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Purpose This study aims to explore the relation among US audit partners’ characteristics, their career advancement and audit quality. Design/methodology/approach This study uses data from Public Company Accounting Oversight Board Form AP, Auditor Reporting of Certain Audit Participants, and publicly available online data sources. The hand-collected data on audit partners’ personal characteristics include gender, work experience and educational background. The measures for audit quality include restatements and audit fees. Findings The authors find that audit partner characteristics matter for the time it takes an individual to reach partnership after completing a bachelor’s degree. There are significant differences in work experience and educational background between partners in the largest (Big N) audit firms and smaller (non-Big N) audit firms. Audit partner traits are related to audit quality, and the effects differ between Big N and non-Big N partners. Originality/value The literature has examined audit partners’ career paths using international data. However, little empirical academic research has examined the career advancement of US audit partners. This study provides initial insights on the career advancement of US partners on a large scale and complements the recent research that examines audit partner characteristics and audit quality in the US market.

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We present an analytical framework of multimarket competition and supporting empirical analysis to explain why and when competing firms in an existing market may prefer an alliance entry over independent entry into a new market. Our findings suggest that an alliance entry is more profitable than an independent entry (i) when the new market is larger relative to the existing market, and (ii) when the competition in the existing market is stronger relative to the new market. We compare these key predictions with archival data from the regional shopping center industry in the United States and find that instances of alliance formation in this industry are consistent with our model-based predictions. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mksc.2016.0988 .