System Dynamics Simulation Approach Research Articles

Impact of replenishment strategies on supply chain performance under e-shopping scenario

With the development of Information and communication technologies (ICT), the supply chain performance and its management techniques have significantly transformed. The internet revolution has bought the surge in online shopping platforms attracting millions of small size manufactures to engage in the nascent business models. The research attempts to identify the factors influencing the supply chain performance for small size manufacturers under e-shopping scenario. The system dynamics simulation approach is attempted to assess the impact of replenishment strategies on supply chain performance indicators. The results reveal the existence of bullwhip effect in the e-shopping supply chains due to backlogged orders and management decisions. The comparison between two different inventory control strategies with replenishment patterns indicates that the target stock level method performs better over economic order quantity method under e-shopping scenario.

Quantifying the Effect of Sharing Information in a Supply Chain Facing Supply Disruptions

In this work, a system dynamics simulation approach is proposed to evaluate the effect of sharing information with partners in a supply chain when it is faced with supply-related disruptions which severely affect the product manufacturing. We focus on a simple two-echelon supply chain involving one retailer and two suppliers, and study the retailer’s decision on allocating orders between the suppliers. Three specific settings of information sharing by the suppliers are investigated: (i) no information shared; (ii) information partially shared; and (iii) information completely shared. After establishing corresponding ordering policy under each setting, we conduct extensive numerical analysis to simulate shocks to suppliers’ manufacturing capacity and calculate the resulting extra cost as measure of the effectiveness of information sharing. Simulation results show that with more information shared by suppliers, the retailer is able to make response to disruptions more accurately and timely, the negative impact of which thus can be reduced by larger extent, even though not completely eliminated.

A study of software development project cost, schedule and quality by outsourcing to low cost destination

Purpose – The purpose of this paper is to find good values of onsite-offshore team strength; number of hours of communication between business users and onsite team and between onsite and offshore team so as to reduce project cost and improve schedule in a global software development (GSD) environment for software development project. Design/methodology/approach – This study employs system dynamics simulation approach to study software project characteristics in both co-located and distributed development environments. The authors consulted 14 experts from Indian software outsourcing industry during our model construction and validation. Findings – The study results show that there is a drop in overall team productivity in outsourcing environment by considering the offshore options. But the project cost can be reduced by employing the offshore team for coding and testing work only with minimal training for imparting business knowledge. The research results show that there is a potential to save project cost by being flexible in project schedule. Research limitations/implications – The implication of the study is that the project management team should be careful not to keep high percentage of manpower at offshore location in distributed software environment. A large offshore team can increase project cost and schedule due to higher training overhead, lower productivity and higher error proneness. In GSD, the management effort should be to keep requirement analysis and design work at onsite location and involves the offshore team in coding and testing work. Practical implications – The software project manager can use the model results to divide the software team between onsite and offshore location during various phases of software development in distributed environment. Originality/value – The study is novel as there is little attempt at finding the team distribution between onsite and offshore location in GSD environment.

Quantifying the economic and demographic impact of transportation infrastructure investments: A simulation study

Investment in transportation infrastructure has been widely utilized as an instrument for inducing economic growth. Such investment usually leads to job creation and an increase in per capita income that attracts population through migration to the region. This increases the utilization of the transport infrastructure over time, resulting in high levels of congestion. The congestion negatively impacts the attractiveness of the region and the gross regional product (GRP). Regions cyclically invest in transport infrastructure that temporally spurs economic activity and migration, and reduces congestion. This research employs a system dynamics simulation approach to capture and mimic the behavior of these complex and cyclical relationships over time. Our approach suggests the modeling of key demographic, transportation infrastructure, travel behavior, and economic activity components to determine the impact of infrastructure investments on regional growth. Given a set of prospective investment scenarios, the model replicates and projects levels of productivity, travel demand, congestion, GRP, and net migration patterns over time. The model also provides insights into the duration of critical cyclical patterns given these prospective infrastructure investments. The simulation model presented in this paper seeks to be utilized as guidance to support decision-making processes that lead to the execution of more exhaustive transportation studies that organize the execution of such investments.

A Markov System Dynamics Approach for Repairable Systems Reliability Modeling

The study and analysis of repairable systems is an important topic in reliability. Analytical techniques become very complicated and unrealistic especially for modern complex systems. There have been attempts in the literature to evolve more realistic techniques using simulation approach for reliability analysis of systems. The purpose of this paper is to develop a novel Markov system dynamics (MSD) simulation framework for the reliability modeling and analysis of a repairable system. This paper proposes a hybrid approach called as MSD approach which combines the Markov approach with system dynamics simulation approach for reliability modeling. This approach will have the advantages of both Markov as well as system dynamics methodologies. The proposed framework is illustrated for a repairable two component system. The results of the simulation obtained in this work when compared with that obtained by traditional Markov analysis clearly validate that this novel MSD approach is an alternative approach for reliability modeling and analysis.

Availability modeling of repairable systems using Markov system dynamics simulation

Purpose– The purpose of this paper is to propose a novel hybrid approach called as Markov System Dynamics (MSD) approach which combines the Markov approach with system dynamics (SD) simulation approach for availability modeling and to study the dynamic behavior of repairable systems.Design/methodology/approach– In the proposed approach the identification of the single unit repairable system all possible states has been performed by using the Markov approach. The remaining stages of traditional Markov analysis are highly mathematically intensive. The present work proposes a hybrid approach called as MSD approach which combines the Markov approach with SD simulation approach to overcome some of the limitations of Markov process in a simple and efficient way for availability modeling and to study the dynamic behavior of this system.Findings– The proposed framework is illustrated for a single unit repairable system. The worked out example shows the steady state point and also it gives the point, interval and steady state availabilities and also the dynamic behavior of the system. However this methodology can be extended easily for more complex multi-state maintainable systems. The results of the simulation when compared with that obtained by traditional Markov analysis clearly validate the proposed approach as an alternative approach for availability modeling of repairable systems.Practical implications– In many practical situations we require to find the time at which our system reaches steady state conditions for planning maintenance activities. The proposed MSD method in this paper is capable of finding this steady state point very easily.Originality/value– The proposed approach clearly indicates the time at which the system reaches its steady state and calculates the point, interval availabilities for planning maintenance activities. The different parties, i.e., engineers and machine operators, can jointly work with this model in order to understand the dynamic behavior of repairable systems.

Developing Causal Relationships for CPFR Index: A System Dynamics Simulation Approach

Collaborative planning, forecasting and replenishment (CPFR) is one of the collaborative strategies in supply chain management that aims to coordinate the diverse processes of supply chain management. Despite being identified as playing an important role in supply chain performance improvement, the dynamic interactions among its subsystems have not been explored in previous research. This research aims to identify the interactions among effective enablers and the potential impact of each enabler on successful CPFR implementation through the development of a structural model and system dynamics simulation modelling. To reach this goal, significant enablers and results reported in previous research have been explored. The causal relationships among different variables have been analysed using through the application of system dynamics and stock and flow diagrams. A dynamic CPFR model is proposed based on a number of assumptions. The resulting causal loop helps the reader to better understand and learn the dynamic interactions of CPFR subsystems. 

Reliability analysis of repairable systems using system dynamics modeling and simulation

Repairable standby system’s study and analysis is an important topic in reliability. Analytical techniques become very complicated and unrealistic especially for modern complex systems. There have been attempts in the literature to evolve more realistic techniques using simulation approach for reliability analysis of systems. This paper proposes a hybrid approach called as Markov system dynamics (MSD) approach which combines the Markov approach with system dynamics simulation approach for reliability analysis and to study the dynamic behavior of systems. This approach will have the advantages of both Markov as well as system dynamics methodologies. The proposed framework is illustrated for a standby system with repair. The results of the simulation when compared with that obtained by traditional Markov analysis clearly validate the MSD approach as an alternative approach for reliability analysis.

Using system dynamics to evaluate renewable electricity development in Malaysia

Purpose – The purpose of this paper is to provide an assessment of Malaysia's renewable capacity target. Malaysia relies heavily on fossil fuels for electricity generation. To diversify the fuel-mix, a technology-specific target has been set by the government in 2010. Considering the complexity in generation expansion, there is a dire need for an assessment model that can evaluate policy in a feedback fashion. The study also aims to expand policy evaluation literature in electricity domain by taking a dynamic systems approach. Design/methodology/approach – System dynamics modelling and simulation approach is used in this study. The model variables, selected from literature, are constituted into casual loop diagram. Later, a stock and flow diagram is developed by integrating planning, construction, operation, and decision making sub-models. The dynamic interactions between the sub-sectors are analysed based on the short-, medium- and long-term policy targets. Findings – Annual capacity constructions fail to achieve short-, medium- and long-term targets. However, the difference in operational capacity and medium- and long-term target are small. In terms of technology, solar photovoltaic (PV) attains the highest level of capacity followed by biomass. Research limitations/implications – While financial calculations are crucial for capacity expansion decisions, currently they are not being modelled; this study primarily focuses on system delays and exogenous components only. Practical implications – A useful model that offers regulators and investors insights on system characteristics and policy targets simultaneously. Originality/value – This paper provides a model for evaluating policy for renewable capacity expansion development in a dynamic context, for Malaysia.

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.

Integrated assessment model of society-biosphere-climate-economy-energy system

The feedback based integrated assessment model ANEMI_2 represents the society-biosphere-climate-economy-energy system of the earth and biosphere. The ANEMI_2 model is based on the system dynamics simulation approach that (a) allows for the understanding and modeling of complex global change and (b) assists in the investigation of possible policy options for mitigating, and/or adapting to changing global conditions within an integrated assessment modeling framework. This paper outlines the ANEMI_2 model and its nine system components: climate, carbon cycle, land-use, population, food production, hydrologic cycle, water demand, water quality, and energy-economy. To evaluate market and nonmarket costs and benefits of climate change, the ANEMI_2 model integrates an economic optimization approach, with a focus on the international energy stock and fuel price, climate interrelations and temperature change. The model takes into account all major greenhouse gases (GHG) influencing global temperature and sea-level variation. Results from several scenarios (a) compare well with other information available in the scientific literature, (b) present comprehensive response of the society-biosphere-climate-economy-energy system to the selected scenarios, and (c) confirm the support role of the ANEMI_2 model in the policy development and analyses.

Coordinating decisions by supply chain partners in a vendor-managed inventory relationship

We look into the linked decision making in the vendor-managed inventory (VMI) relationship. It is a supply chain management model, where the retailer decides the retail price while the vendor determines its capacity commitment. In this model, the retailer and the vendor should coordinate their decisions in order to maximize their individual profit or the total profit combining the two participants together. The vendor has to take into account the demand pattern throughout the product life cycle (PLC) when it decides its capacity commitment, which will affect its inventory management cost during the PLC, while the retailer should change the retail price over the PLC so as to maximize the revenues and minimize the inventory cost at the same time. Employing a system dynamics simulation approach based on differential game theory, which also takes into account the product characteristics such as the demand’s innovation and imitation effects, we analyze and confirm the dynamic coordination of key decision variables by the supply chain partners in the VMI relationship.

A managerial tool for reliability analysis using a novel Markov System Dynamics (MSD) approach

System reliability is considered as an important performance index. Performance of engineering systems can be assessed by various techniques. In the traditional analytical techniques a mathematical model is developed to represent the system and to evaluate its reliability indices. There have been attempts in the literature to evolve more realistic techniques using simulation approach for reliability analysis of systems. This paper proposes a hybrid approach called as Markov System Dynamics (MSD) approach which combines the Markov approach with system dynamics simulation approach for reliability analysis and to study the dynamic behavior of systems. This approach will have the advantages of both Markov as well as System dynamics methodologies. The proposed framework is illustrated for a single component system with a numerical example. The results of the simulation when compared with that obtained by traditional Markov analysis clearly validate the Markov System Dynamics (MSD) approach as an alternative approach for reliability analysis.

A Novel Markov System Dynamics Framework for Reliability Analysis of Systems

System reliability is considered as an important performance index. Performance of engineering systems can be assessed by various techniques. The traditional analytical approach consists of developing a mathematical model that represents the system and to evaluate its reliability indices. There have been attempts in the literature to derive more realistic approaches for the reliability analysis of systems, for example, based on simulations. This paper proposes a hybrid approach called Markov System Dynamics (MSD) approach which combines the Markov approach with system dynamics simulation approach for performing a reliability analysis and for studying the dynamic behavior of systems. This approach will have the advantages of both the methodologies that of Markov processes as well as system dynamics. The proposed framework is illustrated by a numerical example for a single component system with increasing failure rates. The results of the simulation when compared with those obtained by the traditional Markov analysis clearly validate the Markov System Dynamics (MSD) approach as an alternative for reliability analysis.

Decreasing Lab Turnaround Time Improves Emergency Department Throughput and Decreases Emergency Medical Services Diversion: A Simulation Model

The effect of decreasing lab turnaround times on emergency department (ED) efficiency can be estimated through system-level simulation models and help identify important outcome measures to study prospectively. Furthermore, such models may suggest the advantage of bedside or point-of-care testing and how they might affect efficiency measures. The authors used a sophisticated simulation model in place at an adult urban ED with an annual census of 55,000 patient visits. The effect of decreasing turnaround times on emergency medical services (EMS) diversion, ED patient throughput, and total ED length of stay (LOS) was determined. Data were generated by using system dynamics analytic modeling and simulation approach on 90 separate days from December 2, 2007, through February 29, 2008. The model was a continuous simulation of ED flow, driven by real-time actual patient data, and had intrinsic error checking to assume reasonable goodness-of-fit. A return of complete laboratory results incrementally at 120, 100, 80, 60, 40, 20, and 10 minutes was compared. Diversion calculation assumed EMS closure when more than 10 patients were in the waiting room and 100% ED bed occupancy had been reached for longer than 30 minutes, as per local practice. LOS was generated from data insertion into the patient flow stream and calculation of time to specific predefined gates. The average accuracy of four separate measurement channels (waiting room volume, ED census, inpatient admit stream, and ED discharge stream), all across 24 hours, was measured by comparing the area under the simulated curve against the area under the measured curve. Each channel's accuracy was summed and averaged for an overall accuracy rating. As lab turnaround time decreased from 120 to 10 minutes, the total number of diversion days (maximum 57 at 120 minutes, minimum 29 at 10 minutes), average diversion hours per day (10.8 hours vs. 6.0 hours), percentage of days with diversion (63% vs. 32%), and average ED LOS (2.77 hours vs. 2.17 hours) incrementally decreased, while average daily throughput (104 patients vs. 120 patients) increased. All runs were at least 85% accurate. This simulation model suggests compelling improvement in ED efficiency with decreasing lab turnaround time. Outcomes such as time on EMS diversion, ED LOS, and ED throughput represent important but understudied areas that should be evaluated prospectively. EDs should consider processes that will improve turnaround time, such as point-of-care testing, to obtain these goals.

Integrated Analyses of Canada's Water Resources: A System Dynamics Approach

An integrated water resources management model for Canada, CanadaWater, has been developed using the system dynamics simulation approach. The CanadaWater model takes into consideration dynamic interactions between quantitative characteristics of the available water resources and water use that are determined by the socio-economic development level, population and physiographic features of Canadas territory. It is a unique tool that integrates the water quantity and quality sectors with seven sectors that drive economic development: population; agricultural development; food production; capital investment; energy generation; use of non-renewable resources; and persistent pollution. The CanadaWater model is a system dynamics simulation model that provides for investigation of different scenarios. Model simulations are performed for 12 scenarios designed to investigate policy options in the area of fresh water availability, wastewater treatment, economic growth, population growth, energy generation and food production. The conclusions point to a very strong dependence of Canadas future development and well being on maintaining acceptable quality of the water resources and controlling the level of water use in different sectors.

Methodology for Assessment of Climate Change Impacts on Large-Scale Flood Protection System

An original modeling framework for the assessment of climate variation and change impacts on the performance of a complex flood protection system has been developed for the city of Winnipeg in the Red River basin, Manitoba, Canada. The modeling framework allows for the evaluation of different climate change scenarios generated by the global climate models. Temperature and precipitation are used as the main factors affecting flood flow generation. The main contribution of the reported work is the use of a system dynamics modeling and simulation approach in the development of a system performance assessment model. The assessment-modeling framework is based on flood flows, capacity of flood control structures, and failure flow levels at different locations in the basin. The results of this study (shown only to illustrate the methodology) indicate that the capacity of the existing Red River flood protection system is sufficient to accommodate future climate variability and change.

Simulation applied to health services: opportunities for applying the system dynamics approach.

The aim of this essay is to raise awareness and broaden understanding within the health services community of the system dynamics (SD) simulation approach to policy analysis. The application of simulation in health services is reviewed. A comparison is made between the SD and traditional simulation approaches and is illustrated by considering reductions in waiting times for coronary heart disease treatment. Traditionally, simulation studies have tended to focus on the analysis of localized decisions and therefore on problems orientated towards individual patients. Although these methods are extremely powerful and effective, there is scope for an alternative modelling approach which is based on a more holistic perspective; SD is one such approach. It can assist in the design of robust policies by supporting debate on how the underlying structure might influence the evolutionary behaviour of a system. Using this method we can consider the time variation both of tangibles, such as waiting times and health care costs, and intangibles, such as patient anxiety and the effects of various pressures on purchasing decisions. We propose that SD holds great potential in assisting policy formation in health care.