In Contingent Valuation studies, users generally declare willingness to pay (WTP) higher than non-users. This study attempts to investigate if viewing the good during CV survey has different impact on users and non-users WTPs. A framed field experiment was conducted in which users and non-users were surveyed in two locations - one with a view of the forest and the other without it. Our study showed that the WTPs of users were significantly higher than those of non-users only when respondensts did not see forest during the survey. However, when the experiment was conducted in a location where the respondents could see the forest - the difference disappeared. Our results also show that the relationship between declared WTP and both the respondents’ socio-demographic status and their environmental attitudes were weaker among respondents surveyed in a location with a forest view. We believe that the increase in WTP of non-users is temporary and represents a kind of bias. This in turn may be relevant in the design of CVM studies.
Arrow, K., Solow, R., Portney, P. R., Leamer, E. E., Radner, R., & Schuman, H. (1993).
Report of the NOAA panel on contingent valuation. https://edisciplinas.usp.br/pluginfile.php/4473366/mod_folder/intro/Arow_WTP.pdf
Barrick, K. A., & Beazley, R. I. (1990). Magnitude and distribution of option value for the Washakie Wilderness, northwest Wyoming, USA. Environmental Management, 14(3), 367–380. https://doi.org/10.1007/BF02394205
Bartczak, A., Lindhjem, H., Navrud, S., Zandersen, M., & Żylicz, T. (2008). Valuing forest recreation on the national level in a transition economy: The case of Poland. Forest Policy and Economics, 10(7–8), 467–472. https://doi.org/10.1016/j.for-pol.2008.04.002
Bartczak, A. (2015). The role of social and environmental attitudes in non-market valuation. Forest Policy and Economics, 50, 357–365. https://doi.org/10.1016/j.forpol.2014.09.011
Bateman, I., & Turner, R. (1993). Valuation of the environment, methods and techniques: The contingent valuation method. In R. K. Turner (Ed.) Sustainable Environmental Economics and Management: Principles and Practice (pp. 120–191). Belhaven Press.
Bergstrom, J. C., Stoll, J. R., & Randall, A. (1990). The Impact of Information on Environmental Commodity Valuation Decisions. American Journal of Agricultural Economics, 72(3), 614–621. https://doi.org/10.2307/1243031
Berrens, R. P., Bohara, A. K., Jenkins-Smith, H. C., Silva, C. L., & Weimer, D. L. (2004). Information and effort in contingent valuation surveys: Application to global climate change using national internet samples. Journal of Environmental Economics and Management, 47(2), 331–363. https://doi.org/10.1016/S0095-0696(03)00094-9
Bishop, I. D., & Rohrmann, B. (2003). Subjective responses to simulated and real environments: A comparison. Landscape and Urban Planning, 65(4), 261–277. https://doi.org/10.1016/S0169-2046(03)00070-7
Blomquist, G. C., & Whitehead, J. C. (1998). Resource quality information and validity of willingness to pay in contingent valuation. Resource and Energy Economics, 20(2), 179–196. https://doi.org/10.1016/S0928-7655(97)00035-3
Brouwer, R. (2012). Constructed preference stability: A test–retest. Journal of Environmental Economics and Policy, 1(1), 70–84. https://doi.org/10.1080/21606544.2011.644922
Brown, T. C., Richards, M. T., Daniel, T. C., & King, D. A. (1989). Recreation Participation and the Validity of Photo-based Preference Judgments. Journal of Leisure Research, 21(1), 40–60. https://doi.org/10.1080/00222216.1989.11969789
Cameron, T. A., & Englin, J. (1997). Respondent Experience and Contingent Valuation of Environmental Goods. Journal of Environmental Economics and Management, 33(3), 296–313. https://doi.org/10.1006/jeem.1997.0995
Campbell, D., Hutchinson, W. G., & Scarpa, R. (2009). Using Choice Experiments to Explore the Spatial Distribution of Willingness to Pay for Rural Landscape Improvements. Environment and Planning A: Economy and Space, 41(1), 97–111. https://doi.org/10.1068/a4038
Choi, A. S. (2013). Nonmarket values of major resources in the Korean DMZ areas: A test of distance decay. Ecological Economics, 88, 97–107. https://doi.org/10.1016/j.ecolecon.2013.01.014
Choi, A. S., & Fielding, K. S. (2013). Environmental Attitudes as WTP Predictors: A Case Study Involving Endangered Species. Ecological Economics, 89, 24–32. https://doi.org/10.1016/j.ecolecon.2013.01.027
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334. https://doi.org/10.1007/BF02310555
De Steur, H., Buysse, J., Feng, S., & Gellynck, X. (2013). Role of Information on Consumers’ Willingness-to-pay for Genetically-modified Rice with Health Benefits: An Application to China: Information and Willingness-To Pay for GM Rice. Asian Economic Journal, 27(4), 391–408. https://doi.org/10.1111/asej.12020
De Valck, J., & Rolfe, J. (2018). Spatial Heterogeneity in Stated Preference Valuation: Status, Challenges and Road Ahead. International Review of Environmental and Resource Economics, 11(4), 355–422. https://doi.org/10.1561/101.00000097
Dupont, D. P. (2003). CVM Embedding Effects When There Are Active, Potentially Active and Passive Users of Environmental Goods. Environmental and Resource Economics, 25(3), 319–341. https://doi.org/10.1023/A:1024446110640
El-Habil, A. M. (2012). An Application on Multinomial Logistic Regression Model. Pakistan Journal of Statistics and Operation Research, 8(2), 271. https://doi.org/10.18187/pjsor.v8i2.234
Eurostat. (2002). The European Framework for Integrated Environmental and Economic Accounting for Forests. Office for Official Publications of the European Communities. https://ec.europa.eu/eurostat/documents/39314/44178/Handbook-IEEAF-2002.pdf/c7b2aeaa-c4dd-49ce-bf25-05740d90e043
Frör, O. (2008). Bounded rationality in contingent valuation: Empirical evidence using cognitive psychology. Ecological Economics, 68(1–2), 570–581. https://doi.org/10.1016/j.ecolecon.2008.05.021
Giergiczny, M., Jacobsen, J., Glenk, K., Meyerhoff, J., Abildtrup, J., Agimass, F., Czajkowski, M., Faccioli, M., Gajderowicz, T., Getzner, M., Lundhede, T., Mayer, M., McVittie, A., Olschewski, R., Ščasný, M., Strange, N., & Valasiuk, S. (2021). Shaping the future of temperate forests in Europe: Why outdoor recreation matters [Preprint]. In Review. https://doi.org/10.21203/rs.3.rs-841881/v1
Gilbert, A., Glass, R., & More, T. (1992). Valuation of eastern wilderness: Extramarket measures of public support. In: Payne, C., Bowker, J., Reed, P. (compilers), Economic Value of Wilderness. GTR-SE78, Southeastern Forest Experiment Station, USDA Forest Service, Athens, GA. In Payne, C., Bowker, J., Reed, P. (compilers), The Economic Value of Wilderness: Proceedings of the Conference: Jackson, Wyoming, May 8-11, 1991. U.S. Department of Agriculture, Forest Service, Southeastern Forest Experiment Station. https://www.srs.fs.usda.gov/pubs/gtr/gtr_se078.pdf
Gyllin, M., & Grahn, P. (2015). Semantic Assessments of Experienced Biodiversity from Photographs and On-Site Observations – A Comparison. Environment and Natural Resources Research, 5(4), 46. https://doi.org/10.5539/enrr.v5n4p46
Greene, W. H., & Hensher, D. A. (2010). Modelling Ordered Choices: A Primer. Cambridge: Cambridge University Press.
Halstead, J. M., Luloff, A. E., & Stevens, T. H. (1992). Protest Bidders in Contingent Valuation. Northeastern Journal of Agricultural and Resource Economics, 21(2), 160–169. https://doi.org/10.1017/S0899367X00002683
Hanemann, M., Loomis, J., & Kanninen, B. (1991). Statistical Efficiency of Double-Bounded Dichotomous Choice Contingent Valuation. American Journal of Agricultural Economics, 73(4), 1255–1263. https://doi.org/10.2307/1242453
Hanley, N., Schläpfer, F., & Spurgeon, J. (2003). Aggregating the benefits of environmental improvements: Distance-decay functions for use and non-use values. Journal of Environmental Management, 68(3), 297–304. https://doi.org/10.1016/S0301-4797(03)00084-7
Harrison, G. W., & List, J.A. (2004). Field Experiments. Journal of Economic Literature 2004, 42, 1009–1055. https://doi.org/10.1257/0022051043004577
Jia, Y., Huang, Y., Wyer, R. S., & Shen, H. (2017). Physical proximity increases persuasive effectiveness through visual imagery. Journal of Consumer Psychology, 27(4), 435–447. https://doi.org/10.1016/j.jcps.2017.07.001
Johnston, R. J., Boyle, K. J., Adamowicz, W. (Vic), Bennett, J., Brouwer, R., Cameron, T. A., Hanemann, W. M., Hanley, N., Ryan, M., Scarpa, R., Tourangeau, R., & Vossler, C. A. (2017). Contemporary Guidance for Stated Preference Studies. Journal of the Association of Environmental and Resource Economists, 4(2), 319–405. https://doi.org/10.1086/691697
Jørgensen, S. L., Olsen, S. B., Ladenburg, J., Martinsen, L., Svenningsen, S. R., & Hasler, B. (2013). Spatially induced disparities in users’ and non-users’ WTP for water quality improvements – Testing the effect of multiple substitutes and distance decay. Ecological Economics, 92, 58–66. https://doi.org/10.1016/j.ecolecon.2012.07.015
Kniivilä, M. (2006). Users and non-users of conservation areas: Are there differences in WTP, motives and the validity of responses in CVM surveys? Ecological Economics, 59(4), 530–539. https://doi.org/10.1016/j.ecolecon.2005.11.017
Kroh, D. P., & Gimblett, R. H. (1992). Comparing live experience with pictures in articulating landscape preference. Landscape Research, 17(2), 58–69. https://doi.org/10.1080/01426399208706362
LaRiviere, J., Czajkowski, M., Hanley, N., Aanesen, M., Falk-Petersen, J., & Tinch, D. (2014). The value of familiarity: Effects of knowledge and objective signals on willingness to pay for a public good. Journal of Environmental Economics and Management, 68(2), 376–389. https://doi.org/10.1016/j.jeem.2014.07.004
Lifang, Z., Ting, Y., Yang, L., & Li, Z. (2020). Analyses on the Spatial Distribution Characteristics of Urban Rental Housing Supply and Demand Hotspots Based on Social Media Data. 2020 5th IEEE International Conference on Big Data Analytics (ICBDA), 126–130. https://doi.org/10.1109/ICBDA49040.2020.9101317
Liu, C., Lin, M., Qi, X., & Zheng, W. (2021). Estimating the Preservation Value of Wuyishan National Park from the Perspective of Bounded Rational Decision Making. Sustainability, 13(13), 6983. https://doi.org/10.3390/su13136983
Loomis, J., Gonzalez-Caban, A., & Gregory, R. (1994). Do Reminders of Substitutes and Budget Constraints Influence Contingent Valuation Estimates? Land Economics, 70(4), 499. https://doi.org/10.2307/3146643
Lo, A. Y., & Jim, C. Y. (2015). Protest response and willingness to pay for culturally significant urban trees: Implications for Contingent Valuation Method. Ecological Economics, 114, 58–66. https://doi.org/10.1016/j.ecolecon.2015.03.012
Long J. S,. & Freese J. (2014). Regression Models for Categorical Dependent Variables Using Stata, Third Edition (Third Edition). Stata Press.
Lusk, J. L. (2004). Effect of information about benefits of biotechnology on consumer acceptance of genetically modified food: Evidence from experimental auctions in the United States, England, and France. European Review of Agriculture Economics, 31(2), 179–204. https://doi.org/10.1093/erae/31.2.179
MacMillan, D., Hanley, N., & Lienhoop, N. (2006). Contingent valuation: Environmental polling or preference engine? Ecological Economics, 60(1), 299–307. https://doi.org/10.1016/j.ecolecon.2005.11.031
Matel, A., & Poskrobko, T. (2019). Could survey technique or other research conditions “change” our ecological behaviour? – Testing response bias in consumer research. Ekonomia i Środowisko – Economics and Environment, 71(4), 16. https://doi.org/10.34659/2019/4/46
Mitchell, R. C., & Carson, R. T. (1988). Evaluating the validity of contingent valuation studies. Resources for the Future.
Mittal, J., & Byahut, S. (2019). Scenic landscapes, visual accessibility and premium values in a single family housing market: A spatial hedonic approach. Environment and Planning B: Urban Analytics and City Science, 46(1), 66–83. https://doi.org/10.1177/2399808317702147
Napolitano, F., Pacelli, C., Girolami, A., & Braghieri, A. (2008). Effect of Information About Animal Welfare on Consumer Willingness to Pay for Yogurt. Journal of Dairy Science, 91(3), 910–917. https://doi.org/10.3168/jds.2007-0709
Nunnally, J. C., & Bernstein, I. (1994). Psychometric theory 3E. McGraw-Hill Education.
Parsons, G., & Yan, L. (2021). Anchoring on visual cues in a stated preference survey: The case of siting offshore wind power projects. Journal of Choice Modelling, 38, 100264. https://doi.org/10.1016/j.jocm.2020.100264
Pate, J., & Loomis, J. (1997). The effect of distance on willingness to pay values: A case study of wetlands and salmon in California. Ecological Economics, 20(3), 199–207. https://doi.org/10.1016/S0921-8009(96)00080-8
Riera, P., et al. (2012). Non-market valuation of forest goods and services: Good practise guidelines, Journal of Forest Economics, 18(4), 259–270. https://doi.org/10.1016/j.jfe.2012.07.001
Rolfe, J.; Bennett, J.; Louviere, J. Stated Values and Reminders of Substitute Goods: Testing for Framing Effects with Choice Modelling. Australian Journal of Agricultural and Resource Economics 2002, 46, 1–20, https://doi.org/10.1111/1467-8489.00164
Sayadi, S., González-Roa, M. C., & Calatrava-Requena, J. (2009). Public preferences for landscape features: The case of agricultural landscape in mountainous Mediterranean areas. Land Use Policy, 26(2), 334–344. https://doi.org/10.1016/j.lan-dusepol.2008.04.003
Schaafsma, M., Brouwer, R., & Rose, J. (2012). Directional heterogeneity in WTP models for environmental valuation. Ecological Economics, 79, 21–31. https://doi.org/10.1016/j.ecolecon.2012.04.013
Sevenant, M., & Antrop, M. (2011). Landscape Representation Validity: A Comparison between On-site Observations and Photographs with Different Angles of View.
Landscape Research, 36(3), 363–385. https://doi.org/10.1080/01426397.2011.564858
Shechter, M., & Freeman, S. (1994). Nonuse Value: Reflections on the Definition and Measurement. In R. Pethig (Ed.) Valuing the Environment: Methodological and Measurement Issues (pp. 171–194). Springer Netherlands. https://doi.org/10.1007/978-94-015-8317-6_7
Shi, J., Honjo, T., Zhang, K., & Furuya, K. (2020). Using Virtual Reality to Assess Landscape: A Comparative Study Between On-Site Survey and Virtual Reality of Aesthetic Preference and Landscape Cognition. Sustainability, 12(7), 2875. https://doi.org/10.3390/su12072875
Smith, V. K. (1987). Nonuse Values in Benefit Cost Analysis. Southern Economic Journal, 54(1), 19. https://doi.org/10.2307/1058800
Sutherland, R. J., & Walsh, R. G. (1985). Effect of Distance on the Preservation Value of Water Quality. Land Economics, 61(3), 281. https://doi.org/10.2307/3145843
System of Environmental-Economic Accounting 2012. Central Framework. (2014).
United Nations. European Union. Food and Agriculture Organization of the United Nations. International Monetary Fund. Organisation for Economic Cooperation and Development. The World Bank. https://unstats.un.org/unsd/envaccounting/seearev/seea_cf_final_en.pdf
Tabi, A., & del Saz-Salazar, S. (2015). Environmental damage evaluation in a willingness-to-accept scenario: A latent-class approach based on familiarity. Ecological Economics, 116, 280–288. https://doi.org/10.1016/j.ecolecon.2015.05.010
Toma, L., Stott, A. W., Revoredo-Giha, C., & Kupiec-Teahan, B. (2012). Consumers and animal welfare. A comparison between European Union countries. Appetite, 58(2), 597–607. https://doi.org/10.1016/j.appet.2011.11.015
Weber, S., Horak, S., & Marusic, Z. (2002). Valuation of environmental assets: A case of Croatian coastal forests. Tourism Review, 57(1/2), 22–28. https://doi.org/10.1108/eb058375
Whitehead, J. C., Blomquist, G. C., Hoban, T. J., & Clifford, W. B. (1995). Assessing the Validity and Reliability of Contingent Values: A Comparison of On-Site Users, OffSite Users, and Non-users. Journal of Environmental Economics and Management, 29(2), 238–251. https://doi.org/10.1006/jeem.1995.1044
Williams, R. (2012). Using the Margins Command to Estimate and Interpret Adjusted Predictions and Marginal Effects. The Stata Journal: Promoting Communications on Statistics and Stata, 12(2), 308–331. https://doi.org/10.1177/1536867X1201200209
Xiang, Y., Liang, H., Fang, X., Chen, Y., Xu, N., Hu, M., Chen, Q., Mu, S., Hedblom, M., Qiu, L., & Gao, T. (2021). The comparisons of on-site and off-site applications in surveys on perception of and preference for urban green spaces: Which approach is more reliable? Urban Forestry & Urban Greening, 58, 126961. https://doi.org/10.1016/j.ufug.2020.126961
Xiao, Y., Orford, S., & Webster, C. J. (2016). Urban configuration, accessibility, and property prices: A case study of Cardiff, Wales. Environment and Planning B: Planning and Design, 43(1), 108–129. https://doi.org/10.1177/0265813515600120
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