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Research on customer satisfaction measurement and influence factors of fitness club based on large data.

1. Introduction

Nowadays, with the popularization of computer technology and Internet, the industry has benefited from the vast amounts of information, reliable storage, easy to use, instant transmission, processing, computing accurate, easy search and other functions (Shumin Qiu, 2013). Fitness club management as a branch of modern management, the same cannot be separated from the participation of computer and Internet technology (Bo He, Gege Li, 2015). A fitness club is the institution or place where the fitness facilities and services are provided for the members. In China, there are 3 kinds of fitness clubs, the clubs in Starrated hotels to supply service for the hotel customers, the clubs in community based on the government to serve the public for free, and commercial clubs with individual investment. The commercial fitness club usually has a certain fitness equipments and coaches indoor to provide courses and lectures to the members for the purpose of profit. Its main mode is to sale member cards (Tangxun Yang, 2015). This paper studies the commercial fitness clubs, and analyses the influence factors to improve the management of fitness clubs.

Customer satisfaction is the degree of satisfaction of the customers' requirements (Cheng Deng, Yanhui Zhu, 2016). The public satisfaction theory based on customer satisfaction has been used and researched widely. Because the service of fitness club belongs to public service, it makes sense to combines the service with the customer satisfaction (Xuetao Tang, Caiming Xu, 2014). In the fitness club, the customers are the members of the club, and so the customer satisfaction is the satisfaction of members. The purpose of the analysis of customer satisfaction is to find the influencing factors of the club and improve the satisfaction (Xiuling Cao, Haiyan Zhao, 2014). The assessment of customer satisfaction is a means to improve service and the satisfaction of members for fitness club, which has important significance.

In the index research of the assessment of customer service in fitness club at present, there is no related study that focuses on the assessment of customer satisfaction. Though there are more than less researches choose fitness club as the study object, there barely exist any research aimed at service quality or customer satisfaction while many study just one side like employee satisfaction or the coach quality and other just analyse current situation without any countermeasures (Tao Chen, Xinghan Li,2014). In the Research, the fitness club members are the survey object, and the result is got through the distribution of the fitness club customer satisfaction survey. There are 27 variables totally in this questionnaire, and the data is analysed by SPSS and Excel. After the factor analysis, the final analysis of 19 factors in 5 categories is found out. According to the analysis results, the factors of customer satisfaction of fitness club in Hubei province are obvious, and it is convenient to improve the management and satisfaction. It researches the customer satisfaction of the fitness club members according to the management of the club from the perspective of satisfaction. That is strengthening environmental facilities, optimizing course structure, enhancing service awareness, setting flexible and diverse charges, and improving the coaching level of personal instructors.

2. Research object and method

2.1. Survey object

This study adopts the stratified sampling and the investigation object is composed of the commercial fitness club members from Wuchang District, Qiaokou District, Jianghan District, Hongshan District and Jiang'an District in Wuhan City.

2.2. Research method

2.2.1. Method of questionnaire survey

Basic information of research object is shown in Table 1. The survey was distributed in 795 copies. Among them 713 copies of the recycling, Effective number 662, 89.69 percent of the recovery rate, 92.85 percent of the efficiency. Please check the distribution and recovery of the questionnaire (Shown in Table 2).

2.2.2. Method of expert interview

It adopted the method of expert interview to check the setting and the validity of initial questionnaire. There were nine experts whom are professors in social sports research field. The content of interview mainly involved in the dimensions of service composition and the rationality and validity of the questionnaire. Then according to the views of the experts, it conducted a classification. Finally, it determined 27 test items of the questionnaire (shown in Table 3).

2.2.3. Method of mathematical statistics

It used Excel to do a simple analysis of the original data and used SPSS17.0 to do project analysis and exploratory factor analysis of the initial test questionnaire.

3. Research results

3.1. Project analysis

Before the analysis of exploratory factor, the project analysis of the initial questionnaire should be done first. The purpose of the project analysis is to test whether the project of the initial questionnaire reflects assessing content of customer satisfaction.

There were many methods to analyse the project, and the critical ratio method was used in this paper, which is widely recognized by everyone (Guoying Yuan, 2015). The 562 sample data of initial questionnaire was added up, and then ranked by size. The top 27% was the high score group, the corresponding post 27% was low score group (the critical value of high score group was 106, the value of low score group was 84). Then data in each group was averaged in each test item to do the T test. The results were as shown in the 33 tests, the T value of 12 test items was less than the critical value 3.000, and the P value was not significant. So test item A7, B5, B6, C5, C6, D4, D5, D6, E4, E6, E7 and E8 were removed, and the questionnaires included 21 test items (shown in Table 3).

3.2. Exploratory factor analysis

The analysis of exploratory factor to 21 test items was carried on by using SPSS statistical analysis software. In order to determine whether the sample data was suitable for exploratory factor analysis, 562 samples were tested for KMO and Bartlett (shown in Table 4). The results showed that the value of Bartlett was 0.850, KMO was X=3828.073, the degree of freedom was 210, and the probability of significance was P=0.000 (P < 0.005). Therefore, to reject the null hypothesis, that is, the sample data is suitable for exploratory factor analysis.

The principal component analysis was used to analyse 21 dominant variables. The maximum variance method was chosen in the rotating dialog, and the results were analysed by the maximum orthogonal rotation to get the total variance factor load matrix. 5 factors were analysed (shown in Table 5), and their cumulative contribution rate was 57.039%. After the orthogonal rotation, the factors whose Characteristic value is more than 1, and cumulative contribution rate is more than 50%, was chosen by the extraction method of Kaiser. Based on the analysis results, the 5 main factors and 19 high load indexes were further analysed and named. The five factors influenced and interacted with each other, and acted in the satisfaction of the college students. The exploratory factor analysis of 19 item at the same time, to validate the reliability of the item of five dimensions for reliability test (shown in Table 6). Questionnaire total Cronbachs Alpha value is 0.851, the dimensions of Cronbachs Alpha values are far greater than 0.65, so after factor analysis of 19 test items is stable and reliable.

4. Discussion strategies

4.1. Strengthening environmental facilities

Consumers usually know a club through media or friends. They often evaluate the club from the club's external image, traffic, and then decide whether they will come to this club (Qingshan Hu, Zhan Shen, 2015).

So the clubs should strengthen their external image. The choice of site should be scientific and reasonable. The club is the direct place for customers to enjoy the service, and it should be arranged scientific and healthy. So a spacious and comfortable club with high quality fitness facilities will be the attracting point for the consumers.

4.2.Optimizing course structure

Fitness clubs should set special courses according to the requirements of all kinds of consumers. The club should improve continuously the open breadth and depth of course, listen carefully to the reasonable opinion of the club member, and optimize the structure of course (Xuejuan Chen, Xiaohong Niu, 2014). Besides keeping the original number of fitness groups, it is necessary to expand the new consumer groups. It is important to improve the profitability of the club for the purpose of the development of the club.

4.3.Enhancing service awareness

Commercial fitness clubs mainly focus on the white collar, while the white collars pay more attention to the quality of service. So the club should enhance service. It is needed to improve the overall quality of staff, including their professional skills, education level, etiquette, professional ethics and other aspects. Service consciousness is a kind of instinct and habit of service staff, which can be formed by training, education and training. The fitness club should regularly do the training on the service and make the relevant regulations for the examination. A good sense of service can also promote a repeat purchase of consumers, which has a positive meaning for the development of fitness club (Yun Tang, 2015).

4.4.Setting flexible and diverse charges

The charges of commercial fitness club have relatively large span to meet the needs of various types of consumers. The fee of course suits a variety of occupations, and all kinds of income groups can find a suitable club, so people who love fitness will be direct beneficiary. Nowadays, courses of Fitness club are set for relatively concentrated consumer groups and can only meet some demand. For people with low income, the course fee is still relatively high. So it is a great loss for the national fitness. The fitness club should supply a variety of health services and to develop a flexible charging standard to meet the needs of different groups of people.

4.5. Improving the coaching level of personal instructors

Because of their high income and high propensity to consume, most of the club members need personal instructor and private teaching. So the fitness instructors should have rich professional knowledge and higher professional quality of teaching theory and service skills to be more competitive. Otherwise the fitness instructors should also practice basic skills, improve their self-efficacy, and strengthen depth, breadth and expanding frontiers of the professional field.

5. Conclusions

In summary, it has been found out that the fitness club customer satisfaction model includes 5 factors through exploratory factor analysis and confirmatory factor analysis, that is environmental facilities, teaching design, logistics service, price and coaching. Through the analysis of exploratory factors, customer satisfaction of the fitness club includes 5 dimensions, the environment facilities factor, teaching setting factor, logistics service factor, price factor and coaching factor, and 19 test indicators. Through the investigation of the satisfaction of the members of the commercial fitness club, the main factors which affect customer satisfaction are found, and the corresponding measures are put forward to improve the customer satisfaction. The club should strengthen environmental facilities, optimize course structure, enhance service awareness, Set flexible and diverse charges, and improve the coaching level of personal instructors. And the using of the method above makes the test content of the fitness club customer satisfaction model more objective and accurate (Xinxin Feng, 2014).

Recebido/Submission: 05/05/2016

Aceitacao/Acceptance: 19/07/2016

References

Bo He, Gege Li. (2015). Zig Bee-based wireless fitness data acquisition system. Information Technology, 23(5), 35-43. doi: 10.13274/j.cnki.hdzj.2015.05.035

Cheng Deng, Yanhui Zhu. (2016). Study on the Fitness Club Membership Data Mining Based on C4.5 Algorithm [J]. Journal of Hunan University of Technology, 28(6), 539-543.

Guoying Yuan. (2015). The Development of Community Sports Fitness Clubs inBeijing. Journal of Capital University of Physical Education and Sports, 27(3), 219-222. doi: 10.i4036/j.cnki.cnii-45i3.2015.03.006

Kikot T., Fernandes S., & Costa G. (2015). Potencial da aprendizagem baseada-em-jogos: Um caso de estudo na Universidade do Algarve. RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao, 16, pp. 17-29. Doi: 10.170i3/risti.i6.17-29.

Qingshan Hu, Zhan Shen. (2015). Empirical Study of Effects of Demographic Variables on Brand Loyalty of Commercial Health Club. Journal of Wuhan Institute of Physical Education, 49(4), 29-38. doi: 10.15930Zj.cnki.wtxb.2015.04.005

Quinonez Y., Luzardo G., & Granda R. (2016). Implementacion de un sistema multitactil en ambientes educativos para promover y facilitar la evaluacion del trabajo colaborativo en el aula. RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao, 17, pp. 57-65. Doi: 10.170i3/risti.17.66-79.

Tangxun Yang. (2014). Design and Practice on BD Health Club Membership Information System. University of Electronic Science and Technology of China, 35(1), 40-46.

Tao Chen, Xinghan Li. (2014). Brand Positioning of Chinese Fitness Clubs from the Shumin Qiu. (2013). The Application of Computer and Network Technology in Fitness Work. Sport Science and Technology, 21(1), 40-46. doi: 10.14038/j.cnki. tykj.2013.01.021

Xinxin Feng. (2014). Models of the Government Purchasing Public Sports Services. Sports & Science, 35(5), 45-48. doi: 10.13598Zj.issn1004-4590.2014.05.009

Xiuling Cao, Haiyan Zhao. (2014). Investigation Analysis on the Present Situation and Influence Factors of the Expense Group of Fitness Club in China. Journal of Guangzhou Sport University, 34(4), 20-24. doi: 10.13830/j.cnki.cn44-1129/ g8.2014.04.006

Xuejuan Chen, Xiaohong Niu. (2014). A Study China's Fitness Market Personnel Demand and the Personnel Training situation of Social Sports Specialty. Sports & Science, 35(4), 80-84. doi: 10.13598Zj.issn1004-4590.2014.04.017

Xuetao Tang, Caiming Xu. (2014). Research on the Influence Factors of Customer--satisfaction in Jiangsu Province Fitness Clubs. Sports & Science, 35(2), 78-82. doi: 10.13598Zj.issn1004-4590.2014.02.015

Yun Tang. (2015). Social responsibility of the community sports fitness clubs in China. Journal of Shandong Sport University, 31(2), 16-21. doi: 10.14104/j.cnki. 1006-2076.2015.02.004

Zheng Xiang

xiangzheng916@sohu.com

School of Sport, Hubei University for Nationalities, 445000, Enshi, Hubei, China
Table 1 - Basic information of research object (N=795)

                                 Sex

Item                      Male   Female   %

18 years old and below    30     33       5-5%
19-24 years old           72     142      18.6%
25-34 years old           256    430      59-6%
35-45 years old           32     98       11-3%
46 years old and above    23     35       5%
N                         413    738

Table 2 - The distribution and recovery of the questionnaire (N=795)

District    Distribution   Recycling   Valid
            number         number      number

Hongshan    160            148         136
District

Wuchang     165            153         143
District

Qiaokou     145            125         119
District

Jiang'an    165            146         138
District

Jianghan    160            141         126
District

Total       795            713         662

District    Rate of        Efficiency
            recovery (%)   (%)

Hongshan    92.50          91.89
District

Wuchang     92.73          93.46
District

Qiaokou     86.21          95.20
District

Jiang'an    88.48          94.52
District

Jianghan    88.13          89.36
District

Total       89.69          92.85

Table 3 - Test item of fitness club customer satisfaction

Item    Index

A1      Fitness equipment type and quantity
A3      Club surroundings
A5      Fitness environment comfort
A7      Security facilities
B2      Fitness classes
B4      Update teaching content
B6      Group setting arrangement
C2      Service personnel initiative
C4      Ability to solve problems
C6      Service perfection
D2      Charge price is reasonable
D4      charging standard
D6      Private teaching standards
E2      Care for members
E4      The image qualities of coaches
E6      The coach teaching attitude
E8      The coach teaching way
Item    Index

A2      Configuration of fitness equipment
A4      Fitness atmosphere
A6      Indoor ground construction
B1      Club Health Seminar
B3      Fitness project settings
B5      Rich teaching content
C1      Sanitary condition
C3      Service and communication skills
C5      Additional services provided
D1      Preferential measures
D3      Club payment method
D5      Charging projects set up
E1      The teaching level of the coaches
E3      Coaches professional quality level
E5      Coach's guidance ability
E7      The coach teaching methods

Table 4 - Results of the exploratory factor analysis
of customer satisfaction in fitness club (N=562)

Item              Factor 1   Factor 2   Factor 3

A1                0.745

A3                0.758

A4                0.695

A5                0.647

A6                0.534

B1                           0.673

B2                           0.705

B3                           0.761

B4                           0.694

C1                                      0.630

C2                                      0.749

C3                                      0.756

C6                                      0.595

D1

D2

D3

E1

E2

E5

Characteristic    2.889      2.555      2.383
value

Variance          13.759     12.168     11.347
Explained (%)

Cumulative        13.759     25.926     37.273
Variance
explained (%)

Item              Factor 4   Factor 5   Extracting
                                        common degree

A1                                      0.585

A3                                      0.611

A4                                      0.515

A5                                      0.451

A6                                      0.504

B1                                      0.550

B2                                      0.559

B3                                      0.610

B4                                      0.547

C1                                      0.503

C2                                      0.622

C3                                      0.588

C6                                      0.553

D1                0.780                 0.697

D2                0.872                 0.812

D3                0.784                 0.686

E1                           0.718      0.564

E2                           0.735      0.627

E5                           0.552      0.479

Characteristic    2.376      1.775
value

Variance          11.313     8.453
Explained (%)

Cumulative        48.586     57.039
Variance
explained (%)

Table 5 - KMO and Bartlett Spherical test (N=562)

Sampling sufficient                             0.850
Kaiser-Meyer-Olkin

Bartlett test of       Approximate chi square   3828.073
Spherical degree

                       df                       210

                       Sig.                     0.000

Table 6 - Cronbachs Alpha reliability (N=562)

                            Cronbachs Alpha   item number

Environmental facilities    0.761             5
Teaching design             0.755             4
Logistics service           0.713             4
Price setting               0.837             3
Coach                       0.785             3
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Author:Xiang, Zheng
Publication:RISTI (Revista Iberica de Sistemas e Tecnologias de Informacao)
Date:Sep 1, 2016
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