Keywords

1 Introduction

1.1 Research Background

Despite being the world’s largest mobile game market, Japanese mobile game market has faced slower growth since 2013, when the market began to be saturated. By comparison, however, in Chinese mobile game market, Internet companies have devoted more energy to developing mobile games successively since the second half of 2013. As a large quantity of mobile games are launched in the market, mobile games will be undoubtedly become the new growth point of mobile internet.

According to Japanese authoritative market research agency cyber-z’s report (Fig. 1): Japanese mobile game market size in 2014 was 658.4 billion yen, 2015 growth forecast to 746.2 billion yen (Growth rate of 13 %), and it will growth forecast to 823.8 billion yen in 2016 (Growth rate of 10 %). Chinese mobile game market size in 2014 was 380 billion yen, 2015 growth forecast to 574 billion yen (Growth rate of 51 %), and it will growth forecast to 778 billion yen in 2016 (Growth rate of 36 %).

Fig. 1.
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Mobile game market’s revenue growth rate comparison between Japan and China [11]

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The mobile game developed based on the application of social networking service is an interactive behavior that enhances the exchange between people through games. Both Line of Japan and WeChat of China have attracted a large number of users. In Japan, Line has 49 million users, taking up 37.6 % of Japanese population. With the number of monthly active users arriving at 438 million, WeChat has developed into the necessity of Chinese mobile phone users. Supported by the broad customer base, Line and WeChat have established their respective mobile phone platform as its important source of income. For instance, Line achieved a year-on-year growth of 104.2 % in the third quarter of 2014.

Chinese mobile game industry started late compared with that of Japan, but its market size expands rapidly. The internet process of Chinese society and economy has laid a foundation for the application and user attraction of mobile internet. In China that witnesses an explosive growth in the number of smart phone users, mobile game shows a promising prospect.

1.2 The Raising of Questions

As shown by these astonishing data, the development of mobile games hits bottlenecks: the problems such as the severely homogenous game, the short life cycle, the high churn rate, and low payment rate have perplexed the developers and operators of mobile game. Different from the massively multiplayer online game (MMOG) with the life cycle of five to seven years, present mobile game products have a shorter life cycle, normally reaching 6 months.

How to upgrade the customer loyalty of mobile games has become a concern of mobile game industry as well as a conundrum that every game developer has to solve while improving their competitive strengths.

Since Philip Kotler who is honored as the Father of Modern Marketing proposed the question of how enterprises should develop competitive strengths in the 1980s, neither academic community nor business community has ceased the exploration on this question. Afterwards, since Kotler put forward the concept of Marketing 3.0 in 2010, customer orientation has been mentioned and studied frequently. Customer perceived value is the real value of the products or services that enterprises provide for customers. Only when the largest perceived value is created for customers, can customer satisfaction be improved and customer loyalty be built to sustain the competitive edge of enterprises.

The research focus is the influence that customer perceived value of mobile phone has on customer satisfaction and loyalty, and meanwhile, the customer perceived value management method of mobile games is presented accordingly. Besides, suggestions on the development and operation of mobile game enterprises are proposed to help enterprises understand their competitive edges in market.

1.3 Research Objective and Significance

The research is intended to explore the customer perceived value management method of mobile games. Below are the specific research objectives:

  1. 1.

    Analyze the influence that customer perceived value of mobile games has on customer satisfaction;

  2. 2.

    Analyze the influence that customer perceived value of mobile games has on customer loyalty;

  3. 3.

    Make a comparative analysis about the influence that customer perceived value of Chinese and Japanese mobile game users has on customer loyalty;

  4. 4.

    Explore the method to manage customer perceived value of mobile games.

After consulting a large amount of literature, the author finds that customer perceived value has not been widely applied as a research tool in a specific industry in China and Japan yet. Currently, there is little attention paid to the systematic study on the customer perceived value in mobile game industry. Thus, this study is intended to expand the application scope of customer perceived value theory, and introduce it into the study on mobile game industry.

1.4 Research Methods

1. Literature research method

The meanings of mobile game, customer perceived value, customer satisfaction and customer loyalty are made clear by means of literature research and theoretical analysis in an attempt to provide theoretical support for research.

2. Questionnaire survey

In order to conduct a preliminary study on the mechanism in which customer perceived value exercises an influence over customer loyalty, energy is devoted to making an experimental survey and analyzing the survey result to further confirm the questionnaire items before questionnaire research, which is intended to guarantee the referential value of the data obtained in the formal questionnaire survey.

3. Empirical analysis

Based on literature research, the theoretical model regarding the influence of customer perceived value on customer loyalty and satisfaction is built and relevant hypotheses are presented. Additionally, SPSS 22.0 software is utilized to make reliability, validity, correlation, regression and factor analyses on the survey data for the purpose of verifying the hypotheses proposed herein and bringing forward relevant management suggestions.

2 Literature Review

2.1 Concept of Customer Perceived Value

Scholars from home and abroad have made numbers of studies on the concept of customer perceived value, but there is still a lack of a unified definition. As indicated by the definition of customer perceived value given by Philip Kotler, customer perceived value = total customer value + total customer cost. Total customer value refers to the benefits that customers expect to achieve from a certain product or service, and total customer cost to the estimated expenses arising from customer’s evaluation, obtainment and use of the product or service.

From this study, a conclusion that the core of customer perceived value is the trade-off between perceived benefits and perceived sacrifices is drawn. Thus, there are two approaches to elevating customer perceived value, raising perceived benefits or lessening perceived sacrifices. However, due to individual difference, customers vary from each other in the perceived value of the same products or services.

2.2 Dimensions of Customer Perceived Value

According to the studies on the dimensions of customer perceived value in a large amount of literature, the dimensions of customer perceived value will change with products and markets though the customer perceived values in different industries and domains have different compositions and the customer perceived values at home and abroad vary in composition model. On the whole, however, these dimensions of customer perceived value mainly reflect two aspects including perceived benefits and sacrifices, and different scholars have developed different understandings of the embodiments of perceived benefits and sacrifices.

According to the description on the dimensions of customer perceived value in Marketing 3.0 of Philip Kotler, and the previous research achievements regarding perceived value theory of online games, the hypothesis that the perceived value of mobile games encompasses at least 5 dimensions is proposed, including functional value, emotional value, social value, monetary cost, and non-monetary cost. Meanwhile, empirical study is conducted to verify and study the relationship between these dimensions and customer satisfaction and loyalty.

2.3 Concept of Customer Satisfaction and Loyalty

In 1988, American scholar Fornell combined structural equation with mental path of satisfaction formation to propose a new satisfaction model, which has laid a foundation for the building of national satisfaction index models in countries worldwide. Based on this model, SCSB was presented by Sweden and then ACSI and ECSI were developed successively. In 2009, Japan put forward Japanese Customer Satisfaction Index (JCSI for short), which has been widely applied in different industries. The theoretical model of this study is also derived from JCSI, with the major factors including expectation, perceived quality, perceived value, satisfaction, complaints and loyalty. Of these factors, expectation, perceived quality and perceived value are factors that create satisfaction, and then satisfaction will lead to complaints and loyalty (Fig. 2).

Fig. 2.
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Japanese customer satisfaction index

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2.4 The Building of Theoretical Model

The theoretical model of this study is built based on the review and analysis of relevant literature and theories (Fig. 3).

Fig. 3.
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Academic framework

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3 Research Methods

3.1 Research Objective

The research respondents are mainly constituted by smart phone users. Since the questionnaire survey is implemented in both China and Japan, the author focuses attention on college students or the youth in the society, most of whom are smart phone users often playing mobile games and able to provide data support and reference for this study.

The respondents of this study are the mobile game users in the social circle of the author, and the questionnaire survey is made through paper questionnaire, the third-party questionnaire platform, online chatting tools, and email, and the data are collected by various approaches such as interview.

3.2 Questionnaire Design

This study explores the influence that customer perceived value exerts on customer satisfaction and loyalty, as well as the interactive mechanism of all influencing factors by means of questionnaire. The questions relevant to customer perceived value, customer satisfaction, and customer loyalty in this study are derived from previous research achievements.

The questionnaire is made up of ten parts. The first part asks whether the respondents have smart phones and when they use smart phones. The second part is about the name of user’s favorite mobile game. The third part makes a survey on the recreational value of the mobile game. The fourth part pays attention to emotional value of the mobile game. The fifth part relates to the social value of the mobile game. The sixth part revolves around user’s perception on the monetary cost of the mobile game. The seventh part investigates user’s perception on the non-monetary cost of the mobile game. The eighth part focuses attention on users’ satisfaction with the mobile game. The ninth part lays stress on user’s loyalty to the mobile game. The final part collects the information regarding demographic characteristic variables such as gender and age of users, as well as the behavioral characteristic variables of game players, such as game-playing time and the favorite mobile game type (Table 1).

Table 1. Resource of scales
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4 Data Analysis

4.1 Collection of Experimental Survey Data and Sample Description

The respondents of the experiment are the Japanese college students that the author got acquainted with while participating in the exchange activity in Japan. The respondents from different universities are randomly and representatively selected. This survey, carried out in the form of paper questionnaire, involves 30 respondents, and 5 questionnaires are found ineffective because they are obviously inauthentic or the respondents are not mobile game players. As a result of this, there only are 25 effective questionnaires, with the effective collection rate standing at 87.3 %. The basic descriptive statistical data of effective samples are shown in Fig. 4.

Fig. 4.
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Sample constitutes

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4.2 Reliability Analysis

Reliability analysis is intended to analyze the consistency level of the results obtained by one evaluation method and meanwhile judge the reliability of the evaluation through the degree of consistency. The reliability of the test result is closely associated with the degree of the influence that the errors exert on the test result.

According to reliability analyses, Cronbach alpha (α) is the index that depends most heavily on evaluation reliability. Developed by Cronbach in 1951, α is frequently applied to estimating the systematic variations on the variable of every factor. The higher the reliability coefficient α is, the more systematic the variables of the factor will be.

American statistician Hair et al. (1988) insisted that when Cronbach α > 0.7, the data are highly reliable, and when the number of items in measurement is smaller than 6 and Cronbach α > 0.6, the data are reliable.

The internal consistency coefficients of all variables and corresponding measured items are calculated by means of SPSS 22.0 software, with the calculation result shown in Table 2. All the internal consistency coefficients (Cronbach α) of the variables designed in this study are greater than 0.6, which suggests that the variables of the study are highly reliable.

Table 2. Cronbach α analysis of questionnaire
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4.3 Exploratory Factor Analysis

Firstly, there is a need to make factor analysis on customer perceived value. When KMO is 0.546, factor analysis can be performed.

According to principal component analysis, 3 factors are extracted from customer perceived value. It is found that the cumulative explanatory variance is 0.672, greater than 0.5, which implies that these 3 factors can embody sample information effectively. The factor loading matrix derived from the maximum rotation of variance is shown in Table 3. According to factor connotation analysis, factors 1, 2 and 3 have reflected customer perceived value of mobile games, which proves that customer perceived value of mobile games include at least three dimensions, namely, functional value, emotional value and social value.

Table 3. Exploratory factor analysis
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5 Research Limitations and Future Research Plan

5.1 Research Limitations

In this paper, some achievements have been made by studying and empirically analyzing the influence that customer perceived value of mobile games has on customer satisfaction. This study, however, still shows varieties of deficiencies as a result of insufficient time, energy and ability.

  1. 1.

    There is a lack of samples since experimental investigation is the only focus.

  2. 2.

    Little consideration is given to the effect of control variables such as income and educational level and the influencing factors such as frequency of play and game type on satisfaction and loyalty of mobile game customers.

  3. 3.

    The difference between mobile game users of China and those of Japan fails to be analyzed comprehensively from the perspective of game development history.

5.2 Future Research Orientation

Based on the abovementioned research limitations, the study on customer perceived value of mobile games can be conducted from following angles:

  1. 1.

    To expand sample size and diversify the source of respondents. Currently, preparations have been made to conduct a questionnaire survey on the coastal regions of Mainland China and carry out group analysis and research based on user background in March 2015. Meanwhile, the difference in the influence that customer perceived value factors has on customer satisfaction is verified with the hope of helping game developers develop the satisfactory games for customers in different regions.

  2. 2.

    To extend association study. Customer perceived value involves the contents of the disciplines such as consumer psychology, marketing and management. Therefore, in the future, focus can be placed on interdisciplinary study to make the improved theory and model more adaptable to different disciplines.