The impact of environmental innovations on firms competitive advantage the practice in vietnam

I ACKNOWLEDGEMENT For the successful completion of this thesis, I would like to extend my sincere thanks to: Respectful lecturers of University of Economics Ho Chi Minh City, who have transferred to me valuable knowledge during my course, especially PhD Nguyen Thi Nguyet Que, who has always instructed me to fully completion of this thesis Secondly, I would like to thank my colleagues who are from enterprises in province of Dongnai, Binh Duong and Hochiminh city for helping me to collect the data for this thesis Thirdly, I would like to thank my classmates of the eMBA course, University of Economics Ho Chi Minh City for kindly helping me in data analysis Although the author has tried best for this thesis, the errors still may have taken place Therefore, the author is looking forward to the review as well as valuable feedbacks from everyone so that this thesis can be better Nguyen Anh Khoa Ho Chi Minh, Octorber 22 nd 2012 II COMMITMENT I would like to commit that this thesis, “The impact of environmental innovations on firm’s competitive advantage –The practice in Vietnam”, was scientifically achieved through my independent and serious studies The data was collected in reality with clear origin In addition, the data has never been released in any menu Nguyen Anh Khoa III TABLE OF CONTENTS ACKNOWLEDGEMENT I COMMITMENT II TABLE OF CONTENTS III LIST OF FIGURE VIII ABSTRACT Chapter INTRODUCTION 1.1 Introduction 1.2 Research Issues, Objectives & Questions 1.3 Research methodology 1.4 Significance of study 1.5 Structure of study Chapter 2: LITERATURE REVIEW 2.1 Definition of environmental innovation 2.2 Review of previous studies on environmental innovation Table 2.1: antecedent variables of environmental innovations Table 2.2: environmental innovations and dependent variables 14 2.2.1 Influential factors on environmental innovations 18 2.2.2 Impact of environmental innovations on organization’s outcomes 19 2.3 Development of theoretical model and research hypothesis 21 2.3.1 The influence of environmental regulations on environmental innovations 21 2.3.2 Environmental innovations and managerial environmental concerns 23 2.3.3 Environmental innovations and competitive advantage of enterprise 25 2.4 Conclusion 26 IV Figure 2.1: Theoretical model 27 Chapter RESEARCH METHODOLOGY 28 3.1 Introduction 28 3.2 Research procedure 28 Figure 3.1 Research procedure 28 3.3 Questionnaires Design 29 3.3.1 Scale of managerial environmental concerns (MEC) 30 Table 3.1 Scale of managerial environmental concerns 30 3.3.2 Scale of environmental regulations (ER) 30 Table 3.2 Scale of environmental regulations 31 3.3.3 Measurement of environmental innovations variables 31 Table 3.3 Scale of environmental product innovation (EPD) 32 Table 3.4 Scale of environmental product innovation (EPS) 32 3.3.4 Measurement of firm’s competitive advantage(FCA) 33 Table 3.5 Scale of firm’s competitive advantage (FCA) 33 3.4 Data analysis techniques 33 Table 3.6 Specification for cronbach alpha and EFA method 34 3.5 Main survey 34 3.6 Conclusion 35 Chapter DATA ANALYSIS 36 4.1 Introduction 36 4.2 Main study sample profile 36 Table 4.1 Main study profile 36 4.3 Evaluating the scales 37 4.3.1 Cronbach alpha result of main survey 37 Table 4.2 Cronbach alpha result of main survey 39 V 4.3.2 EFA result of main survey 40 Table 4.3a KMO and Bartlett's Test 40 Table 4.3b Total Variance Explained 41 Table 4.3c Rotated Component Matrixa 42 Table 4.4a KMO and Bartlett's Test 43 Table 4.4b Total Variance Explained 43 Table 4.4c Rotated Component Matrixa 44 4.4 Hypothesis Testing 45 4.4.1 Normality assumption test 45 4.4.2 Hypothesis 1a,2a 45 Table 4.5 Normality assumption test 46 Table 4.6a Pearson correlation between each pairs of variables (ER,MEC), (ER,EPD), (MEC,EPD) 47 Table 4.6b MLR result of hypothesis 1a, 2a (Model summary) 48 Table 4.6c MLR result of hypothesis 1a, 2a (ANOVA) 48 Table 4.6d MLR result of hypothesis 1a, 2a (Coefficient) 48 4.4.3 Hypothesis 1b,2b 49 Table 4.7a Pearson correlation between each pairs of variables: MEC, EPS, ER 50 Table 4.7b MLR result of hypothesis 1b, 2b (Model summary) 50 Table 4.7c MLR result of hypothesis 1b, 2b (ANOVA) 51 Table 4.7d MLR result of hypothesis 1b, 2b (Coefficient) 51 4.4.4 Hypothesis 3a,3b 51 Table 4.8a Pearson correlation between each pairs of variables (EPD, EPS, FCA), 52 Table 4.8b MLR result of hypothesis 3a, 3b (Model summary) 52 Table 4.8c MLR result of hypothesis 3a, 3b (ANOVA) 53 Table 4.8d MLR result of hypothesis 3a, 3b (Coefficient) 53 4.4.5 Testing regression assumption on heteroskedasticity 54 4.5 Conclusion 56 VI Figure 4.1 Regression result of theoretical model 56 Chapter DISCUSSION AND CONCLUSION 57 5.1 Introduction 57 5.2 Discussion of Findings 57 5.3 Practical Implications 58 5.4 Limitations and recommendations for future research 59 REFERENCES 61 APPENDIX I - QUESTIONNAIRES 65 APPENDIX II- RESULT OF CRONBACH ALPHA 68 Appendix 2.1 – Cronbach alpha of environmental regulations (ER) 68 Appendix 2.2 – Cronbach alpha of managerial environmental concerns (MEC) 69 Appendix 2.3 – Cronbach alpha of environmental product innovations (EPD) 70 Appendix 2.4 – Cronbach alpha of environmental process innovations (EPS) 72 Appendix 2.5 – Cronbach alpha of firm’s competitive advantage (FCA) 73 APPENDIX III – EFA RESULT 74 Appendix 3.1 –EFA result of 1st running 74 Appendix 3.2 –EFA result of 2nd running&histograms 79 LIST OF TABLES Table 2.1: antecedent variables of environmental innovations Table 2.2: environmental innovations and dependent variables 14 Table 3.1 Scale of managerial environmental concerns 30 Table 3.2 Scale of environmental regulations 31 VII Table 3.3 Scale of environmental product innovation (EPD) 32 Table 3.4 Scale of environmental product innovation (EPS) 32 Table 3.5 Scale of firm’s competitive advantage (FCA) 33 Table 3.6 Specification for cronbach alpha and EFA method 34 Table 4.1 Main study profile 36 Table 4.2 Cronbach alpha result of main survey 39 Table 4.3a KMO and Bartlett's Test 40 Table 4.3b Total Variance Explained 41 Table 4.3c Rotated Component Matrixa 42 Table 4.4a KMO and Bartlett's Test 43 Table 4.4b Total Variance Explained 43 Table 4.4c Rotated Component Matrixa 44 Table 4.5 Normality assumption test 46 Table 4.6a Pearson correlation between each pairs of variables (ER,MEC), (ER,EPD), (MEC,EPD) 47 Table 4.6b MLR result of hypothesis 1a, 2a (Model summary) 48 Table 4.6c MLR result of hypothesis 1a, 2a (ANOVA) 48 Table 4.6d MLR result of hypothesis 1a, 2a (Coefficient) 48 Table 4.7a Pearson correlation between each pairs of variables: MEC, EPS, ER 50 Table 4.7b MLR result of hypothesis 1b, 2b (Model summary) 50 Table 4.7c MLR result of hypothesis 1b, 2b (ANOVA) 51 Table 4.7d MLR result of hypothesis 1b, 2b (Coefficient) 51 Table 4.8a Pearson correlation between each pairs of variables (EPD, EPS, FCA), 52 Table 4.8b MLR result of hypothesis 3a, 3b (Model summary) 52 Table 4.8c MLR result of hypothesis 3a, 3b (ANOVA) 53 Table 4.8d MLR result of hypothesis 3a, 3b (Coefficient) 53 VIII LIST OF FIGURE Figure 2.1: Theoretical model 27 Figure 3.1 Research procedure 28 Figure 4.1 Regression result of theoretical model 56 ABSTRACT As environmental issues becomes a global matter, enterprises in the world also face a real challenge of reducing harmful impact from manufacturing activities under pressure of international and domestic environmental regulations In that scenario, what companies mostly concern about is the relationship between environmental improvement activities and the competitiveness of enterprise as they have to incur the extra cost from environmental activities By regression analysis of 137 samples from enterprises in southern Vietnam, this paper concludes that the competitiveness of enterprises is positively impacted by environmental process innovations In addition, for the environmental innovations to be fully implemented, the government regulation should comprise more stringent requirements of product and process to be environment-friendly Besides, enterprises also should care about the impulse role of management in accelerating the environmental activities in company Chapter INTRODUCTION 1.1 Introduction The worst flood in Thailand history in 2011, the longer winter in Europe in 2011, the Katrina storm in America in 2005… may have partially expressed the bad consequences from harmful impact of waste from daily production of enterprises in the world Moreover, these natural calamities also mean that the current number of environmental protection is not enough to preserve the environment Along with the world, Vietnam is also suffered the natural disaster yearly as a result of harmful discharge into environment Although the “Law on environment protection” was issued in year 2005, many corporations also violate this law as pouring untreated waste into the environment in later years (example: Vedan in 2008, Sonadezi in 2011) Besides, Vietnam has also become an ideal destination to invest in recent years which would consequently make a major impact into environment Thus, exploring the relationship between environmental innovations and firm’s competitive advantage becomes a crucial matter in current situation due to the following reasons: Firstly, the result of the relationship between environmental innovations and firm’s competitive advantage can help partially explain the internal motives that push enterprises to violate the environmental laws in recent years Secondly, in the case that it is a positive relationship, it creates impetus for enterprises to implement environmental activities as they have to obey the environmental laws 72 Appendix 2.4 – Cronbach alpha of environmental process innovations (EPS) Case Processing Summary N % Cases Valid 137 100.0 0 137 100.0 Excluded a Total a Listwise deletion based on all variables in the procedure Reliability Statistics Cronbach's N of Alpha Items 853 Item Statistics Std Deviation Mean N EIP5 3.97 923 137 EIP6 3.80 1.106 137 EIP7 3.73 1.134 137 EIP8 3.64 1.076 137 EIP9 3.80 999 137 Item-Total Statistics Scale Mean Scale Corrected Cronbach's if Item Variance if Item-Total Alpha if Deleted Item Deleted Correlation Item Deleted EIP5 14.97 12.764 568 846 EIP6 15.15 10.846 727 805 EIP7 15.21 10.330 788 787 EIP8 15.30 10.991 731 805 EIP9 15.14 12.679 518 858 73 Scale Statistics Std Mean Variance Deviation 18.94 17.364 N of Items 4.167 Appendix 2.5 – Cronbach alpha of firm’s competitive advantage (FCA) Case Processing Summary N % Cases Valid 137 100.0 0 137 100.0 Excluded a Total a Listwise deletion based on all variables in the procedure Reliability Statistics Cronbach's N of Alpha Items 897 Item Statistics Mean Std Deviation N FCA1 3.94 829 137 FCA2 3.88 900 137 FCA3 3.97 822 137 FCA4 3.86 933 137 74 Item-Total Statistics Scale Mean Scale Corrected Cronbach's if Item Variance if Item-Total Alpha if Deleted Item Deleted Correlation Item Deleted FCA1 11.72 5.632 757 873 FCA2 11.77 5.235 791 860 FCA3 11.69 5.555 792 861 FCA4 11.80 5.223 752 876 Scale Statistics Std Mean Variance Deviation 15.66 9.301 3.050 N of Items APPENDIX III – EFA RESULT Appendix 3.1 –EFA result of 1st running KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Sphericity Approx Chi-Square 796 1.743E3 df 231 Sig .000 75 Communalities Initial Extraction ER1 1.000 617 ER2 1.000 688 ER3 1.000 785 ER4 1.000 668 MEC1 1.000 557 MEC3 1.000 651 MEC4 1.000 631 MEC5 1.000 572 MEC6 1.000 676 EIP1 1.000 610 EIP2 1.000 699 EIP3 1.000 685 EIP4 1.000 519 EIP5 1.000 529 EIP6 1.000 704 EIP7 1.000 781 EIP8 1.000 747 EIP9 1.000 667 FCA1 1.000 751 FCA2 1.000 787 FCA3 1.000 784 FCA4 1.000 784 Extraction Method: Principal Component Analysis 76 Total Variance Explained Extraction Sums of Squared Initial Eigenvalues Loadings Rotation Sums of Squared Loadings % of Compon % of Cumulativ Variance e% Varianc Cumulative ent Total 7.370 33.500 33.500 7.370 33.500 33.500 3.384 15.383 15.383 2.754 12.517 46.017 2.754 12.517 46.017 3.136 14.255 29.638 2.387 10.848 56.865 2.387 10.848 56.865 3.027 13.759 43.397 1.372 6.235 63.100 1.372 6.235 63.100 2.853 12.967 56.364 1.010 4.589 67.688 1.010 4.589 67.688 2.491 11.325 67.688 828 3.765 71.453 731 3.324 74.777 689 3.131 77.908 675 3.066 80.974 10 629 2.859 83.833 11 566 2.572 86.405 12 502 2.280 88.685 13 435 1.979 90.663 14 389 1.767 92.431 15 323 1.468 93.899 16 293 1.333 95.232 17 259 1.178 96.410 18 206 939 97.349 19 195 887 98.236 20 152 692 98.928 21 120 546 99.474 22 116 526 100.000 Extraction Method: Principal Component Analysis Total e % Total % of Variance Cumulative % 77 Component Matrixa Component ER1 431 413 504 -.080 -.015 ER2 529 250 504 -.293 070 ER3 614 148 523 -.198 271 ER4 594 207 382 -.178 306 MEC1 366 -.154 554 291 -.086 MEC3 429 -.429 082 499 166 MEC4 613 -.419 217 178 -.012 MEC5 539 -.189 116 472 -.096 MEC6 586 -.465 175 282 083 EIP1 328 -.106 -.631 037 302 EIP2 566 -.370 -.424 -.150 200 EIP3 523 -.351 -.284 -.384 246 EIP4 682 -.094 -.026 -.056 203 EIP5 695 046 -.051 -.202 023 EIP6 705 -.298 -.115 -.236 -.224 EIP7 750 -.228 -.239 -.166 -.286 EIP8 776 -.132 -.131 081 -.321 EIP9 558 028 073 -.273 -.524 FCA1 543 567 -.301 148 -.150 FCA2 636 501 -.346 101 047 FCA3 528 618 -.243 214 133 FCA4 495 652 -.175 288 -.018 Extraction Method: Principal Component Analysis a components extracted 78 Rotated Component Matrixa Component ER1 265 683 079 -.228 148 ER2 111 789 057 -.009 224 ER3 101 839 222 124 084 ER4 197 754 161 183 040 MEC1 -.059 363 591 -.238 124 MEC3 024 -.009 778 209 -.049 MEC4 -.057 234 665 228 281 MEC5 224 058 695 023 185 MEC6 -.049 170 738 269 166 EIP1 319 -.234 067 669 -.042 EIP2 082 -.021 225 764 240 EIP3 -.061 165 072 765 252 EIP4 217 348 319 461 192 EIP5 281 374 144 387 374 EIP6 047 170 265 439 641 EIP7 191 079 265 445 686 EIP8 322 088 431 258 619 EIP9 137 245 056 012 765 FCA1 818 095 -.006 060 261 FCA2 810 167 029 266 177 FCA3 851 208 033 125 -.006 FCA4 862 173 067 -.042 064 Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization a Rotation converged in iterations 79 Component Transformation Matrix Comp onent 434 449 459 424 468 729 285 -.480 -.369 -.144 -.383 686 270 -.552 -.068 365 -.379 696 -.342 -.347 -.003 319 031 512 -.797 Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization Appendix 3.2 –EFA result of 2nd running&histograms KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Sphericity Approx Chi-Square 787 1.639E3 df 210 Sig .000 80 Communalities Initial Extraction ER1 1.000 616 ER2 1.000 685 ER3 1.000 798 ER4 1.000 673 MEC1 1.000 551 MEC3 1.000 653 MEC4 1.000 630 MEC5 1.000 570 MEC6 1.000 677 EIP1 1.000 617 EIP2 1.000 690 EIP3 1.000 717 EIP4 1.000 511 EIP6 1.000 700 EIP7 1.000 781 EIP8 1.000 751 EIP9 1.000 677 FCA1 1.000 752 FCA2 1.000 802 FCA3 1.000 781 FCA4 1.000 783 Extraction Method: Principal Component Analysis 81 Total Variance Explained Extraction Sums of Squared Rotation Sums of Squared Loadings Loadings Initial Eigenvalues Compon % of Cumulative Variance % % of tive % Total Cumulativ Variance e% Total 6.924 32.971 32.971 6.924 32.971 32.971 3.324 15.829 15.829 2.752 13.104 46.076 2.752 13.104 46.076 3.034 14.447 30.276 2.384 11.354 57.430 2.384 11.354 57.430 3.012 14.341 44.617 1.346 6.408 63.838 1.346 6.408 63.838 2.687 12.796 57.413 1.009 4.806 68.644 1.009 4.806 68.644 2.359 11.232 68.644 828 3.942 72.586 722 3.437 76.023 688 3.278 79.302 630 2.998 82.299 10 587 2.796 85.095 11 521 2.479 87.575 12 447 2.130 89.705 13 414 1.971 91.675 14 326 1.554 93.229 15 294 1.398 94.627 16 262 1.250 95.877 17 259 1.233 97.110 18 206 983 98.093 19 161 769 98.862 20 123 587 99.449 21 116 551 100.000 Analysis Variance % of ent Extraction Method: Principal Component Total Cumula 82 Component Matrixa Component ER1 430 418 500 -.084 -.014 ER2 524 254 502 -.297 073 ER3 619 155 518 -.218 276 ER4 594 213 378 -.191 309 MEC1 382 -.146 549 275 -.085 MEC3 439 -.423 078 498 163 MEC4 620 -.413 214 172 -.012 MEC5 552 -.182 110 459 -.098 MEC6 595 -.459 171 275 081 EIP1 331 -.106 -.634 016 306 EIP2 558 -.371 -.423 -.150 200 EIP3 527 -.349 -.285 -.415 254 EIP4 676 -.091 -.028 -.057 203 EIP6 699 -.296 -.116 -.245 -.222 EIP7 747 -.226 -.242 -.180 -.284 EIP8 781 -.126 -.137 060 -.320 EIP9 559 032 069 -.300 -.518 FCA1 542 570 -.310 125 -.148 FCA2 643 506 -.356 062 052 FCA3 521 620 -.250 211 131 FCA4 492 655 -.183 280 -.020 Extraction Method: Principal Component Analysis a components extracted 83 Rotated Component Matrixa Component ER1 269 081 680 -.233 143 ER2 116 060 787 -.016 220 ER3 104 218 846 128 087 ER4 200 161 757 182 041 MEC1 -.059 582 370 -.236 126 MEC3 022 781 -.012 200 -.052 MEC4 -.056 669 233 218 278 MEC5 224 694 059 018 184 MEC6 -.048 742 170 261 165 EIP1 318 066 -.225 678 -.034 EIP2 084 238 -.025 754 239 EIP3 -.059 068 181 778 266 EIP4 219 329 343 449 187 EIP6 051 273 170 429 640 EIP7 195 273 080 437 686 EIP8 325 434 091 253 620 EIP9 140 051 254 015 769 FCA1 820 -.007 096 062 259 FCA2 812 022 179 278 184 FCA3 852 041 199 116 -.014 FCA4 863 071 166 -.048 057 Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization a Rotation converged in iterations 84 Component Transformation Matrix Comp onent 437 483 444 407 461 732 -.475 286 -.367 -.148 -.391 259 684 -.554 -.071 346 688 -.386 -.352 -.366 -.007 029 323 518 -.791 Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization 85 86 ... process innovation (2) The impact of managerial environmental concerns on environmental product and process innovation (3 )The impact of environmental product and process innovation on firm’s competitive. .. research hypothesis 2.3.1 The influence of environmental regulations on environmental innovations Nowadays, the increasing acknowledgement of community about the environmental matter is pushing the government... product innovation (one part of environmental innovations) However, the stringent regulations only lead to environmental product innovations, which does not contribute novelty of product to the market