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Food safety and quality regulations that are agreed on by the buyer and seller are the cornerstone of food safety and quality.  Earlier, we reported the top-level survey results of 2,300 food manufacturers as to their costs and benefits of becoming compliant with the benchmarked Global Food Safety Initiative (GFSI) schemes. In this paper, we provide a more in-depth statistical analysis with rationale for using these analyses. The Bradley Terry probability model showed that “existing customer requirements” were 4.6 times more important than “potential new customer requirements.” A Multiple Correspondence Analysis associated the reasons for certification using the following customer demographics: the GFSI scheme (British Retail Consortium [BRC] or Safe Quality Foods [SQF]), the region of the world (Europe/EU or North America/NA) and the food safety risk (high, medium or low). EU companies certified by BRC were primarily driven by wanting to improve their business reputation while those certified by the SQF scheme, mostly in NA, were primarily driven by requirements of an existing customer.  A Generalized Linear Model with the multinomial ANOVA and a cumulative logistic link functioned to estimate the amount of agreement on four important questions about Key Performance Indicators, KPI’s sales/revenues, numbers of customers, employees, and suppliers. A Quantile Regression was used to analyze the length of time companies spent becoming GFSI Certified, with 80% of the companies achieving this goal in less than 1 year. Finally, a Logistic Regression and tree-based models used 24 perceived benefits to predict if certification would be beneficial for a new company considering this option.

Food safety, quality, statistical analytics, large data analysis, analytic survey data, generalized regression models, Bradley-Terry probability model, multi-dimensional preference analysis, multiple correspondence analysis and predictive modeling.

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MAUROMOUSTAKOS, A., CRANDALL, P. G., THOMPSON, K. C., & O’BRYAN, C. A. (2020). FURTHER PREDICTIVE STATISTICAL ANALYSIS OF A GFSI SURVEY OF INTERNATIONAL FOOD PROCESSORS. Journal of Basic and Applied Research International, 26(2), 39-52. Retrieved from https://archives.biciconference.co.in/index.php/JOBARI/article/view/5093
Original Research Article


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