A study ò factors afecting the credit activity ò small and medium sized enteprises at vietinbank ò thanh hoa province

Thesis for the Degree of Master A study of factors affecting the credit activity of small and medium-sized enteprises at Vietinbank of Thanh Hoa province June 2017 Department of Business Administration Graduate School of Soongsil University THUY, DO MAI Thesis for the Degree of Master A study of factors affecting the credit activity of small and medium-sized enteprises at Vietinbank of Thanh Hoa province June 2017 Department of Business Administration Graduate School of Soongsil University THUY, DO MAI Thesis for the Degree of Master A study of factors affecting the credit activity of small and medium-sized enteprises at Vietinbank of Thanh Hoa province A thesis supervisor: Gim, Gwang – Yong Thesis submitted in partial fulfillment of the requirement for the Degree of Master June 2017 Department of Business Administration Graduate School of Soongsil University THUY, DO MAI To approve the submitted thesis for the Degree of Master by Thuy, Do Mai Thesis Committee Chair Park Jong Woo (signature) Member Gim Gwang Yong (signature) Member Hoang Dinh Hai (signature) June 2017 Graduate School of Soongsil University ACKNOWLEDGEMENTS Before starting the thesis, I would like to express profound gratitude to the teachers of Korean Soongsil University who taught and conveyed useful knowledge and experience during my study at the University And I would like to give my thanks to Hong Duc University which has created all conditions so I may complete this topic In the course of this study, I have received much help from many teachers I would like to express heartfelt thanks to the lecturers of the Faculty of Business Administration, especialy Prof Gim, Gwang - Yong who is whole-hearted to instruct, help and answer my questions in implementing this study I’d like to give my thanks to Vietinbank Thanh Hoa which helps me to complete this course Finanlly, I’d like to thank people at the office, my friends, family and relatives who are devoted to help me during my work and study Again, thank for your help! TABLE OF CONTENTS ABSTRACT vii CHAPTER INTRODUCTION vii 1.1 Thesis’s rationale 1.2 Research objectives 1.2.1 General objectives 1.2.2 Specific objectives Research objects and scopes 1.4 Research methods 1.4.1 Information collection method 1.4.2 Synthesis and analysis methods 1.4.3 Data processing tools 1.5 Structure of the thesis CHAPTER THEOR ETICAL BACKGROUND 2.1 Small and medium-sized enterprises 2.1.1 Definitions 2.1.2 Factors affecting activities of enterprises 2.1.2.1 Internal environment 2.1.2.2 Micro environment (Operational environment) 2.1.2.3 Macro environment 11 2.2 Basic issues of credit 12 -i- 2.2.1 Definition of credit 12 2.2.2 Credit characteristics 13 2.2.3 Credit roles 15 2.2.4 Credit classification 16 2.2.5 Credit effect assessment targets 18 2.2.5.1 Qualitative targets 18 2.3 Access to credit 26 2.4 Asymmetry theory in credit operations 27 2.5 Overview of research projects 29 CHAPTER RESEARCH METHODS 34 3.1 Research process 34 3.2 Research methodology 36 3.2.1 Qualitative research method 36 3.2.2 Quantitative research method 37 3.2.3 Research sample 38 3.2.4 Data collection 39 3.3 Proposed research model 40 3.4 Data processing method 41 CHAPTER RESEARCH R ESULTS 44 4.1 Situation of credit of small and medium-sized enterprises (SMEs) in Joint-Stock Commercial Bank for Industry and Trade, Thanh Hoa branch 44 - ii - 4.1.1 Situation of capital mobilization of Joint-Stock Commercial Bank for Industry and Trade, Thanh Hoa branch (Vietinbank Thanh Hoa) 44 4.1.2 Situation of outstanding loans to SMEs of the branch 47 4.1.3 Situation of overdue debts and bad debts in lending to SMEs 50 4.1.4 Situation of credit effectiveness to SMEs 52 4.1.5 Assessment of situation of credit to SMEs in VietinBank- Thanh Hoa branch 54 4.1.5.1 Results in risk management 54 4.1.5.2 Limitations in risk management 57 4.2 Analysis of models of factors affecting the access to credit of small and medium enterprises at Vietinbank Thanh Hoa branch 62 4.2.1 Descriptive statistics analysis 62 4.2.2 Bianary logistics regression analysis 71 4.2.2.1 General conformity testing 71 4.4.2.3 Testing of explanation of the model 72 4.4.2.4 Binary Logistic Regression Results 73 4.3 Research results 76 CHAPTER CONCLUSION AND MANAGEMENT IMPLICA TION 81 5.1 Conclusion 81 5.2 Management implication 83 5.3 Limitation of the research 85 - iii - REFER ENC ES 87 APPENDICES 91 - iv - REFERENCES In Vietnamese Annual Reports, reported business results, balance sheet accounting, business oriented development of the Bank for Foreign Trade Success According to Bloomberg, Capital for SME: Bank say ? www.kiemtoan.com.vn Nguyen Huu Tai Curriculum theory-currency financing Hanoi Publishing House Statistics, 2002 Decision No 1627/2001/ QD-NHNN dated 31/12/2001 on the regulation on lending by credit institutions to clients of the Governor of the Stat e Bank Decision No 127/2005/ QD-NHNN dated 03/02/2005 issued amending and supplementing the Decision No 1627/2001 / QD-NHNN dated 12/31/2001 Decision No 90/2001/ ND-CP dated 23/11/2001 of the Government on support for SME development Frederic S Mishkin Money, Banking and Financial Markets, Science and Technical Publishing House Hanoi, 2001 - 87 - Ha Vy SME integration vague, www.vnexpress.net, 2005 Phan Thu Ha Commercial banks, Hanoi Publishing House Statistics, 2006 Phan Dinh Khoi Factors impacting on access to official and non-official credit of farmer households in Mekong River delta, Science Magazine of Can Tho university, part D: Policital, Economic and Law science: 28, 38-53, 2013 Phan Dinh Khoi, Christopher Gan, Gilbert V Nartea, David A Cohen Formal and informal rural credit in the Mekong River Delta of Vietnam: Interaction and accessibility Journal of Asian Economics (26), 1–13, 2013 Tra n Tho Dat Borrowing cost and segment of the rural credit market Economic Research Magazine 10/1998 In English Diagne, A Determinants of household access to and participation in formal and informal credit markets in Malawi Discussion Paper 67 International Food Policy Research Institute, Washington, D.C., 1999 - 88 - He, Guangwen & Li, Lili People’s Republic of China: Financial Demand Study of Farm Households in Longren/Guizhou of PRC ADB Technical Assistance Consult’s Report Project Number: 35412, 2005 Hoff, K, Stiglitz, J E Introduction: imperfect information and rural credit markets World Bank Economic Review, Vol 4, 1993 Kochar, A An empirical investigation of rationing constraints in rural credit markets in India Journal of Development Economics, 53(2), 339–371, 1997 Li, X., Gan, C., & Hu, B Accessibility to microcredit by Chinese rural households Journal of Asian Economics, 22(3), 235–246 2011 M Barslund & F Tarp Formal and Informal Rural Credit in Four Provinces of Vietnam, Journal of Development Studies,Vol 44, No 4, 485–503, April 2008 Mahmoud S Mohieldin and Peter W Wright Formal and Informal Credit Markets in Egypt Economic Development and Cultural Change, Vol 48, No 3, pp 657670, 2000 - 89 - Mohamed, K Access to formal and quasi-formal credit by smallholder farmers and artisanal fishermen: A case of Zanzibar Tanzania: Mkuki na Nyota Publishers, 2003 Nuryartono N, Zeller M and Stefan Schwarze Credit Rationing of Farm Households and Agricultural production: Empirical Evidence in the Rural Areas of Central Sulawesi, Indonesia Conference on International Agricultural Research for Development Stuttgart-Hohenheim, October 11-13, 2005 Stiglitz, J E., and Weiss, A Credit Rationing in Markets with Imperfect Information American Economic Review 71, 1981 Sumon Kumar Bhaumik Interaction between formal and informal sector credit: new evidence from India, Applied Economics Letters, 15, 527–531, 2008 Xavier Giné Access to capital in rural Thailand: An estimated model of formal vs informal credit, Journal of Development Economics (96),16–29, 2011 - 90 - APPENDICES - 91 - Appendix GENDER Cumulative Frequency Valid Percent Valid Percent Percent Male 189 63.0 63.0 63.0 Female 111 37.0 37.0 100.0 Total 300 100.0 100.0 AGE Cumulative Frequency Percent Valid Less than 25 Valid Percent Percent 84 28.0 28.0 28.0 25-40 129 43.0 43.0 71.0 40-50 62 20.7 20.7 91.7 Over 50 25 8.3 8.3 100.0 300 100.0 100.0 Total bachelor Cumulative Frequency Valid High school Vocational school College Percent Valid Percent Percent 75 25.0 25.0 25.0 66 22.0 22.0 47.0 74 24.7 24.7 71.7 - 92 - University 78 26.0 26.0 97.7 2.3 2.3 100.0 300 100.0 100.0 Postgraduate Total sector Frequency Percent Valid Trade and service Construction industry Agriculture Total Valid Cumulative Percent Percent 97 32.3 32.3 32.3 150 50.0 50.0 82.3 53 17.7 17.7 100.0 300 100.0 100.0 timepayment Cumulative Frequency Valid Percent Valid Percent Percent Short-term 238 79.3 79.3 79.3 Long-term 62 20.7 20.7 100.0 300 100.0 100.0 Total - 93 - purpose Cumulative Frequency Valid Borrowing for Percent Valid Percent Percent 227 75.7 75.7 75.7 Other 73 24.3 24.3 100.0 Total 300 100.0 100.0 business combank Cumulative Frequency Valid Not very good Percent Valid Percent Percent 115 38.3 38.3 38.3 Normal 31 10.3 10.3 48.7 Good 15 5.0 5.0 53.7 133 44.3 44.3 98.0 2.0 2.0 100.0 300 100.0 100.0 Very good Not very good Total - 94 - customer Cumulative Frequency Valid Percent Valid Percent Percent Not very good 13 4.3 4.3 4.3 Normal 15 5.0 5.0 9.3 Good 42 14.0 14.0 23.3 190 63.3 63.3 86.7 40 13.3 13.3 100.0 300 100.0 100.0 Very good Not very good Total friend Cumulative Frequency Valid Percent Valid Percent Percent Not very good 18 6.0 6.0 6.0 Normal 19 6.3 6.3 12.3 Good 26 8.7 8.7 21.0 220 73.3 73.3 94.3 17 5.7 5.7 100.0 300 100.0 100.0 Very good Not very good Total - 95 - asset Cumulative Frequency Valid Percent Valid Percent Percent Yes 213 71.0 71.0 71.0 No 87 29.0 29.0 100.0 300 100.0 100.0 Total interest Frequency Valid Percent Valid Cumulative Percent Percent Completely unreasonable 39 13.0 13.0 13.0 Unreasonable 36 12.0 12.0 25.0 Normal 27 9.0 9.0 34.0 188 62.7 62.7 96.7 10 3.3 3.3 100.0 300 100.0 100.0 Reasonable Very reasonable Total - 96 - creditpolicy Valid Frequency Percent Percent Valid Cumulative Percent Completely unreasonable 32 10.7 10.7 10.7 Unreasonable 34 11.3 11.3 22.0 Normal 49 16.3 16.3 38.3 124 41.3 41.3 79.7 61 20.3 20.3 100.0 300 100.0 100.0 Reasonable Very reasonable Total accesscap Cumulative Frequency Valid Percent Valid Percent Percent co 183 61.0 61.0 61.0 khong 117 39.0 39.0 100.0 Total 300 100.0 100.0 Descriptive Statistics N Minimum Maximum Mean Std Deviation ownerexp 300 21 4.06 3.082 firmage 300 18 4.30 2.600 size 300 431 47.746 7.54477 8.860501 loansize 300 150 17000 3435.93 3469.642 Valid N (listwise) 300 - 97 - Block 0: Beginning Block Classification Table a,b Predicted accesscap Observed Step co accesscap Percentage khong Correct co 183 100.0 khong 117 0 Overall Percentage 61.0 a Constant is included in the model b The cut value is 500 Variables in the Equation B S.E Step Constant -.447 Wald df 118 14.280 Sig Exp(B) 000 639 Omnibus Tests of Model Coefficients Chi-square Step df Sig Step 132.690 16 000 Block 132.690 16 000 Model 132.690 16 000 Model Summary Cox & Snell R Step -2 Log likelihood Square 268.559a Nagelkerke R Square 357 - 98 - 485 a Estimation terminated at iteration number because parameter estimates changed by less than 001 Hosmer and Lemeshow Test Step Chi-square df Sig 4.799 779 Contingency Table for Hosmer and Lemeshow Test accesscap = co Observed Step Expected accesscap = khong Observed Expected Total 30 28.991 1.009 30 29 27.806 2.194 30 25 26.727 3.273 30 24 24.942 5.058 30 24 22.308 7.692 30 18 18.962 12 11.038 30 16 15.177 14 14.823 30 8 10.250 22 19.750 30 5.639 24 24.361 30 10 2.196 27 27.804 30 - 99 - Classification Table a Predicted accesscap Observed Step accesscap co co khong Percentage khong Correct 162 21 88.5 33 84 71.8 Overall Percentage 82.0 a The cut value is 500 Variables in the Equation B S.E Wald Sig Exp(B) 764 333 5.266 022 2.147 AGE 094 191 244 622 1.099 bachelor -.273 140 3.817 051 761 ownerexp -.103 054 3.604 058 902 firmage -.177 075 5.529 019 838 size 031 045 482 488 1.032 sector 459 239 3.683 055 1.583 loansize 000 000 971 325 1.000 timepayment 2.097 397 27.895 000 8.138 purpose 409 38.735 000 12.759 Step 1a GENDER 2.546 - 100 - df combank -.054 111 240 624 947 customer 372 207 3.242 072 1.451 friend 503 218 5.316 021 1.654 asset 808 339 5.662 017 2.243 interest 329 155 4.506 034 1.390 creditpolicy -.219 130 2.809 094 804 Constant -10.867 1.752 38.474 000 000 a Variable(s) entered on step 1: GENDER, AGE, bachelor, ownerexp, firmage, size, sector, loansize, timepayment, purpose, combank, customer, friend, asset, interest, creditpolicy - 101 -