010) Fuzzy AHP + fuzzy TOPSIS Selection of outsourcing manufacturing partners Lin et al. (2010) ANP Outsourcing Vendor selection in Taiwanese semiconductor company. Hsu et al. (2013) DEMATEL + ANP + GRA Outsourcing provider selection Festel et al. (2014) Action research Selection of strategic outsourcing partner in a global pharmaceutical manufacturing company Akhavan et al. (2015) Fuzzy quantitative strategic planning matrix (FQSPM) SWOT and F-ARAS, F-COPRAS, F-TOPSIS, F-MOORA. Strategic outsourcing partners evaluation in car manufacturer company in Iran Beikkhakhian et al. (2015) ISM + fuzzy AHP + Fuzzy TOPSIS ISM technique for agile supplier selection criteria evaluation and Fuzzy AHP and TOPSIS for suppliers ranking. Lee et al. (2015) Fuzzy AHP + fuzzy TOPSIS Selection of agile supplier, assessing business impacts and comparison of business cost under skewed order and even order strategy. Hu and Yu (2016) Voting method +Goal programming (GP) Electronic contract manufacturer selection Matawale et al. (2016) Fuzzy multi-level (FML) MCDM approach. Supplier selection in agile supply chain Rezaeisaray et al. (2016) DEMATEL + DEA + fuzzy ANP Outsourcing supplier selection in pipe and fittings manufacturing company Adali and Isik (2017) CRITIC + MAUT Selection of Agile contract manufacturer Wu et al. (2017) Delphi method + ANP + DEMATEL Supply chain agility under uncertainty to achieve competitive advantage Ji et al. (2018) Neutrosophic linguistic sets based MABAC + ELECTRE method Outsourcing provider selection Dubey et al. (2018) Research based view (RBA) Agility, adaptability, and alignment in supply chain create sustainable competitive advantage Percin (2019) Fuzzy SWARA + fuzzy axiomatic design method Selection of Outsourcing provider in Turkish chemical manufacturing company Chen et al. (2019) Capability index and manufacturing time performance index-based model Outsourcing partner selection Liaw et al. (2020) DEMATEL + CRITIC + classifiable TOPSIS Evaluate and classify green manufacturing outsourcing providers in Taiwanese multinational machine tool manufacturing company Garg and Sharma (2020) BWM +VIKOR Sustainable outsourcing partner selection in electronic firm Haoues et al. (2021) Genetic algorithm (GA) techniques To minimize total cost for inhouse and outsourced manufacturing maintenance. Goker (2021) Intuitionistic fuzzy Cognitive Map + COPRAS method Selection of agile outsourcing provider selection in Turkish white goods industry. Singh and Sarkar (2021) Integrated AHP + VIKOR Sustainable Contract manufacturer selection in Automotive industry. Int. J. Prod. Manag. Eng. (2022) 10(2), 143-158Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Sustainable and Agile Manufacturing Outsourcing Partner Selection: a literature review 151 http://creativecommons.org/licenses/by-nc-nd/4.0/ L in e t a l. (2 01 0) x x C he n an d H un g (2 01 0) x x x L io u et a l. (2 01 2) x x x x H su e t a l. (2 01 3) x x x Fe st el e t a l. (2 01 4) x Si va ku m ar e t a l. (2 01 5) x x H u an d Y u (2 01 5) x x A kh av an e t a l. (2 01 5) x x x x x R ez ae is ar ay e t a l. (2 01 6) x x x x M om en i a nd V an dc ha li (2 01 7) x x A da li an d Is ik (2 01 7) Ji e t a l. (2 01 8) x x x So ng (2 01 9) x B üy ük öz ka n an d G öç er (2 01 9) x x x C he n et a l. (2 01 9) x Pe rc in (2 01 9) x x x L ia w e t a l. (2 02 0) x x x G ar g an d Sh ar m a (2 02 0) x x Y az da ni e t a l. (2 02 1) x x x A kh ta r e t a l. (2 02 1) x x G ok er (2 02 1) x x x M et ho ds /T ec hn iq ue s AHP TOPSIS ANP COPRAS VIKOR GRA ARAS MOORA DEA ELECTRE CoCoSo BWM CRITIC SWARA MABAC Cognitive map DEMATEL FMEA Taguchi Loss function Goal Programming Fuzzy Neutrosophic linguistic sets Pythagorean fuzzy sets Fuzzy preference programming Fuzzy axiomatic design Triangular fuzzy hesitant sets Stochastic Fuzzy Intuitionistic fuzzy Action Research Voting method Evidential reasoning Capability index and manufacturing time performance index CFA ANN & GA Table 4. Techniques Used for Outsourcing Partners Selection in the Literature. Int. J. Prod. Manag. Eng. (2022) 10(2), 143-158 Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Akhtar 152 http://creativecommons.org/licenses/by-nc-nd/4.0/ 4. Conclusion and Scope for Future Work The selection of a suitable manufacturing outsourcing partner is strategic decision that is complex and uncertain due to involvement of multiple qualitative and quantitative criteria, alternatives and decision makers. It also involves imprecision and ambiguity in ratings by a group of decision makers. In this paper, an attempt has been made to review the literature on manufacturing outsourcing decisions from 2010-2021. Various criteria have been used but there is increasing trend to use agile as well as environmental sustainability criteria. Majority have used integrated fuzzy MCDM method, which shows that importance of integrated model with fuzzy logic. However, there is no trend on usage of any particular MCDM method. The proposed framework integrates the crucial dimensions of agility and triple bottom line sustainability in manufacturing outsourcing partner evaluation that would contribute to firm’s agility, economics, sustainability and competitiveness. The model also covers the impreciseness in decision makers rating by using fuzzy logic. The criteria listed in Table 2 may be used in the proposed framework for future studies for MPS. Few criteria may be added or substituted depending upon industry and firms requirements. Future research may use fuzzy CRITIC or fuzzy SWARA for criteria weight and fuzzy TOPSIS or fuzzy VIKOR method for alternative selection. To understand the causal relationship among criteria, fuzzy DEMATEL or fuzzy DANP method are good suggestion. Future study should apply a suitable technique, compare the result with other techniques and also carry out sensitivity analysis to improve the accuracy and robustness of the framework. This study will contribute to better understanding of manufacturing outsourcing problem and scope for future studies. The study is also helpful to managers to understand different dimensions of assessment that will improve firm’s agility, sustainability and competitiveness. This study may not be exhaustive. The future studies may cover more databases and latest papers to get a broader picture of manufacturing outsourcing provider evaluation and selection. References Abdel-Basset, M., & Mohamed, R. (2020). A novel plithogenic TOPSIS-CRITIC model for sustainable supply chain risk management. Journal of Cleaner Production, 247, 119586. https://doi.org/10.1016/j.jclepro.2019.119586 Adalı, E.A., & Işık, A.T. (2017). CRITIC and MAUT methods for the contract manufacturer selection problem. European Journal of Multidisciplinary Studies, 2(5), 93-101. https://doi.org/10.26417/ejms.v5i1.p93-101 Figure 2. Proposed Framework of Manufacturing Outsourcing Partner Selection. Manufacturing Outsourcing Partner Selection Agile Criteria Social Criteria Operational/Technical Criteria Environmental Criteria Economic Criteria Integrated Fuzzy Multi Criteria Decision Making Model Int. J. Prod. Manag. Eng. (2022) 10(2), 143-158Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Sustainable and Agile Manufacturing Outsourcing Partner Selection: a literature review 153 https://doi.org/10.1016/j.jclepro.2019.119586 https://doi.org/10.26417/ejms.v5i1.p93-101 http://creativecommons.org/licenses/by-nc-nd/4.0/ Akhavan, P., Barak, S., Maghsoudlou, H., & Antuchevičienė, J. (2015). FQSPM-SWOT for strategic alliance planning and partner selection; case study in a holding car manufacturer company. Technological and Economic Development of Economy, 21(2), 165-185. https://doi.org/10.3846/20294913.2014.965240 Akhtar, M., & Ahmad, M.T. (2021). A stochastic fuzzy multi-criteria group decision-making for sustainable vendor selection in Indian petroleum refining sector. Benchmarking: An International Journal, 29(3), 963-996. https://doi. org/10.1108/BIJ-09-2020-0500 Alfred, A.M., & Adam, R.F. (2009). Green management matters regardless. Academy of Management Perspectives, 23(3), 17-26. https://doi.org/10.5465/amp.2009.43479261 Alimardani, M., Rabbani, M., & Rafiei, H. (2014). A novel hybrid model based on DEMATEL, ANP and TOPSIS for supplier selection in agile supply chains. International Journal of Services and Operations Management, 18(2), 179-211. https://doi.org/10.1504/IJSOM.2014.062000 Al-Shboul, M.D.A. (2017). Infrastructure framework and manufacturing supply chain agility: the role of delivery dependability and time to market. Supply Chain Management: An International Journal, 22(2), 172-185. https://doi. org/10.1108/SCM-09-2016-0335 Arabsheybani, A., Paydar, M.M., & Safaei, A.S. (2018). An integrated fuzzy MOORA method and FMEA technique for sustainable supplier selection considering quantity discounts and supplier's risk. Journal of Cleaner Production, 190, 577-591. https://doi.org/10.1016/j.jclepro.2018.04.167 Awasthi, A., & Kannan, G. (2016). Green supplier development program selection using NGT and VIKOR under fuzzy environment.Computers & Industrial Engineering, 91, 100-108. https://doi.org/10.1016/j.cie.2015.11.011 Awasthi, A., Govindan, K., & Gold, S. (2018). Multitier sustainable global supplier selection using a fuzzy AHP- VIKOR based approach, International Journal of Production Economics, 195, 106-117. https://doi.org/10.1016/j. ijpe.2017.10.013 Bai, C.A., & Sarkis, J. (2014). Determining and applying sustainable supplier key performance indicators. Supply Chain Management: An International Journal, 19(3), 275-291. https://doi.org/10.1108/SCM-12-2013-0441 Bhattacharya, A., & Singh, P.J. (2019). Antecedents of agency problems in service outsourcing. International Journal of Production Research, 57(13), 4194-4210. https://doi.org/10.1080/00207543.2018.1506179 Barhmi, A. (2019). Agility and Responsiveness Capabilities: Impact on Supply Chain Performance, European Scientific Journal, 15(7), 212-224. https://doi.org/10.19044/esj.2019.v15n7p212 Beikkhakhian, Y., Javanmardi, M., Karbasian, M., & Khayambashi, B. (2015). The application of ISM model in evaluating agile suppliers' selection criteria and ranking suppliers using fuzzy TOPSIS-AHP methods. Expert systems with Applications, 42(15-16), 6224-6236. https://doi.org/10.1016/j.eswa.2015.02.035 Blome, C., Schoenherr, T., & Rexhausen, D. (2013). Antecedents and enablers of supply chain agility and its effect on performance: a dynamic capabilities perspective, International Journal of Production Research, 51(4), 1295-1318. https://doi.org/10.1080/00207543.2012.728011 Büyüközkan G., & Göçer, F. (2019). A Novel Approach Integrating AHP and COPRAS Under Pythagorean Fuzzy Sets for Digital Supply Chain Partner Selection. IEEE Transactions on Engineering Management, 68(5), 1486-1503. https:// doi.org/10.1109/TEM.2019.2907673 Chan, A.T., Ngai, E.W., & Moon, K.K. (2017). The effects of strategic and manufacturing flexibilities and supply chain agility on firm performance in the fashion industry, European Journal of Operational Research, 259(2), 486-499. https://doi.org/10.1016/j.ejor.2016.11.006 Chen, K.S., Chang, T.C., & Lin, Y.T. (2019). Developing an outsourcing partner selection model for process with two-sided specification using capability index and manufacturing time performance index. International Journal of Reliability, Quality and Safety Engineering, 26(3), 1950015. https://doi.org/10.1142/S0218539319500153 Chen, L.H., & Hung, C.C. (2010). An integrated fuzzy approach for the selection of outsourcing manufacturing partners in pharmaceutical R&D, International Journal of Production Research, 48(24), 7483-7506. https://doi. org/10.1080/00207540903365308 Cheraghalipour, A., & Farsad, S. (2018). A bi-objective sustainable supplier selection and order allocation considering quantity discounts under disruption risks: a case study in plastic industry, Computers and Industrial Engineering, 118, 237-250. https://doi.org/10.1016/j.cie.2018.02.041 Collin, J., & Lorenzin, D. (2006). Plan for supply chain agility at Nokia: lessons from the mobile infrastructure industry, International Journal of Physical Distribution and Logistics Management, 36(6), 418-430. https://doi. org/10.1108/09600030610677375 Christopher, M. (2000). The agile supply chain competing in volatile markets, Industrial Marketing Management, 29(1), 37-44. https://doi.org/10.1016/S0019-8501(99)00110-8 Int. J. Prod. Manag. Eng. (2022) 10(2), 143-158 Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Akhtar 154 https://doi.org/10.1108/BIJ-09-2020-0500 https://doi.org/10.1108/BIJ-09-2020-0500 https://doi.org/10.5465/amp.2009.43479261 https://doi.org/10.1504/IJSOM.2014.062000 https://doi.org/10.1108/SCM-09-2016-0335 https://doi.org/10.1108/SCM-09-2016-0335 https://doi.org/10.1016/j.jclepro.2018.04.167 https://doi.org/10.1016/j.cie.2015.11.011 https://doi.org/10.1016/j.ijpe.2017.10.013 https://doi.org/10.1016/j.ijpe.2017.10.013 https://doi.org/10.1108/SCM-12-2013-0441 https://doi.org/10.1080/00207543.2018.1506179 https://doi.org/10.19044/esj.2019.v15n7p212 https://doi.org/10.1016/j.eswa.2015.02.035 https://doi.org/10.1080/00207543.2012.728011 https://doi.org/10.1109/TEM.2019.2907673 https://doi.org/10.1109/TEM.2019.2907673 https://doi.org/10.1016/j.ejor.2016.11.006 https://doi.org/10.1142/S0218539319500153 https://doi.org/10.1080/00207540903365308 https://doi.org/10.1080/00207540903365308 https://doi.org/10.1016/j.cie.2018.02.041 https://doi.org/10.1108/09600030610677375 https://doi.org/10.1108/09600030610677375 https://doi.org/10.1016/S0019-8501(99)00110-8 http://creativecommons.org/licenses/by-nc-nd/4.0/ Denyer, D., & Tranfield, D. (2009). Producing a systematic review, in Buchanan, D and Bryman, A. (Eds.), The Sage Handbook of Organizational Research Methods, Sage Publications, London, 671-689. Dos Santos, B.M., Godoy, L.P., & Campos, L.M. (2019). Performance evaluation of green suppliers using entropy- TOPSIS-F. Journal of cleaner production, 207, 498-509. https://doi.org/10.1016/j.jclepro.2018.09.235 Dubey, R., Altay, N., Gunasekaran, A., Blome, C., Papadopoulos, T., & Childe, S.J. (2018). Supply chain agility, adaptability and alignment: empirical evidence from the Indian auto components industry, International Journal of Operations and Production Management, 38(1), 129-148. https://doi.org/10.1108/IJOPM-04-2016-0173 Dobos, I., Vörösmarty, G. (2014). Green supplier selection and evaluation using DEA-type composite indicators. International Journal of Production Economics, 157, 273-278. https://doi.org/10.1016/j.ijpe.2014.09.026 Ebrahimipour, V., Shoja, B.M., & Li, S. (2016). Supplier selection considering product structure and product life cycle cost, International Journal of Quality & Reliability Management, 33(5), 654-675. https://doi.org/10.1108/ IJQRM-05-2015-0069 Fallahpour, A., Udoncy Olugu, E., Nurmaya Musa, S., Yew Wong, K., & Noori, S. (2017). A decision support model for sustainable supplier selection in sustainable supply chain management, Computers and Industrial Engineering, 105, 391-410. https://doi.org/10.1016/j.cie.2017.01.005 Fan, Z.P., Chen, Z., & Zhao, X. (2020). Battery outsourcing decision and product choice strategy of an electric vehicle manufacturer. International Transactions in Operational Research, 29(3), 1943-1969. https://doi.org/10.1111/itor.12814 Fei, L., Deng, Y. & Hu, Y. (2019). DS-VIKOR: A New Multi-Criteria Decision-Making Method for Supplier Selection, International Journal of Fuzzy Systems, 21(1), 157-175. https://doi.org/10.1007/s40815-018-0543-y Festel, G., De Nardo, M., & Simmen, T. (2014). Outsourcing of Pharmaceutical Manufacturing-A Strategic Partner Selection Process. Journal of Business Chemistry, 11(3), 117-132. Garg, C.P., Sharma, A. (2020). Sustainable outsourcing partner selection and evaluation using an integrated BWM- VIKOR framework. Environment, Development and Sustainability, 22(2), 1529-1557. https://doi.org/10.1007/ s10668-018-0261-5 Ghorabaee, M.K., Amiri, M., Zavadskas, E.K., & Antuchevičienė, J. (2017). Assessment of third-party logistics providers using a CRITIC-WASPAS approach with interval type-2 fuzzy sets, Transport, 32(1), 66-78. https://doi.org/10.3846/ 16484142.2017.1282381 Goker, N. (2021). A novel integrated intuitionistic fuzzy decision aid for agile outsourcing provider selection: a COVID-19 pandemic-based scenario analysis. Soft Computing, 25(24), 13723-13740. https://doi.org/10.1007/s00500-021-06037-0 Gören, H.G. (2018). A decision framework for sustainable supplier selection and order allocation with lost sales, Journal of Cleaner Production, 183, 1156-1169. https://doi.org/10.1016/j.jclepro.2018.02.211 Govindan, K., Khodaverdi, R., & Jafarian, A. (2013). A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach. Journal of Cleaner Production, 47, 345-354. https://doi.org/10.1016/j.jclepro.2012.04.014 Grimm, J.H., Hofstetter, J.S., & Sarkis, J. (2014). Critical factors for sub-supplier management: A sustainable food supply chains perspective. International Journal of Production Economics, 152, 159-173. https://doi.org/10.1016/j. ijpe.2013.12.011 Gualandris, J., Golini, R., & Kalchschmidt, M. (2014). Do supply management and global sourcing matter for firm sustainability performance? Supply Chain Management: An International Journal, 19(3), 258-274. https://doi. org/10.1108/SCM-11-2013-0430 Haoues, M., Dahane, M., & Mouss, K.N. (2021). Capacity planning with outsourcing opportunities under reliability and maintenance constraints, International Journal of Industrial and System Engineering, 37(3), 382-409. https://doi. org/10.1504/IJISE.2021.113470 Hasan, M.A., Shankar, R., & Sarkis, J. (2008). Supplier selection in an agile manufacturing environment using Data Envelopment Analysis and Analytical Network Process, International Journal Logistics Systems and Management, 4 (5), 523-550. https://doi.org/10.1504/IJLSM.2008.017599 Helo, P., Hao, Y., Toshev, R., & Boldosova, V. (2021). Cloud manufacturing ecosystem analysis and design, Robotics and Computer-Integrated Manufacturing, 67, 102050. https://doi.org/10.1016/j.rcim.2020.102050 Hervani, A., Helms, M., Sarkis, J. (2005). Performance measurement for green supply chain management. Benchmarking: International Journal, 12(4), 330-353. https://doi.org/10.1108/14635770510609015 Ho, W., Xu, X., & De, P.K. (2010). Multi criteria decision making approaches for supplier evaluation and selection: a literature review, European Journal of Operational Research, 202(1), 16-24. https://doi.org/10.1016/j.ejor.2009.05.009 Hsu, C.C., James, J.H., & Chuang, Y.C. (2013). Integrating DANP and modified grey relation theory for the selection of an outsourcing provider. Expert System with Applications, 40(6), 2297-2304. https://doi.org/10.1016/j.eswa.2012.10.040 Int. J. Prod. Manag. Eng. (2022) 10(2), 143-158Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Sustainable and Agile Manufacturing Outsourcing Partner Selection: a literature review 155 https://doi.org/10.1016/j.jclepro.2018.09.235 https://doi.org/10.1108/IJOPM-04-2016-0173 https://doi.org/10.1016/j.ijpe.2014.09.026 https://doi.org/10.1108/IJQRM-05-2015-0069 https://doi.org/10.1108/IJQRM-05-2015-0069 https://doi.org/10.1016/j.cie.2017.01.005 https://doi.org/10.1111/itor.12814 https://doi.org/10.1007/s40815-018-0543-y https://doi.org/10.1007/s10668-018-0261-5 https://doi.org/10.1007/s10668-018-0261-5 https://doi.org/10.3846/16484142.2017.1282381 https://doi.org/10.3846/16484142.2017.1282381 https://doi.org/10.1007/s00500-021-06037-0 https://doi.org/10.1016/j.jclepro.2018.02.211 https://doi.org/10.1016/j.jclepro.2012.04.014 https://doi.org/10.1016/j.ijpe.2013.12.011 https://doi.org/10.1016/j.ijpe.2013.12.011 https://doi.org/10.1108/SCM-11-2013-0430 https://doi.org/10.1108/SCM-11-2013-0430 https://doi.org/10.1504/IJISE.2021.113470 https://doi.org/10.1504/IJISE.2021.113470 https://doi.org/10.1504/IJLSM.2008.017599 https://doi.org/10.1016/j.rcim.2020.102050 https://doi.org/10.1108/14635770510609015 https://doi.org/10.1016/j.ejor.2009.05.009 https://doi.org/10.1016/j.eswa.2012.10.040 http://creativecommons.org/licenses/by-nc-nd/4.0/ Hu, K-J., & Yu, V.F. (2015). An integrated approach for the electronic contract manufacturer selection problem. Omega, 62, 68-81. https://doi.org/10.1016/j.omega.2015.08.010 Ji, P., Zhang, H.Y., & Wang, J.Q. (2018). Selecting an outsourcing provider based on the combined MABAC-ELECTRE method using single-valued neutrosophic linguistic sets. Computers & Industrial Engineering, 120, 429-441. https://doi.org/10.1016/j.cie.2018.05.012 Kar, A.K. (2015). Reinvestigating vendor selection criteria in the iron and steel industry. International Journal of Procurement Management, 8(5), 570-586. https://doi.org/10.1504/IJPM.2015.070902 Kim, M., & Chai, S. (2017). The impact of supplier innovativeness, information sharing and strategic sourcing on improving supply chain agility: global supply chain perspective, International Journal of Production Economics, 187, 42-52. https://doi.org/10.1016/j.ijpe.2017.02.007 Lahiri, S., Karna, A., Kalubandi, S.C., & Edacherian, S. (2022). Performance implications of outsourcing: A meta-analysis, Journal of Business Research, 139, 1303-1316. https://doi.org/10.1016/j.jbusres.2021.10.061 Lee, J., Cho, H., & Kim, Y.S. (2015). Assessing business impacts of agility criterion and order allocation strategy in multi-criteria supplier selection. Expert Systems with Applications, 42(3), 1136-1148. https://doi.org/10.1016/j. eswa.2014.08.041 Liaw, C.F., Hsu, W.C. J., & Lo, H.W. (2020). A Hybrid MCDM Model to Evaluate and Classify Outsourcing Providers in Manufacturing. Symmetry, 12(12), 1962. https://doi.org/10.3390/sym12121962 Lin, Y.T., Lin, C.L., Yu, H.C. & Tzeng, G.H. (2010). A novel hybrid MCDM approach for outsourcing vendor selection: a case study for a semiconductor company in Taiwan. Expert Systems with Applications, 37(7), 4796-4804. https://doi. org/10.1016/j.eswa.2009.12.036 Liou, J.J.H. (2012). Developing an integrated model for the selection of strategic alliance partners in the airline industry, Knowledge-Based Systems, 28, 59-67. https://doi.org/10.1016/j.knosys.2011.11.019 Luo, X., Wu, C., Rosenberg, D., & Barnes, D. (2009). Supplier selection in agile supply chains: An information-processing model and an illustration. Journal of Purchasing and Supply Management, 15(4), 249-262. https://doi.org/10.1016/j. pursup.2009.05.004 Luthra, S., Govindan, K., Kannan, D., Mangla, S.K., & Garg, C.P. (2017). An integrated framework for sustainable supplier selection and evaluation in supply chains, Journal of Cleaner Production, 140, 1686-1698. https://doi.org/10.1016/j. jclepro.2016.09.078 Malviya, R.K., Kant, R., & Gupta, A.D. (2018). Evaluation and selection of sustainable strategy for green supply chain management implementation. Business Strategy and the Environment, 27(4), 475-502. https://doi.org/10.1002/ bse.2016 Matawale, C.R., Datta, S., & Mahapatra, S.S. (2016). Supplier selection in agile supply chain: Application potential of FMLMCDM approach in comparison with Fuzzy-TOPSIS and Fuzzy-MOORA. Benchmarking: An International Journal, 23(7), 2027-2060. https://doi.org/10.1108/BIJ-07-2015-0067 Mohammed, A., Setchi, R., Filip, M., Harris, I., & Li, X. (2018). An integrated methodology for a sustainable two-stage supplier selection and order allocation problem, Journal of Cleaner Production, 192, 99-114. https://doi.org/10.1016/j. jclepro.2018.04.131 Momeni, M., & Vandchali, H.R. (2017). Providing a structured methodology for supplier selection and evaluation for strategic outsourcing. International Journal of Business Performance and Supply Chain Modelling, 9(1), 66-85. https://doi.org/10.1504/IJBPSCM.2017.083888 Mummalaneni, V., Dubas, K., & Chao, C. (1996). Chinese Purchasing Managers' Preferences and Trade-Offs in Supplier Selection and Performance Evaluation, Industrial Marketing Management, 25(2), 115-124. https://doi.org/10.1016/0019-8501(95)00070-4 Nair, A., Guldiken, O., Fainshmidt, S., & Pezeshkan, A. (2015). Innovation in India: A review of past research and future directions. Asia Pacific Journal of Management, 32(4), 925-958. https://doi.org/10.1007/s10490-015-9442-z Ngai, E.W.T., Chau, D.C.K., & Chan, T.L.A. (2011). Information technology, operational, and management competencies for supply chain agility: findings from case studies, Journal of Strategic Information Systems, 20(3), 232-249. https://doi.org/10.1016/j.jsis.2010.11.002 Önüt, S., Kara, S.S., & Işık, E. (2009). Long Term Supplier Selection Using a Combined Fuzzy MCDM Approach: A Case Study for a Telecommunication Company, Expert Systems with Applications, 36(2), 3887-3895. https://doi.org/10.1016/j.eswa.2008.02.045 Ortiz-Barrios, M.A., Kucukaltan, B., Carvajal-Tinoco, D., Neira-Rodado, D. & Jiménez, G. (2017). Strategic hybrid approach for selecting suppliers of high-density polyethylene. Journal of Multi-Criteria Decision Analysis, 24(5-6), 296-316. https://doi.org/10.1002/mcda.1617 Int. J. Prod. Manag. Eng. (2022) 10(2), 143-158 Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Akhtar 156 https://doi.org/10.1016/j.omega.2015.08.010 https://doi.org/10.1016/j.cie.2018.05.012 https://doi.org/10.1504/IJPM.2015.070902 https://doi.org/10.1016/j.ijpe.2017.02.007 https://doi.org/10.1016/j.jbusres.2021.10.061 https://doi.org/10.1016/j.eswa.2014.08.041 https://doi.org/10.1016/j.eswa.2014.08.041 https://doi.org/10.3390/sym12121962 https://doi.org/10.1016/j.eswa.2009.12.036 https://doi.org/10.1016/j.eswa.2009.12.036 https://doi.org/10.1016/j.knosys.2011.11.019 https://doi.org/10.1016/j.pursup.2009.05.004 https://doi.org/10.1016/j.pursup.2009.05.004 https://doi.org/10.1016/j.jclepro.2016.09.078 https://doi.org/10.1016/j.jclepro.2016.09.078 https://doi.org/10.1002/bse.2016 https://doi.org/10.1002/bse.2016 https://doi.org/10.1108/BIJ-07-2015-0067 https://doi.org/10.1016/j.jclepro.2018.04.131 https://doi.org/10.1016/j.jclepro.2018.04.131 https://doi.org/10.1504/IJBPSCM.2017.083888 https://doi.org/10.1016/0019-8501(95)00070-4 https://doi.org/10.1007/s10490-015-9442-z https://doi.org/10.1016/j.jsis.2010.11.002 https://doi.org/10.1016/j.eswa.2008.02.045 https://doi.org/10.1002/mcda.1617 http://creativecommons.org/licenses/by-nc-nd/4.0/ Parthiban, P., Zubar, H.A., & Katakar, P. (2013). Vendor selection problem: a multi-criteria approach based on strategic decisions. International Journal of Production Research, 51(5), 1535-1548. https://doi.org/10.1080/00207543.2012. 709644 Paydar, M.M., Arabsheybani, A., & Safaei, A.S. (2017). A new approach for sustainable supplier selection. International Journal of Industrial Engineering & Production Research, 28(1), 47-59. Percin, S. (2019). An integrated fuzzy SWARA and fuzzy AD approach for outsourcing provider selection. Journal of Manufacturing Technology Management, 30(2), 531-552 https://doi.org/10.1108/JMTM-08-2018-0247 Rabbani, M., Foroozesh, N., Mousavi, S.M., & Farrokhi-Asl, H. (2019). Sustainable supplier selection by a new decision model based on interval-valued fuzzy sets and possibilistic statistical reference point systems under uncertainty. International Journal of Systems Science: Operations & Logistics, 6(2), 162-178. https://doi.org/10.1080/23302674. 2017.1376232 Rezaeisaray, M., Ebrahimnejad, S., & Khalili-Damghani, K. (2016). A novel hybrid MCDM approach for outsourcing supplier selection: A case study in pipe and fittings manufacturing, Journal of Modelling in Management, 11(2), 536-559. https://doi.org/10.1108/JM2-06-2014-0045 Rostamzadeh, R., Keshavarz Ghorabaee, M., Govindan, K., Esmaeili, A., & Khajeh Nobar, H.B. (2018). Evaluation of sustainable supply chain risk management using an integrated fuzzy TOPSIS- CRITIC approach, Journal of Cleaner Production, 175, 651-669. https://doi.org/10.1016/j.jclepro.2017.12.071 Sarkis, J. (2005). Performance measurement for green supply chain management, Benchmarking: An International Journal, 12, 330-353. https://doi.org/10.1108/14635770510609015 Sen, D.K., Datta, S., & Mahapatra, S.S. (2018). Sustainable supplier selection in intuitionistic fuzzy environment: a decision-making perspective. Benchmarking: An International Journal, 25(2), 545-574. https://doi.org/10.1108/BIJ- 11-2016-0172 Seuring, S. (2013). A review of modeling approaches for sustainable supply chain management. Decision Support Systems, 54(4), 1513-1520. https://doi.org/10.1016/j.dss.2012.05.053 Singh, P.K. & Sarkar, P. A (2021). Multi-Criteria Decision Approach to Select Contract Manufacturer for Sustainable Development of Automotive Products: an Integrated Framework. Process Integration and Optimization for Sustainability, 5, 843-857. https://doi.org/10.1007/s41660-021-00181-8 Sinha, A.K., & Anand, A. (2018). Development of sustainable supplier selection index for new product development using multi criteria decision making, Journal of Cleaner Production, 197, 1587-1596. https://doi.org/10.1016/j. jclepro.2018.06.234 Sivakumar, R., Kannan, D., & Murugesan, P. (2015). Green vendor evaluation and selection using AHP and Taguchi loss functions in production outsourcing in mining industry. Resources Policy, 46, 64-75. https://doi.org/10.1016/j. resourpol.2014.03.008 Song, W., Xu, Z., & Liu, H.C. (2017). Developing sustainable supplier selection criteria for solar air conditioner manufacturer: an integrated approach, Renewable and Sustainable Energy Reviews, 79, 1461-1471. https://doi.org/10.1016/j.rser.2017.05.081 Song, C.H. (2019). Deriving and Assessing Strategic Priorities for Outsourcing Partner Selection in Pharmaceutical R&D: an Approach Using Analytic Hierarchy Process (AHP) Based on 34 Experts' Responses from Korean Pharmaceutical Industry, Journal of Pharmaceutical Innovation, 14, 66-75. https://doi.org/10.1007/s12247-018-9336-y Teerasoponpong, S., & Sopadang, A. (2022). Decision support system for adaptive sourcing and inventory management in small- and medium-sized enterprises, Robotics and Computer-Integrated Manufacturing, 73, 102226 https://doi. org/10.1016/j.rcim.2021.102226 Trapp, A.C., & Sarkis, J. (2016). Identifying robust portfolios of suppliers: a sustainability selection and development perspective. Journal of Cleaner Production, 112, 2088-2100. https://doi.org/10.1016/j.jclepro.2014.09.062 Tse, Y.K., Zhang, M., Akhtar, P., & MacBryde, J. (2016). Embracing supply chain agility: an investigation in the electronics industry, Supply Chain Management - An International Journal, 21(1), 140-156. https://doi.org/10.1108/SCM- 06-2015-0237 Ulutas, A., Shukla, N., Kiridena, S., & Gibson, P. (2016). A utility-driven approach to supplier evaluation and selection: empirical validation of an integrated solution framework, International Journal of Production Research, 54(5), 1554-1567. https://doi.org/10.1080/00207543.2015.1098787 Um, J. (2017). Improving supply chain flexibility and agility through variety management, International Journal of Logistics Management, 28(2), 464-487. https://doi.org/10.1108/IJLM-07-2015-0113 Vasiljević, M., Fazlollahtabar, H., Stević, Ž., & Vesković, S. (2018). A rough multicriteria approach for evaluation of the supplier criteria in automotive industry. Decision Making: Applications in Management and Engineering, 1(1), 82-96. https://doi.org/10.31181/dmame180182v Int. J. Prod. Manag. Eng. (2022) 10(2), 143-158Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Sustainable and Agile Manufacturing Outsourcing Partner Selection: a literature review 157 https://doi.org/10.1080/00207543.2012.709644 https://doi.org/10.1080/00207543.2012.709644 https://doi.org/10.1108/JMTM-08-2018-0247 https://doi.org/10.1080/23302674.2017.1376232 https://doi.org/10.1080/23302674.2017.1376232 https://doi.org/10.1108/JM2-06-2014-0045 https://doi.org/10.1016/j.jclepro.2017.12.071 https://doi.org/10.1108/14635770510609015 https://doi.org/10.1108/BIJ-11-2016-0172 https://doi.org/10.1108/BIJ-11-2016-0172 https://doi.org/10.1016/j.dss.2012.05.053 https://doi.org/10.1007/s41660-021-00181-8 https://doi.org/10.1016/j.jclepro.2018.06.234 https://doi.org/10.1016/j.jclepro.2018.06.234 https://doi.org/10.1016/j.resourpol.2014.03.008 https://doi.org/10.1016/j.resourpol.2014.03.008 https://doi.org/10.1016/j.rser.2017.05.081 https://doi.org/10.1007/s12247-018-9336-y https://doi.org/10.1016/j.rcim.2021.102226 https://doi.org/10.1016/j.rcim.2021.102226 https://doi.org/10.1016/j.jclepro.2014.09.062 https://doi.org/10.1108/SCM-06-2015-0237 https://doi.org/10.1108/SCM-06-2015-0237 https://doi.org/10.1080/00207543.2015.1098787 https://doi.org/10.1108/IJLM-07-2015-0113 https://doi.org/10.31181/dmame180182v http://creativecommons.org/licenses/by-nc-nd/4.0/ Wang, C.N., Yang, C.Y., & Cheng, H.C. (2019). A Fuzzy Multicriteria Decision-Making (MCDM) Model for Sustainable Supplier Evaluation and Selection Based on Triple Bottom Line Approaches in the Garment Industry. Processes, 7(7), 400. https://doi.org/10.3390/pr7070400 Wang, J.J., & Yang, D.L. (2007). Using a hybrid multi-criteria decision aid method for information system outsourcing, Computers & Operations Research, 34, 3691-3700. https://doi.org/10.1016/j.cor.2006.01.017 Wu, C., & Barnes, D. (2011). A literature review of decision-making models and approaches for partner selection in agile supply chains, Journal of Purchasing & Supply Management, 17(4), 256-274. https://doi.org/10.1016/j. pursup.2011.09.002 Wu, K.J., Tseng, M.L., Chiu, A.S., & Lim, M.K. (2017). Achieving competitive advantage through supply chain agility under uncertainty: a novel multi-criteria decision-making structure, International Journal of Production Economics, 190, 96-107. https://doi.org/10.1016/j.ijpe.2016.08.027 Yang, D.H., Kim, S., Nam, C., & Min, J.W. (2007). Developing a decision model for business process outsourcing. Computers & Operations Research, 34(12), 3769-3778. https://doi.org/10.1016/j.cor.2006.01.012 Yazdani, M., Mohammed, A., Bai, C. & Labib, A. (2021). A novel hesitant-fuzzy-based group decision approach for outsourcing risk, Expert Systems with Applications, 184, 115517. https://doi.org/10.1016/j.eswa.2021.115517 Yusuf, Y.Y., Gunasekaran, A., Musa, A., Dauda, M., El-Berishy, N.M., & Cang, S. (2014). A relational study of supply chain agility, competitiveness and business performance in the oil and gas industry, International Journal of Production Economics, 147, 531-543. https://doi.org/10.1016/j.ijpe.2012.10.009 Zarbakhshnia, N., & Jaghdani, T.J. (2018). Sustainable supplier evaluation and selection with a novel two-stage DEA model in the presence of uncontrollable inputs and undesirable outputs: a plastic case study, The International Journal of Advanced Manufacturing Technology, 97(5), 2933-2945. https://doi.org/10.1007/s00170-018-2138-z Zhou, X., Pedrycz, W., Kuang, Y., & Zhang, Z. (2016). Type-2 fuzzy multi-objective DEA model: an application to sustainable supplier evaluation, Applied Soft Computing, 46, 424-440. https://doi.org/10.1016/j.asoc.2016.04.038 Zulkiffli, N.A., & Padlee, F. (2021). Sustainable outsourcing decisions, competitive capabilities and business performance of Malaysian manufacturing SMEs: a confirmatory factor analysis approach. Journal of Sustainability Science and Management, 16(1), 158-173. https://doi.org/10.46754/jssm.2021.01.014 Int. J. Prod. Manag. Eng. (2022) 10(2), 143-158 Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Akhtar 158 https://doi.org/10.3390/pr7070400 https://doi.org/10.1016/j.cor.2006.01.017 https://doi.org/10.1016/j.pursup.2011.09.002 https://doi.org/10.1016/j.pursup.2011.09.002 https://doi.org/10.1016/j.ijpe.2016.08.027 https://doi.org/10.1016/j.cor.2006.01.012 https://doi.org/10.1016/j.eswa.2021.115517 https://doi.org/10.1016/j.ijpe.2012.10.009 https://doi.org/10.1007/s00170-018-2138-z https://doi.org/10.1016/j.asoc.2016.04.038 https://doi.org/10.46754/jssm.2021.01.014 http://creativecommons.org/licenses/by-nc-nd/4.0/