Calls for Papers (special): International Journal of Public Administration in the Digital Age (IJPADA)


Special Issue On: Research in Political Engineering, Public Policy Engineering, Computational Politics, and Computational Public Policy

Submission Due Date
12/31/2017

Guest Editors
Ashu M. G. Solo, Maverick Technologies America Inc., USA

Introduction
Ashu M. G. Solo originated and defined the fields of political engineering, computational politics, public policy engineering, and computational public policy in Solo (2011) and elaborated on these fields in Solo (2014a, 2014b). Basic and advanced methods in engineering, computer science, mathematics, or natural science can be used for political decision making, analysis, modeling, optimization, forecasting, simulation, and expression as well as for public policy formulation, decision making, analysis, modeling, optimization, forecasting, and simulation. This will lead to greatly improved political decision making and public policy.

Political engineering is the application of engineering, computer science, mathematics, or natural science to solving problems in politics. Computational politics is the application of computer science or mathematics to solving problems in politics. Therefore, computational politics is a subset of political engineering. Political engineering and computational politics include, but are not limited to, principles and methods for political decision making, political analysis, political modeling, political optimization, political forecasting, political simulation, and political expression. Political engineering and computational politics are more technically, computationally, mathematically, and scientifically rigorous approaches to the field of political science.

Public policy engineering is the application of engineering, computer science, mathematics, or natural science to solving problems in public policy. Computational public policy is the application of computer science or mathematics to solving problems in public policy. Therefore, computational public policy is a subset of public policy engineering. Public policy engineering and computational public policy include, but are not limited to, principles and methods for public policy formulation, public policy decision making, public policy analysis, public policy modeling, public policy optimization, public policy forecasting, and public policy simulation. Public policy engineering and computational public policy are more technically, computationally, mathematically, and scientifically rigorous approaches to the field of public policy.

The term political engineering has been previously used to refer to designing political institutions. This is an abuse of the word engineering. As it has been previously used, the term political engineering does not require the creative application or development of mathematics, natural science, technical principles, or technical methods. Therefore, Ashu M. G. Solo has given a new and more appropriate definition to the term political engineering. Just like many terms in the dictionary have multiple meanings, the term political engineering can have multiple meanings.

Politicians often determine how to spend limited campaign funds on advertising in certain geographic areas based on their best guesses rather than on a rigorous mathematical and computational analysis of how funds should be allocated for the greatest benefit to their campaigns. Legislators usually determine spending priorities and budget allocations based on passions of the moment, special interest lobbying, parochial interests, ignorant public opinion, or their own ideological biases rather than on a rigorous mathematical and computational analysis of how spending priorities and budget allocations can be made for the greatest public benefit.

An example of political engineering and computational politics is determining the optimal allocation of election campaign funds or campaign resources. The 2012 presidential campaign of President Barack Obama made extensive use of data analytics (Scherer, 2012). An example of public policy engineering and computational public policy is the use of fuzzy logic to effectively quantify the values and beliefs of stakeholders and interested parties, environmental conditions, economic conditions, and social conditions to produce a much better environmental impact assessment (Shepard, 2005).

The definition of the new interdisciplinary fields of public policy engineering, computational public policy, political engineering, and computational politics will greatly increase the pace of research and development in these extremely important fields. Also, they establish new fields of study for universities for students who are interested in engineering, computer science, mathematics, natural science, politics, or public policy. Political engineering, computational politics, public policy engineering, and computational public policy are critical for the future success of politics and public policy. Click on the hyperlinks in the references (Solo, 2011; Solo, 2014a; Solo, 2014b) below for further information on public policy engineering, computational public policy, political engineering, and computational politics.

Objective
Although Ashu M. G. Solo defined and originated the fields of public policy engineering, political engineering, computational public policy, and computational politics (Solo, 2011; Solo, 2014a; Solo 2014b) to motivate more technically, computationally, mathematically, and scientifically rigorous approaches to public policy and politics and to establish new fields of study, there has been some research in these fields. This special issue of the International Journal of Public Administration in the Digital Age (IJPADA) will focus on research that has been done in the fields of political engineering, computational politics, public policy engineering, and computational public policy.

Recommended Topics
Recommended topics for this special issue include, but are not limited to, the following:
  • Political Decision Making, Analysis, Modeling, Optimization, Forecasting, Simulation, and Expression
    • political decision making under uncertainty
    • new technologies in politics
    • application of engineering to politics
    • application of computer science to politics
    • application of mathematics to politics
    • application of natural science to politics
    • application of operations research to politics
    • application of optimization methods to politics
    • uncertainty management in political decision making
    • application of computational intelligence methods to politics
    • application of fuzzy logic to politics
    • application of neural computing to politics
    • application of neural networks to politics
    • application of evolutionary computation to politics
    • application of genetic algorithms to politics
    • application of knowledge-based systems to politics
    • application of machine learning methods to politics
    • application of pattern recognition to politics
    • application of data mining to politics
    • application of analytics to politics
    • application of data integration to politics
    • application of data analysis to politics
    • application of data modeling to politics
    • application of exploratory data analysis to politics
    • application of confirmatory data analysis to politics
    • application of predictive analytics to politics
    • application of text analytics to politics
    • application of statistics to politics
    • application of data visualization to politics
    • application of data dissemination to politics
    • data-driven decision making in politics
    • application of data fusion to politics
    • application of multidimensional matrix mathematics to politics
    • application of decision theory to politics
    • application of game theory to politics
    • application of graph theory to politics
    • political forecasting
    • political modeling
    • political simulation
    • political visualization
    • political software tools
    • political campaign software tools
    • case studies

  • Public Policy Formulation, Decision Making, Analysis, Modeling, Optimization, Forecasting, and Simulation
    • public policy decision making under uncertainty
    • new technologies in public policy
    • application of engineering to public policy
    • application of computer science to public policy
    • application of mathematics to public policy
    • application of natural science to public policy
    • application of operations research to public policy
    • application of optimization methods to public policy
    • uncertainty management in public policy decision making
    • application of computational intelligence methods to public policy
    • application of fuzzy logic to public policy
    • application of neural computing to public policy
    • application of neural networks to public policy
    • application of evolutionary computation to public policy
    • application of genetic algorithms to public policy
    • application of knowledge-based systems to public policy
    • application of machine learning methods to public policy
    • application of pattern recognition to public policy
    • application of data mining to public policy
    • application of analytics to public policy
    • application of data integration to public policy
    • application of data analysis to public policy
    • application of data modeling to public policy
    • application of exploratory data analysis to public policy
    • application of confirmatory data analysis to public policy
    • application of predictive analytics to public policy
    • application of text analytics to public policy
    • application of statistics to public policy
    • application of data visualization to public policy
    • application of data dissemination to public policy
    • data-driven decision making in public policy
    • application of data fusion to public policy
    • application of multidimensional matrix mathematics to public policy
    • application of decision theory to public policy
    • application of game theory to public policy
    • application of graph theory to public policy
    • public policy forecasting
    • public policy modeling
    • public policy simulation
    • public policy visualization
    • public policy software tools
    • case studies


    Submission Procedure
    Researchers and practitioners are invited to submit abstract proposals by August 31, 2017 and full papers by December 31, 2017 for this special theme issue on Research in Political Engineering, Public Policy Engineering, Computational Politics, and Computational Public Policy. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. The author(s) of each submitted paper will be asked to review two other papers. Reviewers will be acknowledged in the special issue. Papers must follow APA style for reference citations.

    Important Dates
    August 31, 2017: Abstract proposal (one paragraph) submission deadline
    September 15, 2017: Abstract proposal acceptance notification
    December 31, 2017: Full research paper submission deadline
    March 31, 2018: Peer review results
    May 31, 2018: Final research paper submission deadline
    June 15, 2018: Final acceptance notification

    All submissions and inquiries should be directed to the attention of:
    Ashu M. G. Solo
    Email: amgsolo@mavericktechnologies.us
    Guest Editor
    International Journal of Public Administration in the Digital Age (IJPADA)

    References
    Scherer, M. (2012). Inside the Secret World of the Data Crunchers Who Helped Obama Win. Time. November 7, 2012. Available at http://swampland.time.com/2012/11/07/inside-the-secret-world-of-quants-and-data-crunchers-who-helped-obama-win/

    Shepard, R. B. (2005). Quantifying Environmental Impact Assessments Using Fuzzy Logic. New York: Springer. Available at http://www.springer.com/us/book/9780387243986 Shepard, R. B. (2005). Quantifying Environmental Impact Assessments Using Fuzzy Logic. New York: Springer. Available at http://www.springer.com/us/book/9780387243986

    Solo, A. M. G. (2011). The New Fields of Public Policy Engineering, Political Engineering, Computational Public Policy, and Computational Politics. In Proceedings of the 2011 International Conference on e-Learning, e-Business, Enterprise Information Systems, and e-Government (EEE'11) (pp. 431-434). Available at http://worldcomp-proceedings.com/proc/p2011/EEE5211.pdf

    Solo, A. M. G. (2014a). The New Interdisciplinary Fields of Political Engineering and Computational Politics. In A. M. G. Solo (Ed.), Political Campaigning in the Information Age (pp. 226-232). Hershey, Penn.: IGI Global. Available at http://www.igi-global.com/chapter/the-new-interdisciplinary-fields-of-political-engineering-and-computational-politics/109123

    Solo, A. M. G. (2014b). The New Interdisciplinary Fields of Public Policy Engineering and Computational Public Policy. In A. M. G. Solo (Ed.), Political Campaigning in the Information Age (pp. 233-238). Hershey, Penn.: IGI Global. Available at http://www.igi-global.com/chapter/the-new-interdisciplinary-fields-of-public-policy-engineering-and-computational-public-policy/109124