Information Sharing for improved Supply Chain Collaboration – Simulation Analysis

Collaboration among consumer good’s manufacturer and retailers is vital in order to elevate their performance. Such mutual cooperation’s, focusing beyond day to day business and transforming from a contract-based relationship to a value-based relationship is well received in the industries. Further coupling of information sharing with the collaboration is valued as an effective forward step. The advent of technologies naturally supports information sharing across the supply chain. Satisfying consumers demand is the main goal of any supply chain, so studying supply chain behaviour with demand as a shared information, makes it more beneficial. This thesis analyses demand information sharing in a two-stage supply chain. Three different collaboration scenarios (None, Partial and Full) are simulated using Discrete Event Simulation and their impact on supply chain costs analyzed. Arena software is used to simulate the inventory control scenarios. The test simulation results show that the total system costs decrease with the increase in the level of information sharing. There is 7% cost improvement when the information is partially shared and 43% improvement when the information is fully shared in comparison with the no information sharing scenario. The proposed work can assist decision makers in design and planning of information sharing scenarios between various supply chain partners to gain competitive advantage

The value of sharing planning information in supply chains

Purpose - The development of information technology has made it possible for companies to get access to information about their customers’ future demand. This paper outlines various approaches to utilize this kind of visibility when managing inventories of end products on an operative level. The purpose is to explain the consequences, for capital tied up in inventory, of sharing four different types of planning information (point-of-sales data, customer forecasts, stock-on-hand data, planned orders) when using re-order point (R,Q) inventory control methods in a distribution network. Design/methodology/approach - A simulation study based on randomly generated demand data with a compound Poisson type of distribution is conducted. Findings - The results show that the value of information sharing in operative inventory control varies widely depending on the type of information shared, and depending on whether the demand is stationary or not. Significantly higher value is achieved if the most appropriate types of information sharing are used, while other types of information sharing rather contribute to decreased value. Sharing stock-on-hand information is valuable with stationary demand. Customer forecast and planned order information are valuable with non-stationary demand. The value of information sharing increases when having fewer customers, and when the order quantities are large. Sharing point-of-sales data is not valuable, regardless of the demand type. Research limitations/implications - The use of simulation methodology is a limitation, because the study has to be limited to a specific model design, and because it is not based on primary empirical data. The study is especially limited to dyadic relationships in supply chains, and to distribution networks with a rather limited number of customers. Practical implications - Guidance is given about what type of information should be appropriate to share when different types of demand patterns and distribution networks, and how order batch sizes and lead times affect the value of information sharing when using re-order point (R,Q) methods. Originality/value - Very limited research providing specific assessments of potential inventory control consequences when sharing planning information in various contexts has been found in the literature. The findings and conclusions should also be valuable for the supply chain integration and collaborative planning literature

Optimal decisions and comparison of VMI and CPFR under price-sensitive uncertain demand

Purpose: The purpose of this study is to compare the performance of two advanced supply chain coordination mechanisms, Vendor Managed Inventory (VMI) and Collaborative Planning Forecasting and Replenishment (CPFR), under a price-sensitive uncertain demand environment, and to make the optimal decisions on retail price and order quantity for both mechanisms. Design/ methodology/ approach: Analytical models are first applied to formulate a profit maximization problem; furthermore, by applying simulation optimization solution procedures, the optimal decisions and performance comparisons are accomplished. Findings: The results of the case study supported the widely held view that more advanced coordination mechanisms yield greater supply chain profit than less advanced ones. Information sharing does not only increase the supply chain profit, but also is required for the coordination mechanisms to achieve improved performance. Research limitations/implications: This study considers a single vendor and a single retailer in order to simplify the supply chain structure for modeling. Practical implications: Knowledge obtained from this study about the conditions appropriate for each specific coordination mechanism and the exact functions of coordination programs is critical to managerial decisions for industry practitioners who may apply the coordination mechanisms considered. Originality/value: This study includes the production cost in Economic Order Quantity (EOQ) equations and combines it with price-sensitive demand under stochastic settings while comparing VMI and CPFR supply chain mechanisms and maximizing the total profit. Although many studies have worked on information sharing within the supply chain, determining the performance measures when the demand is price-sensitive and stochastic was not reported by researchers in the past literature.Peer Reviewe

Logistics horizontal collaboration:an agent-based simulation approach to model collaboration dynamics

Underutilized capacity, long shipping lead time, high cost and lack of sufficient scale are examples of logistics inefficiencies that have troubled many supply chain operations. Logistics horizontal collaboration (LHC) is believed to be an innovative approach to tackle the increasing logistics challenges. This kind of collaborative logistics is quickly gaining momentum in practice but relevant contributions in literature are scarce. So far it remains unclear how LHC could be structured and operated given the limited understanding of the various characteristics and forms of LHC between companies. Furthermore, the explicit impact of LHC on the participating partners, as well as on the supply chain system is understudied. Very few studies have explored the process of collaboration and how it links to performance behaviours. Case studies and Agent-Based Simulation are employed in this thesis to study the research gaps identified above. Case studies are initially conducted to examine the key elements which can support the design of LHC, and to make a classification of models for collaboration. These are followed by Agent-Based Simulation to model a typical collaboration process and work out what benefits would emerge if participating in horizontal collaboration and how the collaboration can produce the impacts on the supply chain operations for individuals and the system as a whole. The case studies suggest that “collaboration structures”, “collaboration objectives”, “collaboration intensity”, and “collaboration modes” are the four key elements critical to the design of a LHC project. Each element represents an important aspect of the collaboration and exhibits different characteristics and forms. Based on these key elements, several typologies are derived which together provide a comprehensive view to explain the different types of LHC in practice. The simulation modelling demonstrates that LHC can significantly benefit the logistics efficiency in terms of capacity utilization and customer service in the sense of order fill-rate, and such beneficial effects are consistently observed in different supply chain environments. In particular, LHC can produce better logistics performance in a relationship-based supply chain network where downstream customers can support upstream shippers with more stable and predictable demand. On the other hand, information sharing in the collaboration, for the most part, does not facilitate the higher collaboration gains for partners. Specifically, sharing either the demand or supply information in the horizontal collaboration is not helpful in increasing collaboration gains. Hence there is a difference for the value of information sharing in the context of horizontal collaboration as opposed to vertical collaboration, the latter of which is often justified as providing more beneficial gains. The research findings provide insights for practitioners and scholars about how to develop a type of collaboration project or study, as well as enabling a better understanding of the dynamic collaboration effects

Impact of vendor-managed inventory on supply chain performance

v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);}  Bu çalışmada, Tedarikçi Yönetimli Envanter (VMI) yaklaşımının tedarik zinciri performansına sağladığı faydaları incelemek için bir benzetim modeli kurgulanmıştır. Benzetim modelinde kapasite sınırı olan bir üretici, bir distribütör, bir toptancı ve bir perakendeciden oluşan dört kademeli bir tedarik zinciri yapısı dikkate alınmıştır. Durağan ve durağan olmayan talep yapılarının dikkate alındığı benzetim modelinde iki farklı yapıda tedarik zinciri canlandırılmıştır. İlk yapı, geleneksel anlayışla yönetilen (TSS) tedarik zinciri yapısıdır. TSS yaklaşımında, tedarik zinciri üyeleri arasında herhangi bir bilgi paylaşımı olmamakta ve birbirleriyle sadece siparişler vererek iletişim kurmaktadırlar. İkinci yapı ise, VMI yaklaşımının uygulandığı tedarik zinciri yapısıdır. VMI yaklaşımı çerçevesinde, perakendecideki envanterin yönetiminden toptancı sorumludur. Benzetim modeli sonucunda elde edilen sonuçlar, VMI yaklaşımının, tedarik zinciri maliyetini önemli ölçüde düşürürken, müşteri gereksinimlerini daha yüksek oranda karşıladığını göstermektedir. Ayrıca elde edilen bulgular; üretim kapasitesinin ve müşteri talebinde gözlenen belirsizliklerin VMI yaklaşımından elde edilen fayda üzerinde anlamlı etkileri olduğunu göstermektedir. İlk olarak üretim kapasitesi dikkate alındığında, üretim kapasitesinin çok sınırlı olmasının VMI yaklaşımlarından elde edilen faydayı düşürdüğü görülmektedir. Müşteri talebinde gözlenen belirsizlikler dikkate alındığında ise, müşteri talebindeki belirsizliğin artmasının VMI yaklaşımından elde edilen faydayı önemli düzeylerde azalttığı görülmektedir. Sonuç olarak, VMI yaklaşımının üretim kapasitesinin yüksek olduğu ve müşteri talebinde gözlenen belirsizliklerin düşük olduğu durumlarda daha faydalı olduğu görülmektedir.    <!--[if !vml]--><!--[endif]-->Anahtar Kelimeler: Tedarikçi yönetimli envanter, bilgi paylaşımı, tedarik zinciri yönetimi, benzetim modeli.In this study, a comprehensive simulation model is built to explore the benefits of a supply chain initiative called ?vendor-managed inventory (VMI)? where the vendors are authorized to manage inventories at retail locations. Under VMI, retailer shares demand information to the vendor who should then make stock level decisions for its own organization and the retailer. In this article, specifically, we are interested in finding answers to the following questions: Under what conditions will VMI more beneficial? How will lead times, demand uncertainty, and manufacturing capacity affect the benefits gained from VMI? From this investigation, we will better understand the required conditions for more successful VMI applications. For this purpose, we consider a four-echelon supply chain consisting of a capacitated manufacturer, a distributor, a wholesaler, and a retailer. The retailer realizes customer demands from gamma distribution. Stationary and non-stationary customer demand structures considered to explore the impacts of different levels of demand uncertainty on the benefits obtained from VMI. In order to evaluate VMI benefits, two stylized supply chain structures are considered. The first situation is a traditional model (TSS) where there is no information sharing and all members in the supply chain independently plan and operate the supply chain. The second situation is a supply chain model with vendor-managed inventory (VMI) where the wholesaler (as being the vendor for the retailer for the given supply chain) takes the full responsibility of managing the retailer?s inventory. Order-up to policy is used for ordering decisions for both systems. A full factorial design of experiment constructed to analyze the impacts of different factors on the benefits obtained from VMI. These factors are demand uncertainty, manufacturing capacity restrictions, and lead times. The levels of the each factor determined as follows: Three levels for the demand uncertainty; demand structure with no seasonal swings, moderate degree of seasonal swings, and high degree of seasonal swings. Manufacturing capacity restrictions measured by ?capacity ratio? which corresponds to the ratio of total capacity to total demand. The levels for the manufacturing capacity restrictions are capacity ratio of 1.10, 1.30, and 1.50. Two levels of lead-time; which is 1 and 4 periods Moreover, total cost for entire supply chain, and customer service level are the dependent variables considered as performance metrics in experimental design. Customer service level is the percentage of customer demand satisfied through the available inventory of the retailer. Since there is more than one dependent variable in the experimental design, MANOVA is conducted to analyze the experimental simulation output. The results of the experimental simulation output indicate that when compared to traditional supply chain, VMI decreases supply chain cost substantially. Compared to the traditional settings, the reduction in the total supply chain cost varies from 6.5% to 43.3% with an average around 17.4%. When the service level is considered, we see that in all cases VMI reaches higher levels of service levels. For example, customer service level increased from 94.4% to 95.9% on the average. These results lead us to conclude that VMI is always beneficial to the supply chain performance. Moreover, the results of the MANOVA indicate that manufacturer?s capacity restrictions and customer demand uncertainty have significant impacts on the benefits obtained from VMI. Firstly, when manufacturing capacity is considered, the findings indicate that as the available manufacturing capacity is higher, the benefits obtained from VMI are also higher. Secondly, when the demand uncertainty is considered, the results indicate that as the uncertainty in customer demand increases, the performance of supply chain with VMI decreases substantially. In conclusion, through comprehensive simulation experiment and subsequent analysis of the simulation outputs, we made the following important findings: VMI significantly improve the performance of the supply chain under all conditions. The benefits gained from VMI significantly influenced by the manufacturing capacity and demand uncertainty. Therefore, VMI is more beneficial under the conditions with is high level of manufacturing capacity and low degree of demand uncertainty. Keywords: Vendor-managed inventory, information sharing, supply chain management, simulatio

Logistics horizontal collaboration:an agent-based simulation approach to model collaboration dynamics

Underutilized capacity, long shipping lead time, high cost and lack of sufficient scale are examples of logistics inefficiencies that have troubled many supply chain operations. Logistics horizontal collaboration (LHC) is believed to be an innovative approach to tackle the increasing logistics challenges. This kind of collaborative logistics is quickly gaining momentum in practice but relevant contributions in literature are scarce. So far it remains unclear how LHC could be structured and operated given the limited understanding of the various characteristics and forms of LHC between companies. Furthermore, the explicit impact of LHC on the participating partners, as well as on the supply chain system is understudied. Very few studies have explored the process of collaboration and how it links to performance behaviours. Case studies and Agent-Based Simulation are employed in this thesis to study the research gaps identified above. Case studies are initially conducted to examine the key elements which can support the design of LHC, and to make a classification of models for collaboration. These are followed by Agent-Based Simulation to model a typical collaboration process and work out what benefits would emerge if participating in horizontal collaboration and how the collaboration can produce the impacts on the supply chain operations for individuals and the system as a whole. The case studies suggest that “collaboration structures”, “collaboration objectives”, “collaboration intensity”, and “collaboration modes” are the four key elements critical to the design of a LHC project. Each element represents an important aspect of the collaboration and exhibits different characteristics and forms. Based on these key elements, several typologies are derived which together provide a comprehensive view to explain the different types of LHC in practice. The simulation modelling demonstrates that LHC can significantly benefit the logistics efficiency in terms of capacity utilization and customer service in the sense of order fill-rate, and such beneficial effects are consistently observed in different supply chain environments. In particular, LHC can produce better logistics performance in a relationship-based supply chain network where downstream customers can support upstream shippers with more stable and predictable demand. On the other hand, information sharing in the collaboration, for the most part, does not facilitate the higher collaboration gains for partners. Specifically, sharing either the demand or supply information in the horizontal collaboration is not helpful in increasing collaboration gains. Hence there is a difference for the value of information sharing in the context of horizontal collaboration as opposed to vertical collaboration, the latter of which is often justified as providing more beneficial gains. The research findings provide insights for practitioners and scholars about how to develop a type of collaboration project or study, as well as enabling a better understanding of the dynamic collaboration effects

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

The impact of freight transport capacity limitations on supply chain dynamics

We investigate how capacity limitations in the transportation system affect the dynamic behaviour of supply chains. We are interested in the more recently defined, 'backlash' effect. Using a system dynamics simulation approach, we replicate the well-known Beer Game supply chain for different transport capacity management scenarios. The results indicate that transport capacity limitations negatively impact on inventory and backlog costs, although there is a positive impact on the 'backlash' effect. We show that it is possible for both backlog and inventory to simultaneous occur, a situation which does not arise with the uncapacitated scenario. A vertical collaborative approach to transport provision is able to overcome such a trade-off. © 2013 Taylor & Francis

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