A Financial Ratio‐Based Predicting Model for Hotel Business Failure

Zhai, S; Choi, Jeong Gil; Kwansa, Francis A.

doi:10.17549/gbfr.2015.20.1.71

Cited by 7 publications

(8 citation statements)

References 12 publications

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“…These findings have been applied to the hotel industry in studies of the relationship between hotels' failure and their financial structure (Zhai et al, 2015;Gémar et al, 2016;Lado-Sestayo et al, 2016;Patiar, 2016). A financial structure loaded with short-term debt makes hotels prime candidates for bankruptcy (Gu and Gao, 2000).…”

Section: Cost Structurementioning

confidence: 98%

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Predicting bankruptcy in resort hotels: a survival analysis

Gémar

Soler

Parra

2019

IJCHM

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Purpose This study aims to examine variables influencing resort hotels’ survival in Spain, which had not previously been analysed. In this country, determining whether the reasons resort hotels close are different from other hotels could be imperative to resort hotels’ survival. Design/methodology/approach The survival analysis used Cox’s semi-parametric proportional hazards regression to determine which variables influence hotel closure and how much each variable increases risk of closure. Findings Resort hotel closure depends on hotel size, location, executive management and the business cycle. Survival is not affected by hotel type or financial structure. Research limitations/implications While this methodology is common in business survival analyses, it has seldom been applied to hotels and has never been used to study the survival of resort hotels. Practical implications Companies need to rethink the location of new hotels. For already-built facilities, good management practices are strategically important for resort hotels’ survival. Originality/value This paper explores the reasons why resort hotels survive. The study’s selection of variables and methodology and its conclusions are unique.

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Section: Cost Structurementioning

confidence: 98%

“…Given the special importance of beach resorts in Spain and changes in global tourism, both hotel and destination managers urgently need to understand what influences hotel continuity. However, surprisingly few studies have examined why hotel companies survive (Zhai et al, 2015;Gémar et al, 2016;Lado-Sestayo et al, 2016;Patiar, 2016).…”

Section: Introductionmentioning

confidence: 99%

Predicting bankruptcy in resort hotels: a survival analysis

Gémar

Soler

Parra

2019

IJCHM

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“…Nevertheless, there is a lack of studies focusing on SMEs in the hospitality industry (Pacheco, 2015;Zainol Abidin et al, 2020). Most of the published works on hospitality failure focused on public-listed firms (Barreda et al, 2017;Fernández-Gámez et al, 2016;Gemar et al, 2019;Kim & Gu, 2006;Park & Hancer, 2012;Youn & Gu, 2010a;2010b;Zhai et al, 2015). Similarly, in the context of Malaysian literature, the majority of research on corporate failures has focused on public-listed firms (Abdullah, 2020;Abdullah & Ahmad, 2005;Alifiah & Tahir, 2018;Low et al, 2001;Yasser & Mamun, 2015).…”

Section: Introductionmentioning

confidence: 99%

Bankruptcy Prediction: Smes in the Hospitality Industry

Abidin

Abdullah

Khaw

2021

International Journal of Banking and Finance

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The objectives of this study are to predict bankruptcy risk among SMEs in the hospitality industry for a three-year horizon period and to investigate the factors that are significant in determining bankruptcy. The contribution of SMEs in the hospitality industry is essential as businesses in the hospitality industry are dominated by SME operators. However, the failure rate among SMEs is relatively high and almost 50 percent of hospitality establishments do not survive beyond five years of operation. The Stepwise logistic model was employed to determine significant predictors that could predict bankruptcy for the period of one year, two years and three years before bankruptcy. Return on assets and firm age were found to be significant in all periods while other variables were identified to be important at a specific period prior to bankruptcy. In addition to return on assets and firm age, debt ratio and total assets turnover were found to be significant predictors of bankruptcy one-year prior to bankruptcy. However, in the two years prior to bankruptcy, debt ratio and total assets turnover were no longer important but current ratio, ownership concentration and gender diversity were found to be significant. As for the three years prior to bankruptcy, additional variables namely debt-to-equity ratio and board size were found to be significant, but ownership concentration and gender diversity ceased to be important. The findings of this study contribute to the limited literature in predicting the bankruptcy risk of small firms for a three-year horizon period by providing empirical evidence from SMEs in the hospitality industry of Malaysia.

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“…The tourism industry in the context of early crisis and insolvency detection seems highly relevant because it is a high-risk industry (Zhai et al, 2015). This can be illustrated and confirmed for Austria by the following time series of insolvency rates (see Table . 1) based on reports by Creditreform.…”

Section: Introductionmentioning

confidence: 55%

Financial distress in the Austrian tourism industry: hotels and restaurants analysis

Situm¹

2023

EJTR

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Considering the limited number of studies on the early detection of crises and insolvencies in the tourism industry, there are several research gaps. Therefore, this study analyzes which financial and non-financial variables significantly influence the financial distress of the tourism businesses (hotels and restaurants) in Austria. The resource-based and network-based views were used as theoretical foundations to determine which variables influence the probability of financial distress, with a total of 776 observations from 2005 to 2015 inclusive. The results show that variables describing the endogenous unsystematic risk of tourism businesses (firm-specific level and destination level) make the greatest contribution to explaining financial distress, while exogenous unsystematic and exogenous systematic risk variables show little or no relevance.

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A Financial Ratio‐Based Predicting Model for Hotel Business Failure

Cited by 7 publications

References 12 publications

Predicting bankruptcy in resort hotels: a survival analysis

Predicting bankruptcy in resort hotels: a survival analysis

Bankruptcy Prediction: Smes in the Hospitality Industry

Financial distress in the Austrian tourism industry: hotels and restaurants analysis

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