Keywords

1 Introduction

1.1 Background

Internet and technology have accelerated the development of wearable fitness device and fitness APP market, providing convenience and fitness guidance for users’ self-healthy management. In China’s fitness app market, 75% fitness APPs did not match wearable devices, Only 25% matched [1, 2]. The physical comfort and aesthetical of wearable devices satisfied users both physically and mentally. However, the associated application also affects the overall user experience. In addition to the real-time tracking of sports data and body physiological data, most of the visual display of self-information and fitness reports mainly depends on the related mobile application. Therefore, the paper aim at Fitness Guide App as the research object.

1.2 Research Significance

At present, most research on user loyalty focus on traditional online shopping [3, 4], and some scholars have also studied on the factors that influence the loyalty of using wearable fitness devices [5,6,7]. However, a holistic loyalty impact analysis of the applications they are associated with is rarely seen. This paper will study the factors that influence the user loyalty in the mobile fitness community and validate four related factors to loyalty: Transaction costs, Motivation, Usability, trust [6] to provide specific case studies for relevant practitioners and academic researchers.

2 Theoretical Framework

The research framework of this paper draws on the individual cognitive model of perception-emotion-intention [2, 8]. It has three stages: perceive information, forms preference and finally constitutes the corresponding intention. On the basis of this research framework, this paper analyzes the mediating effect of trust on loyalty, verifies the relationship between Transaction costs, motivation, usability, trust [6], and loyalty, among the four factors.

2.1 Perceived Elements

According to the literature research, this paper sums up three elements of perceived content: transaction cost, usability and motivation. When choosing store or brand, users need to consider the transaction cost and risk. Traditional asset specificity has different forms, including manpower attribute, time attribute, money attribute, location attribute and so on. Usability is user’s impression and experience of using product, which is changed through time. There is no denying that UED is one of the elements to win user’s trust. Usability has always been one of the most important research issues in human-computer interaction. Structure arrangement, interface and interaction design all affect user’s product perception. Normally, the use of products is driven by different motives. The theory of motivation is very rich, contain Maslow’s hierarchy of needs and Aldrich’s erg theory. The other is process motivation theory, which focuses on the psychological changes between motivation and behavior, contains the theory of reinforcement motivation, goal incentives, expectations and rewards. They have gradually been used and become one of the important theoretical foundations of the human-computer interaction behavior analysis.

2.2 Emotional Element

The emotional element is expressed as trust. Trust is the relationship between user and product, which means contact with producer, service provider and program builder. Trust creates loyalty to attitude and action. Researchers have suggested that trust is an important factor that affects brand loyalty [6]. Brand trust can bring loyalty, the needs of designing trust and motivation mechanism is just as important as usability assessments.

2.3 Intentions

The establishment of e-commerce loyalty is a complex and cumulative process. The measure of loyalty includes two aspects: behavior intention and attitudinal intention. Blackman and Crompton propose that behavior of loyalty including: direct consumption, preferences and making recommendations to others; attitudinal loyalty shows as being immunity to other competing brands and having high price tolerance.

3 Hypothesis Based on SEM Model

3.1 The Influence of Transaction Cost, Usability, Motivation, Trust on Loyalty

The cost of using a new App or buy related product in a new online store includes not only the price of the product, but also the time costs to compare different brands and confirm the process before purchasing [9]. Werner websphere and Ratchford proposed that the construction of nontransferable skills need to be taken into consideration when talking about loyalty. In the case of fitness app, similar perform regulations can reduce the cost of learning. And users prefer to use the current product when competitors have the similar interface design.

  • H1a: Low transaction cost of fitness guidance bring more loyalty for fitness APPs.

Nielsen believes usability means that people can easily and efficiently learn and use the basic functions of the App. According to ISO/IEC 9126-1, Usability is attractive and easy to use which related to the properties of product [10]. Searching, shopping or inputting information online, every decision is a reaction from interface and functional design [11]. Bevan believes usability is a determining factor in end-brand loyalty.

  • H2a: Usability of mobile fitness Apps has an attractive influence on loyalty.

Snakin believes that human behavior is a function of received stimulation. If the stimulation was benefit to him, the behavior would repeat; If it is to his disadvantage, it will weaken and even disappear. Users who aim to lose weight are more likely to use the practice function, while those who focus on social motivation are more likely to use the fitness activity recording that can be shared. Online fitness community users are more likely to be goal-driven than non-OFC users and are more focused on goal - achievement [12]. Therefor according to different goal setting, various motivational reinforcement methods can be adopted to help people adjust their behavior and realize their self-achievement.

  • H3a: Motivation stimulated user’s loyalty of fitness APPs.

Cha argued that the trust mechanism of e-commerce has three independent dimensions: consumer behavior dimension, institutional dimension and technical dimension. Depending on users’ cultural background, the degree of uncertainty about risk avoidance varies [13]. Bivouque and Brislin found that the characteristics of the western members under the influence of individualism were self - reliance, competition, trust of others, and utilitarianism in exchange and competence [14]. Utilitarianists have a high tendency to trust, and individualists believe in others until there is a reason to distrust them [15]. However, under the guidance of collectivism, the Oriental users prefer to trust the people in the group. So, their trust will easily be affected by the experience and evaluation of their relatives, friends and colleagues. Products in different cultural backgrounds should adopt different trust-building systems.

  • H4: The trust of fitness Apps has attractive effect on user loyalty.

3.2 The Relationships Among Transaction Cost, Usability, Motivation and Trust

Other people’s using experience can influence self-willingness to buy and use [16]. EWOM (Feedback and Evaluation of Other Buyers) can help to dispel user’s doubts and reduce the cost of searching information and moral hazard [17]. When a product or service offers a price discount and sales, the user perceives that the cost of the transaction is reduced, and the willingness to purchase and use increases [18]. For example, filters with costs provided by photo-social networking sites are free for seven days’ trail, reducing the cost of investing.

  • H1b: Low transaction cost of fitness guidance bring more trust on fitness APPs.

Friendly interface design, high quality fitness content, in-time feedback will bring pleasure and satisfaction to users. Obvious entrance of function, fluent using and creative interface design attracted more users’ trusty. Fast shopping processing and visualized information can increase trust effectively. Today, the main parts of fitness App contains video or graphic teaching, data tracking, planning and management, sporting, online malls. The reasonable organization of these resources makes it easy for users to use. In the models presented by Werner Derech and Ratchford, products also need to add non - transferable skills to maintain users’ loyalty on the product [9].

  • H2b: The usability of mobile fitness App has an attractive effect on trust.

Motivation-hygiene theory (Frederick Herzberg 1966) pointed out that the motivational factor is easy to satisfy users, but without it, the user will not be dissatisfied. Conversely, when hygiene is absent, users quickly feels dissatisfied. Japanese scholars have proposed that H factor is the necessary condition of user’s emotion identification, and M factor is the charming condition of enhancing emotion recognition. [6] Rupp considered motivational support and technical trust to be important factors in the continued use of wearable fitness devices. In the aspect of structure and visual design of the product, considering how to stimulate the user’s motivation. Making the user use continuously, even become the nontransferable user’s skill. It is very important to keep the loyalty of the product from the beginning to the end.

  • H3b: Motivation has a positive effect on fitness APPs trust.

Researchers have discussed the determinants of loyalty in different areas [6]. This paper makes minor modifications to their research and presents the relationship between trust, motivation, transaction cost, usability and loyalty for fitness Apps, and seven hypotheses are presented as the below table (Table 1).

Table 1. Hypotheses model
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4 Research Methodology

4.1 Measurement of Variables

There are five variables in this study, trust [6], motivation [7], Transaction costs (Williamson 1985) and usability, four exogenous variables, loyalty is endogenous variable, Questionnaire test is used to collect data contained 27 items, seven of which were basic personality information problems about the sample, including sex, career, whether using fitness software. The rest of 20 questions were investigated by Likert Five Scale, and each variable is tested by four items. In order to ensure the reliability and rigor of the study, the scale was designed referring previous study. Using Amos to analyze the structural equation of the theoretical mode, which is convenient to deal with the sample with small data quantity accurately (Table 2).

Table 2. Question scale
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4.2 Data Collection

With the help of the questionnaire star system platform, the distribution and recovery of the questionnaire were carried out. Consumption is the primary indicator of e-commerce, however, as for fitness activities, to some extent, is pursuing self-respect. Chinese scholars used the Answer Tree model to investigate and find out that the difference of using fitness Apps is strongest effected by education background, secondly, region. The utilization rate in urban areas and above is higher than that in counties. Therefore, the sample of this paper comes from Shanghai and Guangzhou, two first-tier cities in China. 500 responses were received, excluding those uncompleted, 456 responses valid. 28.9% of valid samples were male and 71.1% were female, 75.6% have the experience of using fitness App.

5 The Experimental Analysis

5.1 Reliability and Validity Analysis

By using spss software, the internal consistency reliability of the questionnaire is analyzed, and the coefficients are calculated as shown in the table below (Table 3).

Table 3. Reliability statistics
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According to the reliability test of the variables studied, cronbach’s value is 0.875, which is greater than 0.8. It can be seen that the measurement indexes of variables have higher internal consistency reliability.

The validity of the data was tested by KMO and Bartlett sample measure. The closer KMO is to 1, the more efficient the data. Experience shows that KMO is greater than 0.9, indicating that the data is very efficient, KMO between 0.8 to 0.9 indicates that the data is valid, while under 0.5 the data need to be re-collected (Table 4).

Table 4. KMO and Bartlett’s test
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The validity value of KMO is 0.845, which is more than 0.8, indicating that the research data is quite effective. The significance value of bartlett’s spherical test was 0.000, less than 0.01, therefore the relationship between variables is strong and the data validity of this study is good.

5.2 Confirmatory Factors Analysis

In this study, the maximum likelihood method is used for confirmatory factor analysis. In the evaluation of model adaptation degree by confirmatory factor analysis, it is advisable to consider simultaneously the indicators of Absolute Fit, Value-added Fit and Reduced Fit: (1) Generally speaking, X2/df is between 1 and 3 to show that the model has the degree of reduction and adaptation, and more strict adaptation criterion is between 1 and 2. (2) The value of RMR should be as small as possible, and RMR < 0.1 is an acceptable adaptation model. (3) The three indexes of value-added adaptation, TLI, IFI and CFI, are all good for model adaptation with >0.8. (4) The other two indicators, PGFI and PNFI, are all expressed as acceptable models in the range >0.5 (Table 5).

Table 5. Multi-factor structural validity analysis
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It can be seen that all the hypothesis models are within the acceptable range and reach the ideal standard. Therefore, the theoretical model can fit the empirical data structure, and the adaptability of the model is good.

5.3 Analysis Path Factors for the Model

The path coefficients between indexes are estimated by the variance calculation and covariance calculation of variables. In the selection of the model, recursive form is generally adopted, and the observed scalars in the regression equation are generally linear, then all path coefficients can be estimated by maximum likelihood estimation method. Using Amos software to calculate the coefficients is as follows (Table 6).

Table 6. Standardized regression coefficient and significance test
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The fourth column, C.R., is the test statistic (critical ratio) and the critical ratio is the t value of the t-test. When this value is greater than 1.96, the preceding regression coefficient has reached a significant level of 0.05, The value of p in the fifth column is significant. If p < 0.001, it is denoted by the symbol “***”, and if p is >0.001, the value of p is directly rendered. As can be seen from the table, there are 5 hypotheses are correct (Table 7).

Table 7. Results of hypotheses model
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From the above table, P value of motivation and usability is more than 0.05, indicating that motivation and usability have no significant effect on loyalty. However, usability (0.134, P < 0.01), motivation (0.471, P < 0.001) had positive effect on trust, motivation had the greatest influence on trust. Transaction cost (−0.230, P < 0.001) had negative relation to trust, meanwhile had a significant negative impact (−0.230, p < 0.001) on loyalty. Trust (0.227, p < 0.05) had a significant positive effect on loyalty. In conclusion, for transaction cost, trust has a partial mediating effect on loyalty. As for motivation and usability, trust has a complete mediating effect on loyalty.

6 Results and Discussions

In the observation index, behavior intention has better effect on loyalty than attitude intention. Purchasing paid courses and fitness device on fitness Apps is the best expression of loyalty. The experimental results agree with our previous hypothesis that transaction costs have the greatest effect on loyalty. Reduce the transaction costs will increase loyalty and trust.

The effect of usability on loyalty is not significant. It might because, with the popularity of smartphones, Apps’ interface design is mature and has become the basic element of user loyalty, not the charm condition. As for the result that motivation does not significantly influence the trust, it may be affected by personality, educational background and self-recognition, which are unconcentrated in this paper. The small sample size of the experiment, of course, does not represent all people’s views on loyalty. However, this paper can serve as a case study and reference for academics and fitness software practitioners.

Today’s mobile fitness APPs can not only track users’ movement timely, but also intelligently recommend fitness information and instructions that meet the different needs of different users. In addition to well-conduct online fitness platform operation, online fitness platform is also gradually developing offline fitness sphere. How to maintain the relationship between community users and products will affect the development of online fitness community in the future. In the future research, we can study these potential variables affected by time and other regions to complete the theory and provide case study of digital fitness community loyalty.