lower leverage and higher cash levels can reduce the risk of insolvency. However,
Upneja and Dalbor (2001a) showed that restaurant firms with more short- than
long-term debt are more likely to go bankrupt, most likely due to a greater problem
with information asymmetry. Using a multiple-discriminant analysis model, Gu (2002)
showed that restaurant firms with lower earnings before interest and taxes and higher
total liabilities (i.e. debt-burdened) are candidates for bankruptcy. This argument was
supported by Kim and Gu (2006a, 2006b) and Youn and Gu (2009). Kim and Gu (2006b)
argued that what matters in restaurant bankruptcy is long-term debt; the more a firm
relies on debt financing, the higher its interest expenses, the lower the interest coverage
ratio, and the higher the probability of failure. Comparing Gu’s (2002)
multiple-discriminant analysis model of restaurant bankruptcy, Kim and Gu (2006b)
claimed that the logistic model is preferred because of its theoretical soundness,
although both models give similar results. Comparing a logistic regression model
predicting the failures of Korean lodging firms, Youn and Gu (2009) showed that the
artificial neural network model outperforms the logistic model in terms of reduced
Type II errors. They stated that interest coverage is the most important signal of
business failure in the Korean hotel industry.
Kim and Gu (2006a) argued that nonfinancial factors such as geographic
diversification and market segmentation may also help predict bankruptcy because
they are likely to influence the firm’s financial variables and, ultimately, performance.
Diener (2009) explained the regulatory changes in the bankruptcy code since the last
wave of hotel bankruptcies and suggested that the precipitous and concurrent drop in
real estate values and revenues has again raised the specter of insolvency for owners
and lenders. He argued that many other issues, such as utilities, critical vendors, and
taxes could influence this, as could owner-debt relations or favorable economic factors.
While some financial variables clearly signal firm failures and have been well
examined in previous studies, there is need for further investigation of non-financial
issues related to hospitality firm bankruptcy, such as those that have been conducted
in mainstream business (Wu, 2004).
5.2 Firm performance determinants
Firm performance has been a popular research variable. Depending on the context, it
can be measured from the accounting (such as ROA) and finance (stock returns)
perspectives, or a combination of both (such as Tobin’s q). Hospitality researchers have
been interested in what financial attributes lead to better performance. For example,
institutional shareholding and firm size are significant and positive determinants of
firm performance (as measured by a proxy for Tobin’s q) in both the restaurant and
casino industries, while debt has a positive performance impact on the latter only (Tsai
and Gu, 2007a; Tsai and Gu, 2007b). Mao and Gu (2008) indicated that financial
leverage and activity are significant determinants of performance (as measured by a
proxy for Tobin’s q) of US restaurants. They concluded that larger firms, with higher
liquidity, asset turnover, profitability, and faster growth, tend to have higher values.
Financial leverage has a significant but negative effect on restaurant firm performance,
implying that heavy indebtedness tends to reduce firm value in the capital market.
From the accounting perspective, Jung (2008) proposed the application of the Du
Pont ratio for operators to identify the true value drivers and simultaneously the use of
the WACC as the benchmark for performance. Canina and Carvell (2008) argued that