Bilash Kanti Bala

Systems Thinking: System Dynamics

The concept of systems thinking was introduced in Chap. 1 and this chapter presents systems thinking based on systems approach. Systems thinking methodology, participatory systems thinking and systems thinking in action are presented to demonstrate the potentiality of systems thinking to study complex and dynamic systems. Participatory systems thinking is highlighted.

Modelling of Food Security in Malaysia

In the previous chapter, a case study on modelling and policy implication of hilsa fish population in Bangladesh has been presented. This chapter presents modelling of food security in Malaysia as a case study and application of system dynamics. The model is organised as (1) introduction, (2) dynamic hypothesis, (3) causal loop diagram, (4) stock–flow diagram, (5) model validation, (6) simulation and policy analysis and (7) conclusion. The findings suggest that gradual transition to bio-fertiliser, funding for R&D for development of high-yielding hybrid rice and increasing the cropping intensity hold big promise towards productivity enhancement. The promotion training and extension services using participatory approach of learning by doing or the farmer field schools are desirable to reduce the productivity gap.

Stock and Flow Diagram

The concept of stock–flow diagram was introduced in Chap. 2, and this chapter presents concepts, methodology and techniques of constructing stock–flow diagrams. The basic building blocks of the system structure, stock and flow, are explained. Delays and graphical functions are highlighted. Function with and without integrations is presented. A good number of examples are included to demonstrate the techniques of constructing the system structures in terms of stock–flow diagrams and simulation using the software STELLA.

Scenario Planning and Modelling

The models tested for building up confidence (as discussed in Chap. 6) should be used for scenario planning and modelling. This chapter presents scenario planning and modelling. Participatory system dynamics modelling and scenario planning are broadly discussed and the steps in scenario planning are highlighted. Also, policy planning for development strategy and implementation of development strategy and modelling are discussed. Some examples of scenario planning and modelling are presented.

Tests for Confidence Building

The models developed based on the concepts, methodology and techniques of system dynamics discussed in the earlier chapters must be tested to build up confidence in the models. This chapter presents the tests for confidence building in the system dynamics models. These tests are discussed under the broad heading of tests for structure, tests for behaviour and tests for policy implications. The logical sequences of conducting these testes are also presented.

Causal Loop Diagrams

The concept of causal loop diagram was introduced in Chap. 2, and this chapter presents concepts, methodology and techniques of causal loop diagrams. The cause–effect relationships and reinforcing and balancing loops are highlighted with examples. Steps to construct causal loop diagrams are provided. A good number of worked out examples are included to illustrate the techniques of constructing causal loop diagrams for dynamic systems.

Parameter Estimation and Sensitivity Analysis

The computer model based on stock–flow diagram discussed in Chap. 4 needs estimation of parameters and sensitivity analysis of the parameters. This chapter presents parameter estimation and sensitivity analysis. Parameter estimation using aggregated and disaggregated data are discussed. Estimation of table function, conversion factor and normal fractional flow rate is highlighted with examples. Sensitivity analysis and size of solution interval have been explained, and some examples of sensitivity analysis have been presented.

Modelling of Supply Chain of Rice Milling Systems in Bangladesh

In the previous chapters, case studies on system dynamics modelling of boom and bust of cocoa production systems in Malaysia, modelling of hilsa fish population in Bangladesh and modelling of food security in Malaysia have been presented. This chapter presents the application of system dynamics modelling to supply chain of rice milling systems to demonstrate how to construct system dynamics models and simulate these models for policy planning and design. The model presented is an illustration of modelling and simulation of practical problem to provide management scenarios and policy options, and such experiences are essential to face the challenge of modelling and simulation of dynamic systems in practice. To achieve these goals, the model of this case study is organised as follows: (1) introduction, (2) dynamic hypothesis, (3) causal loop diagram, (4) stock–flow diagram, (5) model validation, (6) simulation and policy analysis and (7) conclusion. The model is simulated to address supply chain management scenarios and design the policy options for efficient and sustainable supply chain management of rice milling systems in Bangladesh to ensure the availability of rice to the consumers in an economic manner under uncertainty. The model has the potential to identify and study the critical components of the overall supply chain, allowing for the creation of an efficient and sustainable network.

Modelling of Solid Waste Management Systems of Dhaka City in Bangladesh

In the previous chapters of this part, case studies on system dynamics modelling and simulation of some practical problems have been presented. This chapter presents a case study of environmental management of solid waste management system of Dhaka City, Bangladesh. The model of this case study is organised as (1) introduction, (2) dynamic hypothesis, (3) causal loop diagram, (4) stock–flow diagram, (5) model validation, (6) simulation and policy analysis and (7) conclusion to illustrate the system dynamics applications in environmental management based on systems thinking. Population, uncleared waste, untreated waste, composite index and public concern are projected to increase with time for Dhaka City. Simulated composts, CO2 total, CH4 and BOD from energy, leachate production and BOD from leachate over a period of 30 years are also presented. Simulated results also show that increasing the budget for collection capacity alone does not improve environmental quality; rather an increased budget is required for both collection and treatment of solid wastes of Dhaka City. This model can be used as a tool to assess and design policy options of solid waste management.

Modelling of Hilsa Fish (Tenualosa ilisha) Population in Bangladesh

In the previous chapter, the modelling and simulation of boom and bust of cocoa production systems in Malaysia have been presented. This chapter demonstrates how to construct a system dynamics model of hilsa fish and simulate the model for policy planning and design for sustainable development. The model presented in this chapter is organised as follows: (1) introduction, (2) dynamic hypothesis, (3) causal loop diagram, (4) stock–flow diagram, (5) model validation, (6) simulation and policy analysis and (7) conclusion to illustrate the system dynamics applications based on systems thinking. Such experiences are essential to face the challenge of modelling and simulation of dynamic systems. The model predicts the long-term trends in the hilsa population over several decades and assesses the impacts of harvesting the juveniles and spawning adults. Simulated results show that increased harvesting of the adults entering the rivers and the juveniles in the rivers cause gradual decline in hilsa fish population and even may cause this valuable resource to disappear within a short period of time. Also the optimal strategies for sustainable development of hilsa fish have been addressed.