Applying OR Theory and Techniques to Social Systems Analysis

  • Tatsuo Oyama
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 225)


The paper describes applications of Operations Research (OR) theory and techniques used to solve various types of social problems occurring in our social system. Social systems analysis has for quite some time been the main analytical and scientific approach used to investigate systems and to solve various problems related to modern social systems, including industry, business, the military, public administration, politics, and society in general. We will present here three major roles that operations research (OR) and social systems analysis (SSA) technique have played both practically and theoretically in the solution of social systems problems since it was developed almost 60 years ago. Firstly, we explain briefly OR, SSA, and public policy (PP) regarding what they are, how OR can be contributing to SSA and PP, and how traditional academic disciplines are related each other with the SSA. Secondly, we introduce several examples of the quantitative data analysis, which we have investigated in our school (National Graduate Institute for Policy Studies) to solve various types of social problems including population, traffic and accident, higher education policy, energy policy, and agriculture policy data analyses. Thirdly, we give mathematical modeling analysis with its application to the optimal location model analysis for integrating promotion branch offices in the local government. Fourthly, as an important role of OR as a theory building analysis technique, we explain two problems of apportionment problem and shortest path counting problem. Finally, in the summary section future perspectives of OR are given.


Operations research Social systems analysis Public policy Quantitative data analysis Mathematical modeling analysis Apportionment problem Shortest path counting problem 


  1. 1.
    Miwa, M., Gozun, B., Oyama, T.: Statistical data analyses to elucidate the causes and improve the countermeasures for preventing train accidents in Japan. Int. Trans. Oper. Res. IFORS 13(3), 229–251 (2006)Google Scholar
  2. 2.
    Oyama, T., Miwa, M.: Investigating serious train accidents and natural disaster data in Japan. Commun. Oper. Res. Oper. Res. Soc. Jpn. 53(10), 11–17 (2008) (in Japanese)Google Scholar
  3. 3.
    Anwar, S., Oyama, T.: Statistical data analysis for investigating government subsidy policy for private universities. J. High. Educ. (Springer) 55(4), 407–423 (2007). On line ISSN 1573-174XGoogle Scholar
  4. 4.
    Srivastava, D.C., Oyama, T.: Evaluating the emission reduction targets in UNFCCC Kyoto protocol by applying primary energy data analyses. J. Asian Public Policy 2(1), 36–56 (2009)CrossRefGoogle Scholar
  5. 5.
    Yoshii, K., Oyama, T.: A quantitative factorial component analysis to investigate the recent changes of Japan’s weight-based food self-sufficiency ratio. Am. J. Oper. Res. 6(1), 44–60 (2016)CrossRefGoogle Scholar
  6. 6.
    Ojima, J., Oyama, T.: Index gap minimization model analyses for local promotion branches of Iwate Prefecture. Commun. Oper. Res. Oper. Res. Soc. Jpn. 48(8), 567–573 (2003) (in Japanese)Google Scholar
  7. 7.
    Miwa, M., Oyama, T.: All-integer type linear programming model analyses for the optimal railway track maintenance scheduling. Oper. Res. Soc. India OPSEARCH 41(3), 35–45 (2004)Google Scholar
  8. 8.
    Oyama, T., Miwa, M.: Mathematical modeling analyses for obtaining an optimal railway track maintenance schedule. Jpn. J. Ind. Appl. Math. 23(2), 207–224 (2006)MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Oyama, T.: On a parametric divisor method for the apportionment problem. J. Oper. Res. Soc. Jpn. 34(2), 187–221 (1991)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Oyama, T., Ichimori, T.: On the unbiasedness of the parametric divisor method for the apportionment problem. J. Oper. Res. Soc. Jpn. 38(3), 301–321 (1995)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Oyama, T., Morohoshi, H.: Applying the shortest path counting problem to evaluate the importance of city road segments and the connectedness of the network-structured system. Int. Trans. Oper. Res. 11(5), 555–574 (2004)MathSciNetCrossRefzbMATHGoogle Scholar
  12. 12.
    Kobayashi, K., Morohosi, H., Oyama, T.: Applying path-counting methods for measuring the robustness of the network-structured system. Int. Trans. Oper. Res. IFORS 16(3), 371–389 (2009)Google Scholar
  13. 13.
    Nemhauser, G.L., Rinnooy Kan, A.H.G.: Handbooks in Operations Research and Management Science. North-Holland, Amsterdam, Netherland (1994) (trans. Oyama, T.: Koukyou Seisaku OR, 776 pp. Asakura Shoten Publishing Co., 1998)Google Scholar
  14. 14.
    Oyama, T.: Saitekika moderu bunseki (Optimization Model Analyses), 372 pp. Nikka Giren Publishing Co. (1993) (in Japanese)Google Scholar
  15. 15.
    Oyama, T.: Mathematical programming model analyses and basic formulation techniques. Commun. Oper. Res. Oper. Res. Soc. Jpn. 43(2), 71–75 (1998) (in Japanese)Google Scholar

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© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.National Graduate Institute for Policy StudiesTokyoJapan

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