Mitigating Traffic Congestion: The Role of Intelligent Transportation Systems

References

• Texas A&M Transportation Institute (2015) Annual urban mobility scorecard. Retrieved April 16, 2018, https://mobility.tamu.edu/ums/.Google Scholar
• Anderson ML (2014) Subways, strikes, and slowdowns: The impacts of public transit on traffic congestion. Amer. Econom. Rev. 104(9):2763–2796.Crossref, Google Scholar
• Angrist JD, Pischke JS (2008) Mostly Harmless Econometrics: An Empiricist’s Companion (Princeton University Press, Princeton, NJ).Crossref, Google Scholar
• Arnott R (2001) The economic theory of urban traffic congestion: a microscopic research agenda. Workshop on Environmental Economics and the Economics of Congestion: Coping with Externalities, San Servolo, Italy.Google Scholar
• Arnott R, De Palma A, Lindsey R (1991) Does providing proto drivers reduce traffic congestion? Transportation Res. Part A: General 25(5):309–318.Crossref, Google Scholar
• Arnott R, Small K (1994) The economics of traffic congestion. Amer. Sci. 82(5):446–455.Google Scholar
• Auer A, Feese S, Lockwood S (2016) History of intelligent transportation systems. Report FHWA-JPO-16-329, U.S. Department of Transportation, Washington, DC.Google Scholar
• Autor DH (2003) Outsourcing at will: The contribution of unjust dismissal doctrine to the growth of employment outsourcing. J. Labor Econom. 21(1):1–42.Crossref, Google Scholar
• Barth M, Boriboonsomsin K (2008) Real-world carbon dioxide impacts of traffic congestion. Transportation Res. Record: J. Transportation Res. Board 2058(1):163–171.Crossref, Google Scholar
• Baum-Snow N (2007) Did highways cause suburbanization? Quart. J. Econom. 122(2):775–805.Crossref, Google Scholar
• Becker GS (1965) A theory of the allocation of time. Econom. J. (London) 75(299):493–517.Google Scholar
• Ben-Akiva M, De Palma A, Isam K (1991) Dynamic network models and driver information systems. Transportation Res. Part A: General 25(5):251–266.Crossref, Google Scholar
• Bertrand M, Duflo E, Mullainathan S (2004) How much should we trust differences-in-differences estimates? Quart. J. Econom. 119(1):249–275.Crossref, Google Scholar
• Bharadwaj S, Bharadwaj A, Bendoly E (2007) The performance effects of complementarities between information systems, marketing, manufacturing, and supply chain processes. Inform. Systems Res. 18(4):437–453.Link, Google Scholar
• Blackwell M, Iacus SM, King G, Porro G (2009) CEM: Coarsened exact matching in Stata. Stata J. 9(4):524–546.Crossref, Google Scholar
• Bloom N, Garicano L, Sadun R, Reenen JV (2014) The distinct effects of information technology and communication technology on firm organization. Management Sci. 60(12):2859–2885.Link, Google Scholar
• Bharadwaj AS, Sambamurthy V, Zmud RW (2002) Firmwide IT Capability: An Empirical Examination of the Construct and Its Links to Performance (Emory University, Atlanta).Google Scholar
• Brynjolfsson E, Hitt LM (2003) Computing productivity: Firm-level evidence. Rev. Econom. Statist. 85(4):793–808.Crossref, Google Scholar
• Cervero R (2002) Induced travel demand: Research design, empirical evidence, and normative policies. J. Planning Literature 17(1):3–20.Crossref, Google Scholar
• Chan J, Ghose A (2014) Internet’s dirty secret: Assessing the impact of online intermediaries on HIV transmission. MIS Quart. 38(4):955–976.Crossref, Google Scholar
• Chen Y, Whalley A (2012) Green infrastructure: The effects of urban rail transit on air quality. Amer. Econom. J. Econom. Policy 4(1):58–97.Crossref, Google Scholar
• Cheng ZA, Dimoka A, Pavlou PA (2016) Context may be king, but generalizability is the emperor! J. Inform. Tech. 31(3):257–264.Crossref, Google Scholar
• Couture V, Duranton G, Turner MA (2018) Speed. Rev. Econom. Statist. 100(4):725–739.Crossref, Google Scholar
• Dewees DN (1979) Estimating the time costs of highway congestion. Econometrica 47(6):1499–1512.Crossref, Google Scholar
• Downs A (1962) The law of peak-hour expressway congestion. Traffic Quart. 16(3):393–409.Google Scholar
• Downs A (1992) Stuck in Traffic (The Brookings Institution, Washington, DC).Google Scholar
• Duranton G, Turner MA (2011) The fundamental law of road congestion: Evidence from US cities. Amer. Econom. Rev. 101(6):2616–2652.Crossref, Google Scholar
• Emmerink RH, Verhoef ET, Nijkamp P, Rietveld P (1996) Information provision in road transport with elastic demand: A welfare economic approach. J. Transportation Econom. Policy 30(2):117–136.Google Scholar
• Fagnant DJ, Kockelman K (2015) Preparing a nation for autonomous vehicles: Opportunities, barriers and policy recommendations. Transportation Res. Part A: Policy Practice 77:167–181.Crossref, Google Scholar
• Ge Y, Knittel CR, MacKenzie D, Zoepf S (2016) Racial and Gender Discrimination in Transportation Network Companies (National Bureau of Economic Research, Cambridge, MA).Crossref, Google Scholar
• Glaeser E (2011) Triumph of the City: How Urban Spaces Make Us Human (Pan Macmillan, Basingstoke, UK).Google Scholar
• Goldfarb A, Tucker C (2019) Digital economics. J. Econom. Literature 57(1):3–43.Crossref, Google Scholar
• Goodwin PB (1996) Empirical evidence on induced traffic. Transportation 23(1):35–54.Crossref, Google Scholar
• Government Technology (2010) Driving into the future. 23(6):14–19.Google Scholar
• Government Technology (2011a) Smart highways: Active traffic management technology curbs congestion and improves safety. 24(1):14–20.Google Scholar
• Government Technology (2011b) Taming traffic—Communities use technology to fight congestion. 24(7):16–22.Google Scholar
• Granados NF, Gupta A, Kauffman RJ (2006) The impact of IT on market information and transparency: A unified theoretical framework. J. Assoc. Inform. Systems 7(3):148–178.Google Scholar
• Greenwood BN, Wattal S (2017) Show me the way to go home: An empirical investigation of ride-sharing and alcohol related motor vehicle fatalities. Management Inform. Systems Quart. 41(1):163–187.Crossref, Google Scholar
• Hsu WT, Zhang H (2014) The fundamental law of highway congestion revisited: Evidence from national expressways in Japan. J. Urban Econom. 81:65–76.Crossref, Google Scholar
• Jenkins SP (1995) Easy estimation methods for discrete-time duration models. Oxford Bull. Econom. Statist. 57(1):129–136.Crossref, Google Scholar
• Jones P (1998) Urban road pricing: Public acceptability and barriers to implementation. Road Pricing, Traffic Congestion and the Environment: Issues of Efficiency and Social Feasibility (Edward Elgar Publishing, Cheltenham, UK).Google Scholar
• Malhotra A, Melville NP, Watson RT (2013) Spurring impactful research on information systems for environmental sustainability. Management Inform. Systems Quart. 37(4):1265–1274.Crossref, Google Scholar
• Melville NP (2010) Information systems innovation for environmental sustainability. Management Inform. Systems Quart. 34(1):1–21.Crossref, Google Scholar
• Melville N, Kraemer K, Gurbaxani V (2004) Information technology and organizational performance: An integrative model of IT business value. Management Inform. Systems Quart. 28(2):283–322.Crossref, Google Scholar
• Michaels G (2008) The effect of trade on the demand for skill: Evidence from the interstate highway system. Rev. Econom. Statist. 90(4):683–701.Crossref, Google Scholar
• Mogridge MJ (1997) The self-defeating nature of urban road capacity policy: A review of theories, disputes and available evidence. Transportation Policy 4(1):5–23.Crossref, Google Scholar
• Noland RB (1997) Commuter responses to travel time uncertainty under congested conditions: Expected costs and the provision of information. J. Urban Econom. 41(3):377–406.Crossref, Google Scholar
• Pang MS, Lee G, DeLone WH (2014a) IT resources, organizational capabilities, and value creation in public-sector organizations: A public-value management perspective. J. Inform. Tech. 29(3):187–205.Crossref, Google Scholar
• Pang MS, Tafti A, Krishnan MS (2014b) Information technology and administrative efficiency in U.S. state governments—A stochastic frontier approach. Management Inform. Systems Quart. 38(4):1079–1101.Crossref, Google Scholar
• Pang MS, Tafti A, Krishnan MS (2016) Do CIO IT budgets explain bigger or smaller governments? Theory and evidence from US state governments. Management Sci. 62(4):1020–1041.Link, Google Scholar
• Papageorgiou M, Diakaki C, Dinopoulou V, Kotsialos A, Wang Y (2003) Review of road traffic control strategies. Proc. IEEE 91(12):2043–2067.Crossref, Google Scholar
• Pavlou PA, El Sawy OA (2006) From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development. Inform. Systems Res. 17(3):198–227.Link, Google Scholar
• Pavlou PA, El Sawy OA (2010) The “third hand”: IT-enabled competitive advantage in turbulence through improvisational capabilities. Inform. Systems Res. 21(3):443–471.Link, Google Scholar
• Rai A, Pavlou PA, Im G, Du S (2012) Interfirm IT capability profiles and communications for cocreating relational value: Evidence from the logistics industry. Management Inform. Systems Quart. 36(1):233–262.Crossref, Google Scholar
• Rothenberg J (1970) The economics of congestion and pollution: An integrated view. Amer. Econom. Rev. 60(2):114–121.Google Scholar
• Shapiro C, Varian HR (1998) Information Rules: A Strategic Guide to the Network Economy (Harvard Business School Press, Boston).Google Scholar
• Small KA, Verhoef ET (2007) The Economics of Urban Transportation (Routledge, New York).Crossref, Google Scholar
• Train K (1980) A structured logit model of auto ownership and mode choice. Rev. Econom. Stud. 47(2):357–370.Crossref, Google Scholar
• Van Dyke CW, Walton JR, Ballinger J (2016) Synthesis of Kentucky’s traveler information systems. Accessed October 29, 2019, https://uknowledge.uky.edu/cgi/viewcontent.cgi?article=2575&context=ktc_researchreports.Google Scholar
• Vickrey WS (1969) Congestion theory and transport investment. Amer. Econom. Rev. 59(2):251–260.Google Scholar
• Wachs M (2002) Fighting traffic congestion with information technology. Issues Sci. Tech. 19(1):43–50.Google Scholar
• Winston C (2013) On the performance of the US transportation system: Caution ahead. J. Econom. Literature 51(3):773–824.Crossref, Google Scholar
• Winston C, Langer A (2006) The effect of government highway spending on road users’ congestion costs. J. Urban Econom. 60(3):463–483.Crossref, Google Scholar