Abstract

Freight transportation infrastructure systems facilitate commodity flows across multiple industries. The closure of key infrastructures leads to an interruption of economic productivity that propagates through a system of interconnected industries. Investing in infrastructure and key industries can reduce the vulnerability of many industries by improving their ability to maintain functionality when shocked. This work investigates how a limited budget could be allocated to multiple industries to fortify them prior to a disruption to ultimately enhance the economic resilience across all industries by reducing the vulnerability of the underlying infrastructure. A risk-based economic interdependency model is used to implement a new measure of absorptive capacity to examine the propagation of a failure throughout the economy given the fortification of industry sectors. Sources of uncertainty in this data-driven model are considered, and a soft-robust optimization model is proposed to devise budget allocation under uncertainty. The approach is illustrated with an inland waterway port case study. The results can provide decision makers with managerial insights about how the economic interdependency affects the industries’ share of a budget to enhance absorptive capacity and how the level of budget affects the decision-making process for allocating resources.

Get full access to this article

View all available purchase options and get full access to this article.

References

Alizadeh, A. H., and N. K. Nomikos. 2004. “Cost of carry, causality and arbitrage between oil futures and tanker freight markets.” Transp. Res. Part E 40 (4): 297–316. https://doi.org/10.1016/j.tre.2004.02.002.
Arkansas Waterway Commissions. 2014. “Arkansas Waterway Commissions—Interactive access to website.” Accessed December 31, 2014. http://waterways.arkansas.gov/.
Arnold, B., C. Cammarata, D. Farmer, K. Kowalewski, F. Ladipo, M. Lasky, and D. Moore. 2006. The economic costs of disruptions in container shipments. Washington, DC: Congressional Budget Office.
Aydin, S. G., and G. Shen. 2012. “A retro-analysis of I-40 bridge collapse on freight movement in the U.S. highway network using GIS and assignment models.” Int. J. Transp. Sci. Technol. 1 (4): 379–397. https://doi.org/10.1260/2046-0430.1.4.379.
Barker, K., and Y. Y. Haimes. 2009. “Uncertainty analysis of interdependencies in dynamic infrastructure recovery: Applications in risk-based decision making.” J. Infrastruct. Syst. 15 (4): 394–405. https://doi.org/10.1061/(ASCE)1076-0342(2009)15:4(394).
Barker, K., J. E. Ramirez-Marquez, and C. M. Rocco. 2013. “Resilience-based network component importance measures.” Reliab. Eng. Syst. Saf. 117 (1): 89–97. https://doi.org/10.1016/j.ress.2013.03.012.
Barker, K., and J. R. Santos. 2010a. “A risk-based approach for identifying key economic and infrastructure sectors.” Risk Anal. 30 (6): 962–974. https://doi.org/10.1111/j.1539-6924.2010.01373.x.
Barker, K., and J. R. Santos. 2010b. “Measuring the efficacy of inventory with a dynamic input-output model.” Int. J. Prod. Econ. 126 (1): 130–143. https://doi.org/10.1016/j.ijpe.2009.08.011.
Ben-Tal, A., L. Ghaoui, and A. Nemirovski. 2009. Robust optimization. Princeton, NJ: Princeton University Press.
Bienstock, D., and S. Mattia. 2007. “Using mixed-integer programming to solve power grid blackout problems.” Discrete Optim. 4 (1): 115–141. https://doi.org/10.1016/j.disopt.2006.10.007.
Bullard, C. W., III, and A. V. Sebald. 1977. “Effects of parametric uncertainty and technological change in input-output models.” Rev. Econ. Stat. 59 (1): 75–81. https://doi.org/10.2307/1924906.
Business View Magazine. 2016. “Tulsa Port of Catoosa—Where the barges are running.” Accessed September 21, 2018. https://businessviewmagazine.com/the-tulsa-port-of-catoosa-where-the-barges-are-running/.
Bye, P., L. Yu, S. H. Shivastava, and S. Van Leeuwen. 2013. Vol. 753 of A pre-event recovery planning guide for transportation. Washington, DC: Transportation Research Board.
Çelik, M., Ö. Ergun, and P. Keskinocak. 2015. “The post-disaster debris clearance problem under incomplete information.” Oper. Res. 63 (1): 65–85. https://doi.org/10.1287/opre.2014.1342.
Darayi, M., K. Barker, and J. R. Santos. 2017. “Component importance measures for multi-industry vulnerability of a freight transportation network.” Net. Spatial Econ. 17 (4): 1111–1136. https://doi.org/10.1016/j.scient.2011.02.001.
Davarzani, H., S. H. Zegordi, and A. Norrman. 2011. “Contingent management of supply chain disruption: Effects of dual or triple sourcing.” Sci. Iranica 18 (6): 1517–1528. https://doi.org/10.1016/j.scient.2011.02.001.
DHS (Department of Homeland Security). 2013. National infrastructure protection plan: Partnering for critical infrastructure security and resilience. Washington, DC: US Dept. of Homeland Security.
DoT (Department of Transport). 2018. “BUILD discretionary grants.” Accessed September 21, 2018. https://www.transportation.gov/BUILDgrants.
Fialkoff, M. R., O. A. Omitaomu, S. K. Peterson, and M. A. Tuttle. 2017. “Using geographic information science to evaluate legal restriction on freight transportation routing in disruptive scenarios.” Int. J. Crit. Infrastruct. Prot. 17 (1): 60–74. https://doi.org/10.1016/j.ijcip.2016.12.001.
Haefner, L., R. Goodwin, and L. Porrello. 1996. “The great flood of 1993: Impacts on waterborne commodity flow, rail transportation, and surrounding region.” In Proc., Semisesquicentennial Transportation Conf. Ames, IA: Center for Transportation Research and Education.
Halkin, A., V. Skrypin, E. Kush, K. Vakulenko, and V. Dolia. 2017. “Invest approach to transportation services cost formation.” Procedia Eng. 178 (1): 435–442. https://doi.org/10.1016/j.proeng.2017.01.086.
Ham, H., T. J. Kim, and D. Boyce. 2005. “Implementation and estimation of a combined model of interregional, multimodal commodity shipments and transportation network flows.” Transp. Res. Part B 39 (1): 65–79. https://doi.org/10.1016/j.trb.2004.02.005.
Hosseini, S., and K. Barker. 2015. “Modeling infrastructure resilience using Bayesian networks: A case study of inland waterway ports.” Comput. Ind. Eng. 93 (Mar): 252–266. https://doi.org/10.1016/j.cie.2016.01.007.
Hosseini, S., K. Barker, and J. E. Ramirez-Marquez. 2016. “A review of definitions and measures of system resilience.” Reliab. Eng. Syst. Saf. 145 (Jan): 47–61. https://doi.org/10.1016/j.ress.2015.08.006.
Jonkeren, O., and G. Giannopoulos. 2014. “Analysing critical infrastructure failure with a resilience inoperability input–output model.” Econ. Syst. Res. 26 (1): 39–59. https://doi.org/10.1080/09535314.2013.872604.
Kujawski, E. 2006. “Multi-period model for disruptive events in interdependent systems.” Syst. Eng. 9 (4): 281–295. https://doi.org/10.1002/sys.20057.
Lempert, R. J., and D. G. Groves. 2010. “Identifying and evaluating robust adaptive policy responses to climate change for water management agencies in the American West.” Technol. Forecasting Social Change 77 (6): 960–974. https://doi.org/10.1016/j.techfore.2010.04.007.
Leontief, W. W. 1986. Input-output economics. Oxford, UK: Oxford University Press.
MacKenzie, C. A., K. Barker, and F. H. Grant. 2012. “Evaluating the consequences of an inland waterway port closure with a dynamic multiregional interdependency model.” IEEE Trans. Syst. Man Cybern. Part A: Syst. Humans 42 (2): 359–370. https://doi.org/10.1109/TSMCA.2011.2164065.
MacKenzie, C. A., and C. W. Zobel. 2016. “Allocating resources to enhance resilience, with application to superstorm sandy and an electric utility.” Risk Anal. 36 (4): 847–862. https://doi.org/10.1111/risa.12479.
Nealer, R., C. L. Weber, C. Hendrickson, and H. S. Matthews. 2011. “Modal freight transport required for production of US goods and services.” Transp. Res. Part E 47 (4): 474–489. https://doi.org/10.1016/j.tre.2010.11.015.
Olson, D., and D. Wu. 2013. “The impact of distribution on value-at-risk measures.” Math. Comput. Modell. 58 (9–10): 1670–1676. https://doi.org/10.1016/j.mcm.2011.06.053.
Pant, R., and K. Barker. 2011. On robust decision-making in interdependent economic and infrastructure systems. In Proc., 11th Int. Conf. on Applications of Statistics and Probability in Civil Engineering. Boca Raton, FL: CRC Press.
Pant, R., K. Barker, F. H. Grant, and T. L. Landers. 2011. “Interdependent impacts of inoperability at multi-modal transportation container terminals.” Transp. Res. Part E: Logist. Transp. 47 (5): 722–737.
Pant, R., K. Barker, and T. L. Landers. 2015. “Dynamic impacts of commodity flow disruptions in inland waterway networks.” Comput. Ind. Eng. 89 (Nov): 137–149. https://doi.org/10.1016/j.cie.2014.11.016.
Pant, R., K. Barker, and C. W. Zobel. 2014. “Static and dynamic metrics of economic resilience for interdependent infrastructure and industry sectors.” Reliab. Eng. Syst. Saf. 125 (1): 92–102. https://doi.org/10.1016/j.ress.2013.09.007.
Park, J., J. Cho, P. Gordon, J. E. Moore, II, H. W. Richardson, and S. Yoon. 2011. “Adding a freight network to a national interstate input–output model: A TransNIEMO application for California.” J. Transp. Geogr. 19 (6): 1410–1422. https://doi.org/10.1016/j.jtrangeo.2011.07.019.
Pate-Cornell, M. 1996. “Uncertainties in risk analysis: Six levels of treatment.” Reliab. Eng. Syst. Saf. 54 (2–3): 95–111. https://doi.org/10.1016/S0951-8320(96)00067-1.
Richards, T. J., and P. M. Patterson. 1999. “The economic value of public relations expenditures: Food safety and the strawberry case.” J. Agric. Resour. Econ. 24 (2): 440–462.
Rockafellar, R. T., and S. Uryasev. 2000. “Optimization of conditional value-at-risk.” J. Risk 2 (3): 21–41. https://doi.org/10.21314/JOR.2000.038.
Rose, A. 2004. “Defining and measuring economic resilience to disasters.” Disaster Prev. Manage. 13 (4): 307–314. https://doi.org/10.1108/09653560410556528.
Rose, A. 2007. “Economic resilience to natural and man-made disasters: Multidisciplinary origins and contextual dimensions.” Environ. Hazard. 7 (4): 383–398. https://doi.org/10.1016/j.envhaz.2007.10.001.
Rose, A. 2009. Economic resilience to disasters. Oakridge, TN: CARRI Institute.
Santos, J. R., and Y. Y. Haimes. 2004. “Modeling the demand reduction input-output (I-O) inoperability due to terrorism of interconnected infrastructures.” Risk Anal. 24 (6): 1437–1451. https://doi.org/10.1111/j.0272-4332.2004.00540.x.
Shapiro, A., D. Dentcheva, and A. Ruszczynski. 2009. Lectures on stochastic programming: Modeling and theory. Philadelphia: SIAM and Mathematical Programming Society.
Shen, G., and S. G. Aydin. 2014. “Origin-destination missing data estimation for freight transportation planning: A gravity model-based regression approach.” Transp. Plann. Technol. 37 (6): 505–524. https://doi.org/10.1080/03081060.2014.927665.
The White House. 2011. Presidential policy directive/PPD-8: National preparedness. Washington, DC: US Dept. of Homeland Security.
Tulsa Port of Catoosa. 2011. “Tulsa Port of Catoosa—Interactive access to website.” Accessed December 31, 2011. http://www.tulsaport.com.
Tulsa Regional Chamber. 2018. “2018—Economic profile.” Accessed September 21, 2018. http://www.growmetrotulsa.com/sites/default/files/page-attachments/EDD_2018%20EconomicProfile_Low%2005.16.18.pdf.
US Army Corps of Engineers. 2011. “US Army Corps of Engineers—Interactive access to website.” Accessed December 31, 2011. http://www.iwr.usace.army.mil/ndc.
Vugrin, E. D., and R. C. Camphouse. 2011. “Infrastructure resilience assessment through control design.” Int. J. Crit. Infrastruct. 7 (3): 243–260. https://doi.org/10.1504/IJCIS.2011.042994.
West, G. R. 1986. “A stochastic analysis of an input-output model.” Econometrica 54 (2): 363–374. https://doi.org/10.2307/1913156.
Whitson, J. C., and J. E. Ramirez-Marquez. 2009. “Resiliency as a component importance measure in network reliability.” Reliab. Eng. Syst. Saf. 94 (10): 1685–1693. https://doi.org/10.1016/j.ress.2009.05.001.

Information & Authors

Information

Published In

Go to Journal of Infrastructure Systems
Journal of Infrastructure Systems
Volume 26Issue 1March 2020

History

Received: Aug 3, 2017
Accepted: Jun 3, 2019
Published online: Dec 7, 2019
Published in print: Mar 1, 2020
Discussion open until: May 7, 2020

Permissions

Request permissions for this article.

Authors

Affiliations

Assistant Professor, Great Valley School of Graduate Professional Studies, Pennsylvania State Univ., Malvern, PA 19355. ORCID: https://orcid.org/0000-0002-8166-9712. Email: [email protected]
Senior Postdoctoral Researcher, Environmental Change Institute, Univ. of Oxford, Oxford OX1 3QY, UK (corresponding author). ORCID: https://orcid.org/0000-0003-4648-5261. Email: [email protected]
Kash Barker, Ph.D. [email protected]
Associate Professor, School of Industrial and Systems Engineering, Univ. of Oklahoma, Norman, OK 73019. Email: [email protected]
Nazanin Morshedlou, Ph.D. [email protected]
Postdoctoral Scholar, School of Industrial and Systems Engineering, Univ. of Oklahoma, Norman, OK 73019. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share