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System dynamics is a whole-system modelling and learning approach, useful for tackling non- linear problems, such as sustainable urban development. The purpose of this paper is to review system dynamics applications in the simulation of sustainable urban development over a period from 2005 to 2017. The analysis reveals that the number of applications of system dynamics modelling in the area of urban sustainable development increased in the analysed period. Research has changed its focus from the modelling of environmental problems to more complex models, portraying the multidimensional socio-economic processes that have an impact on the sustainability of urban development. Analysed case studies most often use the behaviour reproduction test for model validation, but without a unified approach. In most cases, modelling has been done in China, Germany and the USA, while urban development in the Eastern European countries, Africa and Latin America has not often been investigated. This paper indicates the knowledge gaps and suggests future research directions. Papers that report the use of system dynamics modelling reveal a wide range of applications in urban sustainability. The analysis shows significant emphasis on environmental problems, while the interest for modelling social problems has been increasing during the last several years. Most of the modelled problems examine the sustainability of resources (land, water) and waste management, which are used for insights into the reasons for the system behaviour, forecasting future behaviour and policy testing. The presented models were developed in most cases for the purpose of understanding the phenomena examined, as well as the future use of the models in policy planning. This brings us back to the need for greater stakeholder involvement, not only in the initial phase, but also during the whole modelling process, which could increase understanding, use and ownership of the models in the future, and thus increase their practical application.

The paper highlights the capacity of the mutual use of selected creative problem solving methods, system dynamics and multi-criteria decision-making methods when dealing with complex problems. It has already been shown that creative approaches are not limited to merely problem definitions and problem structuring, since they can also be used in typically analytical steps in the framework procedure of multicriteria decision making. The goal of this paper is to explore the possibilities how to employ creative problem solving methods in system dynamics, and how to complete system dynamics with multi-criteria decision making. This paper shows that the creative problem solving methods based on questions can be used in structuring complex system dynamic problems with the selected mapping methods. It can be concluded that system dynamic models can help decision makers in enhancing understanding of system behavior over time ; however, the evaluation of the consequences of different strategies showed by these models can be supported by multi-criteria decision making. The mutual assistance of creative, systems dynamic and multi-criteria decision methods is illustrated by contemporary interdisciplinary examples

Monetary policy has often been a topic of heated political discussions in Croatia, especially during the recession years. Each side has displayed various degrees of knowledge of the topics at hand, but the vast difference in opinions indicated a lack of consensus on the question of effectiveness of the mechanisms of monetary policy, as well as its impact. This was taken as an indicator of the need for a better understanding of the complex relationships within a monetary system, especially of the fractional-reserve banking system. The purpose of this paper is to determine the suitability of system dynamics for simulating the behavior of a monetary system, with the two goals: (i) to develop a money supply management simulation model of a fractional-reserve banking system, (ii) to compare the simulation results with the predictions of the theoretical model. The behavior of the model is tested using two scenarios: (i) expansionary monetary policy and (ii) contractionary monetary policy. This paper is limited by the fact that is uses a theoretical fractional-reserve banking model as the basis for the model development, which omits some key aspects of real-world monetary systems, such as loan defaults, variable interest rates, and investment alternatives to deposit accounts. Although this makes the model unsuitable for making real-world predictions, the system dynamics approach adds to its value as by highlighting the interactions of various elements within the model and by enabling the comparison of the behavior of real-world fractional-reserve banking systems and of the simplified models across prolonged periods of time. Further research should focus on examining the effects of including some of the omitted elements on the behavior of the entire system, and on improving its predictive capabilities. This should not only increase its experimental value, but also help create a more useful model by shedding additional light on the interactions between the elements of the Croatian monetary system, and the mechanisms through which it influences the Croatian economy.

Sustainable, environmentally friendly and smart economic growth is requirement for every country. Production, transport, habitation, and natural usage have a strong impact to urban sustainability, and should be managed with the goal of controlled development. System dynamics modelling has been extensively used for studying the phenomena of sustainable urban development. The goal of this paper is to examine the main characteristics of system dynamics modelling of the system dynamics modelling process perspective. System dynamics models with the goal to study and manage urban sustainability for the purposes of urban sustainability management were examined. These models reported the investigation of the issues of phenomena such as waste disposal, pollution, urban growth, housing and transportation planning. Review of examining models gave the insight into following modelling perspectives: the main problems being analysed, main variables being modelled, usage of software and other methodologies, participation of stakeholders, the purposes of the models, and communication of the model results with the public. Broad area of urban sustainability delivered a wide range of approaches. Based on the review, decision makers can be better equipped for making efficient strategic decisions regarding future property management.

Simulation models involve participant into active decision making but in risk-free environment, without real consequences. The main benefit of using system dynamics model is analysis of the obtained results after making decision and understands what went wrong, why and when. Top managers gain valuable experience through system dynamics models which help them in doing business and in accomplishing short and long term business strategies in the real world. Tourism sector is related with high risk of decision making. The reason for that is that it takes a longer time (months or even years) in order to make the consequences of the decisions visible. Simulation models can be used as useful educational tools in tourism, because they allow managers to see the consequences of their actions in very short time, without the real consequences and real damage. Goal of the paper is to explore if system dynamics models could be used in tourism, because of their characteristic of compressing time and space within simulation environment. Paper review two basic fields of applications in tourism: airways and hotel industry. Paper is an introduction of system dynamics models’ usage in tourism, with the goal to present its usage as a powerful learning tool.

System dynamics is a method for analysing characteristics of complex dynamic systems with feedback loops. Its objective is to gather understanding of such systems. Its accompanying part is systems thinking, which bridges the qualitative and quantitative approaches to systems’ analyses. This article introduces the principles and basic elements of systems thinking. Emphasis is put onto systems science's approach to process of innovation.

System dynamics is a powerful tool that enhances learning about company, market and competitors ; portrays the cognitive limitations on the information gathering and processing power of human mind ; facilitates the practice of considering opinions ; and supports building of "What if" scenarios. Although the literature on system dynamics modeling is very rich with applications in many fields, rather few papers on developing system dynamics models were published so far. In this paper we portray current approaches to the development of system dynamics models. These are (1) model development based on influence diagram, (2) model development based on the identification of resources and their states, (3) usage of generic structures for specific domain field, and (4) component strategy for the formulation of system dynamics models. Validation is an important issue that none of these approaches tackles. We propose a “ step-by-step” approach that integrates validation with developing process of system dynamics models. This approach will be demonstrated on the example of development of a simple inventory model.

System dynamics is a powerful tool that enhances learning about company, market and competitors ; portrays the cognitive limitations on the information gathering and processing power of human mind ; facilitates the practice of considering opinions ; and supports building of "What if" scenarios. Although the literature on system dynamics modeling is very rich with applications in many fields, rather few papers on developing system dynamics models were published so far. In this paper we portray current approaches to the development of system dynamics models. These are (1) model development based on influence diagram, (2) model development based on the identification of resources and their states, (3) usage of generic structures for specific domain field, and (4) component strategy for the formulation of system dynamics models. Validation is an important issue that none of these approaches tackles. We propose a “ step-by-step” approach that integrates validation with developing process of system dynamics models. This approach will be demonstrated on the example of development of a simple inventory model.

In the world economy the role of knowledge-based enterprises is rapidly increasing. Knowledge is becoming the main business resource and the basis for competitiveness of an enterprise. These facts are particularly evident in enterprises whose basic activity is providing intellectual services. Knowledge holders and creators in these kinds of enterprises are highly qualified employees. This is why we can say that the competitive ability of such enterprise will depend on the quality of management of highly qualified workforce. This paper describes system dynamics model whose purpose is to make strategic decisions in management of highly qualified workforce in enterprises providing intellectual services on the growing market.

Decision-making in tourism is often very risky because consequences of managers’ actions are visible only after longer time (months or even years). Ideal education tool in tourism would allow managers to compresses time and space in non-risk environment and to gain experience and make mistakes without fear of real damage. Such tool would allow potential managers to see the consequences of his/her actions in few minutes or hours, and to detect possible wrong presumptions about the real world tourism markets. The paper argues that system dynamics models could meet the educational challenge in tourism and allow managers to avoid intuitively correct decisions that are actually not optimal. Paper will review application of system dynamics models in tourism, and will present the usage of system dynamics models as an educational tool in tourism.

Transition economies face the common problem regarding social insurance system, and one of them is tax avoidance. It is important to implement long term modelling because such behaviour could easily lead to the collapse of the social insurance system. Current modelling of pension systems is usually static and recursive, but in the same time, demographics, economic growth, real variables, and feedback effects are important for long term planning. A challenge in public policy making is a sensible social insurance system that offers benefits that are affordable in the short and long run and do not create serious adverse incentives for market work of for household saving. The paper argues that system dynamics can help to meet this challenge and avoid intuitively correct decision making that are actually result of “bounded rationality”. Dynamic model of Croatian social insurance system is used to illustrate the way of using system dynamic modelling as an aid in policy analysis and planning.

Number of decisions on investment, operations, and financing of the firm are based on sales forecasts. However, in selection of forecasting method it is not enough to take into account accuracy of the forecast. It is more important to estimate the influence of forecasting method on the success of the firm. Experiments for measurement of influence of the sales forecasts on the business performance in different consequences should be conducted in order to evaluate efficiency of the forecasting methods. Procedure for conducting such experiments based on system dynamics approach has been proposed. System dynamics approach is based on modeling and simulation of dynamic systems with feedback. Simulation model of the firm has been designed. Financial and real flows that are results of decisions on investment, operations, and financing are main parts of the simulation model. Influence of sales forecasts on the success of the firm has been analyzed. In the example of the experiments, sales forecasts are generated by the two methods (simple exponential smoothing and status quo method), which efficiency are evaluated in different circumstances (step increase, linear growth, and random oscillations of the sales). It has been illustrated that different methods are appropriate in different circumstances. Accuracy of the forecasting method is not a guarantee of the successful business performance. System dynamics approach could be useful in conducting experiments which purpose is to analyze influence of sales forecasts on the business performance. Simulation model of the firm should be designed according to specific characteristics of the particular firm, and could be used for analysis of any number of forecasting methods in different circumstances.

Aim of the paper is to explore the applicability of system dynamics models as tools in education of accounts receivable management, that could increase understanding of consequences of different credit policies. The system dynamics model of accounts receivable management has been created, and has been converted into a game by identifying the decision variables for the players, that are credit period, credit standards, collection policy and cash discount. Proposed models encourages players to make decisions on credit policy and explore the consequences of their decisions on firm’s profitability and cash flow in non-risk environment on compressed time basis.