Psychological influence on survey incentives: valuing climate change adaptation benefits in agriculture

  • Uttam Khanal
  • Clevo Wilson
  • Shunsuke Managi
  • Boon Lee
  • Viet-Ngu Hoang
  • Robert Gifford
Research Article
  • 162 Downloads

Abstract

Psychological influences affect the way people value the environment. However, traditional economic valuation models often do not account for how people are asked about valuing the environment. We examined how valuations by Nepalese farmers differ based on how the questions are asked and which incentives are provided. In a face-to-face choice experiment, incentive receivers spent more time than incentive non-receivers answering the survey, but were not more likely to choose a status quo option. Prepaid survey incentives had minimal effect on the stated welfare measures. The results suggest that prepaid incentives increase response rates, but do not increase welfare estimates. The findings also strengthen the methodological validity of our results, which indicated that farmers are willing to pay a substantial amount to secure climate change adaptation benefits on their land.

Keywords

Choice experiment Survey incentives Response behavior Climate change adaptation 

JEL Classification

Q18 Q51 Q56 

References

  1. Adamowicz W, Boxall P, Williams M, Louviere J (1998) Stated preference approaches for measuring passive use values: choice experiments and contingent valuation. Am J Agr Econ 80:64–75CrossRefGoogle Scholar
  2. Ahlheim M, Börger T, Frör O (2013) The effects of extrinsic incentives on respondent behaviour in contingent valuation studies. J Environ Econ Policy 2:45–70CrossRefGoogle Scholar
  3. Battaglia MP, Khare M, Frankel MR, Murray MC, Buckley P, Peritz S (2007) Response rates: how have they changed and where are they headed? In: Lepkowski JM, Tucker C, Brick JM, de Leeuw ED, Japec L, Lavrakas PJ, Link MW, Sangster RL (Eds) Advances in telephone survey methodology. Wiley, Hoboken, NJ, USAGoogle Scholar
  4. Bech M, Kjaer T, Lauridsen J (2011) Does the number of choice sets matter? Results from a web survey applying a discrete choice experiment. Health Econ 20:273–286CrossRefGoogle Scholar
  5. Boxall PC, Adamowicz WL, Swait J, Williams M, Louviere J (1996) A comparison of stated preference methods for environmental valuation. Ecol Econ 18:243–253CrossRefGoogle Scholar
  6. Cantor D, O’Hare BC, O’Connor KS (2008) The use of monetary incentives to reduce nonresponse in random digit dial telephone surveys. In: Lepkowski JM, Tucker C, Brick JM, de Leeuw ED, Japec L, Lavrakas PJ, Link MW, Sangster RL (Eds) Advances in telephone survey methodology. Wiley, Hoboken, NJ, USAGoogle Scholar
  7. Carlsson F, Mørkbak MR, Olsen SB (2012) The first time is the hardest: a test of ordering effects in choice experiments. J Choice Model 5:19–37CrossRefGoogle Scholar
  8. Clark CF, Kotchen MJ, Moore MR (2003) Internal and external influences on pro-environmental behavior: participation in a green electricity program. J Environ Psychol 23:237–246CrossRefGoogle Scholar
  9. Colombo S, Hanley N, Louviere J (2009) Modeling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture. Agric Econ 40:307–322CrossRefGoogle Scholar
  10. Creel MD, Loomis JB (1991) Confidence intervals for welfare measures with application to a problem of truncated counts. Rev Econ Stat 73:370–373CrossRefGoogle Scholar
  11. de Jalón SG, Iglesias A, Quiroga S, Bardají I (2013) Exploring public support for climate change adaptation policies in the Mediterranean region: a case study in Southern Spain. Environ Sci Policy 29:1–11CrossRefGoogle Scholar
  12. De Leeuw E, De Heer W (2002) Trends in household survey nonresponse: a longitudinal and international comparison. Surv Nonresponse 41–54Google Scholar
  13. Dillman DA, Phelps G, Tortora R, Swift K, Kohrell J, Berck J, Messer BL (2009) Response rate and measurement differences in mixed-mode surveys using mail, telephone, interactive voice response (IVR) and the Internet. Soc Sci Res 38:1–18CrossRefGoogle Scholar
  14. Gajic A, Cameron D, Hurley J (2012) The cost-effectiveness of cash versus lottery incentives for a web-based, stated-preference community survey. Eur J Health Econ 13:789–799CrossRefGoogle Scholar
  15. Gifford R (2011) The dragons of inaction: psychological barriers that limit climate change mitigation and adaptation. Am Psychol 66:290CrossRefGoogle Scholar
  16. Goldenberg J, Han S, Lehmann DR, Hong JW (2009) The role of hubs in the adoption process. J Mark 73:1–13CrossRefGoogle Scholar
  17. Gouldner AW (1960) The norm of reciprocity: a preliminary statement. Am Soc Rev 25:161–178CrossRefGoogle Scholar
  18. Hanley N, Wright RE, Adamowicz V (1998) Using choice experiments to value the environment. Environ Resour Econ 11:413–428CrossRefGoogle Scholar
  19. Hanley N, Mourato S, Wright RE (2001) Choice modelling approaches: a superior alternative for environmental valuation? J Econ Surv 15:435–462CrossRefGoogle Scholar
  20. Hensher DA (2006) How do respondents process stated choice experiments? Attribute consideration under varying information load. J Appl Econom 21:861–878CrossRefGoogle Scholar
  21. Hensher DA, Rose JM, Greene WH (2005) Applied choice analysis: a primer, 1st edn. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  22. Hidano N, Kato T, Aritomi M (2005) Benefits of participating in contingent valuation mail surveys and their effects on respondent behavior: a panel analysis. Ecol Econ 52:63–80CrossRefGoogle Scholar
  23. Islam MM, Barnes A, Toma L (2013) An investigation into climate change scepticism among farmers. J Environ Psychol 34:137–150CrossRefGoogle Scholar
  24. Islam M, Kotani K, Managi S (2016) Climate perception and flood mitigation cooperation: a Bangladesh case study. Econ Anal Policy 49:117–133CrossRefGoogle Scholar
  25. James JM, Bolstein R (1990) The effect of monetary incentives and follow-up mailings on the response rate and response quality in mail surveys. Public Opin Quart 54:346–361CrossRefGoogle Scholar
  26. Lancaster KJ (1966) A new approach to consumer theory. J Polit Econ 74:132–157CrossRefGoogle Scholar
  27. Liebe U, Glenk K, Oehlmann M, Meyerhoff J (2015) Does the use of mobile devices (tablets and smartphones) affect survey quality and choice behaviour in web surveys? J Choice Model 14:17–31CrossRefGoogle Scholar
  28. Louviere JJ, Street D, Burgess L, Wasi N, Islam T, Marley AA (2008) Modeling the choices of individual decision-makers by combining efficient choice experiment designs with extra preference information. J Choice Model 1:128–164CrossRefGoogle Scholar
  29. Medway R (2012) Beyond response rates: the effect of prepaid incentives on measurement error. University of Maryland, College ParkGoogle Scholar
  30. MoE (2010) National adaptation programme of action to climate change. Ministry of Environment, KathmanduGoogle Scholar
  31. Moyer A, Brown M (2008) Effect of participation incentives on the composition of national health surveys. J Health Psychol 13:870–873CrossRefGoogle Scholar
  32. Petrolia DR, Bhattacharjee S (2009) Revisiting incentive effects evidence from a random-sample mail survey on consumer preferences for fuel ethanol. Public Opin Quart 73:537–550CrossRefGoogle Scholar
  33. Price JC, Walker IA, Boschetti F (2014) Measuring cultural values and beliefs about environment to identify their role in climate change responses. J Environ Psychol 37:8–20CrossRefGoogle Scholar
  34. Rajmis S, Barkmann J, Marggraf R (2009) User community preferences for climate change mitigation and adaptation measures around Hainich National Park, Germany. Clim Res 40:61–73CrossRefGoogle Scholar
  35. Ryu E, Couper MP, Marans RW (2006) Survey incentives: cash vs. in-kind; face-to-face vs. mail; response rate vs. nonresponse error. Int J Public Opin Res 18:89–106CrossRefGoogle Scholar
  36. Simmons E, Wilmot A (2004) Incentive payments on social surveys: a literature review. Soc Surv Methodol Bull 53:1–11Google Scholar
  37. Swait J, Louviere J (1993) The role of the scale parameter in the estimation and comparison of multinomial logit models. J Mark Res 30:305–314CrossRefGoogle Scholar
  38. Trussell N, Lavrakas PJ (2004) The influence of incremental increases in token cash incentives on mail survey response is there an optimal amount? Public Opin Quart 68:349–367CrossRefGoogle Scholar
  39. Whitmarsh L (2009) Behavioural responses to climate change: asymmetry of intentions and impacts. J Environ Psychol 29:13–23CrossRefGoogle Scholar

Copyright information

© Society for Environmental Economics and Policy Studies and Springer Japan KK 2017

Authors and Affiliations

  • Uttam Khanal
    • 1
  • Clevo Wilson
    • 1
  • Shunsuke Managi
    • 2
  • Boon Lee
    • 1
  • Viet-Ngu Hoang
    • 1
  • Robert Gifford
    • 3
  1. 1.QUT Business SchoolQueensland University of TechnologyBrisbaneAustralia
  2. 2.Urban Institute, Department of Urban and Environmental Engineering, Faculty of EngineeringKyushu UniversityFukuokaJapan
  3. 3.University of VictoriaVictoriaCanada

Personalised recommendations