Proceedings of the 2009 northeastern recreation research symposium

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A COMPARATIVE ANALYSIS OF MAIL AND INTERNET SURVEYS Benjamin D. Poole University of Massachusetts bpoole@nrc.umass.edu David K. Loomis University of Massachusetts Abstract.—Th e fi eld of survey research is constantly evolving with the introduction of new technologies. Each new mini-revolution brings criticism about the accuracy of the new survey method. Th e latest development in the survey research fi eld has been increased reliance on Internet surveys. Th is paper compares data collected through a mixed-mode (mail and Internet) survey of Zuma Beach users in Malibu, CA, focusing on diff erences in response rate and in responses to questions between the two modes. Two-sample t-tests were performed on each variable to determine diff erences between the modes. Th ese tests found 15 signifi cant diff erences in responses to demographic variables, scale items, and Likert items. Th e format of questions is discussed as a possible explanation for some of these diff erences in responses. 1.0 INTRODUCTION Th e widespread availability of the Internet and the rapid pace at which online technologies develop has led to a rise in Internet-based social research, mainly in the form of electronic surveys. Ease of use, low cost, and advanced capabilities make Internet surveys an attractive medium to many researchers. Internet surveys also have some potential limitations. Two of the most often criticized (and studied) aspects of Internet surveys are lower response rates than mail surveys, which could indicate a nonresponse bias (Manfreda et al. 2002), and real or potential diff erences between data collected online and data from mail-based surveys. To examine these two possible limitations, a mixed-mode survey method was used during a recent research project at Zuma Beach in Malibu, CA. Th e primary goal of this project was to pilot-test questions about social benefi ts of coastal restoration. In addition, the response rates and likeness of data collected between mail and Internet versions of the survey were analyzed. 2.0 METHODS Data were collected through a survey sent to individuals who used Zuma Beach during summer 2008. Th e researchers followed a sampling schedule which randomized the time of day, day of the week, and area of the beach from which they drew their sample. Potential participants were fi rst asked to participate in a research project about beach use. If they agreed to participate, they were asked to provide their name as well as either a mailing address or an email address; those who provided both were randomly assigned to one of the groups. During fi eld-sampling, 1,416 people provided useable contact information. Two-thirds of the sample (949 individuals) subsequently received the mail version of the questionnaire and the remaining one-third (467 individuals) received the Internet version. Th e mail version of the questionnaire was distributed using the Dillman Total Design Method (Dillman 1978). Th e Internet version of the survey was distributed using a similar design (Dillman 2000). Individuals in the Internet group received four email contacts from the researchers, consistent with the traditional Dillman Total Design Method. However, the day of the week on which a participant received the email notifi cations was varied to account for individuals who check their email at diff erent frequencies. 3.0 RESULTS 3.1 Modal Response Rates Th e research sought to determine whether response rates between the two modes were diff erent. Prior research in this fi eld has implied that mail-based surveys have higher response rates than their online counterparts (Smee and Brennan 2000, Fricker and Schonlau 2002, Kaplowitz et al. 2004). Th e response rates in this research are 50 Proceedings of the 2009 Northeastern Recreation Research Symposium GTR-NRS-P-66 231
Table 1.—Modal response rates Initial Sample Non-Deliverable percent for the mail version and 44 percent for the Internet version (Table 1). It is important to note that these two rates are not statistically diff erent (p=0.21). 3.2 Differences in Responses Effective Sample Th e analysis also examined diff erences between the actual responses that participants provided. Diff erences between mail and Internet groups were tested using a two-sample t-test performed on all 144 variables. Using an �-level of 0.10, we expected to observe 14 signifi cant diff erences between responses. An �-level of 0.10 is used instead of the conventional 0.05 because it is a more powerful statistical test, though less rigorous (Trochim 2000, Gigerenzer 2004). In this type of social research, this �-level is suffi cient for drawing statistically signifi cant conclusions. Fifteen signifi cant diff erences occurred between the sets of data in demographic profi le information and responses to scale and Likert items. 3.2.1 Respondent demographic diff erences Th e two groups of respondents were virtually identical in demographics (Table 2). Cole (2005) suggests that mail survey respondents are likely to be older than online survey respondents. In this research project, however, online survey respondents were signifi cantly older (mean age = 45 years) than mail survey respondents (mean age = 41 years). Th e two respondent groups diff er signifi cantly in income level; Internet survey respondents have a Completed Surveys Response Rate Mail version 949 66 883 441 50% Internet version 467 71 396 173 44% Table 2.—Demographic profi le of the average respondent, by mode Mail Respondents Internet Respondents Gender Female Female Age 41* years 45* years Racial category White White Annual income $75,000 - $99,000* $100,000 - $124,999* Level of education Bachelor’s degree Bachelor’s degree Children living at home Yes Yes *Signifi cantly different at the α = 0.10 level. higher average income than mail survey respondents. Th is income diff erence may refl ect diff erent levels of Internet access and/or profi ciency between the two groups. 3.2.2 Response diff erences on scale items Th ree of the 15 signifi cant diff erences in the data were in questionnaire items, where the participant was asked to assess the level of a variable (e.g., familiarity, crowding) on a 9-point scale. In the mail version, participants were instructed to circle a number on a number line to identify their level of a variable (Fig. 1A). Th e Internet version required that respondents click an un-numbered radio button to indicate their level of a variable (Fig. 1B). Online survey respondents consistently rated variables lower on these Discrete Visual Analog Scale (DVAS) items than did mail respondents. DVASs may be more ambiguous than their Likert-type cousins because they lack labels for each point on the scale (Uebersax 2006). Th e presence of a number in the paper version may have helped respondents “anchor” their response to the question by associating their level of a variable with an actual number. Because there was no numerical label for each radio button, Internet participants could rely only on the verbal descriptions at the poles of the scale as a basis for their ratings. In essence, online survey respondents lacked the advantage of having each possible rating “explained” by a numerical label as the mail respondents did. Proceedings of the 2009 Northeastern Recreation Research Symposium GTR-NRS-P-66 232
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United States Department of Agricul
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PROCEEDINGS OF THE 2009 NORTHEASTER
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OUTDOOR RECREATION—TRAILS Experie
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GIS APPLICATIONS AND RECREATION RES
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diff erent points along the spectru
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Proceedings of the 2009 Northeaster
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amount of bare rock. Camel’s Hump
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Larson, M. 2004. A Passive Approach
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THE ROLE OF IMAGINATION IN EXPERIEN
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Table 1.—Special places surveys L
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For some people, being in their spe
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CLIMATE CHANGE AND RESOURCE PLANNIN
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large geographical area (Fig. 1). T
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Divers seen = 4.4 Figure 2.—Norm
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Table 4.—Most-specialized divers
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Sarah Young Human Dimensions of Mar
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3.0 RESULTS AND DISCUSSION Th e FRR
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Table 4.—Divers’ perception of
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YOUTH AND OUTDOOR RECREATION
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A qualitative research design was u
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containers, instead of plastic bags
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WALK, RIDE AND LEARN: STUDENTS’ D
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school. Because of the large sample
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Table 8.—Observation of built str
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“I’M TOO OLD TO GO OUTSIDE!”
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Mean Eco-Affinity Score 5.0 4.5 4.0
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children. In: Klenosky, David B., F
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Cherie LeBlanc Fisher U.S Forest Se
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Table 1.—Comparative statistics f
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did some fi shing himself at each s
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On the other hand, some personal kn
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Illinois Department of Natural Reso
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Consumer behavior researchers have
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50 percent of the households were d
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y respondents indicated that these
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a bivariate approach (instead of th
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HERITAGE TOURISM DEVELOPMENT IN RUR
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Short cruise season. Th e river fre
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Lynda J. Sperazza, Ph.D. Recreation
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2.3 Leisure Participation Values Re
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Dychtwald, K. 1999. Age power: How
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With all research, the research que
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comprehensive. Cross (2005) even ar
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Stillwater, OK: Oklahoma State Univ
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EXPERIENCE USE HISTORY AND ITS RELA
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Table 1.—Comparison of experience
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5.0 DISCUSSION As mentioned previou
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HUMAN DIMENSIONS OF WILDLIFE
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2.0 METHODS Data were collected at
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0 buses 4 buses 8 buses 12 buses Fi
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4.0 DISCUSSION Visitor surveys and
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LEISURE AND HEALTH
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Second, in a world where clean drin
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Table 1.—Importance of different
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Countries also need to be careful a
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Proceedings of the 2009 Northeaster
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Table 1.—Informant profi les Info
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do something and we might think it
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Th ese relational interactions enab
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EXPLORING ELEMENTS THAT INFLUENCE S
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trails, and asking others to stay o
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time/fi nances” in dune protectio
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In summary, this study explored the
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Jinhee Jun Texas A&M University jju
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Table 1.—Sample demographics Indi
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Grayson 1995). Th e fi t of this mo
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Stets, J.E.; Burke, P.J. 2003. A so
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Jiaying Lu Texas A& M University Ji
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Table 1.—Demographic and particip
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Table 3.—Factor analysis of motiv
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species sought, satisfaction, and r
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social nature within sense of place
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Table 1.—Descriptions of key info
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sharing the place with others and a
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Manzo, L.C. 2005. For better or wor
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NORMATIVE TOLERANCES FOR SCUBA DIVE
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neutral point. Bubbles at the top o
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Table 1.—Snorkeler evaluations of
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Davis, D.; Tisdell, C. 1995. Recrea
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William Valliere University of Verm
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Manning, R. 2007. Parks and carryin
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mission is “...to promote and reg
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Figure 1.—Pedestrian walkway LOS
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Acceptability 4 3 2 1 0 -1 -2 -3 -4
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TOURISM TRENDS AND CHALLENGES
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the rankings of 12 attendance motiv
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Table 3.—Comparison of socio-econ
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Table 6.—Entertainment Seekers’
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PLACE MEANINGS
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Stedman (1999) posited that sense o
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points in a focus group session, Ne
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are not shared by current residents
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Page 227 and 228: Demrow, C.C. 2002. Maine trails man
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Page 231 and 232: Chad P. Dawson, Professor State Uni
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Page 243 and 244: Table 1.—Characteristics of parti
Page 245 and 246: Table 3.—Results of discriminant
Page 247 and 248: 5.0 CITATIONS Babbie, E. 2001. Th e
Page 249 and 250: Bernardita Silva Graduate Assistant
Page 251 and 252: Table 1.—Expenditures by 2008 Ame
Page 253 and 254: 6.0 CITATIONS Della Bitta, A.; Lond
Page 255 and 256: the economic impact of travel, and
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Page 259 and 260: not displace other local spending.
Page 261 and 262: 6.0 CITATIONS Adams, P.D.; Parmente
Page 263 and 264: MANAGEMENT AND USE OF PARK, RECREAT
Page 265 and 266: which suggests that diff erent type
Page 267 and 268: Table 2.—Between-groups ANOVA to
Page 269 and 270: forest settings (means = 4.4 and 4.
Page 271 and 272: LEISURE RESEARCH
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Page 275 and 276: Table 2.—Life satisfaction scale
Page 277 and 278: onds within a social group is a mec
Page 279 and 280: “I JUST WANTED TO GET AWAY”: AN
Page 281 and 282: Th e importance of “getting away
Page 283 and 284: Gerlach, J. 1989. Spring Break at P
Page 285: www.nrs.fs.fed.us The U.S. Departme
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