FACTORS AFFECTING CUSTOMER LOYALTY IN MOBILE COMMUNICATION SERVICES IN HANOI, VIETNAM A RESEARCH DISSERTATION PRESENTED TO THE FACULTY OF GRADUATE SCHOOL SOUTHERN LUZON STATE UNIVERSITY LUCBAN, QUEZON, PHILIPPINES THAI NGUYEN UNIVERSITY S.R VIETNAM IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE DOCTOR IN BUSINESS ADMINISTRATION Name: Ngo Anh Cuong (Smile) Thai Nguyen, 2013 ACKNOWLEDGMENT I would like to express our most sincere thanks to the Management Board of the Southern Luzon State University, Thai Nguyen University, teachers of the school have helped me facilitate the learning process throughout I would like to express sincere gratitude and profound Dr Nelly Mendoza, enthusiastic teacher who have dedicated guidance, encouragement, spending time and exchange orientation for me during this research I sincerely thank the Board of the University of Labor and Social affair (ULSA), colleagues in ULSA, classmates DBA1 facilitated enthusiastic help and share my experience to help complete the dissertation Finally, I would like to thank my best friends who have encouraged to complete my dissertation i CONTENTS ACKNOWLEDGMENT i ABSTRACT v APPROVAL SHEET xi Chapter 1: INTRODUCTION 1.1 Background of the study 1.2 Statement of the problem 1.3 Hypotheses 1.4 Significance of the study 1.5 Scope and limitation 1.6 Definition of terms Chapter REVIEW OF RELATED LITERATURES AND STUDIES 10 2.1 Mobile telecommunication services 10 2.2 Hanoi mobile communication services 11 Customer loyalty 16 2.4 Affecting factors to loyal customer 18 2.5 Customer loyalty models 29 2.6 Several topics related to mobilecommunication services 31 2.6.1 Some topics researched in Viet Nam 31 2.6.2 Some topics researched Overseas 32 2.7 Conceptual framework 36 Chapter METHODOLOGY……………………………………… …………….39 3.1 Research design 38 3.2 Determination of sample size 40 3.3 Sampling design and techniques 41 3.4 Research instrument 42 3.5 Data gathering procedure 43 Data processing method 43 ii Chapter 4: PRESENTATION ANALYSIS AND FINDINGS INTERPRETATION OF DATA 46 4.1 Respondents profile 46 4.2 Scale values test 48 4.2.1 Services quality 48 4.2.2 Switching Barriers 50 4.3 Preliminary analysis of the component variables 52 4.3.1 Service quality 53 4.3.2 Switching barriers 55 4.4 Hypothesis test 55 4.5 Factors affecting customer loyalty 60 4.5.1 Analyzing relationship between demographics factors with service providers 60 4.5.2 Relationship beween factors affecting loyalty versus demographic factors ….67 4.5.3 Analyzing the Factors that Affect Customer Loyalty………………………………… 75 Chapter 5: SUMMARY, CONCLUSIONS AND RECOMMENDATIONS…… 84 5.1 Summary of results…………………………………………………… ……… 84 5.2 Conclusions 84 5.3 Recommendations 86 5.3.1 Demographic factors………………………… ……………………………………….88 5.3.2 Service quality 87 5.3.2.1 Calling quality 87 5.3.2.2 Pricing structure 87 5.3.2.3 Convenience in procedures 89 5.3.2.4 Value – add services 89 5.3.3 Switching barrier 90 5.3.3.1 Customer relationship 90 5.3.3.2 Attractiveness of other suppliers 90 REFERENCES…………………………… ……………………………………….95 iii APPENDICES…………………………… ……………………………………… 99 Appendix 1: Questionnaire 97 Appendix 2: Descriptive statistics 101 Appendix 3: Relationship beween factors affecting loyalty versus demographic factors ………………………………………………………………………………104 Apendix 4: Results of Regression and correlation 160 iv ABSTRACT Customer turns to be an important concern for management due to the increasing competition particularly in mobile telecommunication services Customer loyalty plays a very crucial role for achieving the competitive advantage for enterprises According to service providers, service quality - calling quality, pricing structure, value – added service, customer support services, etc, and switching barriers -loss cost, adapting cost, attractiveness of other service providers, etc, are motivational factors to maintain customer loyalty as well as an essential element for business and increasing market share Currently, Hanoi is one of the cities in Vietnam that has a great number of mobile subscribers and suppliers According to the Ministry of Information and Communication, in 2012, there were 9.1 million mobile subscribers in Hanoi In which, ,market share of the service provider as follows: Vinaphone was 31.25%, Viettel was 43.03%, Mobifone was 18.5%, Vietnammobile was 2.57% , Gtel was 4.63% and SPT was 0.02% The main tool is a questionnaire to gather information on customer loyalty for mobile service providers in Hanoi Because the author can not have list customers of service providers Therefore, the sampling method will be conducted random sample but based on several factors: the market share of vendors, demographic (gender, age group and occupation) factors, types of services (post paid and pre- paid) Customer were selected to intervied for this research to be 400 In addition to information about the customer, the questionnaire was designed to include 42 attributes of mobile communication services that customers usually look for the Likert scale was used to rate these attributes In which, is for strongly agree and is for strongly disagree The Subscribers , as the respondent were interviewed irrespective if they are prepaid and postpaid customers v The study used correlation coefficients and chi-squared test to test the hypothesis and assess the relationship between factors with customer loyalty The multiple regression model was used to evaluate the factors affecting customer loyalty in the mobile communications market in Hanoi Results of analyzing demographic factors (occupation, per everage income, subject payment, service providrers and using time) showed that there are relationship between these factors with customer loyalty Result of analyzing multiple regresstion model showed that there were factors affecting customer loyalty In which, the “service quality” had four component factors: calling quality, Pricing structure, value – add services and convenience in procedures The “switching barrier” had three component factors: loss cost, attractiveness of other suppliers and customer relationship According to Nguyen Duc Ky and Bui Nguyen Hung, the “calling quality” was the strongest influential customer loyalty However, this factor was only thirth factor affecting customer loyalty after the “customer relationship” and the “loss cost” in this research The “customer loyalty” was the strongest influential custome loyalty and the “value – add services” was the lowest influential customer loyalty vi LIST OF TABLES Table 3.1 Factors affect customer loyalty in mobile communication services 38 Table 3.2 Subscribers using mobile communication services of Vinaphone 42 are classified by age in Hanoi, 2012……………………………… Table 4.1 The distributive sample by the gender and age…………………… 46 Table 4.2 The distributive sample by the gender and the market share …… 46 Table 4.3 The distributive sample by services type and the market share of 47 service providers Table 4.4 The summary of the distributive sample by gender, age and type of 47 service providers………………………………………………… Table 4.5 Cronbach alpha of component services quality…………………… 48 Table 4.6 Cronbach‟s alpha of the component switching barriers ………… Table 4.7 How to calculate the average value of the variable……………… 52 Table 4.8 The mean value of Service quality………………………………… 54 Table 4.9 The mean value of switching barrier……………………………… 55 Table 4.10 Correlation coeficients of variables……………………………… 57 Table 4.11 Correlation coefficients of switching barrier and customer loyalty 60 51 variables…………………………………………………………… Table 4.12 Relationship between gender with service providers……………… 61 Table 4.13 Relationship between education of subscribers with selection 62 pervice providers…………………………………………………… Table 4.14 Relationship between selection of service provider with occupation 63 of subscrbers……………………………………………………… Table 4.15 Relationship between selection of service provider with per 64 vii average income of subscrbers……………………………………… Table 4.16 Relationship between Value - add service with gender of 66 subscribers………………………………………………………… Table 4.17 Relationship between “ Adapting cost” with gender of subscribers Table 4.18 Relationship between calling quality of service providers with 69 67 per average income of subscribers………………………………… Table 4.19 Relationship between the adapting cost with subscriber‟s ages …… 70 Table 4.20 Relationship between assessment about “the supplier has service 72 packages with different charge to suitable customer demands” with education level of subscribers……………………………………… Table 4.21 Model Summary……………………………………………… 74 viii LIST OF FIGURES Figure 1: Proposed integrated model of service Loyalty 29 Figure 2: Switching barrier model of customer loyalty 31 Figure 3: Customer loyalty about mobile communication service in American 34 Figure 4: The model of impacting satisfaction and switching barrier to customer loyalty the mobile communication service in Korea 34 Figure 5: The proposed model for mobile communication service in Hanoi 37 LIST OF ILLUSTRATIONS Ilustration 1-1: The market share of mobile subscribers in Hanoi, 2011 and 2012 13 ix Value Asymp Sig (2sided) df Pearson Chi-Square 28.748a 12 004 Likelihood Ratio 27.538 12 006 4.583 032 Linear-by-Linear Association N of Valid Cases 400 a cells (30.0%) have expected count less than The minimum expected count is 58 3.5.3 Education level with not happen congestion when the cal is connected Crosstab Not happen congestion when the call is connected Education Disagree Nomarl Agree Below than high school Count diploma % 0% Count High school diploma Associate degree Bachelor degree Master degree an upper % 15.0% Count % 15.5% Count 18 12.2% Count 79 12.0% 67 13.5% 67 42.9% 42.9% 12 36.0% 48.0% 54 % 56 47.0% 33.3% % 15 45.0% 37.5% 19 % 18.2% 81.8% 26 Count Total 175 159 43.8% 39.8% Strongly agree Total 11 0% 100.0% 40 2.5% 100.0% 168 4.2% 100.0% 156 1.9% 100.0% 25 4.0% 100.0% 12 400 3.0% 100.0% Chi-Square Tests Value Asymp Sig (2sided) df a 12 298 15.234 12 229 Linear-by-Linear Association 002 965 N of Valid Cases 400 Pearson Chi-Square Likelihood Ratio 14.047 a cells (40.0%) have expected count less than The minimum expected count is 33 148 3.5.4 Education level with Not losing when your messages send and receive Crosstab Not losing when your messages send and receive Education Strongly Strongly disagree Disagree Nomarl Agree agree Total Below than high school diploma Count High school diploma Count Associate degree Bachelor degree Master degree an upper % % Count % Count % Count % Count Total % 0% 18.2% 0% 9.1% 63.6% 17 9.1% 100.0% 17 15.0% 42.5% 42.5% 31 0% 78 30 54 6% 54 66 0% 72 14 2% 156 156 3.2% 100.0% 12.0% 24.0% 56.0% 168 3.0% 100.0% 19.2% 34.6% 42.3% 40 0% 100.0% 18.5% 46.4% 32.1% 11 25 8.0% 100.0% 158 13 18.0% 39.0% 39.5% 400 3.2% 100.0% Chi-Square Tests Value Asymp Sig (2sided) df Pearson Chi-Square 19.932a 16 223 Likelihood Ratio 21.696 16 153 Linear-by-Linear Association 478 489 N of Valid Cases 400 a 12 cells (48.0%) have expected count less than The minimum expected count is 03 3.5.5 Education level with The scope of coverage Crosstab The scope of coverage Education Below than Count high school % diploma High school Count Strongly Strongly disagree Disagree Nomarl Agree agree Total 9.1% 27.3% 9.1% 0% 10 19 11 54.5% 100.0% 40 149 diploma % Associate degree Count Bachelor degree Count Master degree an upper Count Total 0% 15.0% 25.0% 47.5% % 0% 1.3% 5.1% 2 8.0% 8.0% % 21 Count % 85 58 1.2% 13.7% 50.6% % 23 12.5% 100.0% 1.2% 14 34.5% 100.0% 78 54 9.0% 50.0% 156 34.6% 100.0% 10 10 4.0% 40.0% 49 168 25 40.0% 100.0% 192 133 5.2% 12.2% 48.0% 400 33.2% 100.0% Chi-Square Tests Value Asymp Sig (2sided) df 16 000 57.022 16 000 4.382 Pearson Chi-Square a 036 61.778 Likelihood Ratio Linear-by-Linear Association N of Valid Cases 400 a 12 cells (48.0%) have expected count less than The minimum expected count is 14 3.5.6 Education level withThe supplier has service packages with different char ges to suitable customer demands Crosstab Education The supplier has service packages with different charges to suitable customer demands Disagree Below than high school diploma Count % 18.2% High school Count diploma % 5.0% Associate degree Count Bachelor degree Count % % 1.2% 10 6.4% Nomarl Agree 3 27.3% 27.3% 25 12.5% 62.5% 31 104 18.5% 61.9% 11 95 7.1% 60.9% Strongly agree Total 11 27.3% 100.0% 40 20.0% 100.0% 31 168 18.5% 100.0% 40 156 25.6% 100.0% 150 Master degree an upper Count % 8.0% Count Total 12.0% 60.0% 18 % 15 53 4.5% 25 20.0% 100.0% 242 87 13.2% 60.5% 400 21.8% 100.0% Chi-Square Tests Value Asymp Sig (2sided) df 24.532a 12 017 24.641 Pearson Chi-Square 12 017 1.415 234 Likelihood Ratio Linear-by-Linear Association N of Valid Cases 400 a cells (30.0%) have expected count less than The minimum expected count is 50 3.5.7 Education level with Calling quality Crosstab Calling quality Education Below Count than high % school diploma High school diploma Count % Associate Count degree % Bachelor degree Count % Master Count degree an % upper Total Count % Strongly Disagree Nomarl Agree agree Total 2 18.2% 18.2% 54.5% 28 7.5% 70.0% 22.5% 11 99 52 6.5% 58.9% 31.0% 90 53 4.5% 57.7% 34.0% 10 12.0% 36.0% 40.0% 26 228 130 6.5% 57.0% 32.5% 11 9.1% 100.0% 40 0% 100.0% 168 3.6% 100.0% 156 3.8% 100.0% 25 12.0% 100.0% 16 400 4.0% 100.0% Chi-Square Tests 151 Value Asymp Sig (2sided) df 12 057 20.827 12 053 2.314 Pearson Chi-Square a 128 20.594 Likelihood Ratio Linear-by-Linear Association N of Valid Cases 400 a cells (35.0%) have expected count less than The minimum expected count is 44 3.5.8 Education level with Pricing structure Crosstab Pricing structure Education Below Count than high % school diploma High school diploma Count % Strongly Strongly disagree Disagree Nomarl Agree agree Total 0% 0% Associate Count degree % 0% Count Bachelor degree % Master Count degree an % upper Total Count % 6% 0% 2% 0% 54.5% 36.4% 14 19 10.0% 35.0% 47.5% 19 62 74 11.3% 36.9% 44.0% 51 84 5.1% 32.7% 53.8% 11 10 4.0% 44.0% 40.0% 32 144 191 8.0% 36.0% 47.8% 11 9.1% 100.0% 40 7.5% 100.0% 13 168 7.7% 100.0% 12 156 7.7% 100.0% 25 12.0% 100.0% 32 400 8.0% 100.0% Chi-Square Tests Value Asymp Sig (2sided) df 11.943a 16 748 Likelihood Ratio 12.997 16 673 Linear-by-Linear Association 1.417 234 N of Valid Cases 400 Pearson Chi-Square 152 Value Asymp Sig (2sided) df a 16 748 Likelihood Ratio 12.997 16 673 Linear-by-Linear Association 1.417 234 Pearson Chi-Square 11.943 a 12 cells (48.0%) have expected count less than The minimum expected count is 03 3.5.9 Education level with Value - add service Crosstab Value - add service Education Below than high school diploma High school diploma Associate degree Bachelor degree Master degree an upper Total Strongly Strongly disagree Disagree Nomarl Agree agree Total Count Count % 9.1% % 27.3% 0% Count % % % % 21 15 85 60 10.7% 50.6% 35.7% 11 74 65 7.1% 47.4% 41.7% 0% Count 9.1% 45.5% 18 6% Count 5.0% 52.5% 37.5% 1.2% Count 12 16.0% 48.0% 32.0% 38 1.0% 193 153 9.5% 48.2% 38.2% 11 9.1% 100.0% 40 5.0% 100.0% 168 1.8% 100.0% 156 3.2% 100.0% 25 4.0% 100.0% 12 400 3.0% 100.0% Chi-Square Tests Value Asymp Sig (2sided) df 22.833a 16 118 19.111 16 263 Linear-by-Linear Association 223 637 N of Valid Cases 400 Pearson Chi-Square Likelihood Ratio a 13 cells (52.0%) have expected count less than The minimum expected count is 11 3.5 10 Education level with Convenience in procedure Crosstab 153 Convenience in procedure Education Below than high school diploma High school diploma Associate degree Bachelor degree Master degree an upper Strongly Strongly disagree Disagree Nomarl Agree agree Total Count % 0% Count % Count % % % 94 15 84 15 36 5% 219 168 4.2% 100.0% 156 5.8% 100.0% 25 4.0% 100.0% 124 9.0% 54.8% 31.0% 40 2.5% 100.0% 48 4.0% 60.0% 28.0% 11 9.1% 100.0% 49 9.6% 53.8% 30.8% 1 17 10.1% 56.0% 29.2% 4.0% % 21 17 0% Count 2.5% 52.5% 42.5% 6% Count 18.2% 45.5% 27.3% 0% Count Total 19 400 4.8% 100.0% Chi-Square Tests Value Asymp Sig (2sided) df 14.864a 16 535 12.695 16 695 Linear-by-Linear Association 162 687 N of Valid Cases 400 Pearson Chi-Square Likelihood Ratio a 12 cells (48.0%) have expected count less than The minimum expected count is 06 3.5.11 Education level with Customer suppot service Crosstab Education Customer suppot service Disagree Nomarl Agree Below than high school diploma High school diploma Associate degree Count % Count % Count % 18.2% 81.8% 0% 29 2.5% 72.5% 22.5% 127 38 1.8% 75.6% 22.6% Strongly agree Total 11 0% 100.0% 40 2.5% 100.0% 168 0% 100.0% 154 Count Bachelor degree % % 1 18 % 15 300 156 6% 100.0% 4.0% 72.0% 24.0% Count Total 30 5.1% 75.0% 19.2% Count Master degree an upper 117 25 0% 100.0% 83 3.8% 75.0% 20.8% 400 5% 100.0% Chi-Square Tests Value Asymp Sig (2sided) df 16.146a 12 185 15.239 12 229 Linear-by-Linear Association 064 800 N of Valid Cases 400 Pearson Chi-Square Likelihood Ratio a cells (45.0%) have expected count less than The minimum expected count is 06 3.5.12 Education level with Loss cost Crosstab Education Loss cost Strongly disagree Below than high school diploma Count High school diploma Count Associate degree Count Bachelor degree Count % % % % Disagree Nomarl Agree 18.2% 36.4% 0% 3.6% 3.2% Master degree Count an upper % 12.0% Count 16 Total % Strongly agree 9.1% 27.3% 12 13 20.0% 30.0% 32.5% 31 64 47 18.5% 38.1% 28.0% 24 46 58 15.4% 29.5% 37.2% 4.0% 24.0% 16.0% 32.0% 73 127 129 18.2% 31.8% 32.2% Total 11 9.1% 100.0% 40 17.5% 100.0% 20 168 11.9% 100.0% 23 156 14.7% 100.0% 25 16.0% 100.0% 55 400 13.8% 100.0% Chi-Square Tests Value df Asymp Sig (2sided) 155 Pearson Chi-Square 24.226a 16 085 Likelihood Ratio 22.413 16 130 Linear-by-Linear Association 882 348 N of Valid Cases 400 a cells (36.0%) have expected count less than The minimum expected count is 44 3.5.13Education level with Adapting cost Crosstab Adapting cost Education Strongly Strongly disagree Disagree Nomarl Agree agree Total Below than high school Count diploma % 0% Count High school diploma Associate degree Bachelor degree Master degree an upper % Count 90 0% 44 13 0% 52.0% 28.0% % 47 1.3% 57.7% 28.2% % 92 0% Count 12 2.4% 54.8% 28.0% % 21 1.2% Count 0% 52.5% 30.0% % 0% 81.8% 9.1% 0% Count Total 5% 225 111 1.5% 56.2% 27.8% 11 9.1% 100.0% 40 17.5% 100.0% 23 168 13.7% 100.0% 20 156 12.8% 100.0% 25 20.0% 100.0% 56 400 14.0% 100.0% Chi-Square Tests Value Asymp Sig (2sided) df Pearson Chi-Square 9.220a 16 904 Likelihood Ratio 11.204 16 797 Linear-by-Linear Association 315 575 N of Valid Cases 400 a 13 cells (52.0%) have expected count less than The minimum expected count is 06 3.5.14 Education level with Move in cost Crosstab Education Move in cost Total 156 Strongly Disagree Nomarl Agree agree Below than high school diploma Count High school diploma Count Bachelor degree 0% % Associate degree 9.1% 81.8% % Count 17 % 145 12 % 134 23 0% Count 35 % 345 156 1.9% 100.0% 8.0% 92.0% 168 0% 100.0% 7.7% 85.9% 4.5% 40 5.0% 100.0% 10.1% 86.3% 3.6% Count 11 9.1% 100.0% 7.5% 85.0% 2.5% Master degree an Count upper % Total 34 25 0% 100.0% 14 8.8% 86.2% 3.5% 400 1.5% 100.0% Chi-Square Tests Value Asymp Sig (2sided) df Pearson Chi-Square 13.163a 12 357 Likelihood Ratio 13.731 12 318 Linear-by-Linear Association 269 604 N of Valid Cases 400 a 11 cells (55.0%) have expected count less than The minimum expected count is 17 3.5.15 Education level with attractiveness of other service providers Crosstab Attractiveness of other service provider Education Below than high school diploma High school diploma Associate degree Bachelor degree Strongly Strongly disagree Disagree Nomarl Agree agree Total Count % Count % Count % Count 0% 7.5% 4.2% 5 18.2% 45.5% 36.4% 11 15 20.0% 27.5% 37.5% 47 44 59 28.0% 26.2% 35.1% 53 48 45 11 0% 100.0% 40 7.5% 100.0% 11 168 6.5% 100.0% 156 157 % 3.2% Count Master degree an upper % 12.0% Count Total 34.0% 30.8% 28.8% 20.0% 32.0% 32.0% 18 % 115 4.5% 116 131 28.8% 29.0% 32.8% 3.2% 100.0% 25 4.0% 100.0% 20 400 5.0% 100.0% Chi-Square Tests Value Asymp Sig (2sided) df 14.726a Likelihood Ratio Linear-by-Linear Association 16 545 14.783 Pearson Chi-Square 16 541 2.774 096 N of Valid Cases 400 a cells (36.0%) have expected count less than The minimum expected count is 50 3.5.16 Education level with Customer relationship Crosstab Customer relationship Education Below than high school diploma High school diploma Associate degree Bachelor degree Master degree an upper Total Count % Count % Count % Count % Count % Count % Strongly Strongly disagree Disagree Nomarl Agree agree Total 18.2% 13 53 41 67 41 23.1% 42.9% 26.3% 10 32.0% 20.0% 40.0% 29 7.2% 55 36 4.0% 14 31.5% 32.7% 24.4% 5.8% 11 32.5% 27.5% 35.0% 16 9.5% 27.3% 36.4% 18.2% 2.5% 113 142 108 28.2% 35.5% 27.0% 11 0% 100.0% 40 2.5% 100.0% 168 1.8% 100.0% 156 1.9% 100.0% 25 4.0% 100.0% 400 2.0% 100.0% Chi-Square Tests Value Asymp Sig (2sided) df Pearson Chi-Square 16.907 a 16 392 Likelihood Ratio 16.960 16 388 158 Linear-by-Linear Association N of Valid Cases 2.001 157 400 a 11 cells (44.0%) have expected count less than The minimum expected count is 22 159 Apendix 4: Results of Regression and correlation Model Summary Model R R Square Adjusted R Square Std Error of the Estimate 859a 737 737 41500 912b 832 831 33216 926c 858 857 30632 936d 877 875 28564 944e 892 890 26787 949f 900 899 25712 950g 903 902 25375 ANOVA Model Sum of Squares Regression df Mean Square 192.451 192.451 68.546 398 260.998 Regression 217.198 108.599 43.800 397 260.998 Regression 223.840 74.613 37.157 396 260.998 Regression 228.769 57.192 32.228 395 260.998 Regression 232.727 46.545 28.270 394 260.998 Regression 235.016 39.169 25.982 393 260.998 Regression 235.757 33.680 25.240 392 000f 523.068 000g 064 260.998 592.475 399 399 Residual 000e 066 Total 648.694 399 Residual 000d 072 Total 700.969 399 Residual 000c 082 Total 795.185 399 Residual 000b 094 Total 984.334 399 Residual 000a 110 Total 1.117E3 399 Residual Sig .172 Total F Residual Total Coefficients 160 Unstandardized Coefficients Std Error Standardized Coefficients Beta Collinearity Statistics Model B t Sig (Constant) 193 072 2.675 008 Customer relationship 800 024 859 33.428 000 (Constant) -.019 059 -.318 751 Customer relationship 499 028 536 17.983 Loss cost 344 023 (Constant) -.633 Customer relationship Tolerance VIF 2.100 446 14.977 000 476 2.100 091 -6.935 000 464 026 498 17.897 000 464 2.155 295 022 383 13.463 000 443 2.255 252 030 185 8.414 000 743 1.345 (Constant) 279 145 1.927 055 396 026 425 15.370 000 410 2.442 Loss cost 237 022 307 10.855 000 390 2.562 Calling quality 242 028 178 8.661 000 742 1.348 Attractiveness of other service provider -.162 021 -.198 -7.773 000 481 2.079 (Constant) -.101 145 -.696 487 Customer relationship 322 026 346 12.347 000 351 2.852 Loss cost 205 021 266 9.825 000 374 2.672 Calling quality 476 Customer relationship 000 Calling quality 1.000 Loss cost 1.000 242 026 178 9.223 000 742 1.348 -.153 020 -.187 -7.806 000 479 2.087 206 028 7.427 000 511 1.957 (Constant) -.336 145 -2.314 021 Customer relationship 271 026 291 10.246 000 313 3.191 Loss cost 189 020 245 9.327 000 367 2.724 Calling quality 201 026 148 7.695 000 689 1.451 -.143 019 -.174 -7.548 000 475 2.105 Attractiveness of providers Convenience procedure Attractiveness of providers other in other 172 161 Convenience procedure in 190 027 159 7.092 000 506 1.977 167 028 144 5.884 000 426 2.349 (Constant) -.404 145 -2.794 005 Customer relationship 260 026 279 9.849 000 308 3.246 Loss cost 178 020 232 8.830 000 359 2.788 Calling quality 173 027 127 6.415 000 627 1.595 -.140 019 -.171 -7.516 000 474 2.108 162 028 136 5.884 000 463 2.161 Pricing structure 163 028 141 5.836 000 425 2.352 Value - add service 097 029 080 3.393 001 443 2.259 Pricing structure Attractiveness of providers other Convenience procedure in Predictors: (Constant), Customer relationship Predictors: (Constant), Customer relationship, Loss cost Predictors: (Constant), Customer relationship, Loss cost, Calling quality Predictors: (Constant), Customer relationship, Loss cost, Calling quality, Attractiveness of other providers Predictors: (Constant), Customer relationship, Loss cost, Calling quality, Attractiveness of other providers, Convenience in procedure Predictors: (Constant), Customer relationship, Loss cost, Calling quality, Attractiveness of other providers, Convenience in procedure, Pricing structure Predictors: (Constant), Customer relationship, Loss cost, Calling quality, Attractiveness of other providers, Convenience in procedure, Pricing structure, Value - add service 162 ... analyze factors affecting customer loyalty in the mobile communications market in Hanoi, dissertation uses the experimental model of customer loyalty in the mobile communications market in Ho Chi Minh... effectiveness of the factors affecting the customers loyalty in the mobile information services in the long term To accurately evaluate the factors that affect customer loyalty on mobile communication. .. following: - Identify factors and quantify by scales to analyze factors affecting to customer loyalty on mobile communication market in Hanoi - Research and analyze the factors affecting customer loyalty