\r\n\tIn order to understand the detailed content, these parameters are also divided into different classes such as inert, readily biodegradable, soluble COD, etc. However, still we do not possess detailed knowledge on organics in water sources or wastewater streams. Therefore, during the last decade, scientists tried to divide organics into different classes and understand their treatment potential and natural pathways. This book aims to fill out a very significant gap in this research field. Different treatment processes, monitoring and water determination chapters on dissolved organics, emerging organic pollutants, endocrine disruptors, emerging disinfection by-products, microplastic etc. in water or wastewater are welcome to this book project.
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1. Introduction
Supply chain management (SCM) is crucial in today’s competitive environment and is steadily gaining serious research attention. Companies are facing challenges in discovering ways to fulfill ever-rising customer expectations and remain competitive in the market while keeping costs manageable. To that end, they must carry out investigations to isolate inefficiencies in their supply chain (SC) processes. If a company is buying raw materials for use in manufacturing a product, which it then sells to customers that mean the organization has an SC, which it must then manage. According to [1], SCM is:
“A set of approaches utilized to efficiently integrate suppliers, manufacturers, warehouses, and stores, so that merchandise is produced and distributed at the right quantities, to the right locations, and at the right time, in order to minimize system-wide costs while satisfying service level requirements.”
SCM involves managing a series of activities relating to the planning, coordination and control of the movement of materials, parts and products from suppliers; the management of inventories of procured parts and of issues relating to production; an appropriate and cost-effective storage of products, and finally, transportation to the customer.
Another approach defines SCM in terms of different decision-making (DM) levels, namely, strategic, tactical and operational, and indicates that these DM levels of all scales optimize SC performance. On the other hand, traditional SC can be defined as a network which consists of suppliers, manufacturing facilities, distribution centers from which we procure raw materials, converted into finished good and deliver it to end user [2].
Certain differences exist between SCM and traditional logistics. Traditional logistics consists of actions that usually occur inside single organization boundaries, while SCM essentially defines a network of different companies working in coordination, with their main goal being to deliver finished products to customers. In addition, traditional logistics emphasizes SC functions, including purchasing, distribution and inventory management. SCM includes all the components of traditional logistics, but also tags on actions such as new product development, finance, marketing and customer service [3]. In this chapter, we consider following SC functions as mentioned in Figure 1.
Figure 1.
Considered SC functions.
1.1. Decision-making in SCM
An organization’s strategic, tactical and operational decision-making plays a vital role in ensuring that its SC is operating efficiently, allowing it to achieve the highest levels of customer satisfaction at an optimum cost. Decision-making at each level should focus on gaining a competitive edge and increasing market share. At each level, the nature of decision-making as well as and the related activities are different. There are three levels of decision-making which are (1) strategic-level decisions that have a long-lasting effect on the firm such as decisions related to warehouse location, capacity of warehouse and distribution centers, (2) tactical-level decisions that include decisions for the coming year such as decisions related to production, inventory level, absorption of uncertainty in production plan, transportation, and so on and (3) operational decisions that include decisions which are usually day-to-day such as loading/unloading, daily production plan, and so on.
1.2. MCDM methods and SCM
MCDM is a technique that combines alternative’s performance across numerous, contradicting, qualitative and/or quantitative criteria and results in a solution requiring a consensus [4, 5]. Knowledge garnered from many fields, including behavioral decision theory, computer technology, economics, information systems and mathematics is used. Since the 1960s, many MCDM techniques and approaches have been developed, proposed and implemented successfully in many application areas [6, 7]. The objective of MCDM is not to suggest the best decision, but to aid decision makers in selecting shortlisted alternatives or a single alternative that fulfils their requirements and is in line with their preferences [8, 9, 10] mentioned that at early stages, knowledge of MCDM methods and an appropriate understanding of the perspectives of DM themselves (players who are involved in decision process) are essential for efficient and effective DM.
There are several MCDM methods available such as the analytical hierarchal process (AHP), the analytical network process (ANP), TOPSIS, data envelopment analysis (DEA) and fuzzy decision-making. MCDM has been one of the fastest growing problem areas in many disciplines [11]. Over the past decade, many researchers have applied these methods in the field of industrial engineering, particularly in SCM, in making decisions. All the methods are equally capable of making decisions under uncertainty, and each one has its own advantages.
SCM is an MCDM problem because in the entire SC cycle, we must consider different criteria related to each sub-criterion of the SC cycle. In order to manage the entire SC, we have to identify the relationship of each criterion, which in turn impacts the performance of the SC. Based on the indicators identified, we then make decisions. This shows that decision-making is critical in managing the SC cycle, and that SCM is an MCDM problem. Supply chain management decisions are made under the conflicting criteria of maximizing profit and customer responsiveness while minimizing SC risk. Multiple criteria decision-making in supply chain management provides a comprehensive overview of multi-criteria optimization models and methods that can be used in SC decision-making [12].
1.3. Objective of the study
The objective of this study is to provide a systematic literature review on the application of MCDM methods in the decision process related to the considered SC functions (supplier selection, manufacturing, warehousing and logistics). The literature will be also categorized in terms of decision-making level (strategic, tactical and operational) and sector/application area during the decision process. This study is an attempt to answer the following research questions:
What is the (%) distribution of MCDM methods applications in terms of different SC decision levels (strategic, tactical and operational) and in the SC functions considered?
What is the (%) distribution of MCDM methods applications in terms of area of application?
What are the top MCDM methods applied at each SC functions considered and at different SC decision levels (strategic, tactical and operational).
2. Research methodology
In order to systematically carry out our literature review and use content analysis in the process, we adopt a methodology composed of four steps, based on the practical guidelines provided by Seuring & Gold [13] and Seuring et al. [14]. The process model consists of following steps as mentioned in Figure 2.
Figure 2.
Literature review methodology.
Step 1: The scope of the literature review in this chapter is limited to academic reviewed journals, conference papers and graduate dissertations because of their academic relevance, accessibility and ease of search. We did not include unpublished works, non-reviewed papers, working papers and book chapters. Inclusion of such papers is suggested as a future extension of our work. Papers using only MCDM methods and its integration with MODM methods were also included. However, papers focused solely on applied MODM methods were not included because it is beyond the scope and objective of this study. We searched within titles and abstracts in the Emerald, Elsevier, Taylor & Francis, Springer and Inderscience databases. Keywords that we used are “SCM and MCDM”; “Strategic and SCM”; “Tactical and SCM”; “Operational and SCM”; “MCDM and Supplier selection”; “MCDM and manufacturing”; “MCDM and warehousing”; “MCDM and logistics”; “DM and Supplier Selection”; “DM and Manufacturing”; “DM and Warehousing”; “DM and Logistics”; and so on. We used non-method-specific and method-specific MCDM keywords, DM keywords and SCM keywords. The material selection process led to samples of 140 papers published in more than 80 journals (the complete reference list is presented in a separate reference list).
Step 2: As recommended by [13], descriptive analysis must contain the distribution of selected reviewed articles in terms of time period, papers per country and across journals. Therefore, Figure 3 shows the annual distribution of selected articles across the period of study (2005–2017), Figure 4 shows the top five journals and Figure 5 shows distribution of articles published per country.
Figure 3.
Annual distribution of selected articles across the period of study (2005–2017).
Figure 4.
Top four journals of selected reviewed articles.
Figure 5.
Distribution of articles published per country.
Step 3: Category selection is the most important and essential step of any literature review paper. Category selection developed in this chapter is in line with the objectives set in Section 1.3 and will be able to answer research questions set in the last section. Therefore, in this chapter, we categorized papers in terms of decision-making level, SC functions considered, MCDM methods used and application area. In this step, each author assigned each paper to the specific category. Distribution of papers according to the DM level is aligned with the DM level explained in the abovementioned section, while the SC functions distribution is in line with the standard SC functions definition. Other dimensions, such as the application area and methods applied, were identified by reading the abstract, and in some cases, the conclusion of the article.
Step 4: Once the category selection has been developed, categories’ definitions have been clarified, and the papers were reviewed and categorized accordingly. We developed decision rules, and all authors were agreed on developed rules. All papers were read and categorized by individual reviewer, and all authors came up with the same distribution of articles. Only 11% of the papers had differences which were resolved by discussion. We paid attention to ensure the quality, reliability and validity of the review.
In the discussion given in the following section, we first show qualitative results and then proceed with a quantitative analysis.
3. Qualitative results
In this section, a systematic review of the literature on the application of MCDM methods will be discussed. We divided the literature review into the functions of SCM considered; decision-making level, sectors/application area, and country. Category selection of any literature review paper is critical to select paper and accept or reject them based on inclusion or exclusion principles.
3.1. Supplier selection
Many authors have used different MCDM methods to select suppliers strategically for different purposes and in different applications such as the best supplier selection based on sustainability principles, to integrate information on supplier behavior in a fuzzy environment, to solve the supplier evaluation problem in companies with bulk production costs associated with raw materials, and so on. At the tactical level, supplier selection involves the administration of procurement activities such as multi-product supplier selection problem, factors affecting the supplier selection process, and so on. At the operational level, supplier selection usually involves one-time procurement due to unavoidable factors. At this level of decision-making, a small quantity of a product is usually procured from a supplier to run the production line. Table 1 shows the categorization of papers in terms of decision-making level, MCDM methods used, application area/sector and country in supplier selection.
Use of MCDM methods in supplier selection at different DM levels.
3.2. Manufacturing
Strategically, decision-making associated with manufacturing involves capacity constraints, manufacturing process selection, and make-or-buy decisions, development of a structural model to identify the cause-and-effect relationships between different criteria in manufacturing, and so on. At the tactical level, the decisions considered are related to the production rate, demand forecast errors, utilization of manufacturing facilities and administrative constraints. MCDM methods are widely applied at the tactical level of manufacturing decision-making. At the operational level, the decisions considered are related to the rejection rate during manufacturing, cycle time and machine breakdown.
Table 2 shows the categorization of papers in terms of decision-making level, MCDM methods used, application area/sector and country in manufacturing.
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Table 2.
Use of MCDM methods in manufacturing at different DM levels.
3.3. Warehousing
Due to high client expectations, warehousing decisions are vital for organizations. At the strategic level, the decisions the authors and researchers in the literature considered were warehouse location selection, space utilization and urban distribution center location. Warehousing decisions have a long-term impact on the overall SC, and as a result, trade-offs must be made between conflicting alternatives. At the tactical level, the decisions considered were warehouse layout design, cost per order and response rate. Many authors applied MCDM methods for tactical warehousing decisions. At the operational level, the decisions considered were damages, reconciliation error and order fulfillment rate. Only a few applications of MCDM methods can be found in the literature on warehousing decisions at the operational level. Table 3 shows the categorization of papers in terms of decision-making level, MCDM methods used, application area/sector and country in warehousing.
Use of MCDM methods in warehousing at different DM levels.
3.4. Logistics
Logistics plays an important role in overall SC performance. At the strategic level, the decisions researchers considered were logistics provider selection, service reliability and freight cost. Many authors applied MCDM methods and techniques at the strategic level of decision-making in logistics. At the tactical level, decisions considered relate to logistics network design, mode of transport and establishment of logistic centre. At the operational level, the decisions considered were damages, delayed shipment rate, cost per delivery and operational performance (wrong delivery rate, for instance). A few authors applied MCDM techniques at the operational level. Table 4 shows the categorization of papers in terms of decision-making level, MCDM methods used, application area/sector and country in supplier selection, manufacturing, warehousing, and logistics, respectively.
Use of MCDM methods in logistics at different DM levels.
4. Quantitative result analysis
Today, competition is shifting from individual company performance to SC performance, thus making it essential for companies to measure their SC performance effectively and efficiently. To that end, they need to identify appropriate methods for evaluating the measurement of the performance of the entire SC cycle. This study will help managers, practitioners and researchers select the most appropriate MCDM method for managing their SC cycle and analyze the results quantitatively in the following aspects.
Figure 6 shows the percentage of papers covering each MCDM methods at different strategic, tactical and operational levels of SC decisions.
Figure 7 shows the top three MCDM methods for considered SC functions which are supplier selection, manufacturing, warehousing and logistics.
Figures 8 and 9 show the paper distribution of the application areas for MCDM methods and its distribution at different levels of DM.
Figure 10 shows the paper distribution at different levels of DM in considered SC functions.
Figure 6.
MCDM approach at the strategic, tactical and operational level.
Figure 7.
Top three MCDM methods of considered SC functions.
Figure 8.
Paper distribution of the application areas for MCDM methods.
Figure 9.
Paper distribution at different levels of DM.
Figure 10.
Paper distribution at different levels of DM of considered SC functions.
After summarizing the methods at the strategic, tactical and operational levels of decision-making, researchers and practitioners can now easily select most widely used MCDM methods in SC decision-making. Further, this research will help managers select a suitable technique from widely used MCDM methods for supplier selection, manufacturing, warehousing and logistics.
This study considered the application of MCDM methods in almost all sectors. After an extensive literature review, we found that many authors, managers and researchers have applied MCDM methods in many sectors and at different DM levels as mentioned in Figures 8 and 9, respectively.
Managers and decision makers need to select the best method at each level of decision-making in the entire SC. Figure 10 shows the use of MCDM methods at each level of decision-making in the entire considered SC cycle. We can infer from the figure that at a strategic level, 74% of papers applied MCDM methods in warehousing decisions; at a tactical level, 49% of papers used MCDM methods in manufacturing; and at an operational level, 15% of papers used MCDM methods in supplier selection.
5. Discussion
The systematic literature review on the application of MCDM methods in supply chain management demonstrates the richness of MCDM to take different DM perspectives in the decision process. At the early stage of application, most of the methods focus on the fragmented SC structure with inefficient processes at the supply, manufacturing, warehousing and logistics levels. The subsequent integration of SC processes motivates the application of MCDM to improve the global decision process (more holistic). However, the integration comes with many challenges. First, more criteria have to be considered in the decision process. Second, the number of decision makers increases.
For long-term decisions (strategic and tactical), the decision process involves many criteria resulting from the information collected through the different SC functions. Also, most often, different decision makers (SC actors) are involved in the decision process. Thus, the use of MCDM methods is more suitable for long- and mid-term decisions (around 90%). However, the application of MCDM for short-term decisions (operational/real time) is limited to only 10%. Indeed, operational decisions are made very rapidly, and only partial information is usually available due to lack of data. Thus, the application of MCDM is not predominant and sometimes more difficult to implement.
For the supplier selection process, a detailed analysis (Figure 10) shows that MCDM methods are commonly used for long-term (strategic and tactical) decisions (85%). This result can be explained by the intensification of global commerce due to globalization and ever-greater competition, where supplier selection is critical. Thus, the appropriate supplier selection plays a vital role in organizational success. Conversely, the smallest number of researchers and DMs (15%) used MCDM methods at the operational level because of the fact that supplier selection and evaluation decisions have an impact on product quality, delivery, cost of material and service level. Therefore, decisions such as make-or-buy and the establishment of long-term contracts with suppliers must be aligned with the strategic goals of an organization and cannot merely be taken at the operational level.
Regarding the manufacturing process, long-term (strategic and tactical) decisions are also critical and include the development of technology selection and capacity expansion strategies to overcome shortage, minimize cost and maximize overall production efficiency. Again, the literature review analysis shows that 91% of MCDM methods are applied for long-term (strategic and tactical) decisions. For short-term manufacturing decisions, we are usually in the execution process of production, and there is less flexibility in decision-making. Thus, we notice that only 9% of the studies used MCDM methods for short-term decision-making (operational level).
Long-term warehousing decisions include the location and the design (technology choice and capacity) of the facility, which is one of the drivers of SC management. Moreover, the number of facilities (Warehouses and Distribution Centers) determines the total cost and the response time. For that reason, different criteria are used to make appropriate decisions. A significant amount of MCDM methods are applied in this context (96%). However, only 4% of papers applied MCDM methods at the operational level has been reported in our study.
For logistics activities, Figure 10 shows that many researchers and decision makers applied MCDM methods for long-term (strategic and tactical) efforts (approximately 90%). An effective and efficient logistics system requires long-term planning by considering future expansions, mergers and globalization. Long-term decisions help organizations reduce transportation cost and increase delivery service. For short-term decisions (operational), decision makers are obliged to take rapid action because of uncertainty caused by the manufacturing or logistics service provider. Therefore, this study shows that 11% of researchers and decision makers applied MCDM methods for short-term DM (operational), which is the highest among all considered SC functions.
6. Limitations and further research directions
This chapter has a number of limitations, detailed as follows:
This review is limited to academic reviewed journals and conferences. Therefore, unpublished work, non-reviewed articles, working papers and practitioners’ articles can be included in a future extension of this research.
This review spanned 13 years (2005–2017), and we believe it is representative of the literature on the application of MCDM methods in SCM. Although this study is not exhaustive, it is however comprehensive (140 papers) enough to allow a conclusion.
In the allocation of DM levels (strategic, tactical, and operational) in a particular paper, we followed the definition of DM level by David Simchi-Levi, Kaminsky, & Simchi-Levi (2008).
6.1. Future research directions
In SC, there are many criteria that have to be considered while making decisions. These criteria are often conflicting in nature, and MCDM methods and their integration with other methods are able to provide a framework for DMs in solving SCM problems and challenges. Moreover, with more globalization and digitalization, data availability is increasing, and the potential application of MCDM methods in tackling SCM problems under uncertainties becomes inevitable but needs a transformation. Based on this study, the following future research directions are proposed:
In future, selected papers of this study can be further analyzed to know uncertain criteria that have been used for internal and external uncertainty in considered SC functions.
Analyzed papers were further examined to know the exact criteria that were considered by DM in considered SC functions.
Notwithstanding the above-mentioned limitations and future research direction, we strongly believe that this study is in a very important area, namely, applications of MCDM methods in SCM, and should fill a gap in the literature.
7. Concluding remarks
This chapter presented a systematic literature review on the application of MCDM methods in considered SC functions, namely, supplier selection, manufacturing, warehousing and logistics. A total of 140 papers covering a time span of 13 years from a well-known database were gathered, analyzed and categorized in terms of a long-term and short-term (strategic, tactical, and operational) DM perspective, MCDM method considered and application area. This study concludes that the research and application of MCDM methods in SCM have grown significantly in recent years. This study will help managers and decision makers select appropriate MCDM methods at a specific level of DM (strategic, tactical, and operational) and provide guidelines to managers to see which application area uses which MCDM methods. It is evident from the literature that shows that fuzzy sets and its integration with other MCDM methods have effectively and efficiently been applied at every level of the SC decision-making process as well as in the considered SC functions. This is because of the fact that due to digitalization and massive data available in the organization, perspective of SC has been totally changed. Organizations and decision makers need to change their traditional thinking when it comes to how to manage SC. Moreover, due to the availability of real-time data and information, the application of MCDM for short-term decisions will add a great value to the decision process and reduce uncertainty in managing SC. On the basis of this study, we conclude that fuzzy DM is the most appropriate MCDM method to use at different levels of DM and in building general DM models. Therefore, we believe that this systematic literature review answers all research questions that were raised and achieved the main objectives of our research.
\n',keywords:"SCM, MCDM, strategic, tactical and operational decision-making, fuzzy, AHP/ANP, TOPSIS, systematic literature review",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/59664.pdf",chapterXML:"https://mts.intechopen.com/source/xml/59664.xml",downloadPdfUrl:"/chapter/pdf-download/59664",previewPdfUrl:"/chapter/pdf-preview/59664",totalDownloads:1287,totalViews:812,totalCrossrefCites:1,totalDimensionsCites:6,hasAltmetrics:0,dateSubmitted:"October 15th 2017",dateReviewed:"January 16th 2018",datePrePublished:null,datePublished:"June 27th 2018",dateFinished:null,readingETA:"0",abstract:"Over the last decade, a large number of research papers, certified courses, professional development programs and scientific conferences have addressed supply chain management (SCM), thereby attesting to its significance and importance. SCM is a multi-criteria decision-making (MCDM) problem because throughout its process, different criteria related to each supply chain (SC) activity and their associated sub-criteria must be considered. Often, these criteria are conflicting in nature. For their part, MCDM methods have also attracted significant attention among researchers and practitioners in the field of SCM. The aim of this chapter is to conduct a systematic literature review of published articles in the application of MCDM methods in SCM decisions at the strategic, tactical and operational levels. This chapter considers major SC activities such as supplier selection, manufacturing, warehousing and logistics. A total of 140 published articles (from 2005 to 2017) were studied and categorized, and gaps in the literature were identified. This chapter is useful for academic researchers, decision makers and experts to whom it will provide a better understanding of the application of MCDM methods in SCM, at various levels of the decision-making process, and establish guidelines for selecting an appropriate MCDM method for managing SC activities.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/59664",risUrl:"/chapter/ris/59664",book:{slug:"multi-criteria-methods-and-techniques-applied-to-supply-chain-management"},signatures:"Sharfuddin Ahmed Khan, Amin Chaabane and Fikri T. Dweiri",authors:[{id:"94433",title:"Prof.",name:"Amin",middleName:null,surname:"Chaabane",fullName:"Amin Chaabane",slug:"amin-chaabane",email:"amin.chaabane@etsmtl.ca",position:null,institution:{name:"Polytechnique Montréal",institutionURL:null,country:{name:"Canada"}}},{id:"233200",title:"Dr.",name:"Sharfuddin",middleName:"Ahmed",surname:"Khan",fullName:"Sharfuddin Khan",slug:"sharfuddin-khan",email:"skhan@sharjah.ac.ae",position:null,institution:{name:"Polytechnique Montréal",institutionURL:null,country:{name:"Canada"}}},{id:"233201",title:"Prof.",name:"Fikri",middleName:null,surname:"Dweiri",fullName:"Fikri Dweiri",slug:"fikri-dweiri",email:"fdweir@sharjah.ac.ae",position:null,institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_1_2",title:"1.1. Decision-making in SCM",level:"2"},{id:"sec_2_2",title:"1.2. MCDM methods and SCM",level:"2"},{id:"sec_3_2",title:"1.3. Objective of the study",level:"2"},{id:"sec_5",title:"2. Research methodology",level:"1"},{id:"sec_6",title:"3. Qualitative results",level:"1"},{id:"sec_6_2",title:"3.1. Supplier selection",level:"2"},{id:"sec_7_2",title:"3.2. Manufacturing",level:"2"},{id:"sec_8_2",title:"3.3. Warehousing",level:"2"},{id:"sec_9_2",title:"3.4. Logistics",level:"2"},{id:"sec_11",title:"4. Quantitative result analysis",level:"1"},{id:"sec_12",title:"5. Discussion",level:"1"},{id:"sec_13",title:"6. Limitations and further research directions",level:"1"},{id:"sec_13_2",title:"6.1. Future research directions",level:"2"},{id:"sec_15",title:"7. Concluding remarks",level:"1"}],chapterReferences:[{id:"B1",body:'Simchi-Levi D, Kaminsky P, Simchi-Levi E. Designing and managing the supply chain: Concepts, strategies, and case studies. 3rd Edition. Boston: McGraw-Hill, Irwin; 2008'},{id:"B2",body:'Fox MS, Barbuceanu M, Teigen R. Agent-oriented supply-chain management. 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In: Transportation Research Procedia. 2017. vol. 25. pp. 4836-4855'},{id:"B121",body:'Yazdani M, Zarate P, Coulibaly A, Zavadskas EK. A group decision making support system in logistics and supply chain management. Expert Systems with Applications. 2017;88:376-392'},{id:"B122",body:'Moskolaï J, Houé R, Archimède B, Nlong JM. Sustainability assessment of a transportation system under uncertainty: An integrated multicriteria approach. In: IFAC-PapersOnLine. 2017. vol. 50. pp. 7742-7747'},{id:"B123",body:'Prakash C, Barua MK. An analysis of integrated robust hybrid model for third-party reverse logistics partner selection under fuzzy environment. Resources, Conservation and Recycling. 2016;108:63-81'},{id:"B124",body:'Kucukaltan B, Irani Z, Aktas E. A decision support model for identification and prioritization of key performance indicators in the logistics industry. Computers in Human Behaviour. 2016;65:346-358'},{id:"B125",body:'Osorio JC, Manotas DF, García JL. Multicriteria 3PL selection with risk consideration. Research in Computer Science. 2016;109:51-57'},{id:"B126",body:'Gürcan ÖF, Yazıcı İ, Beyca ÖF, Arslan ÇY, Eldemir F. Third party logistics (3PL) provider selection with AHP application. Procedia - Social Behaviour Science. 2016;235:226-234'},{id:"B127",body:'Bouzon M, Govindan K, Rodriguez CMT, Campos LMS. Identification and analysis of reverse logistics barriers using fuzzy Delphi method and AHP. Resources, Conservation and Recycling. 2016;108:182-197'},{id:"B128",body:'Wang YJ, Han TC, Chou MT. Applying fuzzy AHP in selection of transport modes for Kinmen military logistics. Journal of Marine Science and Technology. 2016;24(2):222-232'},{id:"B129",body:'Tavana M, Zareinejad M, Di Caprio D, Kaviani MA. An integrated intuitionistic fuzzy AHP and SWOT method for outsourcing reverse logistics. AppliedSoft Computing Journal. 2016;40:544-557'},{id:"B130",body:'Mangla SK, Govindan K, Luthra S. Critical success factors for reverse logistics in Indian industries: A structural model. Journal of Cleaner Production. 2016;129:608-621'},{id:"B131",body:'Uygun Ö, Kaçamak H, Kahraman ÜA. An integrated DEMATEL and fuzzy ANP techniques for evaluation and selection of outsourcing provider for a telecommunication company. Computers and Industrial Engineering. 2015;86:137-146'},{id:"B132",body:'Făgărăşan M, Cristea C. Fascicle of Management and Technological Engineering logistics center location: Selection using multicriteria decision making. Ann. ORADEA Univ., no. May, 2015'},{id:"B133",body:'Hwang B-N, Shen Y-C. Decision making for third party logistics supplier selection in semiconductor manufacturing industry: A nonadditive fuzzy integral approach. Mathematical Problems in Engineering. 2015;2015(Mcdm):1-12'},{id:"B134",body:'Haji Vahabzadeh A, Asiaei A, Zailani S. Reprint of ‘green decision-making model in reverse logistics using FUZZY-VIKOR method. Resources, Conservation and Recycling. 2015;104:334-347'},{id:"B135",body:'Akman GG, Baynal KJ. Logistics service provider selection through an integrated fuzzy multicriteria decision making approach. Journal of Industrial Engineering. 2014;2014'},{id:"B136",body:'Tadić S, Zečević S, Krstić M. A novel hybrid MCDM model based on fuzzy DEMATEL, fuzzy ANP and fuzzy VIKOR for city logistics concept selection. Expert Systems with Applications. 2014;41(18):8112-8128'},{id:"B137",body:'Rapee P. The key factors for selecting C2C Logistics Companies by using\\nFuzzy AHP in Thailand\\n. In: IOSR Journal of Business and Management (IOSR-JBM). 2014;16(11):pp. 75-85'},{id:"B138",body:'Tadic SR, Zecevic SM, Krstic MD. Ranking of logistics system scenarios for central Business District. Promet-Traffic & Transportation. 2014;26(2):159-167'},{id:"B139",body:'Jayant A, Gupta P, Garg SK, Khan M. TOPSIS-AHP based approach for selection of reverse logistics service provider: A case study of mobile phone industry. Procedia Engineering. 2014;97:2147-2156'},{id:"B140",body:'Bayazit O, Karpak B. Selection of a third party logistics service provider for an aerospace company: An analytical decision aiding approach. International Journal of Logistics Systems and Management. 2013;15(4):382-404'},{id:"B141",body:'Ho W, He T, Lee CKM, Emrouznejad A. Strategic logistics outsourcing: An integrated QFD and fuzzy AHP approach. Expert Systems with Applications. 2012;39(12):10841-10850'},{id:"B142",body:'Kabir G. Thırd party logıstıc servıce provıder selectıon usıng fuzzy AHP and TOPSIS method. International Journal of Quality Research. 2012;6(1):71-79'},{id:"B143",body:'Liu G, Chen J, Zhong J. An integrated SVM and fuzzy AHP approach for selecting third party logistics providers. Przegląd Elektrotechniczny. 2012;(9):5-8'},{id:"B144",body:'Erkayman B, Gundogar E, Yilmaz A. An integrated fuzzy approach for strategic alliance partner selection in third-party logistics. Scientific World Journal. 2012;2012:486306'},{id:"B145",body:'Erkayman B, Gundogar E, Akkaya G, Ipek M. A fuzzy Topsis approach for logistics Center location selection. Journal of Business Case Studies. 2011;7(3):49-54'},{id:"B146",body:'Gupta R, Sachdeva A, Bhardwaj A. Selection of 3pl service provider using integrated fuzzy delphi and fuzzy TOPSIS. In: Proceedings of the World Congress on Engineering and Computer Science. 2010. vol. 2. no. February 2016. pp. 20-22'},{id:"B147",body:'Perçin S. Evaluation of third-party logistics (3PL) providers by using a two-phase AHP and TOPSIS methodology. Benchmarking An International Journal. 2009;16(5):588-604'},{id:"B148",body:'Çakir E, Tozan H, Vayvay O. A method for selecting third party logistic service provider using fuzzy AHP. Journal of Naval Science Engineering. 2009;5(3):38-54'},{id:"B149",body:'Soh S. A decision model for evaluating third-party logistics providers using fuzzy analytic hierarchy process. African Journal of Business Management. 2010;4(3):339-349'},{id:"B150",body:'Çakir E. Logistics Outsourcing and Selection of Third Party Logistics Service Provider Logistics Outsourcing and Selection of Third Party Logistics Service Provider; 2009'},{id:"B151",body:'Kannan G, Pokharel S, Kumar PS. A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider. Resources, Conservation and Recycling. 2009;54(1):28-36'},{id:"B152",body:'Jharkharia S, Shankar R. Selection of logistics service provider: An analytic network process (ANP) approach. Omega. 2007;35(3):274-289'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Sharfuddin Ahmed Khan",address:"sharfuddin-ahmed.khan.1@ens.etsmtl.ca; skhan@sharjah.ac.ae",affiliation:'
Ecole de Technologie Superieure (ETS), University of Quebec, Canada
Ecole de Technologie Superieure (ETS), University of Quebec, Canada
'},{corresp:null,contributorFullName:"Fikri T. Dweiri",address:null,affiliation:'
University of Sharjah, United Arab Emirates
'}],corrections:null},book:{id:"6562",title:"Multi-Criteria Methods and Techniques Applied to Supply Chain Management",subtitle:null,fullTitle:"Multi-Criteria Methods and Techniques Applied to Supply Chain Management",slug:"multi-criteria-methods-and-techniques-applied-to-supply-chain-management",publishedDate:"June 27th 2018",bookSignature:"Valerio A. P. Salomon",coverURL:"https://cdn.intechopen.com/books/images_new/6562.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"179921",title:"Dr.",name:"Valerio",middleName:"A. 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\n
1. Introduction
\n
Offshoring is the act of delegating part of business work to an external and/or internal entity that is located somewhere else. Outsourcing involves obtaining certain services/products from a third party, while offshoring companies relocate some of their services/product lines to regions that offer them a competitive advantage. Due to the unifying factor of competitiveness, offshoring and outsourcing can be entangled, leaving a very thin line to separate them—especially in the service sector. Offshoring-outsourcing can involve captive outsourcing, nearshoring, and onshoring, depending on the location of the firm. By 2019, India was the number one destination for most offshore-outsourcing activities, owing to its financial attractiveness and skilled labour [1].
\n
Since 2000, the revenue of the global outsourced services industry had been rising steadily, reaching a peak in 2011, after which it started losing ground, as illustrated by the graph in Figure 1. In 2016, the industry market size dropped to USD 76.9 billion, the lowest revenue since 2005. The largest share of the revenue for this industry came from the Americas, followed by Europe and the Middle East, while Africa barely featured. A much smaller share of global revenue came from the Asia-Pacific region [2]. The cardinal role of outsourcing-offshoring is to cut costs such as taxes and production. Some other drivers include enabling a focus on the core business and solving capacity issues. Apart from information technology that accounts for more than 50% of the global outsourcing revenue, other major sectors include business services, energy, healthcare and pharmaceuticals, retail, travel and transport, and telecom and media. Figure 2 depicts the contribution of some of the selected sectors. However, since the outbreak of COVID-19, many industries have since been affected, causing slack in outsourcing/offshoring.
\n
Figure 1.
Global market size of outsourced services from 2000 to 2019 [2].
\n
Figure 2.
Comparison of the total contract value in the global outsourcing market by industry from 2008 to 2011 (in billion USD).
\n
Ever since the first case of the novel coronavirus (2019-nCoV), was detected in Wuhan, China, towards the end of 2019, and declared a global pandemic on 11th March by the World Health Organisation (WHO) [3], attention has now turned to how countries can survive and revive their economies in the new normal. The magnitude of the resultant shock from COVID-19 has not only tested the healthcare and disaster management systems of countries and the agility of policy responses to a public health catastrophe, but it has also significantly impacted businesses and their offshore-outsourcing processes. Unprecedented interruptions to business-as-usual have quickly cascaded across industries and geographies, especially with the implementation of stay-at-home orders in all sub-Saharan countries.
\n
In this chapter, we present how medical industry and other industries have been impacted during the COVID-19 pandemic in relation to offshoring-outsourcing business. COVID-19 pandemic resulted in border closure forcing nations to rethink of onshoring; in this chapter we present the tradeoffs between outsourcing-offshoring and onshoring.
\n
\n
\n
2. Medical sector
\n
Worldwide, the primary goals of the healthcare sector are to cut costs and improve the quality of care. With the acceleration of globalisation, healthcare services are impacted by healthcare outsourcing and offshoring [4]. The healthcare sector’s reliance on offshoring-outsourcing is more pronounced in today’s operating environment. Many incidences during the ongoing pandemic pointed towards either shortages or the non-availability of various materials at the point of requirement or consumption. The items included, among others, face masks and shields, hand sanitisers, surgical-grade materials, and other daily health supplies, escalating the ‘bullwhip’ effect on supply chains leading to onshoring [5].
\n
Despite the opportunities for synergies and improved efficiencies of outsourcing/offshoring, the undertakings are more complex and create longer and more fragmented supply chains which could have disastrous consequences, particularly in the healthcare context [6]. In the first quarter of 2020 (the COVID-19 pandemic), the impact on the production and shipment of pharmaceuticals was not felt. However, the delivery of critical items, such as chemicals, soon started dwindling. The impact led regulators and world leaders to assess the extent to which China dominates the world’s supply of active pharmaceutical ingredients and their chemical raw materials. An ongoing industry effort in the US and Europe to rebalance the pharmaceutical chemical supply chain is likely to be energised by government initiatives to ensure domestic production of drugs.
\n
As the coronavirus virus (COVID-19) pandemic has spread, health facilities have become overwhelmed, with potentially infectious patients seeking testing kits and personal protective equipment (PPE) (goggles, gloves, face shield and masks, air-purifying respirators and gowns). These critical items, which have been either outsourced or offshored, are in high demand. Many locations have experienced a scarcity of these products, at a time when they are needed most to care for highly infectious patients. An increase in PPE supply, in response to this new demand, would require a large increase in PPE manufacturing. An alternative is to outsource homemade masks, which feasibly could include scarves or bandanas. Some countries have even resorted to using unconventional solutions for PPE at local hospitals, such as plastic water bottle cut-outs for eye protection and plastic garbage bags for gowns. Calls for continuity of supplies through the repurposing of industrial capacity and other means seem unlikely to solve the shortage quickly enough, as supply chains have become more dysfunctional during the pandemic [7] and the global crisis can no longer be contained.
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With the urgent need for a rapid acceleration in the manufacturing process for a wide range of test-kits (antibody tests, self-administered, and others), outsourcing and offshoring will play a crucial role in this endeavour. By 2019, the global medical device outsourcing market size was valued at USD 104.5 billion, and it was expected to grow at a compound annual growth rate (CAGR) of 5.2% from 2015 to 2030. Due to the increased spending on contract research organisation (CRO) services, the market for medical device outsourcing is expected to increase during the forecast period. As there is an increased demand for medical devices due to the rising prevalence of chronic diseases, various companies are shifting their focus to research and development, and are outsourcing medical devices [8].
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Changes to the ISO standards are likely to drive the demand for specialists in regulatory affairs and quality assurance service providers in the developed countries, precisely due to small-medium enterprises requiring third-party assistance to comply with the new ISO standards. Original equipment manufacturers and subcontractors in developed countries, such as Canada, Japan, the US, and European Union countries, are anticipated to adopt new ISO standards, thereby driving the market for medical device outsourcing [9]. In addition, recent regulatory changes in Europe relating to the quality and outsourcing of medical devices are also anticipated to increase the demand for quality assurance services and regulatory affairs, thereby, accelerating the outsourcing offshoring market growth [9]. Figure 3 shows the projected revenue growth of the outsourced medical service market.
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Figure 3.
Global medical device sales forecast [8].
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Previously, medical device companies have tended to deliver value, mainly through outsourcing manufacturing and selling their products. However, in the new normal, with mounting pressure on the healthcare system, there are foundational shifts in the care delivery model, and as a result, the industry value chain is set for a drastic overhaul. Therefore, companies will need to step out of their conventional manufacturing role [10]. The WHO reiterated this call to governments and industry to increase PPE manufacturing by 40% to meet rising global demand, and to avoid the severe and mounting disruption to the global supply of PPE being caused by rising demand, panic buying, hoarding and misuse. Thus, putting lives at risk from COVID-19 and other infectious diseases. There is no doubt that the lack of PPE puts health workers and patients at high risk of being infected and infecting others with COVID-19 [11].
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3. Other industries
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Many outsourcing companies that have offshored operations in countries like India, China, Singapore and Vietnam have been devastated by the crisis. Since the global lockdown in March, companies have been failing to deliver orders due to the labour force being forced to stay home. However, although the global crisis damaged businesses, not all companies are losing money. As more people are working from home, the demand for technology that enables online group meetings has skyrocketed. For example, shares in Zoom™ video conferencing companies have risen by 50% since February 2020. Similarly, the demand for TV shows and movies to watch at home soared to the extent that giant streaming services like Netflix™ and YouTube™ reduced the quality of their streaming in Europe to ease the pressure on the internet. Thus, the offshoring-outsourcing of information technology and streaming services is expected to increase post-pandemic to meet the high demand.
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The outsourced service industry seems to be less affected, and where it is affected, it is expected to recover shortly, as giant companies will be looking for better ways to cut costs in the post-pandemic era. However, the manufacturing industry has been strongly hit since it involves the movement of parts. In the midst of the pandemic, customers need advanced technology and automation to cope with the uncertainties that companies have been grappling with for the last decade. The outbreak of the coronavirus affected the supply chain and disrupted the supply chain/operation of manufacturing across the world. Companies that heavily offshore-outsource in Vietnam, China and India have been the most vulnerable. The global automotive industry, which imports more than $14 billion (by 2017) in motor parts from China annually, was significantly impacted [12]. In fact, companies throughout the supply chain are being forced to make tough decisions, like slowing or halting production, resourcing products, and re-evaluating revenue. For example, the Italian-American automobile manufacturer, Fiat Chrysler Automobiles, halted their production in Serbia [13].
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The Indian outsourcing market is worth approximately $50 billion [14]. This includes companies that work in application development areas, such as quality assurance testing services. Companies that rely on outsourcing firms in India range from financial services providers to major technology companies, to name just two of many industries. However, outsourcing firms were simply not prepared for the pandemic and the ensuing lockdown. Outsourcing companies lacked the infrastructure to work remotely while continuing to manage the performance of their teams and meeting client requirements, and their customers are now feeling the pain in the loss of business continuity. Especially in offshore locations, much of the workforce has not previously been set up for this work-from-home scenario, presenting new tactical and operational challenges [15]. The notion of ‘work from home’ is generally not supported by outsourcing companies, and they do not typically provide workers with laptops to use at home. Even if workers have the technology to work from home, including internet connections and secure systems access, many outsourcing firms require client permission for them to do so.
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The outsourcing-offshoring industries do not lend themselves to working from home. For example, because of security concerns, some companies even ask employees to leave even their pens and pencils outside the office. Specifically, the companies that relied on outsourcing firms for their testing services were left in a lurch. Digital quality is now more critical than ever, given our global reliance on digital experiences, and the companies providing those digital experiences are unable to get the testing they need from offshoring-outsourcing firms. In technology, offshoring is simply moving testing from one office to another. Due to cultural and technological factors, that new office may be less capable of ensuring business continuity during a crisis. In addition, offshoring testing services does not equate to an increase in skill sets or the ability to do different types of testing.
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4. Pandemic offshore-outsource tradeoff
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The pandemic has been a wake-up call for outsourcing-offshoring economies; why was the US manufacturing industry unable to supply the necessary materials like face masks, medical ventilators, and PPE? Taken together, the US and other advanced industrial economies have evolved a highly efficient and productive product manufacturing-and-delivery system that provides them with a cornucopia of products at relatively low costs. However, inherent to that system are dependencies and expectations that have been called into question by the pandemic. Such performance has fuelled politicians and policymakers to advocate for a reduction in the outsourcing-offshoring business—cementing President Trump’s call to bring the production industry back from overseas.
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The US alone reduced the corporate rate from 35–21% to encourage companies to re-offshore. Besides that, some US policymakers are proposing a $25 billion fund for companies to re-offshore/re-outsource back to the US from China for the next five years [16]. Companies like Telstra™ in Australia that depend heavily on the Philippines have enacted plans to hire more than 3500 workers back home [17]. At a glance, COVID-19 is likely to deaccelerate outsourcing-offshoring businesses. However, the issue is complex and defies easy solutions, as discussed in the following offshore-outsource tradeoffs.
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4.1 Offshore-outsource vs. onshore skills
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The challenge lies in a combination of how modern supply networks are structured and the operational metrics that apply to manufacturers. Gone are the days when one giant manufacturer, like CAT™ or Toyota™, could design, manufacture, and assemble the components needed to make a product. Today’s manufacturing technology is too complicated to have all the skills in one place. Thus, manufacturers have resorted to outsourcing-offshoring to search for those missing skills at a lower cost. Even something as simple as a lightbulb has components like LED lights that must be made in high-tech industries. Day-to-day equipment like smartphones, computers, and medical equipment contain components that require a great deal of precision and accuracy, and that need considerable training and experience.
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During the pandemic, among the items in most demand were PPE (e.g. masks and gloves) and ventilators; the latter being the most technical that requires detailed skills and experience to manufacture. A ventilator blows air and oxygen into the patient’s lungs, preventing them from collapsing. They are complicated pieces of machinery that cannot be created or grafted quickly. At the start of the pandemic, the US had 62,000 fully functioning ventilators and nearly 100,000 older model ventilators. With COVID-19 hitting every corner of the country, nearly a million ventilators were required to treat the patients [18]. A single ventilator contains hundreds of parts, and it takes days for an experienced team to make and assemble such parts to produce a ventilator. Ford and GM, leading car manufacturers in the US, spent over 30 days trying to organise the production lines and training workers to produce ventilators [19].
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South Africa (SA) was the most affected country in Africa, with almost 750,000 cases of COVID-19 infection by November 2020. For years, South Africa has depended on the United Kingdom (UK) to outsource medical equipment, ventilators included. During the peak of the pandemic in Europe (end of March 2020), Penlon, the leading manufacturer of ventilators in the UK, could not supply SA, citing the incapability of the company to produce extra ventilators for the SA community. In addition, SA could not reproduce the ventilators due to patent rights. The situation reflects the dangers of relying on offshoring or outsourcing vital equipment. However, once SA was able to acquire the patent rights to produce the ventilators, the country did have the necessary skills to produce them. It took weeks for the SA government to find a local ‘peep valve’ manufacturer, a vital component that allows patients to exhale. The skills needed to produce a single medical ventilator range from fabrication, material processing and simulation to software coding, and such skills are hard to find in a single onshore organisation. Thus, to ameliorate production and meet the much-needed demand, outsourcing/offshoring, some of the parts and skills is the only viable option.
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Similarly, the development of a vaccine is one of the critical measures to mitigate the effect of COVID-19. However, very few countries could respond with the required expertise, capacity, and abundant resources. This is mainly because vaccine productions methods place certain requirements on the supply chain that include, but are not limited to, novel skills set, meticulous maintenance, production equipment, and ultra-cold chain storage and shipping process. These rigorous requirements have left many countries with the option of outsourcing the service from leading foreign organisations [20]. Storage is a key part of the vaccine process and requires precise conditions of light, glass vials, and a specific −80°C across the entire supply network to preserve and maintain the effectiveness of the vaccine. The nature of vaccine supply means that there are often several places (warehouses and stores) where items have to be stored before they are finally delivered or administered to beneficiaries. Thus, this is another pandemic tradeoff between outsourcing vs. onshore skills vis-a-vis resources. In particular, the tradeoff is between the onshore skills related to vaccine production to ensure a rapid response and to prevent morbidity and mortality versus costly outsourcing; a demand which is most likely to exceed supply, and which will leave many nations vulnerable and defenceless.
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4.2 Offshore-outsource vs. air pollution tradeoff
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Materials that feed the manufacturing industry are localised. The transport of raw materials from Uganda, the Philippines or Vietnam to outsourcing-offshoring economies could mean incurring high transportation costs. Besides, the stringent environmental laws in developed economies could make the processing of such materials practically impossible. Before the UK and US started practising outsourcing-offshoring of some types of business, they had some of the worst air pollutions in the world. The processing operations were sent to the likes of China and India, countries that are now experiencing the worst air pollution ever [21, 22]. Though outsourcing-offshoring countries have paid some price in terms of job losses, the benefit of improved air and water quality somewhat outweighs the price.
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Air pollution is responsible for 4.2–7.0 million premature deaths every year [3, 23], and it costs $4.6 trillion per year [24]. This number barely makes headlines, although it is more than five times the current COVID-19 deaths. COVID-19 has elicited that there is a clear correlation between emissions and outsourcing-offshoring. Figure 4 shows the mean tropospheric nitrogen dioxide concentration (μmol/m2) as a satellite image from the National Aeronautics and Space Administration (NASA) in January and February 2020. The levels of NO2 plummeted following the virus outbreak in far Asia [25] due to the closure of factories and reduced movement of workers that use cars to go to work. The decrease in ozone precursors, like NO2, could reflect a reduction in ozone levels; however, ozone concentration increased. Ozone breathing triggers COVID-19 like symptoms like chest pain, coughing, and airway inflammation [26]. Another pollutant that is related to manufacturing is particulate matter (PM). PM elevates cancer, premature deaths, coughing and eye diseases, among others [27]. The production of particulate matter below 2.5 microns (PM2.5), a harmful emission, accelerated in countries like China [28] due to outsourcing-offshoring business in the country. As countries are rushing to tradeoff offshoring and outsourcing companies back home, they should meticulously calculate the cost related to air pollution; otherwise, pollution costs might outweigh such a venture.
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Figure 4.
NO2 distribution in eastern Asia in January and February 2020, as reported by NASA. The images were captured by Sentinel-5 satellite [25].
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4.3 Offshore-outsource vs. carbon dioxide tradeoff
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Among the major greenhouse gases (GHGs), carbon dioxide (CO2) tops the list. The emission of CO2 causes global warming and erratic Climate changes (e.g. flooding). By 2018, China was the leading producer of CO2, 10.06 GT (28% of the total CO2 emission), with almost half to the second producer of CO2, the US (5.41 GT, 15% of the world total). The huge amount of CO2 production is attributed to the high number of offshore-outsource manufacturing companies in the country, as China is the number one destination for offshore-outsource companies. The Paris Agreement on limiting the global temperature targets a maximum increase of 1.5°C by 2100; however, the current trends in GHG production show that this goal cannot be achieved. In 2015 and 2016, total warming exceeded 1.0°C [29]. Mitigation pathways to limit the warming by 1.5°C by the end of the century are far behind, and they have received little attention. It is estimated that it will cost US$ 50 trillion to keep the global temperature rise below 3.0°C by the end of the 21st century [30]. If countries are to implement onshoring, and this cost is to be shared based on the emission percentage, it could be too expensive for nations like Brazil and SA to implement onshoring. SA contributes 1% of total CO2 emission; coal contributes 77% of SA’s energy needs. Thus, any manufacturing activity risks the production of CO2—a cost SA may not be able to afford.
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4.4 Offshore-outsource vs. livelihoods
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Another pandemic tradeoff is that of offshore-outsource vs. livelihoods. Most people, especially in many developing nations, live on the poverty line, depending mainly on COVID-19-impacted industries such as travel, tourism, hospitality, call centres, and manufacturing. However, the pandemic presents a catch-22 situation for those nations that provide offshoring and outsourcing business services to multinationals. On the one hand, the countries that provide outsourcing and offshoring services are unable to fulfil their targets due to lockdown, an impact which drives multinationals into bankruptcy and out of their countries. As such, many nations are caught between maintaining their livelihoods by keeping multinational businesses in their countries, which ensures employment, food on the table, jobs, and which prevents multiple deaths from hunger and poverty. On the other hand, against the need to maintain offshore and outsource services, is the risk of increased morbidity and mortality from COVID-19 which places a greater demand on an already strained healthcare system and limited resources such as ventilators and PPE. This has left many nations vulnerable and defenceless to both challenging instances.
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Thus, this requires creating an imminent negative or positive restructuring of offshore-outsource strategies. For example, the several research studies that required clinical trials and the collaborative participation of multinationals in the fight against diseases such as Parkinson’s disease, and leishmaniasis (a parasitic disease associated with poverty and malnutrition) have been suspended. The suspension threatens livelihoods that relied on outsourced and offshored clinical services, and the research skills to reduce the impact of such diseases in society [31]. Also, the disruption to the distribution of outsourced malaria-prevention products, such as insecticidal nets, could lead to an increase in malaria deaths in sub-Saharan Africa. Yet, the continuation of offshore-outsource production and research services equally increase morbidity and COVID-19 mortality.
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5. Conclusion
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Outsourcing-offshoring has played a cardinal role in the development of our economies and is the backbone of the global market. Our study provides a comprehensive analysis of the current and future trend of outsource-offshore post-COVID-19. The current trend of border closure and transport restriction does not favour outsource-offshore practices, rather onshore business. However, meticulous analysis of the supply chain, shows that the cost of onshore outweighs outsource-offshore as summarised in the following tradeoff benefits.
Skills: No nation can have all the skills needed to sustain its population, especially in the developing economies. In countries where skills are available, they are expensive to recall offshore businesses. During the pandemic, South Africa had to depend on Penlon skills to get ventilator rights. It took more than six weeks for South Africa to find a “peep valve” manufacturer, a vital component in ventilators. Besides, in the race to find the coronavirus vaccine, most countries must depend on offshore-outsource business to access the vaccine.
Air pollution: If countries are to practice onshore, their air pollution is expected to become worse, especially in countries that depend on unrenewable resources. Air pollution is responsible for 4.2–7.0 million premature deaths every year, and it costs $4.6 trillion per year; this number is three times compared to current COVID-19 deaths. Also, production of nitrous gases and particulate matter particles will increase upon onshoring. Particulate matter elevates cancer, coughing, eye diseases, among others. Such costs make offshoring-outsourcing a better alternative.
Carbon dioxide: Carbon dioxide is one of the leading causes of global warming and climate change. Today China contributes 28% of total CO2 emission (10.06 GT), mainly due to onshoring. Such emission has increased flooding in the region and has affected farming in a sector that contributes over 10% of China’s Gross domestic product (GDP). If developing countries that depend on agriculture are to practice onshoring, the cost will be too high—thus practising offshoring-outsourcing offers a better alternative.
Livelihood: Offshore-outsource is the bedrock for economic activities that can improve livelihoods and the GDP for countries that offer the business activities for multinationals but keeping the lights on can spiral the COVID-19 cases. However, turning off offshore-outsource activities to combat the upsurge of Covid-19 leads to job loss, economy plunge, livelihood loss, and rise of other healthcare issues induced by poverty, starvation, and mental health. Thus, countries must find an offshore-outsource onshore balancing point that is trailed to their own situation.
Demand for medical supplies: As governments and industries increase manufacturing to meet the rising global demand of especially medical supplies to avoid the severe and mounting disruption to the worldwide supply, offshoring/outsourcing and onshoring models will have to be revised to suit the context while meeting the demand caused by immobility pandemics.
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Acknowledgments
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We gratefully acknowledge Retha Burger for her suggestions and language editing. We also thank the editor and anonymous reviewers for their thorough review and constructive comments.
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\n',keywords:"coronavirus, air pollution, manufacturing, public health, president trump, COVID-19, pandemic, outsourcing, Onshoring, supply chain",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/74604.pdf",chapterXML:"https://mts.intechopen.com/source/xml/74604.xml",downloadPdfUrl:"/chapter/pdf-download/74604",previewPdfUrl:"/chapter/pdf-preview/74604",totalDownloads:166,totalViews:0,totalCrossrefCites:0,dateSubmitted:"October 10th 2020",dateReviewed:"November 29th 2020",datePrePublished:"December 28th 2020",datePublished:null,dateFinished:"December 28th 2020",readingETA:"0",abstract:"The world has become a global village with companies investing in different nations to remain afloat and competitive. In the process of offshoring- outsourcing, companies and nations have become interdependent in their efforts to bridge the supply chain network. However, during a pandemic, such as the Coronavirus (COVID-19) that involved the closure of borders, and during which there was a high demand of lifesaving machines and personal protective equipment, many countries were left scrambling for critical medical products such as ventilators and personal protective equipment for doctors. Hence, the tendency away from offshoring and outsourcing to onshoring production. COVID-19 has elicited that countries need to invest in an onshore business if they are to remain afloat. However, investing in onshore (local) business calls for a tradeoff, which some countries cannot afford. Many countries lack skilled labour (developing countries), and where available, it is too expensive (developed countries) making onshore an expensive venture. Besides, promoting manufacturing companies means increased air pollution and greenhouse gases that are responsible for 4.2–7.0 million premature deaths every year, and which costs $4.6 trillion per year. Such death rates and cost can hinder the onshore business. Therefore, for countries to survive in the era of a pandemic, the best alternative is to build strong ties with offshore-outsource nations.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/74604",risUrl:"/chapter/ris/74604",signatures:"George William Kajjumba, Oluka Pross Nagitta, Faisal A. Osra and Marcia Mkansi",book:{id:"9547",title:"Outsourcing and Offshoring",subtitle:null,fullTitle:"Outsourcing and Offshoring",slug:null,publishedDate:null,bookSignature:"Dr. Mario Franco",coverURL:"https://cdn.intechopen.com/books/images_new/9547.jpg",licenceType:"CC BY 3.0",editedByType:null,editors:[{id:"105529",title:"Dr.",name:"Mario",middleName:null,surname:"Franco",slug:"mario-franco",fullName:"Mario Franco"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Medical sector",level:"1"},{id:"sec_3",title:"3. Other industries",level:"1"},{id:"sec_4",title:"4. Pandemic offshore-outsource tradeoff",level:"1"},{id:"sec_4_2",title:"4.1 Offshore-outsource vs. onshore skills",level:"2"},{id:"sec_5_2",title:"4.2 Offshore-outsource vs. air pollution tradeoff",level:"2"},{id:"sec_6_2",title:"4.3 Offshore-outsource vs. carbon dioxide tradeoff",level:"2"},{id:"sec_7_2",title:"4.4 Offshore-outsource vs. livelihoods",level:"2"},{id:"sec_9",title:"5. Conclusion",level:"1"},{id:"sec_10",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'\nE. Mazareanu, Leading countries in offshore business services worldwide in 2019, 2019. https://www.statista.com/statistics.\n'},{id:"B2",body:'\nStatista, Global market size of outsourced services from 2000 to 2019, 2020. https://www.statista.com/statistics.\n'},{id:"B3",body:'\nS. Aydın, BA. Nakiyingi, C. Esmen, S. Güneysu, M. 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Res. 186 (2020). https://doi.org/10.1016/j.envres.2020.109586.\n'},{id:"B28",body:'\nX. Lu, S. Zhang, J. Xing, Y. Wang, W. Chen, D. Ding, Y. Wu, S. Wang, L. Duan, J. Hao, Progress of Air Pollution Control in China and Its Challenges and Opportunities in the Ecological Civilization Era, Engineering. (2020). https://doi.org/10.1016/j.eng.2020.03.014.\n'},{id:"B29",body:'\nR.J. Millar, J.S. Fuglestvedt, P. Friedlingstein, J. Rogelj, M.J. Grubb, H.D. Matthews, R.B. Skeie, P.M. Forster, D.J. Frame, M.R. Allen, Emission budgets and pathways consistent with limiting warming to 1.5 °c, Nat. Geosci. 10 (2017) 741-747. https://doi.org/10.1038/NGEO3031.\n'},{id:"B30",body:'\nB. Lomborg, Welfare in the 21st century: Increasing development, reducing inequality, the impact of climate change, and the cost of climate policies, Technol. Forecast. Soc. Change. 156 (2020). https://doi.org/10.1016/j.techfore.2020.119981.\n'},{id:"B31",body:'\nR.T. Aruleba, B.O. Osero, R. Hurdayal, COVID-19 might have reversed the war against a serious parasitic disease, Conversat. (2020). https://theconversation.com/covid-19-might-have-reversed-the-war-against-a-serious-parasitic-disease-147042 (accessed 10 November, 2020).\n'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"George William Kajjumba",address:"gwkajjumba@gmail.com",affiliation:'
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UK Research and Innovation (former Research Councils UK (RCUK) - including AHRC, BBSRC, ESRC, EPSRC, MRC, NERC, STFC.) Processing charges for books/book chapters can be covered through RCUK block grants which are allocated to most universities in the UK, which then handle the OA publication funding requests. It is at the discretion of the university whether it will approve the request.)
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