Effects of the ISO 9000 Certification: Empirical Analysis of Russian
Manufacturing Companies
Veronika Vynaryk
National Research University – Higher School of Economics
The effect of the ISO 9000 certification on the economical results of Russian companies has been
anaylised by using the event-study method. Informational dataset is built on the basis of the sample of
industrial companies competitiveness monitoring project, conducted in 2009 by the Institute for Industrial
and Market Studies at HSE. The empirical study methodology is given: hypothesis, informational dataset,
model of effects evaluation. The main finding of the paper is that having the ISO 9001 certificate
stimulates profitability and reduces costs, but does not lead to sales or asset turnover rises.
Keywords: quality management system, ISO 9000 certification effect, industrial companies
A quarter of a century after the adoption of the international quality management systems (QMS)
standard ISO 9000 in 1987,there have been issued more than one million ISO 9001 certificates in
184 countries, including 12491 certificates in Russia (figures correct for December 2012). The
vast majority of companies – certificate holders – operate in industrial sectors of the economy:
914910 in the world and 11741 companies in Russia [The ISO Survey, 2013]. The concentration
of certificates by industry varies significantly in Russia. For example, by the beginning of 2013
more than 70% of companies in the Russian oil and gas sector have implemented and certified
their quality management system and received certification to ISO 9001, in manufacturing this
number was found to be 47%, in power industry - 38%, in construction - 14%, whereas in the
extractive industry only 4%.
On the one hand standards spreading dynamics demonstrate their exceptional popularity, on the
other, provide researchers vast material for the analysis of the effects of the ISO 9000
certification. There exists quite a lot of foreign works on this subject, which covers the entire
period of the standard’s existence and analyse the consequences of certificate implementation in
a number of countries. In an array of studies the Russian segment is very narrow, works which
are presented in it are not always focused on the rigorous study of the ISO 9000 certification
effects; mostly they contain expert analysis of the Russian QMS ineffectiveness or - on the
contrary - successful cases of certification. The lack of empirically identified effects that might
become a motivation for companies to implement ISO 9000 standard breaks the spread of QMS
in industry. It is especially important to identify and evaluate the consequences of ISO 9000
certification for manufacturing companies, given their importance for the national economy
competitiveness.
The aim of the work is to analyse the effects of ISO 9000 certification on Russian manufacturing
companies.
The informational database for this study has been built on the basis of the sample of the
monitoring for manufacturing companies’ competitiveness, conducted by the Institute for
Industrial and Market Studies at HSE in 2009. The sample of 1004 companies operating in 48
Russian regions and 8 manufacturing industries (in correspondence with 2-digit OKVED code)
is transformed into the research database by adding companies’ financial information from the
SPARK (Professional market and company analysis system) database and their certification
information from the firm’s corporate web sites.
1. Review of methodological approaches to the study of the ISO 9000 certification
effects
There are two research approaches which dominate in empirical studies of the effects of ISO
9000 certification: comparing companies’ results before and after certification, and comparing
achievements of certified and non-certified companies.
Data for the comparative analysis of pre- and post-certification results is usually gathered using
questionnaires sent either by post or online. When designing a research sample aimed at finding
differences between certified and non-certified companies statistical, economic and financial
data from international, national and cross-industrial information resources is usually used, as
well as from certified companies register. Samples vary by geography, volume, industry and
company size. Samples’ geography illustrates the dynamics of the quality management systems
distribution in the world: earlier studies (early 2000s) mainly analyse US and European data,
whereas in the last decade, more and more works were performed on data from Australian, Asian
and African companies. The volume of the sample is usually equal to a few hundreds and
contains manufacturing companies, companies operating in construction, trade and services. The
size of the companies in a sample ranges from small and medium to large corporations.
To estimate the ISO 9000 certification effects different methods are used: event-study, case
study, methods of cluster analysis, variance analysis (ANOVA), covariance analysis
(ANCOVA), regression analysis (including multiple regressions, OLS regressions, probit
analysis, Tobit-analysis), generalized method of moments (GMM) and specific statistical tests
such as Kolmogorov - Smirnov test, Shapiro-Wilk test, Wilcoxon signed-rank test etc.
Authors conduct their research on different time intervals and using different measurement
parameters. Time intervals refer to different periods of the QMS ISO 9000 distribution in the
world: beginning in the 1980s - 1990s followed by more modern period of the 2000s; their
length varies from one year to ten-fifteen years. Range of parameters selected for effects
assessment is very wide (see proposed classification of ISO 9000 certification effects in
[Vynaryk, 2012]). External effects are evaluated using the indicators of market share, export
share, sales, number of reclamations, number of returned products, earnings per share (EPS),
return on investment (ROI), market value of shares etc. To assess the internal effects such
indicators as number of defects and repairs, inventory turnover period, occupational injury rate,
return on assets (ROA), return on sales (ROS), return on capital employed (ROCE), return on
labour (ROL) and labour productivity. Researches form different sets of these indicators to
analyse the combination of external and internal effects of ISO 9000 certification.
2. Methodology and hypotheses of empirical research
A proposed methodology of the empirical analysis of the ISO 9000 certification effects on
Russian companies is based on event-study methodology. The basic research approach is to
analyse the effects by comparing performance of certified and non-certified companies.
Event “QMS ISO 9000 implementation” is understood as information (obtained from a
company’s web site) about the issue date of the company’s ISO 9001. Thus, the QMS
implementation is fixed by the fact that a company has a valid ISO 9001 certificate. Certificate
(issued as a result of initial certification or recertification audit) is recognised as valid if after its
receipt no more than three years have passed (ISO 9001 certificate is valid for three years). Thus,
companies with an expired certificate, those which didn’t certify their quality management
system and those which have declared their intention to obtain a certificate but haven’t got a
certificate yet, are eliminated from the analysis.
The main essence of event-study method is to compare the results of a group of companies
affected by the event “QMS ISO 9000 implementation”, with the results of a group of companies
(similar by its characteristics to the first one), which are not affected by this event. The method
measures company performance indicators and makes pairwise comparison of their values (for
certified and non-certified companies) in a certain period (before and after the event “QMS ISO
9000 implementation”).
The main hypothesis of the study is specified below and supposes that QMS ISO 9000
implementation leads to the improvement of economic results of the company.
Hypothesis Н1: the fact that a company has the ISO 9001 certificate leads to increased
profitability.
Hypothesis Н2: the fact that a company has the ISO 9001 certificate leads to decreased
production costs.
Hypothesis Н3: the fact that a company has the ISO 9001 certificate improves the company’s
position in the market.
The first and the second hypotheses mainly take into account internal effects of the QMS ISO
9000 certification, allowing estimation of the QMS influence on profitability and costs, whilst
the third, estimating market position, brings us to the external effects of certification1.
Hypotheses testing allows to obtain an evidence of the QMS integrated effects on a company’s
achievements. Financial indicators were chosen to test the hypotheses as they are viewed as a
generalised measure of the companies’ success. The fact that ISO 9000 certification effects are
measured with the help of financial indicators is due to our aspiration to prove a relationship
between the QMS and companies’ economic results found in foreign studies on Russian data.
Return on assets (ROA) and return on sales (ROS) is used for hypothesis H1 verification.
Production costs to sales ratio is used to check hypothesis Н2. The hypothesis Н3 is verified with
the use of relative change in sales and assets turnover indexes.
The analysis of the above stated financial indexes for each certified firm and corresponding to it
an uncertified one from the control group is organised in seven-year rolling time frame [(t - 3);
(t+3)] within nine-year research interval of 2002-2011, where t states for the year when company
received the ISO 9001 certificate. 2002 and 2011 were chosen as the time frame of the research
interval as within this period (see [Vynaryk, 2013]) there was steady positive dynamics of ISO
9000 certification spread in Russia. Individual effects of the QMS certification stay for a long
time, therefore, for their adequate assessment data from a long time interval (starting at least one
year before the decision of certification is made and finishing three years after the certificate is
obtained) should be used. [(t - 3); (t+3)] seems to be a time interval which meets all the above
requirements.
3. Informational database
An informational database for this study is built on the basis of the sample of the monitoring for
manufacturing companies’ competitiveness, conducted by the Institute for Industrial and Market
Studies at HSE in 2009. The sample of 1004 companies, operating in 48 Russian regions and 8
manufacturing industries (in correspondence with 2-digit OKVED code), is transformed into the
research database by adding companies’ financial information from the SPARK (Professional
We have presented the classification of the effects of the QMS ISO 9000 in the article ”Effects of the quality
management systems certifications (foreign literature review)” published in the Management and business
administration journal (№4, 2012).
1
market and company analysis system) database and their certification information from the
firm’s corporate website. The sample represents about 8% of the average number of employees
from the companies of sampled population in surveyed industries; these companies produced 6%
of the manufacturing industry’s total production in 2007 (ultra-small and ultra-large industrial
companies were excluded from the sample) [Kuznetsov, 2010]. 214 companies with ISO 9001
certificates or 21% were revealed in the sample. They form the main group of the analysis. This
share corresponds to data from the Business Environment and Enterprise Performance Survey
(BEEPS) - a joint initiative of the European Bank for Reconstruction and Development and the
World Bank. [The BEEPS Russia 2005, 2009 datasets]. BEEPS sample of 2005 contains 16.4%
of the Russian manufacturing companies which claimed to have ISO 9001 certificate, in 2009
there were 27.6% of such companies.
Most companies in the sample have less than 500 employees. Among large and medium
companies (with number of employees more than 500 people) there is a higher share of those
with certificates.
More than 76% of the companies received the ISO 9001 certificate after 2005, which helps us to
trace changes in companies’ financial indicators during the chosen time range [(t-3);(t+3)]. 166
companies out of 214 certified were used for the empirical analysis2.
For the purposes of further analysis of the effects of ISO 9000 certification, the original sample
of 1004 companies was divided into two groups. The first main group consisted of 166
companies - certificate holders, the second control group is described in details below.
Descriptive statistics of the formed database is presented in Appendix (tables. A1, A2).
4. Research Model
Standard event-study procedure requires firstly an identification and accurate timing of an event,
selection of an assessment period duration; calculation of the analysed indicators values within
the time intervals in the research interval; hypothesis testing of whether event caused a change in
analysed indicators [Kothari, Warner, 2007]. With correspondence to this procedure we have
created the following algorithm of ISO 9000 certification effects evaluation:
1. fixation of a period when event “QMS ISO 9000 implementation” occurred (event
period);
2. fixation of a “control” year, when three control groups which have not experienced an
event are formed. Also impact of the event on financial indicators is calculated by
comparing these indicators’ values with the indicators of companies from control groups.
Periods within which a comparison of the performance is made are called “evaluation
periods”;
3. companies selected to control groups by their industry and financial indicators;
4. calculation of financial indicators values within “evaluation periods” for non-certified
companies from control groups;
5. calculation of financial indicators values within “evaluation periods” for certified
companies from the main group;
6. “Abnormal” performance evaluation by calculating the difference in values of financial
indicators of certified and non-certified companies within the analysed periods;
7. Testing hypotheses of the impact of the event on financial indicators by pairwise
comparison of their values, calculated for the certified company and its corresponding
non-certified company from a control group;
2
Because of the seven-year rolling time period of analysis within the nine-year research interval of 2002-2011 some
companies received ISO 9001 certificate before 2004, therefore it was impossible to analyse their financial
indicators in the selected time range [(t-3);(t+3)]
8. Checking statistical significance of the results.
The first step of the algorithm – event period fixation. In this study, it is a time period during
which QMS was implemented and certification audit was prepared and carried out. Usually
certification implementation takes from 6 to 18 months [Certification according to ISO 9001,
2006; Corbett, Montes-Sancho, Kirsch, 2005; Lo, Yeung, Cheng, 2007]. Taking into account this
information, event period in this study was chosen as one year. Year t, when the analysed
company received the ISO 9001 certificate, is placed in the centre of the study timeline. This
year fixes first appearance of information about the event – “QMS ISO 9000 implementation”.
At the second step of the algorithm there is chosen “control year” (t - 2), which precedes the
event. This year non-certified companies are divided into three groups. Also there is the chosen
time interval – three years after certification – to test the hypotheses regarding the impact of the
event on the financial indicators of a certified company. To test changes in the pre-certification
period a time period of three years before certificate receipt has been identified. Year (t-3) is
included as we suppose that even before a company has decided to certify its QMS, it is already
significantly different by its performance from those companies which do not implement a QMS.
Selected seven year time period [t-3; t+3] allows us to estimate both short- and long term
certification effects.
The following algorithm steps show how pairwise comparison of financial indicators between
main and control groups is organised within “evaluation periods”. On the third step control
groups are formed. When selecting companies to control groups it is important to eliminate, as
much as possible, the impact of different factors on comparing companies besides the impact of
the event “QMS ISO 9000 implementation”.
Therefore, the main selection principle is similarity of companies from the main group to those
from the control group. Industry and two financial indicators (return on assets and total assets
value) were chosen as similarity criterions. Industry similarity is ensured by selection of
companies from the same industry (with the same first two-digit OKVED codes) as companies
from the main group to a control group. This eliminates challenges related to industry specifics.
To guarantee the similarity by financial indicators we select companies to a control group with
similar values of these indicators with companies from the main group two years prior to the
receipt of ISO 9001 certificates by the main group of companies. Sufficiency of such an
approach of groups forming is proved in the study [Barber, Lyon, 1996], where it is shown that
the selection to the control group of companies, which have previously (regarding event period)
shown similar results to those companies from the main group, increases event-study power.
This is especially true when company has high pre-event results (that can be supposed in a
situation with an event «QMS ISO 9000 implementation»).
To determine the degree of similarity of characteristics of companies from the control group to a
certified company, taking into account the argumentation presented in previous studies [Barber,
Lyon, 1996; Corbett, Montes-Sancho, Kirsch, 2005], we chose the following ranges: for return
on assets: 90% - 110%, total assets: 50% - 200%. While using these ranges the narrowest control
group (formed by similarity of total assets and return on assets) gets a sufficient number of
companies for hypotheses testing. It should be mentioned that there are opportunities to narrow
the range of total assets changes as, to the control group of non-certified companies formed by
similarity of industry and total assets, there was included a very large number of companies.
However, experiments with a range size in event-study method are a time-consuming task, and
therefore it was decided at this stage of the research to restrict total assets variation range to 50%
- 200%.
Therefore non-certified companies similar by industry, ROA and/or total assets to a certified
company two year before the certified company received ISO 9001certificte are chosen to
control groups. In this article we summarise the results obtained while using only one of the
three control groups. This is the narrowest group formed by similarity of industry, ROA and total
assets. However, we should mention that the results obtained were found robust when using the
other two groups, which consists of more non-certified companies than the first one.
After values of the financial indicators of certified and non-certified companies are calculated on
the fourth and the fifth steps, within “evaluation periods”, on the sixth step the comparison is
made. Calculating the values of financial indicators within “pay periods” of certified and noncertified companies, on the sixth step of the algorithm comparison between the performance of
the control and main group is made by calculating “abnormal” performance for all research
periods (after year (t-3) till year (t+3)).
Therefore, for instance, “abnormal” performance APi,t-2,t+1 of a certified company i within period
[(t-2); (t+1)] is defined as:
APi,t-2,t+1 = (P i,t+l - Pi,t-2 )- (PI i,t+l - PIi,t-2 ),
where Pi,t-2 is value of financial indicator of the certified company i in year t-2
Pi,t+1 is value of financial indicator of the certified company i in year t+1
PIi,t -2 is value of financial indicator of company from the certified company i’s control
group in year t-2
PIi,t+l is value of financial indicator of company from the certified company i’s control
group in year t+1.
On the seventh and eights steps of the algorithm we test if “abnormal” performance is
significantly different from zero in an assumed direction. Economic results of certified
companies are admitted “abnormal” if results of conducted tests are significant. To test statistical
significance we first apply Shapiro-Wilk test and Kolmogorov–Smirnov test to check abnormal
performance of financial indicators distribution for normality. If the above tests reject the
hypothesis of normality of the abnormal performance of financial indicators distribution we
would then apply Wilcoxon signed-rank test or sign test (in correspondence to distribution
asymmetry) to test the hypothesis of significant abnormal economic results of the certified
companies. Otherwise, we use t-test to test this statement. As a result we determine whether
abnormal financial indicators significantly differ from zero in assumed direction.
5. Research results
Before hypotheses testing distribution of abnormal performance of financial indicators was
checked for normality. In all cases hypothesis of distribution normality is rejected. Therefore we
use Wilcoxon signed-rank test if |skewness|<1, otherwise sign test is applied.
When testing the Hypothesis H1 of the existence of a positive relationship between having ISO
9001 certificate and the increase in ROA we have obtained the following results: significant
abnormal performance of ROA is observed during the first two years after the company’s
decision to implement QMS ISO 9000, in years one and two, after company has received the
ISO 9001 certificate. Talking about long-term improvements (using t-2 as a base year)3, we see
significant improvements in ROA (significance level - less than 0.05) within the following two
years, after certification. Increase in ROA by year (t+2) of certified companies compared to non3
By short-term effects we understand those changes, which take place within financial indicators of certified
companies with respect to non-certified companies during one year within the seven year rolling time period [t-3;
t+3]. Long-term effects determine changes in those indicators on a longer time period (starting from two years)
within the seven year rolling time period.
certified ones is rather low - only 0.08 percentage points (table. A3), or about 1% (from mean of
7.19% of certified companies in year (t-2) (table A1)).
On the whole hypothesis H1 testing results by ROA show minor positive changes of the
indicator at certified companies.
The second part of hypothesis H1 is tested with the help of ROS -almost the same dynamics as in
the case with ROA is seen. We also record significant improvements in ROS at certified
companies several years before certificate receipt. Moreover, a positive long-term trend with
considerable ROS improvement takes place: 19 percentage points increase by year (t+1), though
a less considerable increase of 1.99 percentage points by year (t+2) (tables A1, A3). Short-term
effects in the years preceding the certification, and in the first year after its receipt also show
significant positive dynamics.
Confirmation of the hypothesis H1 can be interpreted as follows. The indispensable condition for
the QMS ISO 9000 implementation and certification is: company reorganisation, which focuses
the company on the priority of satisfying consumers’ requirements. A positive dynamics in both
financial indicators of profitability shows that certified companies have successfully fulfilled this
condition. ROA increase both in short- and long-terms allows us to admit achieved level as a
result of certification level of the asset management quality. Increases in ROS (especially
considerable in the first year after certification) demonstrates a rise in company’s proceeds of
profitability share, which testifies to a company’s successful realisation of the ISO 9001
certificate signal effect and of steady consumer confidence.
Hypothesis H2 supposes reduction of production costs after QMS implementation and receipt of
the ISO 9001 certificate. We observe significant decreases in production costs (measured by
production costs to sales ratio) in short-term at periods [t-3; t-2] and [t-1; t]; in long-term it is
seen by year (t+2) (table A4). So hypothesis of production cost reduction on certified companies
compared to non-certified ones in whole is confirmed. This fact testifies to the efficiency of
measures to strengthen discipline, moving away from unproductive activities, rationalisation of
resources etc. The incentive of all these improvements is ISO 9000 certification. Constant
control and timely measures to eliminate revealed defects at the initial stage allows elimination
of them with low-costs. At the same time standartisation and documentation of a company’s
operating activity leads to productivity improvements. Production costs to sales ratio decreases
reflects achieved increase in productivity of the company’s manufacturing resources.
Hypothesis H3 which supposes an improvement of the company’s position in the market as a
result of ISO 9001 certificate receipt is tested with the help of relative change in sales and assets
turnover. And, if in the first year after a firm has made this decision there is observed a
significant increase (approximately one percentage point – see table A6), in the following years
(until the year of certification) the direction is changed. Specifics of QMS ISO 9000 impact on a
company can be a possible explanation of this phenomenon. At the first year (at the very
beginning of the QMS implementation) consequences of management innovations are revealed
in the form of increased sale proceeds comparing to the previous pre implementation period.
Further complex reorganisation of all business-processes, which is needed to bring them into
correspondence with the requirements of the ISO 9001 standard and further certification is united
with organisational, financial and technical problems.
Table 1
Significance of financial indicators’ abnormal performance
(Control group formed by similarity of total assets, ROA and industry)
Financial
t-3 to t-2- t-2 to t-1 t-1 to t t to
t+1 to
t+2 to
t-2 to t
t-2 to t+1 t-2 to
t-2 to
t-1 to
t-1 to t-1 to
indicators
t+1
t+2
t+3
t+2
t+3
t+1
t+2
t+3
ROA
+***
+***
+***
+**
+**
+*
ROS
+**
+***
+***
+**
+***
+*
+***
Cost/Revenue
-**
-*
Revenue /Assets
+**
-**
-**
-*
-**
-***
-***
-**
-*** -***
Δ Revenue
+***
-**
+***
-***
-**
-***
-***
-***
Notes
1 – * significance level p<0,1; ** significance level p<0,05; *** significance level p<0,001
2 – +/- indicates positive or negative abnormal performance of financial indicators of certified companies in relation to non-certified ones. Empty cells indicate no
significant abnormal performance.
3 – significance is tested by Wilcoxon signed-rank test or sign test with respect to skewness of abnormal performance distribution value
In the event that a company management and employees are not ready to meet emergent
challenges, they can slow down implementation of new management models that will cause a
slight drop in sale proceeds in this period. The only positive significant change of sale proceeds
of certified companies compared to non-certified is observed in the following year after
certification (table A6). This fact can be interpreted as a consequence of certification signaling
effect: immediately after successful certification process termination, company actively presents
its result – ISO 9001 certificate - to market participants and gets a reaction in the form of sale
proceeds increase.
In the following three years after certification, in both short and long-term prospectives, a
significant decrease in sale proceeds is observed. This fact can be explained by the influence of
external and internal factors. It is also difficult not to accept the fact that negative change of this
indicator occurred, to a certain extent, due to the Russian economic situation in 2008-2012.
During this period of general slowdown of growth rates in manufacturing industries (where
companies from the sample operate), a significant deterioration of the financial situation
occurred: in 2012 compared to 2007 profitability decreased by 32%, paying capacity was halved
[Itogi 2012 goda, 2013]. Research database contains 56.8% of certified companies, which
obtained the ISO 9001 certificate during the period of 2007-2012. Therefore, we can assume that
under the crisis conditions a large amount of testing certified companies may not have got the
expected effect in the form of increase of sale proceeds.
Assets turnover in the first year after certification decision is made shows slight increase –
approximately 1%. (tables A1, A5). After this year all significant changes in this indicator have
negative direction, the value of which rises while moving away from the year of certification.
Thus, till year (t+3) assets turnover in certified companies compared to non-certified ones drops
more than by 25% (tables A1, A5). Behind such a phenomenon can lay the fact that assets of the
certified companies rise quicker than assets of non-certified ones from the control group. ISO
9000 certification assists a company’s innovational initiatives development, activates the
implementation of advanced technical, technological and organizational decisions, and these
processes are accompanied by the growth of total assets. At large, obtained results do not
confirm hypothesis H3.
All in all, obtained results do not confirm hypothesis H3. We generalise hypothesis testing
results below in table 2.
Table 2
Generalised results of certified companies’ abnormal performance
Financial indicators
Hypothesis
H1
ROA
ROS
Changes
(comparison with non-certified companies)
Short-term perspective
Long-term perspective
Increase of the indicator in the
Increase of the indicator by 1 %
first two years after decision to
implement QMS ISO 9000 is
made
Increase of the indicator in the
first two years after ISO 9001
certification
Increase of the indicator few
High positive changes of the indicator
years before certificate receipt
in comparison to year (t-2)
Increase of the indicator in the
first year after certification
Hypothesis
H2
Production costs to
sales ratio
Significant decrease in time
periods [t-3; t-2] and [t-1; t].
Decrease by 5% by year t+2
Hypothesis
H3
relative change in
sales
Significant decrease in years
after decision to certify QMS and
also in period [t+2;t+3]
In the first year after decision to
certify QMS is made increase of
the indicator by 1% is seen
After this all significant changes
of the indicator are negative
Significant growing negative change in
indicator
assets turnover
Significant growing negative change in
indicator
By year (t+3) decrease by more than
25% at certified companies compared
to non-certified.
Production costs to sales ratio is used to check hypothesis Н2. The hypothesis Н3 is verified with
the use of relative change in sales and assets turnover indexes.
Conclusion
The conducted analysis allows us to conclude that after the QMS ISO 9000 implementation and
the ISO 9001 certification, the certified company on the whole obtains better economic results
when compared to an uncertified firm. However, no significant improvement of its market
position are shown.
According to critical expert appraisals, companies that made a decision to implement and certify
their QMS, had demonstrated better results compared to other companies long before the
decision was made. However, given that uncertified companies from the control group had
similar characteristics two years prior to certification to ISO 9001, we can assume that
transformations that occurred in the company after the event are most likely related with the
reorganisation of its internal processes in accordance with the requirements of ISO 9001.
More perceptibly the positive changes of economic outcomes are seen in profitability increases
and in production costs decreases, which can be explained by the organizational transformations
related to the QMS ISO 9000 certification.
The considerable growth in profitability initially takes place in ROS and is due to the net income
increase. At the same time this increase is not sufficient to provide a similar increase of the ROA
- the oppositely directed influence of possible total assets increase takes place. Total assets
growth can also be one of the reasons of negative change in the assets turnover index.
Along with assets turnover, negative dynamics is seen to account for the relative change in sales.
Therefore we can conclude that the observed double negative dynamics of these indexes does not
allow us to talk about the improvement of a company’s market position as a result of the
certification. Such an outcome, which does not correspond with hypothesis Н3, can be explained
by unfavourable economic conditions of the period 2008 - 2012, and also by consequences of
steady growth in the number of ISO 9001 certificates issued in Russia between 2003 to 2010,
that resulted in the loss of the effect of their novelty and according to this to the decline of
certification signaling effect.
A general conclusion of the presented study is that companies with the ISO 9001 certificate show
higher profitability and decreased production costs. Though being an ISO 9001 certificate holder
does not result in increases in sales or assets turnover.
Appendix
Table A1
Descriptive statistics of certified companies in year (t-2)
N
Mean
Median
Standard
deviation
2 275,9
Revenue, mln. 166
1012,7
409
roubles
Cost, mln.
166
791,5
314,7
1 642
roubles
ROA,%
166
7,19
4,25
12,18
ROS, %
166
3,21
2,56
9,43
Assets, mln.
166
975,8
227,5
3 021,2
roubles
Cost/Revenue
166
0,78
0,84
0,21
Revenue/Assets 166
1,65
1,39
1,20
N – number of certified companies used in analysis 4
Minimum
Maximum
0,00
22 200
0,00
13 800
-29,25
-56,21
0,00
63,26
34,93
31 200
0,00
0,00
1,18
8,20
Table A2
Descriptive statistics of non-certified companies in year (t-2)
(Control group formed by similarity of total assets, ROA and industry)
N
Mean
Median
Standard
deviation
434
Revenue, mln. 472 322
205
roubles
Cost, mln.
432 273
106
505,6
roubles
ROA,%
432 4,40
2,48
16,00
ROS, %
469 4,37
4,3000
8,86867
Assets, mln.
434 2341
72,5
514
roubles
Cost/Revenue
472 0,85
0,86
0,13
Revenue/Assets 472 1,83
1,64
1,14
N – number of certified companies used in analysis
4
Minimum
Maximum
0,58
5 400
216,9
3 960
-105,20
-73,54
1,04
88,65
42,10
6 320
0,39
0,01
2,06
10,40
From this point onwards the control group size exceeds number of certified companies as one certified company
corresponds to a set of non-certified companies, similar to certified company by given characteristics of control
group
Table A3
Results of hypotheses testing about existence of abnormal performance by financial indicator ROA
N
Mean
Median
Skewness
Wilcoxon signed-rank
test
0,00***
0,001**
0,807
0,00***
0,048**
0,01
0,078
0,00***
0,035**
0,403
0,051**
0,879
0,261
Sign test
t-3 to t-2
459
,1234
,0573
,763
0,003**
t-2 to t-1
442
,0957
,0783
-0,065
0,005**
t-1 to t
465
-,0085
-,0263
0,458
-3,772
t to t+1
435
,1797
,1506
0,124
0,001***
t+1 to t+2
353
-,1131
-,0517
0,183
-1,217
t+2 to t+3
304
-,0939
-,0926
0,170
0,034
t-2 to t
468
,0847
,0407
0,38
-2,320
t-2 to t+1
433
,2125
,0980
0,027**
1,278
t-2 to t+2
366
,0802
,0839
-0,296
0,019**
t-2 to t+3
320
-,0094
-,0486
0,522
0,016**
t-1 to t+1
433
0,1441
0,0642
0,877
0,211
t-1 to t+2
364
,0465
-,0313
0,724
0,564
t-1 to t+3
318
-,0348
-,0461
0,622
0,537
* significance level p<0.1
** significance level p<0.05
*** significance level p<0.001
N – size of control group, used in analysis
In the table above, marked in grey, are |skewness|>1 values. This is when abnormal performance distribution of financial indicators is admitted as asymmetric and for evaluation of
its existence sign test is used
Table A4
Results of hypotheses testing about existence of abnormal performance by financial indicator ROS
t-3 to t-2
t-2 to t-1
t-1 to t
t to t+1
t+1 to t+2
t+2 to t+3
t-2 to t
t-2 to t+1
N
Mean
Median
Skewness
456
470
467
429
340
289
468
436
,9535
1,5113
-1,9525
23,4874
,2940
-,0527
1,9309
19,4949
,4800
,9700
,0100
,9000
,0100
-1,0300
,9650
1,0850
1,011
2,473
-10,901
8,871
1,180
-,592
3,013
9,743
Wilcoxon signed-rank
test
0,015**
0,00***
0,592
0,00***
0,44
0,30
0,013**
0,00***
Sign test
0,017**
0,00***
0,926
0,001***
0,789
0,011**
0,021**
0,005**
t-2 to t+2
358
1,9859
1,1000
1,163
0,019**
0,051*
t-2 to t+3
302
-,0050
,3950
0,856
0,42
-2,984
t-1 to t+1
433
22,5328
,9700
8,977
0,00***
0,000***
t-1 to t+2
356
,1277
,3750
0,559
0,314
-2,672
t-1 to t+3
303
-,6884
-,7500
0,253
0,206
-2,916
* significance level p<0.1
** significance level p<0.05
*** significance level p<0.001
N – size of control group, used in analysis
In the table above, marked in grey, are |skewness|>1 values. This is when abnormal performance distribution of financial indicators is admitted as asymmetric and for evaluation of
its existence sign test is used
Table A5
Results of hypotheses testing about existence of abnormal performance by financial indicator Cost/Revenue
N
Mean
Median
Skewness
Wilcoxon signed-rank
test
0,044**
0,231
0,064*
0,802
0,259
0,408
0,98
0,907
0,29
0,294
0,64
0,099*
0,762
Sign test
t-3 to t-2
455
-,0175
-,0047
-,902
0,348
t-2 to t-1
470
,0028
,0014
0,89
-6,445
t-1 to t
465
-,0204
-,0092
0,138
-1,810
t to t+1
418
-,0271
-,0001
0,961
-11,772
t+1 to t+2
322
-,0227
-,0011
0,867
-15,361
t+2 to t+3
280
-,0648
,0001
1,00
-16,151
t-2 to t
466
-,0157
,0008
0,963
-6,451
t-2 to t+1
419
-,0436
,0006
1,00
-12,233
t-2 to t+2
326
-,1165
-,0130
0,293
-8,175
t-2 to t+3
281
-,0817
,0061
0,633
-12,238
t-1 to t+1
417
-,0448
-,0034
0,624
-11,826
t-1 to t+2
325
-,1167
-,0142
-7,937
0,096*
t-1 to t+3
281
-,0879
,0037
0,72
-11,944
* significance level p<0.1
** significance level p<0.05
*** significance level p<0.001
N – size of control group, used in analysis
In the table above, marked in grey, are |skewness|>1 values. This is when abnormal performance distribution of financial indicators is admitted as asymmetric and for evaluation of
its existence sign test is used
Table A6
Results of hypotheses testing about existence of abnormal performance by financial indicator Revenue/Assets
N
Mean
Median
Skewness
Wilcoxon signed-rank
test
0,106
0,01**
0,003**
0,017**
0,133
0,006**
0,092
0,00***
0,00***
0,00***
0,00***
0,00***
0,00***
Sign test
t-3 to t-2
457
-,0940
-,0345
-,157
0,19
t-2 to t-1
471
,0190
,0854
0,08
-17,643
t-1 to t
466
-,1736
-,0647
-3,406
0,006**
t to t+1
419
-,3808
-,0483
0,379
-13,355
t+1 to t+2
328
,0328
-,0777
0,109
4,240
t+2 to t+3
282
-,0618
-,0853
1,476
0,015**
t-2 to t
466
-,0500
-,0695
,722
0,126
t-2 to t+1
420
-,4452
-,1626
-11,952
0,002**
t-2 to t+2
332
-,2699
-,3121
1,256
0,001***
t-2 to t+3
289
-,4443
-,3664
,033
0,002**
t-1 to t+1
420
-,5421
-,1638
-11,997
0,004**
t-1 to t+2
331
-,3519
-,2161
-,160
0,008**
t-1 to t+3
289
-,4993
-,3815
-1,426
0,001***
* significance level p<0.1
** significance level p<0.05
*** significance level p<0.001
N – size of control group, used in analysis
In the table above, marked in grey, are |skewness|>1 values. This is when abnormal performance distribution of financial indicators is admitted as asymmetric and for evaluation of
its existence sign test is used
Table A7
Results of hypotheses testing about existence of abnormal performance by financial indicator ΔRevenue
t-3 to t-2
t-2 to t-1
t-1 to t
t to t+1
t+1 to t+2
t+2 to t+3
t-2 to t
t-2 to t+1
N
Mean
Median
Skewness
453
472
462
466
410
323
472
472
-,0240
,0192
-,7968
,0671
-,3558
-2,5179
-,0047
-,6408
,0092
,0761
-,0425
,0836
,0000
-,0563
,0661
,1861
-3,381
-17,404
-21,422
-5,703
-20,044
-17,966
-7,529
-14,943
Wilcoxon signed-rank
test
0,611
0,00***
0,10*
0,00***
0,457
0,008**
0,04**
0,00***
Sign test
0,778
0,002**
0,018**
0,00***
0,113
0,002**
0,048**
0,00***
t-2 to t+2
453
-1,8586
,0000
-12,536
0,00***
0,00***
t-2 to t+3
344
-4,0312
,1190
-10,772
0,016**
0,001***
t-1 to t+1
470
-,2853
,0489
-14,653
0,010**
0,062*
t-1 to t+2
451
-,6270
,0000
-14,519
0,010**
0,056*
t-1 to t+3
344
-1,5664
,0618
0,172
-12,662
0,098*
* significance level p<0.1
** significance level p<0.05
*** significance level p<0.001
N – size of control group, used in analysis
In the table above, marked in grey, are |skewness|>1 values. This is when abnormal performance distribution of financial indicators is admitted as asymmetric and for evaluation of
its existence sign test is used
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