Identify critical factors affecting the customer switching behavior for mobile service providers in vietnam

VIETNAM NATIONAL UNIVERSITY-HCM CITY INTERNATIONAL UNIVERSITY  IDENTIFY CRITICAL FACTORS AFFECTING THE CUSTOMER SWITCHING BEHAVIOR FOR MOBILE SERVICE PROVIDERS IN VIETNAM In Partial Fulfillment of the Requirements of the Degree of MASTER OF BUSINESS ADMINISTRATION In International Buisiness Major By Ms: Lam Thi Cam Tam ID: MBA05036 Advisor: LE THANH LONG, PH.D International University - Vietnam National University HCMC August 2014 IDENTIFY CRITICAL FACTORS AFFECTING THE CUSTOMER SWITCHING BEHAVIOR FOR MOBILE SERVICE PROVIDERS IN VIETNAM In Partial Fulfillment of the Requirements of the Degree of MASTER OF BUSINESS ADMINISTRATION In IB major by Ms: Lam Thi Cam Tam ID: MBA05036 International University - Vietnam National University HCMC August 2014 Under the guidance and approval of the committee, and approved by all its members, this thesis has been accepted in partial fulfillment of the requirements for the degree. Approved: ---------------------------------------------Advisor: Dr. Le Thanh Long ------------------------------------------Chairperson ---------------------------------------------Committee member ------------------------------------------Committee member ---------------------------------------------Committee member ------------------------------------------Committee member Acknowledgement I wish to express my deepest appreciation and gratitude to all the people that have contributed to the completion of this dissertation. On the first line, I would like to express my thanks to International University – Nation University as a whole, especially the useful assistance and prompt feedback from teaching staffs and officers as well. A lot of knowledge as well as many skills that I had not ever possessed before have had from the MBA program almost two years. I had a great fortune to study under supervision of Dr. Le Thanh Long. I am very grateful for his guidance and encouragement. His profound knowledge provided me with an opportunity to broaden my knowledge and to finish this thesis. My gratitude is dedicated to my classmates and friends who always stand beside one and give me the valuable support and recommendation. Last but not least, special thanks also to my family for their ever-present love and support. Lam Thi Cam Tam Ho Chi Minh 2014 i LIST OF ABBREVIATION Abbreviation Equivalence ARPU Average revenue per user CL Customer lock-in MSP Mobile service provider MNP Mobile number portability PP Price SC Switching cost SQ Service quality ii Plagiarism Statements I would like to declare that, apart from the acknowledged references, this thesis either does not use language, ideas, or other original material from anyone; or has not been previously submitted to any other educational and research programs or institutions. I fully understand that any writings in this thesis contradicted to the above statement will automatically lead to the rejection from the MBA program at the International University – Vietnam National University Ho Chi Minh City. ii Copyright Statement This copy of the thesis has been supplied on condition that anyone who consults it is understood to recognize that its copyright rests with its author and that no quotation from the thesis and no information derived from it may be published without the author‟s prior consent. © Lam Thi Cam Tam _ MBA05036 iii Abstract The target of this study is to identify the factors affecting switching behavior in using the mobile service in Vietnamese subscribers. In the conceptual framework model, there were six factors impact to switching behavior including price, service quality, customer lock-in, switching cost collected in two group factors customer satisfaction and switching barrier follow previous hypothesis. Demographic characteristic relate to the level of impact behavior, it is associated with six factors above as intervening variable were also hypothesized to affect switching behavior. The target population for study was the subscribers in Ho Chi Minh City. The author applied quantitative approach as the major method to conduct the study with main statistic technique consisting factor analysis, regression, path analysis. The result found from the study provided clearer understanding for mobile service providers in Vietnam bases on the experimental evidence. It gets whole information from mobile subscribers shown that switching behavior was directly affected by price, switching cost and indirectly by customer satisfaction. Besides, the switching behavior was also indirectly affected by relationship demographic features. With a full overview of switching behavior in telecommunication services in Vietnam, discovering factors impact to switching behavior will be a premise for building strategic marketing and new development of products that Vietnamese providers. From that, plans face with potential competition risk from foreign competitor in future is being prepared. Keywords: switching behavior, mobile services provider, satisfaction failure, alternative attractiveness, brand attractiveness, social influences, switching barrier, and perceived switching cost. iv v Table of Contents Contents List of Tables............................................................................................................... ix List of Figures ............................................................................................................. xi Chapter 1 - INTRODUCTION .................................................................................... 1 1.1. Background of the study .................................................................................. 1 1.2. Telecommunication industry in Vietnam ......................................................... 2 1.3. The Problems statement ................................................................................... 4 1.4. Objectives ......................................................................................................... 6 1.5. Rationale........................................................................................................... 7 1.6. Scope of research ............................................................................................. 8 1.7. Thesis structure ................................................................................................ 9 Chapter 2 – LITERATURE REVIEW ....................................................................... 12 2.1. Switching behavior.......................................................................................... 12 2.2. Impact of switching behavior .......................................................................... 13 2.3. Factors can affect to switching behavior ......................................................... 15 2.4. Conceptual framework model for the research ............................................... 22 Chapter 3 – RESEARCH METHODOLOGY ........................................................... 25 3.1. Research method ............................................................................................. 25 3.2. Research sample .............................................................................................. 25 3.3. Research Methodology.................................................................................... 27 3.4. Data collection ................................................................................................ 30 3.5. Data analysis Techniques ................................................................................ 32 3.5.1. Descriptive statistics ................................................................................ 32 3.5.2. Factor analysis ......................................................................................... 33 vi 3.5.3. Multiple regression .................................................................................. 33 3.5.4. Path analysis ............................................................................................ 33 3.6. Validity Test .................................................................................................... 34 3.6.1. Factor analysis for independent variable ................................................ 34 3.6.2. Factor analysis for Dependent variable .................................................. 37 Chapter 4 - DATA ANALYSIS AND ACHIEVED RESULTS ............................... 41 4.1. Demographic characteristic of the sample ...................................................... 41 4.2. Reliability Test ................................................................................................ 46 4.3. Descriptive statistics of variable ..................................................................... 48 4.4. Factor analysis to Switching behavior ........................................................... 50 4.4.1. Multiple regression .................................................................................. 50 4.4.2. Factor affects to customer satisfaction .................................................... 51 4.4.3. Factor affects to switching barrier .......................................................... 54 4.4.4. Factor affects to switching behavior ........................................................ 55 4.5. Direct and indirect effects of independent on switching behavior ................. 57 Chapter 5 - Conclusions and recommendations ......................................................... 61 5.1. Conclusions ..................................................................................................... 61 5.1.1. Problem recognized from the result of the research ................................ 62 5.1.2. Relationship between switching behavior with influence factors ............ 65 5.1.3. Recommendation ...................................................................................... 68 5.3. Business strategies implies.............................................................................. 70 5.2. Research limitation.......................................................................................... 71 5.4. Suggestions for future research ....................................................................... 72 References .................................................................................................................. 74 APPENDIX A (English Questionnaires) ................................................................... 80 vii APPENDIX B (Vietnamese Questionnaires) ............................................................. 86 APPENDIX C (Cronbach‟s Alpha) ........................................................................... 92 APPENDIX D (Factor loading) ............................................................................... 114 APPENDIX E (Regression Analysis) ...................................................................... 129 viii List of Tables Table 3. 1: KMO and Bartlett's Test for Independent variables ................................ 34 Table 3. 2: Total Variance Explained for Dependent variables ................................. 35 Table 3. 3: Rotated Component Matrix of Independent variables ............................. 36 Table 3. 4: Reliability coefficients of Independent variables arrange follow components ................................................................................................................ 37 Table 3. 5: KMO and Bartlett's Test for Dependent variables ................................... 37 Table 3. 6: Total Variance Explained for Dependent Variables ................................ 37 Table 3. 7: Reliability Coefficients of Dependent Variables ..................................... 38 Table 3. 8: Rotated Component Matrix of Dependent variables ............................... 39 Table 4. 1: Trends 3G on mobile internet .................................................................. 46 Table 4. 2: Interpreting strength of Pearsons correlation ........................................... 47 Table 4. 3: Reliability Coefficients of Independent Variables ................................... 47 Table 4. 4: Reliability Coefficients of Dependent Variables ..................................... 48 Table 4. 5: Descriptive Statistics of Independent variables ....................................... 48 Table 4. 6: Descriptive Statistics of dependent variables ......................................... 49 Table 4. 7: Pearson correlation between independent variables ................................ 51 Table 4. 8: Correlation coefficients between independent variables and its dependent variables ..................................................................................................................... 52 Table 4. 9: ANOVA results on effect of independents on Customer satisfaction ..... 52 Table 4. 10: Correlation coefficients between independent variables and switching barrier ......................................................................................................................... 54 Table 4. 11: ANOVA results on effect of independents on switching barrier ........... 54 ix Table 4. 12: Description and variables‟ Correlation of independents on switching behavior ...................................................................................................................... 55 Table 4. 13: ANOVA results on effect of intermediate variables on switching bahavior ...................................................................................................................... 56 Table 4. 14: Coefficients between dependent variable and SWB .............................. 56 Table 4. 15: Description and variables‟ Correlation of independents on switching behavior ...................................................................................................................... 57 Table 4. 16: ANOVA of independents on switching behavior .................................. 58 Table 4. 17: Coefficients between the independent variable and SWB ..................... 59 x List of Figures Figure 1. 1: Market shares (subscribers) of mobile phone service providers .............. 3 Figure 1. 2: The growth of mobile subscribers in Vietnam from 2004 to 2013 .......... 4 Figure 2. 1: Suggested model ..................................................................................... 23 Figure 3. 1: Progress of researching........................................................................... 31 Figure 4.1: Ratio respondents about providers .......................................................... 42 Figure 4. 2: Distribution follows charge form ........................................................... 42 Figure 4. 3: Distribution rate of Subscriber base on gender ...................................... 43 Figure 4. 4: Distribution rate of Subscriber base on age ............................................ 44 Figure 4. 5: Distribution rate of Subscriber base on income...................................... 44 Figure 4. 6: Distribution rate of type of career........................................................... 45 Figure 4. 7: Number of subscriber distributed on education background of total sample ........................................................................................................................ 46 Figure 4. 8: The practice model of switching behavior ............................................. 60 xi Chapter 1 - INTRODUCTION 1.1. Background of the study Nowadays, there have been many mobile providers with many different service packages given consumers in Vietnam, so Vietnamese consumers have many solutions for choosing mobile providers. In order to receive the best service and maximizing the benefit, satisfaction and minimizing the cost, the consumer usually considers changing more suitable mobile service providers (MSPs). It has increased the pressure of MSPs which must supply services creating satisfaction for their customers to remain and attract customers back or switch to their brand. Moreover, the upcoming introduction of mobile number portability (MNP) to control all mobile subscribe by the government will to emphasize the appearance of a transition period in the mobile telecommunication services market. Therefore, understanding and evaluating what affect customer switching behavior is important. Because a customer‟s switching behavior results in the loss of the future revenue stream from that customer. In particular, switching by a service customer is a loss for a firm‟s high-margin sector of its customer base (Depend Liang, 2012). The cost associated with acquiring new customers, including account setup, credit check, and promotion expenses, can be as much as five times the cost of customer retention efforts (Keaveney, 1995; Peter, 1998). From that, explaining customer behavior why customers choose to stay or switch to their mobile service provider (MSP) in Vietnam become an essential topic for researching. 1 1.2. Telecommunication industry in Vietnam Beginning with a mobile provider in Mobifone brand in 1993, telecommunication in Vietnam officially flow with at telecommunication industry in the world. By itself contribution, Mobifone or mobile service in general in Vietnam opened a new age of information and communication technology plays a role of infrastructure platform to create tools and utilities for developing other sectors as well as improving quality of people's life. Telecommunications has been seen as one of the major factors promoting economic growth in Vietnam. It has proven to be a positive role in promoting development of socio - economic structure, community life and activities of organizations and individuals. . Although formed later than other countries in the region and the world, the mobile telecommunications market in Vietnam developed to a breakneck speed in recent years. Appearance of Vinaphone brand in 1997 created multiform choices of customers with mobile provider services. In 2000, with Viettel brand opened a competitive period on the Vietnam telecommunication market. A small wave of subscribes moved from Mobifone to Vinaphone, from Mobifone to Viettel, from Vinaphone to Viettel besides increasing amount of new subscribes of these providers. With one mobile network from the early days, there have been six MSPs on the market. Furthermore, with the growth of mobile technology faster, shorten cycle technology, cost advantages due to declining investment is a challenge with the old MSP Vinaphone. It broke the single position of Vinaphone. With 6 competitors on the market which apply primarily policies on price cuts and promotions constantly, it has made a wave of subscribes move from one provider to another or using many numbers of many providers at the same time becoming more and more popular 2 phenomenon. This situation shows that switching behavior of customer is the necessary note to providers. For a long time, the mobile network in Vietnam has developed in the race of increasing the number of subscribers. The account of subscribes base reached 140 million threshold at the present. But the area of growth has slowed in width, while in 2012, only incurring 12 million subscribers. The market seems saturated and the network operators are turning to non-voice services on 3G services to increase revenue. Beside there are a phenomena of switching behavior among of providers in Vietnam from 2009 to now. Figure 4 presented that: Figure1. 1: Market shares (subscribers) of mobile phone service providers (Source: White book of Vietnam 2010, 2011, 2012, 2013) In the context of countries which the mobile telecommunications market appearing strong competition and open markets significantly reduced the advantage of monopoly position, with the involvement of multiple vendors, using the competitive strategy mixed strategies including rates, quality basic services, value added services , advertising promotions, discounts and customer care, replacement services OTT, giving them more and more choices, with moving to another provider which are more 3 attractive than sustainable impact on the subscriber‟s mobile networks. Mobile telecommunications market in Vietnam is in fierce competition with the faster growth of mobile technology shorten cycle technology, cost advantages due to declining investments, which has resulted in the opportunity for new service providers to enter the market, and the challenge for service providers present. Therefore, more and more customers have more choice, it is also means that businesses will face many difficulties in retaining patrons and attract new users to the service. Deputy Minister Le Nam Thang said previously the number of subscribers in Vietnam is estimated over 160 million. But as soon as the MIC policy prohibits the sale of SIM account with the development of the new subscriber network has been significantly reduced. Currently only 91 million subscribers and charges incurred numbers used here is consistent with the current market. 1.3. The Problems statement The ratio of 145 million subscribers/100 people in Vietnam (2012 and over 15.5 million 3G subscribers-the statistics from Wireless Intelligence) is considered as the ratio of saturated mobile subscribers (Figure 1). Figure1. 2: The growth of mobile subscribers in Vietnam from 2004 to 2013 (Source: White book 2013) 4 Therefore, the expansion of the market through increasing the number of subscribers is hard work. Currently, the number of subscribers currently reached saturation point and no longer charges for its own advantage. Any business attempting to find and create new customers will meet difficulties and have to spend more on advertising forever. Therefore, whether these customers stay or switch to another subscribers will not only vital but also be a competitive advantage of each particular mobile network. The flows of wave of moving mobile subscribers to the providers to the other providers has been repeated in telecommunication industry in Vietnam after each campaign on promoting of providers. From 2008 to 2012, the amount of the Vinaphone‟s subscribers switched from Vinaphone provider to Viettel provider by the cheap policy of Viettel. However, there has been a change in the number of subscribers switching from Vinaphone, Mobifone or Vietnammobile to Viettel when these providers change competitive strategy in many efforts of making something different. Facing with an increasing rate of customer defection, giant wireless service providers have directed a relentless flood of pitches, including free phones, upgrades, and free minutes to „„sweeten the deal‟‟ and lock-in customers. However, assuming that customer defection can be controlled by providing financial incentives is fundamentally flawed. There is no research evidence to suggest that customer loyalty is driven by financial incentives. On the contrary, extant literature indicates that customer loyalty is in fact driven by a multitude of interrelated factors. Therefore, a solid understanding of these factors must proceed „„intervention‟‟ strategies aimed at curtailing customer defection. Hence, the purpose of this research is to develop and test a model that aids further understanding of the determinants of switching behavior 5 in the mobile telecommunication industry. Such a model will have significant strategic implications for firms in this intensely competitive industry. The biggest challenge faced by telecommunication industry is the process of leaving one mobile phone provider for another. Therefore, losing a customer is a serious setback for the firm of losing the benefits. Then, the firm needs to invest resources in attracting new customers to replace the ones it has lost by advertising, promotion, initial discounts. Peter and Verhoef (2001) shows that it can cost five times more to acquire a new consumer than to retain an old one. Consequently, retaining the current consumer base is much more attractive than searching for new consumers Recognizing the importance of the issue, I decided to select and research topics: “Identify critical factors affecting the customer switching behavior for mobile service providers in Vietnam”. 1.4. Objectives In fact, the factors affecting customer switching behavior for mobile phone service in Vietnam will be an urgency and immense significance not only for each mobile network particular activities, but also for mobile communication industry in our country to answers to question: “How to keep AND attract Vietnamese customer in telecommunication sector, nowadays?” With the target above issues, this research will examine consumer‟s behavior switching to use telecom services from Vietnamese by:  Finding out which factors influent to Vietnamese‟s switching behavior to mobile service providers.  Finding out which key factors can affect mostly to switching behavior to mobile services to providers in Vietnam. 6 The purpose of the research is to contribute for evaluate impacts and tendency about behavior switching: - What to do growth up customers‟ believe and factors that affect customer behavior in staying or switching with a MSP? Particular attention is the reasons why they matter for telecommunications providers, this topic will be discussed by identifying variables have impact switching behavior in choosing any MSP. - Which factor focus on customer churn (customers‟ decision to leave a service provider)? The main findings of the analysis will be presented along with the conclusions, including recommendations to MSPs based on an improved understanding of the factors affecting customers‟ propensity to stay with a provider or switch to another. From that, specific intervention strategies of network operators in Vietnam suggested with the adjustment marketing solutions for telecommunication services to remain and keep customers in the next years out of potential foreign providers when Vietnam implements full WTO agreements in 2015. 1.5. Rationale In the telecommunications services market, especially the market share of mobile, there is always have high growth rates despite the economic crisis. Vietnamese users are evaluated adapt to technology quickly, and increasing routine use data services on mobile when there are the active support of the growth of cheap smartphone devices. Supposing that consumers spend value-added services related to mobile data on the mobile will be increasing, it is more important that they always want to stay with a provider. Research all the factors affecting the consumer behavior of mobile data services should be done in order to find out what factors can influence 7 the consumer stimulus Vietnam and keep major providers for them. There will be solutions helping to develop business strategy suitably with the trend and increasing customers for telecommunication service providers. So: - The research carried out will contribute a more complete picture of consumer perceptions of the mobile data services and consumer motivation it clearer and more realistic. - Research results are one of the few references to the agencies in planning management policies to develop mobile services in depth, ensure quality, meet the requirements of use, confirmed the ability to compete with free data services on the Internet. - Research results such as an image reflect the desire of the customers or the business units in the practice view really taking place. Having a looking at it may bring a key factor of growth, what factors constraining the acceleration of data services mobile broadband in Vietnam. Since then, these telecom companies have the facility to build plans, packaging solutions in business operations per unit. 1.6. Scope of research The research scope will be collected the information from the major city is Ho Chi Minh City. Because, Ho Chi Minh city is the area which has the largest density of mobile subscribers, full of providers, the adaptation with a rapid speed of the oriented consumer changing. And, objects get survey is mobile phone subscribers from 16 ages to 60 ages. At the age, the demand of consumers can use telecommunication services and adapt regular of owning mobile phone subscriber by individual identity. In figure 1 (Chapter 1) showed a clarity shift, change or disappear with the appreciable amount of subscriber of providers in the period from 2011 onwards. 8 Besides, in figure 2 (Chapter 1) also displayed a rate of slowdown increasing with the number of mobile subscribers from 2012 onwards. Another way to increase the number of mobile subscribers in Vietnam in terms of overall telecom sector will not be as powerful as the previous year. The growth of each provider will focus on the movement of subscribers from provider to another provider. The wave of conversion occurs when providers have impact factors. It could be price, service quality, decreased switching barrier. Each provider has its own strategy to attract customers on the basis of the impact of different behaviors. As a result the study of impact to switching behavior will be considered for any subscribers of all providers in the purpose of the fully assess all impacts of the switching behavior of mobile subscribers in Vietnam... Collecting data with survey questions is considered as the primary data. Reference from secondary data such as: reports or annual report of Vietnam Information and Communication Technology - White Books, statistic data of telecommunication companies in Vietnam will add for studying. 1.7. Thesis structure The organization of the study includes five chapters. In which, chapter 1 comprised the general overview of problems of the study have been taken care. This chapter also answers the question what motivates the author to carry out this research. The research purpose, scope and implication of the research were made clearly as well. Chapter 2 will give whole the base of literature review related to switching behavior. In this chapter, the author will introduce some model of factors which affect to switching behavior in telecom sector of many Asian countries from many researchers. By comparing and analyzing base on these review researches, the author 9 will give a model of suitable factors which its adoption to measure in Vietnamese mobile subscribers. Chapter 3 is the presentation about the research method, the way that the study will be conducted. The method was built with integrated approach between qualitative methods and qualitative methods. However, the quantitative method was the major method of the research. The theoretical basis and data base of a telecommunications service sector is fragment of theoretical model recommended. In this section, questionnaire design, unit of analysis, sample size and measureable scale will be clearly indicated. Chapter 4 is the report of the analyzed data and the result from them. This chapter recorded the main concern about finding from the practice data by statistical techniques as descriptive statistics, reliability, explanatory factor analysis, correlations, multiple regression and path analysis. It is the conclusion for the suitability of the model suggested with real influenced factors on switching behaviors of mobile subscriber. Chapter 5, the final section will give the link of existing laws of the telecom service market through surveys and reports in the chapter 4. From that, it will be integrated with the other reports of trends of the market in future to provide a closer view about current situation. And more important, once research questions had been answered and research hypothesis had been testified, the author implicated a suggested suitable developing strategies for remain mobile subscribers in Vietnam. Since then, the author has proposed some solutions to adapt the new trend in the market towards MSPs in Vietnam. Chapter summary 10 This chapter is considered very important as the first step of study that provides the overview of the dissertation. It starts with background relating to switching behavior of mobile subscribers in the Vietnam context with a trend of the high competition. The competition will be stronger and stronger when the MNPs policy (keeping the number of subscriber not switch another provider) applied in 2017. Platform of the research based on literatures supplied in chapter 2 related to switching behavior in the telecommunication sector. 11 Chapter 2 – LITERATURE REVIEW Switching behavior in telecommunication sector in Vietnam appeared clearly when monopoly provider has not existed (supplied in chapter 1). Therefore, the understanding the culture of consumer switching behavior in Vietnam market will be a base of providers who build the effective business strategy in the telecommunication industry. This required knowledge about switching behavior of consumer on the literature was evaluated. These concepts and theories are used as foundation for analysis, suggestions and solutions in the study model. The theories help us understand how and why they are applied for the study. From that the research model is built up like the final target to examine the real relationship between influent factors with switching behavior in the mobile market in Vietnam. 2.1. Switching behavior Switching behavior could be interpreted as a behavioral dimension (Cosmos Antwi-Boateng, 2013). Or “Service switching involves replacing or exchanging the current service provider with another service provider”, Bansal and Taylor (1999) also adopted a behavioral approach to switching in their definition. In other word, switching as “such endings where the supplier (or the customer) is substituted for another alternative” follow Tahtinen and Halinen (2002) defined. With the target to adapt the satisfactory level of the consumers with any product or service, consumers begin a consumer behavior by switching the providers or companies supply them which have suited with their favorites (following M.Sathish 2011). For example, a customer might move funds from one bank to another if she is dissatisfied with the customer service at the first. Consumerswitching behavior is an ever-present danger for a business - if you don‟t keep your 12 customers satisfied, your competitors might directly benefit. Another matter is that consumer switching is a serious threat for businesses that offer continuously delivered services, according to the “Handbook of Developments in Consumer Behavior,” by Victoria Wells and G. R. Foxall. For example, banks, cellular-service providers and insurance companies offer continuous service to customers. After such businesses drop the ball, their customers are likely to avoid further problems by switching to competitors that have better reputations. Therefore, switching behavior refers to replacing the current service provider with another. In context of Vietnam mobile service, it is also able to switch from one service provider to another while still continue to use the service category. It can be the positive contribution for switching intention before having an actual switching action in the future. Therefore, service switching is as the situation where the mobile service users have the intention to switch their present service provider and/ or have switched from one service provider but continuing to use the same service (Farzana Q. Habib, 2011). 2.2. Impact of switching behavior For example, customers might abandon your business because the low-quality service don't meet their needs, forcing them to opt for one of your competitors. Or they might abandon your business because they believe the poor service isn't worth what you‟re charging. In this case, they might do without the type of service you‟re providing rather than opt for a competitor. Either way, you lose. When your product or service is no longer new and exciting to consumers, they might leave just and your business will be threatened by consumer-switching behavior. Switching behavior can become the important element for increasing or decreasing productivity and profitability in the service business (Rehana Kouser, 13 2009). The facing the problems of not only attracting new customer but also retaining the resisting one has been significant challenges to MSPs. Like the method to attract new customers to fill a hole of losing old customers moving other providers, the current provider will spend more and more on the marketing and promotion budgets including new packages and reduction of the service charges. Although, the cost is becoming too much high to remain competent but still most of the MSP are not able to prevent the customers from switching from their services. KyoungAe Kim (2011) explained that when customers elect to continue the relationship with their service provider, they evaluate sunk costs from the existing channel, as well as relationships with alternative channels. If no alternative that can provide better outcomes exists, customers will elect to maintain the existing relationship. On the contrary, customers have sufficient motivation to break off the existing relationship and engage in a new alternative relationship. It is clearly with the current situation in Vietnam mobile‟s market, there are difficulties for finding new customers of the MSPs. When the ratio of 123.7 million subscribers/100 people in Vietnam (White book, 2012), is considered as the ratio of saturated mobile subscribers. Therefore, the expansion of the market through increasing the number of subscribers is hard work. Besides, the state tightened subscribe to user management makes it important to expand the number of subscribers harder. Solutions packages for mobile network operators are very much applicable in the past, but all prices downward. Therefore, the increasing in the number of subscribers rises only very little profit. In other words, the increasing of the density of promotion for mobile phones is no longer trendy. Expanding value-added services such as mobile data trend is expected to grow very strongly by two factors driving the rapid growth of smartphones are cheap and low 3G package. And also the fact that, 14 this trend through the contribution from data revenue increased and now accounts for over 40% of the total revenue of the network. As a way to recover ARPU, MSPs are making hard efforts to develop new services and convergence services. Therefore, it is natural for each MSP to endeavor to minimize its churn-out rate and to maximize its churn-in rate (Daihwan Min; Lili Wan, 2009). Rehana Kouser have view about MSP is trying to formulate the customer oriented strategies, to achieve high customer retention and attracting new customers by creating value using new customer to limit switching behavior to other provider and constantly pulled customer from other to them. In order to achieve this target, MSPs need to understand the factors that affect customer switching. Some factors will be given to discus and examine by referencing some studies have been carried out to find out the factors that influence the decision to retain with the same product of mobile service or to adopt another product of mobile service. 2.3. Factors can affect to switching behavior In Vietnam, the context has being also happened by fierce competition of many MSPs like U.S.A, Korean, China, Pakistan, and EU. Mobile markets have been facing challenge of switching wave from mobile subscribers in the recent years. Many researches evaluate impacts of factors belong to particular condition of each country; group factors effect to switching behavior is also different. Reference from many different researches, Dong-Hee-Shin and Won-Young-Kim‟s model showed that it owns characteristics which appeared in most of models of other researches. It is model contained the most feature factors lead switching behavior in a logic ordering. Applying this model to study the Vietnam market can be recognize necessary factors in the suitable social context as Vietnam with switching behavior in the telecommunication industry. 15 The model about factors impact to switching behavior in the telecommunication industry in the studying of Dong-Hee-Shin clearly showed that customer satisfaction and perceived switching barrier are factor directly impact intention to switch. However, there are more detail factors indirectly impact to behavior switching through effectiveness to customer satisfaction factor and perceive switching barrier. In which, there is the impact of price and service quality into the level of customer satisfaction. Besides, switching cost and customer lock-in impact into level of perceived switching barrier. In fact that, it was also adverted in model of Moon-Koo Kim (2004), switching behavior is the result of customer satisfaction failure and switching barrier. In which, service quality (call quality, value-added services, customer support) lead to customer satisfaction and switching cost (loss cost, move-in cost) plus international relationship lead to switching barrier. In 2009, Daihwan Min and Lili Wan also recognized factors such as customer satisfaction, switching cost, and customer loyalty affect to switching behavior. Although, Yi-Fei Chuang (2011) had the quite different view about pull-and-suck effects in switching intentions in Taiwan mobile sector, it still includes subscriber satisfaction, switching cost. Based on the similar in context of price and quality of service in Vietnam, the model of Dong-Hee-Shin matched a general element for the powerful effect that price and quality has on customer satisfaction. When investment for quality of network coverage area of Viettel has focused from first days give an effective result of increasing number of 2.3.1. Customer satisfaction Customer satisfaction generally means customer reaction to the state of fulfillment, and customer judgment of the fulfilled state (Moon-Koo Kim quote from 16 Oliver, 1997). Oliver (1997) defines satisfaction as a pleasant past-purchasing experience from a product or service with expectancy of the customer. Jahanzaib & Jabeen (2007), Pengfei Cheng & Xinmei Liu (2007), Daihwan Min & Lili Wan (2009) or William Jen (2010), and Rehana Kouser (2012) also found that customer‟s satisfaction is strongly affected on switching behavior. In which, core service failure is a part of forming customer‟s satisfaction failure. Pricing is also considered a main reason of customer‟s satisfaction which the customer leaves from one service provider to another as it is in the unsuitable policy. Moreover, Ho Kyun Shin, Andrey Kima, Chang Won Lee (2011) indicated that subscribers consider price and service quality are the most valuable attributes. But it is associated service quality like one of element impact to customer satisfaction not need be separated. And perceived value becomes the important predictor of satisfaction and customers‟ behavioral intention (William Jen, 2011). Or, Moon-Koo Kim (2004) presented in his model with effects of customer satisfaction (call quality, value-added services, customer support) on customer loyalty. Or Rehat Ali Khan (2012) also emphasized call rate, lower SMS , better service quality and service reliability are parts that affect customer‟s level of satisfaction resulting in either customer retention or switching to another better service. It is clearly that a high satisfy tend to demonstrate a high likely or repurchase and higher tolerance to price increases by providers or price decreases by competitors (Priyanka Gautam, 2011; Yi-Fei Chuang, 2011). Therefore, if one factor as customer satisfaction is not adapted to values of service quality or satisfaction of price, it is likely that as customer satisfaction failure, switching behavior has sign of beginning. Pricing is also considered a big reason of customer‟s satisfaction which the customer leaves from one service provider to another as it is in the unsuitable policy 17 existing in Vietnam or Korea. Therefore, based on research of Ho Kyun Shin, Andrey Kima, and Chang Won Lee (2011) indicated that subscribers do not consider the MNP service an import attribute, while price and service quality are the most valuable attributes. Lee and Murphy (2005) indicated that price is the top switching determinant and more important than service quality and loyalty programs. That is, changes in price perceptions may cause the loyalty-switching transition. In the telecommunications sector, perceived monetary value is a key factor explaining both intentions to use and usage level of mobile services (Kim, 2011). A good price structures can be present at the price tolerant scheme. Price tolerance is the degree to which a customer can bear the price of using cellular service according to level of satisfaction (Rehana Kouser, 2012). It is explained that amount of money which customer are willing pay connection fee for using cellular service as the way of sharing with factors such as technology, services, maintenance and taxes, … By this method, a profit of service providers will be contributed. If an unfair price policy from providers is given, customers tend to switch to other. Service quality “Quality is the extent to which the customers or users believe the product or service surpasses their needs and expectations” – (Gitlow,. 1989). “Quality is the total composite product and service characteristics of marketing, engineering, manufacture and maintenance through which the product in use will meet the expectations of the customer” – (Feigenbaum, 1986). In earlier studies on mobile telecommunication services, service quality has been measured by call quality, pricing structure, network coverage quality, mobile devices, value-added services, convenience in procedures, and customer support (Kim, 2000; Gerpott,2001; Lee & Freick, 2001). Following Dong-Hee-Shin, service quality in the telecom industry is an 18 important indicator to assess a firm's performance, it is considered as a consumer's overall impression of the relative efficiency of the organization and its services. By basing on SERVQUAL instrument developed by Parasuraman (1988) to identifies perceived quality in differences between customer expectations and perceptions factor analysis through tangible, reliability, assurance, and empathy dimensions, which are generic across service contexts. the study show that differences exist between the network operators and how the perceived difference affected switching intention by hypothesized that higher levels of service quality are associated with higher levels of customer satisfaction. In other way, the main factor determining customer satisfaction is the customers‟ own perceptions of service quality (Zeithamal & Bitner, 1996). Therefore, service quality failure can be lead to Customer satisfaction failures can become a contributing factor to a customer switching away (Tax, 1998). Service quality failures make a bad perceived value. Other way, perceived value has attracted significant attention from marketing scholars in general. Perceived value is one of the showing of “Core service” based on equity theory. When analyze “service quality and customer switching behavior in China‟s mobile phone service sector”, Dapeng Liang (2013) show one of seven critical factors lead customers to switch mobile phone service providers is core service failure. Or it is exactly that, service quality success is the guarantee of the quality core services to satisfy customer requirements. 2.3.2. Switching barrier And switching barrier (William Jen, 2010; Moon-Koo Kim, 2004; Dong-Hee Shin, 2008) have the impact of switching cost and international relationship. Furthermore, Priyanka Gautam, 2011 found that due to the moderating role of switching barriers with loyalty in the context of mobile services is not a unified construct but rather one with at least two distinct dimensions: repurchase likelihood 19 and price tolerance. Moreover, there are many types of group service packages or preferential service packages for some special objects used as an invisible tie to remain or promote switching between competitors in the recent years. It is implemented base on investment of interpersonal relationship. The switching barrier refers to the difficulty of switching to another provider that is encountered by a customer who is dissatisfied with the existing service, or to the financial, social and psychological burden felt by a customer when switching to a new carrier (Moon-Koo Kim, 2004 follow Fornell, 1992). Therefore, the higher the switching barrier, the more a customer is forced to remain with his or her existing carrier. According to a previous study, the switching barrier is made up of switching cost, alternative attractiveness, habit and interpersonal relationships. Switching cost In Paul T Mburu‟s study (2012), a definition of Jackson (1985) about switching cost as the psychological, physical and economic costs a customer faces in changing a supplier. Switching costs, such as the investment of time, money, and effort, in customers‟ perception make it difficult to change providers (of Ranaweera & Prabhu, 2003 in Yi-Fei Chuang‟s study, 2010). Switching cost means the cost incurred when switching, including time, money and psychological cost (Dick & Basu, 1994), and is defined as perceived risk, insofar as there are potential losses perceived by customers when switching carriers, such as losses of a financial, performancerelated, social, psychological, and safety-related nature (Murray, 1991). Or other hand, switching cost is as the cost occurred when a customer replaces the current supplier with another (of Porter, 2008 in Daihwan Min‟s study, 2009). Switching cost can be delivered from all cost of switching procedure for new provider (Chen & Hitt 2002), and also the monetary loss when customers must offset the contract to the existing 20 provider. Klemperer (1987) classified switching costs into three types: transaction, learning, and artificial or contractual switching costs. Transaction costs refer to the financial costs incurred when a customer ends an existing relationship with one provider and begins a new relationship with another. Learning costs takes a place when a customer has to put in effort to reach the same level of comfort and facility with the new product or service as the old one. Artificial or contractual costs are those that are deliberately created by a service provider. To sum up, switching cost plays a significant role in the satisfaction or dissatisfaction of switching link. This factor is a key to reduce the switching barrier and motivate competition for meliorating service quality. Switching cost was highlighted as the important role plays in customer retention or switching behavior in researches of Keaveney (1995), Lee et al. (2001), Chen & Hitt (2002), Kim et al. (2004), Daihwan Min et al. (2009), Yi-Fei Chuang (2011) and Farzana Q. Habib et al. (2011). The level of switching costs moderates the link between satisfaction and loyalty (desiring staying or switching a service provider), especially, belonging to market structure. If the market has a single or overwhelmingly large share provider (for example, a monopoly provider of local telephone service), there should be little effect of switching costs on the relationship between satisfaction and brand loyalty. That is, a customer not dissatisfied with high switching costs will not switch; or a customer will switch if there are dissatisfied and low switching costs. Customer lock-in Firms keep developing various strategies to gain control over access to subscribers in an attempt to achieve customer lock-in, which is usually referred to “loyalty” Clarke (2004). It is understood as a combination of customers‟ favorable 21 attitude and the behavior of repurchase Moon-Koo Kim (2004). In other word, it is willingness to remain as a customer of the current Mobile Network Operators, “despite situational influences and marketing efforts having the potential to cause switching behavior” (Daihwan Min, 2009 use from Oliver‟ definition, 1999). Following Dong-Hee-Shin while subscriber lock-in is often regarded as a concept similar to switching barrier, the distinction is clear: subscriber lock-in is a supply-side variable describing providers' efforts to create switching barriers, whereas the perceived switching barrier is a demand-side variable describing consumer perception. The higher the cost of switching carriers within a particular market, the more the subscriber is captured, or locked into the provider may be able to increase the service price without a significant loss of subscribers, providing the service price increase does not exceed the cost of switching providers. This approach forces subscribers to balance switching costs with the benefit of saving money in a competitor's aftermarket. Switching costs thus generates consumer lock-in, allowing firms to earn above-competitive, monopoly profits. While markets with high switching costs serve to retain existing subscribers, this supports the reputation effects. If provider known that they seduce potential subscribers and retain existing subscribers become an economic axiom that lower switching costs force competition for initial subscribers and liberate second period subscribers from a particular aftermarket. 2.4. Conceptual framework model for the research The model will be considered follow the proposed model (Figure 6) for this study. The author‟s goal is to examine the influence of antecedent variables on the model switching behavior. This model consists of the most important variables that affect the Mobile user's switching behavior, customer satisfaction and switching 22 barrier are dependent variables. The independent variables are service quality, price, alternative attractiveness, customer lock-in. Each of these factors will be stated in a hypothesis to examine their potential influence on switching behavior of mobile service users in Vietnam. At particular of the context in Vietnam, factors which given in the model is suitable. Factors affect Service quality Price Switching cost Customer lock-in Affective respone H1+ Customer satisfaction Behavioral respone H5+ H2+ Switching behavior of Mobile Users H3+ Perceived Switching barrier H6+ H4+ Figure2. 1: Suggested model Research Hypotheses: Based upon Theoretical framework the researchers try to test the following hypotheses: H1+: Dissatisfaction of service quality has significant effect on decreasing customer satisfaction. Conclude elements: Network coverage, customer support system, value-added service H2+: Dissatisfaction of Price has significant effects on decreasing customer satisfaction. 23 Conclude elements: bond level, promotion, policy price follow object. H3+: Low level of switching cost has significant effect on decreasing switching barrier. Conclude elements: alternative function, alternative quality, and alternative service. H4+: Low level of customer lock-in has significant effect on decreasing switching barrier. Conclude elements: contractual commitments, bundling services, loyalty programs H5+: Low level of customer satisfaction has significant effect on increasing the switching behavior. H6+: Low level of switching barrier has significant effect on increasing switching behavior. Following differences of group age, gender, income level, profession sector, will have sensitive impact level with different perceived satisfaction level and perceived barrier level. Chapter summary By combination of analyzed models in previous researches, the chosen model corresponds with the context of Vietnam market. In which, price, quality are always popular factors impact to consumer behavior when they are factors affect to customer satisfaction. Some factor can be test factors to find more or adjust impacts for switching behavior such as switching barrier (detail are customer lock-in and switching cost). By sampling method presented in chapter 3 will help us to find out which factor is real and strongest impact to switching behavior. 24 Chapter 3 – RESEARCH METHODOLOGY In base on of the chosen model in chapter 2, item of factors will be changed or added in the model in the meaning of the concordance with the context of Vietnam market. The goal of this chapter is to find the influence of antecedent variables on the mentioned study model of key factors: customer satisfaction, switching barrier. In which, more detail factors affect indirectly as price, service quality, switching cost, customer lock-in. 3.1. Research method In purpose of research, it can be distinguished on functions or techniques applied. With this study, survey is the business research techniques applied in. The method will be used to find out which factor can be key impact on switching behavior of mobile subscribers in Vietnam. Because of less all collected information from variable sources such as mobile providers, other magazine, other or newspaper for understanding behavior of mobile subscribers on the impact to switching reflection. So, the study to investigate over secondary data sources as well as primary data sources in conduct the interview and survey to solve problem as reliability and validity. 3.2. Research sample Usage data in quantitative research to test scientific theories by surveys from mobile services subscribers based the technology acceptance model and relevant theories. The target population for this study was mobile subscriber in Ho Chi Minh City, aged from16 to 60. Because of diversity in population structure of Ho Chi Minh City, it is represented characteristics for the total mobile subscribers in Vietnam market. The population of mobile subscribers in Ho Chi Minh City is 18,799,000. 25 Therefore, researcher uses an adjusted method for the large sample. If we assume that the data is categorical with whole the major variable, the minimum sample size (corrected) is calculated such as: (384) n= ---------------------------- = 383.99 ~ 384 (1 + 384/18,799,000) The method base on James E. Bartlett‟ s method suggested with the alpha level a priori at .05, the level of acceptable error at 5%, standard deviation of the scale as .5. If an anticipated return rate of 65% assumed that it could happen, the maximum sample size of 384/.65 is 590. Moreover, when there was the application of the calculation from with and the confidence interval of 5, the minimum sample size was calculated as 384 samples. Following Farzana Q. Habib used a sample of 535 employees and students of five public universities and two private universities located in Malaysia‟s multimedia super-corridor region. While, KyoungAe Kim chose method mail the survey to all members that had employed internet communities, an invitation to participate in the web-based survey over a two-week period. And the result of participation had 359 users responded and only 344 cases could be used for the analysis. The method collect data of Yi-Fei Chuang based on a large sample size and collected randomly of 1100 questionnaires, the rate questionnaires responded is 873 (79.36% of sample size) but the objects for this study only concentrate post-paid mobile telephone subscribers. These researchers did not randomly select the respondents because of its convenience. It will not be a good way to present characters for whole population in Vietnam which have had major pre-paid subscribers, it is a way that. Sample size is from 350-520 customers from chosen cities of Pakistan, Korea, China and U.S with the period of a month. 26 So, a random sample of Vietnamese mobile service users will be selected. A questionnaire will be prepared based on previous researchers in the literature review chapter. The numbers is the suitable sample size belongs to 350-520 of previous research implemented. Narrow object access data by personal information necessary to choose as the current providers, how much suppliers have been using, which age gap, have changed service providers yet, the income, occupation, is pre-pair mobile service users.... Hence, the collecting data will be implemented in this research in the purpose of exact and confident data by the sample size of samples is from 385 to 500. 3.3. Research Methodology This study was carried out through combination between quantitative method and qualitative method in order to adjust the scale and additional components for orientation switching supplier. In which, quantitative study is major to collect and analyze survey data, as well as scale inspection, testing theoretical models and theories in the field of communications. Following quantitative approach, this study will examine the impact of the select factors on a behavioral intention to use the mobile services. The process of measurement is central to quantitative research because it provides the fundamental connection between empirical observation and mathematical expression of quantitative relationships. However, qualitative research helps to gather an in-depth understanding of human behavior and the reasons that govern such behavior before designing questionnaires. In this research, the most effective tool was the questionnaire that was adopted from previous literature, suggestions of academics and practitioners based on major concepts and variables used for this research. Questionnaire design was firstly started 27 with developing a sound theoretical framework. From collected data by questionnaire, theories were gathered and analyzed. The reliability and validity of all scales of the research was ensured by suitable questions. All of the questions were formulated on a five-point Likert-scale ranging from 1 to 5, equivalent to strongly disagree, disagree, neutral, agree and strongly agree respectively, except for some question about demographic: “However switch mobile provider before?” in which 1 = Never, 2 = seldom, 3 = sometimes, 4 = often, 5 = very often used to measure. The data for analysis will collected in the November-December 2013 period via a structured questionnaire survey (Appendix B). Each variable (or factor) was measured using multiple items. Scale for category data is also used to assess attitudes towards behavior or a topic by presenting some conditions about the topic and taking respondents‟ agreement situation of these conditions. Customer satisfaction The answering from “Strongly Disagree” to “Strongly agree”, that measured subscriber satisfaction. Six questions were used to measure customer satisfaction index which were adopted from question 3.9 to question 3.15. Scale used base on scale of Aneeta Sidhu (2002) and Rehana Kouser (2012). Price Impact of price was measured from question 3.1 to question 3.5. These items group used multi-scale in the research of Dong-Hee-Shin (2004) and Rahat Ali Khan (2012). 28 Service quality The measurement of service quality impacts from 3.6 to 3.8. In which, 3.6 – 3.8 used five point Likert scale from strong disagree to strong agree from items of M. Sathis (2011), D.Liang (2013) and Farzana (2011). Customer lock-in And customer lock-in adopted from question 3.16 to question 3.18 with items referenced from Dong-Hee-Shin (2004) by multi-scale. In which, the researcher chose five point Likert scale have chosen level show full perceived level of consumers. Switching cost Switching cost was measured with items appear in question 3.19, 3.20 and 3.21 matched with D.Liang„s research (2013), Dong-Hee-Shin (2004) and Feick (2001). Switching barrier Finally, items of perceived switching barrier was developed by question 4.1, 4.2, 4.3, 4.4, 4.5. Answers for each item from “I” – “Strongly Disagree” to “Strongly Agree” to measure switching barrier matched with Moon-Koo Kim (2004). Switching behavior To design the questionnaire, researcher divide group of question as group of sample variables. With each factor of the suggested model in chapter 2, we have variables attached below: • Customer satisfaction + Service quality - Network coverage - Value-added services - Customer support program 29 + Price • - Basic service - Promotion - Value-add service - Target group Switching barrier + Switching cost - Cost for changing - Cost for interrupted relationship - Cost for connecting again + Customer lock-in - Contractual commitments - Loyalty program 3.4. Data collection Primary data for this research was collected from the questionnaires (appendix A & B). Researcher planned to deliver the questionnaires to at least 420 subscribers in Ho Chi Minh in four following ways. Firstly, the questionnaires were sent through email. Secondly, the questionnaires were sent to mobile providers (shop of Viettel, Mobifone, Vinaphone, and others) to take information their customers. Thirdly, researcher directly delivered the questionnaire many people at companies, school, university…. And finally, questionnaires were sent reseller who sell or distribution sim and charge card for mobile subscriber. The questionnaires were sent from the end of November 2013 to the end of May 2014. Totally, researcher received the responds from 405 companies including 60 responds from the Google docs; 100 responds from 30 shop of providers by hard copies; 126 responds from sim-card retails by hard copies; 179 responds were received directly from subscribers by hard copies. 3.3. Pretest processing  Progress of researching: Target of research Theoretical Foundations Theoretical model Preliminary studies Scale models of rudiment model Adjusted scale models Test Formal study Complete scale Multivariate regression Reviews & recommend Figure3. 1: Progress of researching 31 3.5. Data analysis Techniques The researcher conducted a pretest, November 2013 on 20 surveys. Base on the pretest results, the author edited some questions for better clarity. The format was also fine-tuned and some of the questions were reordered to capture the required information more effectively. The first question asks the respondents their current cellular carrier. The purpose of the question see if the likelihood of switching. It helps in understanding the respondent‟s view of the current provider compared to the competitors. The next few questions (question 5 to question 10) ask the respondents to divide groups follow demographic feature. It help in understanding level of effect to what factors which each group consumer find important and essential for a service provider. The next question after that the respondents to rate providers in Vietnam on each of the factors identified in the literature review. The purpose of these questions to determine in perceptions with service of each provider and identify variables mobile providers could focus on for future consumer acquisitions. The researcher applied several statistic techniques in order to have the most precise findings for the research. Questionnaires were coded, computerized, and screened for errors before any statistical analysis. 3.5.1. Descriptive statistics Displaying data used to get the general information about the respondents through percentage rate and frequency distribution from values of a variable (e.g., for the variable occupation, gender, age, income…..). It is the corresponding numbers of participants for each value. By running descriptive, data entry errors were checked and frequency procedures to look for outliers through the valid maximum and 32 minimum values of each variable. Any reported value outside this range indicated a data entry error that needed to be corrected for further analysis. The mean of a set of numbers is the arithmetic average of those numbers used measure of central tendency for numerical variables. Beside, one method used to measures of variability is standard deviation which provided information about the amount of spread or dispersion among the variables. 3.5.2. Factor analysis Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables. The information gained about the interdependencies between observed variables can be used later to reduce the set of variables in a dataset. In other way, factor analysis is applied as a data reduction or structure detection method. 3.5.3. Multiple regression In order to explore the relationship between one continuous dependent variable and a number of continuous independent variables or predictors, multiple regressions is a technique that can be used to. Multiple regressions will allow testing the relative contribution of each of the variables whether adding a variable contributes to the predictive ability of the model. 3.5.4. Path analysis Following De Vaus (2002), interpreting strength of path coefficients, interval from 0.5 – 0.9 show that there is a very strong relationship to perfect relationship. In which, the most reliability interval from 0.7 – 0.89 while 0.9 in ideal condition not suit to real context of the market. 33 3.6. Validity Test Validity test refers to whether or not hypotheses claimed show in measurement. On a test with high validity, the items are closely intended focus. By testing the reliability of each variable to ensure data analysis next, factor analysis was used to reduce data. Besides, the target of factor analysis not only cover valid variables into relevant group and delete invalid variables but also check correlation or reliability of the variables in the same scale. Result show that, factor have to load on higher level 0.30 to keep the item belong to factor. If it is lower than 0.30, the item have to move to another factor and excluded from calculations. A way to give up disadvantage of this method when it is ignored the weights of the items that load on a factor, Stevens (2002) suggests using loadings which are about 0.40 or greater for interpretation. Therefore, loading of .40 and above are typically considered the rule of thumb threshold for this study. If the loading is below .40, research eliminates those items. 3.6.1. Factor analysis for independent variable Researcher used total 14 items for four independent variables in which, five items of Price (pp1 to pp5); three items of service quality (sq1 to sq3), three items of Customer lock-in (cl1 to cl3), and three items of switching cost (sc1 to sc3). Table3. 1: KMO and Bartlett's Test for Independent variables Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Approx. Chi-Square Bartlett's Test of Sphericity df Sig. ,842 2424,136 91 ,000 Value of analysis must be above 0.6 is significant (Pallant, 2005). Therefore, index of Kaiser-Meyer-Olkin Measure of Sampling Adequacy as 0.842 is a good 34 value. While the value of Bartlett's Test of Sphericity show that it is significant at level of 0.000 in table 3. In other word, these independent variables are appropriate. Table3. 2: Total Variance Explained for Dependent variables Component 1 2 3 4 Initial Eigenvalues % of Total Variance Cumulative % Rotation Sums of Squared Loadings % of Total Variance Cumulative % 4,983 35,590 35,590 3,562 25,439 25,439 2,129 15,204 50,794 2,127 15,192 40,632 1,356 9,685 60,479 2,012 14,372 55,004 1,190 8,499 68,978 1,956 13,974 68,978 Extraction Method: Principal Component Analysis. From table 4 show that there were four components that had value more than 1. Moreover, these four components could explain 68.978% of the total variance. Among them, component 1 explained 35,590%, component 2 explained 50,794%, component 3 explained 60,479%, and final component explained 68,978% of total variance. 35 Table3. 3: Rotated Component Matrix of Independent variables Factor 1 Factor 1: Price (PP) pp3_3.3. There are more saving packages for target groups (pupils, students, farmers, fishermen, businesses,) pp2_3.2. Promotion easily attracts more attention. pp4_3.4.There are cheap 3G services pp1_3.1 I think service charges are factors to consider firstly. pp5_3.5. There are cheap value- added services Factor 2: Customer lock-in cl1_3.16. Relatives, friends, colleagues, partners are using the same provider. cl2_3.17. I am benefiting from the program provider's preference. cl3_3.18. My phone numbers are familiar to many people, easy to remember, right Feng Shui, can‟t be changed. Factor 3: Switching cost (SC) sc1_3.19. Take much time and cost to connect to people again. sc2_3.20. Switching to other provider will enjoy more favorable package. sc3_3.21. Loss of preferential policies to change. . Factor 4: Service quality (SQ) sq1_3.6. Providers have extensive and stable coverage sq2_3.7. Providers have good voice and 3G quality sq3_3.8. Providers have good content service. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Factor loading Factor 2 Factor 3 Factor 4 ,849 ,827 ,817 ,805 ,757 ,866 ,848 ,668 ,810 ,758 ,748 ,845 ,728 ,696 36 By applying varimax rotation method, there were four created components. Factor 1 corresponded to Price, component 2 indicated Customer lock-in, component 3 indicated Switching cost and component 4 was presented for Service quality. Table3. 4: Reliability coefficients of Independent variables arrange follow components No. Name of component No. of Item Factor 1 Factor 2 Factor 3 Factor 4 Price PP Service quality SQ Switching cost SC Customer lock-in CL 5 3 3 3 Cronbach Alpha 0.893 0.745 0.733 0.752 3.6.2. Factor analysis for Dependent variable The next factor analysis was applied for three dependent variables, it has 15 items. These items were divided into three group including 6 items for Customer satisfaction, 4 items for Switching barrier, 5 items for Switching behavior. Table3. 5: KMO and Bartlett's Test for Dependent variables Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity Approx. Chi-Square df Sig. ,870 2899,453 105 ,000 We can recognize that variable has significant contribution have to value be over 0.6 (Pallant, 2005). The value showed in table 3.6 with Kaiser-Meyer-Olkin Measure of Sampling Adequacy is 0.870 and Bartlett's Test of Sphericity index is significant at the 0.000 level. Table3. 6: Total Variance Explained for Dependent Variables Initial Eigenvalues Component Total 1 2 5,237 2,833 % of Cumulative % Variance 34,912 34,912 18,887 53,798 Rotation Sums of Squared Loadings % of Total Cumulative % Variance 3,943 26,286 26,286 3,207 21,381 47,667 37 3 1,593 10,618 64,416 2,512 16,749 64,416 Extraction Method: Principal Component Analysis. Base on table 3.7, there were three components suitable with three variables like customer satisfaction, switching behavior, switching barrier satisfied the theoretic requirement. In which, component 1 explained 34,912%, component 2 explained 53,798% and final component explained 64,416% of total data variance of the study. Table3. 7: Reliability Coefficients of Dependent Variables Variable Code No of samples No of Item Cronbach’ Alpha Switching behavior SWB 400 4 0.847 Customer CS 400 6 0.895 SB 400 4 0.778 satisfaction Switching barrier 38 Table3. 8: Rotated Component Matrix of Dependent variables Factor 1 Factor 1: Customer satisfaction cs6_3.15. I am satisfied with a good customer support system. cs5_3.14. I don't satisfy because the system of professional customer cares. cs2_3.10. I don't satisfy with the quality match to advertised quality. cs1_3.9. I don't satisfy with the quality of provided services. cs4_3.12. I don't satisfy for the proportionality between price and quality cs3_3.11. I don't satisfy with the clear direction information. Factor 2: Switching behavior swb5_4.5. Waiting for a better new provider to change. swb3_4.3. Will not continue to use the existing provider in a long time. swb1_4.1. I have ever switch to different mobile service providers before swb2_4.2. Change the other provider is what may occur swb4_4.4. Can replace the other provider if I feel better now. Factor 3: Switching barrier sb2_3.23. I was familiar with the existing provider, the change can be disruptive sb1_3.22. Changes will take a lot of effort to get contact to everyone. sb4_3.25. There haven‟t have a policy allows subscribers to be kept phone numbers when they change the current provider. sb3_3.24. Develop a relationship with a new supplier is a problem for me. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Factor loading Factor 2 Factor 3 ,831 ,827 ,791 ,784 ,780 ,673 ,830 ,797 ,785 ,780 ,691 ,822 ,749 ,735 ,699 39 Base on the result, factors are selected most often in the entire sample of respondents, as important factor that would convince respondents to leave their existing service provider. By utilizing cross-tabulation among factor show that variables grouped are logic and suitable literature review and proposed model. Chapter summary This chapter supplies the method of choosing sample, questionnaire, and test reliability of questions. The result show that a good sample size is from 385 to 500 with number of suitable questions. Result of testing also shows that question ensure exact grouping items follow factors for analysis in the next chapter. 40 Chapter 4 - DATA ANALYSIS AND ACHIEVED RESULTS The test result in chapter 3 showed that data collected ensure reliability. By using SPSS software version 20.0 in order to analyze corresponding of items in each factor and factors in relationship with the switching behavior variable. The process of data analysis included steps such as descriptive statistics, reliability test, factor Analysis, correlation testing, regression analysis and cross – tabulation analysis... 4.1. Demographic characteristic of the sample The sample of 400 mobile phone users through areas of HCMC was gathered. Out of those 400 respondents, the highest frequency was for Viettel and Mobiphone are second high ratio over 30% respondents. After this, Vinaphone loses its market share due to the entrance of new cellular companies in Vietnam. While Vietnammobile and G-mobile account for 4% and 2% of respondents. Profile of Vietnamese subscribers belongs to Vietnam‟s demographic features in chosing area for sampling. By showing data in frequency distribution, which list of variables (eg., provider, charge form, gender, …) has reflected corresponding to numbers and percentages of participants for each value. The errors were checked by running descriptive and frequency procedures to look for outliers through the range of the valid maximum and minimum values of each variable. Results showed that there were not any value in outside this range. 41 Figure 4. 1: Ratio respondents about providers Distributing the ratio of respondents to providers also corresponds with market share ratio among mobile providers in Vietnam in figure 1.1. Therefore, the result of sample can be considered as a quite real reflects with trend of consumers in the market. Base on confident level of 95 percent to analyses the results, in which, the ratio between male and female, the range of ages, income levels, and educational background which closed with the real ratio of social characteristics in Vietnam was also chosen. Figure 4. 2: Distribution follows charge form 42 Figure 5.2 show the ratio of charge form of mobile subscriber in samples corresponding to market ratio divided into two type charge forms which subscriber often chose to use. In which, the type of charge form in Vietnam market is from 10% to 15% (White book 2011, 2012, 2013). Besides, the sample also display on frequency of gender match to distribution of gender in Vietnam by figure 5.3. Figure 4. 3: Distribution rate of Subscriber base on gender Total of 400 subscriber were divided into five different ages levels to consider the impact of their behavior on age group. Among 400 answers received, there were 29 respondents had of the age from 16 to 20, 226 respondents had the age from 21 to 30, while 90 respondents had the age from 31 to 40, 40 users in the age from 41 to 50, and 15 people among of them had the age over 50 (figure 5.4). 43 Figure 4. 4: Distribution rate of Subscriber base on age Because Vietnam is in the gold population period, young subscribers are also major potential consumers of mobile services. Although the sampling was conducted in areas are crowded districts of Ho Chi Minh City and there are many mobile service object distributed in the collection, but the statistics show that mobile consumers are almost young. This reflects the social structure used with current consumption of Vietnam in table 8. By running frequency technique in SPSS 20.0, researcher got the general profile about income as firgure 5.5. In 400 answers, there were 118 people had income under 3 million VND/ month, 89 answers had income from 3-5 million VND/month, 109 others were from 5 to 10 million/month, from 10 to 20 got 63 answers and only 21 people with their income were over 20 million VND/month. Figure 4. 5: Distribution rate of Subscriber base on income In term of professional of subscribers, 83 subscribers accounting for 20,8% has been working as public sector employees, 8% of total number of subscribers were company employees. The next, researching was found out 32 subscribers ( 8%) work 44 at home or be small business or self-employed. Statistics also showed that there 12 (3%) Figure 4. 6: Distribution rate of type of career Concerning the education background issue, only 25 subscribers at postgraduate is 6% of total sampling subscriber. The next, 12% is high school, 19% is intermediate, 19% next is colleges, and the last 44% were university. High school Intermediate Colleges University Postgraduate 48 75 77 175 25 45 Figure 4. 7: Number of subscriber distributed on education background of total sample Education background is also one of factors that have a major impact cognitive benefit of the switching behavior based on insights controversial market of existing mobile services. Therefore, when considering the distribution structure of the consumer qualification criteria based on education, mobile service providers also had different policies to entice customers. Or, the template structure also looked at this rationality in sample allocation was the actual survey. And the results showed that the level of current consumers has the characteristics reflected Vietnam social structure in the education as figure 5.7. The using social networking services or free calling services on 3G mobile internet is current trends. Nowadays, the using of 3G services of mobile phone users has been increasing. This is significant impact on consumer behavior of young consumers who have comparatively qualifications and belong to the dynamic group. Figure 5.8 showed the trend of using 3G services consistent with the current trend of the consumer mobile services. And this trend is the rising. Table 4. 1: Trends 3G on mobile internet Trend Never use Sometimes Regularly Always Total Frequency 67 153 125 55 400 Percent 16,8 38,2 31,2 13,8 100,0 4.2. Reliability Test A reference range to check reliability of the sample is literature base given in table 4.2 below: 46 Table 4. 2: Interpreting strength of Pearson’s correlation Coefficient Strength of relationship .00-.19 very weak .20-.39 weak .40-.59 moderate .60-.79 strong .80-1.0 very strong (Source: Evans, 1996) A Cronbach‟s alpha level is considered as a reasonable level have to be in the range from 0.7 to 0.95 (Tho et. al. 2009), and higher Cronbach‟s alpha lead to the greater reliability (Nunally & Burnstein, 1994). However, the alpha level is too high can be the unsafe reliability as there is redundant question in group different factors (Reg Dennick, 2011). Therefore, group variables of factors in this study were checked by SPSS analysis showed that, the Cronbach‟ alpha level is as the above at safe level recommendation (higher 0.7 and lower 0.9 followed by De Vaus, 2002). Table 4. 3: Reliability Coefficients of Independent Variables Variable Code Price Service quality Customer lock-in Switching cost PP SQ CL SC No. of samples No. of Item 400 400 400 400 5 3 3 3 Cronbach Alpha 0.893 0.745 0.752 0.733 From the table 3.9 showed that chosen items in questionnaire and grouping items for factors ensured reliability for analysis independent variables. All Cronbach Alpha are in the range 47 Table 4. 4: Reliability Coefficients of Dependent Variables Variable Code No of samples No of Item Cronbach Alpha Switching behavior SWB 400 4 0.847 Customer CS 400 6 0.895 SB 400 4 0.778 satisfaction Switching barrier Similarly, the table 4.4 showed that chosen items in questionnaire and grouping items for factors ensured reliability for analysis dependent variables. Cronbach‟s alpha of each variable was retested that it achieved at good level in table 4.3 with independent variable and 4.3 with dependent variable suitable with the range of table 4.2. 4.3. Descriptive statistics of variable According to 4.1 index showed that the sampling was done based on the random method as main method. However, the impact of exposure conditions and limitation of sampling period, and students were main access objects. This approach is also appropriate in reality practice, because it is consistent with the elements of the young population structure. They are potential customers in long-term of mobile service providers in the future. Furthermore, they are also the object were affected by which factors impacting consumer taste, easy to change their behavior. Hence, they are often no more loose their loyalty with Vietnamese mobile service providers with high competitive services at current. Table 4. 5: Descriptive Statistics of Independent variables Variables PP_Price policy N Minimum Maximum Mean 400 1,00 5,00 3,3855 Std. Deviation ,97286 48 Variables SQ_Service quality SC_Switching cost CL_Customer lock-in Valid N (list wise) N Minimum Maximum Mean 400 1,00 5,00 3,0792 Std. Deviation ,87390 400 1,00 5,00 3,3833 ,81871 400 1,00 5,00 3,3250 ,76794 400 From Table 4.3, the variable coded PP is at the first line with the highest score of mean (3,3855) according with standard deviation (,97286). It means that PP is the most important factor effect on the switching behavior of mobile subscribers. While, final line is CL with lower level of mean (3, 3250) and the lowest score of standard deviation (, 76794) this forecast a low effectiveness level on the switching behavior. The next, SQ with mean (3, 0792) and standard deviation (, 87390); the third line is SC with mean (3, 3833) and standard deviation (, 81871) give more information about adding two factor impact to switching behavior after price factor. Table 4. 6: Descriptive Statistics of dependent variables Variables N CS_Customer satisfaction SB_Switching barrier SWB_Switching behavior Valid N (list wise) Minimum Maximum Mean 400 1,00 5,00 Std. Deviation 3,0367 1,03854 400 1,00 5,00 3,3669 ,95984 400 1,00 5,00 3,0570 ,71710 400 Similarly, we consider the dependent variables, Customer satisfaction had the highest score of standard deviation (1, 03854) than Switching barrier (, 95984) and mean value at level between “neutral” and “agree”. Follow them, Switching 49 behaviour had the score of mean over 3.0 (3, 0570) at level between “neutral” and “agree”. This means that, switching behavior is a phenomenon needs to be considered as in the main impact of factor to Customer satisfaction if it is failure. 4.4. Factor analysis to Switching behavior Some statistics techniques were applied in order to have the most reliability for the research. The descriptive statistic by checking percentage and frequency of respondents about the purpose of displaying data in a frequency distribution of variables (e.g, gender, age, income, professional, habit, …), the corresponding numbers and percentages of participants for each value. From that, we can easy control reported values outside the range of the valid maximum and minimum values of each variable. This indicated that an error data entry would need to be corrected for further analysis. Besides that, the mean summarizes all of their units in every observed value were used for recognizing the central tendency of numerical variables. The second, factor analysis will be used to identify the underlying factors which express the correlations among a set of variables. It was used to explore the relationship between one continuous dependent variable and continuous independent variables or predictors in multiple regressions. And finally, path analysis was a straightforward extension of multiple regressions to estimates of the magnitude and significance of hypothesized causal connections between variables. 4.4.1. Multiple regression Multiple regressions used to explore the relationship between one continuous dependent variable and continuous independent variables or predictors. Factors such as, price, service quality, customer lock-in, switching cost could be found out a 50 predicted relationship between with customer satisfaction, switching barrier and between customer satisfactions, switching barrier with switching behavior. Table 4. 7: Pearson correlation between independent variables 1 1,000 ,401** 2 3 PP_Price policy SQ_Service 1,000 quality SC_Switching ,415** ,365** 1,000 cost CL_Customer ,203 ,371** ,241 lock-in **. Correlation is significant at the 0.01 level (1-tailed) 4 1,000 As we can see from the Table 4.4, the correlation between independent variables was showed and they appeared as a positive linear relationship between independent variables. Especially, they‟re smaller than 0.59 in interpreting strength of path coefficients, follow Evans, 1996; if the number under this level will be weak relationships among independent variables. Pearson coefficient value which presents for the moderate correlation between price and service quality, is at .401 and the highest value is between switching cost and price at .415. From these results could be concluded that there‟s no multi collinearity problem with dependent variables in the research model. Accordingly, multiple regressions wasn‟t significantly affected. 4.4.2. Factor affects to customer satisfaction This section aim to identify the most chosen factors that lead to user‟s switching behavior with a service provider accroding to the analyzed results in detail. The results concluded that 4 variables of 4 factors group of independent variables. To assess the reliability and validity of measurement scales, Cronbach‟ alpha was used in 51 this research. With the item total correlation < 0.4, we can conclude that there is reliability of dependent and independent variables of this study. After conducted SPSS analysis, factor for two independent variables including total 8 items show that there are significant with value of CS factor to Customer satisfaction. Table 4. 8: Correlation coefficients between independent variables and its dependent variables Pearson Correlation Sig. (1tailed) N CS_Customer satisfaction PP_Price policy SQ_Service quality CS_Customer satisfaction PP_Price policy SQ_Service quality CS_Customer satisfaction PP_Price policy SQ_Service quality CS_Custome r satisfaction 1,000 PP_Price policy ,572 SQ_Service quality ,205 ,572** ,205 . 1,000 ,203 ,000 ,203 1,000 ,000 ,000 ,000 400 . ,000 400 ,000 . 400 400 400 400 400 400 400 The table 4.6 showed that PP_Price impact with the strongest level on Customer satisfaction level. While SQ_Service quality have a weak impact on Customer satisfaction variable. Table 4. 9: ANOVA results on effect of independents on Customer satisfaction Sum of Squares Model 1 df Mean Square F Sig. 104,151 ,000a Regression 148,096 2 74,048 Residual 282,255 397 ,711 Total 430,351 399 a. Predictors: (Constant), SQ_Service quality, PP_Price policy b. Dependent Variable: CS_Customer satisfaction 52 c. Dependent Variable: CS: Customer satisfaction d. ANOVA: F= 104,151, Sig. = .000 e. Model summary: R square = .344 The model was statistically significant at p [...]... than searching for new consumers Recognizing the importance of the issue, I decided to select and research topics: Identify critical factors affecting the customer switching behavior for mobile service providers in Vietnam 1.4 Objectives In fact, the factors affecting customer switching behavior for mobile phone service in Vietnam will be an urgency and immense significance not only for each mobile network... to another while still continue to use the service category It can be the positive contribution for switching intention before having an actual switching action in the future Therefore, service switching is as the situation where the mobile service users have the intention to switch their present service provider and/ or have switched from one service provider but continuing to use the same service. .. evaluated These concepts and theories are used as foundation for analysis, suggestions and solutions in the study model The theories help us understand how and why they are applied for the study From that the research model is built up like the final target to examine the real relationship between influent factors with switching behavior in the mobile market in Vietnam 2.1 Switching behavior Switching behavior. .. behavior could be interpreted as a behavioral dimension (Cosmos Antwi-Boateng, 2013) Or Service switching involves replacing or exchanging the current service provider with another service provider”, Bansal and Taylor (1999) also adopted a behavioral approach to switching in their definition In other word, switching as “such endings where the supplier (or the customer) is substituted for another alternative”... product or service is no longer new and exciting to consumers, they might leave just and your business will be threatened by consumer -switching behavior Switching behavior can become the important element for increasing or decreasing productivity and profitability in the service business (Rehana Kouser, 13 2009) The facing the problems of not only attracting new customer but also retaining the resisting one... key factors can affect mostly to switching behavior to mobile services to providers in Vietnam 6 The purpose of the research is to contribute for evaluate impacts and tendency about behavior switching: - What to do growth up customers‟ believe and factors that affect customer behavior in staying or switching with a MSP? Particular attention is the reasons why they matter for telecommunications providers, ... customers or the business units in the practice view really taking place Having a looking at it may bring a key factor of growth, what factors constraining the acceleration of data services mobile broadband in Vietnam Since then, these telecom companies have the facility to build plans, packaging solutions in business operations per unit 1.6 Scope of research The research scope will be collected the information... switch to their brand Moreover, the upcoming introduction of mobile number portability (MNP) to control all mobile subscribe by the government will to emphasize the appearance of a transition period in the mobile telecommunication services market Therefore, understanding and evaluating what affect customer switching behavior is important Because a customer s switching behavior results in the loss of the. .. switch to their mobile service provider (MSP) in Vietnam become an essential topic for researching 1 1.2 Telecommunication industry in Vietnam Beginning with a mobile provider in Mobifone brand in 1993, telecommunication in Vietnam officially flow with at telecommunication industry in the world By itself contribution, Mobifone or mobile service in general in Vietnam opened a new age of information... Vietnam, so Vietnamese consumers have many solutions for choosing mobile providers In order to receive the best service and maximizing the benefit, satisfaction and minimizing the cost, the consumer usually considers changing more suitable mobile service providers (MSPs) It has increased the pressure of MSPs which must supply services creating satisfaction for their customers to remain and attract customers ... topics: Identify critical factors affecting the customer switching behavior for mobile service providers in Vietnam 1.4 Objectives In fact, the factors affecting customer switching behavior for mobile. . .IDENTIFY CRITICAL FACTORS AFFECTING THE CUSTOMER SWITCHING BEHAVIOR FOR MOBILE SERVICE PROVIDERS IN VIETNAM In Partial Fulfillment of the Requirements of the Degree of MASTER OF BUSINESS ADMINISTRATION... by:  Finding out which factors influent to Vietnamese‟s switching behavior to mobile service providers  Finding out which key factors can affect mostly to switching behavior to mobile services