Understanding Complexities in Public Policy Making Process Through Policy Cycle Model: A System Dynamics Approach

Subroto, Athor

doi:10.2139/ssrn.1992756

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…Obejmuje etapy od identyfi kacji problemu przez analizę polityki i jej instrumentów, konsultacje, koordynację, aż do podjęcia decyzji, wdrożenia i ewaluacji [Freeman i in., 2011]. Poszerzenie ich założeń to także propozycja Meredith Edwards [Subroto, 2012], która model ten określa jako ramy rozwoju polityk, uznając, że są one najbardziej użytecznym narzędziem w procesie rozwiązywania problemów.…”

Section: Zarządzanie Polityką Publiczną Z Uwzględnieniem Jej Złożonościunclassified

Złożoność polityki publicznej – wyzwania w jej tworzeniu i realizacji

Głogowski¹

2018

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The complexity of public policies-the challenge of creation and implementation One of the biggest challenge is to understand the complexity of problems that are implemented by public policies. Therefore, it is necessary to apply public policies that will be complex themselves to resolve complex issues. The aim of the article is to indicate the key factors that will help to better understand this challenge and the issue of the complexity of problems in public policies. Based on the literature analysis, I point out a few key elements (i.e., culture, economics, politics or actors), which are the basis for building public policies and creating a conceptual framework for managing them.

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Section: Zarządzanie Polityką Publiczną Z Uwzględnieniem Jej Złożonościunclassified

Złożoność polityki publicznej – wyzwania w jej tworzeniu i realizacji

Głogowski¹

2018

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“…System Dynamics models are used to analyze quantitative scenarios, or projections, of possible future patterns emerging from a system, including impacts of external interventions on a system’s behavior in the short, medium and long term (Barlas, 2002; Richardson, 1991). In particular, the explicit representation of delays, feedback loops and non-linearities in the model structure allows exploring synergies and trade-offs between the different system elements over time and thereby provides valuable decision-making support (Fredericks, 2008; Subroto, 2012). Due to their integrated nature, System Dynamics models are particularly appropriate for analyzing and addressing complex issues in public policy sectors, such as health (Homer, Hirsch, Minniti, & Pierson, 2004; Homer et al, 2000), energy (Bassi, Schoenberg, & Powers, 2010; Trappey, Trappey, Lin, & Chang, 2011), green economy, climate change and sustainable development (Fiddaman, 2002; UNEP, 2011).…”

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Waterstory Ile

Bassi

Rego²,

Harrisson³

et al. 2015

Simulation & Gaming

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Background: Sustainable management of the municipal water supply is a priority issue in the policy agenda of Maui County, Hawaii. The Maui Economic Development Board launched the WaterStory initiative to educate residents about the determinants and history of Maui’s water resource development. A System Dynamics model was developed and coupled with a user interface to create WATERSTORY, an interactive learning environment (ILE). Purpose: The purpose of this study was to analyze the benefits of WATERSTORY for the identification and assessment of sustainable water management policies in Maui. Method: WATERSTORY is a System Dynamics-based ILE that shows the cross-sectoral impacts of users’ decisions. Both, the simulation model and the ILE resulted from group modeling and ILE testing sessions. Results: The development of the WATERSTORY ILE facilitated the involvement of local communities in the discussion of water management problems and identification of possible solutions. Conclusions: The study suggests that developing a simple ILE is essential in raising the interest of a wide audience involved in sustainable development policy making. After stakeholders gain confidence in the benefit of the ILE, it becomes easier to integrate simulation exercises into planning processes at national, regional and local levels.

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Public Policymaking Framework Based on System Dynamics and Big Data

Nasution

Bazin

Rosalyn³

et al. 2018

International Journal of System Dynamics Applications

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In the process of public policymaking, it is recommended to use system dynamics (SD) and Big Data in e-government. SD could assist in viewing problems in complex system holistically, while Big Data in e-government is for collecting data and information which are used for developing model of system dynamics and its equations. On this occasion, partial least square – structural equation modeling (PLS-SEM) is used to validate the relationship between public policymaking (PP), system dynamics (SD) and Big Data in the e-government. Brief explanation about survey and PLS-SEM are discussed. Some of the statistic parameters, such as path coefficients or beta coefficients, P values, R Square coefficients and effect size are shared and analyzed. These terms are parameters for us to see how strong the relationship between PP, SD and Big Data.

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Understanding Complexities in Public Policy Making Process Through Policy Cycle Model: A System Dynamics Approach

Cited by 3 publications

References 2 publications

Złożoność polityki publicznej – wyzwania w jej tworzeniu i realizacji

Złożoność polityki publicznej – wyzwania w jej tworzeniu i realizacji

Waterstory Ile

Public Policymaking Framework Based on System Dynamics and Big Data

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