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Special topic forum on using archival and secondary data sources in supply chain management research.

Much empirical research in supply chain management has been based on primary data--data that has been collected for the research at hand. Typical methods for collecting primary data include research surveys/questionnaires, direct observations, and case interviews. In contrast to primary data, secondary data is data that has been collected and possibly analyzed or processed by individuals other than the researcher. A researcher can obtain secondary data from large surveys conducted by other researchers, data from government agencies (census data, labor statistics, new housing starts), and from existing archives. Archival data consists of historical records from individuals (letters, papers, computer files, financial records, diaries) and organizations (business records, administrative files, memos, emails, official correspondence).

Primary data has a reliability advantage in the sense that the researcher knows where it came from and how it was collected since he did it himself. Nevertheless, there are several advantages to using secondary data in empirical studies. First, secondary data is more publicly available to a large number of scholars allowing for true research as well as replication and validation studies. Second, secondary data sourced from archives is generally more objective than even primary survey data since it is free from contamination by respondent perceptions and/or memories of the phenomenon of interest. Indeed, some secondary data (such as the financial performance figures and ratios produced by COMPUSTAT) can be classified as purely objective data. A third advantage is that researchers can use secondary data from surveys, censuses, etc. to answer questions or test hypotheses that are far removed from the research intentions or informational requirements of the scholars and/or agencies whose studies or initiatives generated the data. This enhances the credibility of the new research since it removes the possibility that the purpose or intention of the research could have influenced the design of the research questions, survey instrument, and/or population(s) sampled.

Secondary data research requires less money, less time and fewer personnel. Furthermore, a variety of specialized tasks can be completed prior to new survey collection such as defining which groups need over sampling, which research questions need elaboration, reasons to revise hypotheses, and the need to refine measures. Secondary data helps facilitate these tasks. Finally, secondary data can be combined with other types of data to investigate phenomena more thoroughly or in an information setting using tools such as Bayesian inference.

In supply chain management scholarship, locating archived or secondary data is challenging. Often firms have tremendous reserves of data which can be extremely helpful to academic researchers, yet these researchers often stop at getting managers' opinions of corporate history rather than physical records of that history. Thus, the value of research librarians in both academic and corporate settings becomes evident.

In the supply chain management arena, there are a host of topics that could benefit from the application of secondary data (including archival data). Examples include:

* The validation of perceptual measures of overall firm performance [sales revenue, return on investment (ROI)] using secondary data (e.g., COMPUSTAT). (Overall firm performance is often a key dependent variable in supply chain management studies.)

* The use of archival data to examine the effects of strategic supply chain initiatives on competitive performance

* The use of archival data concerning first-tier suppliers' machine change-over times to examine the effects of change-over times on key dimensions of delivery performance (on-time, flexible, etc.).

* The use of archival data (e-mail and other records) pertaining to communication between engineers of buying and supplying firms relative to new product launches to examine the effects of frequency and topics of interactions on launch performance.

* The addition of secondary data from a colleague's data set on supplier development practices in North America to a researcher's own Asian and European data sets containing the identical constructs for a comparative analysis of practices by regions.

* The use of secondary data focused on post-mortems of failed new product development initiatives to identify and examine common themes.

* The use of archival data related to number of SKUs and the size of the supply base to examine their effects on quality and cost performance.

In this special topic forum, we welcome the submission of manuscripts that innovatively employ secondary data, including archival data, to examine cutting edge research topics in supply chain management. We seek papers that demonstrate the advantages of using secondary data either alone or in combination with primary data to investigate questions with clear managerial and practical implications. Authors should endeavor to show how their work contributes to or extends supply chain management theory and/or practice, as well as the techniques of good secondary data discovery use and value.

THE DEADLINE FOR SUBMISSIONS IS SEPTEMBER 15, 2009

Manuscripts must conform to JSCM style guidelines and submission requirements. Early submissions are welcome and the review process will be initiated when papers are received.

An electronic copy of the manuscript that conforms to JSCM's format (see www.blackwellpublishing.com/jscm) should be submitted via e-mail to: Lynn Marstiller at Imarstiller@ism.ws. Please note in the comments to the editors that the submission is for the Special Topics Forum on Using Archival and Secondary Data Sources.

Questions can be addressed to either of the guest editors:

Roger Calantone (rogercal@bus.msu.edu) or

Shawnee Vickery (vickery@bus.msu.edu).

Guest Editors:

Roger Calantone and Shawnee K. Vickery

Michigan State University
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Author:Calantone, Roger; Vickery, Shawnee K.
Publication:Journal of Supply Chain Management
Geographic Code:1USA
Date:Jul 1, 2009
Words:887
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