Modeling dynamicity of willingness to pay mechanism in the case of special assessment district
Abstract
A new public project usually provides economic benefits to property owners. In general, a delay caused by a government budget shortage proportionally reduces the future cash flow of the private developer potentially benefitted from a new public project. Based on that eventuality, this study examines a mechanism of willingness to pay, which asks private developers to voluntarily participate in sharing the budget shortage. This participation process is investigated by applying system dynamics, which demonstrate several causal loops, such as between the delay cause and the reaction of the private developer. In spite of difficulty in predicting the actual effect of this idea due to its conceptual origin, this innovative approach can contribute to real-world exigencies in two ways: the provision of background for research on the on-time completion of public projects via private developer cost-sharing participation and the illustration of an alternative that minimizes private developers’ future revenue deduction caused by delays.
First published online 23 June 2020
Keyword : system dynamics, public development delay, Net Present Value, private developer’s cost sharing, financing alternatives, willingness to pay, special assessment district
How to Cite
Bae, D. S. ., & Kim, S. (2020). Modeling dynamicity of willingness to pay mechanism in the case of special assessment district. International Journal of Strategic Property Management, 24(4), 285-299. https://doi.org/10.3846/ijspm.2020.12881
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Hoyt, L., & Gopal‐Agge, D. (2007). The business improvement district model: a balanced review of contemporary debates. Geography Compass, 1(4), 946−958. https://doi.org/10.1111/j.1749-8198.2007.00041.x
Hussain, S., Zhu, F., & Ali, Z. (2019). Examining influence of construction projects’ quality factors on client satisfaction using partial least squares structural equation modeling. Journal of Construction Engineering and Management, 145(5). https://doi.org/10.1061/(ASCE)CO.1943-7862.0001655
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Hwang, S., Park, M., & Lee, H.-S. (2013). Dynamic analysis of the effects of mortgage-lending policies in a real estate market. Mathematical and Computer Modelling, 57(9−10), 2106−2120. https://doi.org/10.1016/j.mcm.2011.06.023
Kane, K., & Weber, R. (2015). Municipal investment and property value appreciation in Chicago’s tax increment financing districts. Journal of Planning Education and Research, 36(2), 167−181. https://doi.org/10.1177/0739456X15600034
Karna, S., Junnonen, J., & Sorvala, V. (2009). Modelling structure of customer satisfaction with construction. Journal of Facilities Management, 7(2), 111−127. https://doi.org/10.1108/14725960910952505
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Kirkkaleli, D., Athari, S. A., & Ertugrul, H. M. (2017). The real estate industry in Turkey: a time series analysis. The Service Industries Journal, 1−13. https://doi.org/10.1080/02642069.2018.1444033
Maqbool, R. (2018). Efficiency and effectiveness of factors affecting renewable energy projects; an empirical perspective. Energy, 158(1), 944−956. https://doi.org/10.1016/j.energy.2018.06.015
Mathur, S. (2014). Funding public transportation through special assessment districts: addressing the equity concerns. Public Works Management & Policy, 20(2), 127−145. https://doi.org/10.1177/1087724X14550252
Moxnes, E. (1990). System dynamics and decisions under uncertainty. Paper presented at the Proceedings of the International System Dynamics Conference.
Munnell, A. H. (1992). Infrastructure investment and economic growth. Journal of Economic Perspectives, 6(4), 189−198. https://doi.org/10.1257/jep.6.4.189
Munoz-Gielen, D. (2012). Urban governance, property rights, land readjustment and public value capturing. European Urban and Regional Studies, 21(1), 60−78. https://doi.org/10.1177/0969776412440543
Ploth, P. M. (2015). What’s taking so long? Identifying the underlying causes of delays in planning transportation megaprojects in the United States. Journal of Planning Literature, 30(3), 282−295. https://doi.org/10.1177/0885412214566116
Qi, C., & Chang, N.-B. (2011). System dynamics modeling for municipal water demand estimation in an urban region under uncertain economic impacts. Journal of Environmental Management, 92(6), 1628−1641. https://doi.org/10.1016/j.jenvman.2011.01.020
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Rolon, A. (2008). Evaluation of value capture mechanisms from linkage capture to special assessment districts. Transportation Research Record: Journal of the Transportation Research Boar, 2079(1), 127−135. https://doi.org/10.3141/2079-16
Salon, D., & Shewmake, S. (2011). Opportunities for value capture to fund public transport: a comprehensive review of the literature with a focus on East Asia. https://doi.org/10.2139/ssrn.1753302
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Sterman, J. D. (2001). System dynamics modeling: tools for learning in a complex world. California Management Review, 43(4), 8−25. https://doi.org/10.2307/41166098
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Vlachos, D., Georgiadis, P., & Iakovou, E. (2007). A system dynamics model for dynamic capacity planning of remanufacturing in closed-loop supply chains. Computers & Operations Research, 34(2), 367−394. https://doi.org/10.1016/j.cor.2005.03.005
Wang, F. Y., Zhang, J. J., Zheng, X., Wang, X., Yuan, Y., Dai, X., & Yang, L. (2016). Where does AlphaGo go: from church-turing thesis to AlphaGo thesis and beyond. IEEE/CAA Journal of Automatica Sinica, 3(2), 113−120. https://doi.org/10.1109/JAS.2016.7471613
Weber, R., Bhatta, S. D., & Merriman, D. (2007). Spillovers from tax increment financing districts: implications for housing price appreciation. Regional Science and Urban Economics, 37, 259−281. https://doi.org/10.1016/j.regsciurbeco.2006.11.003
Xu, Z., & Coors, V. (2012). Combining system dynamics model, GIS and 3D visualization in sustainability assessment of urban residential development. Building and Environment, 47, 272−287. https://doi.org/10.1016/j.buildenv.2011.07.012
Bae, D. S., & Damnjanovic, I. (2018a). Credit risk assessment and monitoring of TIF bonds. The Journal of Structured Finance, 23(4), 57−68. https://doi.org/10.3905/jsf.2018.2018.1.062
Bae, D. S., & Damnjanovic, I. (2018b). Practical applications of credit risk assessment and monitoring of TIF bonds. Practical Applications, 6(2), 1−6. https://doi.org/10.3905/pa.6.2.285
Bae, D. S., Damnjanovic, I., & Kang, D. H. (2019). PPP renegotiation framework based on equivalent NPV constraint in the case of BOT project: Incheon Airport highway, South Korea. KSCE Journal of Civil Engineering, 23(4), 1473−1483. https://doi.org/10.1007/s12205-019-1444-9
Barlas, Y. (2007). System dynamics: Ystemic feedback modeling for policy analysis. http://www.friends-partners.org/utsumi/Global_University/Global%20University%20System/List%20Distributions/2011/MTI2233_20110311/SYSTEM%20DYNAMICS_%20SYSTEMIC%20FEEDBACK%20MODELING%20FOR%20POLICY%20ANALYSIS%20copy/SYS
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Business Wire. (2016). Fitch Rates Fairfax County, VA Econ. Dev. Auth. Revs ‘AA’; Outlook Stable. https://www.businesswire.com/news/home/20160219006017/en/Fitch-Rates-Fairfax-County-VA-Econ.-Dev
CBRE. (2018). CBRE North America cap rate survey: second half 2018. http://cbre.vo.llnwd.net/grgservices/secure/North%20America%20Cap%20Rate%20Survey_H2%202018_s.pdf?e=1592906262&h=a8e0fa89b43b9fed02c90721204eb983
Chen, J. (2018). Capitalization rate. https://www.investopedia.com/terms/c/capitalizationrate.asp
Coleman, A., & Grimes, A. (2010). Betterment taxes, capital gains and benefit cost ratios. Economics Letters, 109(1), 54−56. https://doi.org/10.1016/j.econlet.2010.08.012
Connolly, C., & Wall, A. (2016). Value capture: a valid means of funding PPPs? Financial Accontability & Management, 32(2), 157−178. https://doi.org/10.1111/faam.12083
Cui, Q. (2009). Systems analysis of project cash flow management strategies. Construction Management and Economics, 28(4), 361−376. https://doi.org/10.1080/01446191003702484
Čeh, M., Kilibarda, M., Lisec, A., & Bajat, B. (2018). Estimating the performance of random forest versus multiple regression for predicting prices of the apartments. International Journal of Geo-Information, 7(5), 168. https://doi.org/10.3390/ijgi7050168
Dulles Corridor Metrorail Project. (2019). Funding. http://www.dullesmetro.com/about-dulles-rail/funding/
Dungan, P. (2014). The Silver Line story: a new route is born after decades of faulty planning, political paralysis. https://www.washingtonpost.com/local/trafficandcommuting/the-silver-line-story-a-new-route-is-born-after-decades-offaulty-planning-political-paralysis/2014/06/23/bdf619c4-f894-11e3-a606-946fd632f9f1_story.html?utm_term=.cc7cd6e0a595
Enoch, M., Potter, S., & Ison, S. (2010). A strategic approach to financing public transport through property values. Public Money & Management, 25(3), 147−154. https://doi.org/10.1111/j.1467-9302.2005.00467.x
Escobari, D., Damianov, D. S., & Bello, A. (2015). A time series test to identify housing bubbles. Journal of Economics and Finance, 39(1), 136−152. https://doi.org/10.1007/s12197-013-9251-5
FHWA. (2018). Silver Line/Dulles Metrorail, Northern Virginia (Webster Rail) - B. https://www.fhwa.dot.gov/ipd/pdfs/value_capture/webster_rail_b.pdf
Franco, E. F., Hirama, K., & Carvalho, M. (2018). Applying system dynamics approach in software and information system projects: a mapping study. Information and Software Technology, 93, 58−73. https://doi.org/10.1016/j.infsof.2017.08.013
Funderburg, R. (2019). Regional employment and housing impacts of tax increment financing districts. Regional Studies, 53(6), 874−886. https://doi.org/10.1080/00343404.2018.1490013
Henden, K. (1994). System dynamics underwood. Paper presented at the International System Dynamics Conference.
Hovmand, P. S., & Ford, D. N. (2009). Sequence and timing of three community interventions to domestic violence. American Journal of Community Psychology, 44(261). https://doi.org/10.1007/s10464-009-9264-6
Hoyt, L., & Gopal‐Agge, D. (2007). The business improvement district model: a balanced review of contemporary debates. Geography Compass, 1(4), 946−958. https://doi.org/10.1111/j.1749-8198.2007.00041.x
Hussain, S., Zhu, F., & Ali, Z. (2019). Examining influence of construction projects’ quality factors on client satisfaction using partial least squares structural equation modeling. Journal of Construction Engineering and Management, 145(5). https://doi.org/10.1061/(ASCE)CO.1943-7862.0001655
Hussain, S., Zhu, F., Ali, Z., Aslam, H. D., & Husssain, A. (2018). Critical delaying factors: public sector building projects in Gilgit-Baltistan, Pakistan. Buildings, 8(1), 6. https://doi.org/10.3390/buildings8010006
Hussain, S., Zhu, F., Ali, Z., & Xu, X. (2017). Rural residents’ perception of construction project delays in Pakistan. Sustainability, 9(11), 2108. https://doi.org/10.3390/su9112108
Hwang, S., Park, M., & Lee, H.-S. (2013). Dynamic analysis of the effects of mortgage-lending policies in a real estate market. Mathematical and Computer Modelling, 57(9−10), 2106−2120. https://doi.org/10.1016/j.mcm.2011.06.023
Kane, K., & Weber, R. (2015). Municipal investment and property value appreciation in Chicago’s tax increment financing districts. Journal of Planning Education and Research, 36(2), 167−181. https://doi.org/10.1177/0739456X15600034
Karna, S., Junnonen, J., & Sorvala, V. (2009). Modelling structure of customer satisfaction with construction. Journal of Facilities Management, 7(2), 111−127. https://doi.org/10.1108/14725960910952505
Kenton, W. (2018). American recovery and reinvestment act. Investopedia. https://www.investopedia.com/terms/a/american-recovery-and-reinvestment-act.asp
Kirkkaleli, D., Athari, S. A., & Ertugrul, H. M. (2017). The real estate industry in Turkey: a time series analysis. The Service Industries Journal, 1−13. https://doi.org/10.1080/02642069.2018.1444033
Maqbool, R. (2018). Efficiency and effectiveness of factors affecting renewable energy projects; an empirical perspective. Energy, 158(1), 944−956. https://doi.org/10.1016/j.energy.2018.06.015
Mathur, S. (2014). Funding public transportation through special assessment districts: addressing the equity concerns. Public Works Management & Policy, 20(2), 127−145. https://doi.org/10.1177/1087724X14550252
Moxnes, E. (1990). System dynamics and decisions under uncertainty. Paper presented at the Proceedings of the International System Dynamics Conference.
Munnell, A. H. (1992). Infrastructure investment and economic growth. Journal of Economic Perspectives, 6(4), 189−198. https://doi.org/10.1257/jep.6.4.189
Munoz-Gielen, D. (2012). Urban governance, property rights, land readjustment and public value capturing. European Urban and Regional Studies, 21(1), 60−78. https://doi.org/10.1177/0969776412440543
Ploth, P. M. (2015). What’s taking so long? Identifying the underlying causes of delays in planning transportation megaprojects in the United States. Journal of Planning Literature, 30(3), 282−295. https://doi.org/10.1177/0885412214566116
Qi, C., & Chang, N.-B. (2011). System dynamics modeling for municipal water demand estimation in an urban region under uncertain economic impacts. Journal of Environmental Management, 92(6), 1628−1641. https://doi.org/10.1016/j.jenvman.2011.01.020
Richardson, G. P. (1991). System dynamics: simulation for policy analysis from a feedback perspective. In P. A. Fishwick, & P. A. Luker (Eds.), Qualitative simulation modelling and analysis (Vol. 5). https://doi.org/10.1007/978-1-4613-9072-5_7
Rolon, A. (2008). Evaluation of value capture mechanisms from linkage capture to special assessment districts. Transportation Research Record: Journal of the Transportation Research Boar, 2079(1), 127−135. https://doi.org/10.3141/2079-16
Salon, D., & Shewmake, S. (2011). Opportunities for value capture to fund public transport: a comprehensive review of the literature with a focus on East Asia. https://doi.org/10.2139/ssrn.1753302
Schoen, J. W. (2018). Trump infrastructure plan comes up $1 trillion short of its funding goal, analysis finds. CNBC. https://www.cnbc.com/2018/02/23/trump-infrastructure-plan-comes-up-1-trillion-short-analysis.html
Soffar, H. (2019). Artificial intelligence in banking advantages, disadvantages & mobile banking services. https://www.online-sciences.com/robotics/artificial-intelligence-in-banking-advantages-disadvantages-mobile-banking-services/
Sterman, J. D. (2000). Business dynamics: systems thinking and modeling for a complex world. McGraw-Hill Education.
Sterman, J. D. (2001). System dynamics modeling: tools for learning in a complex world. California Management Review, 43(4), 8−25. https://doi.org/10.2307/41166098
Tang, V., & Vijay, S. (2001). System dynamics origins, development, and future prospects of a method. http://web.mit.edu/esd.83/www/notebook/System%20Dynamics%20final.doc
Vadali, S., Manuel-Aldrete, R., Bujanda, A., Swapnil, S., Kuhn, B., Geiselbrecht, T., & Tooley, S. (2012). Transportation reinvestment zone handbook (Report 0-6538 Product P1 Handbook). https://rosap.ntl.bts.gov/view/dot/20254/dot_20254_DS1.pdf
Vlachos, D., Georgiadis, P., & Iakovou, E. (2007). A system dynamics model for dynamic capacity planning of remanufacturing in closed-loop supply chains. Computers & Operations Research, 34(2), 367−394. https://doi.org/10.1016/j.cor.2005.03.005
Wang, F. Y., Zhang, J. J., Zheng, X., Wang, X., Yuan, Y., Dai, X., & Yang, L. (2016). Where does AlphaGo go: from church-turing thesis to AlphaGo thesis and beyond. IEEE/CAA Journal of Automatica Sinica, 3(2), 113−120. https://doi.org/10.1109/JAS.2016.7471613
Weber, R., Bhatta, S. D., & Merriman, D. (2007). Spillovers from tax increment financing districts: implications for housing price appreciation. Regional Science and Urban Economics, 37, 259−281. https://doi.org/10.1016/j.regsciurbeco.2006.11.003
Xu, Z., & Coors, V. (2012). Combining system dynamics model, GIS and 3D visualization in sustainability assessment of urban residential development. Building and Environment, 47, 272−287. https://doi.org/10.1016/j.buildenv.2011.07.012