A Note on the Use of Survey Research Firms to Enable Empirical Data Collection

AuthorTobias Schoenherr,Wendy L. Tate,Lisa M. Ellram
Date01 September 2015
Published date01 September 2015
DOIhttp://doi.org/10.1111/jbl.12092
A Note on the Use of Survey Research Firms to Enable Empirical
Data Collection
Tobias Schoenherr
1
, Lisa M. Ellram
2
, and Wendy L. Tate
3
1
Michigan State University
2
Miami University
3
University of Tennessee
This forward thinking article examines the risks and rewards of using survey research rms to enable empirical data collection, and issues a
cautionary note about its application. An exposition and discussion of this form of data collection in supply chain management is relevant
today, due to the survey-fatigueamong the population of business professionals from whom we seek a response. While this approach has
some history in other disciplines, it is still relatively new among supply chain management researchers. To help supply chain management
scholars assess the appropriateness of this type of data collection method, this forward thinking article provides invaluable guidance as derived
from the authorsrecent experiences with the approach. As such, we share our observations and lessons learned. The conclusion is that the use
of survey research rms for empirical data collection can be a viable, alternative approach to self-administered surveys. However, care should
be taken in its application.
Keywords: survey research rms; empirical data collection; research methodology; forward thinking article
INTRODUCTION
The proliferation of empirical surveys to test business-related the-
ory and practice has created survey-fatigueamong the popula-
tion of business professionals from whom we seek a response,
making it increasingly difcult to achieve statistically meaningful
response rates (Boyer and Swink 2008). To meet this challenge
and achieve ever more stringent publication goals, supply chain
management scholars have begun to source data collection to
professional survey research rms in an effort to improve real-
ized sample sizes and access well-screened and targeted respon-
dents (a multitude of selection criteria can be specied).
The marketplace is replete with companies that offer such ser-
vices (Table 1). The rms frequently describe themselves as
offering specialized panelsof targeted respondents and, once
contracted, will administer the survey instrument to one of their
panelsfor a fee. Most often, potential respondents are incentiv-
ized by monetary rewards or points (that can be redeemed for
goods and services) for completing the surveys. While this form
of data collection has some history in other disciplines, espe-
cially marketing
1
(e.g., Bearden and Haws 2012), it is still rela-
tively new among supply chain management researchers (Autry
et al. 2010; Grawe et al. 2011; Tang and Rai 2012; Tokman
et al. 2012; Ellram et al. 2013). The objective of this forward
thinking article is therefore to examine the risks and rewards of
this means of data gathering, and to begin a dialogue about mak-
ing this increasingly popular approach in supply chain manage-
ment more rigorous and acceptable.
The perspective of the authors in this forward thinking article
is based in part on personal experience with a large and well-
respected survey research rm used in a recent study to collect
empirical survey data. This particular data collection approach
was chosen in order (1) to achieve higher quality responses by a
targeted distribution to select potential respondents based on
characteristics specied by the researchers, and (2) to ensure a
large-enough sample size to enable rigorous statistical analysis
and ensuing publication potential in top-tier journals. These prop-
ositions were appealing. However, during the contracting, data
collection, and analysis stages of this research, some issues were
discovered that made us question the approach. For example,
how much did we know about the survey respondentsqualica-
tions, characteristics, and selection, although the desired charac-
teristics were clearly presented to the survey company?
This forward thinking article exposes the challenges of using
paid survey research rms, while at the same time reporting on
lessons learned, in order improve the future rigor of this form of
data collection. When employing survey research rms to collect
empirical data, we encourage researchers to proceed with cau-
tion, and consider the practices described in this article to ensure
reliability and validity of responses. The apparent ease with
which data can be collected should not make the researcher
1
The use of paid research respondents via for example Ama-
zon.coms mechanical Turk (MTurk) and other such services has
grown rapidly in behavioral accounting and consumer behavior
research within the eld of marketing. As such, whereas high-qual-
ity accounting journals noted only two studies using paid online
research respondents in 2000, there were already 24 published
studies relying on this approach in 2012 (Brandon et al. 2014).
While some of the services, such as Amazon.coms MTurk, are
geared toward human intelligence tasks such as completing behav-
ioral experiments (Buhrmester et al. 2011; Crump et al. 2013;
Paolacci and Chandler 2014), others, such as SurveyMonkey, can
support either behavioral experiments or targeted surveys seeking
expert respondents (Brandon et al. 2014).
Corresponding author:
Tobias Schoenherr, Associate Professor of Supply Chain Manage-
ment, Broad College of Business, Michigan State University, North
Business College Complex, 632 Bogue St., Room N370, East
Lansing, MI 48824, USA; E-mail: schoenherr@broad.msu.edu
Journal of Business Logistics, 2015, 36(3): 288300 doi: 10.1111/jbl.12092
© Council of Supply Chain Management Professionals

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