Marketing A Hospitality Program And Its Product

In his dialogue entitled - Marketing A Hospitality Program and Its Product - Jürgen Chopard, Dr. es Sciences (Economics) Director, Centre International de Glion, Glion, Switzerland, Dr. Chopard initially offers: “The recruitment of qualified personnel is extremely difficult in an industry with a poor image; where career paths are not well defined. The author discusses the employment of marketing management techniques to improve the positioning of hospitality education and create a more attractive perception of the hotel industry.” As outlined in the above paragraph, Dr. Chopard vectors-in on marketing strategies from two standpoints; the educational side with its focus on curriculum, and the larger, industry side with its emphasis on public perception and service. These are not necessarily, nor should they be viewed as disparate elements. “ Although some professionals may see schools of hospitality education catering to two markets, students on one hand and industry on the other, in fact, their needs should be viewed as the same and hence a single market,” Dr. Chopard says to bolster his assertion. “The marketing concept is a management orientation that holds that the key task of the organization is to determine the needs and wants of target markets and to adapt the organization to delivering the desired satisfactions more effectively and efficiently than its competitor,” the author confides, with an attribution. From these information/definition leanings, Dr. Chopard continues on a path that promotes the Centre International de Glion, Glion, Switzerland, which he is affiliated with. Why, because they endorse the same principles he is explaining to you. That’s not a bad thing. Essentially, what Dr. Chopard wants you to know is, education and business management are synonymous and therefore should share the same marketing designs and goals. “It is hard to believe that as critically important a sector as education does not use for its own management the techniques which it teaches and which have largely been proved in other fields,” the author provides as counterpoint. Since pedagogical needs so closely relate to the more pragmatic needs of the industry in general, these elements should seek to compliment and engage each other, in fact, collaboration is imperative, Dr. Chopard expresses a priori. “The cooperation of future employers is indispensable in the preparation of the product, so that it is capable of providing the expected services. The need for close relations between training establishments and the hotel and catering industry seems obvious,” Dr. Chopard says. The author reveals some flaws in hospitality marketing strategy, and then contrasts these against how a successful strategy could/should be implemented.

Trends for Meetings and Expositions Industry

During the last decade, the meetings and expositions industry has flourished, even as it has struggled to cope with difficult challenges. This is a taste of things to me. In the years ahead, the global population will continue to grow and change, science and technology will tighten their hold on business and society and the world will knit itself ever more tightly into a single market. As a result, both opportunities and trials will abound.

Using extreme value theory to value stock market returns

Extreme stock price movements are of great concern to both investors and the entire economy. For investors, a single negative return, or a combination of several smaller returns, can possible wipe out so much capital that the firm or portfolio becomes illiquid or insolvent. If enough investors experience this loss, it could shock the entire economy. An example of such a case is the stock market crash of 1987. Furthermore, there has been a lot of recent interest regarding the increasing volatility of stock prices. ^ This study presents an analysis of extreme stock price movements. The data utilized was the daily returns for the Standard and Poor's 500 index from January 3, 1978 to May 31, 2001. Research questions were analyzed using the statistical models provided by extreme value theory. One of the difficulties in examining stock price data is that there is no consensus regarding the correct shape of the distribution function generating the data. An advantage with extreme value theory is that no detailed knowledge of this distribution function is required to apply the asymptotic theory. We focus on the tail of the distribution. ^ Extreme value theory allows us to estimate a tail index, which we use to derive bounds on the returns for very low probabilities on an excess. Such information is useful in evaluating the volatility of stock prices. There are three possible limit laws for the maximum: Gumbel (thick-tailed), Fréchet (thin-tailed) or Weibull (no tail). Results indicated that extreme returns during the time period studied follow a Fréchet distribution. Thus, this study finds that extreme value analysis is a valuable tool for examining stock price movements and can be more efficient than the usual variance in measuring risk. ^

Three essays on the interrelationships among financial restatements, corporate governance, market microstructure and the firm's rate of return

The increase in the number of financial restatements in recent years has resulted in a significant decrease in the amount of market capitalization for restated companies. Prior literature did not differentiate between single and multiple restatements announcements. This research investigated the inter-relationships among multiple financial restatements, corporate governance, market microstructure and the firm’s rate of return in the form of three essays by differentiating between single and multiple restatement announcement companies. First essay examined the stock performance of companies announcing the financial restatement multiple times. The postulation is that prior research overestimates the abnormal return by not separating single restatement companies from multiple restatement companies. This study investigated how market penalizes the companies that announce restatement more than once. Differentiating the restatement announcement data based on number of restatement announcements, the results supported the non persistence hypothesis that the market has no memory and negative abnormal returns obtained after each of the restatement announcements are completely random. Second essay examined the multiple restatement announcements and its perceived resultant information asymmetry around the announcement day. This study examined the pattern of information asymmetry for these announcements in terms of whether the bid-ask spread widens around the announcement day. The empirical analysis supported the hypotheses that the spread does widen not only around the first restatement announcement day but around every subsequent announcement days as well. The third essay empirically examined the financial and corporate governance characteristics of single and multiple restatement announcements companies. The analysis showed that corporate governance variables influence the occurrence of multiple restatement announcements and can distinguish multiple restatements announcement companies from single restatement announcement companies.

A study of stock market fluctuations and their relation to business conditions

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubblelike deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the nonfundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.

Three Essays on the Interrelationships Among Financial Restatements, Corporate Governance, Market Microstructure and the Firm's Rate of Return

The increase in the number of financial restatements in recent years has resulted in a significant decrease in the amount of market capitalization for restated companies. Prior literature does not differentiate between single and multiple restatements announcements. This research investigates the inter-relationships among multiple financial restatements, corporate governance, market microstructure and the firm's rate of return in the form of three essays by differentiating between single and multiple restatement announcement companies. First essay examines the stock performance of companies announcing the financial restatement multiple times. The postulation is that prior research overestimates the abnormal return by not separating single restatement companies from multiple restatement companies. This study investigates how market penalizes the companies that announce restatement more than once. Differentiating the restatement announcement data based on number of restatement announcements, the results support for non persistence hypothesis that the market has no memory and negative abnormal returns obtained after each of the restatement announcements are completely random. Second essay examines the multiple restatement announcements and its perceived resultant information asymmetry around the announcement day. This study examines the pattern of information asymmetry for these announcements in terms of whether the bid-ask spread widens around the announcement day. The empirical analysis supports the hypotheses that the spread does widen not only around the first restatement announcement day but around every subsequent announcement days as well. The third essay empirically examines the financial and corporate governance characteristics of single and multiple restatement announcements companies. The analysis shows that corporate governance variables influence the occurrence of multiple restatement announcements and can distinguish multiple restatements announcement companies from single restatement announcement companies.

A Study of Stock Market Fluctuations and their Relations to Business Conditions

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubble-like deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the non-fundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.