Developed in 1950s, system dynamics is a method for understanding, designing, and managing the changes of a system over time by modelling the relationships between its elements. In social challenges, solving complex problems often requires the expertise of multiple disciplines.

As shown in the figure, participation of these three universities will end up with improvement of the connections and collaborations of the academic centers and industries considering the differences between their educational systems and the current barriers. For example, high unemployment rate of young educated people along with some social barriers for women employment in industrial and manufacturing sectors will be considered and modelled utilizing system dynamics model (shown in). More investigation for the other two countries must be performed in order to realize the potentials for improvement and sharing of the capacity of learning from the other participants. The dialogue is mainly established with the aim of exchanging experience, sharing knowledge and building the facilities for improvement of university and industry collaboration.

To analyse the system dynamic model, first we need to outline the influential variables in the model both types of state and rate. State variables are listed as below. The goal of modelling is to control and monitor and discuss the behaviour of these variables within a long period of time.

State variables:

  • Number of unemployed women (to be treated over 50 years)
  • Number of uneducated women (to be treated over 50 years)
  • Woman education and employment in Iran: statistics and facts

System dynamics approach to simplify the complex model

There are some software applications to assist the modelling of real complex systems into the relationship of their variables. Using Vensim OLE software [4] a simple model based on the above assumptions was developed. In this simplified model, we try to represent the state and rate variables as well as the cause and effect diagrams shown by arrows. This model could be simulated in a time frame should the relationship between the variables become evaluated and preferably quantified. As one aspect of the proposed program, the figure  illustrates the treatment of the gap between the potential and actual participation of women in academy and industry.

Explanation and initial analysis:

Loop 1: Rate of university admission increases the number of educated women graduated from universities. This will in turn increase the rate of unemployment women who are waiting to find job opportunities. The number of unemployed women might be dropped down with rate of employment in industry or service sectors. The higher the number of women at work, the more encouragement of government policies which also affect rate of university admissions and facilitate women education at academic centers.

Loop 2: On the other hand, growth of GDP in an economy and especially Muslim countries may decrease the rate of unemployment rate since almost economic growth and employment move toward the same direction. Industrialized economy imply hiring more work force including women.

Loop 3: Social preference towards women education plays a crucial role in this model. Economic growth may moderate the social resistance to women education. The more the society tends to have educated women, the rate of admission in universities increase wince the families are more willing to send their female siblings to study. Social preference could be also negatively or even positively affected by government policies. Cultural propaganda, press and media and supporting laws may help improving the capacity of universities to welcome women for study.

A plan for treatment of a social gap as a dialogue theme

Functionality chain

Keeping the ideas of the program in mind the functionality of the dialogue can be summarized in Figure 4. The connection between aspects, events and effects of the program have been demonstrated by arrows.