Econometrics and archival data: Reflections for purchasing and supply management (PSM) research |
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| Affiliation: | 1. Department of Supply Chain Management, Eli Broad College of Business, Michigan State University, Travis Kulpa, USA;2. Department of Supply Chain Management, Sam M. Walton College of Business, University of Arkansas, USA;1. Aarhus University, School of Business and Social Sciences, Fuglesangs Allé 4, DK-8210 Aarhus V, Denmark;2. Aalborg University Business School, Fibigerstræde 11, DK-9220 Aalborg Ø, Denmark;3. Norwegian University for Science and Technology (NTNU), Norway;1. Department of Management, University of Bologna, Via Capo di Lucca, 34, 40126, Bologna, Italy;2. Department of Information Systems, Supply Chain Management and Decision Support, NEOMA Business School, Reims, France;3. Department of Marketing and Logistics, Coggin College of Business, University of North Florida, 1 UNF Drive, Jacksonville, FL, 32224, USA;4. Department of Economics and Management, University of Ferrara, Via Voltapaletto 11, 44121, Ferrara, Italy;1. Division of Business, DeSales University, 2755 Station Avenue, Center Valley, PA, 18034, USA;2. School of Business, Robert Morris University, 6001 University Blvd, Moon Twp, PA, 15108, USA;3. Boler College of Business, John Carroll University, 1 John Carroll Blvd, University Heights, OH, 44118, USA;4. School of Business, Georgia Gwinnett College, 1000 University Center Ln, Lawrenceville, GA, 30043, USA;5. G. Brint Ryan College of Business, University of North Texas, 1307 W Highland St, Denton, TX, 76201, USA;1. University of Central Oklahoma, 100 N University Dr, Edmond, OK, 73034, USA;2. University of Applied Sciences Upper Austria, Roseggerstraße 15, 4600, Wels, Austria;3. Michigan State University, N327 Business College Complex, East Lansing, MI, 48824, USA;1. Department of Marketing and Management, College of Business Administration, The University of Texas at El Paso, 500 W University, El Paso, TX, 79902, USA;2. Department of Supply Chain Management, W. P. Carey School of Business, Arizona State University, 300 E Lemon St, Tempe, AZ, 85287, USA;1. Audencia Business School, France;2. Univ. Grenoble Alpes, CNRS, G-SCOP, 38 000, Grenoble, France;3. University of Maastricht, the Netherlands;4. University of Twente, Enschede, the Netherlands |
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| Abstract: | Purchasing and supply management (PSM) has faced unprecedented disruption over the past two years due to COVID-19 pandemic, input shortages, extended supplier lead times, record international transportation costs, and commodity price increases. Studying such phenomena is often best completed using archival data, such as data from government agencies or international organizations. This manuscript emphasizes how leveraging archival data often necessitates an iterative research process whereby researchers must first familiarize themselves with the data to ensure their scientific hypotheses can be appropriately tested. We further provide recommendations regarding how researchers should formulate generalized linear models (GLMs) to test theoretical predictions. Our approach emphasizes mapping scientific hypotheses to statistical hypotheses, as opposed to centering on issues of omitted variable bias (OVB). An illustrative example is provided where Census Bureau trade data are compiled to test whether the insurance and freight costs for waterborne containerized imports from Asian nations that enter through West Coast ports have risen more than the same products imported through East Coast ports. The research suggests the need to reorient how GLMs are formulated to better ensure researchers structure them to appropriately test their theory, in contrast to the current zeitgeist that overly emphasizes OVB. |
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| Keywords: | Archival data Econometrics Sourcing Endogeneity Omitted variable bias Global supply chain |
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