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Procedia - Social and Behavioral Sciences 82 ( 2013 ) 369 – 374

World Conference on Psychology and Sociology 2012 The Relationship Between the Success of Countries at the 2010 Summer and Demo-Economic Factors

Mahdi Shariati Feizabadi a *, Mohammad Khabiri b, Mehrzad Hamidi b

a University of , Tehran, Iran b Physical Education and Sport Sciences Faculty, University of Tehran, Tehran, Iran

Abstract

The main purpose of present study was to predict the success of countries participated at the Guangzhou 2010 Summer Asian Games by demo-economic factors. The present study was causal-comparative and applied. The statistical population consisted of 45 countries at the Guangzhou (not previously analysed). The statistical sample was 36 countries have won medals in that game. The data were collected from different English and Persian evidences and valid websites: World Bank web site and . Kolmogorov – Smirnov, one way ANOVA and stepwise multiple regression tests utilized. K-S test determined data normality (p < 0.05). The results showed a significant relationship between the success of countries at the Guangzhou 2010 Asian Games and all factors of demo-economic (population, GDP, health expense, growth rate, team size, Ex-host). The results of regression analysis showed that among demo-economic factors, team size was able to significantly predict the success of countries at the Guangzhou 2010 Asian Games (R2=0.78, p < 0.0001). In sum, more quota will guarantee the success of countries at the mega events like Asian games.

© 2013 The Authors. Published by Elsevier Ltd. © 2013 The Authors. Published by Elsevier Ltd. Selection and peer review under the responsibility of Prof. Dr. Kobus Maree, University of Pretoria, South Africa. Selection and peer review under the responsibility of Prof. Dr. Kobus Maree, University of Pretoria, South Africa.

Keywords: Asian Games, Success, Medal, Demo-Economic.

1. Introduction

Numerous studies have been done in relation to different "Mega Events", "Wide-Scale Events", "Hallmark Events" and "Sport Events" (Vagenas & Vlachokyriakou, 2011). "Mega Events" are such events which are important for public all around the world (Roche, 2000). There are many factors to show the level of sport events. Increasing number of tourists, the increased turn over, and increased reputation of host country and specially host city are the most important advantages to provoke government for hosting (Andreff & Andreff, 2010). In addition, mega events help the host city to develop its infrastructure.

* Corresponding author: Mahdi Shariati Feizabadi. Tel.: +98-915-820-2501 E-mail address: [email protected]

1877-0428 © 2013 The Authors. Published by Elsevier Ltd. Selection and peer review under the responsibility of Prof. Dr. Kobus Maree, University of Pretoria, South Africa. doi: 10.1016/j.sbspro.2013.06.277 370 Mahdi Shariati Feizabadi et al. / Procedia - Social and Behavioral Sciences 82 ( 2013 ) 369 – 374

The Olympic Council of Asia (OCA) is the most important sport organization in Asia which holds Summer Asian Games every four years (Dolles & Soderman, 2008). Nowadays, after 60 years of its foundation, it has 45 countries as members and 16 committees (Martin, Arin, Palakshappa, & Chetty, 2008). This sport organization holds 6 prominent events in Asia continent (Dolles & Soderman, 2008):

1. 2. Asian Indoor Games 3. 4. Asian Martial – Art Games 5. (AYG) 6. Asian Games: This event is the most important and attractive sport event in Asia. Since 1951 to 1978, the events hold under Asia Federation Games (Benerjee, Marcellino, & Masten, 2005) and after, the OCA was the responsible for these games. Also, the world "Asiade" was allocated to these events, exclusively.

There are many ways to measure countries’ success at the mega events (Deccio & Baloglu, 2002). The lexicographic ranking is a common method for comparing the performance of countries in a mega event (Nevill & Stead, 2003). The ranking based on the number of gold, silver and bronze medals. In other words, the ranking of countries at the Asian Games based on the number and the quality of medals (Kim, Gursoy, & Lee, 2006). The first studies about the mega events, especially Olympic ranking, referred to Berlin 1936 Summer Olympic Games (Pollin & Zhu, 2006). Through the last 4 decades, there were many researches on the demo- economic predictors of success at mega events like Summer Olympic Games, Soccer World Cup, Formula 1 (Roberts, 2004). Although a large number of candidates such as inflation, economic growth, home-neighbouring advantage, political regime, urban population and religious were related to Olympic success (Hoffman, Ging, & Ramasamy, 2004), most of researches concentrated on the logarithmic functions of population and GDP. Charilov and Filtman (2006) reported the main prominent factors of Olympic predictors as follows: population, GDP, life expectancy and death of child (Charilov & Filtman, 2006). Forrest and others tried to forecast the total national team medals of participant countries at the 2008 Summer Olympic Games by utilizing GDP factor. They predict the growth of and UK athletes’ medals and falling of Russia correctly (Forrest, Sanz, & Tena, 2010). Imperiale (2011) also tried to predict 2010 FIFA World Cup by means of socioeconomic predictors. He reported Brazil as champion of these games. In addition to champion, he found a significant relationship between success at Soccer World Cup and some socioeconomic factors such as GDP, inflation and unemployment (Imperiale, 2011). Custonia and Skonia (2011) in a study “Winning Medals at the Olympic Games – Does Croatia Have any Chance?” tried to predict the total medals of Croatia at the Beijing 2008 summer Olympic Games; among the factors such as GDP, population, weather, political regime and home advantage, they reported the economic system as most prominent and important predictor of their athlete’s success at the Olympic games (Custonia & Skonia, 2011). Five hypotheses related to the success at the mega events like Asian Games can be summarized into: Mahdi Shariati Feizabadi et al. / Procedia - Social and Behavioral Sciences 82 ( 2013 ) 369 – 374 371

1. Demographic hypothesis: Different researches investigated the relationship between the population of a country or region with the success of them at the mega events. Populous countries like China or USA are kind of talents pool will brings up tomorrow’s champions (Fan, 2006). 2. Geographic hypothesis: Kazakhstan is an appropriate case study. Once a time, this country was a part of Soviet Union and because of cool weather, all the soviet sport camps were hold in Almata (the capital of Kazakhstan) (Hoffman, Ging, & Ramasamy, 2004). Since the Soviet collapsed, the most champions of Russia come from this region. 3. Economic hypothesis: There are many researches in this field and most of them reported GDP as a prominent and important factor to predict the success of countries at the Olympic Games. Undoubtedly the post- industrialized countries like USA has more chances to succeed at the mega events like the Olympic Games (Hilvoord, Elling, & Stokvis, 2010). 4. Political hypothesis: The governments have two separated politics against the sport: the first choice is attention to professional sport, while the other one is concentrating on the sport for all. It seems that the governments have the most impressive effect on the results of each participant country at the Olympic Games. Johnson and Ali (2008) reported that the countries with communist structure have more chances for the success at the Olympic Games (Johnson & Ali, 2008). 5. Cultural hypothesis: The amount of TV coverage and volunteers’ participation in the mega events can be identified as a cultural element of a country or region (Frey, Iraldo, & Melis, 2007). The number and variety of researches indicated the importance of this problem. This study tried to tackle the relationship between selected demo-economic factors (population, GDP, health expense, team size, Ex-host) with the success (total medals) of countries at the Guangzhou 2010 Summer Asian Games.

2. Methodology

The present study was casual - comparative and applied. The statistical population consisted of 45 countries at the Guangzhou 2010 Summer Asian Games (not previously analyzed); the study sample was 36 countries that won at least one medal in this games. Success was assessed by the total number of medals won by each country (according to literature review). We tried to discover the relationship between some of the demo-economic factors such as population, health-expense, gross domestic product (GDP), team size and Ex-host with the number of medals for each participant country at the Guangzhou 2010 Summer Asian Games. For gathering data, the medal tallies (gold, silver, bronze and total) and Ex-host were collected from Official website of Olympic Council of Asia Website. Valid data gathered related to selected national demographic and economic indicators available in World Bank Website for each participant country for the year preceding the games (2009).In order to analyze the data, descriptive and inferential statistics were utilized. Kolmogorov Smirnov (K-S) test was used to determine the parametric statistical situation. Therefore, the one way ANOVA was utilized to determine the linear relationship between the criterion variable (medals) with the predictor variables (Ex-host, GDP, population, and team size). Finally, the Stepwise Multiple Regression was used to determine the distribution of each predicator variables for predicting the success of each country at the Guangzhou 2010 Summer Asian games.

3. Results

According to table 1, China had the biggest sports board (960) at the Guangzhou 2010 Summer Asian Games. On the other hand, some countries like Lebanon (49) and Iraq (42) participated at least. The amount of GDP for the industrial countries like Japan and were more than poor countries like Laos or Nepal. The 372 Mahdi Shariati Feizabadi et al. / Procedia - Social and Behavioral Sciences 82 ( 2013 ) 369 – 374

champion of Guangzhou 2010 Summer Asian games was the most crowded country by the population about 1331.4 in mil. Although the top four countries of Guangzhou 2010 Summer Asian Games hosted these games, the five bottom countries never hold these games. The health expense for the country like Japan is more than the other presented countries. The number of medals reported in table 1, as follows:

Table 1. Medal tallies and demo-economic factors for 5 top and down country at Guangzhou 2010 Summer Asian Games

Team Growth Health Country Rank Gold Silver Bronze Sum Hosting Population GDP size rate expense China 1 199 119 98 416 1 960 1331.4 3749 0.5 4.6 South 2 76 65 91 232 1 788 48.7 17110 0.3 6.5 Korea Japan 3 48 74 94 216 1 726 127.5 39456 0.1 8.3 Iran 4 20 15 24 59 1 362 72.9 4540 1.3 5.5 Kazakhstan 5 18 23 38 79 0 365 15.9 7241 1.6 4.5 Iraq 32 0 1 2 3 0 42 31.4 2070 2.5 3.9 Lebanon 32 0 1 2 3 0 49 4.2 8269 0.7 8.1 Laos 34 0 0 2 2 0 53 6.3 303 1.8 4.1 Nepal 35 0 0 1 1 0 140 29.3 440 1.8 5.8 Oman 35 0 0 1 1 0 52 2.8 3111 2.1 3 Summit 477 479 621 1577 9132 3905.3

According to table 2, the results of One Way ANOVA indicated that demo-economic factors variables were significant predictors for the success of participant countries at the Guangzhou 2010 Summer Asian games (F = 105.04 , p = 0.0001 ). The coefficient of determination showed that 78 % of the success variance was explained by demo-economic factors.

Table 2. The summary of multiple regression result for success

P - Value R2 Adjusted R2 R F 0.001 0.78 0.77 0.88 105.04

Table 3 showed that the team size (β = 0.88) was the most powerful predictors for the number of total medals of each participant country. The other demo-economic factors (team size, population, GDP, health expense and Ex-host) didn’t have significant relationship with the criterion variable (total medal).

Table 3. The coefficients for success at the Guangzhou 2010 Summer Asian Games

Variables Non-standardized β Coefficient Standardized β Coefficient t P - Value Constant -38.97 -3.45 0.001 Team Size 0.327 0.88 10.26 0.001

Also, the regression equivalent reported as follow:

Y(Constant) = 0.32 (X1) – 38.97

The X1 stands for team size. Mahdi Shariati Feizabadi et al. / Procedia - Social and Behavioral Sciences 82 ( 2013 ) 369 – 374 373

4. Discussion

The first problem raised in was the possibility for the prediction of regular and mega event like Asian Games. Literature review revealed that the results of countries at the hallmark events like Asian Games can be forecasted by some of demo-economic factors such as inflation, health expense, unemployment, GDP, urban population, etc. According to results, team size is the best predictor of participant countries’ success at the Asian Games. The more athletes will bring the chance to achieve more medals. According to table 1, the top five countries included China, South Korea, Japan, Iran and Kazakhstan by sending 3201 athletes and official members as sport board (35.0 % on the whole), achieved 1002 medals (63.5 % on the whole). On the other hand, the bottom five countries included Iraq, Lebanon, Laos, Oman and Nepal with only 336 athletes (3.6 % on the whole) in these games, they had a disappointed results and achieved just 5 medals (0.6 % on the whole) in sum. On the other hand, the other demo-economic factors like population, gross domestic product (GDP), health expense and growth rate couldn't predict the success of countries at Guangzhou 2010 Summer Asian Games. Although some countries such as Indonesia and Pakistan are populated, their dilute demonstration was an appropriate example. These results were similar to the results received by Vlachokyriakou and Vagenas (2011), Hilvood (2010) and Andreff and Andreff (2010) who reported the team size as a significant predictor of countries’ success at mega events like Olympic Games. On the other hand, Morton (2000), Suen and Lui (2008) reported GDP and Population as the most important predictor of countries’ success at mega sport events. It seems their population study on the Olympic Games was an important reason for this contrast. Success at the Asian Games will bring national pride for each country. Government’s attention to championship and allocation enough resources to this section will improve national prestige on the global level. Investment on talent identification and work on adolescents can bring more and more quota and finally they will achieve brilliant medals for their country.

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