Objectives

Discuss About The Adoption Of Iso 9000 And Its Impact On Firm.

One of the major concerns of industries around the world is the quality of management for the betterment of their operations. In the efforts made to improve the management quality of the firms, ISO 9000 was developed and brought to being whose main aim was to give guidance tools to the firms ensuring that the goods and services’ production is as per the customers’ desire and of good quality Montiel, I., Husted, B. W., & Christmann, P. (2012). Since the emergence of ISO 9000 back in the year 1987, it has gained increasing popularity and adopted by both big and small companies since it outlines the companies’ management operations. One of the functions of the international standards organization (ISO) is to ensure that the design of products are at per with the preset standards Lo et al., (2013). Almost 187 countries have adopted ISO 9000 in the management of their companies and quality assurance since 1987. This report is focused in achieving some of the goals by the end as stated below;

Genera objective of this report was to determine the adoption of ISO 9000 and the impacts it has on the performance of the firms.

1. Assessing the impacts of adopting ISO 9000 in the financial performance of the firms
2. Assessing the effects of certifying a firm with ISO 9000 on the management of the firms

Better understanding will be rooted through achieving the two aforementioned objectives on the determinants and impacts of adopting ISO 9000. The effects of certifications of the firms with ISO 9000 in the firms’ management will as well be clarified.

Several researches have been conducted by the researchers around the world in relation to the impacts of ISO 9000 since the time it came to being on the effects and success in business performance Zhu, Q., Cordeiro, J., & Sarkis, J. (2013). Out of all the literatures available in regards to ISO 9000, they will be reviewed to bring support to the results that will be achieved in this report to review the impacts of ISO 9000 on the firms that adopt its use. Some of the previous studies explained that ISO certification results to improved firm’s financial performance Terziovski, M., & Guerrero, J. L. (2014). Further, the reviews of literatures over ISO 9000 tried to show the components that could have effects and links on achieving the financial performance with some of the involved financial benefits Ullah, B., Wei, Z., & Xie, F. (2014). The measure of ISO 9000 can be done indirectly in the determination of the financial performance by employing ample conceptual framework Tarí, J. J., Molina-Azorín, J. F., & Heras, I. (2012). Measure of the success of ISO 9000 certification can be achieved by considering the effectiveness of certification Mokhtar, M. Z., & Muda, M. S. (2012). Although direct relationship might not exist between the financial performance and ISO, the operational performance could be directly increased due to its direct effect on increasing the financial performance. One of the most important benefits enjoyed from certification of the firms are the external perspectives which could be achieved from the valuation of ISO implementation impacts. In regards to that, more of the welfares of ISO 9000 are perceived to be external in nature that showed greater operative performance Starke et al., (2012).

Literature review

Business organizations adopt ISO 9000 with the focus of having quality addition on the ways the business organizations are managed Prajogo, D., Huo, B., & Han, Z. (2012). Consequently, adopting and incorporating ISO 9000 in business organization were towards developing the firms and gearing them towards enjoying the maximum benefits instead of when it was used for non-developmental reasons which would make them enjoy less benefits Heras-Saizarbitoria, I., & Boiral, O. (2015). To seal and realize the benefits from ISO 9000, evaluation of companies should be in accordance to their goals and categories independently to identify ISO 9000 benefits Campos et al., (2015). Companies that are certified by ISO 9000 showed increased profits when market differentiation strategy is carried out in operationalization cost leadership strategy. ISO 9000 gives some of the benefits that act as the motivational factors that are important when carrying out positive predictions Abad, J., Lafuente, E., & Vilajosana, J. (2013). In order to cope up with the everyday changes in the business environment and have particular focus on the improvements of business operation, ISO have to be taken through series of updates to address such changes. Level of practices in ISO 9000 certified companies is higher as compared to those which are non-ISO 9000. All business operations consider time as a great factor for their effectiveness felt. Due to that, companies that were long certified showed great and better improvements of the TQM results than the ones that were newly certified by ISO 9000. Companies that are certified with latest updated ISO with time realize more benefits as compared to those companies that were certified with the traditional or non-updated or older versions of ISO 9000 Nguyen, Q. A., & Hens, L. (2015). The improvement of financial performance of businesses can be easily analyzed and visualized for companies certified with ISO 9000 using 3-5 years period of post-certified.

Businesses and companies irrespective of their sizes are adopting ISO 9000 in their daily management activities. The size of the company or the business does not have any impact upon certification with ISO 9000 hence the effects remain constant Pereira-Moliner, J., Claver-Cortés, E., Molina-Azorín, J. F., & Tarí, J. J. (2012). Different factors such as the area coverage of the company, the number of employees a company have do not show any significant effect on the implementation of ISO 9000 performance. Positive effects are realized on companies’ operational performance when they are certified with ISO 9000. Bids and general external benefits are among other benefits that companies enjoy when they are certified with ISO 9000 hence improving their performances.

Methodology

Since the emergence of ISO 9000 in 1987, companies have acquired and adopted it to enhance the quality of their management. The number of companies joining ISO 9000 have immensely grown in the past decades. The data collection technique that was employed in the collection of data was use of questionnaires. For quality management in the field of operations management, questionnaires have gained increased use in the process since 1980s. For instance, in this case, the National Bureau of Statistics of China conducted census using the questionnaires to collect data from a population of 5717 service firms. That formed that targeted population of the total number of firms in the entire China. Smooth completion of the process included and required the firms to fill in the questionnaires that were sent to them. Relevant authorities (i.e. managing directors and managers) were the ones who were engaged in filling and responding to the questions in the questionnaires on behalf of the firms. The required details were not limited to the number of employees, certification year of the company, when the companies were formed, sales the companies made and so on. Though the expenses involved in the census process are high and time consuming, in order to meet all the firms, the questionnaires were presented to all the firms in china by the National Bureau of China since they all formed part of the population. Since there no sampling method used, no information was left out since all firms in the country were reached and have all their information recorded.  

All the data that were gathered were recorded in Microsoft excel and then transferred into the SPSS for data analysis. Both software were engaged in the representation of data in graphs and tables to bring understanding and for easy interpretations. Descriptive statistics such as the mean, standard deviation minimum, etc. were used to describe the data and inferential statistics such as t-test, correlation and Pearson’s correlations were used to draw inferences and make conclusions. The population parameter of the firms concerning the adoption of ISO 9000 was obtained from the census data since all the firms in china were involved. Due to the accuracy of the data obtained from the censuring process that included all the firms, the data can be relied upon when determining the adoption and impacts of ISO 9000 on the determination of the certification and financial performance of the firms.

This part of the report contains the findings that will give support to the objectives and research questions concerning the impacts of the adoption of ISO 9000 on the performance of the firms. Descriptive statistics and inferential statistics will all be calculated to confirm whether or not ISO 9000 resulted to some impacts on financial performance in the service companies.

Table 1: Descriptive statistics for the service firms
	N	Minimum	Maximum	Mean	Std. Deviation
l	5717	11	969	44.96	74.378
l_yjs	5717	0	161	1.38	5.688
l_benke	5717	0	530	11.85	28.453
l_dz	5717	0	490	12.92	24.306
l_gaozhong	5717	0	689	12.26	31.290
l_chuzhong	5717	0	568	6.54	25.980
revenue	5717	1000	869176	11698.57	32873.609
profit_operating	5717	17	296176	2067.97	7158.417
ksum	5717	1000	978548	16473.16	54666.560
equity	5717	-1367	877989	7693.77	31012.079
kpaid	5717	10	402110	4765.67	17120.175
kstate	5717	0	402110	1201.12	11264.936
koversea	5717	0	150000	348.87	4598.814
kother	5717	0	400000	3215.68	11765.554
ROS	5717	.01	.51	.1911	.12397
ROA	5717	.01	1.02	.2236	.20858
FDIpercent	5717	.00	1.00	.0245	.14937
agefirm	5717	2	61	7.62	7.074
Valid N (listwise)	5717

From the censures conducted by National Bureau of Statistics of China, the smallest number of employees from the censured firms was 11 with the highest number being 969 and the mean number of employees and standard deviation being 44.96 and 74.378 respectively. Considering the level of education, 161 employees had master or doctoral level of education, 530 employees across all firms had bachelor degree, 490 had diploma, 689 employees across all censured firms had high school education level and 568 employees had junior high school or below levels. The minimum firms’ sales revenue was 1000 with their highest sales revenue being 869,176 with the mean revenue for all censured firms being 11,698.57 and standard deviation of 32,873.61. The least profit recorded by the firms from the census was 17 with the maximum profit of 296,176, standard deviation of 7158.42 and a mean profit for the firms being 2067.97 ate the time of census. The total assets of the companies was as well asked for whereas the lowest assets recorded was 1000 and highest assets being 978548 with the mean of 16473.16 and standard deviation of 54666.56. The equity of the companies provided from the census records showed the minimum of -1367 and a maximum firms’ equity being 877989, mean of 7693.77 and standard deviation of 31012.08. The lowest total capital of the companies recorded was 10 and maximum capital of 402110 with the mean of 4765.67 and standard deviation of 17120.175. The minimum total capital from the government was zero (0) and the maximum total capital of 402110, mean of 1201.12 and standard deviation of 11264.94. The minimum capital from the overseas recorded was zero and maximum 150000, mean of 348.87 and standard deviation of 4598.81. The capital from other sources recorded had the maximum recording of 400000 with the mean of 3215.38 and standard deviation of 11765.55. Among other asked variables was return on sales which had the minimum value of 0.01 and maximum of 0.51, mean of 0.1911 and standard deviation of 0.12397. On the other hand, the minimum returns on assets recorded was 0.01 and maximum of 1.02 with the mean of 0.2236 and standard deviation of 0.20858. The minimum percentage of the overseas investment in the total investment was 0.00 with the maximum percentage being 1.00 with the mean of 0.0245 and standard deviation of 0.14937. Finally, the minimum age of certification for the firms with ISO 9000 was 2 years and oldest firm certified with ISO was 61 years with the mean age of 7.62 and standard deviation of 7.074.

H₀: There are no significant means difference between the paired tests of variables in the firms

H₁: There are mean difference between the paired tests of variables in the firms

Table 2: Paired Samples t-test
	Paired Differences	t	df	Sig. (2-tailed)
Mean	Std. Deviation	Std. Error Mean	95% Confidence Interval of the Difference
Lower	Upper
Pair 1	kpaid – kstate	3564.550	12675.367	167.640	3235.913	3893.187	21.263	5716	.000
Pair 2	kpaid – koversea	4416.802	16288.493	215.425	3994.487	4839.118	20.503	5716	.000
Pair 3	kpaid – kother	1549.993	12393.411	163.910	1228.666	1871.320	9.456	5716	.000
Pair 4	kstate – koversea	852.252	11937.301	157.878	542.751	1161.753	5.398	5716	.000
Pair 5	kstate – kother	-2014.558	16289.232	215.435	-2436.892	-1592.223	-9.351	5716	.000
Pair 6	koversea – kother	-2866.809	12589.272	166.501	-3193.214	-2540.405	-17.218	5716	.000
Pair 7	ROS – ROA	-.03248	.17364	.00230	-.03698	-.02798	-14.143	5716	.000

From the paired t-test conducted between the total capital and the capital from the government, (p<0.05) showing that there no statistical significant difference between the two variables in the first pair. No statistical significant difference was as well tested between total capital paid and the capital from the overseas since (p<0.05). Between total capital and the capital from other sources showed not to have statistical significance since (p<0.05). For the test of the statistical mean difference between capitals from the government and capital from the overseas showed no significant difference. The same was tested between capital from the overseas and capital from other sources as well as the test of significant difference between return on sales and returns on assets since they all had the significant test (p<0.05). From the aforementioned test results, the null hypothesis would be rejected and conclude otherwise that there were mean difference between the tested variables in the pairs from the first to the sixth pair.

H₀: There is no correlation between variables

H₁: There was correlation between variables

table 3: Correlations
	l	revenue	profit_operating	ksum	kpaid	kstate	koversea	kother	ROS	ROA
l	Pearson Correlation	1	.471**	.407**	.337**	.272**	.141**	.090**	.225**	-.101**	-.053**
Sig. (2-tailed)		.000	.000	.000	.000	.000	.000	.000	.000	.000
N	5717	5717	5717	5717	5717	5717	5717	5717	5717	5717
revenue	Pearson Correlation	.471**	1	.762**	.549**	.423**	.260**	.184**	.295**	-.041**	.016
Sig. (2-tailed)	.000		.000	.000	.000	.000	.000	.000	.002	.219
N	5717	5717	5717	5717	5717	5717	5717	5717	5717	5717
profit_operating	Pearson Correlation	.407**	.762**	1	.562**	.473**	.334**	.189**	.294**	.189**	.126**
Sig. (2-tailed)	.000	.000		.000	.000	.000	.000	.000	.000	.000
N	5717	5717	5717	5717	5717	5717	5717	5717	5717	5717
ksum	Pearson Correlation	.337**	.549**	.562**	1	.686**	.427**	.235**	.497**	.089**	-.142**
Sig. (2-tailed)	.000	.000	.000		.000	.000	.000	.000	.000	.000
N	5717	5717	5717	5717	5717	5717	5717	5717	5717	5717
kpaid	Pearson Correlation	.272**	.423**	.473**	.686**	1	.672**	.311**	.690**	.082**	-.114**
Sig. (2-tailed)	.000	.000	.000	.000		.000	.000	.000	.000	.000
N	5717	5717	5717	5717	5717	5717	5717	5717	5717	5717
kstate	Pearson Correlation	.141**	.260**	.334**	.427**	.672**	1	.054**	.000	.044**	-.052**
Sig. (2-tailed)	.000	.000	.000	.000	.000		.000	.997	.001	.000
N	5717	5717	5717	5717	5717	5717	5717	5717	5717	5717
koversea	Pearson Correlation	.090**	.184**	.189**	.235**	.311**	.054**	1	.010	.015	-.039**
Sig. (2-tailed)	.000	.000	.000	.000	.000	.000		.447	.242	.003
N	5717	5717	5717	5717	5717	5717	5717	5717	5717	5717
kother	Pearson Correlation	.225**	.295**	.294**	.497**	.690**	.000	.010	1	.071**	-.101**
Sig. (2-tailed)	.000	.000	.000	.000	.000	.997	.447		.000	.000
N	5717	5717	5717	5717	5717	5717	5717	5717	5717	5717
ROS	Pearson Correlation	-.101**	-.041**	.189**	.089**	.082**	.044**	.015	.071**	1	.555**
Sig. (2-tailed)	.000	.002	.000	.000	.000	.001	.242	.000		.000
N	5717	5717	5717	5717	5717	5717	5717	5717	5717	5717
ROA	Pearson Correlation	-.053**	.016	.126**	-.142**	-.114**	-.052**	-.039**	-.101**	.555**	1
Sig. (2-tailed)	.000	.219	.000	.000	.000	.000	.003	.000	.000
N	5717	5717	5717	5717	5717	5717	5717	5717	5717	5717
**. Correlation is significant at the 0.01 level (2-tailed).

A positive correlation of 0.471 was recorded between the number of employees and the revenues generated by the firm. The negative correlation existed between return on sales and return on assets with the numbers of employees. Profit of the company had a strong positive correlation coefficient of 0.762. Total assets of the company also had strong positive correlation of 0.549 with the revenue of the company. The total capital showed to have strong positive correlation 0.686 with the total assets of the company. The return on sales and return on assets posted weak negative correlation with the number of employees in the companies with correlation coefficient of -0.101 and -0.053 respectively. Capital from other sources had strong positive correlation with the total capital of the company with Pearson’s correlation coefficient of 0.69.

The number of employees is directly correlated with the size of the company i.e. the higher the number of employees in the company the larger the size of the company. In regards to that, it can be concluded from the results that some of the companies were bigger in size than others as that could be seen from the lowest number of the employees and the highest number of employees firms had from the census (11 and 969 respectively). From the mean number of employees which was 45 employees showed that a large number of the censured companies were relatively big. Companies were seen to have employees of different levels of education with the highest number (689) of employees having high school education with the least number of employees attaining master and doctoral level of education (161). As from the literature review, large impact in the contribution to the business operation is from the skills of the employees which steer the company towards achieving their objectives (Palpacuer et al, 2011). The human resource department and entire managerial department should observe and prioritize the skills of the employees. Having large number of employees with high school education showed that large number of employees in the firms had low skills since skills are associated with the level of education which would be harmful to the performance and management of the firms. From the hypotheses tested about the significant differences between means of variables using the paired sample t-test showed that there was significant difference between means of the variables and thus there existed mean differences between means. In response to that, all the capital in the businesses should be treated by the managers with equal weight since they have vital importance in the companies. In the correlation test conducted to test for the relationship, some of the variables concerning the capital from the government, oversees and other sources showed to have either negative or positive correlations with others being strong positive correlations. In that regards therefore, all the variables showed at least some relationship. To wind up, the number of employees is one of the factors to be considered in determining the size of the company and should be regulated not to be too high or too low to have a good manageable employees’ ratio. Certifying companies with ISO 9000 had some significant correlation with the company’s sales. As a result, management of the companies should consider adopting ISO 9000 in their companies to continue enjoying the financial benefits.

The research questions and objectives were only concerned and limited to assessing the impacts of adopting ISO 9000 in the financial performance of the firms and assessing the effects of certifying firms with ISO 9000 on the firms’ management.  To bring better understanding of improving the management qualities, researches in the future should be concerned with the impacts of ISO 9000 in minimizing losses in the certified companies. In order to meet this an objective, the research questions should be structured towards addressing matters concerning minimization of ISO 9000 and data collected to give findings in support to that.

References

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