Abstract
The Jordanian banks and the risk analysts in particularly are seeking to adapt and buy new analytical techniques and information systems that help in identifying, monitoring and analysing the credit risk especially for the small firms that represents the biggest firms’ base in the Jordanian markets. This chapter supports that what analysts need is a thinking tool that allow the user to simulate, understand and control different policies or strategies. It will then enable better decision to be made. A simulator based on system dynamics methodology is the thinking tool produced by this chapter. The system dynamics methodology allows the bank to test “What If” scenarios based on a model which captures the behaviour of the real system over time. The objectives of this chapter is to introduce new performance measures using systems thinking paradigm that can be used by the Jordanian banks to assess the credit worthiness of firms applying for credit.
TopLiterature Review
System Dynamics was developed in the second half of the 1950s by Jay W. Forrester at the Alfred P. Sloan School of Management at the Massachusetts Institute of Technology. Forrester’s main study was the activities in Operations Research (or Management Science) that aimed to support managerial decision making through mathematical and scientific methods. According to his studies, he found that operations research was not effective in helping to solve many strategic problems inside the organisations. It was too mathematically oriented and focused too much on optimisation and analytical solutions. It neglected non-linear phenomena and relationships between corporate functions.
Forrester (1961) proposed to move towards closed-loop thinking in order to enhance the decision making process where the decision are seen as a means to affect the environment and changes in the environment also provide input to decisions which aim to influence the connection with this environment. This led Forrester to start studying decision making in social systems from the view point of information feedback control systems, so he made system dynamics more useful and relevant to the study of managerial problems. Forrester developed a method to study and simulate social systems as information feedback systems.
The method was first applied to corporate problems and was called Industrial Dynamics. Forrester (1961) defines Industrial Dynamics as “the study of the information feedback Characteristics of industrial activity to show how organizational structure, amplification (in policies), and time delays (in decision and actions) interact to influence the success of the enterprise. It treats the interactions between the flows of information, money, orders, materials, personnel, and capital equipment in a company, an industry, or a national economy”. Lane (1997) summarises Forrester’s method to modelling and understanding management problems as “social systems should be modelled as flow rates and accumulations linked by information feedback loops involving delays and non-linear relationships. Computer simulation is then the means of inferring the time evolutionary dynamics endogenously created by such system structures. The purpose is to learn about their modes of behaviour and to design policies which improve performance”.
Because social systems contain lots of non-linear relationships, Forrester choose an experimental, or simulation, approach to be utilised in System Dynamics (Vennix 1996). Following Forrester’s studies and publications, the method came to be applied to a large variety of problems and its name changed into the more general System Dynamics.
System dynamics is applied currently by both academic researchers and practitioners from all over the world. Applications of system dynamics have reached most of fields such as: health care, commodity production cycle, economic fluctuations, energy and project management and many more fields. Finally, there is an international system dynamics society at MIT, holding a yearly international system dynamics conference. In addition there is the society’s journal (System Dynamics Review) and a huge number of chapters and literature on the system dynamics subject published in the conferences and journals around the world.
Key Terms in this Chapter
Stock and Flows Diagram: Stock and flow diagrams provide a bridge to system dynamics modeling and simulation. Basically Stock and flow diagrams contain specific symbols and components representing the structure of a system. Stocks are things that can accumulate—(Think of a stock as a bathtub.) Flows represent rates of change—(Think of a flow as a bathtub faucet, which adds to the stock, or a bathtub drain, which reduces the stock.) These diagrams also contain “clouds,” which represent the boundaries of the problem or system in question
Causal Loop Diagram: Causal loop diagrams (CLDs) are a kind of systems thinking tool. These diagrams consist of arrows connecting variables (things that change over time) in a way that shows how one variable affects another
Simulator’s Interface: The interface or the user interface is the aggregate of means by which the user interacts with the system, a particular machine, device, computer program or other complex tools. The simulator in this research is constructed based on the simulation model. It is interactive and provides managers with a user interface that allows them to experiment with the model.
Simulator: A computer simulation is an attempt to model a real-life or hypothetical situation on a computer so that it can be studied to see how the system works. By changing variable, prediction and testing different scenarios.
Systems Thinking: Systems thinking, in contrast, focuses on how the thing being studied interacts with the other constituents of the system—a set of elements that interact to produce behaviour—of which it is a part. This means that instead of isolating smaller and smaller parts of the system being studied, systems thinking works by expanding its view to take into account larger and larger numbers of interactions as an issue is being studied. This results in sometimes strikingly different conclusions than those generated by traditional forms of analysis, especially when what is being studied is dynamically complex or has a great deal of feedback from other sources, internal or external. Systems thinking allows people to make their understanding of social systems explicit and improve them in the same way that people can use engineering principles to make explicit and improve their understanding of mechanical systems.
System Dynamics Model: It’s a computer simulation model based on system dynamics features that aim to confirm that the structure hypothesized can lead to the observed behaviour and to test the effects of alternative policies on key variables over time. Modeling purpose is to solve a problem and also to gain insight into the real problem to design effective policies in a real world, with all its ambiguity, messiness, time pressure and interpersonal conflict. It is a feedback process, not a linear sequence of steps. System dynamics models are very important tools for managers that enable them to design their organizations, shaping its structure, strategies and design rules and enable them to take different decisions in their organizations. It is an effective tool in promoting system thinking in an organization.
Financial Ratios: Financial ratios are a valuable and easy way to interpret the numbers found in statements. It can help to answer critical questions such as whether the business is carrying excess debt or inventory, whether customers are paying according to terms, whether the operating expenses are too high and whether the company assets are being used properly to generate income. When computing financial relationships, a good indication of the company’s financial strengths and weaknesses becomes clear. Examining these ratios over time provides some insight as to how effectively the business is being operated.
System Dynamics: System dynamics is an approach to understanding the behaviour of over time. It deals with internal feedback loops and time delays that affect the behaviour of the entire system. It also helps the decision maker untangle the complexity of the connections between various policy variables by providing a new language and set of tools to describe. Then it does this by modeling the cause and effect relationships among these variables