ISSN: 1543-9518|Vol. 24

An Investigation of Environmental Motivation Factors Affecting Fans of Minor League Baseball

Submitted by: Dr. Soonhwan Lee, Dr. Cynthia Ryder, and Dr. Hee-Joon Shin

Although they are important to the sports spectator experience, there have been few studies of crowd control, concession services, parking, and the like. These environmental motivation factors as they affect fans of specified sports were the focus of this study, which took as its premise that fans of a given sport differ from fans of other given sports in terms of their motivation to follow the progress of a team. The neo-Marxist critique of spectator sports in capitalist society holds that sports spectators are more likely than nonspectators to be actively involved both in sports and in other cultural activities, including politics. Furthermore, many spectator sports actually tend to increase hostility and aggression in fans, rather than rendering fans apathetic or providing them the lucid equivalent of an Aristotelian catharsis (Guttmann, 1981). From ancient times to the present, individuals who have demonstrated allegiance or devotion to a particular sport, a particular team, and/or a particular player have been classified as sports fans.

According to previous studies (Hansen & Gauthier, 1989; Zhang, Pease, Hui, & Michaud, 1995), there are four major factors that affect spectators’ decisions about attending games. The attractiveness of the home team is a first and vital consideration. Individual players’ skill, league standing, breaking of prior records, team record, performance, and star players together affect fans’ attendance at games (Zhang et al.,1997). In Greenstein and Marcum’s study (1981) of Major League Baseball from 1946 to 1975, hypothesized reasons for attendance at games were teams’ win-loss records, pitching staff, and home-run batters. The study results showed that 25% of the variance in attendance was due to team performance. Jones (1984) found a number of significant factors related to hockey game attendance: a winning home team relative to the league, a qualified visiting team relative to the league, a game’s role in progress to season play-offs, superstar players, and preference as to team style (i.e., fighting vs. skating).

The attractiveness of the visiting team (its quality, the presence of star players, the strength of its rivalry with the home team, etc.) is a second major factor in fans’ decision making about game attendance (Zhang et al., 1997), and a third is economic variables including ticket pricing, promotions, and advertising (Hansen & Gauthier, 1989; Zhang et al., 1995). Promotions and income have been found to relate positively to game attendance, while ticket price, televising of games, available entertainment alternatives, and available sport-event alternatives have generally been found to relate negatively to game attendance (Baade & Tiehen, 1990; Bird, 1982; Siegfried & Eisenberg, 1980; Zhang et al., 1995). The fourth significant factor in fans’ decisions to attend games is audience preference, meaning, for example, game schedules, convenience, stadium quality, weather, and team history in a community. Weekend games and end-of-season games increase attendance, while afternoon games decrease attendance; showing no effect on attendance are double headers and home dates (Drever & MacDonald, 1981; Hansen & Gauthier, 1989; Hay & Thueson, 1986; Hill, Madura, & Zuber, 1982; Siegfried & Eisenberg, 1980). In addition, team attractiveness variables and audience preference variables have generally been found to relate positively to game attendance (Baade & Tiehen, 1990; Becker & Suls, 1983; Bird, 1982; Demmert, 1973; Godbey & Robinson, 1979; Hansen & Gauthier, 1989; Jones, 1984; Wall & Myers, 1989; Whitney, 1988; Zech, 1981).

Employing psychological and sociological theories concerning sports fans, Wakefield and Sloan (1995) sought to identify specific stadium factors affecting attendance. Their study argued that spectators who enjoyed spending time at a stadium should be relatively likely to want to spend additional time there, while conversely, spectators who had had an unpleasant experience at a stadium should be relatively unlikely to want to spend additional time there (and risk repetition of the unpleasant experience). Stadium qualities that have been considered environmental motivation factors include parking, cleanliness, comfort (or convenience), food service, and fan behavior, as outlined below.

Where stadium parking spaces are ample, spectators’ enjoyment of the stadium experience may be enhanced. Low-tolerance and task-oriented individuals may experience frustration if locating a parking space and/or walking in to the stadium require excessive amounts of time (Bitner, 1992; Snodgrass, Russell, & Ward, 1988). Spectators dissatisfied with parking conditions are relatively likely to leave a game early and express less satisfaction with their stadium experience.

The cleanliness of a stadium is primarily a function of stadium service quality. For instance, as a game progresses, restrooms and concession areas can fill with trash and spilled food and drink. Spectators confronting such refuse may feel unwilling to use the facilities and may become dissatisfied (Wakefield & Sloan, 1995).

Physical comfort in a stadium is, as Melnick (1993) found, another important factor. The width of aisles and hallways, the arrangement of seats, and the amount of room afforded for concessions and restroom facilities (which may also be thought of as the convenience of stadium facilities) should be sufficient to accommodate social interaction and facilitate enjoyment of the game. A spectator who feels uncomfortable because other spectators are too close or who feels hampered in exiting the stands and accessing restrooms or concessions may leave a game early and hesitate to attend further games (Wakefield & Sloan, 1995).

From a food service perspective, spectators are virtually held captive in the stadium for the three or more hours before and during a game (Wakefield & Sloan, 1995). By offering a variety of appetizing foods, a stadium facility enhances the spectator’s sports encounter.

Finally, fan behavior that is offensive to or abusive of fellow fans may, Bernstein noted (1991), prompt some spectators to leave a game early, especially when such behavior continues throughout a game. Both players’ behavior and the intensity of the two opponents’ rivalry affect fan behavior, as does alcohol consumption.  When stadium managers and personnel carefully monitor fan behavior, moving quickly to end unpleasant situations (in other words, when they practice crowd control), many negative experiences on the part of their patrons can be prevented (Wakefield & Sloan, 1995).

In addition, while each of the five preceding stadium factors would be expected to influence all spectators, those spectators who are most loyal to the home team should be relatively likely to stay throughout a game and to return to the stadium in future, due to their loyalty to the team. In other words, spectators who are loyal to the home team are likely to want to spend time at the stadium, and to return, primarily due to a desire to see the team play (Wakefield & Sloan, 1995).

]Methodology[

The purpose of this study was to examine environmental motivation factors and fan loyalty affecting Alabama residents whose communities had no Major League Baseball team, but did have a Class AA Minor League Baseball (MiLB) team. Specifically, the study sought to ascertain the types of environmental factors (parking, crowd control, stadium cleanliness, convenient facilities, and food and beverage service) affecting fans who are attending professional baseball games. Fan loyalty to specific baseball teams was also analyzed.

To obtain fan responses reflecting realistic evaluations of the related stadium and environmental factors, Wakefield and Sloan’s (1995) adapted Stadium Factors Measurement questionnaire was modified and used with an on-site distribution and collection strategy during each July 2001 home game of the Mobile (Alabama) BayBears. The BayBears are a Class AA MiLB team in the Southern League and play in Hank Aaron Stadium. The questionnaire was distributed in all 14 seating sections of the stadium. The researchers employed a stratified random sampling method with no discriminating factors except age.  Any qustionnaire collected by the researchers that had been completed by an individual under 18 years of age was excluded. Age discrimination was made subjectively in the effort to exclude children whose visit to the baseball stadium was believed to have been influenced by their parents. To promote fans’ participation in the survey, the BayBears organization provided to participants complimentary tickets to any upcoming regular season game in 2001.

To obtain reliability estimates and to establish the construct validity of the instrument, a pilot study was conducted before the data were collected from the final target population. Administration of the existing instrument also served as a field test further establishing its content and face validity. After the questionnaire items had been formulated, the survey was administered to 46 United States Sports Academy graduate students who had survey experience. Their remarks were sought concerning the appropriateness of the questionnaire, relevance of its content, clarity of its questions, ease of completion, and time required for completion. Based on the 46 students’ responses, a few minor changes were made to the instrument. In its final form, the instrument contained 20 items on four pages; average time to complete the survey was 3–4 min.

The 20 separate items comprising the survey covered both sociodemographic characteristics and environmental motivation factors. Participants’ sociodemographic information included demographics as well as behavioral variables. Demographic variables were gender, ethnicity, age, marital status, education level, employment status, income, and residence. Behavioral variables were game attendance rate, type of ticket purchased, reasons for following favorite teams’ progress, and preferred means of following favorite teams’ progress (e.g., at ball park, by television broadcast, by radio broadcast, etc.).

The modified Stadium Factors Measurement questionnaire was used with a 7-point Likert response scale ranging from 1 (strongly disagree) to 7 (strongly agree). The scale was developed and employed in order to indicate respondents’ characteristics related to environmental motivation factors and team loyalty.

]Results[

The data were collected from a stratified random sample of respondents (N = 282) at the Hank Aaron Stadium in Mobile, Alabama. The sample consisted of 155 males (n = 155, 55%) and 127 females (n = 112, 45%) (Table 1). To simplify the data analysis, the variable age was first recoded in seven categories: 18–20 years, 21–30 years, 31–40 years, 41–50 years, 51–60 years, 61–70 years, and 71 or more years. Respondents ranged in age from 18 to 74 years (M = 37.97, SD = 13.07), with 89% falling between age 21 and age 60. Those fans age 18–20 constituted 6% of the sample, while fans 61 years old or older constituted 5.3% of the sample.

The majority of respondents were Caucasian (n = 251, 89.0%), followed by African-American (n = 27, 9.6%), Hispanic (n = 2, 0.7%), Asian (n =1, 0.4%), and other (n = 1, 0.4%). The majority of respondents were married (n = 180, 63.8%). Some 30% (n = 82) had completed college, and approximately 29% (n = 81) had some college education (respondents who had earned a graduate degree or completed some graduate study comprised 17.3% of the sample, n = 49). About 71% (n = 201) of the respondents were employed; 10% were full-time homemakers. Most of the respondents (n = 236, 83.7%) were residents of Alabama, although 46 individuals (16.3%) were nonresidents. More than half the respondents had yearly incomes between $20,000 and $59,999, while another 13.5% earned between $60,000 and $79,999 annually; those earning more than $80,000 comprised about 13% of the sample. The remaining 20% (approximately) had incomes below $20,000 (Table 1).

Concerning game attendance rates, during the previous season, approximately 57.0% of the study respondents (n = 159) had attended BayBears games (including home and away games) less than 3 times per month. In addition, 18.1% of the sample (n = 51) were attending their first BayBears game. The third largest group of respondents reported attending games  3 to 5 times per month during the previous season. Most of the survey participants were attending the game using a single-game ticket (n = 183, 64.9%); 33 respondents had used a group ticket to attend the game (n = 33, 11.7%). The remaining 23% of respondents fell in 5 categories: full-season ticket (4.6%), half-season ticket (2.5%), package ticket (5.7%), guest of season ticket holder (6.4%), and other, for instance a complimentary ticket (4.3%).

More than 25.0% of the respondents (n = 78) said that they followed a favorite baseball team because they had grown up in the host city or state; another 26.0% said they followed a particular team because of its geographic location. Having family members who liked the team was a reason cited by 11.0% of the sample for following a particular team. The presence of a favorite player on the team was the reason given by 11.7% of the sample for following a given team. The majority of respondents (n = 222, 78.7%) reported following a favorite baseball team by watching television; other means employed to follow teams were going to ball parks (n = 24, 8.5%), magazine and/or newspaper coverage (n = 16, 5.7%), Internet coverage (n = 9, 3.2%), radio coverage (n = 3, 1.1%), and other, such as information gained from friends or family members (n = 8, 2.8%) (Table 2).

Analysis of the data on environmental motivation factors in respondents’ attendance at the baseball stadium (Table 3) showed that the most important such factor was cleanliness (M = 5.47, SD = 1.33). Next in importance was convenient facilities (M = 5.40, SD = 1.36), followed by parking (M = 5.33, SD = 1.52), and “fan control” (M = 5.27, SD = 1.36). In terms of team loyalty, the respondents demonstrated positive opinions about a favorite MiLB baseball team even when stadium-related environmental factors were unsatisfactory (M = 5.00, SD = 1.36).

In addition, a group of t tests was employed to look for significant differences in environmental motivation factors affecting Alabama residents and nonresidents (Table 4). Those survey participants who were Alabama residents had significantly higher “loyalty factor” scores (M = 5.15, SD = 1.45) than did nonresident participants (M = 4.26, SD = 1.98), at the .01 level. No other significant difference between residents and nonresidents was observed for the remaining environmental motivation factors considered in the study.

Multiple regression analysis was employed to examine the relationship of loyalty to environmental motivation factors (Table 5). The multiple regression analysis showed three environmental motivation factors to be significantly predictive of the loyalty variable: parking (at the .01 level), convenient facilities (at the .01 level), and food and beverage services (at the .05 level).  The regression model explained 38.9% of variance.

The results of correlation analyses indicated correlations among the environmental motivation factors (Table 6). Significant positive relationships were found among all environmental motivation items, as follows:

1. correlation between parking and stadium cleanliness, r  =  .697 (p < .01)

2. correlation between parking and convenient facilities, r = .567 (p < .01)

3. correlation between parking and food and beverage services, r  =  .489 (p < .01)

4. correlation between parking and fan control, r = .598 (p < .01)

5. correlation between parking and team loyalty, r = .499 (p < .01)

6. correlation between stadium cleanliness and convenient facilities, r = .721 (p < .01)

7. correlation between stadium cleanliness and food and beverage services, r = .532 (p < .01)

8. correlation between stadium cleanliness and fan control, r = .673 (p < .01)

9. correlation between stadium cleanliness and team loyalty, r = .459 (p < .01)

10. correlation between convenient facilities and food and beverage services, r = .604 (p < .01)

11. correlation between convenient facilities and fan control, r = .745 (p < .01)

12. correlation between convenient facilities and team loyalty, r = .572 (p < .01)

Furthermore, significant positive relationships were found between food and beverage services and fan control (r  =  .710, p < .01), between food and beverage services and team loyalty (r = .482, p < .01), and between fan control and team loyalty (r = .531, p < .01). All correlations were significant at the .01 level.

Finally, one-way multivariate analyses of variance (MANOVA) were performed to compare the mean vector scores for the six environmental motivation items with respect to the behavioral variables. The structural coefficients were used to define a function based on an eigenvalue equal to .30, while the standardized coefficients were used to test redundancy of environmental motivation items (Pease & Zhang, 2001). The results of MANOVA showed significant effects on environmental motivation items both for attendance rate, Multivariate F(30, 1086) = .807, p = .001, and for ticket type, Multivariate F(36, 1188) = .811, p =.013. On the other hand, remaining MANOVA results indicated no significant effect for reason for following favorite teams, Multivariate F(42, 1265) = .868, p = .619, and no significant effect for preferred means of following favorite teams, Multivariate F(30, 1086) = .879, p = .224.

Specifically, respondents’ mean vector scores differed significantly,  at the .01 level, based on attendance rate for the preceding baseball season. The loyalty item was the main contributing factor: Respondents who had attended every home game of the preceding season had a higher mean. In addition, their mean vector scores differed significantly, at the .05 level, based on type of ticket used for game attendance. Two factors, parking and loyalty, were the main contributing factors. Respondents using single-game tickets had higher mean scores for parking and stadium cleanliness than did respondents using other kinds of tickets. Respondents using package tickets scored higher than other respondents on items pertaining to convenient facilities and fan control. Respondents who were guests of season ticket holders scored higher than other respondents on items pertaining to food and beverage services and team loyalty. Mean vector scores did not differ significantly, however, in terms of respondents’ reasons for following or preferred means of following a favorite team (Table 7).

Discussion and Recommendations

Mahony, Madrigal, and Howard (2000) have argued that a variety of marketing strategies should be applied with different types of sports consumers they refer to as “high loyal fans,” “spurious loyal fans,” “latent loyal fans,” and “low loyal fans.” Varied strategies are necessary in light of the different consumers’ differing motivations and/or reasons for attending professional sports events and making commitments to professional sports teams. The present study focused on sociodemographics and environmental motivation factors, knowledge of which may affect professional baseball franchises’ marketing strategies and frameworks. While the present study focused on residents of a state that hosts no major-league professional teams, its results may inform the development of efficient business concepts for minor-league professional teams.

The study respondents’ views on environmental motivation items suggest a number of ways to maintain fan satisfaction, perhaps thereby increasing attendance. The three most important concern stadium cleanliness, parking, and convenient facilities; relative satisfaction with these factors affects the likelihood that a spectator will return to the stadium in the future. Wakefield and Sloan’s similar results (1995) led them to advise MiLB administrators to emphasize efforts to ensure that parking, cleanliness, convenience, food and beverage services, and crowd control satisfy the baseball fans who attend games. The present study found, in particular, a correlation between team loyalty and the other environmental motivation factors, and loyalty of course plays one of the biggest roles in determining fans’ willingness to attend games. For this reason, administrators of MiLB teams should use a well-prepared stadium environment to appeal to each of Mahony, Madrigal, and Howard’s types of sports consumer.

Recommendations for future studies are, first, an extension of the scaled motivation items to include psychological and sociological motivation, adding for example promotional events, frequency of media exposure, family effects, and gambling factors. Second, the findings of this study suggest a link to be explored between baseball fans’ motivation to attend games and judgments about satisfaction with game attendance.

 

Table 1 Sociodemographic Characteristics, Frequency and Percentage
Sociodemographic Characteristic
Frequency
Percentage
Age, in Years (N = 282)
18–20
17
6.0
21–30
19
28.0
31–40
84
29.8
41–50
47
16.7
51–60
40
14.2
61–70
11
3.9
71 or over
4
1.4
Gender (N = 282)
Male
155
55.0
Female
127
45.0
 

Ethnicity (N = 282)

 
Caucasian 251 89.0
African-American 27 9.6
Asian 1 .4
Hispanic 2 .7
Other 1 .4
 

Marital Status (N = 282)

 
Never married 65 23.0
Married 180 63.8
Divorced 26 9.2
Separated 2 .7
Widowed 5 1.8
Other 4 1.4
 

Education Level (N = 282)
Lower than high school 9 3.2
Graduated from high school 61 21.6
Some college 81 28.7
Completed college 82 29.1
Some graduate study 19 6.7
Earned graduate degree 30 10.6
 

Employment Status (N = 282)

 
Employed 201 71.3
Unemployed 9 3.2
Retired 23 8.2
Full-time homemaker 28 9.9
Student 17 6.0
Other 4 1.4
 

Residential Status (N = 282)

 
Alabama resident 236 83.7
Not a resident of Alabama 46 16.3
 

Annual Income Level (N = 266)

 
Below $20,000 55 20.7
$20,000–$39,999 65 24.4
$40,000–$59,999 76 28.6
$60,000–$79,999 36 13.5
$80,000–$99,999 16 6.0
Above $100,000 18 6.8

Table 2 Fan Behavior, Frequency and Percentage
Behavior Variable
Frequency Percentage
 

Game Attendance Rate
First time attending a game 51 18.1
Less than 3 times per month during preceding season 159 56.4
3–5 times per month during preceding season 44 15.6
6–10 times per month during preceding season 11 3.9
Every home game during preceding season 14 5.0
Every BayBears game during preceding season 3 1.1
 

Ticket Type

 
Full-season ticket 13 4.6
Half-season ticket 7 2.5
Package ticket 16 5.7
Single-game ticket 183 64.9
Group ticket 33 11.7
Guest of season ticket holder 18 6.4
Other 12 4.3
 

Reasons for Following Favorite Teams’ Progress
Because I grew up in that state and/or city 78 27.7
Because I frequently visited the team’s ballpark with my parents 23 8.2
Because of the team’s location near my current hometown 74 26.2
Because my family (spouse, parents, children) likes the team 31 11.0
Because I remember the team treated me well as a customer 2 .7
Because the team has my favorite players 33 11.7
Because I have a membership of the team 1 .4
Other reasons 40 14.2
 

Preferred Means of Following Favorite Teams’ Progress
At ball park
By television broadcast
By radio broadcast By Internet
Magazine and/or newspaper coverage
Other

Table 3 Relative Importance of Environmental Motivation Variables
Variable Mean Standard Deviation
I like to come back to the Hank Aaron Stadium to watch BayBears games because convenient parking spaces are easily available. 5.33 1.52
I like to come back to the Hank Aaron Stadium to watch BayBears games because I like the cleanliness of the stadium. 5.47 1.33
I like to come back to the Hank Aaron Stadium to watch BayBears games because there are enough and convenient facilities, including hallways, space and arrangements of seats, concessions, restrooms, etc. 5.40 1.36
I like to come back to the Hank Aaron Stadium to watch BayBears games because the food and beverage services are very good. 4.91 1.42
I like to come back to the Hank Aaron Stadium to watch BayBears games because of good stadium fan control. 5.27 1.36
Even if the above question items (E1 through E5) are not satisfied, I like to come back to the Hank Aaron Stadium to watch BayBears games because I am loyal to the BayBears. 5.00 1.58

Table 4 Importance of Environmental Motivation Factors by Alabama Residence vs. Nonresidence
Variable Alabama Resident Mean Number of Respondents Standard Deviation t p
Parking Yes
No		 5.39
5.02		 236
46		 1.51
1.51		 1.54 .125
Cleanliness Yes
No		 5.50
5.32		 236
46		 1.32
1.38		 0.81 .420
Convenient facilities Yes
No		 5.44
5.19		 236
46		 1.33
1.48		 1.14 .256
Food / beverage services Yes
No		 4.93
4.80		 236
46		 1.37
1.66		 0.51 .616
Fan control Yes
No		 5.27
5.23		 236
46		 1.35
1.44		 0.18 .855
Team loyalty Yes
No		 5.15
4.26		 236
46		 1.45
1.98		 2.90** .005
Note: Yes = residents of Alabama, No = nonresidents of Alabama
** Indicates significance at the .01 level

Table 5 Multiple Regression Analysis Examining Relationship of Team Loyalty to Environmental Motivation
Variable
B
SE B
B
t
p
Constant .730 .348 2.097* .037
Parking .261 .071 .250 3.662** .000
Cleanliness -.124 .098 -.104 -1.255 .210
Convenient facilities .453 .092 .388 4.900** .000
Food .178 .074 .160 2.424* .016
Fan control .045 .100 .039 .447 .655
R = .623; R2 = .389; F = 35.099** Dependent variable: team loyalty
* Indicates significance at the .05 level
** Indicates significance at the .01 level
Dependent variable: team loyalty

Table 6 Correlations Among Environmental Motivation Items
  Parking Cleanliness Convenient Facilities Food/Beverage Services Fan Control Team Loyalty
Parking 1.00
Cleanliness .697** 1.00
Facility .567** .721** 1.00
Food .489** .532** .604** 1.00
Fan control .598** .673** .745** .710** 1.00
Loyalty .499** .459** .572** .482** .531** 1.00

Spearman rho, ** Indicates significance at the .01 level

Table 7 Multivariate Analysis of Variance for Environmental Motivation Items with Respect to Behavioral Variables
Behavior Variable
Parking
Clean
  

Facility

  

Food
Fan Control
Loyalty
Attendance Rate in Preceding Season:
Wilks’s (30, 1086) = .807,
p = .001
  Mean

(Standard Deviation)

  Mean(Standard Deviation)  Mean(Standard Deviation)  Mean(Standard Deviation)  Mean(Standard Deviation)  Mean(Standard Deviation)
Never 5.06
(1.27)		 5.20
(1.23)		 5.21
(1.37)		 5.02
(1.33)		 5.16
(1.35)		 4.47
(1.56)
Less than 3 times per month
5.42
(1.45)
5.49
(1.34)
5.36
(1.33)
4.92
(1.34)
5.21
(1.32)
4.90
(1.51)
3–5 times per month
5.32
(1.76)
5.61
(1.35)
5.59
(1.35)
4.82
(1.50)
5.41
(1.33)
5.36
(1.49)
6–10 times per month
5.27
(1.79)
5.82
(1.17)
5.63
(1.29)
4.27
(2.37)
5.18
(1.89)
6.09
(1.64)
Every home game
5.50
(2.17)
5.86
(1.61)
6.00
(1.66)
5.21
(1.72)
5.86
(1.66)
6.28
(1.73)
Every BayBears game
5.33
(1.53)
4.67
(1.53)
4.67
(1.15)
5.00
(1.00)
6.00
(1.00)
4.67
(1.15)
Ticket Type:
Wilks’s (36, 1188) = .811,
p = .013
Full-season ticket
5.00
(1.73)
5.31
(1.70)
5.23
(1.64)
4.85
(1.07)
5.08
(1.66)
5.46
(1.76)
Half-season ticket
5.43
(1.13)
5.43
(1.40)
5.14
(.90)
4.71
(.76)
5.00
(.00)
4.86
(1.86)
Package ticket
5.44
(1.96)
5.87
(1.45)
5.56
(1.71)
4.62
(2.06)
5.62
(1.78)
5.44
(1.90)
Single-game ticket
5.55
(1.38)
5.60
(1.21)
5.51
(1.25)
4.98
(1.42)
5.41
(1.28)
5.11
(1.53)
Group ticket
4.64
(1.76)
5.00
(1.66)
4.85
(1.72)
4.57
(1.58)
4.57
(1.52)
4.18
(1.45)
Guest of season ticket holder
4.94
(1.70)
5.00
(1.53)
5.55
(1.46)
5.17
(1.29)
5.17
(1.54)
5.61
(1.19)
Other
4.75
(1.42)
5.17
(.83)
5.17
(.94)
5.08
(.67)
5.08
(.79)
3.83
(1.58)
Reasons for Following Favorite Teams’ Progress:
Wilks’s (42, 1265) = .868,
p = .619
Because I grew up in that state and/or city

 
5.49
(1.37)
5.46
(1.24)
5.37
(1.33)
4.99
(1.49)
5.32
(1.39)
5.00
(1.59)
Because I frequently visited the team’s ballpark with my parents
6.09
(1.00)
5.78
(.90)
5.22
(1.28)
4.91
(1.00)
5.30
(1.02)
5.17
(1.37)
Because of the team’s location near my current hometown
5.16
(1.53)
5.43
(1.43)
5.32
(1.28)
4.67
(1.43)
5.08
(1.33)
4.85
(1.35)
Because my family (spouse, parents, children) likes the team
5.32
(1.64)
5.52
(1.52)
5.68
(1.42)
5.00
(1.37)
5.45
(1.50)
5.32
(1.74)
Because I remember the team treated me well as a customer
6.00
(1.41)
6.00
(1.41)
6.00
(1.41)
5.50
(2.12)

6.00
(1.41)
6.00
(1.41)
Because the team has my favorite players
5.21
(1.93)
5.45
(1.56)
5.51
(1.62)
4.79
(1.71)
5.27
(1.58)
5.30
(1.69)
Because I have a membership of the team
7.00
(.00)
6.00
(.00)
6.00
(.00)
6.00
(.00)
7.00
(.00)
6.00
(.00)
Other reasons 4.97
(1.46)		 5.32
(1.23)		 5.37
(1.41)		 5.20
(1.28)		 5.30
(1.32)		 4.65
(1.87)
Preferred Means of Following Favorite Teams’ Progress:

Wilks’s (30, 1086) = .879,
p = .224
At ball park 5.33
(1.61)		 5.67
(1.20)		 5.50
(1.32)		 4.71
(1.71)		 5.21
(1.47)		 5.17
(1.43)
By television broadcast 5.35
(1.55)		 5.47
(1.32)		 5.41
(1.34)		 4.92
(1.40)		 5.30
(1.34)		 5.06
(1.55)
By radio broadcast 4.67
(.58)		 4.33
(1.15)		 4.33
(2.08)		 4.33
(.58)		 4.00
(2.64)		 5.33
(1.53)
By Internet 5.78
(.97)		 6.11
(.78)		 6.00
(.71)		 5.67
(1.00)		 5.67
(1.12)		 4.44
(2.01)
Magazine and/or newspaper coverage 5.44
(1.09)		 5.44
(1.59)		 5.31
(1.54)		 5.06
(1.48)		 5.25
(1.18)		 5.25
(1.69)
Other 4.50
(2.00)		 4.62
(1.77)		 4.75
(1.83)		 4.37
(1.68)		 4.75
(1.98)		 3.00
(1.31)

 

]References[

Baade, R. A., & Tiehen, L. J. (1990). An analysis of major league baseball attendance, 1969–1987. Journal of Sport and Social Issues, 14(1), 14–31.

Becker, M. A., & Suls, J. (1983). Take me out to the ball game: The effect of objective, social, and temporal performance information on attendance at major league baseball games. Journal of Sport Psychology, 5(3), 302–313.

Bernstein, S. (1991). The sorry state of “sports heroes”: Antisocial behavior of well-paid sports figures. Advertising Age, 62(15), 25.

Bird, P. J. (1982). The demand for league football. Applied Economics, 14(6), 637–649.

Bitner, M. J. (1992). Servicescapes: The impact of physical surroundings on customers and employees. Journal of Marketing, 56(2), 57–71.

Demmert, H. G. (1973). The economics of professional team sport. Lexington, MA: Heath.

Drever, P., & MacDonald, J. (1981). Attendance at South Australian football games. International Review of Sport Sociology, 16(2), 103.

Godbey, G., & Robinson, J. (1979). The American sports fan: “Spectatoritis” revisited. Review of Sport and Leisure, 4(1), 1–11.

Greenstein, T. N., & Marcum, J. P. (1981). Factors affecting attendance of major league baseball: Team performance. Review of Sport and Leisure, 6(2), 21.

Guttmann, A. (1981). Sports spectators from antiquity to the Renaissance. Journal of Sport History, 8(2), 5–27.

Hansen, H., & Gauthier, R. (1989). Factors affecting attendance at professional sport events. Journal of Sport Management, 3(1), 15–32.

Hay, R. D., & Thueson, N. C. (1986, October). High school attendance and related factors. Paper presented at the conference of the Canadian Congress on Leisure Research, Edmonton, Alberta, Canada.

Hill, J. R., Madura, J., & Zuber, R. A. (1982). The short run demand for major league baseball. Atlantic Economic Journal, 10(2), 31.

Jones, J. C. H. (1984). Winners, losers and hosers: Demand and survival in the National Hockey League. Atlantic Economic Journal, 12(3), 54.

Mahony, D. F., Madrigal, R., & Howard, D. (2000). Using the Psychological Commitment to Team (PCT) Scale to segment sport consumers based on loyalty. Sport Marketing Quarterly, 9(1), 15–25.

Melnick, M. J. (1993). Searching for sociability in the stands: A theory of sports spectating. Journal of Sport Management, 7(1), 44–60.

Pease, D. G., & Zhang, J. J. (2001). Socio-motivational factors affecting spectator attendance at professional basketball games. International Journal of Sport Management, 2(1), 31–59.

Siegfried, J. J., & Eisenberg, J. D. (1980). The demand for minor league baseball. Atlantic Economic Journal, 8(1), 59–71.

Snodgrass, J., Russell, J. A., & Ward, L. M. (1988). Planning, mood and place-liking. Journal of Environmental Psychology, 8(3), 209–222.

Wakefield, K. L., & Sloan, H. J. (1995). The effects of team loyalty and selected stadium factors on spectator attendance. Journal of Sport Management, 9(2), 153–172.

Wall, G. V., & Myers, K. (1989). Factors influencing attendance: Toronto Blue Jays games. Sport Place International: An International Magazine of Sports, 3(1 & 2), 29–33.

Whitney, J. D. (1988). Winning games versus winning championships: The economics of fan interest and team performance. Economic Inquiry, 26(4), 703–724.

Zech, C. F. (1981). An empirical estimation of a production function: The case of major league baseball. American Economist, 25(2), 19–23.

Zhang, J. J., Pease, D. G., Hui, S. C., & Michaud, T. J. (1995). Variables affecting the spectator decision to attend NBA games. Sport Marketing Quarterly, 4(4), 29–39.

Zhang, J. J., Pease, D. G., Smith, D. W., Lee, J. T., Lam, E. T., & Jambor, E. A. (1997, Summer). Factors affecting the decision making of spectators to attend Minor League Hockey games. International Sports Journal, 1(1), 39–53.

]Author Note[

Soonhwan Lee ; Cynthia Ryder, United States Sports Academy; Hee-Joon Shin

 

2013-11-26T20:51:54-06:00February 22nd, 2008|Contemporary Sports Issues, Sports Facilities, Sports Management|Comments Off on An Investigation of Environmental Motivation Factors Affecting Fans of Minor League Baseball
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Student-Athletes’ Perceptions About Abuse by NCAA Division II Tennis Coaches

Submitted by: Vicky-Lynn Martin

Abstract

Male and female NCAA Division II tennis players (southern region) were surveyed about their encounters with coaches’ abusive behavior, to see whether perceptions differed significantly by gender. The researcher discusses whether athletic departments should develop policies and procedures to educate all persons affiliated with them about abusive behavior and whether they should furthermore prosecute coaches who sexually harass or emotionally abuse student-athletes.

The survey instrument was adapted from instruments used in three earlier studies. It was used by the players to rank 20 perceived abusive behaviors. The survey was developed from a review of literature, an expert panel, and a pilot study using Cronbach’s alpha coefficient to gauge validity and internal consistency reliability. The survey was administered on-site to 140 student-athletes participating in NCAA-II’s southern region tennis tournament. All 140 student-athletes returned a completed survey to the researcher. A total of 134 surveys had been completed correctly and were utilized in the study (a 95.7% response rate).

Statistical analysis includes descriptive statistics analyzing ranking of severity of behaviors, along with factor analysis identifying behaviors that led to abusive situations. Frequencies, percentages, means, mean rankings, and standard deviations were the descriptive statistics utilized; the method of factor extraction used was the principal component method, with varimax rotation. Factor analysis investigated areas within perceived abusive behaviors, seeking clusters demonstrating a good degree of correlation.

Student-Athletes’ Perceptions About Abuse by NCAA Division II Tennis Coaches

The question of sexual harassment in university settings has received very little attention over the years. This research study was designed to provide insight into sexual harassment and emotional abuse in American university athletic programs, through an examination of student-athletes’ perceptions of a number of ambiguous behaviors. The study furthermore sought an understanding of the meanings student-athletes assign to sexually harassing behaviors exhibited by their coaches and was meant to contribute to the literature on sexual harassment. In addition, the study sought student-athletes’ views on the atmosphere within university athletic programs.

American athletic departments belong to the community mainstream, but they have developed their own relationships to such an extent that they function independently of the educational community. This fact does not diminish an athletic department’s legal and moral obligation to provide all student-athletes with an environment free from sexual harassment, nor does it take from student-athletes or athletic department employees the right to use community resources to resolve sexual harassment issues.

Subjects and Instrument

Male and female student-athletes from 14 NCAA Division II (southern region) tennis programs were the randomly selected study participants, numbering 140 in all, each team having roughly 10 players. All tennis players were given the opportunity to participate or not participate in the study; participation was strictly voluntary. The athletes who participated in the study were playing in the regional tournament for their university.

On-site face-to-face surveys were used to collect data from participants. The survey instrument, based on three earlier instruments, was adapted specifically for the male and the female student-athletes. They were asked to express their perceptions about various coach behaviors, using a 5-point Likert scale. Responses ranged from 1 (extremely inappropriate) to 5 (extremely appropriate). Preparation of the instrument had included testing by a panel of experts, who reviewed the questions and established the validity of the instrument. The procedure for reliability testing included Cronbach’s alpha reliability coefficient, confirming the internal consistency and reliability of the scores reported for the pilot study respondents on survey items covering coaches’ perceived competency and harassing behavior. Reliability was interpreted as a correlation coefficient utilizing Cronbach’s scale.

Statistical Analysis

The research design pinpointing the student-athletes’ perceptions comprised (a) order of the ranking of perceived coaching behaviors, (b) results of factor analysis determining the severity of perceived behaviors, and (c) investigation of existing literature. Descriptive statistics (frequencies, percentages, means, mean rankings, standard deviations) were used in analyzing rankings of perceived coaching behaviors. The factor analysis employed was the principal component method, with varimax rotation; it investigated the integration of two or more independent variables on a single dependent variable. Areas within the coaching behavior selection were identified for inclusion within clusters demonstrating a high degree of correlation. Factor analysis furthermore identified underlying variables or factors explaining the pattern of correlations within a set of observed variables and was used in data reduction to identify a small number of factors explaining the variance observed in a larger number of manifest variables. Examination of the scree plots supported the extraction of four factors with an eigenvalue greater than 1.0. Cluster titles were assigned to each factor.

Results

Demographic information obtained from the respondents included gender (of player and head coach), race, age, academic classification, scholarship status, and position currently played on team. Demographic data was anticipated to affect perceptions concerning the severity of coaches’ behaviors, but this paper concerns itself with only one of the demographic variables, gender. Table 1 and Table 2 illustrate the total mean ranges, by gender, for the perceived coaching behaviors. Mean values were obtained for each of the 20 coaching behavior items. Among the male respondents, mean values ranged from an inappropriate high of 4.77 (for Item 20, “sexual favors could result in increased scholarship money or rank on the team”) to an appropriate low of 2.53 (for Item 6, “closed door meeting with a player”). Among female respondents, mean values ranged from an inappropriate high of 4.85 (for Item 20, “sexual favors could result in increased scholarship money or rank on the team”) to an appropriate low of 2.36 (for Item 13, “congratulatory hug after the completion of a match”).

Table 1

Male Respondents: Mean Range and Frequency for Survey Items

Mean Range Survey Item Number Frequency
> 4.500 9, 11, 17, 19, 20
5
4.000 – 4.499 16, 18
2
3.500 – 3.999 1, 2, 7, 12, 15
5
3.000 – 3.499 4, 5, 8, 10, 14
5
2.500 – 2.999 3, 6, 13
3
2.000 – 2.499 N/A
< 1.999 N/A
Total
20

Table 2

Female Respondents: Mean Range and Frequency for Survey Items

Mean Range Survey Item Number Frequency
> 4.500 9, 11, 17, 19, 20
5
4.000 – 4.499 1, 2, 15, 16, 18
5
3.500 – 3.999 4, 5, 12, 14
4
3.000 – 3.499 3, 7, 8
3
2.500 – 2.999 6, 10
2
2.000 – 2.499 13
1
< 1.999 N/A
Total
20

The top five perceived coaching behaviors considered most inappropriate for males (listed in rank order) are (a) implied sexual favors could result in increased scholarship money or rank on the team (Item 20), (b) coach’s use of pet names (Item 9), (c) coach solicits player in a personal manner (Item 17), (d) coach initiates contact with player by allowing player to sit on lap (Item 19), and (e) coach puts hands on player’s buttocks while giving tennis instruction (Item 11).

The top five perceived coaching behaviors considered most appropriate for males (listed in rank order) are (a) coach closes the door when meeting with a player (Item 6), (b) coach invites a player out to dinner in a public setting (Item 3), (c) coach gives congratulatory hug to a player after the match (Item 13), (d) coach compliments player on appearance (Item 8), and (e) coach touches player’s arm when giving tennis instruction (Item 10).

Factor analysis was employed to determine the perceived abusive behaviors and specific factors necessary for the implementation of policies and procedures. The factor extraction method comprised use of principal axis factoring and varimax rotation with Kaiser normalization, in order to analyze interrelationships and pattern correlations between observed variables and the perceived behavior items. This resulted in a four-factor solution. Examining the scree plots supported extracting the four factors (eigenvalues greater than 1.0).

The rotated four-factor solution accounted for 66.05% of the variance in respondents’ perceptions about coaches’ ambiguous behaviors. Cluster titles were assigned to each factor so that they could be grouped by degree of severity. To determine factor reliability, the internal consistency of each factor was assessed by computing Cronbach’s alpha coefficient. All four subscales indicated a good level of internal consistency, with coefficients greater than .85.

Four categories with 66% of the total variation for the perceived coaching behaviors were identified through factor analysis. Cluster titles were assigned to each of the four group items.

Table 3

Categorization of Behaviors

Category 1
Item 4
Item 1
Item 2
Item 5
Item 3		 Invitations
Invitation to coach’s house for tactical discussion
Invitation to lunch
Invitation for a drink after training session
Invitation for coffee in a non-public setting
Invitation to dinner in a public setting

 
31%
Category 2
Item 13
Item 10
Item 7
Item 14
Item 11		 Invasion of personal space
Coach gives congratulatory hug
Coach touches arm while giving tennis instruction
Coach sits or stands close when talking with a player
Coach gives a playful shoulder massage or backrub
Coach places hands on player’s buttocks

 
16%
Category 3
Item 8
Item 9
Item 17		 Personal compliments
Coach compliments appearance
Coach uses pet names
Coach solicits in a personal manner

 
10%
Category 4
Item 18
Item 6
Item 19
Item 20		 Inappropriate contact
Coach instigates frequent nightly telephone contact
Coach closes the door when meeting with an athlete
Coach initiates contact of player sitting on his/her lap
Coach implies that sexual favors could result in promotion

 
9%
Miscellaneous
Item 16
Item 15
Item 12		 Did not load
Coach attempts to rape a player
Coach attempts aggressive physical contact
Coach uses profanity when giving instruction

Conclusion

The study findings did not align with prior research results or with the researcher’s expectations. The surveyed university tennis players surprisingly rated the 20 behaviors as appropriate. Explanations for why athletes in this study perceived certain behaviors as appropriate could include the power coaches have over athletes to make decisions for them, or perhaps naiveté among athletes about the abuse potential in the coach-athlete relationship: athletes’ innocence regarding a coach’s power and presence in their lives. Moreover, coaches may be unaware of their power over athletes through implications of their language, jokes, and even their physical presence.

Earlier studies provided evidence of an alarming rise in sexual harassment and emotional abuse in universities and colleges. From these studies, it seems that student-athletes’ perceptions about possibly abusive coach behavior differ with the gender of the athlete, the gender and intentions of the coach, the severity and frequency of inappropriate behavior, judgment of the involvement of the victim, the status of the supervisory role, and personal experience.

Few American athletic departments work to educate either coaches or students about sexual harrassment or emotional abuse, although information about the phenomena can prevent misunderstanding and conflict between coaches and athletes. It is thus not surprising that many of the athletes surveyed for the present study seemed to miss the questionable implications of a coach’s inviting a player for drinks and even the extreme inappropriateness of a coach’s aggressively pursuing physical contact or even attempting to rape a player. Sexual harassment in the university community deserves our attention. To protect student-athletes specifically, it is essential that athletic departments implement antiharrassment and antiabuse policies and procedures. As the body of research on sexual harassment in the sport domain grows, there is hope that these can be instituted nationwide. Then, they must be evaluated and monitored by individuals outside the university setting.

Sexual harassment undermines the mission of sports, which is to improve the physical, mental, and emotional well-being of all participants. Harassment has debilitating consequences for its victims, and it is also potentially damaging to institutions. Failing to acknowledge that athletic departments are home to both harassment and emotional abuse puts universities and colleges in line for more and more lawsuits, which will be extremely costly and harmful to an institution’s reputation.

References

Amorose, J., & Horn, T. S. (2001). Pre- to post-season in the intrinsic motivation of first year college athletes: Relationships with coaching behavior and scholarship status. Journal of Applied Sport Psychology, 13(5), 355–373.

Barak, A., Fisher, W., & Houston, S. (1992). Individual difference correlates of the experience of sexual harassment among female university students. Journal of Applied Social Psychology, 22, 17–37.

Brackenridge, C. (1987, Summer). Ethical problems in women’s sport. In National Coaching Foundation, Coaching Focus (pp. 5–7). Leeds, West Yorkshire, United Kingdom: Author.

Brackenridge, C. (2001). Spoilsports: Understanding and preventing sexual exploitation in sport. New York: Routledge.

Dominowski, W. (2002). When parents take their child’s sport participation beyond reason. Journal of Sports Psychology, 3(3), 1–5.

Finn, R. (1999, March 7). Growth in women’s sports stirs harassment issue. The New York Times. Retrieved from http://www.nytimes.com/library/sports/other/030799women-harass.html

Lambrecht, K. W. (1986). An analysis of the competencies of athletic club managers. Unpublished doctoral dissertation, Oregon State University.

Lenskyj, H. (1992). Unsafe at home base: Women’s experiences of sexual harassment in university sport and physical education. Women in Sport and Physical Activity Journal, 1(1), 19–34.

Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.

Volkwein, K., Frauke, I., Sherwood, D., & Livezey, A. (1997). Sexual harassment in sport: Perceptions and experiences of American female student-athletes. International Review for the Sociology of Sport, 23(3), 283–295.

Zikmund, W. G. (1994). Exploring marketing research (5th ed.). Fort Worth, TX: Dryden.

 

Author Note

Vicky-Lynn Martin, D.S.M.

2016-04-01T09:56:24-05:00February 21st, 2008|Contemporary Sports Issues, Sports Coaching, Sports Management, Sports Studies and Sports Psychology|Comments Off on Student-Athletes’ Perceptions About Abuse by NCAA Division II Tennis Coaches
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Gender Differential in the Goal Setting, Motivation, Perceived Ability, and Confidence Sources of Basketball Players

Submitted by: Dongfang Chie-der, Steve Chen, Chou Hung-yu, and Chi Li-Kang

]Abstract[

Gender differences in goal setting, perceived motivational climate, perceived athletic ability, and perceived sources of confidence in athletic ability were evaluated for a male group and female group of high school basketball players (N = 174). Significant findings included higher scores among males for (a) perceived ego climate and (b) perfection of skills and physical performance as sources of confidence. Significant findings from simple correlation analyses included a positive relationship of both sexes’ task orientation, perceived task climate, and perceived ability, to 8 confidence sources. Male players’ ego orientation was positively related to demonstration of ability, physical performance, and social support. Males’ perceived ego climate and females’ ego orientation were both positively related to 7 of the 8 sources of confidence. Females’ ego orientation, males’ perceived ego climate, and the 8 sources were positively related to confidence perceived prior to competition. Stepwise regression analyses showed males’ task orientation and perceived ability to predict confidence prior to competition; for females, perceived ability and perceived task climate were effective predictors. Respondents derived better confidence in a task-oriented environment, so the researchers advise coaches to create task-oriented practice environments to enhance confidence of male and female players.

]Gender Differential in the Goal Setting, Motivation, Perceived Ability, and Confidence Sources of Basketball Players[

Self-confidence and sport-related confidence have been viewed as crucial factors influencing athletic performance. A number of studies show athletes who are strongly confident in terms of sport concentrate better, have healthier emotions, and demonstrate better game strategies, control of tempos, and performance than less confident athletes (Chi, 1996; Gould, 1981; Mahoney, Gabriel, & Perkin, 1987). The relationship between sport-related confidence and athletic performance should thus be of vital interest to sport psychologists. But sport-related confidence can be an inconsistent and transitory variable. Its instability over time is based largely on where players find their confidence, the confidence source. Research may shed light on how a particular source influences level of confidence, cognition, emotion, and behavior (Vealey, 1986). A careful examination of confidence sources offers to help explain the interaction of social background, organizational culture, and athletes’ individual characteristics.

Competitive sport is an environment for the pursuit of excellence in athletic performance (Duda, 1987). Sport psychology researchers have explored how players develop confidence in their athletic performance. Out of the social-cognitive perspective, achievement goal theory has gradually become popular as a model for testing  (Ames & Archer, 1988; Elliott & Dweck, 1988; Nicholls, 1984, 1989; Mills, 1997; Huang & Chi, 1994).

Prior research on achievement goal theory has shown that a task-oriented climate enhances motivation and confidence (Duda, 1992). There is a relationship between goal orientation and sport-related confidence. Athletes’ task orientation correlates positively to their sport confidence; athletes tending to emphasize acquisition of skill (in other words, perfection) along with the learning process and competitive process tend to have greater sport-related confidence. Shane’s study (2000) of 620 male and female high school or college athletes explored the relationship between goal orientation and sport-related confidence. Its findings showed significant gender differences in task orientation, ego orientation, and several confidence-source factors (skill perfection, demonstration of ability, and physiological/psychological preparation). The findings furthermore showed differences in the perceived sources of sport confidence for high school versus college athletes (both genders).

Studies like Shane’s might lead us to conclude that athletes’ emotions, levels of cognition, and behaviors affect their sport confidence. There is ample research indicating that task-oriented individuals and individuals operating in task-oriented climates have relatively positive emotions as well as a relatively high self-perception and self-perceived ability. Athletes perhaps more than nonathletes self-perceive their abilities, which would make strong impact on their sport confidence (Mills, 1997; Huang & Chi, 1994). Sport confidence research focusing on organizational culture (e.g., perceived motivational climate)  and other environmental factors, however, is rare. In Taiwan, even within sport psychology sport confidence is little used as a research construct.

But what are the variables in athletes’ confidence prior to competing? Where does sport confidence felt by male and female basketball players come from? The present study sought those sources of sport confidence, working from motivational theories and their constructs. The primary focus was relationships among high school basketball players’ goal orientation, perceived motivational climate, perceived ability, sport confidence sources, and pre-competition sport confidence levels, as well as how those relationships differed with the gender of the players.

]Method[

Subjects

The study participants were 174 male (n = 87) and female (n = 87) basketball players who had played in the 2003 HBL [Taiwanese high school basketball league] Division I tournament. The average age of a player was 17.09 years (SD = .91).

Instruments

Four research questionnaires were used to measure four phenomena: (a) participants’ goal orientation, (b) the motivational climate they perceived, (c) perceived personal athletic ability, and (d) perceived personal sport-related confidence.  First, the Sport Goal Orientation Questionnaire (Duda & Nicholls, 1989; modified by Chi, 1993) contains 13 questions and is primarily used to measure individuals’ goal orientation in sport settings. Second, the Perceived Sport Motivation Climate Questionnaire (Seifriz, Duda, & Chi, 1992; modified by Huang & Chi, 1994), which comprises  two parts and 34 questions, is primarily used to measure, in team-sport settings, the motivational climate perceived by individual athletes. Third, a modified version of the Perceived Ability Questionnaire (Nicholls et al., 1985) presented 4 questions. Fourth, the Sport Confidence Questionnaire, Wu and Chi’s modification (2000) of the Vealey et al. Sources of Sports Confidence Questionnaire (1998), was employed to assess the participants’ sources of sport confidence. Wu and Chi’s Sport Confidence Questionnaire contains 35 questions and uses a 7-point Likert scale. Questions address eight proposed sources of confidence, as follows: perfection of skills, 5 questions; demonstration of ability, 6 questions; physiological/psychological preparation, 4 questions; physical performance, 3 questions; social support, 3 questions; vicarious experience, 4 questions; coach’s leadership style, 7 questions; and positive environment, 3 questions. Percentage of variance was 71.03%, and Cronbach’s alpha for the question sets ranged from .70 to .96, indicating strong validity and reliability for the instrument.

Procedures

In advance of the survey administration, coaches and trainers strived to develop good relations with the players and to acquaint themselves well with the practice and game schedules. The researchers informed players participating in the study of the anonymous and strictly confidential nature of their survey responses, and that completing the four instruments would take about 30 minutes. Players met together 2 hours prior to their scheduled practice to complete the instruments. Time was taken at the start of the session to allow the researchers to explain questionnaire content to the participating players.

]Results[

Gender differences were observed when t tests of the data were conducted (Table 1). The differences characterized goal orientation, perceived motivational climate, perceived ability, and sources of sport confidence. Male participants in the study recorded higher scores than female participants did for the sport-related confidence variables perceived ego climate, perfection of skills, and physical performance.

Table 1

Players’ Goal Orientation, Perceived Motivational Climate, Perceived Ability, and Sources of Sport Confidence, by Gender
Gender
Male
Female
Number
  87
   87
    t
Variable
 Mean
   SD
 Mean
  SD
Task orientation 4.052 0.529 4.123 0.569 -0.84
Ego orientation 3.580 0.556 3.500 0.567 0.94
Perceived task climate 3.894 0.437 3.911 0.499 -.24
Perceived ego climate 3.483 0.479 3.264 0.530 2.86*
Perceived ability 4.452 1.171 4.168 1.025 1.69
Perfection of skills 5.365 0.971 5.181 1.056 1.19**
Demonstration 5.523 0.971 5.181 1.056 1.24**
Physiological/psychological preparation 5.508 1.016 5.416 1.046 0.55
Physical performance 4.869 0.897 4.521 1.204 2.16*
Social support 5.272 0.940 5.157 1.199 0.70
Leadership styles 5.492 0.924 5.527 1.145 -0.21
Vicarious experience 5.486 0.932 5.416 1.088 0.33
Positive environment 5.134 1.029 5.038 1.185 0.59
*p < 0.05 **p < 0.01

When simple correlation analyses were performed, positive relationships were observed for the eight sources-of-sport-confidence variables and the task orientations, perceived task climates, and perceived abilities of players of either gender (Table 2, Table 3). (Again, the eight variables are perfection of skills, demonstration of ability, physical performance, physiological/psychological preparation, social support, vicarious experience, coach’s leadership style, and positive environment.) Among the male respondents, ego orientation was positively related to demonstration of ability, physical performance, and social support, while perceived ego climate was positively related to demonstration of ability, physical performance, physiological/psychological preparation, social support, vicarious experience, coach’s leadership style, and positive environment.

Among female respondents, ego orientation was positively related to demonstration of ability, physical performance, physiological/psychological preparation, social support, vicarious experience, coach’s leadership style, and positive environment, while ego climate was positively related to both vicarious experience and positive environment.

Table 2

Simple Correlations Between Variables–Male Respondents (n = 87)
Variable
Task
orientation
Ego
orientation
Perceived
task climate
Perceived
ego climate
Perceived
ability
Perfection of skills .596** .179 .568** .203 .265*
Demonstration of ability .395** .270* .398** .358** .285
Physiological/psychological
preparation		 .430** .093 .478** .260* .272**
Physical performance .320** .212* .284** .288** .373**
Social support .518** .213* .524** .303** .390**
Coach’s leadership style .517** .192 .568** .284** .401**
Vicarious experience .412** .188 .541** .286** .302**
Positive environment .302** .144 .410** .365** .237**

*p < 0.05  **p < 0.01 (two-tailed)

Table 3

Simple Correlations Between Variables–Female Respondents (n = 87)
Variable
Task
orientation
Ego
orientation
Perceived
task climate
Perceived
ego climate
Perceived
ability
Perfection of skills .639** .325** .664** .068 .415**
Demonstration of ability .570** .552** .541** .350** .263**
Physiological/psychological
preparation		 .683** .340** .688** .155 .365**
Physical performance .465** .397** .429** .091 .349**
Social support .637** .457** .648** .128 .426**
Coach’s leadership style .659** .479** .647** .203 .401**
Vicarious experience .595** .250* .684** .058 .536**
Positive environment .511** .309** .494** .227* .500

*p < 0.05   **p < 0.01 (two-tailed)

For the male respondents, perceived task climate effectively predicted demonstration of ability, physical performance, social support, vicarious experience, coach’s leadership style, and positive environment. In addition, their task orientation effectively predicted perfection of skills and physiological/psychological preparation. For the female respondents, perceived task climate was an effective predictor of perfection of skills, physical performance, social support, vicarious experience, and positive environment. In addition, their task orientation was an effective predictor of demonstration of ability, physiological/psychological preparation, coach’s leadership style, and positive environment.

For males, total equality of variance was 22.6%, and the variance for each variable was 17.6% and 5.0%. For females, perceived ability and perceived task climate were effective predictors of confidence perceived prior to competition; the total equality of variance was 43.9%, and the variance for each variable was 39.6% and 4.3%.

]Conclusions[

The study results include significant gender differences in perceived ego climate and three source-of-sport-confidence variables: perfection of skills, demonstration, and physical performance. Additionally, for both genders, sources of confidence were closely related to a player’s task orientation, perceived task climate, and perceived ability. During stepwise regression analyses, both genders’ sources of sport confidence were shown to be effectively predicted by a player’s task orientation, motivation task climate, and self-perceived ability. Such findings are in line with results of several previous studies (Shane, 2000; Vealey, 1998; Wu & Chi, 2000). The findings indicated further that players who were more task oriented, or preferred task-oriented climates, valued the participative process (comprising effort, perfection, and learning) over the win-lose outcome. This emphasis would have a positive effect on both sport-related confidence and the sources of that confidence. For this reason, the researchers suggest first that coaches work harder at creating task-oriented practice environments or climates, and second that they strive to understand the sources of their players’ sport-related confidence, in order to enhance the athletes’ confidence.

Future studies in the area of athletes’ sport-related confidence might investigate sequential effects of different types of motivational climates on sources of sport confidence (effort and performance) as well as on cognitive anxiety, state anxiety, and satisfaction.

]References[

Bandura , A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 191–215.

Chi, L. K. (1996). Stress management of athletes. National Physical Education Quarterly, 25(4), 51–57.

Chou, W. H. (1995). The establishment of sport confidence based on self-efficacy. National Physical Education Quarterly, 25(4), 62–69.

Corbin, C. B., Laurie, D. R., Gruger, C., & Simley, B. (1984). Vicarious success experience as a factor influencing self-confidence, attitudes, and physical activity of adult women. Journal of Teaching in Physical Education, 4, 17–23.

Duda, J. L. (1992). Motivation in sport settings: A goal perspective approach. In G. C. Roberts (Ed.), Motivation in sport and exercise (pp. 57–91). Champaign, IL: Human Kinetics.

Duda, J. L., Chi, L., & Newton, M. (1990). Psychometric characteristics of the TEOSQ. Paper presented at the meeting of the North American Society for the Psychology of Sport and Physical Activity, Houston, TX.

Duda, J. L., Fox, K., Biddle, S. J. H., & Armstrong, N. (1992). Children’s achievement goals and beliefs about success in sport. British Journal of Education Psychology, 26, 40–63.

Feltz, D. L. (1988). Self-confidence and sports performance. In K. B. Pandolf (Ed.), Exercise and sport sciences reviews (pp.423–457). New York: MacMillan.

Huang, C. R., & Kuo, H. Y. (1999). The sources of athletes’ sport confidence. Chinese Physical Education, 13(3), 60–66.

Kao, S. F. (1993). A discussion of sport confidence based on the viewpoint of self-efficacy. Chinese Physical Education, 7(1), 107–110.

Lirgg, C. C. (1991). Gender differences in self-confidence in physical activity: A meta-analysis of recent studies. Journal of Sport & Exercise Psychology, 13, 294–310.

Lu, P. C. (1991). Sport confidence and performance. Chinese Physical Education, 4(4), 21–25.

McCormick, S. S. (2000). The relationship of sources of sport-confidence and goal orientation. Unpublished master’s thesis, Springfield College.

Nicholls, J. G. (1984). Achievement motivation: Conceptions of ability, subjective experience, task choice, and performance. Psychological Review, 91, 328–346.

Seifriz, J., Duda, J. L., & Chi, L. (1992). The relationship of perceived motivational climate to intrinsic motivation and beliefs about success in basketball. Journal of Sport and Exercise Psychology, 14, 375–391.

Vealey, R. S. (1986). Conceptualization of sport-confidence and competitive orientation: Preliminary investigation and instrument development. Journal of Sport and Exercise Psychology, 8, 221–346.

Vealey, R. S. (1988). Sport-confidence and competitive orientation: An addendum on scoring procedures and gender differences. Journal of Sport and Exercise Psychology, 10, 471–478.

Vealey, R. S., Hayashi, S. W., Garner-Holman, M., & Giacobbi, P. (1998). Sources of sport-confidence: Conceptualization and instrument development. Journal of Sport and Exercise Psychology, 20, 50–80.

Wu, S. C. (2000). A research in relationships of athletes’ goal orientation, perceived motivational climates and sport confidence. Unpublished master’s thesis, National College of Sport and Physical Education, Taoyuan, Taiwan, Republic of China.

2017-08-07T11:51:43-05:00February 18th, 2008|Contemporary Sports Issues, Sports Management, Sports Studies and Sports Psychology, Women and Sports|Comments Off on Gender Differential in the Goal Setting, Motivation, Perceived Ability, and Confidence Sources of Basketball Players
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How Teens & Adults Feel About Physical Activity & Physical Education: A Survey Conducted for NASPE

How Teens & Adults Feel About Physical Activity & Physical Education: A Survey Conducted for NASPE
The article reports on an opinion survey that was carried out by Opinion Research Corp. International, a Princeton, New Jersey, company, for the National Association for Sport and Physical Education (NASPE). The National Association for Sport and Physical Education (NASPE), a nonprofit education association of over 18,000 professionals in the fitness and physical activity fields, wanted to explore with adults and teens their attitudes about physical activity and physical education: to learn about their physical activity experiences, positive and negative. NASPE, an association of the American Alliance for Health, Physical Education, Recreation and Dance, is the only national association dedicated to strengthening basic knowledge about sport and physical activity among professionals and the general public. Putting that knowledge into action in schools and communities across the nation is critical to improved academic performance, social reform, and the health of individuals.
The opinion survey comprised self-reports, and following the survey NASPE has raised questions about the accuracy with which Americans view and discuss their exercise and activity habits. Appendix A presents a newspaper article NASPE prepared concerning the survey.
Recent studies by the U.S. Centers for Disease Control and Prevention (CDC) show the number of overweight children has more than doubled in the last three decades; 5.3 million Americans ages 6 to 17 (12.5%) are overweight or obese. The CDC estimates costs of care associated with obesity (e.g., treatment of weight-related diabetes and heart disease) at $100 billion a year, about 8% of the national health care budget.

The lack of physical activity among Americans of all ages is so critical that it is considered to be a major health risk. Recently, the New England Journal of Medicine reported that girls become so sluggish in their teenage years that many barely move at all. African American girls are even more sedentary than whites, according to the report, and this sets the stage for a lifetime of obesity and associated chronic illnesses like high blood pressure and diabetes.

The 1996 Surgeon General’s Report on Physical Activity and Health reports that Americans become increasingly less active with each year of age. Research links inactivity among children to sedentary living among adults. Inactivity and poor diet cause at least 300,000 deaths a year in the United States, more than result from infectious disease, firearms, motor vehicles, and illicit drug use combined. Physical activity (or more directly, inactivity) is a risk factor in many diseases: stroke, heart disease, high blood pressure, osteoporosis, various cancers, diabetes, depression, obesity, and more.

Survey Methodology

The survey, which was conducted by Opinion Research Corp. International of Princeton, New Jersey, is based on interviews with a nationally representative sample of 1,021 adults (18 years of age and older, 50% male, 50% female) and 500 teens ages 12-17. The margin of error for the adult sample is ± 3 percentage points; when broken into subgroups (those with and without children in the household), the margin of error is ± 6 percentage points. The margin of error for the teen sample is ± 4 percentage points. All interviewing was done August 1-4, 2002. The survey was funded with an unrestricted grant from the National Soft Drink Association.

Here are the survey’s major findings concerning adults’ and teens’ beliefs.

Major Findings Concerning Adult Physical Activity

Getting Enough Physical Activity to Maintain a Healthy Lifestyle

The majority of adults (59%) feel that they are getting enough physical activity to maintain a healthy lifestyle. Men are more likely than women to feel they are getting enough physical activity to maintain a healthy lifestyle (65% vs. 53%). Adults outside metropolitan areas (65%) are more apt than adults who live in metropolitan areas (57%) to believe they are getting enough daily physical activity.

Nearly 9 in 10 (88%) American adults report that they exercise for a period of at least 30 min per week, on an average 3.9 days per week. Men are more likely than women to get at least some weekly exercise (91% vs. 84%). Adults under 55 are more likely than older adults to report having at least some weekly exercise (nearly 90% for under 55 vs. 82% for those 55 and older).

Things Which Prevent Adults from Getting Enough Physical Activity

Most adults who reported they do not get enough physical activity tended to say that work (23%), not having enough time (18%), health problems (12%), or lack of interest or motivation (12%) prevented their being physically active.

Importance of Physical Activity

Most adults (73%) state that health is the reason that physical activity is important. A number of adults also mention weight (16%), attitude (10%), and appearance (9%) as additional important reasons. Females are significantly more likely than males to mention health (77% vs. 68%) and weight (19% vs. 13%) as top reasons that physical activity is important.

Improving Job Performance

Almost 9 out of 10 adults (88%) feel that being physically fit will help them improve their job performance. Among adults aged 35-54, 91% feel their job performance is positively affected by being fit; among younger adults, those aged 18-34, 86% share that opinion.

Adults who currently have children in their household are significantly more likely than adults not sharing a household with children to believe that job performance improves with physical fitness (93% vs. 85%). Of those who believe that job performance improves with physical fitness, 93% cite “gives you more energy” as the reason for improved performance, while 85% cite “gives you greater mental alertness,” 83% choose “reduces stress,” and 60% choose “allows better time management.”

Women are much more likely than men to report feeling that, where employment is concerned, physical fitness reduces stress (86% vs. 76%) or allows better time management (65% vs. 55%).

Television Viewing and Personal Computer Usage

On average, American adults watch 2.2 hr of television per day. Women average 2.4 hr per day of television viewing, significantly more than men’s average 2.0 hr daily. Adults 55 years and over are more likely to watch 5 hr or more per day, when compared to adults ages 35-54 (15% vs. 7%) and adults ages 18-34 (15% vs. 8%). In addition, overall, adults are spending almost 2 hr (1.7 hr) each day using a personal computer for Internet browsing, electronic chat, games, and school research.

Major Findings Concerning Physical Activity of Children Sharing Surveyed Adults’ Households

Getting Enough Physical Activity to Maintain a Healthy Lifestyle

Three quarters (76%) of adults having children ages 6-17 in their households feel that their children are getting enough daily physical activity to maintain a healthy lifestyle.

School-Based Physical Education

Adults perceive that their children complete school-based physical education classes on 3.4 days per school week. About three quarters (74%) of adults having children ages 6-17 in their household feel that they have a good understanding of the physical education curriculum at the schools their children attend, and a majority of these adults (84%) perceive their children’s physical education classes in a positive light.

Nearly three fourths (73%) of American adults who have 6- to 17-year-old children in the household believe that physical education furthers the development of learning capabilities in other subject areas like math, reading, and science; more women than men hold this belief (80% vs. 65%). Adults in households with income below $25,000 are more likely (85%) than those in households with income at or above $25,000 (72%) to report feeling that physical education aids in learning other school subjects. Adults in the North Central region are most likely (82%) to agree that their child’s physical education contributes to the development of other learning capabilities.

Some reasons adults give for believing that physical education furthers their child’s development in other school subjects are that physical education “makes child more alert/aware” (26%); enables their child to better “focus/concentrate” (14%); “gives/increases energy” (9%); teaches child to “work with others” (6%); reduces stress experienced by child (6%); involves the use of math (i.e., in sports) (6%), makes child “more healthy” (5%); and provides a break from other tasks, important since children need to move around (5%).

Adults age 55 or more are those most inclined to feel that their child’s participation in physical education improves mental function overall; 71% of adults in this group believe so, while 54% of adults age 35-54 and 51% of adults age 18-34 believe so. Adults who reside in larger households (3 or more persons) are more likely to state that a child’s participation in physical education improves mental function overall (55%), as compared to adults who live alone with a child (40%).

Furthermore, adults with some college education are likelier than those without any college education to hold their child’s physical education important for reasons of health or increased energy. Five percent of the latter group (no college) cited one of those two reasons, while 13% of the former group cited health and 12% of the former group cited increased energy. It is interesting to compare these proportions with results broken down by income: Among adults with household incomes of $50,000 or more, 13% cited health and 18% cited energy, while among those with household incomes between $25,000 and $49,999, 9% cited health and 2% cited energy, and among those at less than $25,000, 9% cited health and 0% cited energy.

Daily Non-School-Based Physical Activity of Child

Surveyed adults having children in their households between 6 and 17 years of age report that their children spend an average of 2.5 hr daily in after-school physical activity. Most parents (72%) say they encourage the child’s physical activity either all the time or frequently; 7% say they infrequently or never encourage the child’s physical activity.

Broken down by region, significantly more adults in the West (53%) encourage children’s physical activity all of the time than in the Northeast (30%) or North Central (28%) regions.

Things Which Prevent Child from Getting Enough Physical Activity

Television (42%) and computers and video games (41%) are the barriers to child’s physical activity most commonly cited by adults whose households include a child. Lack of interest or motivation (29%), too much homework (28%), and lack of access to safe facilities (21%) follow closely behind.

On average, the child of a parent surveyed for this study spends 2.2 hr each day watching television, 1.9 hr each day reading or doing homework, 1.4 hr daily on the computer/Internet, 1.2 hr playing video games, and 1.1 hr daily talking on the telephone.

Physical Activity and Child’s Self-Esteem

The majority of the surveyed adults having children ages 6-17 (84%) feel that participation in physical activity (e.g., a sport) has a positive effect on a child’s self-esteem. A particularly high percentage (94%) of adults in the Northeast region affirms the connection between physical activity and self-esteem. Furthermore, an overwhelming majority (85%) of the adults with children 6-17 believe that participation in sports or physical activity minimizes a child’s ability to get into trouble.

Attitude Toward Physical Activity and Physical Education

Nearly 8 of 10 parents (79%) feel that their own attitudes concerning physical activity in turn affect their children’s attitudes toward physical activity. A larger proportion of the relatively affluent parents surveyed (household income of $50,000 or more) agree (86%) that their own attitudes affect the children’s attitudes when it comes to physical activity; a smaller proportion of relatively non-affluent parents (household income under $25,000) agreed (67%).

Similarly, 8 in 10 parents (77%) feel that their own attitudes towards physical education in turn affect the attitudes of their children toward physical education.

Major Findings Concerning Teen Physical Activity

Getting Enough Physical Activity to Maintain a Healthy Lifestyle

A large majority of the 12- to 17-year-olds surveyed (84%) say they obtain enough daily physical activity to maintain a healthy lifestyle. Younger teens (those age 12-14) are more likely than older teens (those age 15-17) to say they get enough physical activity every day (88% vs. 81%). Among teens, males are more likely than females to say their daily physical activity is sufficient to maintain a healthy lifestyle (88% vs. 81%).

When asked what person could be most helpful to them in terms of becoming more physically active, few teens cite their doctors (4%), their teachers (5%), or celebrities (3%). Instead, the surveyed teens say that friends, parents, and professional athletes could help them increase their physical activity (56%, 18%, and 11%, respectively). Older teens are more likely than younger ones to think of friends as persons most helpful in increasing physical activity (60% for older teens vs. 51% among 12- to 14-year-olds).

Daily After-School Physical Activity of Teens

Slightly more than half of teens (59%) participate in organized team or club sports after school. Teens in the Northeast region participate in such afterschool programs at a rate of 70%, while teens in the South and West participate at a rate of 56% and 49%, respectively.

School-Based Physical Education

An overwhelming majority of teens (92%) feel they should receive some type of daily physical education at school. This opinion was expressed by younger teens (age 12-14) at a rate of 96% and by older teens (age 15-17) at a rate of 87%.

Of the surveyed teens, half (50%) say that they should have school-based physical education classes five days a week; only 3% of the teens feel that school-based physical education should take place one day a week. Teens in the Northeast region are much less likely than teens in other regions to state that they should receive physical education five days a week.

More than three quarters of all teens (78%) classify their school-based physical education experiences as very good or good. Younger teens (age 12-14) are more likely than older teens (age 15-17) to enjoy their physical education classes (85% vs. 71%).

Parents’ Attitudes Towards Physical Activity and Physical Education

Nearly 6 in 10 teenagers (56%) would say that their parents’ attitudes have no effect on their own feelings about physical activity; fewer teen girls than teen boys, however, see their feelings as separate from those of parents (48% vs. 63%).

In addition, a majority of teenagers (64%) say that their parents’ attitudes towards physical education have no effect on their own feelings. Again, fewer teen girls than teen boys (60% vs. 69%) say that their parents’ attitudes toward physical education have no bearing on their own attitudes.

Sports and Physical Activity to Stay Out of Trouble

A large majority of the teens (85%) express a belief that participation in a sport or other physical activity will help them stay out of trouble. The 12- to 14-year-olds are significantly more likely than the 15- to 17-year-olds to say participation can help them stay out of trouble (92% vs. 78%).

Non-Physical Activities

The average daily time spent watching television is 2.2 hr, according to the surveyed teens, with younger teens (age 12-14) watching significantly longer than older teens (age 15-17), 2.4 hr vs. 2.0 hr. Moreover, teen boys watch television for longer periods each day than teen girls do, an average 2.3 hr daily vs. an average 2.1 hr daily. Teens in the South region and North Central region say they watch significantly more television daily than their counterparts in the Northeast region. Daily averages are 2.5 hr in the South, 2.3 hr in the North Central, and 1.8 hr in the Northeast.

Most teens feel that their downtime, on an average day, is largely devoted to using a personal computer for Internet browsing, electronic chat, games, and/or research related to school. On average, the teens spend 1.9 hours daily in such pursuits. They report spending a further 1.9 hours per day, on average, using a PC to complete homework. Finally, they report spending only 1 hr on an average day playing video games.

How Adults’ and Teens’ Opinions About Physical Activity Compare

Getting Enough Physical Activity to Maintain a Healthy Lifestyle

Adults having children ages 6-17 in their households report that the oldest child participates in physical activity for at least 30 min on an average 4.9 days per week. Teens themselves (age 12-17) say that they participate in physical activity for at least 30 min on an average of 4.2 days per week.

On average, adults with children under 12 say that, in the past week, their child participated in physical activity for at least 30 min on 5.5 days. In comparison, adults with children ages 12-17 say that, in the past week, their child participated in physical activity for at least 30 min on an average 4.9 days.

In the North Central region, adults with children in their households say their children participated in at least 30 min of physical activity on 5.4 days per week, on average; in the West, that figure is also 5.4. In the North Central region, however, the figure is 5.1 days per week, on average, while in the South region it is 5.0.

About three quarters of all adults (76%) with children ages 6-17 in their households believe that their children are getting enough daily physical activity to maintain a healthy lifestyle. A slightly larger percentage of teens ages 12-17 (84%) feel that they are getting enough physical activity to maintain a healthy lifestyle.

How Much Physical Education Is Desired?

Adults with children ages 6-17 in their households report feeling that their children should participate in school-based physical education for an average 4.1 days per week. Teens ages 12-17 feel that an average of 3.8 days per week should be devoted to physical activity.

Appendix A

Article Prepared About the Survey by NASPE

New Physical Activity Opinion Survey Demonstrates Perceptions Do Not Meet Reality: Upcoming Healthy School Summit (Oct. 7, 8) Will Discuss Role of Schools

RESTON, VA, October 3, 2002 — How accurate is self-assessment? That’s the question the National Association for Sport and Physical Education (NASPE) is asking itself after recently commissioning an opinion survey of adults and teenagers about their perceptions of physical activity and physical education. In spite of the U.S. Surgeon General’s Report on Physical Activity and Health (1996) stating that 60% of adults are not getting enough physical activity, the majority of adults (88%) and teenagers (84%) participating in this survey reported that they are getting enough physical activity to maintain a healthy lifestyle. The recommended exercise for adolescents and adults is at least 30 minutes per day on most if not all days.

“It appears perceptions do not meet reality,” said NASPE President Kim Graber, Ph.D., of the University of Illinois, Urbana/Champaign. “The lack of physical activity among Americans of all ages is so critical, it is considered to be a major health risk factor. Yet nearly nine in 10 (88%) adults report getting 30 minutes of exercise at least once a week. They average 3.9 exercise sessions per week.

  • Teens ages 12-17 say that on average, they participate in physical activity for at least 30 minutes, 4.2 times per week.
  • Seventy-six percent of adults feel that their children also get enough physical activity.

“Clearly the physical activity community must find better and more creative ways to provide parents and teens with a better understanding about the amount and type of activity needed to maintain good health,” continued Dr. Graber.

The Healthy School Summit, scheduled for October 7 and 8 in Washington, DC, will examine the ways schools can be part of the solution for addressing poor diets and sedentary lifestyles. Citing a looming health crisis among the nation’s children, Mrs. Laura Bush, Dr. David Satcher and more than 30 national organizations, including NASPE, will develop national, state and local initiatives to create healthier school environments.

NASPE Executive Director Judith C. Young, Ph.D., questioned the participants’ recording of their screen time. “While the Centers for Disease Control and Prevention report teens watching more than five hours of television viewing per day, the adults and teenagers said they watched 2.2 hours of television per day and spent another two hours a day using a personal computer for Internet browsing, chat rooms, games, and school research,” said Dr. Young.

Teenagers admit to spending the “majority of their downtime” on a personal computer.

  • The majority of parents feel that television (42%) and computers or video games (41%) are the largest barriers to their child’s physical activity.
  • Lack of interest or motivation (29%), too much homework (28%), and lack of access to safe facilities (21%) are other reasons for inactive daily routines.

Perceived Benefits of Physical Education Nationwide

While only 51.7% of students are enrolled in a physical education class, the majority of adults (84%) with children ages 6-17 have a positive perception about their child’s physical education classes. Nearly three fourths believe that physical activity and physical education will support learning in other subject areas, such as math, reading or science. Adults also believe physical education makes children more alert/aware; focus better; increases energy; learns how to work with others, reduces stress and helps make the children healthier.

While nearly 79% of parents feel that their own attitudes towards physical activity and physical education affect their child’s attitude, more than half of teenagers say their parents’ attitudes are not important in influencing their attitudes toward physical activity (56%) and physical education (64%).

  • Teens selected friends (56%) as the best source to help them be more active, followed by parents (18%) and professional athletes (11%).
  • Few felt that teachers (5%), their doctors (4%) or celebrities (3%) would help them to be more active.

Adults feel their job performance is positively affected by being more fit because it gives them more energy, greater mental alertness, reduces stress and allows for better time management. Those adults who don’t think they’re getting enough physical activity most often say it’s because of:

  • their job (23%), not having enough time (18%), health problems (12%), or lack of interest or motivation (12%).

In addition, the majority of parents feel that participation in a sport or physical activity positively affects their child’s self-esteem. A large majority of teens (85%) join adults in believing that their participation in sports or physical activity will help them stay out of trouble.

The survey, which was conducted by Opinion Research Corporation International of Princeton, NJ, is based on interviews with a nationally representative sample of 1,021 adults (18 years of age and older, 50% male/50% female) and 500 teens, ages 12-17. The margin of error for the adult sample is + or – 3 percentage points; when broken into subgroups (those with children in the household) the margin of error is + or – 6 percentage points. The margin of error for the teen sample is + or – 4 percentage points. All interviewing was done from August 1-4, 2002.

Information about the National Association for Sport and Physical Education (NASPE) can be found on the Internet at www.aahperd.org, the web site of the American Alliance for Health, Physical Education, Recreation & Dance (AAHPERD). NASPE is the largest of AAHPERD’s six national associations. A nonprofit membership organization of over 18,000 professionals in the fitness and physical activity fields, NASPE is the only national association dedicated to strengthening basic knowledge about sport and physical education among professionals and the general public. Putting that knowledge into action in schools and communities across the nation is critical to improved academic performance, social reform and the health of individuals.

Author Note

This survey was funded with an unrestricted research grant from the National Soft Drink Association.

2016-04-01T09:22:47-05:00February 18th, 2008|Contemporary Sports Issues, Sports Exercise Science, Sports Studies and Sports Psychology|Comments Off on How Teens & Adults Feel About Physical Activity & Physical Education: A Survey Conducted for NASPE
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Marketing Sport and a City: The Case Of Athens 2004

Submitted by: George Karlis,

The opportunity for a city to host the Olympic Games constitutes an enormous economic, social, and cultural commitment, as the Olympics are the world’s biggest sporting event. It is an opportunity that, if properly managed and marketed, will bring a number of positive long-term benefits to the rest of the country in which the city is located.

While the Games last only 2-3weeks, 10 years of preparation will have gone before to ensure both a successful bid and the smooth operation of the Games once the bid wins. The experience of cities that have hosted the Olympic Games demonstrates that, if they are carefully planned and promoted, the Games can generate significant growth over a long period. A primary factor in such growth is the increase in tourism that  a nation can continue to enjoy long after the Olympic Games have concluded. The aim of this paper is to examine the nature of the impact hosting the Games makes on tourism and to discuss marketing strategies that the city of Athens should follow in order to maximize the positive impact of tourism surrounding the 2004 Olympic Games.

From a tourism perspective, the Olympic Games can certainly be considered the most important sporting event. Frequently, organizers’ purpose in undertaking such events is to increase tourism in a city or country. In general, the benefits from organizing such events include the following:

  1. attracting high-income tourists and creating a new generation of tourists who might visit the host country repeatedly
  2. creating a favorable image of the host country as a tourism destination
  3. creating and/or modernizing a locale’s tourism infrastructure
  4. using the international media’s presence to communicate with the world
  5. creating a skilled workforce in the organization, management, and funding sectors specializing in unique, tourist-friendly sporting events

Properly managed, the Olympic Games can change a country’s tourism industry significantly and for the long term. Effects tend to fall within three categories, the Olympic market, the internal tourism market, and the international tourism market. The Olympic market consists of a network of economic activities that result from organization of the event and require significant investment of time and funding. Aspects of the Olympic market are marketing (mainly promotion and public relations), funding and donations, preparation of athletic and related facilities, tickets and other spectator services, transportation and accommodation (of athletes, spectators, dignitaries), and safety and emergency services. For every Olympiad, a workforce is formed to undertake these tasks, creating thousands of jobs and extensive activity in the host city. (Later in this paper, an attempt is made to estimate economic and non-economic effects of the Olympic market, based on previous studies.)

A large nation’s internal tourism market also experiences an impact when one of its cities is to host the Olympic Games. However, in Greece as opposed to the U.S. or even Australia, the internal tourism market is of less significance. In terms of both area and population, Greece is the smallest country chosen to host an Olympic Games. One might go so far as to refer to Greece itself as the “city” that has undertaken the responsibility of hosting the Games.

The right to host the Olympics brings with it long-term effects on the city and nation’s international tourism market, as well. Such effects begin to be felt immediately after a country has won a bid to host the Games and persist until several years after the closing ceremony. In the case of Athens, this period covers the years 1998 to 2011. International tourism will extend to three types of tourist: visitors traveling before the Games, spectators and other visitors during the Games, and visitors drawn to the country at some point by the Olympics-related publicity. The first category comprises, for Athens, persons who will visit Greece in preparation for the Games, such as the members of the Olympic family, media representatives, sponsoring organizations’ representatives, athletes, dignitaries, and some spectators. Such individuals also constitute the second category and can be expected to peak in number as the Olympic athletes compete. Finally, the third category includes all tourists from outside Greece who will visit Greece between 1998 and 2011 due to promotional efforts linked to the 2004 Games.

Games’ Direct Impact on Tourism

The direct impact of the Olympic Games on tourism is embodied in the arrival of all those directly involved in Olympic athletic events, as well as those participating in the associated cultural Olympiad; direct impact’s chronology is before and during the Games. Whatever the city hosting the Games, demands associated with direct impact remain similar and are based mainly on  the number of sports included (currently 28). While estimating direct impact involves some rather arbitrary decisions, the final overall result is not influenced, as it is of very small size. Moreover, a slight increase in the relevant figures was allowed to reflect visitors at the cultural Olympiad. Table 3 presents estimates of the numbers of tourists anticipated to be directly associated with the 2004 Athens Games during the period 1998-2003.

The tourist category of most importance is the before-Olympics visitors, who include numbers of representatives of the International Olympic Committee (IOC). The IOC is contractually obligated to send representatives to Greece regularly to audit activities and check the progress of the Games’ organization. The second largest category of visitors includes members of international federations for various sports. They monitor the development of facilities in which competition will take place. The third category consists of athletes. As the date of the Games approaches, athletes begin to visit the country to become accustomed to the climate and sporting facilities. The final category is made up of sponsors and members of the media.

The total number of visitors expected in Greece during 1998-2004 on Olympic Games’ business will number 111,000. This figure constitutes a very small percentage of all tourists who will ultimately visit Greece as the result of the publicity about the country linked to the 2004 Games.

Consequences for Greece, for Athens

Again, the effect of the Olympic Games on tourism has relevance both for Athens and for Greece as a whole. Initially, forecasts of the numbers of tourists throughout Greece were made. These forecasts were then used to estimate the number of tourists to arrive in Athens, according to three national scenarios. The first national scenario is confined to those arrivals directly linked to the Games and assumes that the level of demand will be minimal. The second national scenario assumes a steady increase in demand leading up to the Games and stabilizing a few years after the Games. The third national scenario assumes a small increase in tourism before and during the Games, a large increase after the Games, and a small decrease several years after the Games.

The Olympic Games of 2004 will present a great opportunity for the rehabilitation of Athens and the Attica prefecture as a whole. Some infrastructure projects are already under way; together with Athens’ international promotions during the coming seven years, these projects may help Athens enhance the proportion of the Greek tourism industry it claims. Under a first city scenario, Athens will maintain, at the least, its share of all tourists arriving in Greece, which early in the 1980s was 40% but slipped to 16% in the mid 1990s.

Under the second city scenario, Athens’ share of the total number of tourists in Greece will increase significantly, attaining for the period 1998-2011 an average 22% of all tourists. During the 1990s, the proportion of tourists in Greece who were visiting Athens was as high as 22.3%, but averaged 18.22%.

According to a third scenario, Athens’ share in the numbers of foreign visitors to Greece should move from 18% in 1998 to 22% in 2004; after 2004, the city’s share should decrease, returning to the 18% figure in 2011.  Across the whole period, the average proportion of Greek tourism claimed by Athens is forecast to be 16.9%.

Each one of these scenarios for Athens is combined with the three scenarios for the whole country. Thus, the total number of possible outcomes for Attica comes to nine. The fluctuations of these effects are the same as the fluctuations relating to Greece as a whole. They are not presented here because the effects for the Attica area are estimated as a percentage of the whole. Under the first two scenarios, the percentage is assumed to follow a distribution moving from 18% to 22% and then returning to 18%.

Maximizing Benefits to Tourism Industry That May Surround the Games

The Olympic Games are a unique tourism-sport event presenting an outstanding opportunity to develop long-term gains for a nation’s tourism Industry. Supply and demand continue to figure in marketing, and in the case of Greece and the 2004 Olympics, it must be ensured that the tourism infrastructure can meet the demand for accommodation posed by extra thousands of tourists yet not overestimate the number of tourists who will visit Greece.

Figure 1 diagrams the approach to marketing the 2004 Games, one that involves three basic, interdependent elements. The first is supply, which includes organization of and preparation for the Games, the choice of the host city, all services that will be required , media (television, radio, and print), and grants offered by IOC and the host city. The second element of the marketing system comprises intermediaries between the supply and the demand. Often, these intermediaries participate in securing the successful bid for the Olympics, for instance by finding sponsors, working to attract spectators, and generally organizing the athletic events. The third element of the marketing system is demand, which includes all national athletic teams, all federations supporting the Olympic sports, spectators and tourists, the media audience (television viewers, radio listeners, and readers), and all official sponsors of the Games. The Los Angeles Games proved the importance of sponsorship to the presence of adequate funding.

How can Athens and Greece best tap into the elements of this framework to maximize publicity generated by the Games? When the Sydney Games come to an end, Athens and Greece could pursue a series of strategies, including the following:

1. Host athletic events during the period prior to the Games to allow Olympic athletes to experience the Greek climate. Events should be organized in various regions of Greece.

2. Host athletic events featuring non-Olympic sports, in cooperation with these sports’ international federations.

3. Host participative athletic events targeting those potential tourists who enjoy recreational athletics.

4. Before and after the Games, organize Olympics-related excursions highlighting the regions associated with athletics in ancient Greece.

5. Organize international cultural exhibitions and scientific and professional conferences offering an Olympics angle.

6. Supply the international media with information before and after the Games, using news broadcasts.

The forecasts presented earlier are based on the assumption the all of these strategies will be implemented to the fullest. The strategies, nevertheless, are only some of the strategies (activities and events) that could help Greece maximize benefits deriving from the Games. Other strategies should be developed to ensure the best management of the Games.

Conclusion

The Olympic Games in 2004 will have important economic effects on the host city Athens. Publicity surrounding the Olympics and the Olympic competitions themselves are expected to increase foreign tourism in Greece during 1998-201. New jobs will be created and the nation’s GDP will grow, very probably to the tune of 0.8% for annual growth from 1998 to 2011, which should increase employment by 32,000 annually.

The most important source of the increase in economic activity will be money spent by foreign tourists visiting both Athens and Greece as a result of Olympic exposure. The prediction of this study is that these such cash inflows will come to 2.3 trillion drachmas for the 14-year period 1998-2011, an average of 161 billion drachmas (1999 prices). According to the central scenario of this study, increased tourism due to the Olympic Games will come to 440,000 visitors annually for the period 1998-2011, or 6 million visitors in all.

Increased tourism will create additional need for accommodation. According to this study, such demand can be satisfied without additional investment in accommodation infrastructure, by improving existing accommodation units, especially across the Attica area. During the 2004 Games, peak demand in the Attica area will occur in August and is likely to amount to 1.9 million overnight stays during the 17 days of the Games. Existing hotel accommodations in the Attica area, along with use of temporary facilities such as camps, student dormitories, cruise ships, apartments, and private residences should provide accommodations for  2.6 million, more than adequate for the anticipated number of visitors.

While simply sheltering visitors to the Games is important, it is not enough. The supply of accommodations of various types must also be carefully managed. One conclusion of this study is that, although Greece may be able to cope with the unusual numbers of tourists arriving, this does not preclude problems while hosting them. To discourage any problems, government, organizing committee, and hotel management must work together from the time the Games in Sydney end. Especially critical will be the enhancement of the quality of Attica’s high-end hotels.

Long-term increases in demand for accommodation resulting from the 2004 Olympics is expected to be very small. At the end of the examined period, the supply of beds in Attica will amount to 100,000, while demand should be roughly the same, 103,000. The demand for beds across Greece will come to 858,000, while the supply will come to 834,000.

References

  1. Getz, D. (1997). Event management and event tourism. New York: Cognizant Communication.
  2. Getz, D. (1998). Trends, strategies, and issues in sport-event tourism. Sport Marketing Quarterly, 7(2), 8-13.
  3. Gibson, H. (1998). Sport tourism: A critical analysis of research. Sport Management Review, 1, 45-76.
  4. Holden, K., Peel, D. A., & Thompson, J. L. (1990). Economic forecasting: An introduction. Cambridge, Cambridgeshire, England: Cambridge University Press.
  5. Ludwig, S., & Karabetsos, J. D. (1999). Objectives and evaluation processes utilised by sponsors of the 1996 Olympic Games. Sport Marketing Quarterly, 8(1), 11-20.
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2013-11-26T21:15:22-06:00February 18th, 2008|Contemporary Sports Issues, Sports Facilities, Sports Management|Comments Off on Marketing Sport and a City: The Case Of Athens 2004
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