Advanced Methods for Decision Support for Sustainability - Research Paper Example

Decision Support for Sustainability By + Decision Support for Sustainability The world is faced with the problem of pollution. Pollution is mainly attributed to poor disposal of waste products. Products like polythene bags are not bio degradable. They, therefore, lie around for years, resulting in wide spread pollution. To prevent this, the populace can adopt green supply chain management where used packaging and unused products are taken back to the manufacturers’ for re-use (Kersten, 2000). A green sustainable supply chain is the process of making use of inputs that are environmentally friendly and using production processes whose by- products can be recycled or can improve the existing environment. The whole process produces outputs that can be used again when the products’ life cycle ends. This therefore creates a sustainable supply chain. The benefit of such a system is that it helps reduce production costs in the long run while also helping the environment. The world economy continues to grow at an alarming rate, particularly in the developing nations. This increases the peoples spending power and ultimately their demand for products. Companies are coming up with ways by which their processes can be environmentally friendly. They are doing this by trying to cut down on their waste products. The decision making process for green supply chain implementation usually involves four steps: Identification of environmental costs Keenly analyze the process and identify opportunities that would result in cost savings and have minimal impact on the environment. Calculate the benefits to be gained from using the alternatives proposed. Decide which improvement solution to use, implement and monitor its effects. Use of a green sustainable supply chain helps the environment while at the same time helping us save on costs. One of the means of supply chain management in the manufacturing industry is by recycling products. Existing products can also be improved to be more efficient, the company can adapt to recycling unused products instead of letting them go to waste. This is beneficial to the company in many ways; it is portrayed to the public as a conservative company while saving on costs of acquiring raw materials. 2. Different alternative decisions can be evaluated for when the company is trying to select a green supply chain management. The options available were: resell, remanufacture, refurbish. The option must also be able to increase the company’s profitability. Considering these options we also investigate the factors that influence the choice of each one to the organization. We analyse these options in a decision-making process model, using the Analytical Hierarchical Process (AHP), to evaluate which alternative is the most relevant. The proposed AHP model enables top managers to assess the significant variables and the most suitable option. For this study the three alternatives are analysed: Resell Manufacture Refurbish Data Analysis method To select the most reliable option we use The Analytical Hierarchical Process (AHP) model. This is because it gives an easy framework for the decision-making process. It has the following advantages: The decisive factors can be broken down to manageable levels Gives the opportunity to discuss about divergences Enables to modify only one element/comparison of the model Obliges to think about the whole problem Gives an accurate measurement system Classifies, prioritises and synthesize complexity The software chosen to compute the model Is the Super decisions software. Analytical hierarchical process (AHP) The AHP model is a structured framework. It is a simplified model simulating a complex problem. This model is a multi-criteria decision-making process. It breaks down a complex issue into manageable factors in a hierarchic order: goal, objectives, criteria, eventually sub-criteria and alternatives (Respicio & Burstein, 2012). An interesting opportunity is the possible integration of both qualitative and quantitative data. Then it compares the factors pair by pair, by giving a numerical value to the relative importance of each factor. Eventually, it synthesises which factors are the most important and should be used to influence the results of the situation studied The proposed AHP model It considers the different variables affecting the green supply chain management goal of the organisation (Jain & Chee, 2010). This allows the evaluation of the different structures available to top managers while considering their goal and the options available to them: resell, remanufacture, refurbish. The suggested AHP model offers the opportunity to consider influencing variables regarding use of the three option (National Research Council, 2013). The factors for this model are hierarchically organised in three levels as follows: Level 1: Goal: To choose the best option for green supply chain management in the organisation Level 2: Objectives: cost, quality of the product, time, corporate social responsibility Level 3: Criteria: customer service, procedures, product standardisation, expertise, cost of stock, supplier relationship, local supplier experience, complexity of structure. Study of the pair-wise comparisons The model is built when the connections between nodes have been done. We then complete the comparisons so as to prioritise goal, objective, criteria and alternatives. Data obtained was converted to numerical values to come up with a suitable model. These values are the ones we use to make pair-wise comparisons using the preference scale below. GOAL: OBJECTIVES Green Energy: Objectives Cost Quality Time Cost 1 5 6 Quality 1/5 1 2 Time 1/6 ½ 1 OBJECTIVES: CRITERIA With respect to Cost: Criteria Procedures Product standardisation Expertise Cost of stocks Supplier relationship Local supplier experience Complexity of structure Procedures 1 1/9 1/5 1/4 1/7 1 3 Product st. 9 1 7 6 5 8 9 Expertise 5 1/7 1 1/3 1/4 4 3 Cost of sto. 4 1/6 3 1 1/5 4 6 Supplier rel. 7 1/5 4 5 1 4 7 Loc. sup. Exp. 1 1/8 1/4 1/4 1/4 1 2 Comp. Struc. 1/3 1/9 1/3 1/6 1/7 1/2 1 With respect to quality: Criteria Customer service Product standardisation Expertise Supplier relationship Local supplier experience Customer ser. 1 7 3 5 6 Product st. 1/7 1 1/6 ¼ ½ Expertise 1/3 6 1 4 5 Supplier rel. 1/5 4 1/4 1 3 Loc. sup. Exp. 1/6 2 1/5 1/3 1 With respect to time: Criteria Customer service Procedures Supplier relationship Local supplier experience Complexity of structure Customer ser. 1 1/4 2 2 1/6 Procedures 4 1 3 4 ¼ Supplier rel. ½ 1/3 1 2 1/5 Loc. Sup. Exp. ½ 1/4 1/2 1 1/7 Comp. Struc. 6 4 5 7 1 CRITERIA: CRITERIA In the AHP model, we can link factors at the same hierarchic level can be also linked. With respect to Customer Service: Criteria Expertise Product standardisation Expertise 1 8 Prod. Standard. 1/8 1 CRITERIA: ALTERNATIVES With respect to Customer Service: Alternatives Centralisation Mixed structure Decentralisation Centralisation 1 1/5 1/7 Mixed structure 5 1 1/3 Decentralisation 7 3 1 With respect to Expertise: Alternatives Centralisation Mixed structure Decentralisation Centralisation 1 4 7 Mixed structure 1/4 1 3 Decentralisation 1/7 1/3 1 With respect to Local Supplier Experience: Alternatives Centralisation Mixed structure Decentralisation Centralisation 1 1/5 1/9 Mixed structure 5 1 1/4 Decentralisation 9 4 1 With respect to Management of Stocks: Alternatives Centralisation Mixed structure Decentralisation Centralisation 1 3 6 Mixed structure 1/3 1 3 Decentralisation 1/6 1/3 1 With respect to Procedures: Alternatives Centralisation Mixed structure Decentralisation Centralisation 1 3 7 Mixed structure 1/3 1 5 Decentralisation 1/7 1/5 1 With respect to Product standardisation: Alternatives Centralisation Mixed structure Decentralisation Centralisation 1 3 9 Mixed structure 1/3 1 6 Decentralisation 1/9 1/6 1 With respect to Supplier Relationship: Alternatives Centralisation Mixed structure Decentralisation Centralisation 1 3 6 Mixed structure 1/3 1 4 Decentralisation 1/6 1/4 1 With respect to Complexity of structure: Alternatives Centralisation Mixed structure Decentralisation Centralisation 1 3 1/5 Mixed structure 1/3 1 1/7 Decentralisation 5 7 1 Results of the model The software uses all separate comparisons in order to determine which of the alternatives will best suit the goal. According to the model, the alternatives with respect to the goal is sorted in the sequence (Centralisation > Mixed structure > Decentralisation). The priorities are 0.5616, 0.2462 and 0.1922 respectively. The organisation can chose the option that best helps them choose their best alternative for green supply chain management. Conclusion The aim of this paper was to determine what objectives and criteria are considered when the choice of a green supply chain management system that was more efficient for the company. Data collected enables to identify the relative importance of factors with respect to each other’s. The results indicate the priority the organisations managers give to objectives and criteria. The main contribution of this paper is the connection of the available alternatives and the goal of the company through the computation in an AHP model which makes easier for managers to appreciate the model to take the best decision corresponding to their company. It helps managers to assist them in their structuring decision (Kropp & Scheffran, 2006). 3. For the multi criteria decision model I used is the analytical hierarchy process. This method is used to obtain ratio scales from paired comparisons. This input is obtained from the actual measurements such as weight or price, weight. It can also be obtained from subjective personal opinion such as individual preference and feelings of satisfaction (Dolk, 2012). AHP allows for some small inconsistency in the judgments because as human we are not always consistent. The ratio scales in use are derived from the main Eigen vectors while the consistency index is obtained as a result of the principal Eigen value. Pair-wise Comparison In this scenario we have to choose between two options of suppliers. In this scenario, let us assume we have Supplier A and supplier B. we ask which supplier we prefer than the other, we also state how much we prefer it in comparison to the other supplier. We therefore come up with a relative scale to measure how much we prefer the supplier on the left (A) in comparison to the supplier on the right (B). If we prefer supplier A to supplier B, we put a mark between number 1 and 9 on the left side, on the other hand if we prefer supplier B we simply put a mark but on the left side. In the case above, suppose I favor supplier B, I will place a mark as below If there are three supplier options, then the pairwise comparison will follow the following series: Supplier A, B and C, we have to select a favorable option between these 3 options.     This shows that the number of comparisons in any given situation is a combination of the number of things to be compared. In our case, we have 3 options (Supplier A, supplier B and Supplier C), we have 3 comparisons. The table shows the number of comparisons available. Number of things 1 2 3 4 5 6 7 number of comparisons 0 1 3 6 10 15 21 Even though the scaling is not necessary 1 to 9, in this scenario it involves use of qualitative data: ranking, subjective opinions and preference. We therefore use a scale from 1 to 9. 4. There are several criteria which are influenced by the alternative solutions: Expertise Cost of stocks Supplier relationship Local supplier experience Price is a major factor in making decisions. It influences various factors and the demand of the products. Any changes should be carefully researched before being put into action. Any changes in the price should be carefully monitored as it has a lot of effects in regards to the organization (Jakeman, 2008). Bibliography Kersten, G. 2000, Decision support systems for sustainable development: a resource book of methods and applications, Boston, Kluwer Academic. Respicio, A., & Burstein, F. 2012, Fusing decision support systems into the fabric of the context, Amsterdam, IOS Press. Leeuwen, J. V., & Timmermans, H. J. P. 2006, Innovations in design & decision support systems in architecture and urban planning, Dordrecht, Springer. International Conference on Changeable, Agile, Reconfigurable & Virtual Production & Zaeh, M. F. (2013), Enabling manufacturing competitiveness and economic sustainability: proceedings of the 5th International Conference on Changeable, Agile, Reconfigurable and Virtual Production” Munich, Germany Dolk, D. 2012, Modeling for decision support in network-based services: The application of quantitative modeling to service science, Heidelberg, Springer. Jakeman, A. J. 2008, Environmental modeling, software and decision support state of the art and new perspectives, Amsterdam, Elsevier. National Research Council (U.S), 2013, Sustainability for the nation: resource connections and governance linkages. Gupta, J. N. D., Forgionne, G. A., & Mora, M. 2006, Intelligent decision-making support systems foundations, applications, and challenges, London, Springer. Jain. L. C., & Chee, P. L 2010, Handbook on decision making, Vol 1, Vol 1, Berlin, Springer-Verlag. Kropp, J. P., & Scheffran, J 2006, Advanced methods for decision making and risk management in sustainability science, New York, Nova Science Publishers. Read More