Web Survey Bibliography
For 20 years the debate about clean air regulation has centered on acid rain and the controversy about acid rain in the Adirondack Park, which covers some six million acres in New York State. But until now policymakers have never had an estimate of the economic value of improvements to the park to New York State residents. Our five-year study quantifies the change in total economic value (the sum of use and nonuse value) that would result from an improvement in the ecological attributes of the Adirondack Park that could be expected to follow from policies currently under consideration, such as Clear Skies. To obtain these estimates a contingent valuation survey was administered to a random sample of New York State residents through the Internet, Web TV, and mail.
Our preferred estimates of the mean willingness to pay (WTP) using the base case characterization of ecological improvements range from $48 to $107 per year per household in New York State. The alternative scope case scenario yields mean WTP ranging from $54 to $159 per year per household. Multiplying these population-weighted estimates by the approximate number of households in the state yields benefits ranging from about $336 million to $1.1 billion per year. The instrument passes an external scope test and a test of sensitivity to bid, both of which are important measures of validity for stated preference studies.
The results of this study help complete the two-decade-long project of integrated assessment across natural and social sciences, resulting in economic estimates that can be used to guide policymaking to address the ecological effects of acid rain in North America. The values above exceed cost estimates of reducing SO2 and NOx emissions from power plants subject to the Clear Skies initiative if the cost share is determined according to the share of these emissions actually being deposited in the park.
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Web survey bibliography (4086)
- Sample Representation and Substantive Outcomes Using Web With and Without Incentives Compared to Telephone...; 2016; Lipps, O.; Pekari, N.
- Effects of Data Collection Mode and Response Entry Device on Survey Response Quality; 2016; Ha, L.; Zhang, Che.; Jiang, W.
- The Dynamic Identity Fusion Index: A New Continuous Measure of Identity Fusion for Web-Based Questionnaires...; 2016; Jimenez, J.; Gomez, A.; Buhrmester, M.; Whitehouse, H.; Swann, W. B.
- Recommended Practices for the design of business surveys questionnaires; 2016; Macchia, S.
- Navigation Buttons in Web-Based Surveys: Respondents’ Preferences Revisited in the Laboratory; 2016; Romano Bergstrom, J. C.; Erdman, C.; Lakhe, S.
- Collecting Data from mHealth Users via SMS Surveys: A Case Study in Kenya; 2016; Johnson, D.
- “Money Will Solve the Problem”: Testing the Effectiveness of Conditional Incentives for...; 2016; DeCamp, W.; Manierre, M. J.
- Effects of Incentive Amount and Type of Web Survey Response Rates; 2016; Coopersmith, J.; Vogel, L. K.; Bruursema, T.; Feeney, K.
- Effect of a Post-paid Incentive on Response to a Web-based Survey; 2016; Brown, J. A.; Serrato, C. A.; Hugh, M.; Kanter, M. H.; A.; Spritzer, K. L.; Hays, R. D.
- Web-based versus Paper-based Survey Data: An Estimation of Road Users’ Value of Travel Time Savings...; 2016; Kato, H.; Sakashita, A.; Tsuchiya, Tak.
- Reminder Effect and Data Usability on Web Questionnaire Survey for University Students; 2016; Oishi, T.; Mori, M.; Takata, E.
- Feasibility of using a multilingual web survey in studying the health of ethnic minority youth.; 2016; Kinnunen, J. M.; Malin, M.; Raisamo, S. U.; Lindfors, P. L.; Pere, L. A.; Rimpelae, A. H.
- Respondents of a follow-up web-based survey; 2016; Stoddard, S. A.; Amparo, P.; Popick, H.; Yudd, R.; Sujeer, A.; Baath, M.
- An Examination of Opposing Responses on Duplicated Multi-Mode Survey Responses; 2016; Djangali, A.
- Is One More Reminder Worth It? If So, Pick Up the Phone: Findings from a Web Survey; 2016; Lin-Freeman, L.
- Reducing Underreports of Behaviors in Retrospective Surveys: The Effects of Three Different Strategies...; 2016; Lugtig, P. J.; Glasner, T.; Boeve, A.
- Dropouts in Longitudinal Surveys; 2016; Lugtig, P. J.; De Leeuw, E. D.
- Participant recruitment and data collection through Facebook: the role of personality factors; 2016; Rife, S. C.; Cate, K. L.; Kosinski, M.; Stillwell, D.
- What drives the participation in a monthly research web panel? The experience of ELIPSS, a French random...; 2016; Legleye, S; Cornilleau, A.; Razakamanana, N.
- When Should I Call You? An Analysis of Differences in Demographics and Responses According to Respondents...; 2016; Vicente, P.; Lopes, I.
- Evaluating a New Proposal for Detecting Data Falsification in Surveys; 2016; Simmons, K.; Mercer, A. W.; Schwarzer, S.; Courtney, K.
- Quantifying Under- and Overreporting in Surveys Through a Dual-Questioning-Technique Design. ; 2016; de Jong , M.; Fox, J.-P.; Steenkamp, J. - B. E. M.
- The use and positioning of clarification features in web surveys; 2016; Metzler, A., Kunz, T., Fuchs, M.
- Take the money and run? Redemption of a gift card incentive in a clinician survey. ; 2016; Chen, J. S.; Sprague, B. L.; Klabunde, C. N.; Tosteson, A. N. A.; Bitton, A.; Onega, T.; MacLean, C....
- Online Surveys are Mixed-Device Surveys. Issues Associated with the Use of Different (Mobile) Devices...; 2016; Toepoel, V.; Lugtig, P. J.
- Mail merge can be used to create personalized questionnaires in complex surveys. ; 2016; Taljaard, M.; Chaudhry, S. H.; Brehaut, J. C.; Weijer, C.; Grimshaw, J. M.
- Electronic and paper based data collection methods in library and information science research: A comparative...; 2016; Tella, A.
- Stable Relationships, Stable Participation? The Effects of Partnership Dissolution and Changes in Relationship...; 2016; Mueller, B.; Castiglioni, L.
- Identifying Pertinent Variables for Nonresponse Follow-Up Surveys. Lessons Learned from 4 Cases in Switzerland...; 2016; Vandenplas, C.; Joye, D.; Staehli, M. E.; Pollien, A.
- The 2013 Census Test: Piloting Methods to Reduce 2020 Census Costs; 2016; Walejko, G. K.; Miller, P. V.
- A Technical Guide to Effective and Accessible web Surveys; 2016; Baatard, G.
- The Validity of Surveys: Online and Offline; 2016; Wiersma, W.
- Methods can matter: Where Web surveys produce different results than phone interviews; 2016; Keeter, S.
- Computer-assisted and online data collection in general population surveys; 2016; Skarupova, K.
- Sunday shopping – The case of three surveys; 2016; Bethlehem, J.
- Solving the Nonresponse Problem With Sample Matching?; 2016
- Will They Stay or Will They Go? Personality Predictors of Dropout in Online Study; 2016; Nestler, S.; Thielsch, M.; Vasilev, E.; Back, M.
- Do Polls Still Work If People Don't Answer Their Phones?; 2016; Edwards-Levy, A.; Jackson, N. M.
- HUFFPOLLSTER: Why Reaching Latinos Is A Challenge For Pollsters; 2016; Jackson, N. M.; Edwards-Levy, A.; Velencia, J.
- A Framework of Incorporating Thai Social Networking Data in Online Marketing Survey; 2016; Jiamthapthaksin, R.; Aung, T. H.; Ratanasawadwat, N.
- Creation and Usability Testing of a Web-Based Pre-Scanning Radiology Patient Safety and History Questionnaire...; 2016; Robinson, T. J.; DuVall, S.; Wiggins III, R
- Comprehension and engagement in survey interviews with virtual agents; 2016; Conrad, F. G.; Schober, M. F.; Jans, M.; Orlowski, R. A.; Nielsen, D.; Levenstein, R. M.
- Development of a scale to measure skepticism toward electronic word-of-mouth; 2016; Zhang, Xia.; Ko, M.; Carpenter, D.
- Improving social media measurement in surveys: Avoiding acquiescence bias in Facebook research; 2016; Kuru, O.; Pasek, J.
- Psychological research in the internet age: The quality of web-based data; 2016; Ramsey, S. R.; Thompson, K. L.; McKenzie, M.; Rosenbaum, A.
- Internet Abusive Use Questionnaire: Psychometric properties; 2016; Calvo-Frances, F.
- Revisiting “yes/no” versus “check all that apply”: Results from a mixed modes...; 2016; Nicolaas, G.; Campanelli, P.; Hope, S.; Jaeckle, A.; Lynn, P.
- The impact of academic sponsorship on Web survey dropout and item non-response; 2016; Allen, P. J.; Roberts, L. D.
- Moderators of Candidate Name-Order Effects in Elections: An Experiment; 2016; Kim, Nu.; Krosnick, J. A.; Casasanto, D.
- Predictive inference for non-probability samples: a simulation study ; 2016; Buelens, B.; Burger, J.; van den Brakel, J.