W. Douglass Shaw

2.7k total citations
85 papers, 1.9k citations indexed

About

W. Douglass Shaw is a scholar working on Economics and Econometrics, General Decision Sciences and Sociology and Political Science. According to data from OpenAlex, W. Douglass Shaw has authored 85 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 67 papers in Economics and Econometrics, 21 papers in General Decision Sciences and 19 papers in Sociology and Political Science. Recurrent topics in W. Douglass Shaw's work include Economic and Environmental Valuation (64 papers), Decision-Making and Behavioral Economics (21 papers) and Transportation Planning and Optimization (14 papers). W. Douglass Shaw is often cited by papers focused on Economic and Environmental Valuation (64 papers), Decision-Making and Behavioral Economics (21 papers) and Transportation Planning and Optimization (14 papers). W. Douglass Shaw collaborates with scholars based in United States, Italy and United Kingdom. W. Douglass Shaw's co-authors include Paul M. Jakus, Peter Feather, Mary Riddel, Richard T. Woodward, Therese Grijalva, Mark Burris, A M Walker, Robert P. Berrens, Robert D. Rowe and Edward R. Morey and has published in prestigious journals such as SHILAP Revista de lepidopterología, Water Resources Research and Ecological Economics.

In The Last Decade

W. Douglass Shaw

81 papers receiving 1.6k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
W. Douglass Shaw United States 25 1.3k 472 356 259 233 85 1.9k
Joseph A. Herriges United States 28 2.2k 1.7× 342 0.7× 223 0.6× 464 1.8× 250 1.1× 65 3.0k
William H. Desvousges United States 27 2.1k 1.7× 245 0.5× 541 1.5× 452 1.7× 252 1.1× 60 2.9k
Russell K. Blamey Australia 20 1.4k 1.1× 144 0.3× 385 1.1× 453 1.7× 162 0.7× 35 1.8k
Tannis Hett 4 1.7k 1.4× 141 0.3× 269 0.8× 552 2.1× 179 0.8× 5 2.1k
Ju‐Chin Huang United States 14 1.1k 0.8× 159 0.3× 217 0.6× 184 0.7× 105 0.5× 46 1.5k
John P. Hoehn United States 20 1.9k 1.5× 161 0.3× 398 1.1× 705 2.7× 207 0.9× 55 2.6k
Silvia Ferrini United Kingdom 21 1.1k 0.9× 189 0.4× 313 0.9× 670 2.6× 103 0.4× 70 1.9k
Ece Özdemiroğlu United Kingdom 11 1.1k 0.9× 98 0.2× 323 0.9× 372 1.4× 107 0.5× 29 1.5k
J.R. DeShazo United States 24 1.2k 1.0× 188 0.4× 171 0.5× 175 0.7× 102 0.4× 52 2.0k
Daigee Shaw Taiwan 19 772 0.6× 165 0.3× 539 1.5× 421 1.6× 238 1.0× 50 2.0k

Countries citing papers authored by W. Douglass Shaw

Since Specialization
Citations

This map shows the geographic impact of W. Douglass Shaw's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by W. Douglass Shaw with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites W. Douglass Shaw more than expected).

Fields of papers citing papers by W. Douglass Shaw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by W. Douglass Shaw. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by W. Douglass Shaw. The network helps show where W. Douglass Shaw may publish in the future.

Co-authorship network of co-authors of W. Douglass Shaw

This figure shows the co-authorship network connecting the top 25 collaborators of W. Douglass Shaw. A scholar is included among the top collaborators of W. Douglass Shaw based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with W. Douglass Shaw. W. Douglass Shaw is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Burris, Mark, et al.. (2016). Models of transportation choice with risk: an application to managed lanes. Transportation Letters. 9(5). 276–295. 12 indexed citations
2.
Leidner, Andrew J., W. Douglass Shaw, & Steven T. Yen. (2014). An historical perspective on health‐risk awareness and unhealthy behaviour: cigarette smoking in the United States 1949–1981. Health Expectations. 18(6). 2720–2730. 7 indexed citations
3.
Huang, Chao, Mark Burris, & W. Douglass Shaw. (2014). A Prospect Theory Approach to Estimating the Use of Managed Lanes. Transportation Research Board 93rd Annual MeetingTransportation Research Board. 2 indexed citations
4.
Burris, Mark, et al.. (2012). The Value of Travel Time and Reliability of Houston Managed Lane Travelers-Evidence from Stated Preference Survey and Actual Usage Data. Transportation Research Board 91st Annual MeetingTransportation Research Board. 3 indexed citations
6.
7.
Patil, Sunil, Mark Burris, & W. Douglass Shaw. (2011). Travel using managed lanes: An application of a stated choice model for Houston, Texas. Transport Policy. 18(4). 595–603. 12 indexed citations
8.
Higgins, Lindsey M., et al.. (2011). Attributes affecting preferences for traffic safety camera programs. Accident Analysis & Prevention. 43(3). 1042–1048. 7 indexed citations
9.
Shaw, W. Douglass & Justin S. Baker. (2010). Models of Location Choice and Willingness to Pay to Avoid Hurricane Risks for Hurricane Katrina Evacuees. International Journal of Mass Emergencies & Disasters. 28(1). 87–114. 16 indexed citations
10.
Jakus, Paul M., et al.. (2010). An Empirical Model of Perceived Mortality Risks for Selected U.S. Arsenic Hot Spots. Risk Analysis. 30(10). 1550–1562. 18 indexed citations
11.
Jakus, Paul M., et al.. (2009). Risk perceptions of arsenic in tap water and consumption of bottled water. Water Resources Research. 45(5). 75 indexed citations
12.
Woodward, Richard T. & W. Douglass Shaw. (2008). Allocating Resources in an Uncertain World: Water Management and Endangered Species. American Journal of Agricultural Economics. 90(3). 593–605. 12 indexed citations
13.
Shaw, W. Douglass, et al.. (2005). Health Benefits and Uncertainty: An Experimental Analysis of the Effects of Risk Presentation on Auction Bids for a Healthful Product. Economics bulletin. 4(1). 1–8. 11 indexed citations
14.
Grijalva, Therese, Robert P. Berrens, Alok K. Bohara, Paul M. Jakus, & W. Douglass Shaw. (2002). Valuing the Loss of Rock Climbing Access in Wilderness Areas: A National-Level, Random-Utility Model. Land Economics. 78(1). 103–120. 37 indexed citations
15.
Netusil, Noelwah R., et al.. (2001). Contingent Valuation of Some Externalities from Mine Dewatering. Journal of Water Resources Planning and Management. 127(6). 369–377. 4 indexed citations
16.
Shaw, W. Douglass. (2000). Conrad, Jon. Resource Economics. Cambridge (UK): Cambridge University Press, 1999. 213 pp. Price unknown. American Journal of Agricultural Economics. 82(4). 1054–1055. 1 indexed citations
17.
Eiswerth, Mark E., et al.. (2000). The value of water levels in water‐based recreation: A pooled revealed preference/contingent behavior model. Water Resources Research. 36(4). 1079–1086. 70 indexed citations
18.
Shaw, W. Douglass. (1997). Natural resource damage assessment: economics and settlements. International Journal of Environmental Studies. 51(4). 285–299. 1 indexed citations
19.
Jakus, Paul M. & W. Douglass Shaw. (1996). An Empirical Analysis of Rock Climbers' Response to Hazard Warnings. Risk Analysis. 16(4). 581–586. 20 indexed citations
20.
Shaw, W. Douglass. (1991). Recreational demand by tourists for saltwater beach days: Comment. Journal of Environmental Economics and Management. 20(3). 284–289. 11 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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