I I V niversity of Economics II Institute of social studies Ho Chi Minh City The Hague Vietnam Netherlands I i I Vietnam - Netherlands Project forMA Program in Development Economics I -000 - I I I I DETERMINANTS OF I I APPLICATION SOFTWARE ADOPTION: The Case of SMEs in HCMC By LE THANH BINH Academic Supervisor: Associate Dr NGUYEN DINH THO ~ I Ho Chi Minh City, March 2011 i L -~ -~ -~ -· -~ - ~ _j Declaraiion I declare that the thesis hereby submitted for the Master degree at the VietnamNetherlands Program for M.A in Development Economics is my own work and has not been previously submitted by me at another university for any degree Ho Chi Minh City, March 2011 Le Thanh Binh Acknowledgements In the first of all, my heartfelt thank goes to my supervisor, Associate Dr Nguyen Dinh Tho During the course of my thesis research and writing, I received precious guidance, useful comments and encouragements My deepest thank also goes to Associate Professor Dr Nguyen Trong Hoai, Co- Director of Vietnam - The Netherlands Program for M.A in Development Economics, for his encouragements during the course and thesis research In addition, I wish to offer much thanks to: my kindly and enthusiastic classmate, Mr Nguyen Ngoc Danh, who was always ready to give me his ideas and recommendations; my friend and ex-colleague, Mr Marc Nguyen, who assisted me to edit English writing of my thesis My heartfelt gratitude also goes to my wife and my son, Trinh and Trung Quoc, who are my love and motivation during the studying time 11 ;: • Abstract This study mms to investigate the factors that affect the adoption of application software by SMEs in Ho Chi Minh City A sample of 140 firms in HCMC was surveyed to test the model It was found that perceived usefulness and ease of use of application software are potential predictors of application software adoption It was also found that IT • knowledge has impacts on the adoption of application software BOM Innovativeness was not significant It may be due to the limitation of this study Some questionnaires were answered by who were not from BOM and the sample was not large enough to make sure the results are entirely credible The findings of this study suggest that the government and software firms should focus on improving the IT knowledge of people who work in the office, especially people from BOM Software fim1s should promote the usefulness and ease of use of application software In addition, the laws of intellectual property and laws to protect the software users are also recommended to the government Ill Table of Contents DECLARATION I ACKNOWLEDGEMENTS 11 ABSTRACT III TABLE OF CONTENTS IV LIST OF FIGURES VI LIST OF TABLES VII LIST OF EXHIBITS VIII ABBREVIATION VIII CHAPTER - OVERVIEW ! 1.1 INTRODUCTION 1.2 THE CONTEXT OF VIETNAMESE SOFTWARE INDUSTRY 1.3 OBJECTIVES OF THE RESEARCH 1.4 RESEARCH QUESTIONS 1.5 RESEARCH METHODOLOGY AND SCOPE CHAPTER 2- LITERATURE REVIEW 2.1 INTRODUCTION 2.2 DEFINITIONS 2.3 THEORIES AND EMPIRICAL STUDIES 3.1 Innovative ness 2.3.2 Perceived Usefulness 2.3.3 Perceived Ease ofUse 11 2.3.4 IT Knowledge 11 IV 2.3.5 Size ofFirms 12 Competitive Intensity 13 Type ofBusiness , 13 CHAPTER - METHODOLOGY 15 3.1 INTRODUCTION 15 3.2 RESEARCH PROCESS ········· 15 3.2.1 Questionnaire Design 15 3.2.2 Survey Design 16 3.3 0PERATIONALIZATION OF MEASUREMENT 16 3.1 Dependent Variable 16 3.3.2 Independent Variables 18 3.3.2.1 BOM Innovativeness 18 3.3.2.2 BOM IT Knowledge 18 3.3.2.3 BOM Perceived Usefulness 19 3.3.2.4 BOM Perceived Ease of Use 20 3.3.3 Moderator Variables 21 3.3.3.1 Competitive Intensity 21 3.3.3.2 Business Size 22 3.3.3.3 Type of Business 22 3.3.4 Measurement Scale and Notation ofVariables 22 3.3.4.1 Measurement Scale 22 3.3.4.2 Notation of Variables 23 3.4 SURVEY DESIGN 23 CHAPTER 4- FINDINGS AND DISCUSSION 24 4.1 INTRODUCTION 24 4.2 THE SAMPLE ~· 24 4.3 DESCRIPTIVE ANALYSIS 24 v 4.4 RELIABILITY ANALYSIS 26 4.5 REVISE MODEL 27 4.6 FACTOR ANALYSIS.·········· 28 4.7 OLS REGRESSION 31 4.8 HYPOTHESIS TESTING 34 4.9 DISCUSSIONS 37 CHAPTER 5- IMPLICATIONS AND CONCLUSIONS 39 5.1 INTRODUCTION 39 • 5.2 MAIN RESULTS CONTRIBUTION AND IMPLICATIONS 39 5.3 LIMITATIONS AND DIRECTIONS FOR FUTURE RESEARCHES 42 REFERENCES · 43 APPENDICES 48 APPENDIX 1: THE QUESTIONNAIRE .48 APPENDIX 2: NOTATION OF VARIABLES 55 APPENDIX 3: CRONBACH'S ALPHA 57 APPENDIX 4: FACTOR ANALYSIS 60 APPENDIX 5: HETEROSKEDASTICITY TEST 63 vi List of Figures Figure 2.1 -Conceptual Model 13 Figure 3.1 - Research Process 15 Figure 4.1 -Revised Conceptual Model 26 List of Tables Table 2.1 -List of Applications Table 4.1- Type ofBusiness 24 Table 4.2- Business Size 24 Table 4.3 -Application Software 25 Table 4.4- Reliability Analysis 25 Table 4.5- Rotated Component Matrix( a) 27 Table 4.6- KMO and Bartlett's Test 28 Table 4.7- KMO and Bartlett's Test (ASADOPT) 29 Table 4.8- Component Matrix (a) 29 Table 4.9- Frequency Analysis of sum values of two items of CINT 30 Table 4.10- Business Type with dummy variables 30 Table 4.11 -The dummy variables of the business size 31 Table 4.12 -Regression with data survey 32 Table 4.13- Summary of Hypothesis Testing 34 V11 List of Exhibits Exhibit 3.1 -Application Software Adoption 17 Exhibit 3.2 - Innovativeness 18 Exhibit 3.3- IT Knowledge 18 Exhibit 3.4 - Perceived usefulness 19 Exhibit 3.5- Perceived ease of use 20 Exhibit 3.6- Competitive intensity 21 Abbreviation BOM Board Of Managers VIII Determinants of Application Software Adoption: The Case of SMEs in HCMC Chapter Overview 1.1 Introduction Nowadays information technology plays a crucial role in economic development Among them, the software industry is growing faster than most other industries The world software market was approximately US$11 billion in 1988 (Schware 1992), and is about US$600 billion (Rizk 2002) Software industry is viewed as a good choice for developing countries to leverage their economy and strengthen their national competitive power (Lee & Lee 1994) For example, the annual growth rate of India's software industry has been consistently over 20 percent since 1996 The revenues from software industry oflndia were US$8.7 billions in 2001 (Economy Watch) The annual growth rate of Brazil's software industry has been also 11%-12% (Schware 1992) According to Schware (1992), the developing countries should focus more on the domestic software market; therefore, it makes software exports develop faster because of increases in experience and innovation in software production In acknowledging the importance of the software industry to the economic development, the Vietnamese government has paid much attention to developing the software industry in general, and the domestic software market in particular by issuing many policies to support the software industry and software firms and by investing a lot of money to its development Vietnam's domestic software market has a lot of potential with approximately 7,000 organizations, 6,000 state firms, and nearly 260,000 limited firms However, the number of firms using application software continues to be very limited In the year of 2006, the revenues of application software were only 93 million USD (Laodong 2007) Many conferences have been organized to discuss on how to leverage the demand of domestic application software but to date, no effective , Determinants of Application Software Adoption: The Case of SMEs in HCMC Vai phdn mJm tmg d1,mg, cong ty chung toi CO dU(J'C thong tin th6ng ke lien quan din doanh nghi?p re h071 I By using application software, our firm would find it more effective in making business decisions V&i phdn mJm U11g d1;1ng, cong ty chung toi c6 thi dua D D D D D quyit djnh hi¢u qua han Overall, our firm would consider that application software is useful for managing business activities N6i chung, cong ty chung toi xem phdn mJm U11g d?tng Ia hiru dl;lng cho vi¢c quan ly cac hor;~t dong doanh nghi¢p Perceived ease of use I DD'Q'C nh~n thrrc D D D D D Ia d~ sfr dl}.ng Application software which is easy to learn would be good for our firm Phdn mJm tmg d1;1ng di h9c se t6t cho doanh nghi¢p chung toi D D D D D It is easy to look up the information related to our business by using application software Thcjt di dang tim kiim thong tin lien quan din doanh nghi¢p bi:mg phdn mim tmg d1,mg • D D D D D It is easy to use application software to improve the communication between the departments in our firm Thcjt di dang sit d1;1ng phdn mJm img d1;1ng di cai tiin vi¢c trao dJi thong tin giu cac b{J phcjn doanh nghi¢p D D D D D Overall, our firm prefer application software which is easy to use N6i chung, cong ty chung t6i thich phdn mJm tmg d1;1ng D D D D D 50 ' Determinants of Application Software Adoption: The Case of SMEs in HCMC di sir dl:fng h(Jn IT Knowledge I Ki~n thrrc cong ugh~ thong tin I would rate my own understanding of computers (before my company computerized) as very good compared to other people in similar positions T6i tv acmh gia muc a(J hidu biit vJ may tinh cua t6i (tru&c c6ng ty t6i tin h9c h6a) Ia rdt t6t so v&i nhfmg nguai khac vf tri tu(Jng au(Jng D D D D D Competitive Intensity I CU'img dq c~nh tranh The rivalry among firms in the industry in which my company is operating is very intense Sv C(lnh tranh cac doanh nghi¢p cimg nganh cua c6ng ty chung t6i rdt miinh li?t D D· 0 There are many products/services in the market which are different from ours but perform the same functions C6 nhiJu san phdm va djch Vl:f cimg thi truirng khac • vfrf SCtn phdm VG djch Vl:f CUQ chung toi nhung thl!C hi¢n cimg chuc nang D D D D D Business Size I D(} 1611 doanh nghi~p Number of employees: s6 lu(111g nhan vien 51 Determinants of Application Software Adoption: The Case of SMEs in HCMC Type of Business I Lo~i doanh nghi~p You can circle more than one Bc;m co thi ch(Jn nhidu han mr}t D D (i) Manufacturipg Simxudt (ii) Commerce Thuong mt;ti (iii) Service Djch V¥ Ownership I Quy~n sO' hfru D D (i) State-owned Sa hi'ru nha nubc (ii) Private-owned Sa hU:u tu nhan (iii) Joint-stock C6phdn Adoption of application software I Sv Iva chQn phAn m~m rrng dt,mg D Does your firm use application software? YES/NO Cong ty br;m co su dl;lng phbn mJm ung dl;lng khong? COIKHONG Strongly Strongly Disagree Agree Our firm has applied application software efficiently and effectively in financial management D D D D D 52 Determinants of Application Software Adoption: The Case of SMEs in HCMC C6ng ty chung t6i dii cip dt,mg phan mem tmg d1,mg hi¢u qua va co kit qua vi¢c quan l;! tai chinh Our firm has applied application software efficiently and effectively in the improvement of our inventory control activities and purchasing activities C6ng ty chung t6i dii cip d11ng phdn mJm ung d11ng hi¢u qua va co kit qua vao vi¢c cai tiin ccic ho(}t d(Jng mua hang va quan l;! kho D D D D D Our firm has applied application software efficiently and effectively to improve our sales activities and customer services C6ng ty chung t6i dii cip d11ng phdn mJm tmg d11ng hi¢u qua va co kit qua di cai tiin ccic ho(}t d(jng kinh doanh va dfch Vl:f khcich hang D D D D D Our firm has applied application software efficiently and effectively in the utilization a11d simplification of human resource management C6ng ty chung t6i dii cip d11ng phdn mdm tmg dl;lng hi¢u qua va co kit qua vi¢c t6i uu hoa va dan gian hoa vi¢c quan ly nguJn hrc D D D D D Our firm has applied application software efficiently and effectively in the simplification of manufacturing resources planning C6ng ty chung t6i dii cip dl;lng phdn mJm ung dt,mg hi¢u qua va co kit qua vi¢c dan gian hoa vi¢c ho(}ch djnh ngudn hrc san xu.dt D D D D D Software Applications I Cac phin m~m lfng dt,mg 53 Determinants of Application Software Adoption: The Case of SMEs in HCMC For each computer applications in use in your company, please put a tick against the application (This is a survey to know how many firms use each software application) D6i vbi mJi ung d!,tng may tinh dang Slf dz;ng cong ty, vui long aanh ddu vao 1Ing dz;ng a6 (Day Ia khao sat biit baa nhieu cong ty Slf dz;ng tirng phdn m~m ung dz;ng) Application I Ung d1}ng In-use I Dang sir d1}ng Accounting I Ke toan D D D D D D D D Inventory control I Quim ly kho • Sales I Quim ly kinh doanh Purchasing I Mua himg Personnel and Payroll I Nhan SlJ va tien Iuong CRM I Quim ly quan h~ khach hang SCM I Quc'm ly chu6i cung cap MRP I Ho~ch djnh ngu6n )lJc san xuat Others (please specify) I Khac (vui long ghi ro) 54 Determinants of Application Software Adoption: The Case of SMEs in HCMC ' Appendix 2: Notation of Variables Notation Innovativeness INNO BOM usually has original ideas INNOl BOM would sooner create something new than improve INN02 something existing BOM often risks doing things differently INN03 Perceived usefulness OPU By using application software, our firm would manage OPUl information related to our business more easily By using application software, our firm would process and OPU2 obtain information related to our business more quickly By using application software, our firm would obtain the OPU3 statistic data related to our business more cheaply By using application software, our firm would find it more OPU4 effective in making business decisions Overall, our firm would consider that application software OPUS is useful for managing business activities • Perceived ease of use OPEU Application software which is easy to learn would be good OPEU1 for our firm It is easy to look up the information related to our business OPEU2 by using application software It is easy to use application software to improve the OPEU3 communication between the departments in our firm • 55 Determinants of Application Software Adoption: The Case of SMEs in HCMC Overall, our firm prefer application software which is easy OPEU4 to use IT Knowledge ITKNOW I would rate my own understanding of computers (before my ITKNOW company computerized) as very good compared to other people in similar positions Competitive Intensity CINT The rivalry among firms in the industry in which my CINTI company is operating is very intense There are many products/services in the market which are · CINT2 different from ours but perform the same functions Our firm has applied application software efficiently and AASI effectively in financial management Our firm has applied application software efficiently and AAS2 effectively in the improvement of our inventory control activities and purchasing activities Our firm has applied application software efficiently and AAS3 effectively to improve our sales activities and customer services Our firm has applied application software efficiently and AAS4 effectively in the utilization and simplification of human resource management Our firm has applied application software efficiently and AAS5 effectively in the simplification of manufacturing resources planning 56 Determinants of Application Software Adoption: The Case of SMEs in HCMC Appendix 3: Cronbach's Alpha • Cronbach's Alpha of AAS factor Reliability Statistics Cronbach's Alpha 873 Cronbach's Alpha Based on Standardized Items N of Items 876 i i Item-Total Statistics I I Scale Mean if Item Deleted Scale Variance if Item Deleted I Appiy AS in financial management [AAS1] Apply AS in inventory control [AAS2] Apply AS in sales and customer services [AAS3] 13.83 15.485 14.14 14.617 I I I I i I I Corrected Item-Total Correlation Squared Multiple Correlation I Cronbach's Alpha if Item Deleted 699 593 i 847 677 542! 853 I I i 13.84: 15.426 729 566 Apply AS in human resource management [AAS4] Apply AS in manufacturing resource planing [AAS5] I 841 I I • I I : 13.95 14.03 i i 14.564 758 598 832 14.822 657 558 858 : Cronbach's Alpha of Innovativeness factor Reliability Statistics Cronbach's Alpha 453 i i' I Cronbach's Alpha Based on Standardized , Items ; N of Items 452 57 Determinants of Application Software Adoption: The Case of SMEs in HCMC Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted 6.10 2.648 3131 6.48 2.648 322: BOM has origi nal ideas [INN01] BOM would cr eat something new [INN02] BOM takes ris ks [INN03] • • Corrected Item-Total Correlation ! I I Squared Multiple Correlation Cronbach's Alpha if Item Deleted ' 114 289 117 273 040 i 486 ! I' 6.69 3.024 201 i Cronbach 's Alpha of Perceived Usefulness factor Reliability Statistics Cronbach's Alpha 821 Cronbach's Alpha Based on Standardized ' Items N of Items 828 Item-Total Statistics Scale Mean if Item Deleted Firm would ma nage information m ore easily [OPU1] Firm would process information more quickly [OPU2] Firm would ob tain statistic data more cheaply [OPU 3] Firm would ma ke business decis ions more effectively (OP U4] AS (applicatio n software) is seemed to be useful for managing biz activities [OPU 5] i 15.50 15.56 I 15.95 16.02 ! Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation 8.206: 674 i I 578! 770 7.710 753: 634: 745 8.798 396 I 180 i 855 8.346 621 ! 438 I I 15.69' Cronbach's Alpha if Item Deleted i I 784 I 7.894 675 i 494 768 58 Determinants of Application Software Adoption: The Case of SMEs in HCMC • Cronbach's Alpha of Perceived Ease ofUse factor Reliability Statistics Cronbach's Alpha Based on Cronbach's Standardized Alpha Items N of Items 808! 808 I Item-Total Statistics I I Scale Mean if Item Deleted AS being easy to learn would be good [OPEU1] Easy to look up information by using AS [OPEU2] Easy to use AS to improve communication [OPEU3] Firm prefers AS which is easy to use [OPEU4] • 11.70 I Scale Variance if Item Deleted I ! i Corrected Item-Total Correlation 5.8771 I Squared Multiple Correlation 644 516 : I I I Cronbach's Alpha if Item Deleted 751 I ' ' ! I 11.98 I 6.244! i 653 I I ! I 11.75 11.57 745 4581 ! I 7.013 i I 538! I ! : ' i I i 669 I 6.293 i 365 798 I 506 738 I Cronbach's Alpha of Competitive Intensity factor Reliability Statistics • Cronbach's Alpha 809 I Cronbach's Alpha Based ' on Standardized Items N of Items 809: Item-Total Statistics Scale Mean if Item Deleted Competition is very high [CINT1] Many products/services in the market [CINT2] : Scale Variance if Item Deleted I I ' ' Squared Multiple Correlation I I Cronbach's Alpha if Item Deleted I I 3.57 ~ i Corrected Item-Total Correlation ! 1.159 i 680 I 462 (a) 680 462 (a) i 3.73 t 1.159 i l a The value IS negat1ve due to a negat1ve average covanance among 1tems Th1s v1olates reliability model assumptions You may want to check item codings 59 • Determinants of Application Software Adoption: The Case of SMEs in HCMC Appendix 4: Factor Analysis • Factor analysis of Adoption of Application Software factor (Dependent factor) KMO and Bartlett's Test Kaiser-Meyer-Oikin Measure of Sampling Adequacy Bartlett's Test of Sphericity 801 Approx Chi-Square 294.530 df Sig 10 000 Total Variance Explained Component I ···-·· ;_ _Extraction Sums of S(!uared Loadings ~n.it@IE:i@!l't~!~s -· , %-of T ! %of , I I Variw1ce Cumulative % ! ! Total Variance I Cumulative% I Total 3.341 i 708 416 299 237 I I I 66.816 14.154 8.315 5.985 4.73o I I I 66.816 80.970 89.285 95.270 100.000 3.341 66.816 66.816 Extractron Method: Pnncrpal Component Analysrs Component Matrix(a) Componen t • Apply AS in financial management [AAS1] Apply AS in inventory control [AAS2] Apply AS in sales and customer services [AAS3] Apply AS in human resource management [AAS4] Apply AS in manufacturing resource planing [AAS5] 814 799 835 853 784 Extractron Method: Prrncrpal Component Analysis a components ~xtracted 60 Determinants of Application Software Adoption: The Case of SMEs in HCMC • Factor analysis of independent factors KMO and Bar1:1ett's Test Kaiser-Meyer-Oikin Measure of Sampling Adequacy .818 Approx Chi-Square Bartlett's Test of Sphericity 650.893 df Sig 66 000 Rotated Component Matrix(a) -~ Q_ompcm_ent ~ ~ I I ! • Firm would manage information more easily [OPU1] Firm would process information more quickly [OPU2] Firm would obtain statistic data more cheaply [OPU3] Firm would make business decisions more effectively [OPU4] AS (application software) is seemed to be useful for managing biz activities [OPU5] AS being easy to learn would be good [OPEU1] Easy to look up information by using AS [OPEU2] Easy to use AS to improve communication [OPEU3] Fim• prefers AS which is easy to use [OPEU4] A member of BOM is very good at computer [ITKNOW] Competition is very high [CINT1] Many products/services in the market [CINT2] i 884 112 ' i • 150 127 i I I I 835 I 299 419 243: 164 i -.018 ' i 309 -.420 I I ! I 655 247! 287: -.228 ! I I I 629 360 I 407 I ! -.014 I ; 314 796 030: 241 : 105 799' 257: -.157 263: 563 397 -.220 262 799 096 176 187 367 752 252: 165 825 123 ~ 146 826 129 I I i I I I 057 i : I 215 Extraction Method: Pnnc1pal Component Analysis Rotation Method: Varimax with Kaiser Normalization a Rotation converged in iterations 61 - - Determinants of Application Software Adoption: The Case of SMEs in HCMC Total Variance Explained Component _ I Total i l 1 5.405 1.226 1.179 45.045 10.215 9.828 818 715 6.814 65.088 71.903 5.962 77.865 645 574 5.372 4.783 83.237 88.020 10 11 463 346 242 208 3.858 2.883 2.019 1.735 91.878 94.761 96.780 98.514 12 178 1.486 S~!._~_l.,oadings InitiaL Eigen values Extraction Sums of i %of ' , I % of : ' Variance Cumulative % Total I Variance i Cumulative % 45.045 55.260 5.405 1.226 1.179 45.045 10.215 9.828 818 6.814 100.000 I 45.045 55.260 65.088 71.903 I 2.839 2.663 2.116 1.011 23.656 45.844 63.478 8.424! 71.903 23.656 22.188 17.634 I I I I I ! i ! I ! Rotation Sums of Sguar~Load_!_r1~_ %of I I Total I Variance I Cumulative % I : I Extract1on Method: Pnnc1pal Component Analysis 62 " Determinants of Application Software Adoption: The Case of SMEs in HCMC Appendix 5: Heteroskedasticity Test • , White Heteroskedasticity Test: F-statistic 1.465173 Obs*R-squared 55.24219 Probability Probability Test Equation: Dependent Variable: RESID"2 Method: Least Squares Date: 04/02/10 Time: 15:02 Sample: 140 Included observations: 103 Excluded observations: 36 Coefficient Variable 0.186862 0.424713 CINT -1.320573 CINT*DBTYPE1 0.289535 CINT*DBTYPE2 -0.689046 CINT*ITKNOW -0.212865 CINT*OPEU -0.453140 CINT*OPU -0.796483 CINT*SIZE1 -0.046529 CINT*SIZE2 CINT*SIZE3 -0.382309 1.026955 DBTYPE1 DB TYPE 1*DBTYPE2 -0.533199 DBTYPE1*1TKNOW -0.109505 DBTYPE1*0PEU 0.321087 DBTYPE1*0PU 0.158296 DBTYPE1*SIZE1 0.036310 DBTYPE1*SIZE2 -0.593641 0.314866 DBTYPE1*SIZE3 -1.640799 DBTYPE2 -0.156045 DBTYPE2*1TKNOW -0.426130 DBTYPE2*0PEU 0.155155 DBTYPE2*0PU 1.353349 DBTYPE2*SIZE 1.446942 DBTYPE2*SIZE2 1.557673 DBTYPE2*SIZE3 0.110262 ITKNOW 0.195025 ITKNOW"2 0.060786 ITKNOW*OPEU -0.033448 ITKNOW*OPU 0.479597 ITKNOW*SIZE1 0.221317 ITKNOW*SIZE2 0.125691 ITKNOW*SIZE3 Std Error 0.735589 1.002619 0.701837 0.666914 0.823499 0.435150 0.477587 1.123535 1.075971 1.148450 0.554746 0.735529 0.398436 0.261101 0.220662 0.646598 0.490640 0.585653 1.008187 0.320739 0.254442 0.230159 0.915306 0.938666 1.005033 0.658018 0.195493 0.183650 0.173432 0.502364 0.453395 0.576705 c j • 0.086139 0.140914 t-Statistic 0.254030 0.423603 -1.881594 0.434142 -0.836729 -0.489178 -0.948811 -0.708908 -0.043244 -0.332891 1.851215 -0.724920 -0.274836 1.229745 0.717369 0.056155 -1.209931 0.537632 -1.627475 -0.486518 -1.674764 0.674119 1.478575 1.541488 1.549872 0.167567 0.997606 0.330989 -0.192861 0.954680 0.488133 0.217946 Pro b 0.8004 0.6734 0.0650 0.6658 0.4062 0.6266 0.3467 0.4813 0.9657 0.7404 0.0693 0.4715 0.7844 0.2238 0.4761 0.9554 0.2313 0.5929 0.1092 0.6285 0.0995 0.5030 ~448 0.1287 0.1267 0.8675 0.3227 0.7419 0.8478 0.3438 0.6273 0.8282 63 Determinants of Application Software Adoption: The Case of SMEs in HCMC ~ OPEU OPEU''2 OPEU*OPU OPEU*SIZE1 OPEU*SIZE2 OPEU*SIZF3 OPU OPU/\2 OPU*SIZE1 OPU*SIZE2 OPU*SIZE3 SIZE1 SIZE2 SIZE3 R-squared Adjusted R-squared S E of regression Sum squared resid Log likelihood Durbin-Watson stat -0.159585 0.452674 -0.352539 0.016422 0.096415 0.170322 0.134130 0.128682 1.042333 0.578937 0.301311 1.921397 0.617227 0.346564 1.780989 0.713037 0.528604 1.348905 0.649483 0.399557 1.625507 0.022157 0.094443 0.234603 -0.425140 0.302151 -1.407046 -0.563475 0.311440 -1.809257 -0.339788 -0.838352 0.405305 0.592215 0.709486 0.834710 0.139487 0.721411 0.193353 -0.094012 -0.111381 0.844058 0.536332 Mean dependent var 0.170278 S.D dependent var Akaike info criterion 0.669103 Schwarz criterion 25.51881 -74.29203 F-statistic 2.06622_9_ Prob(F-statistic) 0.7257 0.8654 0.3017 0.0597 0.0802 0.1827 0.1096 0.8154 0.1648 0.0757 0.4053 0.4074 0.8474 0.9117 0.489802 0.734559 2.335768 3.512443 1.465173 0.086139 p-value > 0.05 => Heteroskedasticity does not exist in this model 64 ... a software development finn Determinants of Application Software Adoption: The Case of SMEs in HCMC 2.3 Theories and empirical studies Application software refers to many kinds of software applications,... focuses on application software in Ho Chi Minh City's market Determinants of Application Software Adoption: The Case of SMEs in HCMC Applications chosen for the study are the ones used for managing... Hypothesis 2: Firms with the BOM who perceive the usefulness of application software have positive effect on adopting application software 10 Determinants of Application Software Adoption: The Case