Article

Does Country Attractiveness Matter in International Competition? The Case of Countries’ Bidding to Host Major Sports Events

Taylor & Francis
International Journal of Public Administration
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Abstract

A country’s attractiveness is a factor in its success in many areas of international competition, such as encouraging international investment, but its impact on international sporting events remains unexplored. Using various measurements of country attractiveness, statistical tests of the proposition that a country’s economic, social, and environmental attractiveness are correlated with its success in bidding to host international sporting events were conducted using data on the results of competitions to host 54 world championships in Olympic sports/disciplines from 1990 to 2012. The results presented here affirm the impact of country attractiveness on the success of bids to host such events.

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Sponsorship has become a core issue in sport marketing and a critical concern for event management. It is now an integral part of major events and involves an ongoing commitment by Olympic partners who need to find new ways to gain the maximum returns from their investment. Complementary promotions with tourism organisations of the host country represent one such opportunity. There is also growing recognition that service delivery by tourism and hospitality industries may determine the success of many sponsor activities, such as guest hospitality programs. The dynamic nature of Olympic sponsorship is reviewed in the context of the marketing policy framework of the International Olympic Committee. Factors affecting sponsorship at the Sydney 2000 Games are considered with reference to AMP, Ansett Australia, and Visa. It is shown that tourism organisations can play a more active role in attracting sponsors and achieving positive outcomes for the host country.
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In this paper a count data regression model accounting for endogenous censoring with household specific censoring thresholds is presented. The presented modelling approach is utilized in an analysis of household choice of total number of nights to spend on monthly recreational trips. The empirical study reveals that the suggested approach is feasible and that accounting for endogenous censoring gives a better fit to the data.
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The canonical parameterization of the negative binomial derives directly from the exponential form of the negative binomial probability distribution function. Unlike the NB-2 and NB-1 parameterizations, it is not derived as a Poisson-gamma mixture model, and has the heterogeneity or ancillary parameter as a term in the mean and variance functions. However, the canonical negative binomial can be used effectively to model count response data. The Heterogeneous Canonical Negative Binomial command is similar to Stata's gnbreg command, allowing the ancillary parameter to itself be parameterized. The value of this option is that one may better understand which predictors influence model heterogeneity. That is, it assists in identifying the source of correlation in the data. The command also displays both the AIC and Deviance statistics to aid in model comparison and provides use of Stata's maximum likelihood and survey options.
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This chapter discusses job market signaling. The term market signaling is not exactly a part of the well-defined, technical vocabulary of the economist. The chapter presents a model in which signaling is implicitly defined and explains its usefulness. In most job markets, the employer is not sure of the productive capabilities of an individual at the time he hires him. The fact that it takes time to learn an individual's productive capabilities means that hiring is an investment decision. On the basis of previous experience in the market, the employer has conditional probability assessments over productive capacity with various combinations of signals and indices. This chapter presents an introduction to Spence's more extensive analysis of market signaling.
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I. Introduction, 488. — II. The model with automobiles as an example, 489. — III. Examples and applications, 492. — IV. Counteracting institutions, 499. — V. Conclusion, 500.
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Why is the entry flow of the manufacturing sector extremely high in Taiwan, and does it contribute to the prevailing entrepreneurship? This article aims to explore what factors inspire potential entrants to go into an industry. Based on a theoretical formulation of the Poisson probability entry model, a count data model is employed to investigate the determinants of entry flows. The empirical results reveal that traditional entry barriers indeed lower the entry flow. The entry incentives, including price cost margin and industry growth, play a lesser role at attracting new firms, while alternatively the market size acts as a better proxy of an entry incentive in explaining entry flows. Incumbents' responses to entry, R&D and advertising intensity are found to be associated with a significant negative impact on entry flows. This article also finds that there is a higher bound of covariate of entry, about 10%, that can be attributed to the immeasurable personality of entrepreneurs-entrepreneurship. Rather be the chicken's beak than be the cow's behind.1 The trade that might cause life hazard will be dealt, while the trade that might cause a loss will not be dealt. Two traditional Chinese proverbs