BUACC5931, Semester 2 Report: ISO9000 Adoption Factors in China

This report delves into the correlation between ISO9000 implementation and various factors within China's service industry, including industry type, firm characteristics, and internal/external pressures. Drawing on extensive literature, the study reveals that enhanced firm image and competitiveness are more significant drivers of ISO9000 certification than customer or supplier demands. The analysis, based on a dataset of 5717 companies, indicates that only a small percentage (8%) are ISO certified. Quantitative data analysis, including regression and t-tests, explores the relationships between certification and variables such as company age, employee qualifications, and revenue generation. The findings suggest a positive, though slight, correlation between company age and ISO certification. The report concludes that despite the importance of ISO9000 for marketability and internal improvements, only a small percentage of companies are certified. The study recommends further investment in the telecommunication industries and addresses limitations such as insufficient funding and time constraints, and biases in the data. Future research should focus on obtaining better data representation and appropriate time management.

EXECUTIVE SUMMARY
 This report discusses the correlation among the
implementation of ISO9000 and other factors such as
industry, firm levels and internal and external institutional
pressure, just to list a few. A review of quite a number of
available literatures provide meaningful insight that are
crucial in understanding the adoption of ISO9000 and its
relationship with other factors in China’s service industry.
 In China, enhanced firm image and competitiveness are the
more powerful driving agents of ISO 9000 certification than
customer and supplier pressures. Furthermore, we observed
a clearly defined desire for absolute legitimacy and much
needed support within the organizational fields within which
these firms operate.

INTRODUCTION
 The ISO 9000 quality management system was initiated in
1987 by the International Organization for Standardization
(ISO) with the intention of standardising quality systems,
however, the ISO 9000 family of standards have undergone
significant changes from their time of initiation to date.
Despite all these changes, more and more studies have
continued to be undertaken with the main aim of figuring
out the factors that drive different business industry players
to obtain ISO certification.
 Kadash 2012 and other renowned researchers have put
these factors into consideration from a dual perspective
that splits these factors into two categories namely, the
internal and external factors. The internal factors refer to
aspects such as decrease in cost, desire for improved
productivity and profitability whereas, external factors refer
to aspects such as enhanced company image and pressure
from clients or suppliers.

LITERATURE REVIEW
 As we have already indicated during the commencement of
this report, the predominant approach on the existing
research papers has looked at the factors from the
internal/external aspects point of view. According to this
research approach, the internal factors include the utmost
desire for improved productivity and profitability, decrease
in cost, improved quality etc. whereas the external aspects
include pressure from clients or suppliers, enhanced firm
image and so on .
 Generally, the ISO 9000 standardization has grown into a
major prerequisite for any firm to attain world-wide market
entry thus, a number of research works on the factors that
drive firms into obtaining ISO certification are of the opinion
that external factors are far much more superior to the
internal factors (Kadash, 2012)

METHODOLOGY
 The data consisted of 5717 companies, each having details
including the ISO certification, years founded, number of
employees with their qualifications, revenue and profit
labels. The aim of the study was to establish statistical
relationship between companies ISO certification and other
variables such as education and revenues.
 The data analysis performed were quantitative since the
data were numeric based and numeric data analysis were
perform to find the relationship between ISO certification
and other variables. The percentages, frequencies and the
measures of central tendencies and dispersions were also
performed using appropriate data techniques.
 The choice of the picking quantitative analysis of data can
be justified by inability of qualitative data to perform
statistic relationship between variables, which was the main
aim of the analysis.

DATA
ANALYSIS
From the data chart, it was found that only 460 companies out of
the possible 5717 were ISO certified.
Only 8% percent were certified and 92% not

MEASURES OF CENTRAL TENDENCIES
l l_yjs l_benke l_dz l_gaozhong
mean 45 1 12 13 12
mode 12 0 0 0 0
median 23 0 4 7 5
sd 74.3710662 5.687924 28.4509811 24.3037332 31.2872762
var 5531.05549 32.3524795 809.458323 590.671447 978.893652
l_chuzhong revenue profit_operating ksum equity kpaid
7 11,702 2,069 16,473 7,694 4,766
0 1500 300 2000 1000 1000
0 4,206 692 3,972 1,600 1,000
25.9777685 32875.9301 7158.955581 54661.7784 31009.3671 17118.6779
674.844454 1080826781 51250645.01 2987910023 961580847 293049133

DESCRIPTIVE STATISTICS ANALYSIS
The mean, mode, median, standard deviation and
variance of the companies number of employees
and their respective academic qualifications and
also the revenues, profit operating , Ksum, equity
and Kpaid are list in the above charts

INFERENTIAL STATISTICS
ANOVA
Df SS MS F Significance F
Regressio
n 1 5.231242 5.231242 71.56456 3.37E-17
Residuals 5715 417.7563 0.073098
SUM 5716 422.9876
Regression computed results
Multiple-R 0.111209
R-Square 0.012367
Adj R-Square 0.012195
Std Error 0.270367
Obs 5717

EXPLANATION
we found a multiple R value of 0.111209 which shows that the
relationship between ages of the company is slightly lower but
relates to it positively showing that the older the company the
higher probability of being ISO certified. The R square which is the
coefficient of determination is being used as an indicator of
goodness of fit.
From the Anova part, the F part and the F significance are the most
crucial parts, having 3.37E-17 is a good figure and the model is
okay.

T TEST DATA
Testing the means difference between companies that are ISO certified and revenue
generated
Hypothesis
HO: μ1- μ2=0
H1: μ1- μ2≠0
Explanations
To reject our null hypothesis we base our results on the following decision criterion
If T stat< -t critical two tail test
But we have our T stat at -18. 8098 and t critical at 1.960379
This is not the real situation here, we there fail to reject the null hypothesis and
conclude that it is not statistical significant to conclude that companies
certification and their revenues differ. Both the certified and the uncertified
companies generate revenues.

T TEST DATA RESULTS
t-Test: Paired Two Sample for Means
0 6
Mean 0.080476 6.544962
Variance 0.074012 675.0806
Observations 5716 5716
Pearson Correlation 0.001072
Hypothesized Mean Difference 0
df 5715
t Stat -18.8098
P(T<=t) one-tail 6.23E-77
t Critical one-tail 1.64512
P(T<=t) two-tail 1.25E-76
t Critical two-tail 1.960379

DISCUSSION AND MANAGERIAL ADVICES
 From the data analysis performed it was found that only 460
companies out of the possible 5717 were ISO certified, that’s a very
small percentage just 8% the other 92% were not certified. Martinez
and Garcia. (2009) argued that ISO 9000 is important since it
increases marketability, improving internal communication and
enabling enacting of safety and health standards.
 Bigliardi, Ivo and Galati (2012) advocated for adoption of open
innovation in the telecommunication industry, which over time would
result in the industry success. The managers and companies
managing directors are urged to also invest more in
telecommunication industries