conjoint ananlysis shoe industry

Product : Leather Shoes

PDM : Sec – A of 41

IBS, Hyderabad (2009-11)

Team Sec - A

ANURAG SHUKLA 09BSHYD0148

SETHI PIYUSH MAHAVIR 09BSHYD0757

SAURABH TOSHAN 09BSHYD0754

SOUMI RAY 09BSHYD0852

SHUBHODEEP ROY

CHOUDHURY

09BSHYD0799

PATEL TAPANKUMAR

SUNILBHAI

09BSHYD1017

NEW PRODUCT DEVELOPMENT LEATHER SHOES Submitted to Prof. T.V.Ramraj



INDIAN LEATHER FOOTWEAR INDUSTRY The footwear industry is a significant segment in the leather industry in India. India ranks second among the footwear producing countries next only to China. This is a labor intensive industry and it is concentrated in the small and cottage industries. While leather shoes and uppers are concentrated in large scale units, the sandals and ‘chappals’ are produced in the household and cottage sectors. The leather industry is the 8th largest earner of foreign exchange for the country and it employs around 2.5 million people (mostly women). Some facts and figures related to the Indian Footwear Industry:

• 2.06 billion pairs of footwear produces in a year. • About 16% of the global production is produced in India. • Major Foreign destination markets : U.S.A – 12%, EU countries – 63%, Hong

Kong – 10%, Australia – 1.5%, others – 13.5%. • India has the best tanning expertise.

India has become the most favored destination for production of leather footwear. The major production centers in India are Chennai, Ranipet, Ambur in Tamil Nadu, Mumbai in Maharashtra, Kanpur in U.P, Jalandhar in Punjab, Agra and Delhi. Shoes marketed in India wear brand names like Florsheim, Bata, Khadims, Action, Liberty, Woodland, Red Tape, Red Chief, Lee Cooper, etc. As part of its effort to play a lead role in the global trade, the Indian leather industry is focusing on key deliverables of innovative design, consistently superior quality and unfailing delivery schedules. The availability of abundant raw material base, large domestic market and the opportunity to cater to world markets makes India an attractive destination for technology and investments. The Indian footwear industry is provided with institutional infrastructure support through premier institutions like Central Leather Research Institute, Chennai, Footwear Design & Development Institute, Noida, National Institute of Fashion Technology, New Delhi, etc in the areas of technological development, design and product development and human resource development.

Export and Import of footwear from and to India constitute a significant share in the total exports and imports in India. The different types of leather footwear exported from India are dress shoes, casuals, moccasins, sport shoes, horrachies, sandals, ballerinas, booties.



This project has been undertaken to study NEW PRODUCT DEVELOPMENT in the leather footwear market in India. This study considers various attributes and their various levels like:

1) PRICE (Rs.) : • 500 • 1000 • 1500

2) BRAND PREFERENCE :

• Branded • Unbranded • Indifferent

3) SHAPE :

• Flat nose • Long nose • Rounded nose

4) HEEL :

• Low • Flat • High

5) LACE :

• With lace • Without lace

Since we proposed to launch the product for men, in two colors, viz. Black and Brown, that attribute has not been taken into analysis; and respondents are men. The complete project work is divided into two parts, viz. Conjoint Analysis and Multi Dimensional Scale mapping.



Conjoint Analysis



To begin with, we have run the Design.exe file which prompted us to enter the no. of features. The no. of features in our analysis for Formal Leather shoes are 5, namely- Price, Brand Preference, Shape, Heel and lace.

The features are now defined in Design Specifications with model type as Part Worth. Apart from feature named Lace which is having 2 levels all other features have 3 levels which are defined in the next screen.

16 cards were then selected to be generated by the software with n/T value to be 1.6 which is greater than 1.3 and hence an acceptable value.



The levels of each attribute were then entered which are as shown-

The files were then saved twice as a card file and a design file. Duplicity for any card is checked in the next step and no duplicate card was found at this stage hence there was no need to change, replace or eliminate any card

The condition no. was then checked and found to be 2.13 which is within the acceptable limit of 25.



The correlation matrix is then analyzed which is shown as below-

In order to test the reliability and validity of our research we then proceeded to add 4 holdout cards to the existing 16 cards generated by the software. It was made sure that these holdout cards do not dominate the cards generated by the design.



Duplicity for any card is again checked in the next step and cards 5 and 18 were found to be duplicate, hence one of the attribute of card 5 was altered to make sure that there was no duplicity in the cards later.

The file is saved twice here in this stage as card and design file. The design file created is further used in the study. The cards were then visually verified for their consistency in their contents by displaying the cards under the display head.



The Design stage was then exited, and we then proceeded to run the LINMAP.EXE. Number of selection was chosen as 1 since we are going in for a new analysis.

Full profile conjoint was then selected to carry out further analysis.



After the previous routine steps we then proceeded with the initial ordering of the features as obtained via the software as shown under-



Specification file was then created in the previous snapshot.



After this we again went back to analyze the holdout data.



The correlation between holdout data and the predicted scores is found to be 0.17 which is indeed very less than the acceptable value of 0.7; several attempts were made to lower down the average percentage of pairs violated including addition of some more respondents but this was the fair data which we managed to get without manipulations.



Determining Group utility function was the next step in the analysis-



The Group Statistics showed that the first preference for users was Price which was rated as most important by 34.8% respondents then comes the preference for lace which was important to 32.58% respondents. The other preferences are shown as above. We now proceed to determine the no. of respondents violating in our study, for this we again go back to the initial screen and select option 4.

The threshold violations are then set to 20% in our study, and the distribution of number of violations is then asked for by selecting option 2.



The above screenshot shows the % of violations for the first respondent, and as can be seen the respondent’s first preference is for the shape then brand followed by other features. Likewise we obtained violations for each and every respondent and the cumulative violations (exceeding the threshold of 20%) for the entire set are depicted in the next screenshot.



This shows that 27.3% of our respondents violated the threshold acceptance region of 20%.



SEGMENT.EXE Here we try to locate the segment where our product fits the best.



From below, we can plot a graph of clusters.

Probable cluster, we can target. Above graph shows that we can form two clusters, based upon respondents’ responses. Below is a group utility function, which shows % importance of each attribute of our product. It is evident from below table that “PRICE” and “LACE” are the most prominent attributes to be taken care in designing the product (SHOE).

0

10000

20000

30000

40000

50000

60000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Axi

s Ti

tle

Cluster

Distance



PRICE 1000 500 1500 REL. IMP. = 34.8% -5.735 0.467 5.268

BRAND PREFERENCE INDIFFERENT

NON-BRANDED

BRANDED

REL. IMP. = 8.57% 1.267 -1.444 0.177

SHAPE LONG NOSE FLAT NOSE

ROUNDED NOSE

REL. IMP. = 4.12% 0.566 0.171 -0.737

HEEL FLAT HIGH LOW

REL. IMP. = 19.92% 2.635 -3.663 1.027

LACE WITH LACE

WITHOUT LACE

•

REL. IMP. = 32.58% 5.149 -5.149



Here we can see that utility decreased as price increased from Rs. 500 to Rs. 1,000. But thereafter it shows that utility increased as price increases beyond Rs. 1,000. So, charging high prices, i.e. beyond 1000 we can not only increase customer utility, but can also fetch more profits. This gives us room to enter into a segment where consumers are ready to pay premium prices.

Most of the respondents are indifferent to brand.

-8

-6

-4

-2

0

2

4

6

500 1000 1500

REL.

IMPO

RTA

NCE

PRICE

PRICE

-2

-1.5

-1

-0.5

0

0.5

1

1.5

NON-BRANDED INDIFFERENT BRANDED

REL.

IMPO

RTA

NCE

BRAND PREFERENCE



Above graph shows lowest utility for ROUNDED NOSE and highest utility for LONG NOSE. This is an indication of how fashion conscious, respondents are.

Above shows FLAT HEELS are preferred by most of the respondents.

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

FLAT NOSE ROUNDED NOSE LONG NOSE

REL.

IMPO

RTA

NCE

SHAPE OF NOSE

-4

-3

-2

-1

0

1

2

3

FLAT LOW HIGH

REL.

IMPO

RTA

NCE

HEEL HEIGHT



Above graph shows respondents are more inclined to have a pair of shoes WITH LACE. Here our analysis shows that the complete respondent group can is divided into two clusters. Group #1 is more focused on LACE, HEEL and PRICE, whereas Group #2 is more concerned about SHAPE and HEEL.

-6

-4

-2

0

2

4

6

WITHOUT LACE WITH LACE

REL.

IMPO

RTA

NC

SHOE LACE



SIMULATION

Simulation file : SHOE-A.SIM is created.

.EXE Here we simulate a market scenario. We take product features of competitors and map their market share. Then we add our product and check that how successfully our product fetches market share of the existing competitors.

It asks no. of product we wish to simulate. Here we have taken 2 probable competitors’ product features.



Entre features of product #1.

Entre features of product #2.

Following shows market share of both the products (LEATHER SHOES) in the existing market (based upon the responses we have collected, it simulates customer preferences and calculates % of people who will buy which of these 2 products, of competitors)



Followings are the features of our product we intend to launch, against above 2 products of the competitor. (Here product #1 shows our launched product, which we intend to compare with that of our competitors’.) Here based upon the segment criteria, we derived earlier, we have taken values/information accordingly. Here we have banked upon two main criteria, i.e. PRICE, SHAPE and LACE.

Following shows respective market shares of the products. Here please note that product #1 and product #2 are competitors’ products, and product #3 is our prospective launching. We can see that market share of product #1 has been reduced from 48.468% to 24.24% and that of product #2 has been reduced from 51.52% to 21.21%. This is due to introduction of our new product in the market. From above, we can infer that our product has very high prospects of being popular and stands high adoptability from customers.



So, here we can conclude that the product we proposed will be successful in the market, which will have following attributes:

• Price : Rs. 1500 • Branded • Long Nose • High Heel • With Lace



Multi Dimensional Scale Analysis



POSITIONING USING MDS

Selection of the brands The number of brands included in our study of the footwear market is 4. The brands taken into consideration fulfill almost all possible attributes a footwear customer looks for. The brands represent both the high end market for foot-wears as well as the lower end of the market. This gives an overall view of the market in accordance to price, comfort, durability and many other factors discussed later. The four brands taken into consideration are:

• BATA • KHADIM • WOODLAND • FLOROSCHEIM

The idea behind the selection of these brands is also because these brands are the major players in the footwear industry. BATA originally an international brand but because of its strong presence in the Indian market is often mistaken by the consumers as an Indian brand. KHADIM is an Indian brand while WOODLAND and FLOROSCHEIM both are international brands but with a strong presence in the Indian market. So therefore by these selections we have tried to compare with two Indian and two International brands. We conducted a preliminary study where we asked the respondents to name few footwear brands and then looking at the no of frequencies of each brands i.e. how many times they were recalled by the respondents we zeroed into these four brands. The other brands which were discussed about were:

• LIBERTY • ACTION • LEE COOPER • RED TAPE

Going by the frequency of brand recall we thus decided to take into consideration the first four brands.



Selection of Attributes related to the brands The selection of the attributes was done after we conducted focus group study. The focus group studies were conducted in order to understand which are the attributes a consumer relates to a particular brand or what are the attributes a consumer looks for while purchasing a foot-wear. After two focus group studies the attributes which came up for the brands are: Affordability Flexibility Durability Quality Stylish Comfortable Firm Grip

The attributes are explained in brief below Affordability: a consumer before a purchase considers the price of the product and this attribute is one of the important elements of a purchase decision. Flexibility: By flexibility the consumer looks how flexible the shoe is in terms of running, walking or trekking. Durability: The consumer looks for how durable the product is i.e. how long the product will last. Quality: The quality in terms of everything matters a lot to the consumer because that’s what decides the value for money. Stylish: The style of a shoe is another important element of footwear especially in the case of formal and sports shoes. Comfortable: The footwear if isn’t comfortable then no other attributes matter Firm-Grip: The sole of the footwear needs to have a firm-grip so as to support and maintain balance.

Process of the study using MDS The process of the study can be broadly divided into four stages namely

1. Preparing the questionnaire 2. Filling up of the questionnaire 3. Data entry into EXCEL and SPSS 4. Analyzing the results and data interpretation



Preparing the questionnaire

The questionnaire was prepared after the focus group studies where the aim was to zero in the brands of the competitors following which to derive at the attributes a consumer looks for. The questionnaire prepared is attached at the end of the report. The questionnaire was divided into two parts. The first part required the respondents to rate the brands on the basis of the attributes on a likert scale. A specimen question is provided below Q. Rate the brand BATA on the basis of the following attributes where 1 refers to closest and 10 refers to the farthest to that attribute Affordability 1 2 3 4 5 6 7 8 9 10 Durability 1 2 3 4 5 6 7 8 9 10 Flexibility 1 2 3 4 5 6 7 8 9 10 Comfort 1 2 3 4 5 6 7 8 9 10 Style 1 2 3 4 5 6 7 8 9 10 Quality 1 2 3 4 5 6 7 8 9 10 Firm Grip 1 2 3 4 5 6 7 8 9 10 The second part required the respondents to compare two attributes and also two brands. A specimen question is given below Q. Rate the following pairs on a scale of 1-10 where I refer to absolute closeness and 10 refer to absolute dissimilarity. Affordable/ Durable 1 2 3 4 5 6 7 8 9 10 Durable/Quality 1 2 3 4 5 6 7 8 9 10

Filling up the questionnaire

A survey was then conducted with a sample size of 50 respondents in the campus with 25 males and 25 females.

Data entry into EXCEL and SPSS

After the questionnaires were filled the data was entered into EXCEL and SPSS for analysis. The respondents rating were averaged and then entered. In some places the average would arrive in decimals wherein we took the nearest decimal. The data was entered into a form of a matrix shown below



In the matrix above the comparison between one attribute to itself is shown by 1. Analyzing the data in SPSS

The data entered was then imported to SPSS for further analysis.

The SPSS analysis is explained in detail in the next section

SPSS analysis using Multidimensional Scaling Once the data has been entered in SPSS the next step was to analyze the data using Multidimensional Scaling. The whole process has been explained step-wise 1. Select ANALYZE tab and then select SCALE and select Multidimensional Scaling



2. On the selection of MDS from SCALE tab the output viewer opens up



Analysis of the Multidimensional Scaling Model

Object Points

In the above chart the points of the brands represents the positioning of the brands in the market and their closeness to the attributes as in how close are they to the attribute. It is evident from the chart that KHADIM is considered both “durable” and “affordable” because of its proximity towards both the attributes. While BATA is more of “affordable” and somewhat “flexible”. The international brands WOODLAND and FLOROCHEIM are in a different position in the market. WOODLAND is considered “comfortable” and “flexible”. While FLOROCHEIM can be attributed to “quality” because of its proximity to the point.

Positioning of our brand in the market

Looking at the chart above the positioning of our brand would be done at the space above because that refers to the area which is not covered by any brand in the market. The area is viewed below in the chart.



The positioning of our brand will be done in the area near to “style” “durability” and “quality”. This space in the market is uncovered by any other brands and this would be the ideal space to capture in the foot-wear market.

Positioning Theme of our Brand QUESTIONNAIRE

PART 1 Q. Rate the brand BATA on the basis of the following attributes where 1 refers to closest and 10 refers to the farthest to that attribute Affordability 1 2 3 4 5 6 7 8 9 10 Durability 1 2 3 4 5 6 7 8 9 10 Flexibility 1 2 3 4 5 6 7 8 9 10 Comfort 1 2 3 4 5 6 7 8 9 10 Style 1 2 3 4 5 6 7 8 9 10 Quality 1 2 3 4 5 6 7 8 9 10



Firm Grip 1 2 3 4 5 6 7 8 9 10 Q. Rate the brand KHADIM on the basis of the following attributes where 1 refers to closest and 10 refers to the farthest to that attribute Affordability 1 2 3 4 5 6 7 8 9 10 Durability 1 2 3 4 5 6 7 8 9 10 Flexibility 1 2 3 4 5 6 7 8 9 10 Comfort 1 2 3 4 5 6 7 8 9 10 Style 1 2 3 4 5 6 7 8 9 10 Quality 1 2 3 4 5 6 7 8 9 10 Firm Grip 1 2 3 4 5 6 7 8 9 10 Q. Rate the brand WOODLAND on the basis of the following attributes where 1 refers to closest and 10 refers to the farthest to that attribute Affordability 1 2 3 4 5 6 7 8 9 10 Durability 1 2 3 4 5 6 7 8 9 10 Flexibility 1 2 3 4 5 6 7 8 9 10 Comfort 1 2 3 4 5 6 7 8 9 10 Style 1 2 3 4 5 6 7 8 9 10 Quality 1 2 3 4 5 6 7 8 9 10 Firm Grip 1 2 3 4 5 6 7 8 9 10 Q. Rate the brand FLOROCHEIM on the basis of the following attributes where 1 refers to closest and 10 refers to the farthest to that attribute Affordability 1 2 3 4 5 6 7 8 9 10 Durability 1 2 3 4 5 6 7 8 9 10 Flexibility 1 2 3 4 5 6 7 8 9 10 Comfort 1 2 3 4 5 6 7 8 9 10 Style 1 2 3 4 5 6 7 8 9 10 Quality 1 2 3 4 5 6 7 8 9 10 Firm Grip 1 2 3 4 5 6 7 8 9 10

PART 2 Q. Fill in the table comparing two attributes with each other and with Brands on a scale of 1-10 where 1 refers to absolute similarity and 10 refers to absolute dissimilarity. Aff Flex Dur Qlty Styl Com Firm Bata Wdld Flor Khad Affordable 1 Flexibility 1 Durable 1



Quality 1 Stylish 1 Comfortable 1 Firm-grip 1 BATA 1 WOODLAND 1 FLOROSCHEIM 1 KHADIM 1

If we combine both of our analysis – Conjoint Analysis and MDS Analysis – we conclude the following attributes that should be featured in our prospective product:

• Price : Rs. 1500 • Branded • Long nose & High Heel – with some fashionable features • Durable • Quality • With Lace

conjoint ananlysis shoe industry

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