Analysis of Young People’s Attitudes toward Mutual Aid Support System in Local Community Using Sensitivity Analysis of Bayesian Network

  • Shimpei Matsumoto Hiroshima Institute of Technology
  • Nobuyuki Ohigashi Hiroshima Institute of Technology
Keywords: vulnerable road users, resource-sharing, mutual assistance, local community activation, Bayesian network, sensitivity analysis


We have shown the concept of an information-sharing system to support vulnerable road users living in the suburban slope residential areas where public transport is scarce. Then we also have constructed a web service to support their daily life named MASS. The role of MASS is to facilitate the encounter between local community people and to provide the opportunity of resource sharing for solving the difficulties in daily life by mutual assistance. To effectively solve the problems of vulnerable road users, mainly older people with MASS, young people’s active participation is essential because most of the resources of skills will be provided by young people. Therefore, to discuss our system’s continuity as a general service, the previousresearch has conducted an attitude survey on young people’s awareness of resource sharing in their local community and analyzed it with Bayesian networks. From the analysis, the previous research has shown the relationship between the factors, which are not clarified so far, and obtained results that support several hypotheses. However, the previous research has analyzed only the results of evaluating MASS from a subjective view and has not dealt with the survey results of evaluating MASS from an objective viewpoint. Furthermore, each explanatory variable’s strength concerning the objective variable (each one’s evaluation about MASS) was not sufficiently clear. This study aims to analyze the sensitivity of each explanatory variable for the objective variable in the constructed model of Bayesian networks and perform inference using the model. From the experiment, we were able to clarify the strength of each explanatory variable quantitatively.


N. Ohigashi, A. Tanaka and S. Watanabe, Traffic Awareness Investigation by Questionary Survey in Housing Complexs, Research bulletin of the Hiroshima Institute of Technology, Vol.43,pp.113-117 (2009), In Japanese.

N. Ohigashi and S. Matsumoto, Research on the Possibility of Riding-together Traffic in Residential Estates, Bulletin of Hiroshima Institute of Technology, Research, Vol.49, pp.19-22 (2015), In Japanese.

S. Matsumoto and N. Ohigashi, Examining an Effective Way to Support Vulnerable Road Users in Itsukaichi District, Hiroshima City, Information Engineering Express, Special issue on Business Management of Technology, Vol.2, No.3, pp.43-52 (2016).

S. Matsumoto, N. Ohigashi, T. Hasuike, Developing a Transportation Support System for Vulnerable Road Users in Local Community, Proc. of 2016 5th IIAI International Congress on Advanced Applied Informatics, pp.797-800 (2016).

S. Matsumoto, N. Ohigashi and T. Hasuike, Design and Development of a Web Service to Support Daily Life of Vulnerable Road Users in Suburban Residential Estates in Hiroshima City, Proc. of 2017 6th IIAI International Congress on Advanced Applied Informatics, In USB (2017).

D. Demailly, A. Novel, The sharing economy: make it sustainable. Studies, (03/14), 30 (2014).

J. Hamari, M. Sjoklint, A. Ukkonen, The sharing economy: Why people participate in collaborative consumption. Journal of the Association for Information Science and Technology, (2015).

S. Matsumoto, N. Ohigashi, T. Hasuike, Livelihood Assistance System for Vulnerable Road Users in Suburban Residential Areas based on Mutual Assistance, International Journal of Service and Knowledge Management, ISSN: 2189-9231, Vol 1, No 2, pp.13-31 (2017).

T. Dillahunt, A. Malone, The promise of the sharing economy among disadvantaged communities. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, pp.2285-2294. ACM (2015).

D. Rauch, D. Schleicher, Like uber, but for local government law: The future of local regulation of the sharing economy. Ohio St. LJ, 76, 901 (2015).

D. Wosskow, Unlocking the sharing economy: An independent review (2014).

S. Denning, An economy of access is opening for business: five strategies for success. Strategy & Leadership, 42(4), pp.14-21 (2014).

A. Andreotti, G. Anselmi, T. Eichhorn, C. Hoffmann, M. Micheli, Participation in the Sharing Economy, Report from the EU H2020 Research Project Ps2Share: Participation, Privacy, and Power in the Sharing Economy (2017).

S. Matsumoto, N. Ohigashi, Attitude Survey of Young People to Examine the Usefulness of a Skill Sharing Web Service for Regional Vulnerable Road Users, Proceeding of 7th International Congress on Advanced Applied Informatics, pp.724-729 (2018).

S. Matsumoto, N. Ohigashi, Analyzing Young People’s Awareness for Mutual Assistance Support System with Bayesian Network, Proceeding of 8th International Congress on Advanced Applied Informatics, pp.762-767 (2019).

S. Russell, P. Norvig :“ Artificial Intelligence A Modern Approach ”, Prentice Hall Series in Artificial Intelligence (1995)

R. E. Neapolitan : ”Learning Bayesian Networks ”, Artificial Intelligence, Prentice Hall (2004)

J. Pearl, Probabilistic Reasoning in Intelligent Systems, Networks of Plausible Inference (2nd ed.), San Francisco, CA: Morgan Kaufmann (1988).

M. Yasuda, S. Kataoka, K. Tanaka, Stochastic graphical models: Bayesian networks and their environs, Operations research as a management science research, 58(4), pp.191-197 (2013), In Japanese.

J. Pearl, Bayesian Networks: a Model of Self-Activated Memory for Evidential Reasoning, Proc of Cognitive Science Society, pp.329-334 (1985).

F. Jensen, An Introduction to Bayesian networks, University College London Press (1996).

E. Castillo, J. Gutierrez, and A.Hadi, Expert systems and probabilistic network models, Springer-Verlag (1997).

R. Cowell, A. Dawid, S. Lauritzen, and D. Spiegelhalter, Probabilistic Networks and Expert Systems, Springer-Verlag (1999).

Y. Motomura, Bayesian Network Softwares, Journal of the Japanese Society for Artificial Intelligence, Vol.17, No.5, pp.559-565 (2002).

Technical Papers