Mega sports events such as the Olympics and the FIFA World Cup are highly attended and countries compete ferociously to host such events due to their perceived long term positive effects. Inbound tourist forecasting is an important aspect of the hosting decision both for the organizing committees and the hosting nations. As a precaution against letting the event fall into incapable hands, which can lead into chaos and mismanagement, measures needs to be taken. Capacity evaluation of interested parties is possible, only by knowing the number of people who may attend the event. However, due to the infrequent occurrence of such events, it is not straightforward to do so.
In this thesis, focus is made on a regression model known as the Gravity Model to predict the number of inbound tourists between pairs of countries. A large set of quantitative and quantified-qualitative factors having impact on the touristic behavior of people is studied and models from the literature are validated using this data. The results are discussed and important suggestions are made. Moreover, the Gravity Model is extended and new predictors are introduced accounting for significant aspects of tourism in general and mega events in particular. The new model will give more accurate results potentially.
","abstract_html":"<p>Mega sports events such as the Olympics and the FIFA World Cup are highly attended and countries compete ferociously to host such events due to their perceived long term positive effects. Inbound tourist forecasting is an important aspect of the hosting decision both for the organizing committees and the hosting nations. As a precaution against letting the event fall into incapable hands, which can lead into chaos and mismanagement, measures needs to be taken. Capacity evaluation of interested parties is possible, only by knowing the number of people who may attend the event. However, due to the infrequent occurrence of such events, it is not straightforward to do so.</p> <p>In this thesis, focus is made on a regression model known as the Gravity Model to predict the number of inbound tourists between pairs of countries. A large set of quantitative and quantified-qualitative factors having impact on the touristic behavior of people is studied and models from the literature are validated using this data. The results are discussed and important suggestions are made. Moreover, the Gravity Model is extended and new predictors are introduced accounting for significant aspects of tourism in general and mega events in particular. The new model will give more accurate results potentially.</p>","abstract_has_math":false,"creators":["Stanekzai, Abdul Sami"],"institution":null,"degree_name":"Master of Science (MS)","degree_level":"Thesis","degree_discipline":"Engineering Management & Systems Engineering","degree_department":null,"school":null,"contributors":["Ghaith Rabadi","T. Steven Cotter","Mamadou Seck"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-07-01T07:00:00Z","date_published":"2016-07-01T07:00:00Z","updated_at":"2026-07-24T03:33:54Z","subjects":["Gravity model","Mega sport events","Ordinary least square regression","Tourists forecasting","Business Administration, Management, and Operations","Economics","Engineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["9781369285109"],"render_values":[{"text":"9781369285109","href":null,"code":true}]}]},"links":{"outbound_url":"https://digitalcommons.odu.edu/emse_etds/5","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Ghaith Rabadi","T. Steven Cotter","Mamadou Seck"]},{"key":"dc:creator","label":"Author","values":["Stanekzai, Abdul Sami"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2016-10-18T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Engineering Management & Systems Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Gravity model","Mega sport events","Ordinary least square regression","Tourists forecasting","Business Administration, Management, and Operations","Economics","Engineering"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["9781369285109","https://digitalcommons.odu.edu/emse_etds/5"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Mega sports events such as the Olympics and the FIFA World Cup are highly attended and countries compete ferociously to host such events due to their perceived long term positive effects. Inbound tourist forecasting is an important aspect of the hosting decision both for the organizing committees and the hosting nations. As a precaution against letting the event fall into incapable hands, which can lead into chaos and mismanagement, measures needs to be taken. Capacity evaluation of interested parties is possible, only by knowing the number of people who may attend the event. However, due to the infrequent occurrence of such events, it is not straightforward to do so.
In this thesis, focus is made on a regression model known as the Gravity Model to predict the number of inbound tourists between pairs of countries. A large set of quantitative and quantified-qualitative factors having impact on the touristic behavior of people is studied and models from the literature are validated using this data. The results are discussed and important suggestions are made. Moreover, the Gravity Model is extended and new predictors are introduced accounting for significant aspects of tourism in general and mega events in particular. The new model will give more accurate results potentially.
"]},{"key":"dc:title","label":"Title","values":["Extension of the Gravity Model: A Risk Integrated Approach Towards the Impact Analysis of Mega Sports Events on Inbound Tourist Arrivals"]}]}],"canonical_facts":{"dc:contributor":["Ghaith Rabadi","T. Steven Cotter","Mamadou Seck"],"dc:creator":["Stanekzai, Abdul Sami"],"dc:date.available":["2016-10-18T07:00:00Z"],"dc:description.abstract":["Mega sports events such as the Olympics and the FIFA World Cup are highly attended and countries compete ferociously to host such events due to their perceived long term positive effects. Inbound tourist forecasting is an important aspect of the hosting decision both for the organizing committees and the hosting nations. As a precaution against letting the event fall into incapable hands, which can lead into chaos and mismanagement, measures needs to be taken. Capacity evaluation of interested parties is possible, only by knowing the number of people who may attend the event. However, due to the infrequent occurrence of such events, it is not straightforward to do so.
In this thesis, focus is made on a regression model known as the Gravity Model to predict the number of inbound tourists between pairs of countries. A large set of quantitative and quantified-qualitative factors having impact on the touristic behavior of people is studied and models from the literature are validated using this data. The results are discussed and important suggestions are made. Moreover, the Gravity Model is extended and new predictors are introduced accounting for significant aspects of tourism in general and mega events in particular. The new model will give more accurate results potentially.
"],"dc:identifier":["9781369285109","https://digitalcommons.odu.edu/emse_etds/5"],"dc:subject":["Gravity model","Mega sport events","Ordinary least square regression","Tourists forecasting","Business Administration, Management, and Operations","Economics","Engineering"],"dc:title":["Extension of the Gravity Model: A Risk Integrated Approach Towards the Impact Analysis of Mega Sports Events on Inbound Tourist Arrivals"],"thesis:degree_discipline":["Engineering Management & Systems Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Science (MS)"]},"updated_at":"2026-07-24T03:33:54Z"}