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Effectiveness of Supply Chain Management on Fashion Industry of Pakistan 1

Proceedings of 2nd International Conference on Business Management (ISBN: 978-969-9368-06-6)

EFFECTIVENESS OF SUPPLY CHAIN MANAGEMENT ON FASHION INDUSTRY

Effectiveness of Supply Chain Management on Fashion Industry of Pakistan

Muhammad Babar, Muhammad Bilal

National University of Sciences and Technology

Islamabad, Pakistan.



Abstract

The aim of this paper is to find the effectiveness of supply chain management on the fashion

industry of Pakistan. The purpose was to see whether there is any contribution by supply

chain in the growth of the fashion industry. A research has been carried out in firms, by

applying primary research tools mainly questionnaire. A quantitative research has been

carried out which showed that a strong relationship is existing of quality and sourcing and a

moderate relationship of on time delivery and planning as independent variables of supply

chain on fashion industry in Pakistan.

Keywords – Supply chain, Fashion industry



Introduction

Supply chain management (SCM) is the synchronized set of procedures to design and

implement all the steps which is used in acquiring raw materials from suppliers, process

those into finished goods and providing it to end users. It consists of chain-wide information,

planning, resource management and universal performance measurement. Main goal of SCM

is to minimize the lead time and also reducing cost of the product. There are different

variables that affect SCM. Those variables are planning and management of logistics, raw

material transportation, better infrastructure, proper warehouses and extremely competent

planning and controlling of shipments. All those variables help in lowering the lead time of

value chain and cost.

If we look at the trends in textile and fashion industries of the world, the thing we notice is

that the lead time is decreasing day by day. Textile and clothing is one of the oldest sectors in

the history of the industrial development. Textile and clothing is one of the top

manufacturing industries throughout the world and it is contributing considerably towards the

economic growth of developing countries [1]. Textile industry contributes a good portion of

the Pakistani exports and thus helping Pakistani economy. Fashion industry and textile go

hand in hand as all the raw material needed in fashion industry comes from textile and

clothing industry. As per the Oscar Wilde "Fashion is a form of ugliness so intolerable that

we have to alter it every six months."

They must do whatever it takes to stay on top of textile and fashion industries [3]. The

delivery of products of fashion items in terms of lead-time and cost has changed. The

competition has increased and it has become hostile in recent times [3]. The root causes of

this situation are high demands, advancements in technology and the globalization process



[4]. Also, always research the company or individual you will be interviewing with [5]. The

objective of this research is to analyze the overall performance of supply chain management

of fashion industry in Pakistan.

Methodology

To conduct this research, primary data was collected in the form of questionnaires as the

research tool from Kohinoor mills Rawalpindi Islamabad. A standardized questionnaire was

developed and delivered to the respondents to gather data. Primary data was collected from

30 respondents. The theoretical framework was developed to measure the supply chain of

fashion industry on the dimensions of planning, quality, sourcing and on time delivery. The

statistical tool used for evaluating and interpreting the questionnaires into meaningful

information for resulting analysis is Statistical Package for Social Sciences (SPSS).

Figure 1: Theoretical Framework

Figure 1 explains the theoretical framework used in the study. Four independent variables or

dimensions namely quality, sourcing, planning and on time delivery are used to measure the

dependent variable supply chain management.



Discussion

TABLE I shows the respective Cronbach alphas of 4 independent variables used in the study.

Variables titled are quality, planning, sourcing and on time delivery. Among these four

variables sourcing and quality showed high internal consistency of 0.706 and 0.691

respectively, whereas planning and on time delivery showed a relatively lower internal

consistency of 0.547 and 0.519 respectively.

Table I: Reliability Stats for Independent Variable

TABLE II illustrates the mean scores of planning. Among the items used to measure this

dimension, defined marketing plan shows the highest mean score of 2.03. The items of

underutilized capacity, industrial planning and machine upgrading show relatively lower

mean scores of 2.0 each. The rest of items show very low mean scores.Table II: Mean Score

of Planning



TABLE III illustrates the mean scores of quality. Among the items used to measure this

dimension, imported raw material shows the highest mean score of 2.5. This means the

highest dependency of this item on the dimension. On the other hand, the item of

compensation comparison show the least mean score of 2.03 which shows the lowest

dependency of this item on the dimension of quality



Table III: Mean Score of Quality

TABLE 1V illustrates the mean scores of sourcing. Among the items used to measure this

dimension, modes of transportation shows the highest mean of 2.70 among all the items with

sourcing as a dimension. Another item that showed a very high mean is transportation in

Pakistan which is 2.60 which means that it’s contributing a lot to the supply chain

management. Order delivery within the lead time however shows the lowest mean score of

1.87. This shows a poor contribution to this dimension and hence to supply chain

management.

TABLE V illustrates the mean scores of on time delivery as a dimension. Among the items

used to measure this dimension, contacting retailers to estimate demand shows the highest

mean score of 2.07 which means supply and availability on time is highly contributing to this

dimension and so to the supply chain management. Responding to fluctuations in market



however shows the lowest mean score of 1.77. This shows a poor contribution to this

dimension and so to the supply chain management.

Table IV: Mean Score of Sourcing

Table V: On Time Delivery

Table VI illustrates the correlation table between the dependent variable supply chain and the

independent variables quality, planning, sourcing and on time delivery. The table shows that

correlation is significant between the dependent and independent variables. Quality and

sourcing are showing significantly strong correlation with the dependent variable supply

chain management. Quality is showing a correlation of 64.9% and sourcing of 64.1%. On



time delivery is also correlated significantly to supply chain management and showing a

value 62.2%. The dimension of planning is showing a relatively lower but good correlation

of 50.6%. As a whole, all the independent variables are strongly correlated to the dependent

variable.

Table VII shows the regression analysis of the dependent variable supply chain management

and independent variable quality. The value of the R square comes out to be 0.421 which

shows that 42.1 % of supply chain management (dependent variable) is explained by the

independent variable quality.

Table VI: Correlation Table

Table VII: ANOVA of Quality



Table VIII shows the regression analysis of the dependent variable supply chain management

and independent variable sourcing. The value of the R square comes out to be 0.441 which

shows that 44.1% of supply chain management (dependent variable) is explained by the

independent variable sourcing.

Table VIII: ANOVA of Sourcing

Table IX shows the regression analysis of the dependent variable supply chain management

and independent variable on time delivery. The value of the R square comes out to be 0.387

which shows that 38.7% of supply chain management (dependent variable) is explained by

the independent variable on time delivery.

Table IX: ANOVA of On Time Delivery



Table X shows the regression analysis of the dependent variable supply chain management

and independent variable planning. The value of the R square comes out to be 0.256 which

shows that 25.6 % of supply chain management (dependent variable) is explained by the

independent variable planning.

Table X: ANOVA of Planning

Figure 2 illustrates a scatter plot matrix showing the extent of correlation between all the

variables used in the study. The scatter plot proves that a strong correlation exists between

the four independent variables with the dependent variable



Figure 2: Correlation Diagram

Figure 3 explains the scatter plot matrix of the regression analysis of the independent variable

sourcing and the dependent variable supply chain management. The figure clearly shows the

value of R square or coefficient of determination which shows a more realistic and authentic

result of the regression coefficient. The value of R square for sourcing is 0.441 which shows

that dependent variable supply chain is explained or predicted by a value of 44.1% by the

independent variable sourcing. This proves a moderate fit relation between dependent and

independent variable.



Figure 3: Regression of Sourcing


on time delivery and the dependent variable supply chain management. The figure clearly

shows the value of R square or coefficient of determination which shows a more realistic and

authentic result of the regression coefficient. The value of R square for sourcing is 0.387

which shows that dependent variable supply chain is explained or predicted by a value of

38.7% by the independent variable on time delivery. This proves a moderate fit relation

between dependent and independent variable.



Figure 4: Regression of on time Delivery


planning and the dependent variable supply chain management. The figure clearly shows the




independent variable planning. This proves a modest fit relation between dependent and

independent variable.



Figure 5: Regression of Planning


quality and the dependent variable supply chain management. The figure clearly shows the




independent variable quality. This proves a moderate fit relation between dependent and

independent variable and the strongest than other independent variables.

Figure 6: Regression of Quality

Conclusion

On the basis of the findings, we can conclude that among all the independent variables,

sourcing as an independent variable is showing highest reliability i.e. 0.706 and hence

proving that the research is a reliable one. Also quality as a dimension showing 0.691 score,



proving it`s high reliability. Other two dimensions, namely are planning and on time delivery

showing their respective reliabilities of 0.547 and 0.519 respectively as well. Overall, we can

infer that the research is a reliable and valid one. Also, on the basis of above findings, it is

concluded that the quality showing a correlation of 64.9% and is significantly correlated to

our dependent variable supply chain management. Other dimension showing a high

correlation of 64.1% is sourcing, hence highly correlated to supply chain management. .

Out of the four dimensions, on time delivery showing a correlation of 62.2% and planning

with 50.6% showing a bit moderate correlation to supply chain management. On part of the

regression analysis, out of the dimensions, sourcing as an independent variable is explaining

our dependent variable supply chain management to a value of 44.1%. Second to that quality

as an independent variable is explaining the dependent variable to a value of 42.1%. Also on

time delivery is explaining to a value of 38.7% and planning is explaining supply chain

management with a value of 25.6%.

We conclude that as fashion industry in Pakistan has been growing for the past 5, 6 years at

reasonably good pace, supply chain is playing a very major role in the growth of fashion

industry. We strongly recommend that supply chain must be given the primary importance in

order to keep the growing at the rapid speed. Also on the final words, we hope that this

research would provide a great deal of help to the prospect scholars and the organizations

working for the fashion industry. This knowledge will open the new horizons of study for

them.



References

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textile/cloting sector: An exploratory study in the region of Capania” (IRAT) CNR,

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G. M. Allenby & P.E. Rossi (1991), “Quality Perceptions and Asymmetric Switching

between Brands”, Marketing Science, Vol. 10, No. 3 (Summer, 1991), pp. 185-204.

P. Vogt & A. Wojak (2007). “Carrer Opportunities in the fashion Industry”, Checkmark

books (Aug, 200).

H.J. Chao & V. Pucik (2005), “Relationship between Innovativeness, Quality,

Growth, Profitability, and Market Value”, Strategic Management Journal,

Vol. 26, No. 6 (Jun, 2005), pp. 555-575.

J. Giacobellow, (2003). “Carers in the Fashion Industry” ISBN – 10 (0823940829), Aug

2003.

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