International Science Index


The Application of Dynamic Network Process to Environment Planning Support Systems


In recent years, in addition to face the external threats such as energy shortages and climate change, traffic congestion and environmental pollution have become anxious problems for many cities. Considering private automobile-oriented urban development had produced many negative environmental and social impacts, the transit-oriented development (TOD) has been considered as a sustainable urban model. TOD encourages public transport combined with friendly walking and cycling environment designs, however, non-motorized modes help improving human health, energy saving, and reducing carbon emissions. Due to environmental changes often affect the planners’ decision-making; this research applies dynamic network process (DNP) which includes the time dependent concept to promoting friendly walking and cycling environmental designs as an advanced planning support system for environment improvements.

This research aims to discuss what kinds of design strategies can improve a friendly walking and cycling environment under TOD. First of all, we collate and analyze environment designing factors by reviewing the relevant literatures as well as divide into three aspects of “safety”, “convenience”, and “amenity” from fifteen environment designing factors. Furthermore, we utilize fuzzy Delphi Technique (FDT) expert questionnaire to filter out the more important designing criteria for the study case. Finally, we utilized DNP expert questionnaire to obtain the weights changes at different time points for each design criterion. Based on the changing trends of each criterion weight, we are able to develop appropriate designing strategies as the reference for planners to allocate resources in a dynamic environment. In order to illustrate the approach we propose in this research, Taipei city as one example has been used as an empirical study, and the results are in depth analyzed to explain the application of our proposed approach.

[1] Wey, Wann-Ming and Chiu, Yin-Hao, 2013. "Assessing the Walkability of Pedestrian Environment under the Transit-oriented Development”, Habitat International, Vol. 38, pp. 106-118.
[2] Cervero, R., Sarmiento, O. L., Jacoby, E., Gomez, L. F., and Neiman, A., 2009. Influences of Built Environments on Walking and Cycling: Lessons from Bogotá. International Journal of Sustainable Transportation, 3(4), 203-226.
[3] J. Korpela, M. Tuominen, Inventory forecasting with a multiple criteria decision tool, International Journal of Production Economics 45 (1–3) (1996) 159–168.
[4] A.R. Blair, R. Nachtmann, J.E. Olson, T.L. Saaty, Forecasting the exchange rates: an expert judgment approach, Socio-Economic Planning Sciences 21(6) (1987) 363–369.
[5] Hsu-Shih Shih, E. Stanley Lee, Shun-Hsiang Chuang, Chiau-Ching Chen, A forecasting decision on the sales volume of printers in Taiwan: An exploitation of the Analytic Network Process, Computers and Mathematics with Applications 64 (2012) 1545–1556.
[6] M.P. Niemira, T.L. Saaty, An analytic network process model for financial-crisis forecasting, International Journal of Forecasting 20 (4) (2004) 573–587.
[7] J. Korpela, M. Tuominen, Inventory forecasting with a multiple criteria decision tool, International Journal of Production Economics 45 (1–3) (1996) 159–168.
[8] S. Yuksel, An integrated forecasting approach to hotel demand, Mathematical and Computer Modelling 46 (7–8) (2007) 1063–1070.
[9] T.L. Saaty, Theory and Applications of the Analytic Network Process: Decision Making with Benefits, Opportunities, Cost, and Risks, RWS Publications, Pittsburgh, 2005.
[10] T.L. Saaty, Decision Making with Dependence and Feedback: The Analytic Network Process, RWS Publications, Pittsburgh, 1996.
[11] Saaty TL. Fundamentals of decision making and priority theory with the analytic hierarchy process. Pittsburgh, Pennsylvania: RWS Publications; 2006.
[12] Bell A, Ge K, Popkin B. 2002. The road to obesity or the path to preservation: Motorized transportation and obesity in China. Obesity Research 10(4):277–283.