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The role of modern logistics in economic development is being highlighted and regional logistics has an effective role in the development of various industries such as regional trade, tourism and finance and has important value for the reduction of enterprise material consumption and the improvement of comprehensive service quality. The main research content of multifractal theory is fractal systems’ scale distribution characteristic, which is to reveal the intrinsic scale invariance of irregular shapes in nature by mathematical methods, and to analyze the characteristics of the original system and the inherent evolution of dynamics. System dynamics simulation of the logistics economic system is helpful to understand the development trend and mutual relationship of regional logistics and regional economy, and provide countermeasures and suggestions for the development of the two. On the basis of summarizing previous study results, this paper analyzed the research situation and significance of dynamic correlation analysis of regional logistics, expounded the development background, current status and future challenges of fractal theory, elaborated the basic principle and method of correlation test and phase space reconstruction of time series, performed the multifractal characteristic analysis of regional logistics industry’s agglomeration degree and time series, constructed dynamic correlation analysis model of regional logistics based on multifractal theory, discussed coupling correlation between regional logistics dynamics and multifractal dynamics; and final empirical analysis showed that the dynamic correlation between the development level, variation speed and variation acceleration of regional logistics has multiple fractals and time-dependent nonlinear dependence; the proposed analytical model can effectively analyze and predict the dynamic development trend of regional logistics. The study results of this paper provide a reference for further researches on the dynamic correlation analysis of regional logistics from the perspective of multifractal feature.

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.

Defining complex system dynamics (SD) models in complex organizational settings is hard. This is so because the numbers of variables to consider are many and the question of causation is complicated to untangle. Second, SD models are ambiguous and hard to conceptualize. In this paper, we explore the use of a domain modeling method object-role modeling (ORM) in the process of developing SD models. We do so, because domain modeling methods help to identify relationships among entities within the scope of the problem domain and provide a structural view of the domain. The addition of a domain modeling method to the process of developing SD models is to improve SD model conceptualization, enable transformation and reuse of information plus underpin SD with a domain modeling method that allows creation of database. To realize this, we come up with a procedure in our overall research which we refer to as grounded system dynamics (GSD) a combination of ORM and SD. To reason about the combination of SD with a domain modeling method (ORM), we identify and evaluate relationships between their constructs. Basing on the identified relations, ORM to stock and flow diagram (SFD) steps are defined and applied to a real-life case study national medical stores (NMS) situated in Uganda. On completion, we draw conclusions.

Increasingly, the development of today’s “smart” products requires the integration of both software and hardware in embedded systems. To develop these, hardware firms typically enlist the expertise of software development firms to offer integrated solutions. While hardware firms often work according to a plan-driven approach, software development firms draw on Agile development methods. Interestingly, empirically little is known about the implications and consequences of working according to contrasting development methods in a collaborative project. In response to this research gap, we conducted a process study of a collaborative development project involving a software firm and a hardware firm, within which the two firms worked according to contrasting development methods. We found that the software firm was gradually compelled to forgo its Agile method, creating a role conflict in terms of its way of working. As such, our results contribute to the literature on Agile–Stage-Gate hybrids by demonstrating how, in collaborative embedded systems development, hybridization of development methods may cause projects to fail. Our main practical implication entails the introduction of the “sequential Agile approach.”

System Dynamics (SD) is a method that allows for integrated modelling of technical as well as managerial aspects responsible for the dynamic complexity of systems. Therefore, simulation of SD models can also be a tool for problem analysis within software organisations.

In this paper, experience with SD modelling of software processes and projects within Siemens is reported. Special focus is put on problems encountered during knowledge acquisition for SD model building, like inadequate guidance while conducting SD modelling projects, and insufficient methodical support for re-using available or generating missing knowledge. Both problems were addressed in a research project, jointly conducted by Fraunhofer IESE and Siemens Corporate Technology. One of the results of this project is a prescriptive process model for building SD models. This process model, which is briefly outlined in the paper, provides guidance for a systematic development of SD models in software organisations.

The efficient and optimal management of water resources is of great importance due to the strong dependence of human life on water. Also, the availability and utilization of the existing water resources in regions with water shortages, such as the Middle East, impose high social, economic, and environmental costs. Therefore, water resource management policies should incorporate all aspects of supply, allocation, control, and monitoring of resources. This study provides a dynamic simulation model for water resource management in the Yazd province of Iran to examine the effect of different policies on the other variables and choose the most suitable policies over time. For this purpose, we used a system dynamics approach to propose an integrated water resources management model, considering a comprehensive view of different aspects. The proposed model included over 230 influential variables in water resources, along with economic, demographic, technological, agricultural, industrial, public policy-making, water demand-supply, and virtual water volume subsystems. After we validate the model, we define three scenarios (optimistic, baseline, and pessimistic) and four policy packages (i.e., business as usual, focusing on economic development, focusing on sustainable development based on ecological balance, and focusing on water conservation) in the time horizons of 10, 20, and 50 years. The simulation results indicated that we require a reform in the Yazd economic development strategies through policies such as changing the cropping pattern and reducing water-consuming industries. Moreover, water supply enhancement by raising the inter-basin transfer of water alone cannot be an effective solution for reducing the water shortage in Yazd province and may even worsen the water shortage in the long run. We conclude that the “Focus on Water Conservation” policy is the best solution to reduce water shortage. The results of the baseline scenario show that adopting the FWC policy changes the increasing trend of water shortage in the province and decreases them from more than 53 billion m³ in the “Business as Usual” policy to less than 20 billion m³ in the year 2040. As the FWC would decrease more than 10 billion m³ of the virtual water level imbalance compared to BAU policy and make more investments in water efficiency plans, it preserves the current resources of water in the long run.

The vast accumulation of biological pathway data scattered in various sources presents challenges in the exchange and integration of these data. Major new standards for representation of pathway data and the ability to check inconsistency in pathways are inevitable for the development of a reliable pathway data repository. Within the context of biological pathways, the cell system ontology (CSO) had been developed as a general framework to model system dynamics and visualization of diverse biological pathways. CSO provides an excellent environment for modeling, visualizing, and simulating complex molecular mechanisms at different levels of details. This paper examines whether CSO addresses the integration capability of pathway data with system dynamics. We present a conversion tool for converting BioPAX to CSO. Transforming the data from BioPAX to CSO not only allows an analysis of the dynamic behaviors in molecular interactions but also allows the results to be stored for further biological investigations, which is not possible in BioPAX. The conversion is done using simple inference algorithms with the addition of view- and simulation-related properties. We demonstrate how CSO can be used to build a complete and consistent pathway repository and enhance the interoperability among applications.

Malaysian employees' public pension plan was studied to analyze pension expenditure due to salary risk and demographic risk. By integrating risk management and System Dynamics (SD) approach, the risk factors involved were identified, a causal loop diagram was constructed, and the SD model was developed. By using a sample of actual data, the proposed model was then validated through behavior validity test and a risk analysis was conducted. Then, risk monitoring was performed through policy evaluation in which the impact of different policy scenarios on pension expenditure was analyzed. Risk management and dynamics simulation approach in analyzing pension expenditure were shown to be useful in evaluating the impact of changes and policy decisions on risk.

The spiral tip is vital to the understanding of the spiral wave behaviors. Most studies of spiral tip dynamics focused on the prevention, control, and elimination of spiral wave, while few studies focused on the recognition of spiral wave. In real systems with the spiral wave, the recognition of the spiral wave should be before control or elimination. In the paper, we study the recognition of the spiral tip via deterministic learning. It mainly consists of two phases: the identification phase and the recognition phase. In the identification phase, the dynamics of spiral tips of the training set is accurately identified by using deterministic learning. In the recognition phase, a set of errors is obtained for a test spiral tip by employing an estimator model. Finally, the recognition of test spiral tip is achieved according to the smallest error principle. Numerical simulations based on the spiral tip generated by the Barkley model are performed to demonstrate the effectiveness and feasibility of the proposed method.

Discrete event simulation is a popular aid for manufacturing system design; however in application this technique can sometimes be unnecessarily complex. This paper is concerned with applying an alternative technique to manufacturing system design which may well provide an efficient form of rough-cut analysis. This technique is System Dynamics, and the work described in this paper has set about incorporating the principles of this technique into a computer based modelling tool that is tailored to manufacturing system design.

This paper is structured to first explore the principles of System Dynamics and how they differ from Discrete Event Simulation. The opportunity for System Dynamics is then explored, and this leads to defining the capabilities that a suitable tool would need. This specification is then transformed into a computer modelling tool, which is then assessed by applying this tool to model an engine production facility.

Understanding the sources of sustained competitive advantage is the fundamental task of strategic management research. An interesting concept of fast strategy has emerged, which builds a firm's competitiveness from its ability to react to change more rapidly than its competitors. We approach this concept with a simulation model based on a hybrid modeling technique. The simulation model is used to test the profitability of the fast strategy concept in different business environment conditions. The theoretical finding of our study supports the fast strategy concept and shows that there are some internal and external factors that control the value of agility. The methodological finding of this work is that the hybrid modeling technique offers an interesting platform for understanding the effects of environmental dynamics in strategic and technology management research.

Environmental decision-making generally involves issues of complexity, uncertainty and information feedback. The complexity of environmental problems calls for integrated and multi-disciplinary approaches, which include civil society and stakeholder groups affected by or affecting environmental decisions. This paper presents a participatory modelling framework to facilitate public and stakeholder involvement in environmental decision-making. Results from a case study in the Ria Formosa Natural Park in Portugal illustrate the process of participatory modelling. The use of the System Dynamics modelling methodology facilitates the identification of the fundamental structure underlying the processing of information flows in order to achieve the desired behaviour of environmental decisions. It sets up a collaborative environment for the involvement of stakeholders in the development and experimentation of alternative policy scenarios. Along with the achievement of a simulation model, this approach is likely to foster trust in institutions, promote team learning and increase commitment towards actions.

Aiming at the navigation congestion of water conservancy projects, the shipowner’s psychological mechanism and behavior evolution are embedded into the dynamic model, which explores the evolution law using empirical data. The structural equation model (SEM) was constructed based on four variables: Shipowner personality, waiting time perception, congestion charging experience and anchorage environmental facilities (AEF). Taking the Three Gorges Project as an example, the influence relationship and degree are empirically tested. Then the dynamic evolution process was simulated by using the system dynamics (SD). The results suggest that the waiting time perception and congestion charge can weaken the shipowner’s intention, while the anchorage environment facilities can enhance the intention. The different personality characteristics will bring different effects, and the waiting time perception is the key intermediary. The psychological cost determines the dynamic evolution. Adjusting the factor can help the ship transfer between the navigable building and turning over the dam, realizing the balanced “double-channel” and alleviating navigation congestion.

The decisions on public health policies have great impact on our society and citizens. These decisions made by policy makers are typically driven by various types of continuously changing and interlinked determinants, such as economic, social, political, and technological factors. In this dynamic setting, it is not possible for one person, or even for a team, to understand the whole system, and all cause–effect relations. Therefore, there is a need for datadriven decision support tools.

Here, attention is turned to the potential of system dynamics modeling and innovation network orchestration for developing such tools. In the book chapter, it is shown how orchestration of a network and the use of system dynamics modeling (that makes visible the causes and effects of systemic challenges) come together in relation to developing an innovative data-driven decision support system for policy makers.

The 2030 UN Agenda provides a list of 17 Sustainable Development Goals (SDGs). Typically, SDGs are viewed as non-hierarchical, if not standalone, objectives. Our aim is to represent the structure of multilayered relationships among the SDGs, where possible assigning influence links in order to configure a systems thinking view. We develop a Causal Loop Diagram (CLD) of the SDGs, which illuminates multiple linkages among these global targets and begins to address measurement issues in pursuing the Agenda. To close the system and further operationalize SDG interrelationships, we propose the addition of one further goal — population growth limits — using a system dynamics modeling analysis. Our main contribution supports the systems view that SDGs constitute a highly-interconnected network. While acknowledging that the articulation and initial efforts toward implementing the SDGs have themselves been major steps forward, we further posit that consideration of their systemic interconnectedness is indispensable for increasing the chances of achieving sustainability on planet Earth.