Relationship between Changes in Cash Flow and Investments in Publicy Traded Restaurant Firms in the United States

This research investigated the relationship between investments in fixed assets and free cash flows of U.S. restaurant firms while controlling for future investment opportunities and financial constraints. It also investigated investment and cash-flow sensitivity in the context of economic conditions. Results suggested that investments in small firms (with higher financial constraints) had relatively weaker sensitivity to cash flows than investments in large firms (with higher sensitivity). Controlling for economic conditions did not significantly change results. While the debate over sensitivity of investments to cash flows remains unresolved, it has not been explored widely in industry contexts, especially in services such as the restaurant industry. In addition to its contribution to this literature, this paper provides implications for cash-flow management in publicly traded restaurant companies.

Protecting Your Assets: A Well-Defined Credit Policy Is The Key

In - Protecting Your Assets: A Well-Defined Credit Policy Is The Key – an essay by Steven V. Moll, Associate Professor, The School of Hospitality Management at Florida International University, Professor Moll observes at the outset: “Bad debts as a percentage of credit sales have climbed to record levels in the industry. The author offers suggestions on protecting assets and working with the law to better manage the business.” “Because of the nature of the hospitality industry and its traditional liberal credit policies, especially in hotels, bad debts as a percentage of credit sales have climbed to record levels,” our author says. “In 1977, hotels showing a net income maintained an average accounts receivable ratio to total sales of 3.4 percent. In 1983, the accounts receivable ratio to total sales increased to 4.1 percent in hotels showing a net income and 4.4 percent in hotels showing a net loss,” he further cites. As the professor implies, there are ways to mitigate the losses from bad credit or difficult to collect credit sales. In this article Professor Moll offers suggestions on how to do that. Moll would suggest that hotels and food & beverage operations initially tighten their credit extension policies, and on the following side, be more aggressive in their collection-of-debt pursuits. There is balance to consider here and bad credit in and of itself as a negative element is not the only reflection the profit/loss mirror would offer. “Credit managers must know what terms to offer in order to compete and afford the highest profit margin allowable,” Moll says. “They must know the risk involved with each guest account and be extremely alert to the rights and wrongs of good credit management,” he advocates. A sound profit policy can be the result of some marginal and additional credit risk on the part of the operation manager. “Reality has shown that high profits, not small credit losses, are the real indicator of good credit management,” the author reveals. “A low bad debt history may indicate that an establishment has an overly conservative credit management policy and is sacrificing potential sales and profits by turning away marginal accounts,” Moll would have you believe, and the science suggests there is no reason not to. Professor Moll does provide a fairly comprehensive list to illustrate when a manager would want to adopt a conservative credit policy. In the final analysis the design is to implement a policy which weighs an acceptable amount of credit risk against a potential profit ratio. In closing, Professor Moll does offer some collection strategies for loose credit accounts, with reference to computer and attorney participation, and brings cash and cash discounts into the discussion as well. Additionally, there is some very useful information about what debt collectors – can’t – do!

Private Club Financial Performance

This article reveals the median financial results for the club industry for 2011 using 24 financial ratios. The results are based on the submission of balance sheet and selected income statement numbers from 80 clubs. The ratios are reported as median results for the entire sample as well as the median results for the top and low performing clubs delineated by return on assets. The biggest differences between the two extreme groups of clubs are (1) average collection period, (2) operating cash flows to current liabilities and long-term debt, (3) fines interest earned, (4) fixed charge coverage ratio, (5) food and beverage inventory turnovers, (6) profit margin, (7) return on assets, (8) operating efficiency ratio, (9) labor cost percentage.

Fixed Site Amusement Rides: Who Regulates Safety?

There is currently no national regulation of fixed site (ex. roller coaster) amusement ride safety. The current regulatory system is highly fragmented and consists of many disparate efforts by State and local agencies, judicial intervention in the form of tort litigation and industry self regulatory compliance. The Federal government has no authority over fixed site ride safety. The authors review the state of fixed site ride regulation and the merits of both centralized and de-centralized regulation, including a proposed Federal statute conferring jurisdiction of the matter upon the Consumer Products Safety Commission. They conclude with proposals for enhancing the management of fixed site ride safety.

Does the Pareto Distribution of Hurricane Damage Inherit its Fat Tail from a Zipf Distribution of Assets at Hazard?

Tropical Cyclones are a continuing threat to life and property. Willoughby (2012) found that a Pareto (power-law) cumulative distribution fitted to the most damaging 10% of US hurricane seasons fit their impacts well. Here, we find that damage follows a Pareto distribution because the assets at hazard follow a Zipf distribution, which can be thought of as a Pareto distribution with exponent 1. The Z-CAT model is an idealized hurricane catastrophe model that represents a coastline where populated places with Zipf- distributed assets are randomly scattered and damaged by virtual hurricanes with sizes and intensities generated through a Monte-Carlo process. Results produce realistic Pareto exponents. The ability of the Z-CAT model to simulate different climate scenarios allowed testing of sensitivities to Maximum Potential Intensity, landfall rates and building structure vulnerability. The Z-CAT model results demonstrate that a statistical significant difference in damage is found when only changes in the parameters create a doubling of damage.