Discussion of Research Methods and Their Findings related to Performance

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Questionnaire was used to collect the data. Internet was used to collect the data. Personal visits were also made for some questionnaires. 3.2 Sampling Technique The technique for my study was convenience, because it was most suitable technique for me to collect the data.

3.3 Sample Size

The size of population for the study is 30.

3.4 Instrument of Data Collection

We used the questionnaire as an instrument to collect the data.

3.4.1 Validity and Reliability test

3.5 Research Model developed

Quality management

Information technology Value chain performance

Technological diversity

Customer service

3.6 Statistical techniques

Simple regression techniques were used for the statistical test through the Spss software.

CHAPTER 4: RESLUTS

4.1 Finding and interpretation of results

H1: Has a significant Quality management impact on value chain performance?

TABLE 4.1

The above given table shows the model summary of the applied model. Enter method is used to developed the results of this study. The R square value shows .352 or 35% variation. It means that a single unit alteration in the (free or) independent variable (Quality management) is bringing 35% change in the dependent variable that is value chain performance.

TABLE 4.2

The above given table shows that the model is applicable for test because of significant value of the model is less than 0.05. Our regression model is suitable to be applied for this test.

In the coefficient table we see the dependent variable and independent variable relationship. The significance value is below .05. We can observe from this table that the quality management has a significant impact on the value chain activities. The above results show the acceptance of our hypothesis. The beta value 3.970 shows that there is positive relation between the value chain activities and quality management.

H2

Technological diversity and introduction of modern technology will have positive effect on the value chain performance

TABLE 4.4

The above given table shows the model summary of the applied model. Enter method is used to developed the results of this test. The R square value shows .171 or 17% variation. It means that a single unit alteration in the (free or) independent variable (Technological diversity) is bringing 17.1% change in the dependent variable that is value chain performance.

TABLE 4.5

. The above given table shows that the model is applicable for test because of significant value of the model is less than 0.05. Our regression model is suitable to be applied for this test

TABLE 4.6

In the coefficient table we see the dependent variable and independent variable relationship. The significance value is below .05. We can observe from this table that the Technological diversity has a significant impact on the value chain activities. The above results show the acceptance of our hypothesis. The beta value 2.445 shows that there is positive relation between the value chain activities and quality management.

H3:

Information technology is has significant impact on value chain performance

TABLE 4.7

The R square value is .302 or 30.2%. It shows that there is 30.2% change in the dependent variable due to one unit change in the independent variable.

TABLE 4.8

The above given table shows that the model is applicable for test because of significant value of the model is less than 0.05. Our regression model is suitable to be applied for this test.

TABLE 4.9

.In the coefficient table we see the dependent variable and independent variable relationship.The significance value is below .05. We can observe from this table that the information technology has a significant impact on the value chain activities. The above results show the acceptance of our hypothesis. The beta value 3.539 shows that there is positive relation between the value chain activities and quality management.

H4:

Customer service has significant impact on value chain performance

TABLE 4.10

The above given table shows the model summary of the applied model. Enter method is used to developed the results of this test. The R square value shows .257 or 25.7% variation. It means that a single unit alteration in the (free or) independent variable (Customer service) is bringing 25.7% change in the dependent variable that is value chain performance.

TABLE 4.11

The above given table shows that the model is applicable for test because of significant value of the model is less than 0.05. Our regression model is suitable to be applied for this test.

TABLE 4.12

In the coefficient table we see the dependent variable and independent variable relationship.The significance value is below .05. We can observe from this table that the Customer service has a significant impact on the value chain activities. The above results show the acceptance of our hypothesis. The beta value 3.539 shows that there is positive relation between the value chain activities and quality management.

4.2 Hypothesis Assessment Summary

No.

HYPOTHSIS

Beta

SIG.

RESULT

H0

Quality management has a significant impact on value chain performance

.593

.000

Accepted

H1

Technological diversity and introduction of modern technology will have positive effect on the value chain performance

. 413

.021

Accepted

H2

Information technology is has significant impact on value chain performance

.549

.497

Accepted

H3

Customer service has significant impact on value chain performance

.507

.004

Accepted

CHAPTER 5: DISCUSSIONS, CONCLUSION,

IMPLICATIONS AND FUTURE RESEARCH

5.1 Discussion

This research project has provided illuminating guidance for improving value chain performance for the textile sector. The acceptance of our hypotheses informs us that the textile garment sector will have to focus on the deterministic parameters studied in this project viz. Quality management, customer service, Technological excellence and information technology.

It is clear that the culture of customer service has lagged behind in Pakistan. As a result, many manufacturers have not recognized the importance of quality. A few unscrupulous exporters burnt their hands as whole lots of material marked for exports were rejected due to poor quality. On occasions customers were provided high quality sample, while material supplied was of poor quality resulting in rejection and loss of reputation.

This kind of practices are gradually disappearing as internal pressure from exporting organizations, competitive pressures from global competitors have made close compliance to customer requirement essential to success.

The importance's of high quality machinery to produce consistently high quality products and supply chain compatibility with the customers are also recognized as indispensable for the value chain. The textile exporters have invested in state of the art machinery and customer relationship management, supplier relationship management and enterprise resource planning software to help improve communications as well as supply chain efficiency.

The acceptance of our hypotheses shows that the textile sector has recognized the importance of these factors the value chain parameters assessed in this research project are being recognized by textile exporters as essential for business.

5.2 Conclusion:

In the conclusion, this study identified that quality management, customer service, technological diversity and information technology have a critical role in the value chain activities. Quality management which came up with the highest beta shows the high significance. Textile exporters must recognize quality as a critical determinant of the success in the competitive global business. Information integration, access to sophisticated production machinery and above all customer service dimension must be recognized as critical to their success.

5.2 Implications and Recommendation

Implication of this research is obvious. In order to survive in a world market that focuses on efficiency and not on regional quota opens both challenges and opportunities. Pakistan's textile sector can benefit from developing high quality indigenous textile machinery. Access to information technology such as ERP is essential to manage business operations as well as communications with the global partner. High cost of proprietary ERP has created many obstacles in acquiring the required information technology. Locally developed software promises much needed assistance in this area and needs to be supported by both government and textile exporters.

5.3 Future Research

The information collected and analyzed for the textile sector is applicable to any sector interested in exporting its products such as sports equipment, leather products, surgical equipment etc. The parameters investigated and identified in this research could be verified for their importance to various Export oriented industries.

Major research and development effort is clearly required in developing indigenous resources valuable to the supply chain. The prohibitive cost of information technology software, could be controlled by developing local software that could seamlessly integrate with proprietary software needs to be developed and research in this area would be truly helpful to the supply chain.

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