PIANC Smart Rivers 2022
Reviewing Presentation documents
Topic:
Inland Navigation Structure
Logistics
River System Management
Smart Shipping
Special Sessions
Waterway Infrastructure
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1
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Region:
Afghanistan
Albania
Algeria
America
Andorra
Angola
Antigua and Barbuda
Argentina
Armenia
Aruba
Australia
Austria
Azerbaijan
Bahamas
Bahrain
Bangladesh
Belarus
Belgium
Belize
Benin
Bermuda
Bhutan
Bolivia
Bosnia and Barbados
Bosnia and Herzegovina
Botswana
Brazil
British Virgin Islands
Brunei
Bulgaria
Burkina Faso
Burundi
Cambodia
Cameroon
Canada
Cape Verde
Cayman Islands
Central African Republic
Chad
Chile
China
China(Hong Kong)
China(Macao)
China(Tai wan)
Colombia
Comoros
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Croatia
Cuba
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Democratic Republic of the Congo
Denmark
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Dominican Republic
Ecuador
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Ethiopia
Falkland Islands
Faroe Islands
Fiji
Finland
France
Gabon
Gambia
Georgia
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Ghana
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Grenada
Guatemala
Guinea
Guinea-Bissau
Guyana
Haiti
Honduras
Hungary
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India
Indonesia
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Italy
Jamaica
Japan
Jordan
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Kiribati
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Laos
Latvia
Lebanon
Lesotho
Liberia
Libya
Liechtenstein
Lithuania
Luxembourg
Macedonia
Madagascar
Malawi
Malaysia
Maldives
Mali
Malta
Mauritania
Mauritius
Mexico
Micronesia
Moldova
Monaco
Mongolia
Montenegro
Morocco
Mozambique
Myanmar
Namibia
Nauru
Nepal
Netherlands
New Zealand
Nicaragua
Niger
Nigeria
North Korea
Norway
Oman
Pakistan
Palau
Palestine
Panama
Papua New Guinea
Paraguay
Peru
Philippines
Poland
Portugal
Puerto Rico
Qatar
Romania
Russia
Rwanda
Saint Kitts and Nevis
Saint Lucia
Saint Vincent And The Grenadine
San Marino
Sao Tome and Principe
Saudi Arabia
Senegal
Serbia
Seychelles
Sierra Leone
Singapore
Slovak Republic
Slovenia
Solomon Islands
Somalia
South Africa
South Korea
Spain
Sri Lanka
Sudan
Suriname
Swaziland
Sweden
Switzerland
Syria
Tajikistan
Tanzania
Thailand
Togo
Tonga
Trinidad and Tobago
Tunisia
Turkey
Turkmenistan
Tuvalu
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States of America
Uruguay
Uzbekistan
Vanuatu
Venezuela
Vietnam
Wallis and Futuna
Western Samoa
Yemen
Zambia
Zimbabwe
Email:
Is corresponding author or not (one only):
Author
2
Name:
Affiliations:
Region:
Afghanistan
Albania
Algeria
America
Andorra
Angola
Antigua and Barbuda
Argentina
Armenia
Aruba
Australia
Austria
Azerbaijan
Bahamas
Bahrain
Bangladesh
Belarus
Belgium
Belize
Benin
Bermuda
Bhutan
Bolivia
Bosnia and Barbados
Bosnia and Herzegovina
Botswana
Brazil
British Virgin Islands
Brunei
Bulgaria
Burkina Faso
Burundi
Cambodia
Cameroon
Canada
Cape Verde
Cayman Islands
Central African Republic
Chad
Chile
China
China(Hong Kong)
China(Macao)
China(Tai wan)
Colombia
Comoros
Costa Rica
Croatia
Cuba
Cyprus
Czech Republic
Democratic Republic of the Congo
Denmark
Djibouti
Dominica
Dominican Republic
Ecuador
Egypt
El Salvador
Equatorial Guinea
Eritrea
Estonia
Ethiopia
Falkland Islands
Faroe Islands
Fiji
Finland
France
Gabon
Gambia
Georgia
Germany
Ghana
Gibraltar
Greece
Grenada
Guatemala
Guinea
Guinea-Bissau
Guyana
Haiti
Honduras
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Jamaica
Japan
Jordan
Kazakhstan
Kenya
Kiribati
Kuwait
Kyrgyzstan
Laos
Latvia
Lebanon
Lesotho
Liberia
Libya
Liechtenstein
Lithuania
Luxembourg
Macedonia
Madagascar
Malawi
Malaysia
Maldives
Mali
Malta
Mauritania
Mauritius
Mexico
Micronesia
Moldova
Monaco
Mongolia
Montenegro
Morocco
Mozambique
Myanmar
Namibia
Nauru
Nepal
Netherlands
New Zealand
Nicaragua
Niger
Nigeria
North Korea
Norway
Oman
Pakistan
Palau
Palestine
Panama
Papua New Guinea
Paraguay
Peru
Philippines
Poland
Portugal
Puerto Rico
Qatar
Romania
Russia
Rwanda
Saint Kitts and Nevis
Saint Lucia
Saint Vincent And The Grenadine
San Marino
Sao Tome and Principe
Saudi Arabia
Senegal
Serbia
Seychelles
Sierra Leone
Singapore
Slovak Republic
Slovenia
Solomon Islands
Somalia
South Africa
South Korea
Spain
Sri Lanka
Sudan
Suriname
Swaziland
Sweden
Switzerland
Syria
Tajikistan
Tanzania
Thailand
Togo
Tonga
Trinidad and Tobago
Tunisia
Turkey
Turkmenistan
Tuvalu
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States of America
Uruguay
Uzbekistan
Vanuatu
Venezuela
Vietnam
Wallis and Futuna
Western Samoa
Yemen
Zambia
Zimbabwe
Email:
Is corresponding author or not (one only):
Abstract :
*(250~1000 words)
Waterway transport in Brazil is notoriously associated with cargo flows in coastal and long-distance maritime navigation, beside to inland navigation sections. Of course, the country's territorial predicates, such as a vast coastline and waterway network, contribute to reinforcing this vision. The amount of extensive rives arranged in the country, sometimes, minimizes the visibility of other navigation modalities. This is the case of crossing navigation, which can be defined, by Brazilian legislation, as that which occurs transversally to the courses of rivers and canals, connecting two points on the same bank or when it occurs between two points of the same road or railroad intercepted by body of water. The country's urbanization process, allied to the expansion of the economic frontier, which have occurred concomitantly in the last five decades, are responsible for the increase in the number of cities and urban settlements and for the increase in the country's arable area. However, in many cases, transport infrastructure did not keep pace with the process of territorial occupation. In this sense, many highways were provided without the proper instruments for transposing watercourses. As a result, several crossing shipping companies emerged. This type of operator grows every day in view of the need to interconnect cities, rural areas and production regions. Nowadays, there are hundreds of crossing lines in operation. One of the main issues inherent to these services is the prices charged and the respective affordability. Considering the scenario described, the present work sought to estimate modest price ranges from a sample of vehicle transport prices in crossing navigation. For this, the statistical method of Linear Regression was applied. Regression analysis is the statistical methodology for predicting values of one or more response (dependent) variable from a collection of predictor (independent) variable values. It can also be used for assessing the effects of the predictor variables on the responses. Comparing the price charged on a particular crossing line with that resulting from the proposed model, three possible outcomes are assumed. The practiced price may be above or below the forecast range. Alternatively, it will be within the model's prediction range. In concentrated market situations, the operator tends to maximize its gains to the detriment of low tariffs. The use of the proposed methodology may be the first step to indicate evidence of a practice harmful to competition or abuse of economic power. If the practiced price is within the model's prediction range, then it can be considered statistically similar to that practiced in the market. Otherwise, a more detailed analysis of the specific case will be necessary in order to identify possible variations in relation to the common practice of the market.
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