PERCEPTION OF LEGACY OUTCOMES FOR HOST RESIDENTS’ QUALITY OF LIFE: UNDERSTANDING SUPPORT FOR MAJOR SPORTS EVENTS IN TAIWAN

Figure 1. The results of testing the hypothesized model

Introduction

Background The greatest attraction of sports (mega) events may be their legacies

(Horne, 2007). Generally speaking, however, a ‘legacy’ is what we get in return for our investment (Grix, 2013) as well as how a Games is remembered (Kaplanidou, 2012). It is therefore the host community that is most likely to gain or lose from a legacy of an event which affects their quality of life (QOL) in the long-run (IOC Olympic Studies

Center, 2003).

Purpose The purposes of this study are (1) to empirically examine a model linking residents’ evaluation of legacy outcomes as performing to expectations, QOL, and

support for hosting major sporting events, and (2) to explore host residents subgroups to understand the winners and losers who gain and lose from major sporting event

legacy.

Hypothesis

H1: Residents’ evaluation of legacy outcomes has a direct positive effect on the residents’ support for events.

H2: Residents’ evaluation of legacy outcomes has a direct positive effect on QOL.

H3: Residents’ perceptions of QOL have a direct positive effect on the residents’

support for events.

H4: There is a significant indirect relationship between the residents’ evaluation of legacy outcomes and resident’s support for events

Method

Data Collection Purposive sampling and a household face to face survey were used to collect the data (April, 2014) from the host communities in Taipei and Kaohsiung,

Taiwan. The two major events (the 2009 World Games and the 2009 Deaflympics) were chosen because they were the most significant international events ever held in Taiwan in terms of their scale.

Questionnaire Respondents were asked to assess the legacy outcomes relating to infrastructure (8 items), economy and tourism (6 items), environment (7 items), knowledge (4 items), sport development (3 items), culture (3 items), emotional (3 items) and social and health (5 items) characteristics.

Outcome evaluation

The outcome evaluation items were anchored from 1 = does not meet my expectations at all through 3 = meets expectations to 5 = exceeds expectations.

QOL

Three statements (Kaplanidou 2010; Perdue, Long, and Kang 1999) captured the residents’ opinions on their QOL. These questions

were measured on a 5-point Likert scale (1 = strongly disagree, 3 = no opinion, and 5 = strongly agree).

Event support

Event support wasmeasured on a 5-point Likert scale (1 = strongly disagree, 3 = no opinion, and 5 = strongly agree) using three

statements adapted from Ko and Stewart (2002) and Kaplanidou (2010).

Demographic

items Gender, age, occupation and monthly income

Result and Discussion

Model fit comparison Table 1 shows that the analyses of the evaluation of legacy outcomes indicated that both models 4 and 5 are satisfactory. This means that the eight-factor second-order model fits the theoretical model.

Reliability and Validity In terms of the reliability assessment, all the composite

reliabilities were above the recommended 0.7 (Fornell & Loarcker, 1981). The average variances extracted were above 0.78, indicating that the measurement model’s

convergent validity was adequate (Fornell & Larcker, 1981).

Hypothesis Test The overall fit indices indicated that the model approached an

acceptable fit (χ2= 2514.133, p < .001; χ2/df = 2.7; RMSEA = 0.06; NFI = 0.96; CFI = 0.97;

IFI = 0.97). The findings indicate that all kinds of legacy outcomes (the first-order) are important to QOL, and that QOL mediates the relationship between evaluation of

legacy outcomes and support for events, thus supporting H2, H3, and H4. Although the evaluation of legacy outcomes has significantly direct effect on support for hosting

major sporting events, by introducing the QOL, the relationship changed into a non-

significant relationship (see Figure 1), thus partially supporting H1. The findings suggest that the eight legacy outcomes aspects were evaluated as important to QOL by host

residents for event success (i.e., event support). Thus, legacy outcomes in particular associated with the eight legacy aspects should be equally addressed and planned during the bidding stage for long-term quality of life consequences for residents.

Cluster Analysis Cluster analysis indicated two segments, non-beneficiaries (288 respondents) and beneficiaries (105 respondents). Most of the respondents in the beneficiary group were students and others below thirty years old, with a monthly

income of less than USD1000, while the non-beneficiary group was mainly composed of senior employees, with monthly incomes of more than USD1000 (see Table 4). In

turn, the elder residents of higher social and economic status who seek a quality living standard certainly need interventions to upgrade their QOL by leveraging legacies from sporting events. The findings are consistent with Kim, Gursoy, and Lee (2006) who

found that students are most likely to favor major sporting events. Similar to Ma et al.’s (2013) research on the 2009 World Games, they found that higher-level income

earners were the non-beneficiary group, suggesting a need for addressing event-

related plans concerning quality of life improvement. Overall, event legacy leveraging strategies are needed during planning process for benefiting wider inactive participants of major sporting events such as the employed, the shopkeeper, and the retired.

PERCEPTION OF LEGACY OUTCOMES FOR HOST RESIDENTS’ QUALITY OF LIFE:

UNDERSTANDING SUPPORT FOR MAJOR SPORTS EVENTS IN TAIWAN

Jhu-Jyun Hsu Shang-Chun Ma Chia-Chian Lee

Institute of Physical Education, Health, & Leisure Studies, National Cheng Kung University, Tainan City, Taiwan

Table 1. Confirmatory factor analysis model fit comparisons (second-order)

Model χ

(df) GFI CFI RMSEA AIC

Evaluation of legacy outcomes

(1)Null model 58189.648(741) - - - 5279.931

(2)One-factor first-order 2217.03(674) 0.767 0.975 0.078 2529.026 (3)Eight-factor first-order (no

correlation between latent variables)

2502.02(682) 0.753 0.962 0.082 2698.024

(4) Eight-factor first-order (correlation between latent variables)

2317.03(674) 0.767 0.975 0.078 2529.026 (5)Eight-factor second-order 2183.28(692) 0.778 0.976 0.074 2359.063

Note: A (1) null model stands for Chi-square for independence model which was generated by the Lisrel output, and model (2) to model (5) were based on Joreskog and Sorbom (1992)

Note: *p < 0.05

Future Research & Conclusions

The present research empirically examined the relationships between legacy outcomes, QOL, and event support, which remains an under-explored area. Thus the findings

based on an assessment of long-term consequences could benefit academics and

practitioners. Meanwhile, this study confirmed that the eight legacy outcome aspects are significant contributors through latent concepts to explain the QOL and event

support, helping to fill the gap between supply side (e.g., event providers) and the demand side (e.g., host residents) of the events. This will assist to shape a clear road map to a successful sustainable event. Segmentation with key stakeholders’ profiles provides sport event organizers with practical implications. Building on the present

model, future studies may account for the multidimensionality of the QOL component

(e.g., life satisfaction, happiness, experiences of life, etc.) to provide a more complete

set of higher-order constructs. More work is also needed to explore strategic event

leveraging to benefit different segments of key stakeholders.