Case Study: Improved Statistical Exploration and Analytics of Categorical Survey Data Related to Food Safety

• Activity Number: 442
• Type: Contributed
• Date/Time: Tuesday, August 11, 2015 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistical Consulting
• Author(s): Andy Mauromoustakos* and Phil Crandall and Corliss Obryan and Kevin Thompson
• Companies: University of Arkansas and University of Arkansas and University of Arkansas and University of Arkansas
• Keywords: GSFI ; Factor Analysis ; MCA ; JMP

Abstract

For more than a decade, the Global Food Safety Initiative (GFSI) has worked to harmonize international food safety requirements for firms exporting to numerous international markets. The savings from having a single certification has been possible because all 3rd party auditors' requirements have been shown to meet the GFSI benchmark standards. This gives retail food purchasers anywhere in the world the assurance that all of their food suppliers who are GFSI certified have meet the same rigorous, high standards. An International survey of more than 800 food suppliers across North and South America, Eastern and Western Europe and the Pacific region was conducted to document the benefits of GFSI compliance. Responses to more than 200, mostly categorical variables, were obtained. This paper focuses on the statistical analysis rather than the results of the survey. The new JMP Pro Version 12 with improved categorical analysis and enhanced graphics would be used to conduct several univariate and multivariate analysis techniques. It is hoped that this improved functionality will enhance the communication of the complex results from this large survey