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The Small Business Administration (SBA) supports franchising by backing up loans issued by regular lending organizations. However, the SBA does not directly consider firm strategies as part of its lending process. To appreciate how franchisor characteristics influence franchisee failure, we developed a heuristic model using the methodology and power of predictive analytics. We use multi-year data from the World Franchising Council’s surveys on franchisors’ characteristics and from the SBA on franchisee loan defaults. The data cover 271 diverse US franchise chains that are present in both databases. Our model predicts potential defaults of SBA-backed loans issued to American franchisees and we identify 13 variables that help explain franchisee failure. Our paper contributes to the franchising literature by considering parent firms’ characteristics to predict franchisee failure. In addition, we offer guidance for stakeholder groups—lenders, franchisors and franchisees— to minimize the risk of lending and business failure.

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Competitiveness Review