Introduction to Using Archival and Secondary Data Sources in Supply Chain Management Research
This issue of the Journal is devoted to the Special Topic Forum on Using Archival and Secondary Data Sources in Supply Chain Management Research.
Edited by Roger J. Calantone, Ph.D., the Eli Broad Chaired University Professor of Business at Michigan State University, East Lansing, Michigan,
and Edited by Shawnee D. Vickery, Ph.D., Professor of Operations and Supply Chain Management in the Eli Broad College of Business at Michigan State University, East Lansing, Michigan.
So You Already Have a Survey Database? A Seven-Step Methodology for Theory Building from Survey Databases: An Illustration from Incremental Innovation Generation in Buyer-Seller Relationships
Across business disciplines, the importance of database research for theory testing continues to increase. The availability of data also has increased, though methods to analyze and interpret these data lag. This research proposes a method for extracting strong measures from survey databases by a progression from qualitative to quantitative techniques. To test the proposed method, this study uses the Industrial Marketing and Purchasing (IMP) survey database, which includes data from firms in several European countries. The proposed method consists of two phases and seven steps, as illustrated in the context of the firm's incremental innovation generation for buyer-seller relationships. This systematic progression moves from a broad but valid empirical case study to the development of a narrow and reliable measure of incremental innovation generation in the IMP database. The proposed method can use supply chain survey databases for theory development without requiring primary data collection, assuming certain conditions. Subroto Roy, Ph.D., is Associate Professor of Marketing at the University of New Haven, West Haven, Connecticut.
The Contribution of Third-Party Indices in Assessing Global Operational Risks
In the face of global uncertainties and a growing reliance on third-party indices to obtain a snapshot of a country's operational risks, we explore the related questions: How accurately do third-party indices capture a country's operational risk; and how does the operational risk of the country, in turn, affect the volume of its import and export supply chains? We examine these questions by empirically investigating 81 member countries of the World Trade Organization (WTO) using archival data collected from UN agencies, independent think tanks, the WTO and the Economist Intelligence Unit. We use seven third-party indices to gauge a country's internal environment, and map those indices to corresponding country-specific operational risks to further understand the consequent effects of those operational risks on trading volume. Results provide strong evidence for the use of certain third-party indices in assessing operational risk. In addition, operational risks are found negatively to affect the volume of import and export supply chains, albeit in varying degrees. Kuntal Bhattacharyya, MBA, is a Ph.D. candidate in the Department of Management and Information Systems in the College of Business, Kent State University, Kent, Ohio, Pratim Datta, Ph.D., is Assistant Professor of Information Systems in the Department of Management and Information Systems in the College of Business, Kent State University, Kent, Ohio
and O. Felix Offodile, Ph.D., is Professor of Management and Information Systems in the Department of Management and Information Systems in the College of Business, Kent State University, Kent, Ohio.
A Procedure for Secondary Data Analysis: Innovation by Logistics Service Providers
This paper presents a procedure for confirmatory and exploratory research with a limited amount of secondary data. The methodology is exemplified by research on the innovation activities and performance of logistics service providers (LSPs), thereby extending the work of Wagner. A research hypothesis is derived, stating that the context of LSPs to innovation is significantly different from that of other service providers. Secondary data from the 2006-2008 Mannheim Innovation Panel, an annual survey on the innovation behavior of German firms, is assessed and found suitable to test that hypothesis. The χ2 test of independence is used to test the hypothesis. Multiple activity and performance indicators can be used as operationalizations that are later tested in parallel, with the help of the Bonferroni correction. Then, the distribution of categorical variables is recalculated, and multiple scenarios for missing values are taken into account. Empirical and critical χ2 values are computed, and the test result is aggregated. The findings indicate that the LSP context of innovation is indeed significantly different from that of other service providers. Those differences are then analyzed and interpreted. The results show that innovators among LSPs appear to have similar innovation benefits to non-LSPs, while for LSPs, innovation appears to be more costly. This could explain the lower share of innovation-active LSPs. The paper concludes by discussing the limitations of the methodology, and of the content-related findings. Christian Busse, Dipl.-Ing., is a Ph.D. candidate in Business Administration at the WHU — Otto Beisheim School of Management in Vallendar, Germany.
Impact of Disasters on Firms in Different Sectors: Implications for Supply Chains
Disasters keep damaging infrastructure, disrupting supply chains and affecting firm profitability. There is an urgent need for better understanding of disaster impact on supply chains, but very few publications address this issue. This exploratory study takes an indirect approach and investigates disaster impact on firms in various industry sectors. This approach allows us to take full advantage of large secondary databases of firm and disaster data in order to analyze the impact of over 3,500 disasters on more than 100,000 firm-year observations over 15 years. Our results indicate that disasters impact all sectors within a supply chain. We found that damage by windstorms and floods seem to be dramatically different from that of an earthquake, providing evidence against the "all-hazards" approach. We also show that the impact of floods on total asset turnover of a firm is dependent on the firm's position in the supply chain. We found that, while upstream partners enjoy a positive impact, downstream partners have to plan for the opposite. Supply chain managers can use our results better to understand disaster impact on their business. Our study suggests a supply chain-wide mitigation strategy rather than a company-specific one. Nezih Altay, Ph.D., is Associate Professor of Management in the College of Commerce at DePaul University, Chicago, Illinois
and Andres Ramirez, Ph.D., is Assistant Professor of Finance at Bryant University, Smithfield, Rhode Island.
Exploring the Relationship between Efficient Supply Chain Management and Firm Innovation: An Archival Search and Analysis
This paper illustrates the use of secondary data for operations and supply chain management research by investigating the association between efficient supply chain management and innovation of firms. An empirical inquiry is conducted using archival financial statement information and patent citation data for firms in the manufacturing sector, over a 10-year period from 1987 to 1996. Longitudinal analysis, focusing on the influence of efficient supply chain management on a firm's innovation over time, is conducted. Results and limitations are discussed, along with a summary of steps which may be followed when using secondary data for operations and supply chain management research. Sachin B. Modi, Ph.D., is Assistant Professor of Supply Chain Management in the Department of Information, Operations and Technology Management at the University of Toledo, Toledo, Ohio
and Vincent A. Mabert, Ph.D., is Professor Emeritus of Operations Management in the Operations and Decision Technologies Department in the Kelley School of Business at Indiana University, Bloomington, Indiana.