Discussion and Responses
Supporting Policy Making
Policy-making in the twenty-first century has become a complex process due to the rapidly changing environment characterized by the copious data. Although policy intervention can be a costly and challenging process, contemporary technology can assist in improving the quality of decision-making. Computational power, social media, and the enormous amount of data available provide numerous opportunities for policy-makers in different fields to develop accurate strategies through various simulation methods and modelling approaches to create substantial value in different areas of the society including business and politics.
In an increasingly competitive world, simulation models are essential tools for analyzing complex data from diverse sources. There are several types of simulation models which work differently; therefore, helping policymakers in different sectors make informed decisions. They include social, computational, and systems modelling.
Social simulation modelling focuses on analyzing data from the social sciences, including psychology, law, and organizational behavior. In essence, the approach aims to support human reasoning through the help of a computer (Janssen, Wimmer, & Deljoo, 2015). On the other hand, computational simulation methods analyze digital information from computers using algorithms and equations to capture trends in behavior. More often, computational simulation is applied in physics, economics, healthcare, and engineering (Groesser & Jovy, 2016). Meanwhile, systems simulation modelling helps policymakers to study complex variables from real-world interactions. The information is processed through a comprehensive study of numeric data, which displays complex relationships within a system (Janssen et al., 2015). The three simulation models assist policymakers from different sectors to make an informed decision using accurate data studied and analyzed by computers.
In hindsight, technology has assisted policymakers in making accurate decisions regarding business, politics, and even social behavior using analyzed data. In addition, the application of the three simulation models may be applied in both small scale and large scale. To that end, which simulation model best applies to assist policymakers in improving a struggling economy?
Please incorporate more open ended questions in the discussion to challenge your peers and to add a little more value to the discussion forum
Discussion topic need to be written in 500 – 700 words with APA format. Need to respond at-least 2 peer students discussion topics
References
Groesser, S. N., & Jovy, N. (2016). Business model analysis using computational modelling: A strategy tool for exploration and decision-making. Journal of management control, 27 (1), 61-88.
Janssen, M., Wimmer, M. A., & Deljoo, A. (2015). Policy practice and digital science: Integrating complex systems, social simulation and public administration in policy research. New York, NY: Springer International Publishing.
Solution Preview
Policy Making and Computational Simulation
A struggling economy is an economy where growth is slow, declining or not growing at all. Factors affecting the growth of an economy can be a single component or all the components of the economy. Some of the economic factors that are possible elements affecting the growth and development of a given economy include inflation rates of employment, interest rates, changes in demography, fiscal and financial policies of determining the competitive state of environments which organisations operate. These economic forces impact either negatively or positively on the resulting outcomes of organizations marketing actions by defining the magnitudes and strengths of the demand of the organization’s products.
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