a study on service quality in unorganised retailing
TRANSCRIPT
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.
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
Within Groups 59.679 56 1.066
Total 69.943 69
OCCUPATION
Between Groups 14.835 13 1.141 .992 .471
Within Groups 64.436 56 1.151
Total 79.271 69
INCOME
Between Groups 14.194 13 1.092 .859 .598
Within Groups 71.177 56 1.271
Total 85.371 69
MARITAL
STATUS
Between Groups 2.123 13 .163 .895 .563
Within Groups 10.220 56 .182
Total 12.343 69
FAMILY SIZE
Between Groups 3.893 13 .299 .523 .901
Within Groups 32.050 56 .572
Total 35.943 69
FREQUENCY
OF BUYING
Between Groups 5.799 13 .446 .777 .680
Within Groups 32.144 56 .574
Total 37.943 69
PURCHASE
AMOUNT
Between Groups 9.139 13 .703 1.310 .235
Within Groups 30.061 56 .537
Total 39.200 69
NO. OF
YEARS
Between Groups 12.192 13 .938 1.032 .435
Within Groups 50.894 56 .909
(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
SquaresDf Mean Square F Sig.
GENDER Between Groups 2.004 6 .334 1.363 .244
Within Groups 15.439 63 .245
Total 17.443 69
AGE
Between Groups 5.480 6 .913 .658 .683
Within Groups 87.392 63 1.387
Total 92.871 69
EDUCATIONA
L
QUALIFICATI
ON
Between Groups 4.495 6 .749 .721 .634
Within Groups 65.447 63 1.039
Total 69.943 69
OCCUPATION
Between Groups 8.062 6 1.344 1.189 .324
Within Groups 71.210 63 1.130
Total 79.271 69
INCOME
Between Groups 9.547 6 1.591 1.322 .261
Within Groups 75.825 63 1.204
Total 85.371 69
MARITAL
STATUS
Between Groups .706 6 .118 .637 .700
Within Groups 11.637 63 .185
Total 12.343 69
FAMILY SIZE
Between Groups .733 6 .122 .218 .970
Within Groups 35.210 63 .559
Total 35.943 69
FREQUENCY
OF BUYING
Between Groups 3.169 6 .528 .957 .462
Within Groups 34.774 63 .552
Total 37.943 69
PURCHASE
AMOUNT
Between Groups 7.045 6 1.174 2.301 .045
Within Groups 32.155 63 .510
Total 39.200 69
NO. OF YEARS Between Groups 5.696 6 .949 1.042 .407
(CUSTOMER
LOYALTY)
Within Groups 57.390 63 .911
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 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
SquaresDf Mean Square F Sig.
GENDER
Between Groups 2.879 6 .480 2.076 .069
Within Groups 14.564 63 .231
Total 17.443 69
AGE
Between Groups 6.542 6 1.090 .796 .577
Within Groups 86.329 63 1.370
Total 92.871 69
EDUCATION
QUALIFICATI
ON
Between Groups 4.106 6 .684 .655 .686
Within Groups 65.837 63 1.045
Total 69.943 69
OCCUPATION
Between Groups 2.097 6 .349 .285 .942
Within Groups 77.175 63 1.225
Total 79.271 69
INCOME
Between Groups 9.892 6 1.649 1.376 .238
Within Groups 75.479 63 1.198
Total 85.371 69
MARITAL
STATUS
Between Groups 1.627 6 .271 1.595 .163
Within Groups 10.715 63 .170
Total 12.343 69
FAMILY SIZE
Between Groups 2.330 6 .388 .728 .629
Within Groups 33.613 63 .534
Total 35.943 69
FREQUENCY
OF BUYING
Between Groups 4.422 6 .737 1.385 .234
Within Groups 33.521 63 .532
Total 37.943 69
PURCHASE
AMOUNT
Between Groups 2.068 6 .345 .585 .741
Within Groups 37.132 63 .589
Total 39.200 69
NO.OF YEARS
(CUSTOMER
Between Groups 7.163 6 1.194 1.345 .251
Within Groups 55.923 63 .888
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 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
SquaresDf Mean Square F Sig.
GENDER Between Groups .125 4 .031 .117 .976
Within Groups 17.318 65 .266
Total 17.443 69
AGE
Between Groups 2.041 4 .510 .365 .833
Within Groups 90.831 65 1.397
Total 92.871 69
EDUCATION
QUALIFICATI
ON
Between Groups 1.388 4 .347 .329 .857
Within Groups 68.554 65 1.055
Total 69.943 69
OCCUPATION
Between Groups 3.759 4 .940 .809 .524
Within Groups 75.513 65 1.162
Total 79.271 69
INCOME
Between Groups .162 4 .040 .031 .998
Within Groups 85.210 65 1.311
Total 85.371 69
MARITAL
STATUS
Between Groups 1.102 4 .275 1.593 .187
Within Groups 11.241 65 .173
Total 12.343 69
FAMILY SIZE
Between Groups 1.104 4 .276 .515 .725
Within Groups 34.839 65 .536
Total 35.943 69
FREQUENCY
OF BUYING
Between Groups 1.458 4 .365 .649 .629
Within Groups 36.485 65 .561
Total 37.943 69
PURCHASE
AMOUNT
Between Groups 1.574 4 .394 .680 .608
Within Groups 37.626 65 .579
Total 39.200 69
NO.OF YEARS
(CUSTOMER
Between Groups 5.734 4 1.434 1.625 .179
Within Groups 57.352 65 .882
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 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
significant value is less than 0.05, it means that the demographic variable influences the
factor.
ANOVA FOR RESPONSIVENESS
Sum of
Squaresdf Mean Square F Sig.
GENDER Between .720 5 .144 .551 .737
Groups
Within Groups 16.723 64 .261
Total 17.443 69
AGE
Between
Groups4.574 5 .915 .663 .653
Within Groups 88.298 64 1.380
Total 92.871 69
EDUCATIONAL
QUALIFICATION
Between
Groups1.495 5 .299 .280 .923
Within Groups 68.448 64 1.069
Total 69.943 69
OCCUPATION
Between
Groups2.771 5 .554 .464 .802
Within Groups 76.500 64 1.195
Total 79.271 69
INCOME
Between
Groups4.870 5 .974 .774 .572
Within Groups 80.502 64 1.258
Total 85.371 69
MARITAL
STATUS
Between
Groups.736 5 .147 .811 .546
Within Groups 11.607 64 .181
Total 12.343 69
FAMILY SIZE
Between
Groups2.691 5 .538 1.036 .404
Within Groups 33.252 64 .520
Total 35.943 69
FREQUENCY OF
BUYING
Between
Groups4.169 5 .834 1.580 .178
Within Groups 33.774 64 .528
Total 37.943 69
PURCHASE
AMOUNT
Between
Groups
4.152 5 .830 1.517 .197
Within Groups 35.048 64 .548
Total 39.200 69
NO.OF YEARS
(CUSTOMER
LOYALTY)
Between
Groups3.028 5 .606 .645 .666
Within Groups 60.058 64 .938
Total 63.086 69
INTERPRETATION
The above table shows the significant values of the demographic variable with regard
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