Using Importance-Performance Matrix Analysis to Evaluate the Financial Performance of American Banks During the Financial Crisis

This research applies a technique that identifies areas of improvement that can be addressed by managerial decisions or policy activities. It extends the application of partial least squares structural equation modeling (PLS-SEM) using an importance-performance map analysis (IPMA). The IPMA determines priority factors that should receive management's attention. The PLS path model was tested by comparing 140 failed U.S. banks with the same number of nonfailed banks from 2006 to 2008. This model assembles 15 indicators with four predecessor constructs (i.e., profitability of 2006, profitability of 2007, risk of 2006, and risk of 2007) and one final target construct (i.e., profitability of 2008). Profitability and risk of 2007 mediate the path of profitability and risk of 2006 and profitability of 2008. The IPMA indicated that failed banks were predisposed to decreasing financial performance in 2008 because of their poor performance in 2006 and 2007. Conversely, nonfailed banks were more likely to experience increasing financial performance in 2008 because of their positive performance in 2006 and 2007. This study indicates that managers who use IPMA to prioritize their financial decisions will obtain useful conceptual insights and are unlikely to be misled. Although IPMA can be conducted on the indicator level as well, this article limits its analysis by focusing on the construct level only. The use of IPMA is ubiquitous in end-user surveys, but its application to banking is still in its embryonic state. For originality, this work prioritizes the application of IPMA using secondary data collected from financial statements to assess the performance of American banks during the crisis.