Stock and Flow Diagram

Based on a CLD, we prepared a quantitative model for the simulation part, which is shown as an SFD in Figure 8.4. This model measures the variability on timescale due to the cause and effect relationships of variables. CLDs represent a complete mental model for understanding the relationship. An SFD is a mathematical simulation model where the stock and flow of the system captures the dynamic nature of the system. In our SFD


Close loop diagram.

model, there are four stocks: public bus capacity, metro capacity, population, and ICT infrastructure. To make a smart city, a government needs to invest in relevant infrastructures, such as public transportation and ICT infrastructure. This investment will lead to the enhancement of both public transport, in the form of new metros and buses, and the ICT infrastructure, after the implementation time delays. Here, only two transportation modes, buses and metros, have been taken for the analysis, as buses contribute to nearly half of public transport, and metros are preferred as a smart choice of transportation. New public transport capacity will increase public transport reliability, and will reduce travel time and cost. The increase in public transport capacity will also positively impact local accessibility. On the other hand, more buses will lead to more traffic congestion, negatively impacting local accessibility. The degree of local accessibility and ICT infrastructure defines our smart city attractiveness index. The population will increase by two different modes: one is through normal population, and the other is due to smart city attractiveness. Since the requirement for public transport and ICT infrastructure will increase due to the increase in population, the government will infuse money to make a sustained smart city, based on the gap between the target and existing capacities. Vensim Software is used to run the model. Initial values, based on Lucknow city data, are used for the calculation given in Table 8.2.


Stock and flow diagram.


  • 1. Only one dimension, smart mobility, has been taken for the study.
  • 2. Energy perspective on greenhouse gas emission is not considered directly, as only buses and metros have been considered in public transportation.
  • 3. Private funding is not considered separately.
  • 4. Private vehicle, vehicle ownership, and GDP factors are not included in the model.
  • 5. The city area is constant over the period of analysis.
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