Vốn cho tăng trưởng kinh tế bền vững trường hợp nghiên cứu tại tỉnh đồng nai, việt nam

MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAM BANKING UNIVERSITY OF HO CHI MINH CITY CAPITAL FOR SUSTAINABLE ECONOMIC GROWTH: THE CASE FROM DONG NAI PROVINCE IN VIETNAM DISSERTATION IN FINANCE - BANKING HCMC, 09/2022 MINISTRY OF EDUCATION AND TRAINING STATE BANK OF VIETNAM BANKING UNIVERSITY OF HO CHI MINH CITY CAPITAL FOR SUSTAINABLE ECONOMIC GROWTH: THE CASE FROM DONG NAI PROVINCE IN VIETNAM DISSERTATION IN FINANCE - BANKING Major: Finance - Banking CODE: 34 02 01 Advisor: Assoc Prof Dr HCMC – 09/2022 i COMMITMENT The author guarantee that the dissertation “Capital for sustainable economic growth: the case from Dong Nai province in Vietnam” is the research Except for the references cited in this dissertation The author guarantee that the whole or a small part of this dissertation has never been published or used to obtain a degree elsewhere No other people’s products/studies have been used in this dissertation that has not been appropriately cited This dissertation has never been submitted to receive any degree at any university or other training institution HCMC, September 02, 2022 D ii ACKNOWLEDGEMENT The author would like to sincerely thank the Banking University of Ho Chi Minh City administrators and teachers, especially the teachers directly teaching K22 Ph D students who have enthusiastically taught, passed on experience, and supported the author while studying at the Banking University of Ho Chi Minh City The author would like to express his gratitude and respect to the science instructor, Assoc Prof Dr enthusiastically supported, encouraged, and instructed the author to implement and complete this dissertation The author also expressed gratitude to the Board of Directors and officers at enterprises in Dong Nai province, managers who participated in the author’s interviews and surveys The author also thanked family and friends for their help, creating favorable conditions for the author to complete the dissertation Although the author has made great efforts, the dissertation cannot avoid its shortcomings I hope to receive comments from my teachers and friends Sincerely! HCMC, September 02, 2022 Author iii ABSTRACT In recent years, the mobilization and use of investment capital, especially foreign investment capital, have significantly affected the country’s speed and quality of economic growth and each locality Besides, Dong Nai has favorable conditions to develop the marine economy with the Southeast provinces These economic, demographic, and geographic factors help facilitate Dong Nai’s promotion of economic development However, Dong Nai still faces significant challenges in developing specific sectors and products with comparative advantages Attracting and effectively using investment capital is always a complex problem for locations still weak in infrastructure, financial sophistication, attractive policies, the efficiency of using capital sources, and many inadequacies when implementing investment projects Therefore, this study aims to identify factors affecting the investment capital attraction for sustainable economic growth The author tested Cronbach’s Alpha, confirmatory factor analysis (CFA), and structural equation model (SEM) Based on the research results, the author proposed policy implications for attracting investment capital for sustainable economic growth in Dong Nai province The study surveyed 000 managers related to enterprises with investment capital in Dong Nai province, but 939 samples were processed and answered 39 questions The data was collected from June 2020 to November 2020 Based on the things mentioned above, eight factors affect the investment capital attraction for sustainable economic growth in Dong Nai province Technology (Te); Working and living environment (Wle); infrastructure (In); investment costs (Ic); human resources (Hr); investment policies (Ip); regional connectivity (Rc); and public service quality (Psq) Besides The results are also scientific and important for Dong Nai province researchers and policymakers to apply research results to improve investment capital attraction based on high and low standardized coefficients Finally, the author proposed policy implications for attracting investment capital to improve Dong Nai province's sustainable economic growth: technology, Working and living environment, infrastructure, investment costs, human resources, investment policies, regional connectivity, and public service quality Keywords: Capital, sustainable, economic, growth, Dong Nai, Vietnam iv TÓM TẮT LUẬN ÁN Trong năm gần đây, việc huy động sử dụng vốn đầu tư, vốn đầu tư nước ngồi ảnh hưởng khơng nhỏ đến tốc độ chất lượng tăng trưởng kinh tế nước địa phương Bên cạnh đó, Đồng Nai có điều kiện thuận lợi để phát triển kinh tế với tỉnh Đông Nam Bộ Các yếu tố kinh tế, nhân học địa lý giúp tạo điều kiện cho Đồng Nai thúc đẩy phát triển kinh tế Tuy nhiên, Đồng Nai phải đối mặt với thách thức lớn việc phát triển ngành, sản phẩm cụ thể có lợi so sánh Thu hút sử dụng hiệu vốn đầu tư toán phức tạp địa phương cịn yếu sở hạ tầng, khó khăn tài chính, sách hấp dẫn, hiệu sử dụng nguồn vốn, nhiều bất cập triển khai dự án đầu tư Do đó, nghiên cứu nhằm xác định nhân tố ảnh hưởng đến việc thu hút vốn đầu tư để tăng trưởng kinh tế bền vững Tác giả kiểm định độ tin cậy thơng qua hệ số Cronbach’s Alpha, phân tích nhân tố khẳng định (CFA), mơ hình cấu trúc tuyến tính (SEM) Trên sở kết nghiên cứu, tác giả đề xuất hàm ý sách thu hút vốn đầu tư để tăng trưởng kinh tế bền vững địa bàn tỉnh Đồng Nai Nghiên cứu khảo sát 000 cán quản lý liên quan đến doanh nghiệp có vốn đầu tư địa bàn tỉnh Đồng Nai, có 939 mẫu xử lý trả lời 39 câu hỏi Dữ liệu thu thập từ 6-11/2020 Dựa liệu trên, kết có yếu tố ảnh hưởng đến việc thu hút vốn đầu tư để tăng trưởng kinh tế bền vững tỉnh Đồng Nai Công nghệ (Te); Môi trường sống làm việc (Wle); sở hạ tầng (In); chi phí đầu tư (Ic); nguồn nhân lực (Hr); sách đầu tư (Ip); kết nối khu vực (Rc); chất lượng dịch vụ cơng (Psq) Kết mang tính khoa học quan trọng nhà nghiên cứu hoạch định sách tỉnh Đồng Nai việc ứng dụng kết nghiên cứu để nâng cao khả thu hút vốn đầu tư dựa hệ số chuẩn hóa cao thấp Cuối cùng, tác giả đề xuất hàm ý sách thu hút vốn đầu tư nhằm nâng cao tốc độ tăng trưởng kinh tế bền vững tỉnh Đồng Nai: công nghệ, Môi trường sống làm việc, sở hạ tầng, chi phí đầu tư, nguồn nhân lực, sách đầu tư, kết nối vùng chất lượng dịch vụ công Từ khóa: Vốn, bền vững, kinh tế, tăng trưởng, Đồng Nai, Việt Nam v CONTENTS Page Commitment Acknowledgment Summary of dissertation List of acronyms List of tables List of figures CHAPTER INTRODUCTION 1 Reason for study 1 Objectives of the study General objective 2 Specific objective Research questions 4 Scope and delimitation of the study 4 Scope and objective of the study 4 The time of study 5 Research methods Scientific and practical significance of research 6 The scientific significance of research 6 The practical significance of research 7 Organization of the study CHAPTER 2: LITERATURE REVIEW AND RESEARCH MODEL Theoretical framework 1 Economic growth 2 Sustainable economic growth 13 Capital and investment attraction for sustainable economic growth 17 The relationship between investment attraction 20 Factors affecting investment attraction 23 2 Review of related studies 2 Review of related studies in other countries 31 31 vi 2 Review of related study in Vietnam 37 The experiences in investment capital attracting 42 Asian countries 42 Vietnam 47 3 The lessons in investment capital attraction for Dong Nai 51 The gap in the studies 53 The scientific basis for building a research model 54 The scientific basis for building a research model 54 Research model and research hypothesis Summary of chapter CHAPTER RESEARCH METHODOLOGY 55 59 60 Research procedure 60 Qualitative research 63 Qualitative research results 63 2 Group discussion results 76 3 Questionnaire design 76 The results of the scale test through preliminary quantification 77 Exploratory Factor Analysis (EFA) 83 3 Quantitative research 86 3 Sample size and sampling techniques 86 3 Data collection instrument 87 3 Data analysis techniques 87 Summary of chapter CHAPTER RESEARCH RESULTS Overview of Dong Nai province 91 92 92 1 Geographical position 92 Topography 92 Land 93 4 Climate 94 Population 94 Infrastructure 94 vii Traffic 95 Resources 95 Tourism 96 10 Status of attracting investment capital from 2019 to 2020 96 Research results 99 Descriptive statistics of the research sample 99 2 Cronbach alpha test of reliability 102 Exploratory factor analysis (EFA) and Confirmatory factor analysis 109 4 Testing of structural equation modeling (SEM) 113 Testing model by Bootstrap (N = 000) 118 Testing analysis of variance (ANOVA) 119 T-Test the means of two groups (T-test) 121 Summary of chapter CHAPTER 5: CONCLUSIONS AND POLICY IMPLICATIONS 130 131 Conclusions 131 Policy implications 134 Technology 134 2 Regional connectivity 136 Public service quality 138 Investment costs 140 5 Human resources 142 Investment policies 144 Infrastructure 147 Working and living environment 149 Limitations and suggestions for further research 152 Limitations of the research 152 Suggestions for further research 152 Summary of chapter REFERENCES APPENDIX 152 i vii-xx viii LIST OF ACRONYMS No Code Contents ANOVA Analysis of variance CFA Confirmatory factor analysis EFA Exploratory factor analysis EU European Union FDI Foreign direct investment FL Factor loading GDP Gross Domestic Product GNI Gross National Income GNP Gross National Product 10 HCMC Ho Chi Minh City 11 HR Human resources 12 IC Investment costs 13 IMF International Monetary Fund 14 IN Infrastructure 15 IP Investment policies 16 KMO Kaiser - Meyer – Olkin 17 MAN Management capacity Organization for Economic Co-operation and 18 OECD Development 19 PSQ Public service quality 20 RC Regional connectivity 21 SDM Spatial Durbin Model 22 SEM structural equation modeling 23 Sig Significant 24 SPSS Statistic Package for Social Sciences 25 TE Technology 26 WLE Working and living environment lii 10 e1 e2 e3 e4 e5 e6 e7 e8 e9 e10 e11 e12 e13 e14 e15 e16 e17 e18 e19 e20 e21 e22 e23 e24 e25 e26 e27 e28 e29 e30 e31 e32 e33 e34 e35 e36 e37 e38 e39 Estimate S E C R 687 080 555 755 046 16 229 309 019 16 075 110 016 029 101 020 055 086 015 594 086 036 397 134 035 872 161 031 145 243 033 424 170 013 13 598 249 017 14 805 104 012 505 218 015 14 112 233 013 18 499 195 028 025 304 030 10 211 094 034 776 167 028 957 206 039 290 192 046 197 170 047 639 225 044 167 167 012 13 415 178 016 11 255 034 014 466 211 013 15 956 108 036 956 196 035 553 228 024 506 238 023 10 491 483 046 10 553 522 040 13 200 235 091 581 313 087 590 236 070 386 690 078 833 168 090 863 199 020 10 075 354 039 133 110 019 794 P Label *** *** *** *** *** *** 017 *** *** *** *** *** *** *** *** *** *** 006 *** *** *** *** *** *** *** 014 *** 003 *** *** *** *** *** 010 *** *** *** 062 *** *** *** liii Model Fit Summary CMIN Model Default model Saturated model Independence model NPAR CMIN DF P CMIN/DF 152 2753 498 628 000 385 780 000 39 32331 079 741 000 43 632 RMR, GFI Model Default model Saturated model Independence model RMR GFI AGFI PGFI 027 871 840 701 000 000 197 312 275 296 Baseline Comparisons Model Default model Saturated model Independence model NFI RFI IFI TLI Delta1 rho1 Delta2 rho2 915 900 933 921 933 000 000 000 000 000 000 000 000 Parsimony-Adjusted Measures Model Default model Saturated model Independence model PRATIO PNFI PCFI 848 775 790 000 000 000 000 000 000 NCP Model Default model Saturated model Independence model NCP LO 90 HI 90 2125 498 1966 695 2291 769 000 000 000 31590 079 31005 129 32181 356 FMIN Model Default model Saturated model Independence model FMIN F0 LO 90 HI 90 935 266 097 443 000 000 000 000 34 468 33 678 33 055 34 308 Model Default model Independence model RMSEA LO 90 HI 90 PCLOSE 060 058 062 000 213 211 215 000 RMSEA CFI liv AIC Model Default model Saturated model Independence model AIC BCC BIC CAIC 3057 498 3071 039 3793 910 3945 910 1560 000 1629 488 5338 956 6118 956 32409 079 32412 554 32598 027 32637 027 ECVI Model Default model Saturated model Independence model ECVI LO 90 HI 90 MECVI 260 090 437 274 663 663 663 737 34 551 33 928 35 182 34 555 HOELTER Model Default model Independence model HOELTER HOELTER 05 01 235 244 24 25 Scalar Estimates (Group number - Default model) Maximum Likelihood Estimates Regression Weights: (Group number - Default model) ICA < - IP ICA < - IN ICA < - PSQ ICA < - WLE ICA < - RC ICA < - HR ICA < - IC ICA < - TE SEG < - ICA Ip1 < - IP Ip2 < - IP Ip3 < - IP Ip4 < - IP In1 < - IN In2 < - IN In3 < - IN In4 < - IN In5 < - IN Psq1 < - PSQ Psq2 < - PSQ Estimate S E C R 236 051 630 149 049 059 158 033 712 077 024 197 178 031 810 092 025 703 102 028 625 475 027 17 624 295 020 14 775 000 325 061 21 897 936 283 851 131 297 183 000 313 062 21 297 971 054 17 923 050 056 18 666 004 056 17 795 000 487 195 616 P Label *** 002 *** 001 *** *** *** *** *** *** *** *** *** *** *** *** *** lv Psq3 < - PSQ Wle1 < - WLE Wle2 < - WLE Wle3 < - WLE Wle4 < - WLE Rc1 < - RC Rc2 < - RC Rc3 < - RC Rc4 < - RC Hr1 < - HR Hr2 < - HR Hr3 < - HR Hr4 < - HR Ic1 < - IC Ic2 < - IC Ic3 < - IC Ic4 < - IC Ica2 < - ICA Ica3 < - ICA Seg1 < - SEG Seg2 < - SEG Seg3 < - SEG Seg4 < - SEG Ica1 < - ICA Te4 < - TE Te3 < - TE Te2 < - TE Te1 < - TE Estimate S E C R 856 308 026 000 918 021 43 170 857 034 25 258 961 035 27 266 000 735 036 20 348 573 057 10 118 944 075 12 649 000 935 025 37 923 805 056 14 436 900 061 14 778 000 950 023 41 284 979 040 24 279 111 043 25 772 094 026 42 290 994 029 34 315 000 390 059 23 697 975 053 18 488 377 059 23 227 000 000 945 016 58 006 939 027 34 167 965 025 38 282 P Label *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** Standardized Regression Weights: (Group number - Default model) ICA < - IP ICA < - IN ICA < - PSQ ICA < - WLE ICA < - RC ICA < - HR ICA < - IC ICA < - TE SEG < - ICA Ip1 < - IP Ip2 < - IP Ip3 < - IP Ip4 < - IP In1 < - IN In2 < - IN In3 < - IN In4 < - IN Estimate 100 089 115 089 175 105 108 531 556 541 698 056 072 753 958 741 750 lvi In5 < - IN Psq1 < - PSQ Psq2 < - PSQ Psq3 < - PSQ Wle1 < - WLE Wle2 < - WLE Wle3 < - WLE Wle4 < - WLE Rc1 < - RC Rc2 < - RC Rc3 < - RC Rc4 < - RC Hr1 < - HR Hr2 < - HR Hr3 < - HR Hr4 < - HR Ic1 < - IC Ic2 < - IC Ic3 < - IC Ic4 < - IC Ica2 < - ICA Ica3 < - ICA Seg1 < - SEG Seg2 < - SEG Seg3 < - SEG Seg4 < - SEG Ica1 < - ICA Te4 < - TE Te3 < - TE Te2 < - TE Te1 < - TE Estimate 686 653 944 097 987 889 867 941 942 629 483 870 963 899 815 866 895 839 903 955 940 834 681 900 664 866 885 961 924 869 920 Covariances: (Group number - Default model) IP < > IN IP < > PSQ IP < > WLE IP < > RC IP < > HR IP < > IC IN < > PSQ IN < > WLE IN < > RC IN < > HR IN < > IC PSQ < > WLE PSQ < > RC PSQ < > HR Estimate S E - 008 005 - 008 005 - 055 014 - 001 008 - 016 009 - 008 008 001 009 010 016 - 008 014 036 016 163 018 006 017 - 044 017 - 060 020 C R P Label -1 718 086 -1 584 113 -4 096 *** - 148 883 -1 786 074 -1 000 317 091 928 605 545 - 539 590 263 024 308 *** 331 740 -2 586 010 -2 940 003 lvii PSQ < > IC WLE < > RC WLE < > HR WLE < > IC RC < > HR RC < > IC HR < > IC IP < > TE IN < > TE PSQ < > TE WLE < > TE RC < > TE HR < > TE IC < > TE e31 < > e32 e27 < > e28 e23 < > e24 e19 < > e20 e15 < > e16 e11 < > e12 e6 < > e7 e43 < > e44 e44 < > e45 e45 < > e46 e32 < > e33 e30 < > e31 e28 < > e29 e26 < > e27 e24 < > e25 e22 < > e23 e20 < > e21 e18 < > e19 e14 < > e15 e12 < > e13 e10 < > e11 e9 < > e10 e7 < > e8 e5 < > e6 Estimate S E C R P Label 035 017 074 038 - 089 028 -3 230 001 117 031 759 *** 043 029 501 133 - 001 027 - 029 977 - 024 025 - 943 346 102 029 557 *** - 014 009 -1 586 113 044 016 789 005 008 017 503 615 116 031 776 *** 018 027 677 499 019 030 641 522 112 028 947 *** 000 012 - 010 992 040 012 305 *** 336 024 13 738 *** 053 010 583 *** - 242 132 -1 841 066 - 005 006 - 759 448 - 069 014 -4 803 *** 006 017 349 727 - 009 009 - 981 326 - 004 017 - 234 815 - 076 029 -2 596 009 061 026 321 020 086 044 963 050 - 076 056 -1 366 172 079 031 538 011 - 018 040 - 461 645 053 028 932 053 - 067 030 -2 212 027 202 056 604 *** 181 014 12 745 *** - 053 013 -4 017 *** - 073 014 -5 382 *** - 280 070 -3 998 *** 100 024 175 *** lviii Correlations: (Group number - Default model) IP < > IN IP < > PSQ IP < > WLE IP < > RC IP < > HR IP < > IC IN < > PSQ IN < > WLE IN < > RC IN < > HR IN < > IC PSQ < > WLE PSQ < > RC PSQ < > HR PSQ < > IC WLE < > RC WLE < > HR WLE < > IC RC < > HR RC < > IC HR < > IC IP < > TE IN < > TE PSQ < > TE WLE < > TE RC < > TE HR < > TE IC < > TE e31 < > e32 e27 < > e28 e23 < > e24 e19 < > e20 e11 < > e12 e43 < > e44 e44 < > e45 e45 < > e46 e32 < > e33 e30 < > e31 e28 < > e29 e26 < > e27 e24 < > e25 e22 < > e23 e20 < > e21 e18 < > e19 e14 < > e15 e12 < > e13 e10 < > e11 e9 < > e10 e5 < > e6 Estimate - 045 - 038 - 159 - 004 - 048 - 026 003 020 - 018 075 368 009 - 088 - 103 065 - 111 125 050 - 001 - 032 120 - 042 094 015 127 023 022 135 - 001 167 524 238 - 022 061 - 047 - 021 - 605 256 315 - 648 210 - 083 326 - 905 902 734 - 606 - 844 372 lix Variances: (Group number - Default model) IP IN PSQ WLE RC HR IC TE e42 e41 e5 e6 e7 e8 e9 e10 e11 e12 e13 e14 e15 e16 e18 e19 e20 e21 e22 e23 e24 e25 e26 e27 e28 e29 e30 e31 e32 e33 e34 e35 e36 e37 e38 e39 e40 e43 e44 e45 e46 Estimate 127 251 372 957 678 920 783 881 414 137 307 235 - 049 - 075 191 039 194 214 284 500 100 - 216 026 214 232 115 086 560 732 193 072 191 301 249 194 297 170 093 195 110 306 230 090 240 125 073 134 253 149 SE 021 021 069 056 063 075 052 047 026 012 021 031 069 077 014 021 014 015 016 064 132 207 033 031 027 031 052 041 039 047 060 054 041 049 028 029 029 034 013 012 017 012 008 012 009 018 019 021 018 CR 977 11 686 431 17 060 10 843 12 250 15 200 18 570 16 209 11 110 14 423 493 - 708 - 980 13 509 853 13 819 14 580 17 638 769 758 -1 044 784 923 739 731 660 13 647 18 930 120 202 510 300 043 949 10 414 896 762 15 209 435 17 910 19 579 10 706 19 770 13 445 023 206 12 201 204 P Label *** *** *** *** *** *** *** *** *** *** *** *** 479 327 *** 064 *** *** *** *** 448 296 433 *** *** *** 097 *** *** *** 229 *** *** *** *** *** *** 006 *** *** *** *** *** *** *** *** *** *** *** lx Model Fit Summary CMIN Model Default model Saturated model Independence model NPAR CMIN DF P CMIN/DF 139 2979 759 641 000 649 780 000 39 32331 079 741 000 43 632 RMR, GFI Model Default model Saturated model Independence model RMR GFI AGFI PGFI 036 862 832 709 000 000 197 312 275 296 Baseline Comparisons Model Default model Saturated model Independence model NFI RFI IFI TLI Delta1 rho1 Delta2 rho2 908 893 926 914 926 000 000 000 000 000 000 000 000 Parsimony-Adjusted Measures Model Default model Saturated model Independence model PRATIO PNFI PCFI 865 785 801 000 000 000 000 000 000 NCP Model Default model Saturated model Independence model NCP LO 90 HI 90 2338 759 2172 784 2512 185 000 000 000 31590 079 31005 129 32181 356 FMIN Model Default model Saturated model Independence model FMIN F0 LO 90 HI 90 177 493 316 678 000 000 000 000 34 468 33 678 33 055 34 308 Model Default model Independence model RMSEA LO 90 HI 90 PCLOSE 062 060 065 000 213 211 215 000 RMSEA CFI lxi AIC Model Default model Saturated model Independence model AIC BCC BIC CAIC 3257 759 3270 142 3931 189 4070 189 1560 000 1629 488 5338 956 6118 956 32409 079 32412 554 32598 027 32637 027 ECVI Model Default model Saturated model Independence model ECVI LO 90 HI 90 MECVI 473 296 658 486 663 663 663 737 34 551 33 928 35 182 34 555 HOELTER Model Default model Independence model HOELTER HOELTER 05 01 221 229 24 25 Regression Weights: (Group number - Default model) Parameter ICA < - IP ICA < - IN ICA < - PSQ ICA < - WLE ICA < - RC ICA < - HR ICA < - IC ICA < - TE SEG < - ICA Ip1 < - IP Ip2 < - IP Ip3 < - IP Ip4 < - IP In1 < - IN In2 < - IN In3 < - IN In4 < - IN In5 < - IN Psq1 < - PSQ Psq2 < - PSQ Psq3 < - PSQ Wle1 < - WLE Wle2 < - WLE Wle3 < - WLE SE SE-SE Mean Bias SE-Bias 047 000 225 - 011 001 049 000 150 001 001 047 000 142 - 016 001 024 000 076 - 001 000 050 001 161 - 017 001 032 000 076 - 016 000 032 000 104 002 000 038 000 472 - 002 001 025 000 295 - 001 000 000 000 000 000 000 105 001 329 004 001 667 007 068 132 009 723 007 275 143 010 000 000 000 000 000 085 001 315 002 001 068 001 975 004 001 067 001 051 001 001 063 001 007 003 001 000 000 000 000 000 476 005 506 018 007 632 006 968 113 009 000 000 000 000 000 031 000 918 000 000 050 000 856 - 001 001 lxii Parameter Wle4 < - WLE Rc1 < - RC Rc2 < - RC Rc3 < - RC Rc4 < - RC Hr1 < - HR Hr2 < - HR Hr3 < - HR Hr4 < - HR Ic1 < - IC Ic2 < - IC Ic3 < - IC Ic4 < - IC Ica2 < - ICA Ica3 < - ICA Seg1 < - SEG Seg2 < - SEG Seg3 < - SEG Seg4 < - SEG Ica1 < - ICA Te4 < - TE Te3 < - TE Te2 < - TE Te1 < - TE SE SE-SE Mean Bias SE-Bias 050 000 960 - 001 001 000 000 000 000 000 039 000 735 - 001 001 149 001 552 - 021 002 243 002 909 - 035 003 000 000 000 000 000 033 000 937 002 000 217 002 777 - 028 003 241 002 869 - 031 003 000 000 000 000 000 027 000 950 000 000 057 001 976 - 004 001 060 001 108 - 003 001 033 000 096 003 000 045 000 998 004 001 000 000 000 000 000 095 001 393 003 001 057 001 976 001 001 095 001 379 002 001 000 000 000 000 000 000 000 000 000 000 023 000 945 000 000 029 000 939 000 000 023 000 964 - 001 000 lxiii Test of Homogeneity of Variances Levene Statistic ICA SEG df1 474 483 df2 4 Sig 934 934 755 748 ANOVA Sum of Squares Between Groups df Mean Square 511 628 757 883 934 811 764 394 485 938 621 SEG Within Groups 302 018 934 323 Total 304 503 938 ICA Within Groups Total Between Groups F Sig 006 092 921 105 Test of Homogeneity of Variances Levene Statistic ICA SEG df1 931 606 df2 3 Sig 935 935 425 611 ANOVA Sum of Squares Between Groups df Mean Square 753 918 761 641 935 815 764 394 471 938 490 SEG Within Groups 303 032 935 324 Total 304 503 938 ICA Within Groups Total Between Groups F Sig 127 337 512 210 lxiv Test of Homogeneity of Variances Levene Statistic ICA SEG df1 771 604 df2 3 Sig 935 935 510 613 ANOVA Sum of Squares Between Groups df Mean Square 567 856 761 826 935 815 764 394 059 938 353 SEG Within Groups 303 443 935 325 Total 304 503 938 ICA Within Groups Total Between Groups F Sig 050 369 088 353 Test of Homogeneity of Variances Levene Statistic ICA SEG 328 427 df1 df2 4 Sig 934 934 055 223 ANOVA Sum of Squares Between Groups df Mean Square 232 558 762 161 934 816 764 394 104 938 526 SEG Within Groups 302 399 934 324 Total 304 503 938 ICA Within Groups Total Between Groups F Sig 684 603 624 166 lxv Group Statistics Gender ICA SEG N Mean Std Deviation Std Error Mean Male 420 3198 88571 04322 Female Male 519 420 3680 3970 91655 55591 04023 02713 Female 519 3892 58125 02551 Independent Samples Test Levene's Test for Equality of Variances F Sig t-test for Equality of Means t df Sig (2tailed) Mean Std Error Difference Difference 95% Confidence Interval of the Difference Lower ICA SEG Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed 146 703 - 813 - 816 328 249 209 210 937 908 18 937 911 34 Upper 416 - 04817 05926 - 16447 06812 415 - 04817 05905 - 16406 06771 835 00781 03741 - 06561 08124 834 00781 03724 - 06527 08090 lxvi Group Statistics Marital status ICA SEG N Mean Std Deviation Std Error Mean Single 388 3024 89959 04567 Married Single 551 388 3775 3943 90446 55984 03853 02842 Married 551 3916 57715 02459 Independent Samples Test Levene's Test for Equality of Variances F Sig t-test for Equality of Means t df Sig (2Mean Std Error tailed) Difference Difference 95% Confidence Interval of the Difference Lower ICA SEG Equal variances assumed Equal variances not assumed Equal variances assumed Equal variances not assumed 016 901 -1 256 -1 257 036 309 073 074 937 835 98 937 848 58 Upper 210 - 07509 05981 - 19246 04228 209 - 07509 05975 - 19237 04219 942 00277 03778 - 07137 07691 941 00277 03758 - 07099 07653 ... cứu, tác giả đề xuất hàm ý sách thu hút vốn đầu tư để tăng trưởng kinh tế bền vững địa bàn tỉnh Đồng Nai Nghiên cứu khảo sát 000 cán quản lý liên quan đến doanh nghiệp có vốn đầu tư địa bàn tỉnh. .. đó, Đồng Nai có điều kiện thuận lợi để phát triển kinh tế với tỉnh Đông Nam Bộ Các yếu tố kinh tế, nhân học địa lý giúp tạo điều kiện cho Đồng Nai thúc đẩy phát triển kinh tế Tuy nhiên, Đồng. .. tỉnh Đồng Nai, có 939 mẫu xử lý trả lời 39 câu hỏi Dữ liệu thu thập từ 6-11/2020 Dựa liệu trên, kết có yếu tố ảnh hưởng đến việc thu hút vốn đầu tư để tăng trưởng kinh tế bền vững tỉnh Đồng Nai