Supply Chain Behavior Research Articles

Modeling and estimating continuous Improvised Explosive Device supply chain behavior

Over a given period of time, coalition forces can collect data on the number of Improvised Explosive Devices (IEDs) that are found or detonated. However, the number of IEDs emplaced and in construction, as well as the rates in which IEDs are moving throughout the supply chain, remains unknown. We show that using the data on IEDs detonated and found, we can mathematically estimate the behavior of the entire supply chain, thus providing estimates on previously unknown aspects of the IED supply chain. This provides useful information on the unobservable parts of the supply chain and offers better metrics for gauging the effectiveness of counter-IED efforts.

Simulation modeling framework for uncovering system behaviors in the biofuels supply chain network

A full realization of alternative energy such as biofuels depends on the existence of a viable supply chain (SC) network. An agent-based simulation approach is pursued to understand the dynamics of the biofuels SC network. The interests of three SC actors are represented: users, biorefineries, and farmers. Each actor type has a binary decision option: adoption or non-adoption of biofuels. This SC network model is characterized by distributed control, time asynchrony, and resource contention among actors, who make decisions based on incomplete knowledge and delayed information. The decision dynamics of these actors are modeled using a computational ecosystem construct. A preliminary set of coupled payoff function for each actor type and each decision is developed to represent interdependencies among SC actors. The simulation model was used to evaluate three archetypes of subsidy policy. The SC network behavior is observed in terms of fraction of actors adopting the biofuel option. The SC network shows behaviors ranging from fixed point equilibrium under no delay and perfect knowledge to periodic and chaotic oscillations. The network behavior is very sensitive to the time delay parameter that partly influences the quality of information on which actors’ decisions are based. Several regions of SC behavior are identified. In particular, a chaotic behavior was observed. The work provides a methodological basis for further development, including identification of policies to control undesirable system behaviors.

Improving the Efficiency of Manufacturing Supply Chain Using System Dynamic Simulation

Supply chain is a network of different business units which focuses on integration among all units in order to produce and distribute end products to the customer. Nowadays, due to increased uncertainty in customer demand, it is necessary to be sure that the supply chain networks operate as efficient as possible in order to satisfy the customer demand at the lowest cost. Enhancing the efficiency of the supply chain necessitates the interaction between different members of the supply chain which can be achieved through supply chain management. Hence, the development of modeling approach in order to understand and analyze the dynamic behavior of supply chains is brought into consideration. This paper proposes a system dynamic simulation model for manufacturing supply chain. System dynamic is used as suitable method to understand and analyze the interactions of various components via feedback structure. The objective of this paper is to simulate the manufacturing supply chain of an electronic manufacturing company in Malaysia. The simulation model is used to study the system’s behavior (in terms of production rate, inventory levels, and backlog orders) under two different operational conditions (named as fixed and varied capacity policies) and compare their efficiency in terms of total cost. The analysis shows that the proposed operational condition, which is varied capacity policy, improves the system efficiency in terms of cost.

A study on how open innovation influences on supply chain behavior

Article history: Received December 10, 2013 Received in revised format 25 June 2014 Accepted June 26 2014 Available online July 2 2014 This paper presents a study to investigate the effects of open innovation factors on supply chain behavior in Iranian gas industry. The study uses two questionnaires, one to measure the effects of open innovation factors developed by Chesbrough (2003) [Chesbrough, H. W. (2003). Open innovation: The new imperative for creating and profiting from technology. Harvard Business Press.] and the other to measure the effects of supply chain behavior. Using Pearson correlation ratio as well as Stepwise regression model, the study has determined a positive and meaningful relationship between open innovation and supply chain behavior. In our survey, while intellectual property management and networking had no impact on supply chain behavior, three variables of research and development, cooperation and entrepreneurship influence positively on supply chain behavior. © 2014 Growing Science Ltd. All rights reserved.

An Exploratory Simulation Model for Contraception Methods’ Supply Chain in Egypt

Abstract This paper presents a real case study conducted in Egypt in which discrete-event simulation model was developed to simulate the supply chain's behavior of the contraception methods for Egypt Ministry of Health (MOH). SIMIO simulation modelling tool was used for the implementation to effectively model and analyze the real system behavior, in addition to providing an effective means for supporting the decision making process through insightful analysis and representations of the number of served customer over time and the inventory level across various warehouses.

Process Control, the Bull Whip Effect and the Supply Chain

The purpose is to introduce the demand for statistical quality control practice in the supply chain environment. We show both the need and application of these measures, especially the need for multivariate quality concepts to reduce the costs of operating supply chains, to control the flow throughout the supply chain and in the dynamic behavior of supply chains to utilize concepts associated with multivariate methods and auto correlated variables. We note that the quality output is as important as the “bull whip” efficiency in the supply chain.

Robust design of (s, S) inventory policy parameters in supply chains with demand and lead time uncertainties

Demand and lead time uncertainties have significant effects on supply chain behaviour. In this paper, we present a single-product three-level multi-period supply chain with uncertain demands and lead times by using robust techniques to study the managerial insights of the supply chain inventory system under uncertainty. We formulate this problem as a robust mixed-integer linear program with minimised expected cost and total cost variation to determine the optimal (s, S) values of the inventory parameters. Several numerical studies are performed to investigate the supply chain behaviour. Useful guidelines for the design of a robust supply chain are also provided. Results show that the order variance and the expected cost in a supply chain significantly increase when the manufacturer’s review period is an integer ratio of the distributor’s and the retailer’s review periods.

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.

Standard Bridge Engineering Supply Chain Behavior Analysis Using Computer Simulation Technology

This paper tries to use systematic approaches for analysis and design of the construction supply chain operation model. According to the Supply Chain Operations Reference Model, SCOR Model of Supply Chain Council, SCC in 1996 and based on this model and application to the SCOR Model, this research places focus on the supplydemand behaviors of the Taiwan High Speed Railroad (HSR) construction process as a case study. This paper uses the concept of SCOR Model and appliance to Dynamic Simulation software, namely, SIMPROCESS, trying to assist in establishing a hierarchical model to explore the behavior of construction supply chain process and developing a performance evaluation method which can help improve supply chain management (SCM) of the construction project.

From waste to value – a system dynamics model for strategic decision-making in closed-loop supply chains

Although the field of closed-loop supply chain management has attracted a lot of attention in recent years and the management of reverse logistics processes has become a major field of supply chain management, there is still a lack of research conducting analyses using a comprehensive approach that takes the complexity of problems of reverse logistics processes into account. Hence, the purpose of this paper is to develop a model that allows an original equipment manufacturer in the electronics industry to test different value recovery strategies for business-to-business products in a closed-loop supply chain setting. For this purpose system dynamics is used because this approach enables one to capture the high complexity of reverse logistics processes and is suitable, contrary to traditional optimisation approaches, for analysing the dynamic behaviour of closed-loop supply chains comprehensively. The simulation analysis identifies leverage points for the improvement of decisions concerning reverse logistics. In particular, the simulation runs conducted highlight the high complexity and connectivity inherited with various value recovery processes. The paper contributes to a better understanding of supply chain dynamics, the impact of product backflow, and reverse logistics.

Decentralised planning coordination with quantity discount contract in a divergent supply chain

This paper proposes to solve a supply chain planning problem with realistic features. The problem consists of planning productions, transportations and storage activities in a supply chain at a tactical level on a finite horizon. The main features considered are decentralised decision making and iteration of the planning process on a rolling horizon basis. In each planning process, the actors optimise their local planning and coordinate to achieve a good overall planning. A multi-agent system is used to model such supply chain behaviour. The study is conducted in a divergent two-echelon supply chain with one manufacturer and multiple independent retailers. Coordination is achieved using a standard contract in practice, known as the ‘quantity discount’ contract. The planning framework on the supply chain structure is detailed. Lot-sizing models integrating the quantity discount are presented for the local planning problems. Experimental tests are conducted with three major parameters: quantity discount price, quantity discount breakpoint and rolling horizon length. They are used to determine the quantity discount parameters in achieving the best supply chain profit, and to analyse the increasing profit of the actors. A decision-making tool which is able to consider realistic features of supply chain planning is therefore resulted.

Supply chain channel strategies with quality and marketing effort-dependent demand

We investigate the equilibrium behaviors of a two-stage supply chain (SC) under three supply chain structures: (i) manufacturer Stackelberg (MS), (ii) retailer Stackelberg (RS) and (iii) vertical Nash (VN). Given quality and marketing effort-dependent demand, we develop models to optimize the retailer's and the manufacturer's effort levels and profits using different channel strategies. We find that the retailer's profit and marketing effort level are most sensitive to the marketing cost coefficient in the MS model. The manufacturer's profit and quality-improvement effort level are most sensitive to the quality cost coefficient in the RS model. Numerical examples are provided to illustrate the efficiency and effectiveness of the proposed models. Finally, we find that if the retailer does not exert marketing effort, the manufacturer will commit much less quality-improvement effort. Similarly, if the manufacturer does not make any commitment to quality-improvement effort, then the retailer will exert less marketing effort. In general, investing in marketing efforts is most profitable to the retailer under RS, while investing in quality efforts is most profitable to the manufacturer under MS.

Connecting product design, process and supply chain decisions to strengthen global supply chain capabilities

The importance of product design as a main determinant of process design has been emphasized in operations management literature for decades, but the direct and indirect impacts of product design on process and supply chain activities is a research area that has received less attention to date. This multiple case study addresses this research gap by assessing how and why changes in product design shape process and supply chain practices and in particular, how these changes influence global supply chain behavior and capabilities.Utilizing a 3DCE theory base, multiple manufacturing case studies are compared and contrasted to examine the interrelationships and dependencies among product, process and supply chain behaviors and capabilities. Product design changes were found to alter the scope and scale of process and supply chain modifications in specific ways that alter firms' competitive product design customization capabilities and competencies; flexible, advanced process technologies; and collaborative supplier practices.This study contributes to operations management literature by providing a rich empirical analysis of operations system interplay. The study develops substantive research propositions and a 3DCE theoretical framework that may be used to drive future operations management research and in addition, provides managerial insights that can be used to strengthen supply chain capabilities in a global and dynamic context.

A model measurement system for collaborative supply chain partners

The purpose of this paper is to understand business performance in the context of an electronic component company. This paper developed a system dynamics model that describes supply chain process structure and examines scenarios, as well. Thus, this study adopted the signal-to-noise (SN) ratio defined by the Taguchi method to evaluate the robustness of a specific supply chain behavior. Resulting in poor inventory cost performance with uncertainty demand, this paper shows how the factor delivery time and lead time of an order can improve performance. Finally, this paper serves as a guideline for decisions that require different inventory strategies.

Managing Supply Chain Execution: Monitoring Timeliness and Correctness via Individualized Trace Data

Improvements in information technologies provide new opportunities to control and improve business processes based on real‐time performance data. A class of data we call individualized trace data (ITD) identifies the real‐time status of individual entities as they move through execution processes, such as an individual product passing through a supply chain or a uniquely identified mortgage application going through an approval process. We develop a mathematical framework which we call the State‐Identity‐Time (SIT) Framework to represent and manipulate ITD at multiple levels of aggregation for different managerial purposes. Using this framework, we design a pair of generic quality measures—timeliness and correctness—for the progress of entities through a supply chain. The timeliness and correctness metrics provide behavioral visibility that can help managers to grasp the dynamics of supply chain behavior that is distinct from asset visibility such as inventory. We develop special quality control methods using this framework to address the issue of overreaction that is common among managers faced with a large volume of fast‐changing data. The SIT structure and its associated methods inform managers on if, when, and where to react. We illustrate our approach using simulations based on real RFID data from a Walmart RFID pilot project.

State of Art and Research Demands for Simulation Modeling of Green Supply Chains

In this paper, we review simulation and modeling techniques focusing on green and sustainable supply chains. We start by introducing green supply chains and the importance of being aware of environmental friendliness. We show how environmental performance is measured and analyzed, and then discuss the extension of green to sustainable supply chains. Taking into account the complex interrelations within supply chains, we give an overview of modeling and simulation techniques. This enables us to explain how supply chain behavior can be predicted and optimized under a set of given objectives. We conclude by suggesting the possibilities provided by modeling and simulating green and sustainable supply chains and propose future research.

Optimizing Product Cost with Supply Chain Cost Modeling

Demands on the electronics industry for smaller, better, and cheaper packages have made the supply chain more complex. Outsourcing, new technologies, and increasing performance requirements make designing and building the right product for the right price more difficult than ever. We will present a framework for understanding and managing the supply chain through cost modeling. Cost models that accurately reflect the cost impact from technology and design decisions enable a more precise understanding of supply chain behavior. Cost models can show the extra cost of adding a layer, the expected savings from relaxing design rules, or the cost of package on package assembly compared to 3D packaging with through silicon vias (TSVs). The models also provide context to understanding the ″should cost″ of a product and the path to achieving it. Since the guidance from cost models is based on the actual supplier cost drivers and pricing behavior, designer cost reduction efforts will result in higher savings compared to not using the cost models. Without cost models, designers risk missing their suppliers' real cost drivers and, therefore, the opportunity to decrease cost. This cost modeling framework allows the designers to realize the lowest cost product by matching the right design with the right supplier. It is a method for understanding a design decision's cost impact: a design change, a supplier change, or even the impact of new technology.

Study on Supply Chain Cooperative Games between Airport and Cargo Airways within International Air-Transport Hub

Speed economy, proposed by Japanese scholars Masaki Tamura, refers to get the cost savings flow by accelerating the transaction process [1], which brings the a large market space to the cargo/express delivery industry [2]. Due to the rapidly growth of China air cargo/express market and the ongoing increasingly opening up of the sky, inter-national cargo/express giants have set up their hubs in China. The arrival of these global logistics integrators has brought a lot of influence to the development of airport. Hereinto, the unbalance between the scales of China cargo hubs and the rapid demand of air cargo/express development, the cooperation model of airports and air cargo/express have become the most urgently issue to explore. Therefore, on the basis of airport and airway co-competition analysis, the characteristics of the air cargo supply chain, and the airports and cargo airlines supply chain behavior, this paper will use the non-co- operative game of principal-agent model and the cooperative game model to analysis the revenue distribution of airport and cargo airway on the supply chain, this paper applies the cooperative game theory within a supply chain to analyze the cooperation model of airports and air cargo/express, so as to makes strategy suggestions on airport development.

Simulation of retail supply chain behaviour and financial impact in an uncertain environment

Traditionally, attention has been focused on uncertainty in customer demand. However, uncertainty is also inherent in the market on the supply side, because the quantity and quality of raw materials delivered from external suppliers may differ from those requested. This paper quantifies the financial impact of having uncertainty in a retail supply chain. Having unstable inventory records leads to profit losses in a supply chain. These inventory records may not be correct due to various causes such as transaction errors, misplacement, etc. These inaccuracies are caused by uncertainties in customer demand, parts supply and variations in the process itself. The aim of this paper is to examine the relationship between inventory inaccuracy and financial performance. The results indicate that each type of uncertainty can have different impacts on the chain and the elimination of uncertainty can more or less reduce supply chain costs and hence, increase profit.

An Alternative Theoretical Explanation and Empirical Insights into Overordering Behavior in Supply Chains*

The beer game and the supply line underweighting theory are central to our knowledge of decision making in dynamic environments such as supply chains. The core of these theories is that people are incapable of recognizing the pipeline inventory and this is the main cause of overordering and dysfunctional behavior. This article identifies lacunae in the theoretical and empirical foundations of extant literature and proposes an alternate explanation, a “correction model,” explaining why overreactions occur. We adopt a multi-method research design, comprising a field case study and laboratory experiments, to ground our findings. [Submitted: July 19, 2010. Revisions received: December 8, 2010; March 14, 2011. Accepted: March 28, 2011.]