The model code has been completed, for your reference only, if you need more, please see the end of the article
1. Problem Analysis
First, historical data related to the Olympic host city/country needs to be collected. This needs to address aspects such as economics, land use, human satisfaction (including athletes and spectators), travel, infrastructure development, environmental impact, and more. Data collection can be carried out by consulting sources such as official documents of the International Olympic Committee, news reports, academic papers, and data from various national statistical offices or relevant institutions. The goal of this phase is to obtain sufficient data for in-depth analysis and research.
The collected data can then be initially explored using descriptive statistical analysis and visualization tools. Data distributions, trends, and associations can be better understood, providing the basis for subsequent analysis. On the basis of preliminary analysis of historical data, a set of comprehensive evaluation index system is established.
These metrics should cover economics, land use, human satisfaction (athletes and spectators), travel, opportunities for future improvements, host city/country prestige, etc. to help us get a more complete picture of the impact of Olympic hosting. In addition, we also need to assign a certain weight to each indicator to reflect its relative importance. We evaluate and rank different strategies based on AHP, TOPSIS and Monte Carlo simulations. At this stage, we need to apply the comprehensive evaluation index system to various potential strategies to determine which strategies perform best in various aspects. In addition, we can also use methods such as sensitivity analysis to examine the performance of strategies under different assumptions and parameter settings, so as to ensure that our recommendations are robust in different situations. Based on the analysis results, we will provide specific strategic recommendations to the IOC. This includes determining the optimal hosting plan for the Olympic Games, such as setting up a permanent venue, holding it in quarters, and so on. At the same time, we also need to consider how to fully consider the needs of various stakeholders in the process of implementing these strategies to ensure the success of the Olympic Games
Finally, regular evaluation and adjustment of the effectiveness of the implemented strategy is recommended. In the actual operation process, some unexpected problems may occur, or the effect of some strategies may not meet expectations. Therefore, in the process of implementing the strategy, we need to continuously collect new data, conduct monitoring and evaluation, and adjust the strategy according to the actual situation, so as to ensure the long-term sustainability and success of the Olympic Games.
2. Model assumptions
In response to the questions raised in this paper, we made the following model assumptions:
1. It is assumed that the historical data collected are representative and can reflect the real situation of the host city/country of the Olympic Games in all aspects.
2. Assume that the indicators included in the comprehensive evaluation index system can fully measure the impact of the Olympic Games.
3. Assume that the weights assigned to each indicator can accurately reflect their relative importance.
4. Assume that various external factors in the process of strategy implementation can be regarded as constant or controllable. External factors such as the policy environment, international relations, and market conditions remain stable to a certain extent and do not have a significant impact on the implementation of the strategy.
5. Assuming that the holding mode and scale of the future Olympic Games are consistent with historical data.
3. Symbol description
The commonly used symbols in this paper are shown in the table below, and other symbols are explained in the text
| symbol |
Symbolic meaning |
| N |
Sample size for historical Olympic Games data. |
| CR |
consistency ratio |
| P |
random probability distribution |
| Alpha |
Parameters for adjusting weights |
| A |
comparison matrix |
| R |
Sort results of policies |
4. Modeling and solving
5.1 Data preprocessing
First, preprocess the data given in the text
data standardization
Data standardization is mainly to scale the data to a fixed interval according to a certain ratio. On the one hand, it can make the data characteristics of different dimensions dimensionless. On the other hand, data standardization will reduce the complexity of numerical calculations and further accelerate the speed of model convergence. and improve the accuracy of the model. In large data scale or neural network models, data standardization is essential. However, the practical application of data standardization is not only beneficial. Data standardization may also lead to deviations in prediction results. The main reason is that the prediction results after data standardization are also scaled to a fixed range, losing the actual numerical meaning. It needs to be restored through the method of denormalization, and the deviation is generated at this time.
There are two commonly used data standardization methods: min-max standardization and Z-Score standardization. Z-Score standardization is selected according to the characteristics of educational data, also called standard deviation standardization. It is mainly based on mean and standard deviation to standardize data. method works when the maximum and minimum values in the sequence are unknown.
The formula is skipped, if you can’t type it out, let’s just look at the analysis.
Number of Olympic Games held by country
The data comes from the Olympic official website
The python code of the picture is as follows (pandas is required, remember to fill in the root directory of the data marked in red):
import pandas as pd
import matplotlib.pyplot as plt
# 读取历届奥运会举办城市数据
olympics_data = pd.read_csv("你所放置文件的根目录", encoding='gbk')
# 读取世界发展指标投资数据
investment_data = pd.read_csv("你所放置文件的根目录", encoding='gbk')
# 读取全球劳动力参与和失业数据
labor_data = pd.read_csv("你所放置文件的根目录", encoding='gbk')
# 读取全球 GDP 及人均 GDP 数据
gdp_data = pd.read_csv("你所放置文件的根目录", encoding='gbk')
# 历届奥运会举办城市分布图
olympics_count = olympics_data.groupby('Country')['City'].count()
olympics_count.plot(kind='bar')
plt.title("Number of Olympic Games Hosted by Country")
plt.xlabel("Country")
plt.ylabel("Number of Olympic Games")
plt.show()
Tourism data by country
The data comes from the World Tourism Organization
Some pictures for your reference. The data comes from the World Tourism Organization, the Olympic official website, and the United Nations. Where can I find the data?
You can go to the World Bank, United Nations Environment Programme, US National Bureau of Statistics, World Health Organization, US Government Open Data, github, etc.
5.2 Establish an indicator system
(Note, you can think about it yourself here, I have written each indicator in more detail, and you can consider other indicators yourself)
Next, in order to comprehensively evaluate the impact of hosting the Olympic Games, we established an index system that includes six aspects including economy, land use, human satisfaction, travel, future improvement opportunities, and prestige. These indicators are as follows:
1. Economic aspects
The economic aspect is an important aspect to evaluate the impact of hosting the Olympic Games. The following are specific indicators:
Economic benefits of the Olympic Games: including direct economic benefits and indirect economic benefits. Direct economic benefits refer to the economic benefits generated during the preparation and holding of the Olympic Games, such as venue construction, event operation and tourism; indirect economic benefits refer to the impact and long-term benefits brought about by the Olympic Games, such as the improvement of the city's image and regional development opportunities.
Sponsors and advertising revenue: The Olympic Games is an important platform to attract sponsors and advertisers. Sponsorship and advertising revenue can reflect the promotion of the Olympic Games to the economy.
Tourism income: The Olympic Games is an important factor in attracting tourists to travel. Tourism revenue can reflect the role of the Olympic Games in promoting local tourism.
2. Land use
Land use is an important aspect to evaluate the impact of hosting the Olympic Games. The following are specific indicators:
Land area for Olympic venues and infrastructure construction: The construction of Olympic venues and infrastructure requires a large amount of land resources, which will have a certain impact on land use and environmental protection.
Sustainable design of venues: The design and construction of Olympic venues should consider environmental sustainability factors such as energy efficiency, water use and waste management.
Surrounding environment of venues: The construction and holding of Olympic venues will have a certain impact on the surrounding environment, such as noise pollution and air pollution.
3. Human Satisfaction Aspects
The aspect of human satisfaction is an important aspect to evaluate the impact of hosting the Olympic Games. The following are specific indicators:
Athletes and spectators' evaluation of event organization and venue facilities: Olympic Games should guarantee the safety and service quality of event organization and venue facilities, so as to improve the satisfaction of athletes and spectators.
Participation and support of local residents for the Olympic Games: The interests and needs of local residents should be fully considered in the hosting of the Olympic Games, and the participation and support of local residents for the Olympic Games should be enhanced to improve the social acceptance and sense of identity of the Olympic Games.
4. Travel
Travel is an important aspect in evaluating the impact of hosting the Olympic Games. The following are specific indicators:
Traffic conditions during the Olympic Games: During the Olympic Games, urban traffic pressure is high, and whether the traffic conditions are good or not will have a great impact on the travel of tourists and residents.
Travel methods and expenses of tourists: The attractiveness of the Olympic Games to tourists has a lot to do with the travel methods and expenses of tourists.
5. Opportunities for future improvement
The aspect of future improvement opportunities is an important aspect to evaluate the impact of hosting the Olympic Games. The following are specific indicators:
Reuse of venues and infrastructure after the Olympic Games: The reuse of Olympic venues and infrastructure is of great significance for improving the long-term benefits and sustainability of the Olympic Games.
Opportunities for the development of tourism and local economy: The hosting of the Olympic Games should bring opportunities and potential for the development of local tourism and economy.
6. Prestige
The prestige aspect is an important aspect to evaluate the influence of hosting the Olympic Games. The following are specific indicators:
The impact of hosting the Olympic Games on the international reputation and image of the host city/country: hosting the Olympic Games can enhance the international image and reputation of the host city/country, which is of great significance to international cooperation and cultural exchanges.
The above is the index system we have established, which can evaluate and comprehensively analyze the impact of the Olympic Games from different angles.
5.2.1 Analytic Hierarchy Process
We construct a hierarchical structure model of indicators in six aspects, in which economy, land use, human satisfaction, travel, future improvement opportunities, and reputation are the first-level factors, and the following are the second-level factors respectively.
Then in the next step, we start to formulate the judgment matrix
Based on expert opinions and relevant literature, we formulated a pairwise comparison judgment matrix, and obtained the weight of each factor according to the standardized processing method of the AHP method.
Formula skipped.
We get the judgment matrix as follows:
| economy |
land use |
human satisfaction |
travel |
Future Improvement Opportunities |
prestige |
|
| economy |
1 |
3 |
4 |
2 |
4 |
2 |
| land use |
44929 |
1 |
3 |
44928 |
3 |
44928 |
| human satisfaction |
44930 |
44929 |
1 |
44928 |
2 |
44928 |
| travel |
44928 |
2 |
2 |
1 |
3 |
1 |
| Future Improvement Opportunities |
44930 |
44929 |
44928 |
44929 |
1 |
44928 |
| prestige |
44928 |
2 |
2 |
1 |
2 |
1 |
judgment matrix
According to the judgment matrix, we get the weight of each factor as follows:
| factor |
Weights |
| economy |
0.2464 |
| land use |
0.1361 |
| human satisfaction |
0.1856 |
| travel |
0.1589 |
| Future Improvement Opportunities |
0.1277 |
| prestige |
0.1453 |
Table 5.2 Weight of each factor
According to the above calculation,
We get the consistency ratio of the judgment matrix, just calculate it yourself.
The latter is to use TOPSIS to get the evaluation model
You can see below ↓