The drop and collect survey among industrial populations: theory and empirical evidence
Introduction
Collecting, analysing and interpreting data in a methodologically sound way is at the heart of science Hunt, 1991, Popper, 1994. While a myriad ways of collecting these data are available to the researcher, one of the dominant means in researching organisations is the paper-and-pencil questionnaire (Stablein, 1996), itself dominated by the mailed questionnaire (Cavusgil & Elvey-Kirk, 1998). However, despite its many advantages, the mail questionnaire technique is plagued by a major problem: nonresponse. Or, more specifically, low response rates Baruch, 1999, Chrisnall, 1997, Delener, 1995, Kinnear & Taylor, 1991. This low response problem appears to be greater Mehta & Sivadas, 1995, Mendelson & Pillai, 1999, Tse, 1998 with the increasingly adopted but less representative online survey approaches Dommeyer & Moraiarty, 1999/2000, Taylor, 1999–2000. There is little doubt that this untoward trend, with its implications for nonresponse bias (Schlegelmilch & Diamantopoulos, 1991), questions the validity and generalisability of research findings.
The nature of this problem is further complicated by the fact that response behaviour among organisations is contingent upon difficult-to-control organisational characteristics (Tomaskovic-Devey, Leiter, & Thompson, 1994). Although several studies into the determinants of nonresponse- and response-inducing techniques Baldauf et al., 1999, Cavusgil & Elvey-Kirk, 1998, Diamantopoulos et al., 1991, Greer et al., 2000, Jobber, 1986, Jobber & O'Reilly, 1998, Harvey, 1987, Karimbady & Brunn, 1991 have suggested the importance of measures like prenotification, follow-ups and the use of response incentives, the application of these measures does not appear to have resulted in any significant overall improvement in response rates reported in academic publications, especially among organisational populations Baruch, 1999, Taylor, 1999–2000, and even more so in international research contexts (Harzing, 1997).
Two related explanations may account for the decline in (or low) response rates among organisational populations. One is that the mail questionnaire technique has become a victim of its own success, that is, its many advantages (low cost, ability to reach a widely dispersed sample, lack of interviewer bias and relatively easy implementation (e.g., Diamantopoulos et al., 1991, Hart, 1987, Schlegelmilch & Diamantopoulos, 1991) have resulted in such widespread usage that the average organisational respondent is left feeling swamped Baldauf et al., 1999, Diamantopoulos et al., 1991. The observed research fatigue in oversampled organisational populations Brock, 2000, Cooper, 2000 appears to support this. It may also be the case that the ‘impersonal’ mail questionnaire approach—including its online variant—is perceived, to an extent, as a ‘put-off’ among organisational populations, which generally favour more personal methods (Roth & BeVier, 1998). There may, indeed, be a link between the perceived impersonality of the mail questionnaire method and the increasing level of respondent fatigue and antipathy to survey instruments.
One data collection technique which appears to share most of the best characteristics of the mail questionnaire method without the associated impersonality is the drop-and-collect-survey (DCS) method (Brown, 1984). As the name implies, the DCS method involves the researcher(s) and/or properly trained field assistants in personally delivering—and later collecting—the survey instrument (the questionnaire) either directly to the target respondent or indirectly via a gatekeeper (e.g., a secretary).
It is arguable that this interpersonal feature of the DCS plays a large part in the very high response rates reported in studies that employed this method Baker, 1991, Brown, 1987, Fox et al., 1998, Lovelock et al., 1976, Stover & Stone, 1974, e.g., 50–70% (Kinnear & Taylor, 1991), 77% (Brown, 1987), up to 80% (Lin & Germain, 1998) and 90% (Brown, 1984). In addition to supporting Jobber and O' Reilly's (Jobber & O'Reilly, 1998) (p. 104) views that “[a] key issue in survey research is the choice of delivery system,” the foregoing evidence raises the more fundamental question of why the DCS delivery system is virtually unexplored in organisational research (as opposed to consumer research), and why it is usually mentioned only implicitly (e.g., Yavas, 1987). It is, indeed, a matter of concern that nearly a decade and half after Brown's (1987) observation that the DCS has attracted little serious discussion, the situation has not really improved, even in the face of the worryingly low response rates associated with mail (and online) questionnaires. The extent to which the identified neglect is caused by the general lack of specific guidelines on the ‘whens,’ ‘hows’ and ‘whys’ of DCS usage (including potential demerits) is unclear. What is obvious, however, is the urgent need to facilitate greater and more effective use of the DCS technique through the provision of appropriate operational guidelines.
This paper seeks to assist in this process. Based on insights from relevant literature schemes, a theory explaining the effectiveness of the DCS is developed, with some five research propositions pertaining to its usage among organisations advanced. These are subsequently tested using empirical data from two separate DCS-based investigations undertaken among industrial populations in two different countries, Nigeria and Germany. The paper further presents a DCS decision and implementation framework, drawing from the present researchers' findings, as well as relevant insights from the previous DCS literature: pre-, since and including Brown (1987). It is envisaged that this best practice guide should assist future researchers in considering and implementing the DCS technique.
The rest of this paper is structured as follows. First, we present the theoretical underpinning of DCS, replete with a number of research propositions. Second, we present the methodology employed in the two DCS-based investigations. This is followed by the analysis of the empirical findings and tests of the research propositions. The penultimate section discusses the findings and presents the DCS decision and implementation framework. The paper concludes with some remarks, including relevant comments on the study's limitations and future research directions.
Section snippets
A theory of the DCS: social presence in a social exchange context
As stated in the introduction, the DCS can achieve very high response rates. This raises the question of why that is the case and highlights the need for greater understanding of the underlying theory for the DCS. The following paragraphs, therefore, aim to provide the theoretical bases for the DCS, particularly among organisations.
Survey response behaviour is essentially human cooperative behaviour (Cavusgil & Elvey-Kirk, 1998). The sender of the questionnaire (the researcher) seeks the
Methodology
As mentioned earlier in the introduction, the empirical base for this paper derives from two separate investigations conducted among industrial organisations in Germany and Nigeria. The drawing of our samples from these two countries was entirely fortuitous, merely reflecting the nationalities of the present researchers.
The Nigerian study was undertaken in late 1996 among labour intensive, low-technology firms located in one of three major Nigerian industrial cities, namely Lagos (Southwest),
Analysis and results
Proposition 1 suggests that the DCS among organisations will result in significantly higher response rates than mailed questionnaires. In order to assess whether this was achieved, a reference point was needed. A recent review by Baruch (1999) provides such a reference. He reported an average response rate for questionnaires targeting top managers or representatives of organisations of 35.5% with a standard deviation of 13.3%. Based on this reference point, we defined a significantly higher
Discussion
This paper has examined the potentials of the DCS to improve upon the worryingly low response rates associated with the arms-length mail questionnaire method, among organisational respondents. Drawing from relevant literature streams, it explains the theoretical underpinning of the DCS and advances some five propositions relating to its use among organisations. These propositions were subsequently analysed, using empirical evidence from two separate DCS-based studies undertaken among Nigerian
Conclusions, limitations and directions for future research
This study suggests that a number of significant benefits can be gained from employing the DCS in organisational surveys. These benefits, including higher response rates, greater generalisability and cost effectiveness, would appear to hold irrespective of whether the delivery system is used in advanced economies (e.g., Germany) or developing economies (e.g., Nigeria). These findings are important, as they suggest a viable alternative to the clearly over-used, and increasingly less effective,
Acknowledgements
All the authors contributed equally to the paper. Correspondence should be directed to Dr. Kevin Ibeh. The helpful comments of Professors Stephen Young and Susan Hart on an earlier version of this paper are gratefully acknowledged.
Dr. Kevin Ibeh is Lecturer and Co-Deputy Director at the Strathclyde International Business Unit, University of Strathclyde.
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Dr. Kevin Ibeh is Lecturer and Co-Deputy Director at the Strathclyde International Business Unit, University of Strathclyde.
Dr. Jürgen Kai-Uwe Brock is a Senior Manager for New Markets and Relations in the Security and Chip Card ICs Division of Infineon Technologies and a Research Associate of the Strathclyde International Business Unit at the Department of Marketing, University of Strathclyde.
Dr. Josephine (Yu) Zhou is a lecturer in the Hospitality Management Department at the International University of Applied Science in Bad Honnef, Germany. Her research and teaching focuses on research methodology, strategic management, human resources management and international business.