A Study on Service Quality in Unorganised Retailing

CHAPTER 1

INTRODUCTION

1.1 INDUSTRY-OVERVIEW

The retail industry is focused on the sale of goods or merchandise from a specific

location for direct consumption by the purchaser. North America is the home of most of the

world’s largest retailers, since the U.S. dominates the global retailing industry. Not only is the

retail industry responsible for two-thirds of the U.S.’s GDP, U.S. retail companies have also

established a presence on every continent. The largest retail giants globally are Wal-Mart

(USA), Metro AG (Germany), Carrefour (France) and Tesco (UK).

The industry employs a staggering number of people, and given its rapid proliferation,

this number is always on the rise. The backbone of the sector are the operations and supply

chain management jobs but there are various other options as well, from sales executives and

store managers to merchandise planners and buyers.

PERFORMANCE

In today’s dynamic and shaky business world, the retail industry is constantly

upgrading itself. With an endless array of customer choices, fierce competitors, pervasive use

of the internet, and a complex global economy, retailers need to focus on finding ways to

sustain and grow their businesses. Traditional growth models that focused on rolling out more

stores and adding more product lines, no longer enjoy the return on investment they once did.

Successful retailers are those who are able to adapt and change to the environment and

develop new ways of serving customers, respecting the dynamics of current trends and

adapting accordingly.

The retail industry in India is hailed as a sunrise sector, and is estimated to double in

value from US$ 330 billion in 2007 to $640 billion by 2015. In fact, India has topped AT

Kearney's annual Global Retail Development Index (GRDI) for the third year in a row as the

most attractive market for retail investment.

The bad news is, despite the fact that India has one of the largest numbers of retail

outlets in the World, organized retail accounts for only 4% of the total market. This makes it

especially difficult to apply sophisticated merchandising and sales tools, enhance consumer

interaction and also, make very accurate analysis. Analysts believe the sector is likely to

show significant growth of over 9 % per annum over the next 10 years and also see rapid

development in organized retail formats, with the proportion likely to reach a more

respectable 25% by 2018.

GROWTH POTENTIAL

The key growth areas include the urban, luxury segment on one end of the spectrum

and serving the rural sector on the other. In addition, government policy encouraging FDI in

the segment has resulted in a plethora of international retailers keen on entering the market;

American retail giant Wal-Mart has tied-up with Bharti Enterprises and global coffee giant

Starbucks' has tied up with PVR Limited. In addition, Carrefour, Boots and others are also

expected to come in. With so much action, it is natural that there is a huge scope for

employment opportunities, and experts estimate that the sector will generate employment for

2.5 million people in 2010. The top retail companies in India include the Raheja Group,

Reliance Retail, Tata Trent, Future Group, RPG Retail, and Ebony Retail Holdings.

FUTURE PROSPECTS

There are many opportunities for those seeking to enter this sector, and entry level

positions such as sales executives don’t even require a degree. Naturally, the higher order

jobs for graduates with relevant degrees and work experience, involve more responsibility,

challenges and remuneration. MBAs are increasingly being recruited, which marks a change

of HR policy, from the traditional preference to hire those from the FMCG and hospitality

sectors. In fact, senior executives in retail such as operations heads are extremely well looked

after, and HR consultants believe they are paid in excess of Rs. 60 lakhs.

The good news for graduates is that since the sector is so young and vibrant, career

growth happens very rapidly, and these positions are very achievable in a compressed time

period. Successful candidates across all levels are those who are dynamic, able to multi-task

and are equipped with great communication skills.

1.2 INDIAN RETAIL INDUSTRY

The India Retail Industry is the largest among all the industries, accounting for over

10 per cent of the country’s GDP and around 8 per cent of the employment. The Retail

Industry in India has come forth as one of the most dynamic and fast paced industries with

several players entering the market. But all of them have not yet tasted success because of the

heavy initial investments that are required to break even with other companies and compete

with them. The India Retail Industry is gradually inching its way towards becoming the next

boom industry.

The total concept and idea of shopping has undergone an attention drawing change in

terms of format and consumer buying behavior, ushering in a revolution in shopping in India.

Modern retailing has entered into the Retail market in India as is observed in the form of

bustling shopping centers, multi-storied malls and the huge complexes that offer shopping,

entertainment and food all under one roof.

A large young working population with medium age of 24 years, nuclear families in

urban areas, along with increasing working women population and emerging opportunities in

the services sector are going to be the key factors in the growth of the organized Retail sector

in India. The growth pattern in organized retailing and in the consumption made by the Indian

population will follow a rising graph helping the newer businessmen to enter the India Retail

Industry.

In India the vast middle class and its almost untapped retail industry are the key

attractive forces for global retail giants wanting to enter into newer markets, which in turn

will help the Indian Retail Industry to grow faster. Indian retail is expected to grow 25 per

cent annually. Modern retail in India could be worth US$ 175-200 billion by 2016.

The Food Retail Industry in India dominates the shopping basket. The Mobile phone

Retail Industry in India is already a US$ 16.7 billion business, growing at over 20 per cent

per year. The future of the Indian Retail Industry looks promising with the growth of the

market, with the government policies becoming more favorable and the emerging

technologies facilitating operations.

UNORGANIZED RETAIL SECTOR

India is the only one country having the highest shop density in the world, with 11

outlets per 1000 people (12 million retail shops for about 209 million households). Rather we

can see the democratic scenario in Indian Retail (because of low level of centralization, low

capital input and due to a good number of self organized retail). India started its Retail

Journey since ancient time.

In Ancient India there was a concept of weekly HAAT, where all the buyers & sellers

gather in a big market for bartering. It takes a pretty long times to & step to shape the modern

retail. In between these two concepts (i.e. between ancient retail concept & the modern one

there exist modern kirana/ mom and pop shops or Baniya ki Dukan.

The Indian retail industry is divided into two sectors- organized and unorganized.

Organized retail sector refers to the sectors undertaken by licensed retailers, that is,

those who are registered for sales tax, income tax, etc. These include the corporate retail

formats of the exclusive brand outlets, hypermarkets, supermarkets, departmental stores and

shopping malls.

Unorganized retailing, on the other hand, refers to the traditional formats of low-cost

retailing, for example, hand cart and pavement vendors, & mobile vendors, the local kirana

shops, owner manned general stores, paan/beedi shops, convenience stores, hardware shop at

the corner of your street selling everything from bathroom fittings to paints and small

construction tools; or the slightly more organized medical store and a host of other small

retail businesses in apparel, electronics, food etc.

CHARACTERISTICS OF UNORGANIZED RETAIL

Small-store (kirana) retailing has been one of the easiest ways to generate self-

employment, as it requires limited investment in land, capital and labor. It is generally family

run business, lack of standardization and the retailers who are running this store they are

lacking of education, experience and exposure. This is one of the reasons why productivity of

this sector is approximately 4% that of the U.S. retail industry.

Unorganized retail sector is still predominating over organized sector in India,

unorganized retail sector constituting 98% (twelve million) of total trade, while organized

trade accounts only for 2%. The reasons might be

1. In smaller towns and urban areas, there are many families who are traditionally using these

kirana shops/ 'mom and pop' stores offering a wide range of merchandise mix. Generally

these kirana shops are the family business of these small retailers which they are running for

more than one generation.

2. These kirana shops are having their own efficient management system and with this they

are efficiently fulfilling the needs of the customer. This is one of the good reasons why the

customer doesn’t want to change their old loyal kirana shop.

3. A large number of working class in India is working on daily wage basis, at the end of the

day when they get their wage, they come to this small retail shop to purchase wheat flour,

rice etc for their supper. For them this the only place to have those food items because

purchase quantity is so small that no big retail store would entertain this.

4. Similarly there is another consumer class who are the seasonal worker. During their

unemployment period they use to purchase from this kirana store in credit and when they get

their salary they clear their dues. This type of credit facility is not available in corporate retail

store, so this kirana stores are the only place for them to fulfill their needs.

5. Another reason might be the proximity of the store. It is the convenience store for the

customer. In every corner of the street an unorganized retail shop can be found that is hardly

a walking distance from the customer’s house. Many times customers prefer to shop from the

nearby kirana shop rather than to drive a long distance organized retail stores.

6. This unorganized stores are having n number of options to cut their costs. They incur little

to nil real-estate costs because they generally operate from their residences.

Their labour cost is also low because the family members work in the store. Also they

use cheap child labour at very low rates.As they are operating from their home so they can

pay for their utilities at residential rates. Even they cannot pay their tax properly.

Currently the value of the retail market is estimated at around $ 270 billion with a

growth rate of 5.7 per cent per annum according to the Indian retail report which creates a big

threat for the small unorganized retailers.

The well established organized retail sector in India are Pantaloon Retail, Shoppers’

Stop, Spencers, HyperCITY, Lifestyle, Subhiksha & newly emerging Reliance etc. Over

20,000 new retail outlets are expected to open within this segment. Major corporate retail like

Wal-Mart and have started to try and take over the Indian retail sector.

But in India the unorganized retail is a source which fulfills foods and other

necessities of millions of Indians. Not only that it is also act like a convenience store for the

customer offering right product at right time at right place. In a country with large numbers of

people, and high levels of poverty, this model of retail democracy is the most appropriate

one.So these unorganized retail sector need to be promoted so that they can organize &

supply food to Indian consumer.

1.3 COMPANY PROFILE

EFARM PRIVATE LIMITED

One of the key problems for Indian

farmers is the marketing of their produce

to end consumers. It often goes through

several middlemen, in very inefficient manner, which contributes to over 40% of wastage.

Also, most farmers being less educated, lack proper planning and market inputs to properly

plan their cultivation. Often the decision on what to grow, when to harvest are all based on

adhoc decisions rather than well planned approach.

The end consumers are often hit by huge variations in prices and quality and

availability, that food security is one of the biggest problems facing our nation today. Though

several modern retailers have been operational for over a decade, owing to a combination of

factors such as high operational costs, localized presence in metros, and low margins have

forced even many large chains to shut operations.

There is hence a critical need for an efficient, low cost agri supply chain mechanism to

connect farmers with the end markets.

E-Farm is a young social enterprise firm based in Chennai. EFarm is India's first end-

to-end agri supply chain platform, providing a combination of technology solutions and on-

ground distribution mechanism to enable farmers reach end markets in an effective

manner.EFarm ties in farmers, intermediaries, logistics providers, distributors, small time

retailers, all the way up to your local road side vendor into a single chain backed up best of

breed information systems to deliver fresh, clean, low priced farm produce.In simple words

we are a ’hi-tech' subjiwallah' - connecting farmers, business consumers and intermediaries

(such as transport operators, storage providers etc) using a more organized supply chain

mechanism.

The key benefits for each segment are:

For Farmers For Buyers For Intermediaries

Wider Market Reach

Procure all grades/varieties

Better prices

Accurate Weights

Market demand data

Lower/Stable prices

Consistent quality

Accurate weights

Timely delivery

IT/MIS support

Planned capacity utilization

Linkages to supply and markets

Income from value addition

Consistent demand

EFARM's solution takes a more holistic approach, addressing the key needs and pain

points of all stakeholders in the agri supply chain - farmers, transporters, and intermediaries

end consumers - to evolve a sustainable, transparent and efficient new distribution

mechanism. It operates in the B2B space and serves bulk consumers of agri produce such as

hotels, caterers, retail chains, food processing industries and vegetable vendors, and also runs

a retail outlet for the Indian army.

EFarm’s solution is based on following key strategies:

Develop a IT based backbone for data gathering, analysis ,planning and monitoring the

entire operation

Setup low cost collection centre’s close to villages in partnership with farmers for

organized collection and grading

Setup distribution centre’s in metros , close to customer location , for final delivery

Train intermediaries like transport operators in proper handling of perishables to reduce

transit wastage

Map the demand and supply and ensure just in time distribution

EFarm is currently operational in Chennai and sources from over 1500 farmers in

surrounding areas of Tamilnadu.

VISION

To be India's first fully integrated agri supply chain platform by 2015

MISSION

Build a professional agri supply chain network, adopting innovative technologies and

indigenous processes, through a collaborative and inclusive business model, thus creating

a viable solution for India's agriculture crisis.

OWNER

1. Venkat Subramanian, Founder / COO

Venkat oversees the strategy, operations and technology areas of EFarm. He also likes to

teach, write and mentor students. Venky did his under graduation from IIT, Kharagpur in

B.Arch and his Master in Computer Science from University at Albany, NY. Prior to starting

EFarm, he has held techno-commercial roles for various IT firms across the globe.

2. Srivalli Krishnan, Co-Founder / CEO

Srivalli, (code named ‘Valli-The Boss’), heads Sales & Marketing, Finance and Customer

Relationship. She is passionate about social ventures, women’s SHGs and creating

employment for differently abled and under privileged. She is an internet-junkie and when

not working at EFarm, can often be found at facebook’s Farmville .Srivalli did her MBA

from ICFAI and B.Com from Bangalore University. Prior to EFarm, she had worked for over

8 years in leading MNCs such as Accenture, TATA AIG, ICICI Bank; she has run two start-

ups and organized fund raising for NGOs as part of CSR programs.

KEY PRODUCT/SERVICES

Vegetables

Fruits

Exotics / Organic Produce Processed Items (peeled , cut vegetables)Compost

Non perishable Commodities (future)

Marketing

Distribution Technology

Training

Support services.

BUSINESS MODEL

Technology

1. Cost of production calculator

2. Agri SCM

3. Billing & Accounting & Inventory Management (MS accounting)

4. demand/supply simulation (SCM)

5. POS solution - in Tamil

6. Digital image recognition for agri produce

OPERATIONS

Planning

1. Identify supply regions around key metro area

2. Identify farmers groups and clusters

3. Gather farmers cultivation data

4. Gather customers demand requirements

5. Match demand and supply and plan for procurement

6. Setup collection centre’s in procurement areas and train local villagers in key tasks

7. Setup distribution centre’s within key metro areas and train staff for local distribution

Daily operations

1. Aggregate each day's orders requirements

2. Procure from collection centre’s based on demand

3. Sort/Grade produce into broad categories

4. Transport from collection centre to distribution centre(at metro) through truck

5. Unload and check quality of arrivals

6. Weigh and bag as per customer specifications

7. Transport to customer premises through local distribution vehicles

8. Gather customer feedback and record issues if any.

ORGANIZATIONAL SETUP

COMPETITORS

Reliance fresh.

Palamuthirsolai.

MAJOR CUSTOMERS

Food court

in Express

Avenue.

Nutri7 restaurant.

Nawab restaurant.

Taj flight services.

Sangeetha SVR leading restaurant chain.

Oberoi flight & kitchen services.

Sky gourmet flight services

EFARM PVT LTD

Mr. Venkat Subramanian

(COO/Founder)

Mrs. Srivalli Krishnan

(CEO/Co-Founder)

Mr. Rajendran

(Business Development)

MS. Veena

HR

Ms. Preethi

Finance

Mr. Baskar Operation

Mr. Sameul IT Department

Mr. Sashanka Marketing

.. And several local

.. And several local

INTRODUCTION TO K2J (KISSAN 2 JAWAN )

About K2J (KISSAN 2 JAWAN )

eFarm launches retail outlet to serve Indian Army

eFarm launches retail outlet to serve Indian Army

eFarm has been invited by the South Zone Army HQ located at Chennai to setup and

run a vegetables & fruits outlet for the jawans of ATNK&K regiments (that's andra,

tamilnadu, karnataka & kerala). Well, though we technically dont get into retail side,

but the command coming from none less than a Major General , we had to gladly

oblige.

KEY PRODUCT/SERVICES:

Vegetables

Fruits

Exotics / Organic Produce Processed Items (peeled , cut vegetables)Compost

Non perishable Commodities (future)

CHAPTER 2

CONCEPTS & REVIEWS

2.1 OVERVIEW OF THE STUDY

Retail is the fastest growing sector in Indian economy with a compounded annual growth

rate of 46.4 percent for the past three years. Traditional retail outlets are paving way to newer

formats like supermarkets, specialty store and Hypermarkets. In India, the organized retailers

are entering the grocery market at a rapid rate and posing a threat to the livelihood of Kirana

shop owners. It is important to find out how a retailer is represented in the minds of the

consumer and what differentiates one retail experience from another. It is also important to

analyze whether a retail business meets the customer needs and expectations which can be

measured by assessing the retail service quality. The managerial implications of the present

study will thus help unorganized retailer to frame effective marketing strategies to face the

competition.

2.2 REVIEW OF LITERATURE

Boshoff and Terblanche (1997) tried to test the reliability and validity of RSQS in South

African retail setting that the instrument was a valid and reliable one. Mehta, Lalwani and

Han (2000) on testing the reliability of the scale in retail environments in Singapore found the

scale reliable. Siu and Cheung (2001) tested the applicability of RSQS in a department store

chain in HongKong and found that reliability dimension did not factor out and felt that RSQS

can be applied with some modifications. Kim and Jin (2002) tested the validity of RSQS in

discount stores for US and Korean customers. They found the dimension Policy to be

unreliable in both the countries and a new dimension called Personal Attention factored out.

Siu and Chow (2003) by using the adapted version of Siu and Cheung (2001) examined the

service quality of a Japanese Supermarket in HongKong. The original dimension of problem

solving areas integrated with Personal interaction and a new factor emerged in the study,

which was named as Trustworthiness. Kaul (2007) tested the applicability of RSQS in Indian

specialty apparel store context and found RSQS not valid and suggested future research to

develop a modified scale for the Indian context.

Since only a limited number of studies have been attempted to measure service have been

attempted to measure service quality in retail settings, there is a significant gap in the

literature in this area of research. No study has been made to measure Retail Service Quality

in an unorganized retail setting. The present study addresses the gap by studying the

applicability of RSQS in TamilNadu among the customers who shop in unorganized retail

store.

CHAPTER 3

MAIN THEME OF THE PROJECT

3.1 NEED OF THE STUDY

In India, the organized retailers are entering the grocery market at a rapid rate and

posing a threat to the livelihood of Kirana shop-owners. The Indian customers are highly

price sensitive which forces the market players to operate on razor thin margins. It is

important to find out how a retailer is represented in the minds of the consumer and what

differentiates one retail experience from another. It is also important to analyze whether a

retail business meets the customer needs and expectations which can be measured by

assessing the retail service quality in unorganized retail outlets.

3.2 OBJECTIVE OF THE STUDY

1. To identify the service quality factors in unorganized retail outlets.

2. To analyze the customers’ expectation and perception on various service quality

factors in unorganized retail outlets.

3. To identify the retail service quality in unorganized retail outlets.

3.3 LIMITATIONS OF THE STUDY

1. The errors and bias of the data analysis due to the influence of non-respondents to the

questions is unavoidable

2. Biases in responses could also be due to the presence of the researcher.

3. Hesitations on the part of respondents to express their views exactly on the

questionnaire.

4. The study expresses the opinion of customers, which changes periodically.

5. The tools used to analyze the data are subject to their own assumptions and drawbacks

3.4 CONCEPTUAL FRAMEWORK

3.4.1. SERVICE QUALITY

Although several definitions have been proposed for service quality the one described

by Parasuram et al. (1985) has gained importance. Service quality perceptions result from the

comparison of consumer expectation with actual service performance. Quality evaluations are

not made solely on the outcome of the process of service delivery.

Later Parasuraman et al. (1988) defined service quality as conformance of customer

specifications since it is the customers who define quality and not management. The authors

also defined perceived service quality as the judgment of the customers about an entity’s

overall excellence or superiority. They also added that perceived quality is only a form of

attitude which is related to satisfaction and results from a comparison made between

expectations and perceptions of performance and it differs from objective quality.

3.4.2 SERVQUAL

SERVQUAL is the most widely used scale foe measuring service quality. Initially,

Parasuram et al. (1985) developed the SERVQUAL as a standardized measurement scale of

service quality based on the gap analysis. It is operationalised as Q=P-E, where Q=service

Quality, P=customer’s perception of service and E=customer’s service expectation. It was a

landmark contribution in the field of service quality.

3.4.3 RETAIL SERVICE QUALITY SCALE

On studying the characteristics of store retailing Finn and Lamb (1991), Gaglino and

Hathcote (1994) found that parameters that define service quality in retail setting differs from

other pure services. Thus measures were developed for measuring service quality in pure

service set ups may not be suitable to retail store context.

Realizing the need for developing a scale to measure retail service quality, Dabholkar

et al. (1996) made extensive research to develop the Retail Service Quality Scale. In the

process they were able to identify five dimensions that were central to service quality in retail

settings viz., physical aspects, reliability, personal interaction, problem solving and policy.

Though these five dimensions were distinct they were highly correlated. Physical aspects

dimension included the appearance of the physical facilities as well as the convenience of

store layout and public areas. Reliability dimension is concerned with the store’s ability to

keep promises and do things right. The personal interaction dimension is concerned with

whether or not the store has courteous and helpful employees who inspire confidence and

trust. Problem solving dimension includes assessing the store’s performance on the basis of

its ability to handle potential problems. Policy dimension included aspects like high quality

merchandise, convenient parking, convenient store hours, acceptance of major credit cards

and availability of a store credit card.

The RSQ scale proposed by Dabholkar et al. included 28 items, 17 of which came

from the SERVQUAL scale developed by Parasuram, Zeithmal and Berry (1988) and the

remaining 11 items from the researchers’ review of literature and qualitative research. After

testing the RSQ scale with the customers of a US Department store, the authors found that the

scale was suitable for studying retail businesses that offered a mix of services and goods.

Retailers can use this instrument as a diagnostic tool to determine service areas that are weak

and needed attention. The authors suggested that replicate studies can be conducted for other

retailers offering a mix of services and goods as an extension of their research.

CHAPTER 4

RESEARCH METHODOLOGY

The study was confined to only part of city which is Chennai. Since the study is

focused on unorganized outlets only Kirana store named K2J(Kissan to Jawan) has been

selected. Hence the customer who had a shopping experience in the store has been included

for the study.

The respondents were given questionnaire after their shopping in the store. The

convience sampling method has been applied. 100 customers were selected for the survey.

Out of 100 customers only 70 customers responded the questionnaire at the reusable level.

The required data have been collected with the help of a pre-structured interview

questionnaire. It was ensured that the customers have shopped at least twice in the retail

outlet before responding to the survey.

The questionnaire included statements of the customer expectation and perception

about retail service quality factors of the store. 21 statements related to retail service quality

factors were listed and the customers are requested to rate these statements on a five point

scale depending on their level of agreement to these statements. After the data collection

appropriate statistical tools were applied for processing the data.

4.1 RESEARCH DESIGN

The research design adopted in this research is “Descriptive Research Design”.

4.2 SAMPLE SIZE

The sample size taken for the study is 100 out of which only 70 respondents

responded to the questionnaire. The samples were selected on a random basis.

4.3 DATA COLLECTION

The required data have been collected with the help of a pre-structured questionnaire .

Primary Data is collected with the help of questionnaire. This data gives the conclusion about

the topic. Secondary data is also used from research work carried out in the past.

4.4 TOOLS FOR ANALYSIS

The tools used for analysis and interpretation of the data are

PERCENTAGE METHOD

In this project Percentage method test was used. The percentage method is used to know

the accurate percentages of the data we took, it is easy to graph out through the percentages.

The following are the formula

CHI-SQUARE ANALYSIS

In this project chi-square test was used. This is an analysis of technique which analyzed

the stated data in the project. It analysis the assumed data and calculated in the study. The Chi-

square test is an important test amongst the several tests of significant developed by statistical.

Chi-square, symbolically written as x2 (Pronounce as Ki-Spare), is a statistical measure used in

the context of sampling analysis for comparing a variance to a theoretical variance.

ONE WAY ANNOVA

The One-Way ANOVA compares the mean of one or more groups based on one

independent variable (or factor).

FACTOR ANALYSIS

Factor analysis is a statistical method used to describe variability among observed,

correlated variables in terms of a potentially lower number of unobserved, uncorrelated

variables called factors.

http://en.wikipedia.org/wiki/Variable_(mathematics)

http://en.wikipedia.org/wiki/Variance

http://en.wikipedia.org/wiki/Statistics

CHAPTER 5

ANALYSIS AND INTERPRETATION

PERCENTAGE ANALYSIS FOR DEMOGRAPHIC PROFILE OF CUSTOMERS

TABLE-1 GENDER DISTRIBUTION OF CUSTOMERS

GENDER NO.OF.RESPONDENTS

Male 33

Female 37

FIGURE 5.1- GENDER DISTRIBUTION OF CUSTOMERS

47%

53%

%.OF.RESPONDENTS

MaleFemale

Inference:

From the above pie chart it can be analysed that 33 respondents are male and 37 respondents

are female

TABLE-2 AGE DISTRIBUTION OF CUSTOMERS

Age Total

Below 10 0

10-20 yrs 5

20-30 yrs 25

30-40 yrs 16

40-50 yrs 16

50 Above 8

FIGURE 5.2 - AGE DISTRIBUTION OF CUSTOMERS

10-20 yrs 20-30 yrs 30-40 yrs 40-50 yrs 50 Above0

5

10

15

20

25

30

Age

Inference:

The majority of the respondent is from the age group between 20-30yrs

TABLE-3 EDUCATIONAL QUALIFICATION OF CUSTOMERS

Education Qualification Total

PG 30

UG 18

School level 16

Uneducated 6

FIGURE 5.3 - EDUCATIONAL QUALIFICATION OF CUSTOMERS

PG UG School level Uneducated0

5

10

15

20

25

30

35

Educational qualification

Inference:

The majority of the respondents are PG graduates

TABLE-4 OCCUPATION OF CUSTOMERS

Occupation Total

Student 12

Professional 26

Business 13

Housewife 19

FIGURE 5.4 - OCCUPATION OF CUSTOMERS

Student Professional Business Housewife0

5

10

15

20

25

30

OCCUPATION

Inference:

The majority of the respondents’ occupation is professionals and housewife

TABLE-5 INCOME DISTRIBUTION OF CUSTOMERS

Income Total

Below 10k 17

10k - 20k 21

20k - 30k 15

Above 30k 17

FIGURE 5.5 - INCOME DISTRIBUTION OF CUSTOMERS

Below 10k 10k - 20k 20k - 30k Above 30k0

5

10

15

20

25

Income

Inference:

It is inferred that the majority of respondents monthly income ranges

from 10-20k

TABLE-6 MARITAL STATUS OF CUSTOMERS

FIGURE 5.6 - MARITAL STATUS OF CUSTOMERS

Marital Status

SingleMarried

Inference:

It is inferred that the majority of the respondents are married

Marital Status Total

Single 16

Married 54

TABLE-7 FAMILY SIZE OF THE CUSTOMERS

Family Size Total

2 0

3 17

4 34

Above 4 19

FIGURE 5.7 - FAMILY SIZE OF THE CUSTOMERS

2 3 4 Above 405

10152025303540

Family Size

Inference:

The majority of the respondents family size is 4 in number

TABLE-8 FREQUENCY OF BUYING

Frequent Buying Total

Daily 14

weekly 30

Monthly 26

FIGURE 5.8 - FREQUENCY OF BUYING

Daily weekly Monthly0

5

10

15

20

25

30

35

Frequency of Buying

Inference:

Majority of respondents by weekly followed by monthly

TABLE-9 AVERAGE AMOUNT SPENT BY THE CUSTOMERS ON EACH

PURCHASE

Purchase Amount Total

Below 100 Rs 14

100 - 500 Rs 28

500 Rs & Above 28

FIGURE 5.9 - PURCHASE AMOUNT

Below 100 Rs 100 - 500 Rs 500 Rs & Above0

5

10

15

20

25

30

Purchase Amount

Total

Axis Title

Axis Title

Inference:

The purchase amount of majority of respondents is in the range of 100-500 and 500 above

TABLE-10 NUMBER OF YEARS A CUSTOMER BEING A CUSTOMER TO A

PARTICULAR SHOP

No of yrs Purchasing Total

less than 6 mths 3

6mths - 1 year 15

1 - 2 Year 9

More than 2 Yrs 43

FIGURE 5.10 - NUMBER OF YEARS A CUSTOMER BEING A CUSTOMER TO A

PARTICULAR SHOP

less than 6 mths 6mths - 1 year 1 - 2 Year More than 2 Yrs05

101520253035404550

Total

Inference:

The majority of the respondents are loyal for more than 2years

5.1 FACTOR ANALYSIS

KMO and Bartlett’s Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .511

Approx. Chi-Square 347.598

Bartlett's Test of Sphericity Df 210

Sig .000

KMO and Bartlett’s test for the data collected from 70 respondents are shown in the

above table. The KMO Measure of Sampling Adequacy indicates whether Factor Analysis is

suitable for the collected data. If the value is greater than 0.5, it indicates that factor analysis

is suitable for the data.

INTERPRETATION

From the above table of KMO and Bartlett’s test, it can be inferred that Factor

Analysis is suitable for the data. KMO measure of Sampling Adequacy is 0.511 which is

greater than 0.5 indicates that Factor Analysis can be applied to the data.

TOTAL VARIANCE EXPLAINED

Com

pone

nt

Initial EigenvaluesExtraction Sums of Squared

Loadings

Rotation Sums of Squared

Loadings

Total% of

Variance

Cumulativ

e %Total

% of

Variance

Cumulative

%Total

% of

VarianceCumulative %

1 3.415 16.260 16.260 3.415 16.260 16.260 3.206 15.265 15.265

2 2.043 9.727 25.987 2.043 9.727 25.987 1.949 9.283 24.548

3 1.823 8.682 34.669 1.823 8.682 34.669 1.881 8.958 33.507

4 1.652 7.867 42.535 1.652 7.867 42.535 1.807 8.606 42.113

5 1.540 7.333 49.869 1.540 7.333 49.869 1.629 7.756 49.869

6 1.282 6.104 55.972

7 1.222 5.818 61.790

8 1.181 5.622 67.413

9 .892 4.248 71.661

10 .820 3.905 75.566

11 .759 3.616 79.182

12 .690 3.287 82.469

13 .643 3.064 85.533

14 .615 2.927 88.460

15 .552 2.630 91.090

16 .452 2.151 93.241

17 .395 1.882 95.123

18 .338 1.607 96.730

19 .283 1.350 98.080

20 .231 1.100 99.180

21 .172 .820 100.000

Extraction Method: Principal Component Analysis.

ROTATED COMPONENT MATRIX

Component

1 2 3 4 5

V1 .705 -.054 -.038 .119 -.048

V5 .698 -.093 -.101 .131 -.178

V21 .631 -.092 -.164 -.176 .082

V13 .514 -.207 -.035 .051 .346

V20 .497 -.234 .343 .208 -.408

V8 .469 .141 -.103 -.013 .116

V9 .458 .228 .385 -.042 .040

V14 .363 .272 .115 .009 .143

V11 -.001 .685 .035 .259 .330

V18 -.046 .570 .251 -.068 -.155

V17 -.257 .563 .092 .021 -.259

V2 -.241 -.512 .336 .361 .040

V6 -.210 -.102 .690 -.110 -.155

V4 -.076 -.239 -.654 .096 -.160

V7 -.447 .163 .551 .093 .075

V3 -.039 -.046 .192 -.790 .107

V15 .224 -.156 -.016 .661 .133

V19 .423 -.259 -.069 -.555 .073

V12 .230 -.022 -.084 -.098 .692

V16 .299 .304 -.172 -.058 -.588

V10 .045 .182 .282 .289 .388

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 8 iterations.

Rotated component matrix table shows the different variables to be grouped under a

factor. The variables which have values greater than 0.5 (irrespective of the sign) should be

grouped under one factor.

INTERPRETATION

The above table shows that the variables are grouped under 5 factors and have been

listed as follows.

Factor 1-Variables 1, 5, 21, 13, 20

Factor 2-variables 11, 8, 17, 2

Factor 3-Variables 6, 4, 7

Factor 4-Variables 3, 15, 19

Factor 5-Variables 12, 16

TITLES OF THE FACTORS

Factor 1-Physical aspects and cost

Factor 2-Product availability and variety

Factor 3-Convenience and clarity

Factor 4-Quality of product

Factor 5-Responsiveness

ANALYSIS OF VARIANCE (ONE-WAY ANOVA)

ANOVA FOR PHYSICAL ASPECTS AND COST

Sum of

SquaresDf Mean Square F Sig.

GENDER Between Groups 3.432 13 .264 1.055 .415

Within Groups 14.011 56 .250

Total 17.443 69

AGE

Between Groups 16.452 13 1.266 .927 .532

Within Groups 76.420 56 1.365

Total 92.871 69

EDUCATION

QUALIFICATI

ON

Between Groups 10.264 13 .790 .741 .716


Total 69.943 69

OCCUPATION

Between Groups 14.835 13 1.141 .992 .471


Total 79.271 69

INCOME

Between Groups 14.194 13 1.092 .859 .598


Total 85.371 69

MARITAL

STATUS

Between Groups 2.123 13 .163 .895 .563


Total 12.343 69

FAMILY SIZE

Between Groups 3.893 13 .299 .523 .901


Total 35.943 69

FREQUENCY

OF BUYING

Between Groups 5.799 13 .446 .777 .680


Total 37.943 69

PURCHASE

AMOUNT

Between Groups 9.139 13 .703 1.310 .235


Total 39.200 69

NO. OF

YEARS

Between Groups 12.192 13 .938 1.032 .435


(CUSTOMER

LOYALTY)

Total 63.086 69

The table shows the significant value of all the demographic variables. The significant value

can be used to know whether the demographic variables influence the factors. If the

significant value is less than 0.05, it means that the demographic variable influences the

factor.

INTERPRETATION

The above table shows the significant values of the demographic variable with regard

to the first factor. All the significant values are greater than 0.05 which indicates that the

demographic variables do not influence the physical aspects of the store and cost (First

Factor).

ANOVA FOR PRODUCT AVAILABILITY AND VARIETY

Sum of


GENDER Between Groups 2.004 6 .334 1.363 .244


Total 17.443 69

AGE

Between Groups 5.480 6 .913 .658 .683


Total 92.871 69

EDUCATIONA

L

QUALIFICATI

ON

Between Groups 4.495 6 .749 .721 .634


Total 69.943 69

OCCUPATION

Between Groups 8.062 6 1.344 1.189 .324


Total 79.271 69

INCOME

Between Groups 9.547 6 1.591 1.322 .261


Total 85.371 69

MARITAL

STATUS

Between Groups .706 6 .118 .637 .700


Total 12.343 69

FAMILY SIZE

Between Groups .733 6 .122 .218 .970


Total 35.943 69

FREQUENCY

OF BUYING

Between Groups 3.169 6 .528 .957 .462


Total 37.943 69

PURCHASE

AMOUNT

Between Groups 7.045 6 1.174 2.301 .045


Total 39.200 69

NO. OF YEARS Between Groups 5.696 6 .949 1.042 .407

(CUSTOMER

LOYALTY)


Total 63.086 69




factor.

INTERPRETATION


to the second factor. All the significant values are not greater than 0.05. The significant value

for the demographic variable Purchase amount is 0.045 which is less than 0.05. This indicates

that the amount spent by the customers on purchase influence the availability and variety of

products offered by the retailer (Second Factor).

ANOVA FOR CLARITY AND CONVENIECE

Sum of


GENDER

Between Groups 2.879 6 .480 2.076 .069


Total 17.443 69

AGE

Between Groups 6.542 6 1.090 .796 .577


Total 92.871 69

EDUCATION

QUALIFICATI

ON

Between Groups 4.106 6 .684 .655 .686


Total 69.943 69

OCCUPATION

Between Groups 2.097 6 .349 .285 .942


Total 79.271 69

INCOME

Between Groups 9.892 6 1.649 1.376 .238


Total 85.371 69

MARITAL

STATUS

Between Groups 1.627 6 .271 1.595 .163


Total 12.343 69

FAMILY SIZE

Between Groups 2.330 6 .388 .728 .629


Total 35.943 69

FREQUENCY

OF BUYING

Between Groups 4.422 6 .737 1.385 .234


Total 37.943 69

PURCHASE

AMOUNT

Between Groups 2.068 6 .345 .585 .741


Total 39.200 69

NO.OF YEARS

(CUSTOMER

Between Groups 7.163 6 1.194 1.345 .251


LOYALTY)Total 63.086 69




factor.

INTERPRETATION


to the third factor. All the significant values are greater than 0.05 which indicates that the

demographic variables do not influence the clarity in billing and the convenience (Third

Factor).

ANOVA FOR QUALITY OF PRODUCT AND STAFF RESPONSE

Sum of


GENDER Between Groups .125 4 .031 .117 .976


Total 17.443 69

AGE

Between Groups 2.041 4 .510 .365 .833


Total 92.871 69

EDUCATION

QUALIFICATI

ON

Between Groups 1.388 4 .347 .329 .857


Total 69.943 69

OCCUPATION

Between Groups 3.759 4 .940 .809 .524


Total 79.271 69

INCOME

Between Groups .162 4 .040 .031 .998


Total 85.371 69

MARITAL

STATUS

Between Groups 1.102 4 .275 1.593 .187


Total 12.343 69

FAMILY SIZE

Between Groups 1.104 4 .276 .515 .725


Total 35.943 69

FREQUENCY

OF BUYING

Between Groups 1.458 4 .365 .649 .629


Total 37.943 69

PURCHASE

AMOUNT

Between Groups 1.574 4 .394 .680 .608


Total 39.200 69

NO.OF YEARS

(CUSTOMER

Between Groups 5.734 4 1.434 1.625 .179


LOYALTY)Total 63.086 69




factor.

INTERPRETATION


to the fourth factor. All the significant values are greater than 0.05 which indicates that the

demographic variables do not influence the quality of the product and the response provided

by the staff to the customers (Fourth Factor).

The table shows the significant value of all the demographic variables. The significant

value can be used to know whether the demographic variables influence the factors. If the


factor.

ANOVA FOR RESPONSIVENESS

Sum of

Squaresdf Mean Square F Sig.

GENDER Between .720 5 .144 .551 .737

Groups


Total 17.443 69

AGE

Between

Groups4.574 5 .915 .663 .653


Total 92.871 69

EDUCATIONAL

QUALIFICATION

Between

Groups1.495 5 .299 .280 .923


Total 69.943 69

OCCUPATION

Between

Groups2.771 5 .554 .464 .802


Total 79.271 69

INCOME

Between

Groups4.870 5 .974 .774 .572


Total 85.371 69

MARITAL

STATUS

Between

Groups.736 5 .147 .811 .546


Total 12.343 69

FAMILY SIZE

Between

Groups2.691 5 .538 1.036 .404


Total 35.943 69

FREQUENCY OF

BUYING

Between

Groups4.169 5 .834 1.580 .178


Total 37.943 69

PURCHASE

AMOUNT

Between

Groups

4.152 5 .830 1.517 .197


Total 39.200 69

NO.OF YEARS

(CUSTOMER

LOYALTY)

Between

Groups3.028 5 .606 .645 .666


Total 63.086 69

INTERPRETATION


to the fifth factor. All the significant values are greater than 0.05 which indicates that the

demographic variables do not influence responsiveness of the retailer (Fifth Factor).

CHI-SQUARE

Chi-square table comparing Physical aspects and cost, Product availability and variety,

Convenience and clarity, Quality of product and Responsiveness

H0=there is no relation between staff competency and service timeHa= there is observable relation between staff competency and service time

FACTORS F1 F2 F3 F4 F5

F1 - .067 .005 .021 .012

F2 .067 - .460 .150 .061

F3 .005 .460 - .841 .190

F4 .021 .150 .841 - .029

F5 .012 .061 .190 .029 -

INTERPRETATION

The chi-square analysis between the factors is as follows.

Factor 1-PHYSICAL ASPECTS AND COST

Physical aspects and cost (F1) has a significant association with Clarity in billing and

convenience to the customers (F3),Quality of product and Staff response (F4).and

Responsiveness (F5). And no significant association between Product availability and variety

(F2)

Factor 2-PRODUCT AVAILABILITY AND VARIETY

Product availability and variety(F2) has a significant association with Clarity in

billing and convenience to the customers (F3), Quality of product and Staff response (F4).and

Responsiveness (F5). And no significant association between Physical aspects and cost (F1)

Factor 3-CLARITY AND CONVENIENCE

Clarity in billing and convenience(F3) has a significant association with Physical

aspects and cost (F1), Product availability and variety (F2) .and Responsiveness (F5). And no

significant association between Quality of product and Staff response (F4)

Factor 4- QUALITY OF PRODUCT AND STAFF RESPONSE

Quality of product and staff response(F4) has a significant association with Physical

aspects and cost (F1), Product availability and variety(F2) and Responsiveness (F5). And no

significant association between convenience (F3)

Factor 5- RESPONSIVENESS

Responsiveness(F5) has a significant association with Physical aspects and cost (F1)

Clarity in billing and convenience to the customers (F3),Quality of product and Staff

response (F4). And no significant association between Product availability and variety(F2).

CHAPTER 6

6.1 FINDINGS

The important retail service quality factors identified by customers in unorganized outlet

are Store Merchandise, Access, Personal Interaction, problem Solving, Policy and

Physical Aspects.

The most important retail service quality factors are Store Merchandise and Access. In

unorganized retail outlet customer’s expectations are higher than customer’s perception in

case of store merchandise, Policy, Problem Solving and physical Aspects which confirm

that there is a service quality gap in unorganized retail outlets. Only in case of Access and

Personal Interaction the customer’s perception is greater than customer’s expectation.

The present study has identified store merchandise and Access as a new factor of RSQ in

unorganized outlet.

Identifying the RSQ factors in unorganized outlets is the first of its kind study in the

research in retailing.

The retail service quality is identified in factors like Store merchandise, Policy, Problem

Solving, Personal interaction and Access.

6.2 SUGGESTIONS

Retail sector in India is facing an intense competition in the present scenario. For retail

outlets that aim to develop a competitive advantage, the measurement of retail service

quality scale is imperative and is considered as an important marketing tool.

The present study reveals that customers were not satisfied with the factors like Store

merchandise, Policy, Problem Solving and Physical Aspects in case of unorganized

outlets.

This indicates that the retailer should take necessary steps to improve the quality and

variety of Store Merchandise. Although location might be an advantage of Kirana store,

this cannot be long-lived.

At any moment the big-box retailers can foray into the residential areas where these

Kiranas operate, with counterfeiting strategies. So there is a need for the Kirana store to

upgrade themselves and bring changes in their operations.

The Kirana store can modernize their outlets by bringing changes like cleanliness,

attractive arrangements of merchandise. They can give a different experience to

customers by allowing them to move around to pick up things by themselves, provide

computerized billing and accept debit/ credit cards.

There should be an assistant to help the customers with the cart, also to provide a tour of

the same

6.3 CONCLUSION

In India consumers are showing a rapid change by shifting their buying from

unorganized outlets to organized outlets. In the emerging Indian retail environment, this study

has brought new insights into retail service quality. The managerial implications of the

present study will thus help unorganized retailers to frame effective marketing strategies to

face the competition.

BIBLIOGRAPHY

Boshoff, Christo, and Terblanche, Nic S. (1997), “Measuring Retail Service Quality: A

Replication Study”, South African Journal of Business Management, 1997, No.4

Kaul, Subhashini, (2005), “Measuring Retail Service Quality: Examining Applicability of

International Research Perspectives in India”, working paper 2005, Indian Institute of

Management, Ahmedabad.

Kim, S., Jin, B. (2001), “An Evaluation of the Retail Service Quality Scale for U.S. and

Korean Customers of Discount Stores”, Advances in Consumer Research, Vol.28

Mehta, S.C., Lalwani, A.K. (2000), “Service Quality in Retailing: Relative Efficiency of

Alternative Measurement Scales for Different Product-Service Environments”, International

Journal of Retail and Distribution management, Vol.28

Parasuraman, A., Berry, L.L. & Zeithmal V.A (1988). SERVQUAL: A Multiple-Item Scale

for Measuring Consumer Perceptions of Service Quality, Journal of Retailing.

Siu, N.Y.M. and Cheung, J.T.H. (2001), “A Measure of Retail Service Quality”, marketing

Intelligence and Planning, Vol.19

Siu, N.Y.M. and Chow, Donald K.H. (2003), “Service Quality in Grocery Retailing: The

Study of a Japanese Super Market in HongKong”, Journal of International Consumer

Marketing, 2003, No.1

RETAIL SERVICE QUALITY IN UNORGANIZED RETAIL OUTLETS

1. GENDER

MALE FEMALE

2. AGE

BELOW10 10-20 20-30 30-40 40-50 50 &ABOVE

3. EDUCATIONAL QUALIFICATION

PG UG SCHOOL LEVEL UNEDUCATED

4. OCCUPATION

STUDENT PROFESSIONAL BUSINESS HOUSEWIFE

5. INCOME

BELOW 10000 10000-20000 20000-30000ABOVE 30000

6. MARITAL STATUS

SINGLE MARRIED

7. FAMILY SIZE

2 3 4 ABOVE 4

8. FREQUENCY OF BUYING

DAILY WEEKLY MONTHLY

9. AMOUNT SPENT ON EACH PURCHASE

BELOW 100 100-500 500&ABOVE

10. NUMBER OF YEARS YOU HAVE BEEN THE CUSTOMER OF THAT PARTICULAR SHOP

LESS THAN 6 MONTHS 6 MONTH – 1 YEAR1 – 2 YEARS MORE THAN 2 YEARS

11. TYPE OF GOODS PURCHASED FREQUENTLY

__________________________

RETAIL SERVICE QUALITY IN UNORGANIZED RETAIL OUTLETS

Name of the retail outlet:

Rate the following statements on a 5-point rating scale

S.No. STATEMENTSTRONG

LY AGREE

AGREE

NEUTRAL

DISAGREE

STRONGLY

DISAGREE

1The store has a modern outlook

(lighting, A/c, Computerized billing, attractive Display)

2 The store is easy to reach

3Working hours of the store are

convenient (extended hours, early morning hours)

4Arrangements of goods is attractive

in this store

5The staff are wearing neat and tidy

uniform

6Fresh items are also available in this store daily (vegetables, egg, bread,

etc.)

7the store offers goods in loose items/

smaller quantities

8The store layout makes it easy to move around to find what I need

9 The store offers a variety of products

10Products sold in this store are what I

want

11There is sufficient stock available in

this store12 Products sold are of good quality13 The store makes check out quicker

14Customers feel safe in their transactions with this store

15The receipt contains clear and

detailed information

16Sales staff of this store are courteous

and helpful17 The store provides door delivery

18Products are available at all price

ranges in this store

19This store handles customer

complaints willingly

20This store gives individual attention

to customers

21The store’s offers and discounts do

not have hidden costs

A Study on Service Quality in Unorganised Retailing

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