Does the Starting Point Matter? The Literature‐Driven and the Phenomenon‐Driven Approaches of Using Corporate Archival Data in Academic Research

AuthorMark J. Cotteleer,Xiang Wan
DOIhttp://doi.org/10.1111/jbl.12114
Date01 March 2016
Published date01 March 2016
Does the Starting Point Matter? The Literature-Driven and the
Phenomenon-Driven Approaches of Using Corporate Archival Data
in Academic Research
Mark J. Cotteleer
1
and Xiang Wan
2
1
Marquette University College of Business Administration
2
The Ohio State University
Despite recent and perhaps myopic criticisms of archival data with regard to supporting causal theoretical claims, it would be folly to disre-
gard the exploratory and grounded theory development potential that these substantial, rich, and timely archives hold. The question then
becomes one of how academics might tap into such archives. This paper considers this issue from a pragmatic perspective, drawing on the
experiences of various academics with extensive experience in constructing data-access relationships with industry. With the support of scholars
who published their work using corporate archival data in leading academic journals, we suggest a phenomenon-driven approach paralleled with
the traditional literature-driven approach in academic studies. This paper highlights best practices, pitfalls, and future opportunities, with the aim
of serving as a guide for intrepid scholars interested in capitalizing on contemporary big data initiatives supported at many rms.
Keywords: empirical research; archival data; academic-industry partnership
INTRODUCTION
The explosive growth of data held by corporations and individu-
als is well documented. One estimate projects total worldwide
data storage to be 3.77 zetabytes by 2016 (Mearian 2014). As
data-intensive technologies continue to evolve, it is likely that
the rate of creation will only accelerate in the coming years. In
concert, rms have begun to view the analysis of all that data
as a key competitive weapon, investing in new approaches to
collect and analyze data, both Bigand small.
But what about the academic community, and in particular,
business scholars? Albeit for potentially different reasons, the
scholarly community also has strong interests in learning about
companies and their customers (and their suppliers, and partners,
and many other stakeholders). It follows that these vast reservoirs
of data collected by companies represent an arguably underuti-
lized source of data to be tapped. So how might an interested
researcher approach the challenge of gaining access to and use of
such data? In this paper, we provide an exploration of researcher
experiences in using corporate data for the research projects.
After reviewing the literature and interviewing a group of
scholars from a variety of universities, we summarize two
approaches of using corporate data in academic research: the lit-
erature-driven approach and the phenomenon-driven approach.
These two approaches are not mutually exclusive from each
other. Since typical research using corporate data incorporates
both existing theories and empirical data (Ketokivi and Choi
2014), both research approaches require literature gaps and cor-
porate data. The main difference between these two approaches
is their starting points. The literature-driven approach starts with
the theoretical contribution, while the phenomenon-driven
approach starts with the empirical contribution. Does the starting
point matter, if a research work has both theoretical and empiri-
cal contributions? The answer may vary from one individual to
another. While theoretical grounding is a good place to start a
research project, some research topics cannot be easily explored
by strictly building on theory in a vacuum. When an empirical
setting is right in front of you, why cant you start with empirical
issues? The purpose of this paper is to suggest an alternative
path (phenomenon driven) to academic research in addition to
the traditional literature-driven approach.
We accomplish this not simply by drawing on our own experi-
ence, but also on that of other scholars, at different career stages,
each of whom has demonstrated success in their pursuits. We
thank the following researchers for their participation in our
interviews and their generous expression of their experience:
Elliot Bendoly, Nathan Craig, John Ettlie, Bradley Staats,
Zeynep Ton, Anita Tucker, Brent Williams, Yuliang (Oliver)
Yao, and Qiuping Yu.
The remainder of this paper is organized as follows. The rst
section compares the literature-driven and the phenomenon-
driven approaches. The second section reviews some empirical
research papers, using corporate archival data, at top supply
chain management journals, while the third section describes the
interview methodology. Main ndings are summarized in the
fourth section. Suggestions of future research are provided in the
nal section.
TO BE LITERATURE DRIVEN OR PHENOMENON
DRIVEN?
The literature-driven approach starts with surveying the existing
literature, identifying important gaps, and then designing a study
to address those gaps, incrementally advancing the overall body
of knowledge (as shown in Figure 1). The phenomenon-driven
approach values opportunities presented by the company relation-
Corresponding author:
Mark J. Cotteleer, Research Associate Professor, Center for Supply
Chain Management, Marquette University College of Business
Administration, 1250 W. Wisconsin Ave., Milwaukee, WI 53233,
USA; E-mail: Mark.cotteleer@marquette.edu
Journal of Business Logistics, 2016, 37(1): 2633 doi: 10.1111/jbl.12114
© Council of Supply Chain Management Professionals

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