Analysis of ISO 9000 Adoption Determinants and Firm Performance

This report investigates the determinants of ISO 9000 adoption and its subsequent impact on firm performance, using secondary data extracted from an Economic Census conducted by the National Bureau of Statistics, China. The study aims to determine if there are significant differences in return on assets (ROA) and return on sales (ROS) between ISO 9000 certified and uncertified companies, as well as revenue differences across various industry types. Through descriptive analysis, the study reveals that only a small percentage of firms are ISO 9000 certified, with Business services being the most prevalent industry type. The report employs two-sample t-tests and ANOVA to analyze the hypotheses, concluding that there is no significant difference in ROA, ROS, or revenues based on ISO 9000 certification or industry type within the dataset. The findings highlight the importance of quality management systems and their potential impact on firm performance, while also acknowledging limitations and suggesting avenues for further research.

Running Head: DETERMINANTS OF ADOPTION OF ISO9000 AND ITS IMPACT ON FIRM
PERFORMANCE
Determinants of Adoption of ISO9000 and its Impact on Firm Performance
Name of the Student
Name of the University
Author Note

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DETERMINANTS OF ADOPTION OF ISO9000 AND ITS IMPACT ON FIRM
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Executive Summary
The main aim of this study is to identify some of the determinants of the adoption of ISO 9000
and hence to analyze the impact of these factors on the performance of the firm. The data to
conduct this study has been collected from an Economic Census conducted by the National
Bureau of Statistics, China. Thus, the source of the data is secondary. The difference in the return
on assets, return on sales earned between the certified and uncertified companies has been tested
here and it has been observed that there is no difference in these returns. The differences in the
revenues earned by different types of firms has also been tested and found out that there lies no
difference in this case either.

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Table of Contents
1.0 Introduction................................................................................................................................3
2.0 Literature Review......................................................................................................................4
2.1 Sales Growth of Industry.......................................................................................................4
2.2 ISO 9000 and Return on Assets.............................................................................................4
2.3 Revenue and Type of Industry...............................................................................................5
3.0 Research Methodology..............................................................................................................5
4.0 Analyses and Findings...............................................................................................................6
4.1 Descriptive Analysis..............................................................................................................6
4.2 Inferential Statistics.............................................................................................................11
5.0 Results and Discussions...........................................................................................................13
6.0 Limitations and Further Study.................................................................................................14
References......................................................................................................................................15

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1.0 Introduction
The quality management system standard of ISO900 has been the major standard of
measurement of the product qualities and system standard measurements all over the world. This
is widely used to state the quality and standards of the products of the company all over the
world. This series is used since its introduction in 1987. By the end of 2013, ISO 9000 has been
so famous within the companies such that that this system has been adopted by more than
1,129,000 facilities in 189 countries.
Due to this huge popularity of the system, it has been of high interest to the academics
and practitioners to understand the determinants of adoption of ISO 9000 and the impact of its
adoption on the firm’s performance. The data has been collected from the National Bureau of
Statistics, China. This is a sample data from extracted from an Economic Census conducted in
2008of the service firms. The dataset contains 24 variables. The data considered in this case is
secondary data.
The main objectives of the research can thus be given as follows:
 Is there any significant difference between the return on assets by the ISO certified and
not certified companies?
 Is there any significant difference between the return on sales by the ISO certified and not
certified companies?
 Is there any significant difference between the revenues earned by different types of
industries?
The analysis will be performed using the appropriate statistical techniques using the
statistical software SPSS.

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2.0 Literature Review
2.1 Sales Growth of Industry
The companies that are growing highly with time inspire the new markets, which are
entering the market (Christmann & Taylor, 2006). These new companies are not that popular and
thus they need establishment and recognition for themselves (Wu, Chu, & Liu, 2007). The
certification from ISO 9000 is thus very important for the companies as this certification gives a
signaling effect to the market stating whether the companies have accepted the quality seriously
(Du, Yin, & Zhang, 2016). It has been seen that a lot of organizations take a very conventional
approach towards the industrial buying. This leads the firms to ask for proposals only from ISO
9000 certified firms (Fikru, 2014a). Thus, firms without the ISO 9000 certification are highly
probable to be ruled out from the potential lists of suppliers. Thus, this certification becomes
very important for the potential customers. From this theory, the following hypothesis can be
framed.
H1: There is significant difference between the return on sales (ROS) by the ISO certified and
uncertified companies.
2.2 ISO 9000 and Return onAssets
Return on Assets (ROA) is one of the most important feature to measure corporate
performance. It has been observed from past studies that the companies that are certified by the
ISO 9000 experience profit than the companies that are not registered. (researchgate.net, 2017).
Another study has shown that return on assets (ROA) and return on sales (ROS) of the ISO 9000
certified companies has been almost twice as that of the companies which are not certified
(Fikru, 2014b ). Thus, this can be said that the ISO certified companies are more profitable than
the companies, which are not certified. The overall findings have shown that the registered

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companies have an earning which is much better than the companies which are not registered
(Fikru, 2016). It has also been observed that the companies certified by ISO 9000 has abnormal
growth towards their return of assets (ROA) and these improvements have been lasting for a long
period (Nakamura, Takahashi, & Vertinsky, 2001). Thus, the following hypothesis can be
framed from thus discussion.
H2: There is significant difference between the return on assets (ROA) by the ISO certified and
uncertified companies.
2.3 Revenue and Type of Industry
It has already been observed from the discussions about the past studies that the ISO
certified companies are highly profitable compared to the companies that are not certified
(Terziovski & Guerrero, 2014). Thus, the revenue earned by the certified companies must also be
higher than the companies that are not certified (Pekovic, 2010). Thus, it is important for the
industries to understand which type of industry earns more revenue. With the discussion of these
factors, the following hypothesis can be framed.
H3: There is significant difference between the revenues earned by different types of industries.
3.0 Research Methodology
The analysis of the hypotheses stated in the previous section has to be performed in this
study. The first hypothesis that has been stated is to be analyzed with the help of two sample t-
test. Two-sample t-test is the most appropriate method to compare the means of two variables. In
this case, the mean return on sales for the companies that are certified by ISO 9000 is to be
compared with the mean return on sales for the companies, which are not certified by ISO 9000.

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The second hypothesis that has been framed is also to be tested using the two-sample t-
test technique. In this case, the mean return on assets (ROA) for the companies that are certified
by the ISO 9000 is to be compared with the mean return on assets for the companies that are not
certified by ISO 9000.
The third hypothesis that has been stated is to be tested initially with the help of one-way
ANOVA technique. The Analysis of Variance (ANOVA) technique is the best measure to check
whether there is any significant relationship between the means of more than two variables or
not. The ANOVA technique is a generalization of the two-sample t-test.
4.0 Analyses and Findings
4.1 Descriptive Analysis
Here, descriptive analysis of all the variables considered in this study will be done. The
first variable that has been considered is the certification of the company. Whether a company is
certified or not is described in this variable. The qualities “certified” and “not certified” are
coded as 1 and 0 respectively. The coding is done for the sake of this study. According to the
analysis it can be seen that from the sample collected of 5717 industries, only 8 percent of the
industries are ISO 9000 certified. Thus, it can be said that is not a very easy task to get certified
by ISO 9000. The companies have to work real hard and provide the clients with high quality
products and services so as to gain the certification from ISO 9000. Figure 4.1 shows the data
graphically with the help of a bar chart.
Table 4.1: Certification dummy
Frequency Percent Valid Percent Cumulative Percent
Valid
not certified 5257 92.0 92.0 92.0
certified 460 8.0 8.0 100.0
Total 5717 100.0 100.0

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Figure 4.1: bar graph showing the ISO 9000 certification of the companies
The second variable that has been taken into consideration is the type of industry. The
different types of industries that has been recorded are
 Storage and transportation (with an industry code of 52)
 Telecommunication (with an industry code of 60)
 Computer services (with an industry code of 61)
 Software (with an industry code of 62)
 Business services (with an industry code of 74)
 Research and development (with an industry code of 75)
 Specialized technology services (with an industry code of 76) and
 Technology exchange and promotion (with an industry code of 77)

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The results of the analysis show that most of the firms in the market are Business services firms.
This constitutes 47.6 percent of the industries that are present. This is almost half of the total
number of firms that exist in totality. Thus, it can be said that Business services is the leading
firms in the market. Figure 4.2 shows the distribution of the different types of industries with the
help of a bar graph.
Table 4.2: Type of Industry
Frequency Percent Valid Percent Cumulative
Percent
Valid
storage and transportation 392 6.9 6.9 6.9
Telecommunication 184 3.2 3.2 10.1
computer services 365 6.4 6.4 16.5
software 390 6.8 6.8 23.3
Business services 2722 47.6 47.6 70.9
Research and Development 222 3.9 3.9 74.8
Specialized technology services 1200 21.0 21.0 95.8
Technology exchange and
promotion 242 4.2 4.2 100.0
Total 5717 100.0 100.0

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Figure 4.2: Different types of industries
The third variable that has been considered is Return on Sales (ROS) of a company. From
the table of the descriptive statistics (table 4.3) it can be seen that the mean Return on sales
considering all the firms is 0.1911. This is a very low value. Thus it can be said by studying the
return on Sales overall, for all the firms that the firms do not earn much by selling the products.
The returns they receive by selling the products give the firms very little profit. It can also be
seen that the values are positively skewed. Thus, it can be said that most of the firms have a very
little return on sales.
Table 4.3: Descriptive Statistics of ROS
N Minimum Maximum Mean Std. Deviation Variance Skewness
Statistic Statistic Statistic Statistic Statistic Statistic Statistic Std. Error
return on sales 5717 .01 .51 .1911 .12397 .015 .514 .032
Valid N (listwise) 5717
The fourth variable of consideration is the Return on Assets (ROA). It can be seen from
table 4.4 that the mean of the return of assets is also found to be very low (0.2236). The standard

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deviation is found to be 0.21 which is also very less. Thus, it can be said that the values are not
much scattered and are close to the mean value. Thus, the return on assets is very low for the
firms. The skewness measure for the return on assets variable is found to be 1.5. This indicates
that the values of return on assets are positively skewed. More values lie below the mean value.
Thus, most of the companies experience a very low return on assets.
Table 4.4: Descriptive Statistics of ROA
N Minimum Maximum Mean Std. Deviation Variance Skewness
Statistic Statistic Statistic Statistic Statistic Statistic Statistic Std. Error
return on asset 5717 .01 1.02 .2236 .20858 .044 1.500 .032
Valid N (listwise) 5717
The fifth and the last variable that has been considered for this study is “the revenue
earned by the firms”. From the descriptive analysis (Table 4.5), it can be seen that the mean
revenue earned by the firms is quite high (11698.57). The standard deviation of this variable is
extremely high (32873.609). Thus, it can be said that the values of revenues are highly scattered
and are not at all close to the mean revenue. The data is positively skewed. Thus, it can be said
that most of the firms have revenue which is less than the mean revenue.
Table 4.5: Descriptive Statistics of Revenue
N Minimum Maximum Mean Std.
Deviation
Variance Skewness
Statistic Statistic Statistic Statistic Statistic Statistic Statistic Std.
Error
sales 5717 1000 869176 11698.57 32873.609 1080674167.528 11.328 .032
Valid N
(listwise) 5717

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4.2 Inferential Statistics
In this part, the hypotheses that have been framed in the literature review is to be
analyzed using the appropriate statistical techniques. The hypothesis 1 will be tested at first. The
null hypothesis is given as
H1: There is significant difference between the return on sales (ROS) by the ISO certified and
uncertified companies.
This hypothesis has been tested using the independent sample t-test. The results of the t-
test show that the two tailed significance value (p-value) is 0.000 (table 4.7) which is less than
the 95 percent level of significance (0.05). Thus, the null hypothesis described above (H1) has
been rejected. Thus, it can be said that there is no significant difference between the return on
sales for the ISO 9000 certified and not certified companies.
Table 4.6: Group Statistics for ROS
certification dummy N Mean Std. Deviation Std. Error Mean
return on sales not certified 5257 .1943 .12344 .00170
certified 460 .1538 .12417 .00579
Table 4.7: Independent Samples Test for ROS
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower Upper
return
on sales
Equal
variances
assumed
.953 .329 6.750 5715 .000 .04053 .00600 .02876 .05230

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Equal
variances not
assumed
6.716 541.462 .000 .04053 .00603 .02867 .05238
The second hypothesis that has been framed can be tested using the independent samples
t-test. The hypothesis is given as,
H2: There is significant difference between the return on assets (ROA) by the ISO certified and
uncertified companies.
The results of the t-test show that the two tailed significance value (p-value) is 0.000
(table 4.9) which is less than the 95 percent level of significance (0.05). Thus, the null hypothesis
described above (H2) has been rejected. Thus, it can be said that there is no significant difference
between the return on assets for the ISO 9000 certified and not certified companies.
Table 4.8: Group Statistics for ROA
certification dummy N Mean Std. Deviation Std. Error Mean
return on asset not certified 5257 .2285 .21102 .00291
certified 460 .1668 .16839 .00785
Table 4.9: Independent Samples Test for ROA
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower Upper
return
on asset
Equal
variances
assumed
38.491 .000 6.102 5715 .000 .06169 .01011 .04187 .08151
Equal
variances not
assumed
7.368 592.837 .000 .06169 .00837 .04525 .07814

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The third and final hypothesis that has been considered in this study is given as follows:
H3: There is no significant difference between the revenues earned by different types of
industries.
This has been tested using the technique of analysis of variance (ANOVA). The test
results (table 4.10) show that the significance value is less than the 95 percent level of
significance (0.05). Thus, it can be said that the null hypothesis has been rejected in this case.
Thus, the revenue earned by a firm differs significantly with the type of the industries. Table
4.11 shows the differences in the revenues earned between the types of industries separately. If
the significance value in the table 4.11 is greater than 0.05, then it can be concluded that there is
significant difference between the revenues earned between the two types industries. Thus, the
revenues earned from the storage and transportation industries differ from that earned by
computer services, business services, specialized technology services and technology exchange
and promotions. The revenues differ in all the other types of firms considered. Thus, it can be
seen that though in some cases there are differences in the revenues earned, in a lot other cases,
there is no difference.
Table 4.10: ANOVA for Revenue
sales
Sum of Squares df Mean Square F Sig.
Between Groups 58983697589.393 7 8426242512.770 7.863 .000
Within Groups 6118149843999.096 5709 1071667515.151
Total 6177133541588.488 5716
Table 4.11: Multiple Comparisons
Dependent Variable: sales
LSD
(I) industry code 2 (J) industry code 2 Mean Std. Error Sig. 95% Confidence Interval

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DETERMINANTS OF ADOPTION OF ISO9000 AND ITS IMPACT ON FIRM
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Difference (I-
J)
Lower
Bound
Upper
Bound
storage and
transportation
s -5906.518* 2925.427 .044 -11641.47 -171.57
computer services 8096.887* 2381.160 .001 3428.91 12764.86
software 506.992 2341.305 .829 -4082.86 5096.84
Business services 6511.190* 1768.489 .000 3044.28 9978.10
Research and
Development -471.017 2749.759 .864 -5861.59 4919.55
Specialized technology
services 6178.134* 1904.443 .001 2444.70 9911.56
Technology exchange
and promotion 7416.250* 2676.233 .006 2169.82 12662.68
Telecommunication
storage and
transportation 5906.518* 2925.427 .044 171.57 11641.47
computer services 14003.405* 2959.790 .000 8201.09 19805.72
software 6413.510* 2927.823 .029 673.87 12153.15
Business services 12417.708* 2493.589 .000 7529.33 17306.09
Research and
Development 5435.500 3263.681 .096 -962.55 11833.55
Specialized technology
services 12084.652* 2591.782 .000 7003.77 17165.53
Technology exchange
and promotion 13322.767* 3201.977 .000 7045.68 19599.86
computer services
storage and
transportation -8096.887* 2381.160 .001 -12764.86 -3428.91
Telecommunication -14003.405* 2959.790 .000 -19805.72 -8201.09
software -7589.895* 2384.102 .001 -12263.64 -2916.15
Business services -1585.697 1824.769 .385 -5162.94 1991.54
Research and
Development -8567.904* 2786.289 .002 -14030.09 -3105.72
Specialized technology
services -1918.753 1956.817 .327 -5754.86 1917.35
Technology exchange
and promotion -680.637 2713.753 .802 -6000.62 4639.35
software storage and
transportation
-506.992 2341.305 .829 -5096.84 4082.86

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DETERMINANTS OF ADOPTION OF ISO9000 AND ITS IMPACT ON FIRM
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Telecommunication -6413.510* 2927.823 .029 -12153.15 -673.87
computer services 7589.895* 2384.102 .001 2916.15 12263.64
Business services 6004.198* 1772.448 .001 2529.53 9478.87
Research and
Development -978.009 2752.307 .722 -6373.58 4417.56
Specialized technology
services 5671.142* 1908.120 .003 1930.50 9411.78
Technology exchange
and promotion 6909.258* 2678.851 .010 1657.69 12160.82
Business services
storage and
transportation -6511.190* 1768.489 .000 -9978.10 -3044.28
Telecommunication -12417.708* 2493.589 .000 -17306.09 -7529.33
computer services 1585.697 1824.769 .385 -1991.54 5162.94
software -6004.198* 1772.448 .001 -9478.87 -2529.53
Research and
Development -6982.207* 2284.959 .002 -11461.59 -2502.82
Specialized technology
services -333.056 1134.355 .769 -2556.82 1890.71
Technology exchange
and promotion 905.060 2195.924 .680 -3399.79 5209.91
Research and
Development
storage and
transportation 471.017 2749.759 .864 -4919.55 5861.59
Telecommunication -5435.500 3263.681 .096 -11833.55 962.55
computer services 8567.904* 2786.289 .002 3105.72 14030.09
software 978.009 2752.307 .722 -4417.56 6373.58
Business services 6982.207* 2284.959 .002 2502.82 11461.59
Specialized technology
services 6649.151* 2391.733 .005 1960.45 11337.86
Technology exchange
and promotion 7887.267* 3042.320 .010 1923.17 13851.37
Specialized technology
services
storage and
transportation -6178.134* 1904.443 .001 -9911.56 -2444.70
Telecommunication -12084.652* 2591.782 .000 -17165.53 -7003.77
computer services 1918.753 1956.817 .327 -1917.35 5754.86
software -5671.142* 1908.120 .003 -9411.78 -1930.50
Business services 333.056 1134.355 .769 -1890.71 2556.82

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Research and
Development -6649.151* 2391.733 .005 -11337.86 -1960.45
Technology exchange
and promotion 1238.116 2306.823 .591 -3284.13 5760.37
Technology exchange
and promotion
storage and
transportation -7416.250* 2676.233 .006 -12662.68 -2169.82
Telecommunication -13322.767* 3201.977 .000 -19599.86 -7045.68
computer services 680.637 2713.753 .802 -4639.35 6000.62
software -6909.258* 2678.851 .010 -12160.82 -1657.69
Business services -905.060 2195.924 .680 -5209.91 3399.79
Research and
Development -7887.267* 3042.320 .010 -13851.37 -1923.17
Specialized technology
services -1238.116 2306.823 .591 -5760.37 3284.13
*. The mean difference is significant at the 0.05 level.
5.0 Results and Discussions
From the testing results it has been seen that the hypothesis 1 has been rejected. That is,
according to the data collected, there is no difference in the return on sales earned by an industry
which is ISO 9000 certified and not certified. This contradicts the past studies as discussed in the
literature review.
Hypothesis 2 has also been rejected. From here, it can be said that, according to the data,
there is no difference in the return on assets earned by an ISO 9000 certified company and an
uncertified company. This result also contradicts the past studies as mentioned in the literature
review.
Though there is no difference in the return on sales earned by the certified and not
certified industries, still the companies should work hard to get the certification in order to secure
their existence in the market.

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It can be seen that hypothesis 3 has also been rejected. There are differences in the
revenues earned by different types of industries but the differences can only be observed in a
very few types of industries. In most other industries, there has been no difference. Thus, it is
evident that any new company that is to be built, should be of the type of industry in which it is
easier to get ISO 9000 certification. The revenues earned by the different industries do not show
any significant difference. Thus, the type of industry that gets certified easily should be of most
importance to the entrepreneurs.
6.0 Limitations and Further Study
In the above study, only three factors have been tested. These three factors were assumed
to be the major factors. There are a lot of other determinants that affect the ISO 9000
certification of companies. Those were not considered in this study. The relationship of the
firm’s performance with the number of employees, the qualification of the employees could also
be another important factor towards ISO certification. Thus, there are a lot of further scope of
study which has not been considered in this research.

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References
Christmann, P., & Taylor, G. (2006). Firm self-regulation through international certifiable
standards: determinants of symbolic versus substantive implementation. Journal of
International Business Studies, 37(6), 863-878.
Company Financial Performance and ISO 9000 Registration: Evidence from Malaysia.
(2017). researchgate.net. Retrieved 10 September 2017, from
https://www.researchgate.net/publication/232886687_Company_Financial_Performance_
and_ISO_9000_Registration_Evidence_from_Malaysia
Du, Y. Z., Yin, J. L., & Zhang, Y. L. (2016). How innovativeness and institution affect ISO 9000
adoption and its effectiveness: evidence from small and medium enterprises in China.
Total Quality Management & Business Excellence, 27(11-12), 1315-1331.
doi:10.1080/14783363.2015.1075874
Fikru, M. G. (2014a). Firm Level Determinants of International Certification: Evidence from
Ethiopia. World Development, 64, 286-297. doi:10.1016/j.worlddev.2014.06.016
Fikru, M. G. (2014b). International certification in developing countries: The role of internal and
external institutional pressure. Journal of Environmental Management, 144, 286-296.
doi:10.1016/j.jenvman.2014.05.030
Fikru, M. G. (2016). Determinants of International Standards in sub-Saharan Africa: The role of
institutional pressure from different stakeholders. Ecological Economics, 130, 296-307.
doi:10.1016/j.ecolecon.2016.08.007

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PERFORMANCE
Nakamura, M., Takahashi, T., & Vertinsky, I. (2001). Why Japanese firms choose to certify: A
study of managerial responses to environmental issues. Journal of Environmental
Economics and Management, 42(1), 23-52. doi:10.1006/jeem.2000.1148
Pekovic, S. (2010). The Determinants of ISO 9000 Certification: A Comparison of the
Manufacturing and Service Sectors. Journal of Economic Issues (Taylor & Francis Ltd),
44(4), 895-914. doi:10.2753/JEI0021-3624440403
Terziovski, M., & Guerrero, J. L. (2014). ISO 9000 quality system certification and its impact on
product and process innovation performance. International Journal of Production
Economics, 158, 197-207.
Wu, S. Y., Chu, P. Y., & Liu, T. Y. (2007). Determinants of a firm's ISO 14001 certification: An
empirical study of Taiwan. Pacific Economic Review, 12(4), 467-487.
doi:10.1111/j.1468-0106.2007.00365.x