Table of Contents Title: Literature Review on Application of Quantitative Methods in Design and Analysis of “Dairy Supply Chain”......................................................................................................................1 Supply Chain Design..............................................................................................................1 Supply Chain Analysis...........................................................................................................3 Summary of Findings.............................................................................................................6 REFERENCES................................................................................................................................7
Title: Literature Review on Application of Quantitative Methods in Design and Analysis of “Dairy Supply Chain” Supply chain management refers to the flow of goods and services of a product from suppliers to end users. It is an integration of key business process which provides information that adds value of business for customers and stakeholders(Prakash and et. al., 2017). In context with agriculture industry, SCM helps in developing the area for meeting demand of global market. The present assignment is going to conduct a literature review on dairy supply management, by exploring some articles from secondary resources. All important aspects of SC design including authorities, flow of products or services, risks decisions and more are well explained in this part of literature review(Ivanov and et. al., 2016). Supply Chain Design Dairy supply chain encompasses with corporations which are responsible mainly for production and distribution of dairy based products. This process among other agriculture base businesses refers to most complex that starts with raw milk production, but ends when customers, processors and others utilize the same(Tostivint and et. al., 2017). The Australian Dairy Industry is considered as the third biggest industry after wheat and beef production. It adds a total value that earns over A$13.7 billion which is considered as the biggest value adding industries in today's agriculture business (Investment and The Australian Dairy Industry,2019). Design and Structure of dairy supply chain of Australia follows the given procedure, that consistsmorethanonprimaryproductsuppliers.Thesesuppliersmakeinteractionwith distributors to add value to dairy products which is eventually presented to end customers (Behzadi and et. al., 2017). 1
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Dairy farmers and Australian industries work in cooperation with a range of key partners thatincludes:DataGene,DairyBio,DairyManagementInc.,GeoffreyGardinerDairy Foundation, De Laval, Department of Agriculture and Food Western Australia, Department of Agriculture and Water Resources, Dairy Manufacturer's Sustainability Council etc. All these organisations collaborate together as collective for ensuring better outcomes(Palmieri, Forleo and Salimei, 2017). Here, in dairy supply chain of Australia, flow of products or services can also be well-defined by given figure:- 2
Supply Chain Analysis As per the article given by Venkata Subbaiah and et. al. (2009), it has been analysed that supply chain network within dairy industry can be build by using a multi-objective function (Supply Chain Management in Dairy Industries,2009). It is basically formulated for minimising cost which is subjected to supplies, distribution and plant capacities, production through custom demand requirements etc. This function includes various costs as material, production and transportation that aid to increase efficiency of supply chain management, within dairy industry (Dani, 2015). Muhammad Ziaullah (2014) has given an article on identifying the issue within informal channel bargaining power (Dairy Supply Chain Management and Critical an Investigation on Dairy Informal Channel Partners in Pakistan. 2014). For this purpose, the critical failure of SCM in dairy industry, secondary data is presented in tabular manner then mathematical formulae has been used to calculate the increased percentage in milk production worldwide (Dubey, Gunasekaran and Ali, 2015). This would help in developing the fact sheet through which effective strategies and policies can be developed, to avoid wastages, losses and more, for sustaining the dairy supply chain. 3 Illustration1: Flow of Dairy Products and Services
The article given by Habtamu Lemma (2015), mainly aims to identify the determinants in dairy industry related to supply chain coordination (Measuring Supply Chain Coordination in Milk and Dairy Industries: A Confirmatory Factor Model,2015). It concerns more on how to get sustainability in competitive business management. For this purpose, confirmatory model and factor analysis methods have been used in data analysis which is quantitative in nature and items were measured through a pilot test method. Here, factor analysis in dairy supply chain process resultsinkeyco-ordinationindicators(KirilovaandVaklieva-Bancheva,2017).While confirmatory model gives standardized result by constructing non-price and price coordination, relationship and product development decision for developing coordination among milk and dairy industries. InthearticlegivenbyJavid,SeyedandFathian(2013),Fuzzymixed-integer programming (FLP) has been used to incorporate the possible alterations in transportation network, monetary value of time, facility investment costs and production process' changes (Dynamic diary facility location and supply chain planning under traffic congestion and demand uncertainty: A case study of Tehran,2013). Along with this, conceptual modelling is also used to model the problem that showcase flow of supply chain management within dairy industry(Mor and et. al., 2015). Through non-linear mixed-integer programming, the dynamic facility location as well as supply chain planning within traffic congestion and demand uncertainty can be formulated easily. In the article which is proposed by Sahar Validi, Arijit Bhattacharya (2018), some mathematicalformulaehasbeenusedtoexploretheoutcomes.ItincludesBi-objective programming, Mixed-integer programming, two-phase and DoE-guided meta-heuristic sulution approaches (Sustainability distribution system design: a two-phase DoE-guided meta-heuristic solution approach for a three-echelon bi-objective AHP-integrated location-routine model, 2018).These proposed model helps in bridging the gap among existing distribution system and environmental impact of distribution(Behzadi and et. al., 2017). It majorly considers capacities related to processing plants, retailers within dairy industry and routes connecting them, in order to minimise the emission of harmful gases. Stefan Bojnec (2014) has analysed the export competitiveness within dairy products of EU countries by using revealed comparative advantage (RCA) index (Export competitiveness of dairy products on global markets: The case of The European Union Countries,2014). This 4
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method is mainly used in international economics to calculate relative advantages for a certain product. In this research, it has computed the dairy products' share and measures specialisation of a nation, by dividing share of same in global exports(Ivanov and et. al., 2016). It states that if RCA is greater than one then such country is more specialised for a given dairy product in terms of exports, otherwise not. Anne and et. al. (2013) have demonstrated through their article to identify where dairy industry need to innovate, for reducing GHG emissions in supply chain in order to achieve high benefits (Dairy farm greenhouse gas impacts: A parsimonious model for a farmer's decision support tool,2013). To conduct this investigation parsimonious simplified model has been used. It helps in identifying the key parameters of influence within dairy industry that contributes to increase carbon footprint(Dani, 2015). Yang, Kevin and Kong (2019) has used Poisson distribution method for studying the determinants of adoption of different voluntary milk safety measures by farmers and other suppliers of dairy industry (Factors affecting the adoption of on-farm milk safety measures in Northern China-An examination from the perspective of farm size and production type,2019). Here, empirical result has indicated that adoption is affected in positive manner by farm size (Prakash and et. al., 2017). The article given by Hisham, El-Osta and Mitchell state the importance of technology in increasing efficiency of dairy supply chain (Technology Adoption and Its Impact on Production Performance of Dairy Operations,2000). To perform the investigation of this topic, these researchers have estimated a deterministic parametric frontier, including Cobb-Douglas method for interpreting the estimates(Tostivint and et. al., 2017). Along with this, Wald F test is also used for examining whether dairy industries gain high return on investment or not. The article proposed by Zeki, Funda and Gulcin (2011) is based on fuzzy approach, with main aim is to identify the logistic requirement as well as supply chain management for dairy management (A fuzzy QFD approach to determine supply chain management strategies in the dairy industry,2011). For determining the best suitable logistics requirements, now dairy industriesareadoptingtheconceptofqualityfunctiondeploymentinordertoproduce innovation in their production and supply chain management(Palmieri, Forleo and Salimei, 2017). To analyse the concept of this approach, these researchers have used multi-objective 5
mathematical programming method. This method helps in optimising a range of problems simultaneously so that better decision can be taken. Sameh, Ramin and Jishnu (2014) have used MANOVA analysis method to investigate thestudy(SUSTAINABLEDISTRIBUTIONSYSTEMINFOODRETAILSECTOR-A SIMULATIONMODELLINGAPPROACH,2014).Thistechniqueisusedtoanalysethe outcomes obtained through Guru Simulation software at confidence interval of 95%.This article has provided a systematic method by which dairy industries can make decisions upon optimal number, location of distribution facilities, including optimal types of fleet for minimising the CO2 emission as well as transportation cost(Dubey, Gunasekaran and Ali, 2015). Here, maximum responsiveness aid to ascertain the optimal number of transportation asset required for meeting demand of customers through effective supply and distribution chain. Forreviewingthedevelopmentofsustainablemanufacturingprocesswithindairy industry, the researchers Sujit, Eztuah and Siti Nurmaya (2016) have used weighted performance system (Development of sustainable manufacturing performance evaluation expert system for small and medium enterprises, 2016). For avoiding the rule explosion, the theory is proposed use of two inputs as well as three membership functions within each fuzzy system at development stage. Here, weighted performance of dairy industry with respect to measure is taken as input within fuzzy systems(Kirilova and Vaklieva-Bancheva, 2017). Along with this, weighted performance values as well as importance weights of each measures are mostly determined in terms of performance ratings and weights of each corresponding indicators. Limitations: These current papers have covered some limitations that researchers must recognize because there are various mathematical formulae are used for investigating the studies on dairy supply chain. In some cases of above mentioned articles, it has been recognised from view points ofSharma, Chandana and Bhardwaj (2015),that numerous different approaches are used in articles that need expert mind to interpret the result. It has also noticed here, that any minute errorinapplyingmathematicalmodelondatalikelinearprograming,multi-objective programming methods would obtain wrong answers(Mor and et. al., 2015). This may impact negatively on entire outcomes of result. Furthermore, research studies also need to be conducted forarangeofvariableconstraintswithinsupplychain.Itincludesintegration,supplier 6
management, collaboration, quality management, supply chain trust and more, for benchmarking the best DSCM practices. Summary of Findings It has been summarised from this assignment by reviewing various articles that Supply chain management refers to a plan that helps in controlling the material as well as information flow amongsuppliers,distributors,facilities,warehousesandcustomers.Themainbehind implementation of SCM within agriculture and dairy industry is to minimize the cost, maximize customer services and increase flexibility within flow of supply dairy products or services. Here, supply chain of a business process also comprises with major five main activities that are- purchase of raw materials and goods from suppliers, transportation of dairy products from suppliers to end customers, production of the dame at facilities, transportation of such items from facilitates to ware houses then to end customers. In this present assignment, through analysing various articles a supply chain model is developed by implementation of various approaches like fuzzy system for a dairy industry, mainly in Australia. This supply chain of dairy industry includes four major echelons viz. raw milk suppliers, plant, warehouse and customers. For increasing effectiveness of system, dairy industries now concern more on adopting fuzzy system that mainly emphasis on production and distribution activities. It develops a view for finding out purchase plan of raw materials like milk and production plan of product mix as well as transportation plan of the products. Through this process, sustainability of SC can be gained within dairy industries. 7
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REFERENCES Books and Journals Prakash, S.and et. al., 2017. Risk analysis and mitigation for perishable food supply chain: a case of dairy industry.Benchmarking: An International Journal. 24(1). pp.2-23. Tostivint, C. and et. al., 2017. Measuring food waste in a dairy supply chain in Pakistan.Journal of cleaner production. 145. pp.221-231. Palmieri, N., Forleo, M. B. and Salimei, E., 2017. Environmental impacts of a dairy cheese chain including whey feeding: an Italian case study.Journal of Cleaner Production. 140. pp.881-889. Dubey, R., Gunasekaran, A. and Ali, S. S., 2015. Exploring the relationship between leadership, operationalpractices,institutionalpressuresandenvironmentalperformance:A framework for green supply chain.International Journal of Production Economics. 160. pp.120-132. Kirilova, E. G. and Vaklieva-Bancheva, N. G., 2017. Environmentally friendly management of dairysupplychainfordesigningagreenproducts'portfolio.Journalofcleaner production. 167. pp.493-504. Mor, R. S. and et. al., 2015. Technological implications of supply chain practices in agri-food sector-a review.International Journal of Supply and Operations Management. 2(2). p.720. Behzadi, G. and et. al., 2017. Robust and resilient strategies for managing supply disruptions in an agribusiness supply chain.International Journal of Production Economics. 191. pp.207-220. Ivanov, D. and et. al., 2016. Dynamic recovery policies for time-critical supply chains under conditions of ripple effect.International Journal of Production Research. 54(23). pp.7245-7258. Dani, S., 2015.Food supply chain management and logistics: From farm to fork. Kogan Page Publishers. Sharma, V. K., Chandana, P. and Bhardwaj, A., 2015. Critical factors analysis and its ranking for implementationofGSCMinIndiandairyindustry.JournalofManufacturing Technology Management. 26(6). pp.911-922. Online InvestmentandTheAustralianDairyIndustry.2019.[Online]AvailableThrough: <https://www.dairyaustralia.com.au/about-dairy-australia/about-the-industry/ investment-and-the-australian-dairy-industry>. SupplyChainManagementinDairyIndustries.2009.[Online]Available Through:<https://www.researchgate.net/publication/44260057_Supply_Chain_Manage ment_in_a_Dairy_Industry_-_A_Case_Study>. Dairy Supply Chain Management and Critical an Investigation on Dairy Informal Channel PartnersinPakistan.2014.[Online]Available Through:<https://www.researchgate.net/publication/271515088_Dairy_Supply_Chain_ Management_and_Critical_an_Investigations_on_Dairy_Informal_Channel_Partners_in _Pakistan>. Measuring Supply Chain Coordination in Milk and Dairy Industries: A Confirmatory Factor Model.2015.[Online]AvailableThrough:<https://www.omicsonline.org/open- access/measuring-supply-chain-coordination-in-milk-and-dairy-industries-a- confirmatory-factor-model-2162-6359-1000244.php?aid=52368>. 8
Dynamic diary facility location and supply chain planning under traffic congestion and demand uncertainty:AcasestudyofTehran.2013.[Online]Available Through:<https://www.sciencedirect.com/science/article/pii/S0307904X13002333>. Sustainability distribution system design: a two-phase DoE-guided meta-heuristic solution approach for a three-echelon bi-objective AHP-integrated location-routine model. 2014.[Online]AvailableThrough:<https://link.springer.com/article/10.1007/s10479- 018-2887-y>. Export competitiveness of dairy products on global markets: The case of The European Union Countries.2014.[Online]AvailableThrough: <https://www.sciencedirect.com/science/article/pii/S0022030214005025>. Dairy farm greenhouse gas impacts: A parsimonious model for a farmer's decision support tool. 2013.[Online]Available Through:<https://www.sciencedirect.com/science/article/pii/S0958694612001999>. Factorsaffectingtheadoptionofon-farmmilksafetymeasuresinNorthernChina-An examination from the perspective of farm size and production type.2019. [Online] AvailableThrough: <https://www.sciencedirect.com/science/article/pii/S2095311919625670>. Technology Adoption and Its Impact on Production Performance of Dairy Operations.2000. [Online]AvailableThrough:< https://www.researchgate.net/publication/43289418_Technology_Adoption_and_Its_Im pact_on_Production_Performance_of_Dairy_Operations>. A fuzzy QFD approach to determine supply chain management strategies in the dairy industry. 2011. [Online] Available Through:<file:///C:/Users/user/Downloads/s10845-012-0639- 4.pdf>. SUSTAINABLEDISTRIBUTIONSYSTEMINFOODRETAILSECTOR-ASIMULATION MODELLINGAPPROACH.2014[Online]AvailableThrough:<http://www.msc- les.org/proceedings/foodops/2017/FOODOPS2017_45.pdf>. Development of sustainable manufacturing performance evaluation expert system for small and mediumenterprises.2016.[Online]AvailableThrough: <https://www.sciencedirect.com/science/article/pii/S2212827116001578>. 9