Maximizing visitors at college football bowl games. Issue 3 (9th October 2017)
- Record Type:
- Journal Article
- Title:
- Maximizing visitors at college football bowl games. Issue 3 (9th October 2017)
- Main Title:
- Maximizing visitors at college football bowl games
- Authors:
- Popp, Nels
Jensen, Jonathan
Jackson, Rhett - Abstract:
- Abstract : Purpose: The purpose of this paper is to isolate factors predictive of event attendees, and assist tourism professionals such as members of host committees, in maximizing the number of out-of-town visitors to their region and optimizing tourism-related revenue when hosting college football bowl games. Design/methodology/approach: A total of 16 demand variables were entered into a hierarchical regression model, including the stature of the event and market-related variables, as well as team-related variables reflecting team or program stature and current season performance. Findings: A final model containing seven variables (bowl age, market population, conference affiliation, bowl game stature, season wins, home attendance, and distance traveled) predicted 77.5 percent of the variance in bowl game attendance. Research limitations/implications: This paper illustrates the use of predictive modeling for major sport event attendance with a unique sample and variables explored. Future research may build off the model to explore attendance for other populations or events. Practical implications: The applied nature of this study allows practitioners working in the tourism and event management field to incorporate a predictive model to best select participants in sporting events to maximize event attendees. Originality/value: Understanding the variables which predict event attendees in the context of college football bowl games provide useful data to practitioners. ThisAbstract : Purpose: The purpose of this paper is to isolate factors predictive of event attendees, and assist tourism professionals such as members of host committees, in maximizing the number of out-of-town visitors to their region and optimizing tourism-related revenue when hosting college football bowl games. Design/methodology/approach: A total of 16 demand variables were entered into a hierarchical regression model, including the stature of the event and market-related variables, as well as team-related variables reflecting team or program stature and current season performance. Findings: A final model containing seven variables (bowl age, market population, conference affiliation, bowl game stature, season wins, home attendance, and distance traveled) predicted 77.5 percent of the variance in bowl game attendance. Research limitations/implications: This paper illustrates the use of predictive modeling for major sport event attendance with a unique sample and variables explored. Future research may build off the model to explore attendance for other populations or events. Practical implications: The applied nature of this study allows practitioners working in the tourism and event management field to incorporate a predictive model to best select participants in sporting events to maximize event attendees. Originality/value: Understanding the variables which predict event attendees in the context of college football bowl games provide useful data to practitioners. This study advances this area of research by treating event participants as unique observations (something which has not been done in prior studies), and looking at a new data set which incorporates the College Football Playoff era. … (more)
- Is Part Of:
- International journal of event and festival management. Volume 8:Issue 3(2017)
- Journal:
- International journal of event and festival management
- Issue:
- Volume 8:Issue 3(2017)
- Issue Display:
- Volume 8, Issue 3 (2017)
- Year:
- 2017
- Volume:
- 8
- Issue:
- 3
- Issue Sort Value:
- 2017-0008-0003-0000
- Page Start:
- 261
- Page End:
- 273
- Publication Date:
- 2017-10-09
- Subjects:
- Attendance -- Predictors -- Bowl games -- College football
Special events -- Management -- Periodicals
Festivals -- Management -- Periodicals
394.2068 - Journal URLs:
- http://www.emeraldinsight.com/ ↗
http://www.emeraldinsight.com/journals.htm?issn=1758-2954 ↗ - DOI:
- 10.1108/IJEFM-02-2017-0014 ↗
- Languages:
- English
- ISSNs:
- 1758-2954
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 4762.xml