The effect of reassured anonymity and sponsor on mail survey response rate and speed with a business population.
The popularity of the mail survey derives from the many advantages it offers the survey researcher. These are:
* low cost;
* ease of use over a large geographic area;
* likelihood of reaching sample members difficult to contact by other means;
* lack of interviewer bias;
* assurance of each sample member being asked the same questions in the same way; and
* ability to exercise centralized control over the survey.
On the limitation side is the potential bias brought about by low response rates. Improving mail response rates, as such, has been the focus of considerable research (Faria and Dickinson, 1992). This study investigates the effects of assuring respondents of both anonymity and survey sponsor on the response rate and response speed, with a business population. As opposed to incentives, anonymity and sponsor add little, if any, cost to mail surveys, yet have been the subject of little mail survey research, especially with business audiences.
Owing to the widespread use of mail surveys, researchers are interested in the effects of specific methodological characteristics on various outcome measures. Most reported research has concentrated on examining the effects of specific response inducement techniques on response rates with consumer samples. Of concern in these studies have been the effects of such characteristics as pre-contacts, follow-ups, questionnaire format and length, type of postage, personalization, cover letter appeal, questionnaire and cover letter color, deadline dates, premiums, and monetary rewards. Excellent reviews of a large number of studies have been written by Armstrong (1975), Armstrong and Lusk (1987), Blumberg et al. (1974), Bruvold and Comer (1988), Church (1993), Duncan (1979), Harvey (1987), Heberlein and Baumgartner (1978), Houston and Ford (1976), Janssens and Pessemier (1980), Kanuk and Berenson (1975), Linsky (1975), Peterson and Kerin (1981), Scott (1961), Yammarino, et al. (1991) and Yu and Cooper (1983).
Despite the considerable research, there is little consensus regarding the effects of various inducement techniques on response rates. Past research has identified only two factors on which there is agreement; mail survey response rates will be enhanced through the use of:
(1) monetary incentives; and
Unfortunately, both of these factors add considerable cost to the surveys. The issues of anonymity and survey sponsor, items of little or no additional survey cost, have received limited attention (particularly with business populations) and mixed reviews. Owing to the lack of additional cost and the ease of use of these variables, their effect on survey response rates should be of interest to survey researchers.
The issue of anonymity is considered to be an important one in the mail survey literature. It is generally held that the assurance of anonymity or confidentiality encourages response, although empirical findings are mixed. The authors reviewed 23 studies which examined the impact of anonymity on response rate. In 16 of the studies, anonymity was shown to have no significant effect on response rate (Albaum, 1987; Butler, 1973; Childers and Skinner, 1985; DeLamater and MacCorquodale, 1975; Downs and Kerr, 1986; Erdos and Regier, 1977; Faria and Dickinson, 1989; Futrell, 1981; Futrell and Swan, 1977; Jones, 1979; King, 1970; Mason et al. 1961; Mitchell, 1973; Pearlin, 1961; Rosen, 1960; Wildman, 1977). The remaining seven studies reported a statistically significant increase in response rate with promised anonymity (Andreasen, 1970; Fuller, 1974; Houston and Jefferson, 1975; Pressley and Dunn, 1985; Scott, 1961; Singer, 1978; Tyagi, 1989).
Four studies have examined anonymity and response speed (Albaum, 1987; Faria and Dickinson, 1989; Tyagi, 1989; Wildman, 1977). Consistent with many studies of this criterion, all four report no significant response speed difference between a coded questionnaire format (not anonymous) and a non-coded format.
Anonymity may be more important to business populations than it is to the general population, as businesspeople may perceive some risk with regard to their job or position, especially if job-related questions are asked. Only four of the anonymity studies involved a business population. Of these, two reported a response rate increase with anonymity (Pressley and Dunn, 1985; Tyagi, 1989) while two reported no anonymity effect (Futrell, 1981; Futrell and Swan, 1977). The one study that reported on the response speed of a business population (Tyagi, 1989) showed no significant difference based on anonymity/non-anonymity. The present study considers the circumstance in which anonymity is assured and focusses on the manner in which that assurance is communicated. The approach used in this study may help to clarify the mixed results found in past studies addressing the anonymity issue.
Bachmann (1987) has noted that there is a paucity of published research on the effect of sponsorship on survey response rates. This is particularly true with regard to business populations, and the findings from the limited published research are mixed.
Fourteen published studies, spread over a 27-year period, have examined the use of a university sponsor versus some other form of organizational sponsorship. Doob et al. (1973), Faria and Dickinson (1992), Greer and Lohtia (1994), Hawkins (1979), Jones and Lang (1980), Jones and Linda (1978), Peterson (1975) and Resnik and Harmon (1985) reported higher return rates for university sponsors than for government or commercial sponsors. Albaum (1987), Bachmann (1987), Houston and Nevin (1977), Nitecki (1976), O'Connor et al. (1981), and Scott (1961), on the other hand, reported higher response rates from government or commercial sponsors than from university sponsorship, or no response rate differences.
Only five studies were found which examined sponsor and response speed. Albaum (1987) and Scott (1961) reported that a university sponsor achieved faster responses than either a commercial or government sponsor, while Peterson (1975) and Faria and Dickinson (1992) reported faster responses to a commercial sponsor than to a university sponsor. Houston and Nevin (1977) reported no response speed difference between a university sponsor and a commercial sponsor. Only the Faria and Dickinson (1992) and Greer and Lohtia (1994) studies involved the use of a business population.
Owing to the mixed results reported in past studies, and the limited research involving business audiences, the present study was designed to clarify the effects of survey sponsor and anonymity on both mail response rate and response speed with a business population.
Purpose and hypotheses
The present study tested two anonymity conditions and two survey sponsors. The two anonymity conditions, as will be explained later, involved a single versus a double assurance of anonymity. As all past research has involved anonymity/non-anonymity conditions, this study pioneers new territory with regard to the use of anonymity in mail surveys. If anonymity is important in mail surveys, the reassurance of this condition should further enhance survey responses. The two sponsorship conditions involved a university sponsor and a commercial sponsor. The commercial sponsor was a research firm unknown to the survey sample.
The business sample used in this study comprised dealers contractually related to an identified manufacturer supplier. As the study involved sample members' perceptions of the manufacturer's products and services, including such sensitive issues as feelings towards specific manufacturer personnel, the assurance of anonymity was necessary. Following from this, emphasizing anonymity by means of a second stated assurance was expected to reinforce the effect of anonymity resulting in both a higher response rate and a greater speed of response. The authors proposed the following hypotheses:
H1: Mailings including a second assurance of anonymity will achieve a significantly higher response rate than those with a single assurance of anonymity.
H2: Mailings including a second assurance of anonymity will elicit a significantly greater speed of response than those with a single assurance of anonymity.
As reviewed earlier, past research results concerning survey sponsor are mixed. In the present study, the main role of the sponsor was to guarantee that respondent anonymity was maintained. The sponsor administered the survey and also acted as a shield between the client and individual respondents. This is in contrast to other implications of survey sponsorship, such as respondent inferences as to the purpose of the research. For instance, university and marketing research firm sponsorship in other circumstances might be perceived as differing with respect to a profit motive underlying the research. Even in the present study, university sponsorship was expected to be perceived by potential respondents as less susceptible to client influence. And with this, university sponsorship was expected to result in both a higher response rate and a greater speed of response. These assumptions lead to:
H3: The university sponsorship condition will result in a significantly higher response rate than the commercial sponsorship condition.
H4: The university sponsorship condition will result in a significantly greater speed of return than the commercial sponsorship condition.
As the survey sponsor was automatically serving as a shield between the client and the potential respondent, no interaction between the sponsorship and anonymity assurance treatments was hypothesized. And, as the predominance of past research has found no material effect, the additional response quality criterion of item omission was not studied.
The population under study consisted of dealerships for a major manufacturer. The dealerships handle the new and used products of the manufacturer, the parts and servicing needs of customers, and provide finance for major purchases. Customers of the dealerships are also businesspeople. Across the country there are 208 dealerships for the manufacturer, all of whom were surveyed. Packets containing two cover letters, a four-part questionnaire, and postage-paid return envelope were mailed to each dealership using first-class postage.
The questionnaire was quite lengthy (11 pages) and covered the new product operations of the dealership (35 questions), parts operations (62 questions), service operations (19 questions), and financing operations (19 questions); a total of 135 questions. It was anticipated that the questionnaire would take approximately two hours to complete and might require input from several people.
The questionnaire was accompanied by two cover letters. One, stapled to the questionnaire, was written by the director of marketing of the manufacturer. This letter stressed the importance of completing the questionnaire and indicated that the anonymity of each respondent would be assured by having the questionnaire returned to a source separate from the manufacturer. In half of the cover letters (104) the source was identified as a commercial market research firm, with return envelope to the market research firm, and in the other half (104) the source was identified as a university with the return envelope being to the university address.
A second cover letter, placed on top of the previous cover letter and the questionnaire, was from the survey researcher. Half of these cover letters were on the letterhead of a commercial market research firm and half were on the letterhead of a large university. This second cover letter introduced the survey that would follow, identified the type of information that was sought and why, and indicated the approximate time that it would take to complete the survey. In half of these cover letters (104) a second assurance of anonymity was given while in the other half (104) no such second assurance was made. Where given, the assurance of anonymity was detailed in the third paragraph of each cover letter.
Anonymity and survey sponsor
Thus, the experiment reported here is of a 2 x 2 factorial design as shown in Table I. The effect of two variables, anonymity and survey sponsor, were tested at two levels each. From the population of 208 dealerships, individual dealerships were randomly assigned to one of the four treatment groups, resulting in 52 potential respondents per cell.
Analysis and results
For each combination of treatment levels, response rate was operationally defined as the number of questionnaires returned divided by 52. Reflecting the ongoing relationship between sample members and the manufacturer and, hence, the currency of the available mailing list, no questionnaires were returned as undeliverable. Response speed was defined as the number of business days (i.e. Saturdays and Sundays were not counted) elapsing between the time of mailing and the day a completed questionnaire was received.
Percentage response rates and average days to respond for each combination of treatment levels are presented in Table I. The overall response rate was 75.5 percent and the overall mean number of days to respond was 12.08.
A two-way fixed-effects factorial analysis of variance was used to test the research hypotheses. More specifically, as all four hypotheses were based on a priori directional theories, actual statistical tests were contrasts.
As speed of response is intervally scaled, this criterion satisfied the dependent variable requirement for use of analysis of variance. While response is dichotomous, i.e. either a completed questionnaire was returned or it was not, Lunney (1970) has shown that analysis of variance may be applied to dichotomous data if the treatment level proportions are not extreme, the sample size is large ([greater than] 50), and sample sizes under each treatment combination are equal. These conditions hold in this study.
The single assurance of anonymity resulted in a 73.1 percent response rate, compared to 77.9 percent for the double assurance of anonymity. As the hypotheses are based on a priori theory, the appropriate test is a directional contrast (Neter and Wasserman (1974, p. 590)). While the response rate difference is in the direction hypothesized, the contrast of 4.8 percent is not significant (p [greater than] 0.2) and H1 is not supported.
University Commercial sponsor sponsor Average % Days % Days % Days
No second assurance 82.7 11.7 63.5 11.6 73.1 11.6 Second assurance 84.6 12.2 71.2 12.9 77.9 12.5 Average 83.7 11.9 67.3 12.3 75.5 12.1
Table I. Percentage response rates and average days to respond
The double assurance of anonymity resulted in a slower response speed than did the single assurance, mean days being 12.49 and 11.63, respectively. The contrast of 0.86 days is statistically significant (p [less than] 0.025) but is not in the direction hypothesized. Thus, H2 is not supported. Significance notwithstanding, the speedier average response of less than one day does not represent a material difference in most research situations.
The university sponsor treatment resulted in an 83.7 percent response rate, compared to 67.3 percent for the commercial research firm sponsorship. This difference is in the direction hypothesized, and the contrast of 16.4 percent is highly significant (p [less than] 0.005). Thus, H3 is supported.
The university sponsor treatment also resulted in slightly greater response speed than commercial sponsorship, mean days being 11.91 and 12.29, respectively. The contrast of 0.38 days is not significant (p [greater than] 0.1), however, and H4 is not supported.
As anticipated, for neither response rate nor response speed was interaction significant. However, the second assurance of anonymity did increase the response rate by 7.7 percent for the commercial sponsorship condition and only 1.9 percent for the university. This might suggest that respondents better trust universities to keep survey responses confidential and do not require a second assurance of anonymity with this type of sponsorship. This issue may warrant further attention.
The type of survey sponsor yielded a difference of over 16 percentage points in response rate, the increase with university sponsorship being about 24 percent above the commercial sponsorship rate. The benefit of this relationship accrues naturally to university-based researchers, but may seem to be outside the control of other researchers. However, the natural advantage that seems to accrue to universities may also be available to commercial firms. Universities commonly engage in joint research with industrial partners. Other means to achieving this benefit include faculty consultants, executive development programs, small business consulting units, university business research bureaus, members of the business community who also hold university appointments, business advisory boards, licensing agreements, and so on. Companies which frequently conduct mail surveys may find it worthwhile to establish a university affiliation.
The statistically insignificant impact of a double assurance of anonymity warrants further consideration. Response rate was, indeed, nominally improved by 4.8 percentage points. The power of the statistical test was limited by the cell sample size of 52. Had the cell sample size been, say, 130, this improvement would have been significant (p [less than] 0.1). One consideration then, when interpreting the results from this research, is the limited power owing to the sample size.
A second consideration for the researcher is that providing a second assurance of anonymity is essentially cost free, the only cost being the space occupied in the cover letter. Thus, since there is essentially no cost, researchers should consider including a second assurance, with the real probability that response rate will be increased. In the present study, in fact, the response rate for the commercial sponsorship condition was increased by 7.7 percent with the second assurance of anonymity - a response rate difference that could be quite important in many studies.
A third consideration is the nature of this experimental treatment. The second assurance of anonymity is a very subtle treatment and its effect should not be expected to be great. The offer of an incentive, in contrast, is brought very clearly to the attention of the potential respondent. Different types of appeals are blatantly conveyed to potential respondents. Indeed, even the assurance of anonymity compared to no assurance being given addresses what might be a serious concern to potential respondents. And it is the initial assurance that would be expected largely to assuage potential respondents' concerns. The second assurance is simply a reinforcement of an effect already established by the initial assurance.
The most effective combination of treatment levels in this study, university sponsorship with a second assurance of anonymity, yielded a response rate one-third greater than the least effective combination - commercial sponsorship with only a single assurance of anonymity (84.6 percent versus 63.5 percent). This very substantial improvement suggests that university sponsorship should be used where legitimately feasible and that, in surveys where response is to be anonymous, the cost-free measure of adding a second assurance should be utilized.
Finally, the high overall response rate of 75.5 percent and the fairly low number of overall mean business days for questionnaire return of 12.08, especially considering the lengthy questionnaire used in this study, suggest that the mail survey can be a very effective and timely means of gathering data from business-related populations.
In summary, this study has shown that:
* it is possible to achieve very high response rates, even with a lengthy questionnaire, when using mail surveys;
* university sponsorship can significantly increase response rate over the use of a commercial sponsor; and
* a second assurance of anonymity may add slightly to response rate.
References and further reading
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Andreasen, A.R. (1970), "Personalized mail questionnaire correspondence", Public Opinion Quarterly, Vol. 24, Summer, pp. 273-7.
Armenakis, A.A. and Lett, W.L. (1982), "Sponsorship and follow-up effects on response quality of mail surveys", Journal of Business Research, Vol. 10, pp. 251-62.
Armstrong, J.S. (1975), "Monetary incentives in mail surveys", Public Opinion Quarterly, Vol. 39, Spring, pp. 111-16.
Armstrong, J.S. and Lusk, E.J. (1987), "Return postage in mail surveys", Public Opinion Quarterly, Vol. 51, Summer, pp. 233-48.
Bachmann, D.P. (1987), "Cover letter appeals and sponsorship effects on mail survey response rates", Journal of Marketing Education, Vol. 46, Fall, pp. 45-51.
Berdie, D.R. (1973), "Questionnaire length and response rate", Journal of Applied Psychology, Vol. 58, Fall, pp. 278-80.
Blumberg, H.H, Fuller, C. and Hare, P. (1974), "Response rates in postal surveys", Public Opinion Quarterly, Vol. 28, Spring, pp. 113-23.
Brown, M.L. (1966), "Use of postcard query in mail surveys", Public Opinion Quarterly, Vol. 29, Winter, pp. 635-7.
Bruvold, N.T. and Comer, J.M. (1988), "A model for estimating the response rate to a mailed survey", Journal of Business Research, Vol. 16, Spring, pp. 101-16.
Butler, R.P. (1973), "Effects of signed versus unsigned questionnaires for both sensitive and nonsensitive items", Journal of Applied Psychology, Vol. 57, June, pp. 348-9.
Champion, D.J. and Sear, A.M. (1968), "Questionnaire response rate: a methodological analysis", Social Forces, Vol. 47, December, pp. 335-9.
Childers, T.L. and Ferrell, O.C. (1979), "Response rates and perceived questionnaire length in mail surveys", Journal of Marketing Research, Vol. 16, August, pp. 429-31.
Childers, T and Skinner, S. (1985), "Theoretical and empirical issues in the identification of survey respondents", Journal of the Market Research Society, Vol. 27, January, pp. 39-53.
Church, A.H. (1993), "Estimating the effect of incentives on mail survey response rates: a meta-analysis", Public Opinion Quarterly, Vol. 57, Spring, pp. 62-79.
DeLamater, J. and MacCorquodale, P. (1975), "The effects of interview schedule variation on reported sexual behavior", Sociological Methods and Research, Vol. 4, Spring, pp. 215-36.
Doob, A.N., Friedman, J.L. and Carlsmith, J.M. (1973), "Effects of sponsor and prepayment on compliance with a mailed request", Journal of Applied Psychology, Vol. 57, Fall, pp. 346-7.
Downs, P. and Kerr, J.R. (1986), "Recent evidence on the relationship between anonymity and response variables for mail surveys", Journal of the Academy of Marketing Science, Vol. 14, Spring, pp. 72-82.
Duncan, J. (1979), "Mail questionnaires in survey research: a review of response inducement techniques", Journal of Management, Vol. 5, Spring, pp. 39-55.
Erdos, P. and Regier, J. (1977), "Visible vs. disguised keying on questionnaires", Journal of Advertising Research, Vol. 17, Fall, pp. 13-18.
Faria, A.J. and Dickinson, J.R. (1989), "The effect of survey sponsor, questionnaire length, and anonymity on mail survey response rate and response speed", Proceedings of the Fourth Bi-annual World Marketing Congress, Academy of Marketing Science, Singapore, July, pp. 351-6.
Faria, A.J. and Dickinson, J.R. (1992), "Mail survey response rate, speed, and cost", Industrial Marketing Management, Vol. 21, January, pp. 51-61.
Fuller, C. (1974), "Effect of anonymity on return rate and response bias in mail surveys", Journal of Applied Psychology, June, pp. 292-6.
Futrell, C. (1981), "Effects of signed versus unsigned attitude questionnaires", Journal of the Academy of Marketing Science, Vol. 9, Spring, pp. 93-8.
Futrell, C. and Swan, J. (1977), "Anonymity and response by salespeople to a mail questionnaire", Journal of Marketing Research, Vol. 14, November, pp. 611-16.
Goldstein, L. and Friedman, H.H. (1979), "A case for double postcards in surveys", Journal of Advertising Research, Vol. 19, April, pp. 43-7.
Greer, T and Lohtia, R. (1994), "Effects of source and paper color on response rates in a mail survey", Industrial Marketing Management, Vol. 23, February, pp. 47-54.
Harvey, L. (1987), "Factors affecting response rates to mailed questionnaires: a comprehensive literature review", Journal of the Market Research Society, Vol. 29, Winter, pp. 341-53.
Hawkins, D.I. (1979), "The impact of sponsor identification and direct disclosure of respondents' rights on the quantity and quality of mail survey data", Journal of Business, Vol. 52, Winter, pp. 577-90.
Heberlein, T. and Baumgartner, R. (1978), "Factors affecting response rates to mailed questionnaires: a quantitative analysis of the published literature", American Sociological Review, Vol. 51, Spring, pp. 447-62.
Houston, M.J. and Ford, N.M. (1976), "Broadening the scope of methodological research on mail surveys", Journal of Marketing Research, Vol. 13, November, pp. 397-403.
Houston, M. and Jefferson, R. (1975), "The negative effects of personalization on response patterns in mail surveys", Journal of Marketing Research, Vol. 12, February, pp. 114-7.
Houston, M. and Nevin, J. (1977), "The effects of source and appeal on mail survey response patterns", Journal of Marketing Research, Vol. 14, August, pp. 374-8.
Janssens, D. and Pessemier, E.A. (1980), "Response rates in mail surveys: a review and summary", Working Paper 714, Krannert Graduate School of Management, Purdue University, West Lafayette, IN.
Jones, W.H. (1979), "Generalizing mail survey inducement methods: population interactions with anonymity and sponsorship", Public Opinion Quarterly, Vol. 33, Spring, pp. 102-11.
Jones, W. and Lang, J. (1980), "Sample composition bias and response bias in a mail survey: a comparison of inducement methods", Journal of Marketing Research, Vol. 17, February, pp. 69-76.
Jones, W. and Linda, G. (1978), "Multiple criteria effects in a mail survey experiment", Journal of Marketing Research, Vol. 15, May, pp. 280-4.
Kanuk, L. and Berenson, C. (1975), "Mail surveys and response rates: a literature review", Journal of Marketing Research, Vol. 12, November, pp. 440-53.
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Linsky, A. (1975), "Stimulating response to mailed questionnaires: a review", Public Opinion Quarterly, Vol. 21, Fall, pp. 384-8.
Lunney, G.H. (1970), "Using analysis of variance with a dichotomous dependent variable: an empirical study", Journal of Educational Measurement, Vol. 37, Winter, pp. 263-9.
Mason, W.S., Dressel, R.J. and Bain, R.K. (1961), "An experimental study of factors affecting response to a mail survey", Public Opinion Quarterly, Vol. 12, Summer, pp. 296-9.
Mitchell, W.G. (1973), "Systematic synthesis of response results", Journal of Advertising Research, Vol. 13, September, pp. 37-40.
Neter, J. and Wasserman, W. (1974), Applied Linear Statistical Models, Richard D. Irwin, Inc, Homewood, IL.
Nitecki, D. (1976), "Effects of sponsorship and nonmonetary incentive on response rate", Journalism Quarterly, Vol. 55, Summer, pp. 581-3.
O'Conner, P.J., Sullivan, G. and Jones, W. (1981), "An evaluation of the characteristics of response quality induced by follow-up survey methods", paper presented at the annual meetings of the Association of Consumer Research, Miami Beach, FL.
Pearlin, L. (1961), "The appeals of anonymity in questionnaire response", Public Opinion Quarterly, Vol. 25 Winter, pp. 640-47.
Peterson, R.A. (1975), "An experimental investigation of mail survey responses", Journal of Business Research, Vol. 3, July, pp. 199-210.
Peterson, R. and Kerin, R. (1981), "A note on alternative contact strategies in mail surveys", Journal of the Market Research Society, Vol. 31, July, pp. 409-18.
Pressley, M.M. and Dunn, M.G. (1985), "A factor-interactive experimental investigation of inducing response to questionnaires mailed to commercial populations", Proceedings of the 1985 American Marketing Association Summer Educators' Conference, American Marketing Association, Chicago, IL, pp. 356-61.
Resnick, A.J. and Harmon, R.R. (1985), "The impact of sponsorship, labeling and incentives on mail survey response rates: a foot-in-the-door perspective", 1985 AMA Educators' Conference Proceedings, American Marketing Association, Chicago, IL, pp. 59-64.
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Tyagi, P.K. (1989), "The effects of appeals, anonymity, and feedback on mail survey response patterns from salespeople", Journal of the Academy of Marketing Science, Vol. 17, Summer, pp. 235-41.
Watson, J. (1976), "Improving the response rate on mail research", Journal of Advertising Research, Vol. 19, June, pp. 48-9.
Wildman, R.C. (1977), "Effects of anonymity and social setting on survey responses", Public Opinion Quarterly, Vol. 41, Spring, pp. 74-9.
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(A.J. Faria is Professor and Chairman of Marketing and John R. Dickinson is Professor of Marketing in the Faculty of Business Administration, University of Windsor, Windsor, Ontario, Canada.)
Executive summary and implications for the practitioner
(Supplied by Marketing Consultants for MCB University Press)
Want more responses, guv?
Issues surrounding response rates are, as any direct marketer will tell you, a matter where science gives only an equivocal set of answers. Like market researchers we look for ways to lift response rates via incentives, additional letters (lift letters) attention to the response mechanism and the copy of the mailing. Undoubtedly there are an enormous number of factors that affect response rates. Some are within the control of the marketer while others exist in the market itself There are no right answers to the question of what constitutes a responsive mailing but plenty of wrong ones.
When we look at postal surveys and questionnaires these issues of not knowing what is right but knowing what is wrong emerge again and Faria and Dickinson focus on two potential "right" answers - anonymity and sponsorship. However, they show that stressing anonymity does not produce the response benefits expected, especially where the sponsor is a university department. In some ways their findings reinforce the problem by demonstrating that an approach, while not "wrong", cannot be proven as "right".
What emerges is that the best mailing construction is circumstantial in that it depends on the questions being asked, who is doing the asking and who is being asked. Some matters are more sensitive and require anonymity while others are less so, and protecting the identity of respondents makes little material difference. Similarly, some questions might reasonably be asked by a commercial enterprise of its customers while others are seen as intrusive.
Direct marketers argue that good mailings depend on several factors unconcerned with the minutiae of tactics. The same must apply to postal surveys since the same objective - a response - is required. These factors include:
* Relevance - how significant is the content to the recipient? Does it reflect directly on their work or is it tangential? It is implicit in Faria and Dickinson's article that the questionnaire they sent out was highly relevant to the sample's work.
* Benefits - while it is sometimes difficult to see the benefits of responding to a survey, the circumstances described in this test suggest that because of the subject matter the recipient could see distinct benefits to responding despite the time commitment involved. Researchers must ask the question as to why those receiving a postal survey should consider responding. This reason should be spelt out in the mailing.
* Ease of response - although this particular example involved a particularly long questionnaire and the details of questions asked are unclear the issue of how easy it is to respond is important. The provision of pre-printed reply envelopes (ideally pre-paid) and clear unequivocal questions do make a difference to response rates. Most of us will give up quickly if we find what we are doing arduous or overly time-consuming. Especially when the task is peripheral to our work.
* Clarity - there is nothing worse than unclear directions. Researchers pay a great deal of attention to constructing the questionnaire properly. Avoiding equivocal questions, providing enough space for responses, ensuring the questions flow and minimizing time for completion are all seen as important. However, at least in my experience, the covering letter and associated instructions are seldom given the same amount of thought and attention. Since the letter is the most significant element in any mailing it should receive the same attention as the other elements.
* Timing - while it is not always possible to predict time problems with recipients researchers should consider when they mail a survey as well as its construction. Avoiding mailings that arrive on a Friday or a Monday has long been a tenet of business-to-business direct mail since they are often the busiest days. Similarly, avoiding holiday weekends or times when children are off school makes sense since most managers have less time for things such as direct mail and surveys at these times.
Managers have been guilty of ignoring academic research into what makes postal surveys effective and the considerable body of literature on the subject demonstrates its importance to researchers. But academics and researchers considering responsiveness need to learn from those whose jobs and expertise are directed toward generating responses. Direct marketers are among the most scientific of managers. Their decisions on mailing construction and related issues are based, in the main, on factual information rather than folklore and anyone looking to get a response from someone should look at the techniques developed to achieve better response rates in direct mail.
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|Author:||Faria, A.J.; Dickinson, John R.|
|Publication:||Journal of Business & Industrial Marketing|
|Date:||Jan 1, 1996|
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