Determinants Of Adoption Of ISO 9000 And Its Impact On Firm Performance

Data Collection and Analysis

Discuss about the International Certification in Developing Countries.

Complete customer satisfaction is the motto of the most of the industries (manufacturing as well as service industries). There are many industries who claims that they fulfill all the customer’s needs. Each consumer have different approach to select his or her service provider. Certification is one of the most common approach of the customer for selecting the service provider. Certification is nothing but the provision by an external body of written assurance (in terms of certificate) that the product, service or system in question meets specific requirements.

ISO is an independent, non-governmental international organization with a membership of 161 national standards bodies. Through its members, it brings together experts to share knowledge and develop voluntary, consensus-based, market relevant International Standards that support innovation and provide solutions to global challenges. The ISO 9000 series of quality management systems standard has been widely applied all over the world since its introduction in 1987. By the end of 2013, ISO 9000 had been adopted by over 1,129,000 facilities in 189 countries. Both academics and practitioners are interest in understanding the determinants of adoption of ISO 9000, and the impact of the adoption of ISO 9000 on firm financial performance (Christmann & Taylor, 2006; Du, Yin, & Zhang, 2016; Fikru, 2014a, 2014b, 2016; Nakamura, Takahashi, & Vertinsky, 2001; Pekovic, 2010; Wu, Chu, & Liu, 2007).

In this study, we have data of 5717 industries out of which 460 are certified (5257 not certified). We analyzed the certified and non-certified firms. Data is collected for both certified and non-certified firms with respective to industry type, foundation year of industry,  number of employees with education level (master/Doctor, bachelor, diploma holder, High school, Junior high school and below), sales of company, profit of company, Total asset of the company, Equity of the company, Total capital, Capital from government, Capital from overseas, Capital from other sources, Return on sales, Return on assets, Percentage of overseas investment in the total investment, Overseas investment and Age of the company.

In this study we determine the determinants of ISO 9000. We analyzed the certified and non-certified industries with respective to industry type. We considered the number of employees with education level and age of the company are the important variable for predicting the status of certification. We studied the impact of certification on the performance of the industry. We considered sales of company, profit of company, Total asset of the company, Equity of the company, Total capital, Capital from government, Capital from overseas, Capital from other sources, Return on sales, Return on assets, Percentage of overseas investment in the total investment, Overseas investment variables as a performance variables.

Determinants of Adoption of ISO 9000

We test whether the proportion of certified firm is same for all the industry type or not. We study whether the number of employees with education level and age of the company are the significantly different for certified firms or not. We test whether the performance variables are significantly different for certified and non-certified firms.

In today’s world certification is an important concern for all the industries. Numerous empirical studies have examined the determinants of firm participation in ISO Certification in developed as well as developing countries. (Christmann & Taylor, 2006; Du, Yin, & Zhang, 2016; Fikru, 2014a, 2014b, 2016; Nakamura, Takahashi, & Vertinsky, 2001; Pekovic, 2010; Wu, Chu, & Liu, 2007). For example, Fikru(2016) finds that foreign ownership, plant size and business communications through company website are important for the adoption of standards in Africa. DeCanio and Watkins (1998) conclude that firm size, earnings and insider shareholders are significant determinants of voluntary participation of US firms in the Green Lights programme. Fikru (2014a) finds that international connectivity, sources of finance such as credit from local banks or local customers, and manager’s human capital as significant determinants of international standards.

The use of different statistical tools and techniques is becomes mandatory for analysis. The selection of proper tools and techniques is very important for the analysis of data. We used the frequency distribution, descriptive statistics for the study variables. We observed the proportion of certified firm is same for all the industry type or not. We used t-test for  determining the determinants of adoption of ISO 9000.  We used t-test for testing the significance of performance variables for certified and non-certified firms. We used one way ANOVA for the significance of performance variables for certified firms by considering the type of industry as a level. We have mostly used SPSS software for analysis.

Table 1 summarizes the frequency distribution of certified and non-certified firms. Out of 5717 firms 460 (8%) are certified and 5257 (92%) are non-certified. Table 2 gives the frequency distribution of industry type. Business Service accumulated 47.6 % and Specialized technology services accumulated 21% of total 5717 industries.

Table 1: Frequency Distribution of Certification dummy

	Frequency	Percent	Cumulative Percent
not certified	5257	92.0	92.0
certified	460	8.0	100.0
Total	5717	100.0

Table 2: Frequency Distribution of Industry Type

	Frequency	Percent	Cumulative Percent
storage and transportation	392	6.9	6.9
Telecommunication	184	3.2	10.1
computer services	365	6.4	16.5
software	390	6.8	23.3
Business services	2722	47.6	70.9
Research and Development	222	3.9	74.8
Specialized technology services	1200	21.0	95.8
Technology exchange and promotion	242	4.2	100.0
Total	5717	100.0

We observed the proportion of certified firm accordingly to the industry type and reported in Table 3. From Table 3, one can observed that 19% software, 18% Specialized technology services, 15% Research and Development firms are certified. Cerification adoption was very little in the Telecommunication (2%),   Business services (3%), storage and transportation (4%), Technology exchange and promotion (5%) and computer services (8%).

Impact of ISO 9000 Certification on Firm Performance

Table 3: Proportion of Certified firms industry type wise

industry type	Proportion	No. of Observation	Std. Deviation
storage and transportation	.04	392	.186
Telecommunication	.02	184	.146
computer services	.08	365	.275
software	.19	390	.397
Business services	.03	2722	.161
Research and Development	.15	222	.357
Specialized technology services	.18	1200	.386
Technology exchange and promotion	.05	242	.218
Total	.08	5717	.272

To determine the determinant of adoption of ISO 9000, we used the logistic regression. Here certification dummy is our response variable which has dichotomous scale. (0 for non-certified and 1 for certified). We used employee number, education levels and company age as an independent variables for fitting the logistic model to the certification dummy variable. First we observed the descriptive statistics of the predictor variables (independent variables) education levels and company’s age for certified and non-certified firms.

Table 4a: Descriptive Statistics for predictor variables (independent variables) education levels and company’s age for certified firms.

	N	Minimum	Maximum	Mean	Std. Deviation
employee number	460	11	913	100.53	129.464
master and doctor	460	0	136	4.54	11.735
bachelor	460	0	388	38.83	55.588
diploma	460	0	343	31.00	44.440
high school	460	0	689	19.52	51.921
other	460	0	245	6.64	26.653
age of company in years	460	2	56	10.28	9.144
Valid N (listwise)	460

Table 4b: Descriptive Statistics for predictor variables (independent variables) education levels and company’s age for certified firms.

	N	Minimum	Maximum	Mean	Std. Deviation
employee number	5257	11	969	40.10	65.257
master and doctor	5257	0	161	1.10	4.713
bachelor	5257	0	530	9.49	23.266
diploma	5257	0	490	11.34	20.950
high school	5257	0	600	11.63	28.711
other	5257	0	568	6.54	25.923
age of company in years	5257	2	61	7.39	6.815
Valid N (listwise)	5257

By comparing Table 4a and 4b, we can see that mean of number of employee, number of masters and doctors, bachelors, diploma holders and number of employees attended high school for certified firm is more than non-certified firms. Mean age of certified firm is also more than mean age of non-certified firms.

Table 5 represents the Pearson’s correlation coefficient and it’s significance. All the predictor variable are positively correlated with response variable and significant expect the number of employees having education below high school and other. From Table 5, one can observe the correlation between the predictor variables.

We run the independent two sample t test for comparing the mean number of employee, masters and doctors, bachelors, diploma holder, attended high school, other and age of company in years. Table 6a shows the mean, standard deviation and standard error for each variable for certified and non-certified firms.

Table 6b represents the independent two sample t test for the considered variables. Table 6b also shows the Levene’s Test for Equality of Variances for all the variables. Levene’s Test for Equality of Variances suggest that there is significant differences between the variance of considered variable for the certified and non-certified firms. So we assume that unequal variances assumption for the independent two sample t test. SPSS gives the output for both the assumptions under equal as well as unequal variance assumption. From Table 6b, we conclude that mean of number of employees, masters and doctors, bachelors, diploma holder, attended high school and age of company in years are significantly different for the certified and non-certified firms.  Mean of number of employees, masters and doctors, bachelors, diploma holder, attended high school and age of company in years for the certified firm is more than non-certified firms. We can say that as the number of employees, masters and doctors, bachelors, diploma holder, attended high school and age of company in years are the important variables for the certified firms and are to be considered as the main determinant.

Conclusion

We considered sales of company, profit of company, Total asset of the company, Equity of the company, Total capital, Capital from government, Capital from overseas, Capital from other sources, Return on sales, Return on assets, Percentage of overseas investment in the total investment, Overseas investment variables as a performance variables. We firstly summarizes the descriptive statistics for the performance variable for certified and non-certified firms in the Table 7a and Table 7b respectively.91.066

From Table 7a and Table 7b, we can observed the differences in summary statistic of the performance variables for certified and non-certified firms. Now we are interested in testing whether there is significant differences in the performance variables for certified and non-certified firms. We run the

	N	Minimum	Maximum	Mean	Std. Deviation
sales	5257	1000	869176	1.01E4	29617.093
profit	5257	17	296176	1865.26	6911.274
asset	5257	1000	978548	1.50E4	53574.923
equity	5257	-1367	877989	6899.36	30642.061
capital paid	5257	10	402110	4371.79	16971.715
capital from state	5257	0	402110	1138.29	11427.342
capital from overseas	5257	0	150000	329.61	4650.860
capital from other	5257	0	400000	2903.90	11278.126
return on sales	5257	.01	.51	.1943	.12344
return on asset	5257	.01	1.02	.2285	.21102
percentage of FDI	5257	.00	1.00	.0244	.14940
Valid N (listwise)	5257

We run the independent two sample t test for comparing the mean of Sales of the company, Profit of the company, Total asset of the company, Equity of the company, Total capital,

Capital from government, Capital from overseas, Capital from other sources, Return on sales

Return on assets, Percentage of overseas investment in the total investment for certified and non-certified firm.

Table 8 represents the independent two sample t test for the performance variables. Table 8 also shows the Levene’s Test for Equality of Variances for all the performance variables. Levene’s Test for Equality of Variances suggest that there is significant differences between the variance of performance variable for the certified and non-certified firms. So we assume that unequal variances assumption for the independent two sample t test. SPSS gives the output for both the assumptions under equal as well as unequal variance assumption. From Table 8, we conclude that mean of Sales of the company, Profit of the company, Total asset of the company, Equity of the company, Total capital, Capital from other sources, Return on sales and Return on assets for certified and non-certified firm are significantly different whereas mean of Capital from government, Capital from overseas  and Percentage of overseas investment in the total investment are not significantly different for certified and non-certified firm.

We now test whether there is any significant difference in the performance variable in the certified firms of different industry type. We used one way ANOVA as an analysis tool for testing this claim. Table 9 summarizes the ANOVA table for performance variable in the certified firms of different industry type.  From Table 9, we can conclude that Sales of the company, Profit of the company, Capital from government and Return on assets are significantly different for different type of industries which are certified

We observed that 19% software, 18% Specialized technology services, 15% Research and Development firms are certified. Certification adoption was very little in the Telecommunication (2%),   Business services (3%), storage and transportation (4%), Technology exchange and promotion (5%) and computer services (8%).

We conclude that mean of number of employee, number of masters and doctors, bachelors, diploma holders and number of employees attended high school for certified firm is more than non-certified firms. Mean age of certified firm is also more than mean age of non-certified firms. We can say that as the number of employees, masters and doctors, bachelors, diploma holder, attended high school and age of company in years are the important variables for the certified firms and are to be considered as the main determinant.

We observe that mean of Sales of the company, Profit of the company, Total asset of the company, Equity of the company, Total capital, Capital from other sources, Return on sales and Return on assets for certified and non-certified firm are significantly different whereas mean of Capital from government, Capital from overseas and Percentage of overseas investment in the total investment are not significantly different for certified and non-certified firm.

One may recruits more number of employees, masters and doctors, bachelors, diploma holder, attended high school to adopt the ISO certification. This ISO certification brings the industry or firm into new heights.

This study is specially for determining determinants of the adoption of ISO 9000 standards only. There are many more standard e.g. ISO 14000 etc. for which different study can be done. There may be more variables which affect the adoption of ISO 9000 standards e.g. geographical area, turn over, salary paid to the employees, other benefits to the employee, customer satisfaction etc. One can study this type of study by considering the given limitations. One can used advanced statistical tools such as logistic regression, factor analysis for data analysis.

References

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