Digital Model for Distance Education Management in Thai Supply Chain

The purposes of this study were to study and to evaluate digital model for distance education management in Thai supply chain . The samples are ten experts in the field of digital ,supply chain and curriculum . The data is analysed by means and standardized deviations. The paper result shows that a simulation consists of seven elements namely main elements, Suppliers, Manufacturer, ,finished product ,Customers, satisfaction and Return The assessment of a simulation using Black-Box testing. The paper findings revealed that a simulation is appropriate at the high which mean that Digital model for distance education management in Thai supply chain could be applied in support the task

Modelling an End to End Supply Chain system Using Simulation

Within the current uncertain environment industries are predominantly faced with various challenges resulting in greater need for skilled management and adequate technique as well as tools to manage Supply Chains (SC) efficiently. Derived from this observation is the need to develop a generic/reusable modelling framework that would allow firms to analyse their operational performance over time (Mackulak and Lawrence 1998, Beamon and Chen 2001, Petrovic 2001, Lau et al. 2008, Khilwani et al. 2011, Cigollini et al. 2014). However for this to be effectively managed the simulation modelling efforts should be directed towards identifying the scope of the SC and the key processes performed between players. Purpose: The research attempts to analyse trends in the field of supply chain modelling using simulation and provide directions for future research by reviewing existing Operations Research/Operations Management (OR/OM) literature. Structural and operational complexities as well as different business processes within various industries are often limiting factors during modelling efforts. Successively, this calls for the end to end (E2E) SC modelling framework where the generic processes, related policies and techniques could be captured and supported by the powerful capabilities of simulation. Research Approach: Following Mitroff’s (1974) scientific inquiry model and Sargent (2011) this research will adopt simulation methodology and focus on systematic literature review in order to establish generic OR processes and differentiate them from those which are specific to certain industries. The aim of the research is provide a clear and informed overview of the existing literature in the area of supply chain simulation. Therefore through a profound examination of the selected studies a conceptual model will be design based on the selection of the most commonly used SC Processes and simulation techniques used within those processes. The description of individual elements that make up SC processes (Hermann and Pundoor 2006) will be defined using building blocks, which are also known as Process Categories. Findings and Originality: This paper presents an E2E SC simulation conceptual model realised through means of systematic literature review. Practitioners have adopted the term E2E SC while this is not extensively featured within academic literature. The existing SC studies lack generality in regards to capturing the entire SC within one methodological framework, which this study aims to address. Research Impact: A systematic review of the supply chain and simulation literature takes an integrated and holistic assessment of an E2E SC, from market-demand scenarios through order management and planning processes, and on to manufacturing and physical distribution. Thus by providing significant advances in understanding of the theory, methods used and applicability of supply chain simulation, this paper will further develop a body of knowledge within this subject area. Practical Impact: The paper will empower practitioners’ knowledge and understanding of the supply chain processes characteristics that can be modelled using simulation. Moreover it will facilitate a selection of specific data required for the simulation in accordance to the individual needs of the industry

Supply Chain Simulation: Experimentation without Pain

Bridging the gap between theory and practice has always been a key issue for students and graduates. The magnitude and scope of subject areas that students at third level institutions have to learn in theory means that visualising them without any practical experience can be very difficult. Understanding the complexity of supply chain networks and how to manage them create a considerable level of difficulty for students and professionals. Theories and applications included in supply chain management subjects are the key to empathise the real challenges. Nevertheless, teaching these theories needs substantial efforts and new innovative approaches to deliver the concepts and assure successful transfer of the learning outcomes. To complicate things more, the levels of uncertainty and risk within an entire supply chain are still not fully recognised or understood even by industry professionals. Research studies showed the need for more transparency and collaborative approaches to take place among supply chain partners in order to achieve more sustainable operations. Making sure students comprehend the scale of activities and stochastic nature of a supply chain before they carry on their industrial careers is therefore crucial. Using computer simulation integrated with structured modelling techniques, a detailed, animated and generic supply chain simulation-based learning framework can be developed to incorporate many areas of learning undertaken by students in relation to the supply chain management. Experimenting on the simulation models allow the students to examine quantitatively the impact of changing critical factors (e.g. inventory level, demand, suppliers’ lead time) on the performance of supply chain. This paper demonstrates the impact of using interactive simulation technologies in teaching third level education with special reference to supply chain management and discusses the benefits of learning through such a level of immersion

A new method for improving decisionmaking in the supply chain risk management process. Supporting the learning project management organisation by applying advanced business modelling simulation techniques

The rise of importance of supply chain risk management both, in the scientific and business world, is essentially the result of solving an economical paradox. How can an organisation continuously increase its growth in revenue and increase its profit in a world in which the flow of goods and financial means is reaching a never seen complexity? This provides both, a threat and an opportunity to those organisations. The key is how to identify, manage and prevent operational risk. The following thesis aims at providing a new approach on the subject targeting project management organisations by bringing together three different disciplines, supply chain risk management, business modelling and simulation and the concept of the learning organisation. The research is based on a literature review of the identified fields followed by an empirical assessment aiming to understand the main risks threatening a project’s supply chain, the current state of supply chain risk management and application of business modelling and simulation in practice as well as gaining an understanding how the principles of the learning organisation are lived within a project management organisation. Furthermore, the thesis is providing an exemplary approach on how a simulation model could be built assessing identified supply chain risks. The literature review, as well as the empirical assessment, conducted via the combination of questionnaire and interview, is clearly showing that, while the topic of supply chain risk management has become a constant part of the scientific discussion the real-world application, especially in the context of business modelling and simulation applying the principles of the learning organisation is still executed hesitantly. Furthermore, the thesis provides an example by which current state of the art simulation software is used to allow supply chain professionals to conduct each step of the supply chain risk management process in a virtual environment. The relevancy of the work is founded in the combination of the three fields offering a new approach to complex project management organisations in further developing their supply chain risk management capabilities

The impact of dual sourcing on food supply chain networks: the case of Egyptian strawberries

Supply chain management for fresh produce differs significantly from that of other products. Similarly to other products, fresh produce quality plays a key role in consumer selection behavior. The key difference consists in the fact that, for fresh produce, quality varies over time and it is dramatically affected by storage conditions. Maintaining product quality along the distribution chain is therefore of utmost importance in these chains. Dual sourcing is a common practice adopted in supply chain management for enhancing sourcing flexibility and reducing transportation costs. This work investigates the impact of dual sourcing strategies on quality of fresh fruit traded in international food supply chains. By means of a discrete-event simulation model we investigate dual sourcing in the context of a prototype supply chain that mimics the structure and the operating conditions of a real supply chain

A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain

[EN] The challenges of global economies foster supply chains to have to increase their processes of collaboration and dependence between their nodes, generating an increase in the level of vulnerability to possible impacts and interruptions in their operations that may affect their sustainability. This has developed an emerging area of interest in supply chain management, considering resilience management as a strategic capability of companies, and causing an increase in this area of research. Additionally, supply chains should deal with the three dimensions of sustainability (economic, environmental, and social dimensions) by incorporating the three types of objectives in their strategy. Thus, there is a need to integrate both resilience and sustainability in supply chain management to increase competitiveness. In this paper, a systematic literature review is undertaken to analyze resilience management and its connection to increase supply chain sustainability. In the review, 232 articles published from 2000 to February 2020 in peer-reviewed journals in the Scopus and ScienceDirect databases are analyzed, classified, and synthesized. With the results, this paper develops a conceptual framework that integrates the fundamental elements for analyzing, measuring, and managing resilience to increase sustainability in the supply chain. Finally, conclusions, limitations, and future research lines are exposed.This study was supported by the Valencian Government in Spain (Project AEST/2019/019).Zavala-Alcívar, A.; Verdecho Sáez, MJ.; Alfaro Saiz, JJ. (2020). A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain. Sustainability. 12(16):1-38. https://doi.org/10.3390/su12166300S1381216Roberta Pereira, C., Christopher, M., & Lago Da Silva, A. (2014). Achieving supply chain resilience: the role of procurement. Supply Chain Management: An International Journal, 19(5/6), 626-642. doi:10.1108/scm-09-2013-0346Pettit, T. 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Supply Chain Management: An International Journal, 22(1), 16-39. doi:10.1108/scm-06-2016-0197Umar, M., Wilson, M., & Heyl, J. (2017). Food Network Resilience Against Natural Disasters: A Conceptual Framework. SAGE Open, 7(3), 215824401771757. doi:10.1177/2158244017717570Stone, J., & Rahimifard, S. (2018). Resilience in agri-food supply chains: a critical analysis of the literature and synthesis of a novel framework. Supply Chain Management: An International Journal, 23(3), 207-238. doi:10.1108/scm-06-2017-0201Colicchia, C., Creazza, A., Noè, C., & Strozzi, F. (2019). Information sharing in supply chains: a review of risks and opportunities using the systematic literature network analysis (SLNA). Supply Chain Management: An International Journal, 24(1), 5-21. doi:10.1108/scm-01-2018-0003Annarelli, A., & Nonino, F. (2016). Strategic and operational management of organizational resilience: Current state of research and future directions. 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Managing Disruption Risks in Supply Chains. Production and Operations Management, 14(1), 53-68. doi:10.1111/j.1937-5956.2005.tb00009.xChristopher, M., & Peck, H. (2004). Building the Resilient Supply Chain. The International Journal of Logistics Management, 15(2), 1-14. doi:10.1108/09574090410700275Wu, T., Huang, S., Blackhurst, J., Zhang, X., & Wang, S. (2013). Supply Chain Risk Management: An Agent-Based Simulation to Study the Impact of Retail Stockouts. IEEE Transactions on Engineering Management, 60(4), 676-686. doi:10.1109/tem.2012.2190986Fang, H., & Xiao, R. (2013). Resilient closed-loop supply chain network design based on patent protection. International Journal of Computer Applications in Technology, 48(1), 49. doi:10.1504/ijcat.2013.055566Gong, J., Mitchell, J. E., Krishnamurthy, A., & Wallace, W. A. (2014). An interdependent layered network model for a resilient supply chain. Omega, 46, 104-116. doi:10.1016/j.omega.2013.08.002Mari, S., Lee, Y., & Memon, M. (2014). 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Measuring the Resilience of Supply Chain Systems Using a Survival Model. IEEE Systems Journal, 9(2), 377-381. doi:10.1109/jsyst.2014.2339552LOH, H. S., & THAI, V. V. (2015). Cost Consequences of a Port-Related Supply Chain Disruption. The Asian Journal of Shipping and Logistics, 31(3), 319-340. doi:10.1016/j.ajsl.2015.09.001Torabi, S. A., Baghersad, M., & Mansouri, S. A. (2015). Resilient supplier selection and order allocation under operational and disruption risks. Transportation Research Part E: Logistics and Transportation Review, 79, 22-48. doi:10.1016/j.tre.2015.03.005Cardoso, S. R., Paula Barbosa-Póvoa, A., Relvas, S., & Novais, A. Q. (2015). Resilience metrics in the assessment of complex supply-chains performance operating under demand uncertainty. Omega, 56, 53-73. doi:10.1016/j.omega.2015.03.008Salehi Sadghiani, N., Torabi, S. A., & Sahebjamnia, N. (2015). Retail supply chain network design under operational and disruption risks. 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Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers. Transportation Research Part E: Logistics and Transportation Review, 101, 176-200. doi:10.1016/j.tre.2017.02.004Kırılmaz, O., & Erol, S. (2017). A proactive approach to supply chain risk management: Shifting orders among suppliers to mitigate the supply side risks. Journal of Purchasing and Supply Management, 23(1), 54-65. doi:10.1016/j.pursup.2016.04.002Li, H., Pedrielli, G., Lee, L. H., & Chew, E. P. (2016). Enhancement of supply chain resilience through inter-echelon information sharing. Flexible Services and Manufacturing Journal, 29(2), 260-285. doi:10.1007/s10696-016-9249-3Otto, C., Willner, S. N., Wenz, L., Frieler, K., & Levermann, A. (2017). Modeling loss-propagation in the global supply network: The dynamic agent-based model acclimate. 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What is the challenge in creating a process-based digital twin?

Supply chain management (SCM) has become increasingly relevant for organisations. Firms that have a strategy to optimise their performance in the supply chain (SC) are more prone to be successful. Most companies use data analytics for this purpose, and in order to continuously look for competitive advantage. One of the most important issues that organisations must deal with in SCM is inventory control. This thesis proposes the digital twin technology to solve this problem, by means of predictions made from historical data. This thesis conducted a series of simulation experiments to test the capacity of a digital twin simulation to be a better decision-maker than a classical model. The classical model chosen as a baseline was the economic order quantity (EOQ) model. The digital twin was designed with a reinforcement learning (RL) application based on a neural network (NN) and trained several times. Three different trials challenging the limitations of the baseline model were carried out. In order to overcome the EOQ model limitations, two delivery reliability indicators were created, thus allowing to generate different scenarios. Results showed that the inventory level and costs are affected in a different way depending on which reliability parameter is modified. The digital twin did not beat the EOQ model in any of the trials but an approach to it was achieved. Although the same number of iteration trainings were run in all the trials, the learning level reached was not the same. In two of the three trials, 30% of the experiments led to the same results as the classical model, whereas in the last one only 10% of the experiments reached them. This study is only a first approach to a big issue, the SCM. The digital twin can consider other external factors that classical models cannot. However, lots of resources that were not available in this project would be needed in order to properly model and simulate a real-world situation supply chain management, digital twin, neural network, reinforcement learningOutgoin

Evolution of Supply Chain Collaboration: Implications for the Role of Knowledge

Increasingly, research across many disciplines has recognized the shortcomings of the traditional “integration prescription” for inter-organizational knowledge management. This research conducts several simulation experiments to study the effects of different rates of product change, different demand environments, and different economies of scale on the level of integration between firms at different levels in the supply chain. The underlying paradigm shifts from a static, steady state view to a dynamic, complex adaptive systems and knowledge-based view of supply chain networks. Several research propositions are presented that use the role of knowledge in the supply chain to provide predictive power for how supply chain collaborations or integration should evolve. Suggestions and implications are suggested for managerial and research purposes