Description
Factors affecting organized Retail Stores
INTRODUCTION OF INDUSTRY
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Overview
The Indian retail industry is divided into organized and unorganized sectors. Organized retailing refers to trading activities undertaken by licensed retailers, that is, those who are registered for sales tax, income tax, etc. These include the corporate-backed hypermarkets and retail chains, and also the privately owned large retail businesses. Unorganized retailing, on the other hand, refers to the traditional formats of low-cost retailing, for example, the local kirana shops, owner manned general stores, paan /beedi shops, convenience stores, hand cart and pavement vendors, etc. India?s retail sector is wearing new clothes and with a three-year compounded annual growth rate of 46.64 per cent, retail is the fastest growing sector in the Indian economy. Traditional markets are making way for new formats such as departmental stores, hypermarkets, supermarkets and specialty stores. The Indian retail sector is highly fragmented with 97 per cent of its business being run by the unorganized retailers like the traditional family run stores and corner stores.
Over the past few years, the retail sales in India are hovering around 33-35 per cent of GDP as compared to around 20 per cent in the US. The table gives the picture of India?s retail trade as compared to the US and China.
The last few years witnessed immense growth by this sector, the key drivers being changing consumer profile and demographics, increase in the number of international brands available in the Indian market, economic implications of the Government increasing urbanization, credit availability, improvement in the infrastructure, increasing investments in technology and real estate
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building a world class shopping environment for the consumers. In order to keep pace with the increasing demand, there has been a hectic activity in terms of entry of international labels, expansion plans, and focus on technology, operations and processes. International retailers see India as the last retailing frontier left as the China?s retail sector is becoming saturated. However, the Indian Government restrictions on the FDI are creating ripples among the international players like Walmart, Tesco and many other retail giants struggling to enter Indian markets. As of now the Government has allowed only 51 per cent FDI in the sector to „one-brand? shops like Nike, Reebok etc.
However, other international players are taking alternative routes to enter the Indian retail market indirectly via strategic licensing agreement, franchisee agreement and cash and carry wholesale trading (since 100 per cent FDI is allowed in wholesale trading).
Current Status :
India?s retail industry accounts for 10 percent of its GDP and 8 percent of the employment to reach $17 billion by 2010.
The Indian retail market is estimated at US$ 350 billion. But organized retail is estimated at only US$ 8 billion. However, the opportunity is huge-by 2010, organized retail is expected to grow at 6 per cent by 2010 and touch a retail business of $ 17 billion as against its current growth level of 3 per cent which at present is estimated to be $ 6 billion, according to the Study undertaken by The Associated Chambers of Commerce and Industry of India (ASSOCHAM). Indian retailing is clearly at a tipping point. India is currently the ninth largest retail market in the world. And it is names of small towns like Dehradun, Vijayawada, Lucknow and Nasik that will power India up the rankings soon.
Organized retail in India has the potential to add over Rs. 2,000 billion (US$45 billion) business by the Year 2010 generating employment for some 2.5
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million people in various retail operations and over 10 million additional workforce in retail support activities including contract production & processing, supply chain & logistics, retail real estate development & management etc. It is estimated that it will cross the $650-billion mark by 2011, with an already estimated investment of around $421 billion slated for the next four years.
Transition from Traditional to Modern Retailing :
With a share of over 95 per cent of total retail revenues, traditional retailing continues to be the backbone of the Indian retail industry. Over 12 million small and medium retail outlets exist in India, the highest in any country.
Traditional retail formats are highly popular in small towns and cities with primary presence of neighborhood “kirana” stores, push-cart vendors, “melas” and “mandis”. Modern/organized retailing is growing at an aggressive pace in urban India, fuelled by burgeoning economic activity. Increasing number of domestic and international players are setting up base in the country and expanding their business to tap this growing market.
Increasing Penetration of Organized Retail :
Organized retail in India is largely restricted to the urban and semi-urban regions, with consumer exposure to modern retailing formats like malls and stand-alone stores, etc., for specific product categories.
Clothing and textiles/apparel segment dominates the organized retail sector with revenues worth US$ 4.76 billion, contributing to over 36 per cent of the organized retail pie.
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Apparel is one of the fastest growing verticals, with higher number of domestic and foreign brands, and increasing consumer willingness to pay for quality.
Footwear has the highest organized retail penetration, primarily due to players like Bata India Pvt. Ltd. And Liberty, with wide distribution network and customer confidence.
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SWOT Analysis of Organized Retail Stores : Strengths :
? Demographic favor ? Rising disposable income ? Increase in number of people in earner category. ? Urbanization ? Shopping convenience ? Low labor cost of skilled ones. ? Changing consumer habits and lifestyles. ? Plastic card revolution. ? Greater availability of quality retail space.
Weakness :
? Policy related issues ? Limited consumer insight ? Inadequate human resources ? Taxation hurdle ? Underdeveloped supply chain
Opportunities :
? Potential for investment. ? Sectors with high growth potential. ? Fastest growing formats. ? Rural retail. ? Wholesale trading. ? E-retailing ? Retail franchising
Threats:
? Political issues. ? Social issues.
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? Inflation. ? Lack of differentiation among the malls that are coming. ? Poor inventory turns and stock availability measures.
Types of retail stores :
It is in retailing that very drastic changes have occurred during the last twodecades. Some institutions have disappeared whereas newer ones have been added. This process of deletion / addition still continues in newer forms. There is large scale retailing shops together with very small units, both working simultaneously. They have from hawkers and peddlers, who have no permanent place, to well organized, settled retail shops like chain stores, departmental stores, etc. The institutions carrying on the retail business can be classified as under. ? ? ? In-store Retailing Non-Store Retailing Franchising
In-store Retailing 1. Hyper market 2. Department Stores 3. Super Markets 4. Discount Houses 5. Chain Stores or 6. Multiple Shops Non-Store Retailing 1. Direct Selling 2. Telemarketing 3. Online Retailing 4. Automatic vending 5. Direct Marketing Franchising
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Key Players in Indian Retail Sector :
? AV Birla Group has a strong presence in apparel retail and owns renowned brands like Allen Solly, Louis Phillipe, Trouser Town, Van Heusen and Peter England. The company has investment plans to the tune of Rs 8000 – 9000 crores till 2010. ? Trent is a subsidiary of the Tata group; it operates lifestyle retail chain, book and music retail chain, consumer electronics chain etc. Westside, the lifestyle retail chain registered a turnover of Rs 3.58 mn in 2006 ? ? Landmark Group invested Rs. 300 crores to expand Max chain, and Rs 100 crores on Citymax 3 star hotel chain. Lifestyle International is their international brand business. ? K Raheja Corp Group has a turnover of Rs 6.75 billion which is expected to cross US$100 million mark by 2010. Segments include books, music and gifts, apparel, entertainment etc. ? Reliance has more than 300 Reliance Fresh stores; they have multiple formats and their sale is expected to be Rs 90,000 crores ($20 billion) by 2009-10. ? Pantaloon Retail has 450 stores across the country and revenue of over Rs. 20 billion and is expected to touch 30 million by 2010. Segments include Food & grocery, e-tailing, home solutions, consumer electronics, entertainment, shoes, books, music & gifts, health & beauty care services.
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BIG BAZAAR:
The Big Bazaar is formed by the CEO of Future Group, Mr. Kishore Biyani on jan-2001. The Group does not promise more than what it gives. Their basic attraction is linked to affordability, is their Unique Selling Price. In 2001 the group opened its first store on VIP Road, Calcutta, which was the primary departmental store offering regulated services for parking, steel, ships, clothes, electronics, etc. under one roof at competitive prices. Big Bazaar has been a huge hit with the lower middle and middle class people as a large customer base. Big Bazaar is a chain of supermarkets in India, which takes account of every family's needs and requirements. This dealer is a subsidiary of Future Group, trousers Retail India Ltd. and is a response to the U.S. Wal-Mart. Big Bazaar has released its doors to fashion, general merchandise as sports goods, cutlery, crockery, cutlery, and home furnishings, etc. at best economical price.
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D – MART :
D Mart, R K Damani - promoted retail chain on 2002, is planning to go national in the next couple of months, by opening stores in „key? cities such as Bangalore, Delhi and Hyderabad. The nine-year-old chain would add at least 25 stores in the next one year to its existing 33 stores in Maharashtra and Gujarat, said an executive with D Mart. The retailer recently opened a 25,000 sq ft store in Hyderabad. R K Damani is one of the biggest stock market investors in the country. Though D Mart was among the few retailers who owned properties rather than leasing these out, it is also looking at taking properties on rent to increase its footprint. D Mart?s expansion plan coincides with the plans of other retail majors, such as Bharti Retail and Reliance Retail, who have already hit the expansion trial, following recovery in economy and consumer spending. According to consultants, D Mart?s slow expansion became a boon for it as last year?s economic slowdown proved painful for retailers, especially for the mid-size ones, as customers curbed spending to save cash.
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RELIANCE FRESH:
Reliance Fresh is the convenience store format which forms part of the retail business of Reliance Industries of India which is headed by Mukesh Ambani, and started on october-2006. Reliance plans to invest in excess of Rs 25000 crores in the next 4 years in their retail division. The company already has in excess of 560 reliance fresh outlets across the country. These stores sell fresh fruits and vegetables, staples, groceries, fresh juice bars and dairy products. A typical Reliance Fresh store is approximately 3000-4000 square feet and caters to a catchment area of 2–3 km. Post launch, in a dramatic shift in its positioning and mainly due to the circumstances prevailing in UP, West Bengal and Orissa, it was mentioned recently in news dailies that, Reliance Retail is moving out of stocking fruits and vegetables. Reliance Retail has decided to minimize its exposure in the fruit and vegetable business and position Reliance Fresh as a pure play super market focusing on categories like food, FMCG, home, consumer durables, IT and wellness , with food accounting for the bulk of the business. When the first Reliance Fresh store opened in Hyderabad last October, not only did the company said the store?s main focus would be fresh produce like fruits and vegetables at a much lower price, but also spoke at length about its “farm-to-fork?? theory. The idea the company spoke about was to source from farmers and sell directly to the consumer removing middlemen out of the way.
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Challenges for Organized Retail Stores :
The challenges facing the Indian organized retail sector are various and these are stopping the Indian retail industry from reaching its full potential. The behavior pattern of the Indian consumer has undergone a major change.
This has happened for the Indian consumer is earning more now, western influences, women working force is increasing, desire for luxury items and better quality. He now wants to eat, shop, and get entertained under the same roof. All these have lead the Indian organized retail sector to give more in order to satisfy the Indian customer.
The biggest challenge facing the Indian organized retail sector is the lack of retail space. With real estate prices escalating due to increase in demand from the Indian organized retail sector, it is posing a challenge to its growth.
Trained manpower shortage is a challenge facing the organized retail sector in India. The Indian retailers have difficulty in finding trained person and also have to pay more in order to retain them. This again brings down the Indian retailers profit levels. The Indian government has allowed 51% foreign direct investment (FDI) in the India retail sector to one brand shops only. This have made the entry of global retail giants to organized retail sector in India difficult. This is a challenge being faced by the Indian organized retail sector. But the global retail giants like Tesco, Wal-Mart, and Metro AG are entering the organized retail sector in India indirectly through franchisee agreement and cash and carry wholesale trading. Many Indian companies are also entering the
Indian organized retail sector like Reliance Industries Limited, Pantaloons, and Bharti-Telecoms. But they are facing stiff competition from these global retail giants. As a result discounting is becoming an accepted practice. This too brings down the profit of the Indian retailers. All these are posing as challenges facing the Indian organized retail sector.
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SURVEY OF LITERATURE
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SURVEY OF LITERATURE
Mathew Joseph and Manisha Gupta - September 2008: The Indian retail sector is booming and modernizing rapidly in line with India?s economic growth. In this review the author talked about the impact of organized retailing on traditional retailing. With the increase in number of various formats for shopping like malls, departmental stores, hypermarkets etc the Indian consumer?s preferences are changing towards and that ?s the reason foreign investors like the king of retail Wal-Mart also came into the Indian retail ground in collaboration with Bharti. There is a huge untapped market is present in India right now which contains a number of opportunities for retailers.
Organized Vs Unorganized retailing:
The concept of retail is comparatively very old in Indian context. Before anybody knew about what retail is, we had kirana stores, medical stores and lot many other stores working surprisingly well all over the country.
Recently with the entrance of big players like Wal-Mart or Reliance, people are getting idea of the traditional stores going to be vanished. But just to remind us, we should never forget how deep rooted is this old concept. The very modern organized stores have taken the idea of retailing nowhere else than from these old shops. To establish a successful retail chain almost all the giants are doing its of market research on these traditional stores. Now to understand what is so unique about it, we should see how they actually work.
The tradition stores are shops where the various product available are the range of product really required by the visiting customers. They cautiously take care of the choice of the customers and bring the product which is demanded by them. They try to satisfy them with the wide range and at the same time maintain a good relationship to retain them and consequently convert them into their loyal customer. These owners also study the emerging
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trend in the market bring the latest goods to their stores and then learn how is it actually affecting the sales of theirs. Although there stores have comparatively less product range the selection made is quite relevant. As a result with less SKUs (store keeping unit)they are able to maintain a large profit from it.
Now coming to the recently evolved organized sector, the USP of these stores is the large width and depth of the SKUs in them. Accessibility of the customers to the product and choice in selecting them often leads to compulsive buying of the product. Let it be Big Bazaar or more the very arrangements and display processing often tempts the customer to buy the products least required.
Having looked at their features let us now find the loopholes of such model. However good is the ambience and wide is the product range, when it comes the selling price of the various goods, traditional shops are always more efficient than these newly evolved stores. These retail shop lacking the interaction with the customers have miserably failed in building base with loyal customer. No matter how much the companies talk about CRM
(customer relationship management), when it comes to the implementation they endeavor it only through the discount sales driven by their profit motive.
Private labeling:
A private label can be defined as a brand name owned by a retailer or wholesaler for a line or variety of items under control or exclusive distribution (euro monitor, 1998). A private label is characterized by a product produced, improved, processed, packed or distributed exclusively by the organization that has the brand control (AC Nielson,2002). Retailer private labels are often also referred as owned labels, store brands, or distributer-owned brands.
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Global growth and scenario of the private label: In an international review, the Boston consultancy growth(2003) revels that in countries such as UK, Belgium, Germany, France, Spain, Italy, and the USA, the share of store brands increased substantially between 1997and 2002, in some cases to over 30%. According to A.C.Nielsen(2001) and agricultural and agri-food, Canada (2001) countries as diverse as Canada, Australia, Philippines, Hong Kong, Mexico, Chile have experienced the same phenomenon of private labeled growth.
Objectives of introducing the private label
Retailer with own labels as well as planning to have their own labels, target strategic objectives in their business plan. Primary objectives of introducing private labels are as follows. ? To get better bargaining power while negotiating with national brand manufacturers ? To provide better value to customers in terms of product offerings with lower mark ups?. ? To increase profitability on a gradual basis. ? To create powerful own labels in order to gain more market share. ? To enhance store image. ? To create store loyalty through unique private label offerings.
Impulse Buying:
An impulse purchase or impulse buy is an unplanned decision to buy a product or service, made just before a purchase. One who tends to make such purchases is referred to as an impulse purchaser or impulse buyer.
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Research findings suggest that emotions and feelings play a decisive role in purchasing, triggered by seeing the product or upon exposure to a well crafted promotional message. Marketers and retailers tend to exploit these impulses which are tied to the basic want for instant gratification. For example, a shopper in a supermarket might not specifically be shopping for confectionary. However, candy, gum, mints and chocolate are prominently displayed at the checkout aisles to trigger impulse buyers to buy what they might not have otherwise considered. Alternatively, impulse buying can occur when a potential consumer spots something related to a product that stirs a particular passion in them, such as seeing a certain country's flag on the cover of a certain DVD. Sale items are displayed in much the same fashion. Impulse buying can also extend to so-called "big ticket" items such as automobiles and home appliances. Automobiles in particular are as much an emotional purchase as a rational one. This in turn leads auto dealers all over the world to market their products in a rapid-fire, almost carnival-like manner designed to appeal to emotion over reason. Impulse buying disrupts the normal decision making models in consumers' brains. The logical sequence of the consumers' actions is replaced with an irrational moment of self gratification. Impulse items appeal to the emotional side of consumers. Some items bought on impulse are not considered functional or necessary in the consumers' lives. Preventing impulse buying involves techniques such as setting budgets before shopping and taking time out before the purchase is made. A study published in the June 2008 issue of the Journal of Consumer Research suggests that consumers are more susceptible to making impulsive purchases for one brand over another if they are distracted while shopping. In the study, Central Michigan University Psychology professor Bryan Gibson surveyed college students by measuring their preference for a variety of soft drinks, including Coke and Pepsi. Results of Gibson's study found that implicit
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attitudes, or those that people may not be conscious of and able to verbally express, predicted product choice only when participants were presented with a cognitive task, suggesting that implicit product attitudes may play a greater role in product choice when the consumer is distracted or making an impulse purchase.
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IMPORTANCE OF THE STUDY
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IMPORTANCE OF THE STUDY:
Study will indicate the preference level of the customers towards organized retail stores. Study will indicate the factors which influences more to customers to visit the organized retail stores. Study will reflect impulse buying behavior of customers. The study will indicate weather private label products are preferred or not. Study will also indicate which products are sold more under private labeled brand as well as satisfaction level of customers towards it.
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OBJECTIVES OF THE STUDY
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OBJECTIVES OF THE STUDY:
? To study the factors influencing customers to prefer organized retail stores. ? To study the preference level, of products to be purchased by customers from organized retail stores.
? To study impulse buying behavior of the customers in organized retail stores. ? To study the buying behavior of customers towards private labeled products of organized retail stores.
? To know the satisfaction level of customers towards private labeled brands.
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RESEARCH METHEDOLOGY
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Research Design;-
? Descriptive Research We have used descriptive research design for our study. The objective of descriptive research is to describe the existing problem or a situation to provide insights and understanding. The analysis of primary data is qualitative and the research is most reliable on primary data .
Limitation of the Study;-
? Respondents may give biased answers for the required data. ? Some respondents had also not given their personal details so it is not possible to get other data from those if needed. ? Samples are suspected by the researcher, so it is as per convenience and suspecting skill of us.
Sources of data:-
Primary sources :
? Information by customers of organized retail stores.
Secondary sources :
? Secondary data was collected from the internet, journals, magazines, articles and previous project reports.
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Data Collection Method:The survey was conducted through structured questionnaire method of data collection.
Population:The population of the entire research is customers of the organized retail stores in VVnagar, Anand, and Baroda cities.
Sampling Method:Sample design is a definite plan of obtaining some items from the whole population. In this survey we have used convenience sampling as our sampling method.
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SAMPLING FRAME
1. Sampling Technique
Convenience-Non probability sampling (A non probability sampling technique is that in which each element in the population does not have an equal chance of getting selected)
2. Sample Unit
Person who visits the Organized Retail Stores .
3. Sample size
200 respondents
4. Method
Personal interview through Questionnaire.
5. Data analysis method
Graphical method.
6. Area of survey
Anand, V.V.nagar and Baroda.
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DATA ANAYSIS AND INTERPRITATION
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Distribution of respondents
(1) Gender wise Distribution:
Table No – 1 CATEGORY TOTAL PERCENTAGE MALE 107 53.5 FEMALE 93 46.5 Graph No – 1
As the graph indicates around 47% of all respondents are female and rest are male. Which indicates that the ratio of male and female is almost 1:1
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(2) Age wise Distribution:
Table No – 2 category Total 0-26 26-35 36-45 above 45 Graph No – 2 percentage 93 43 37 27 46.5 21.5 18.5 13.5
As the graph represents about 46.5% of respondents fall into the age category of 0-26.
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(3) Occupation wise Distribution:
Table No – 3 Column1 Student Housewife Service Business Others Graph No – 3 total percentage 72 36 33 16.5 69 34.5 20 10 6 3
As the graph indicates majority of our respondents fall into category of students and service that is 36% and 34.5% simultaneously.
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(4) Income wise Distribution:
Table No – 4 INCOME 0-2 lacs 2-3 lacs 3-4 lacs 4-5 lacs Graph No – 4 TOTAL PERCENTAGE 78 39 46 23 36 18 40 20
As the graph indicates majority of our respondents fall into income category of 0-2 lacs that is 39%.
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Question wise Analysis of the Data
Q-1: How frequently do you visit the retail stores?
Table No – 5 CATEGORY TOTAL PERCENTAGE FREQUENTLY 40 20 FORTNIGHTLY 24 12 WEEKLY 50 25 MONTHLY 86 43 Graph No – 5
As the graph represents 43% of the respondents visited the retail store monthly, 25% of the respondents visited the retail store weekly, 20% of the respondents visited the retail store frequently, and 12% of the respondents visited the retail store.
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Q-2 : Choose from the following for which you visit the retail stores?
Table No – 6 CATEGORY Shopping Price Entertainment Time pass Graph No – 6 TOTAL PERCENTAGE 166 83 85 42.5 51 25.5 58 29
As the graph represents 83% of the respondents visited the retail stores for shopping, 42.5% of the respondents visited the retail store for comparison of price, 25.5% of the respondent visited for entertainment and 29% of the respondent visited for time pass.
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Q-3 : What are the factors which influence you to visit the retail stores?
Table No – 7 CATEGORY Ambience One stop Staff courtesy Extra service Product variety Price New product Graph No – 7 TOTAL PERCENTAGE 83 41.5 144 72 22 11 15 7.5 109 54.5 85 42.5 78 39
As the graph represents 72% of the respondents visit the retail store for one stop shopping, 54.5% of the respondents visit for product variety, 42.5% of the respondents visit for price, 39% visit for new product availability, 11% visit for staff courtesy and 7.5% of the respondents visited for extra service.
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Q-5 : Show your preference level from purchasing the following product category from the retail stores. (Data in percentage)
Table No – 8 HIGHLY CATEGORY PREFERED Grocery Electrics Packaged foods Snacks & biscuits Cosmetics Clothing Health care Handlooms Vegetables/Fruits Jewellery Sports/Toys Stationary Graph No – 8 NOT PREFERED PREFERED 32 47 21 5.5 26 68 46 42 12 62 15 16.5 9.5 3.5 4 2 7 9 29.5 42.5 49.5 39 28 32 15 34 31 8 42.5 34 51.5 68.5 64 83 59 60
As per the graph indicates snacks & biscuits (62%) and packet food products(46%) are highly preferred by the respondents, whereas grocery(47%), cosmetics(42.5%), clothing(49.5%) fall in preferred category and electronics items(68%), health care(51.5%), vegetables/fruits(64%), sports/toys(59%), stationary items(60%) fall in not preferred category.
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Q-6 : Does advertisement influence you to visit the retail store?
Table No – 9 ADVERTISEMENT TOTAL EVERYTIME SOMETIME NEVER PERCENTAGE 25 12.5 111 55.5 64 32
Graph No – 9
As the graph indicates 55.5% of respondents are influenced by advertisement „sometime?, 32% respondents are „never? influenced by advertisement, 12.5% respondents are „every time? influenced to visit the retail stores.
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Q-7 : Do you purchase the product which you have not planned before visiting the retail stores?
Table No – 10 UNPLANNED EVERYTIME SOMETIME NEVER Graph No – 10 TOTAL PERCENTAGE 51 25.5 125 62.5 23 11.5
As per the graph indicates 62.5% of the respondent?s sometime purchase the products, 25.5% of the respondents purchase the product every time, 11.5% of the respondents never purchases the products.
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Q-8 : Choose from the product category which you find cheaper in the retail stores.
Table No – 11 CATEGORY TOTAL Grocery Electrics Packaged foods Snacks & biscuits Cosmetics Clothing Health care Handlooms Vegetables/Fruits Jewellery Sports/Toys Stationary PERCENTAGE 108 54 6 3 56 28 149 15 43 1 3 12 0 3 3 74.5 7.5 21.5 0.5 1.5 6 0 1.5 1.5
Graph No – 11
As the graph represents 74.5% of the respondents choose snacks and biscuits finds cheaper than other products.
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Q-9 : Do you buy the products which are sold at retail store under their own brand?
Table No – 12 PRIVATE BRAND EVERYTIME SOMETIME NEVER Graph No – 12 TOTAL PERCENTAGE 5 2.5 72 36 123 61.5
As the graph represents about 61.5% of respondents never preferred the products which are private labeled, 36% of the respondents sometime preferred and 2.5% respondents every time preferred the private label products.
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Q-10 : From the following give preference to the product categories you purchase under the name of retail stores.
Table No – 13 CATEGORY TOTAL Grocery Electrics Packaged foods Snacks & biscuits Cosmetics Clothing Health care Handlooms Vegetables/Fruits Jewellery Sports/Toys Stationary Graph No – 13 PERCENTAGE 44 22 6 3 28 14 24 7 19 1 3 6 3 3 8 12 3.5 9.5 0.5 1.5 3 1.5 1.5 4
As the graph indicates majority of respondents preferred grocery i.e. 22%, on the other hand healthcare (0.5%), handlooms-jwellery-sports/toys (1.5%) are least preferred. While packaged foods (14%), snacks and biscuits (12%), clothing (9.5%) are averagely preferred by the respondents.
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Q-11 : Choose satisfaction level for the retail stores own labeled products.
Table No – 14 SATISFACTION LEVEL HIGHLY SATISFIED SATISFIED NEUTRAL DISSATISFIED HIGHLY DISSATISFIED Graph No – 14 TOTAL 3 56 17 1 0 PERCENTAGE 1.5 28 8.5 0.5 0
As the graph indicates from about 200 respondents only 77 number of respondents preferred private labeled products among which 28% of the respondents are satisfied with the private labeled products, 8.5% respondents are neutral and 1.5% of the respondents are highly satisfied.
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CROSS TABULATION AND CHI-SQUARE TEST
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CROSS TABULATION AND CHI SQUARE TEST
CROSS TABULATION : In this part simultaneous analysis of two variables is carried out through cross tabulation. Hypotheses testing are also included in this part.
CHI SQARE TESTING : To check the association between two variables statistically, chi square test is performed. Although there are no assumptions made as to the shape of the data distribution for this nonparametric technique, there are restrictions on its application. As a rule of thumb, if the degree of freedom is greater than one, not more than 20% of the cells should have expected frequencies of less than 5. If this requirement can?t be made researcher should attempt to combined cells, until it confirms to this rule, but only if the combination would not render the data meaningless. As per this rule for the data in tables 15.1.1,15.2.1,15.3.1,15.4.1 (for testing chi square of private labeling with age, gender, occupation, income) has been changed and cells has been merged.
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Age and private labeling
Table No – 15.1.1 : Age * Private Brand Cross tabulation private brand Every time 2 0 1 2 5
Never Age below26 26-35 36-45 above 46 Total 51 29 25 18 123
Sometimes 40 14 11 7 72
Total 93 43 37 27 200
As the above table indicates that requirement of chi -square is not fulfilled so, the data has been merged and then chi square test is applied.
Hypothesis : H0 : there is no association between the age of the respondents and his/her preference for purchasing private labeled products. H1 : there is association between the age of the respondents and his/her preference for purchasing private labeled products.
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Table No – 15.1.2 : Age * Private Brand Cross tabulation private brand Never Age below 26 26-35 36-45 above 45 Total 51 29 25 18 123 sometimes &every time 42 14 12 9 77 Total 93 43 37 27 200
Table No – 15.1.3 : Chi-Square Test Value Pearson Chi-Square Likelihood Ratio No. of Valid Cases Df Asymp. Sig. (2sided) 0.353 0.352
3.264(a) 3 3.266 200 3
a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 10.40.
Conclusion:
As indicated in the table, value of the chi-square test is >.05 so, we failed to reject our null hypothesis. So, there is no association between the age of the respondents and his/her preference for purchasing private labeled products.
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Gender and private labeling
Table No – 15.2.1 : Gender * Private Brand Cross tabulation private brand Every time 1 4 5
Never Gender Femal e Male Total 56 67 123
sometime 36 36 72
Total 93 107 200
As the above table indicates that requirement of chi -square is not fulfilled so, the data has been merged and then chi square test is applied.
Hypothesis : H0 : there is no association between the gender of the respondents and his/her preference for purchasing private labeled products. H1 : there is association between the gender of the respondents and his/her preference for purchasing private labeled products.
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Table No – 15.2.2 : Gender * Private Brand Cross tabulation private brand Sometimes & Never every time Gender Male Female Total 67 56 123 40 37 77
Total 107 93 200
Table No – 15.2.3 : Chi-Square Tests Asymp. Sig. (2-sided) 0.728 0.840 0.728 Exact Sig. (2-sided) Exact Sig. (1-sided)
Value df Pearson Chi-Square .121(b) 1 Continuity Correction(a) 0.041 1 Likelihood Ratio 0.121 1 Fisher's Exact Test 0.772 0.420 N of Valid Cases 200 a. Computed only for a 2x2 table b. 0 cells (.0%) have expected count less than 5. The minimum expected count is 35.81. Conclusion: As indicated in the table, value of the chi-square test is >.05 so, we failed to reject our null hypothesis. There no is association between the gender of the respondents and his/her preference for purchasing private labeled products.
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Occupation and private labeling
Table No – 15.3.1 : Occupation * Private Brand Cross tabulation private brand Every sometime time 34 14 15 7 2 72 2 1 1 1 0 5
Never Occupation Student 36
Total 72 33 69 20 6 200
housewife 18 service business others Total 53 12 4 123
As the above table indicates that requirement of chi -square is not fulfilled so, the data has been merged and then chi square test is applied.
Hypothesis : H0 : there is no association between the occupation of the respondents and his/her preference for purchasing private labeled products. H1 : there is association between the occupation of the respondents and his/her preference for purchasing private labeled products.
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Table No – 15.3.2 : Occupation * Private Brand Cross tabulation private brand sometimes &every time Total 36 15 16 8 2 77 72 33 69 20 6 200
Never Occupation Student 36
housewife 18 service business others Total 53 12 4 123
Table No – 15.3.3 : Chi-Square Tests Asymp. Sig. (2sided) 0.020 0.017
Value Pearson Chi-Square Likelihood Ratio No. of Valid Cases
Df
11.614(a) 4 12.004 200 4
a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is 2.31.
Conclusion As indicated in the table, value of the chi-square test is <.05 so, null hypothesis is rejected. There is association between the occupation of the respondents and his/her preference for purchasing private labeled products.
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Income and private labeling
Table No – 15.4.1: Income * Private Brand Cross tabulation private brand Every time 3 1 0 1 5
Never Income 0-2 lacs 2-3 lacs 3-4 lacs Above 4 lacs Total 48 31 18 26 123
sometime 27 14 18 13 72
Total 78 46 36 40 200
As the above table indicates that requirement of chi -square is not fulfilled so, the data has been merged and then chi square test is applied.
Hypothesis : H0 : there is no association between the income of the respondents and his/her preference for purchasing private labeled products. H1 : there is association between the income of the respondents and his/her preference for purchasing private labeled products.
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Table No – 15.4.2 : Income * Private Brand Cross tabulation private brand sometimes &every time 30 15 18 14 77
Never Income 0-2 lacs 2-3 lacs 3-4 lacs above 4 lacs Total 48 31 18 26 123
Total 78 46 36 40 200
Table No – 15.4.3 : Chi-Square Tests Asymp. Sig. (2sided) 0.409 0.414
Value Pearson Chi-Square Likelihood Ratio No. of Valid Cases 2.892(a) 2.855 200
df 3 3
a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 13.86.
Conclusion As indicated in the table, value of the chi-square test is >.05 so, we fail to reject null hypothesis. There is no association between the income of the respondents and his/her preference for purchasing private labeled products.
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FACTOR ANALYSIS
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Factor Analysis:
One of the most widely used interdependency techniques for data reduction is factor analysis. According to Luck and Rubin1, factor analysis seeks to identify a set of dimensions that is not readily observed in a large set of variables. The analysis summarizes a majority of the information in the data set in terms of relatively new few categories, known as factors. Two basic reasons for using factor analysis are (i) to simplify a set of data by reducing a large number of measures (in which some may be interrelated causing multicollinearity) for a set of respondents to a smaller manageable number of factors (which are not interrelated) that still retain most of the information found in the original data set and (ii) to identify the underlying structure of the data in which a large number of variables may really be measuring a small number of basic characteristics of the sample.
Bartlett’s test of sphericity
Bartlett?s test of sphericity is a test statistic used to examine the hypothesis that the variables are uncorrelated in the population. In other words, the population correlation matrix is an identity matrix; each variable correlates perfectly with itself but has no correlation with the other variables under study2. As shown in Table 16.1, for the 12 variables under study, the significance value of Bartlett?s Test is 0.000, this leads to rejection of the idea that the correlation matrix is identity matrix.
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Kaiser-Meyer-Olkin Test for Sampling Adequacy :
The Kaiser-Meyer-Olkin (KMO) measure for sampling adequacy is an index used to examine the appropriateness of factor analysis. It compares the magnitudes of observed correlation coefficients to magnitude of partial correlation coefficients. The KMO value varies from 0 to 1. High value (between 0.5 and 1.0) indicates factor analysis is appropriate. Small values of KMO Statistic indicate that correlations between pair of variables cannot be explained by other variables, and hence, factor analysis is not suitable. As shown in table 16.1, The KMO value found for this study is 0.671, which is nearer to 1. Hence, this value is acceptable and justifies the appropriateness of factor analysis.
Table No – 16.1 : KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity Approx. Chi-Square Df Sig. 0.671 357.629 66 0.000
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Communalities
Communality is the amount of variance a variable can explain with all the factors being considered. This is also the percentage of total variance explained by the common factors3. The method selected for conducting the factor analysis here is Principal Component Analysis. In this method the total variance in the data is considered. The initial communalities for Principal Component Analysis are 1. However, the primary concern is the extracted communalities, which are achieved after extraction of factors. The communalities can be found mathematically by squaring the factor loading of a variable across all factors and then summing these figures. This term may be interpreted as a measure of “uniqueness”. For the present study communalities are calculated with computer software and are as shown in Table 16.2 A low communality figure indicates that the variable is statistically independent and cannot be combined with other variables. A look at table16.2, shows that the extracted communalities are high (greater than 0.5), and hence, acceptable for all the Variables.
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Table No – 16.2 : Communalities Initial Grocery Electronics Packet goods Snacks & biscuits Cosmetics Clothing Health care Handlooms Vegetables/1ruits Jewellery Sports/toys Stationary 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 Extraction 0.473 0.513 0.676 0.651 0.450 0.553 0.622 0.493 0.608 0.559 0.630 0.584
Extraction Method: Principal Component Analysis.
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Variance explained
It is required that the scale constructed and the components extracted should be able to explain maximum variance in the data. For this, an analysis of the Eigen values is required. Eigen value represents the total variance explained by each factor. Table 16.3 shows the Eigen values of all the variables that can be extracted. A maximum of 12 components can be extracted as there are 12 variables. The table also shows the cumulative variance. However, it is required that the maximum amount of variance should be explained in minimum number of components – for this reason extraction of the components is required. Only those factors are extracted for which the Eigen values are greater than one. For the present study, one of the factors having the Eigen value of 1.199which is very nearer to one, is also considered as a factor. Thus, the factors extracted in the study are five in number and together contribute 56.768% of total variance. This is a fair percentage of variance to be explained and assumes of the appropriateness of the factor analysis. Thus extracting four dimensions from a total of 12 variables for measuring the satisfaction level is good by all means.
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Table No – 16.3 : Total Variance Explained
Initial Eigen values Compo nent Total 1 2 3 4 5 6 7 8 9 10 11 12 2.709 1.666 1.239 1.199 0.928 0.827 0.773 0.660 0.595 0.514 0.496 0.394 % of Varianc e 22.572 13.883 10.322 9.990 7.735 6.894 6.443 5.502 4.957 4.281 4.136 3.285 Cumul ative % 22.572 36.455 46.777 56.768 64.502 71.396 77.839 83.342 88.298 92.579 96.715 100.00
Extraction Sums of Squared Loadings % of Varian ce 22.572 13.883 10.322 9.990 Cumul ative % 22.572 36.455 46.777 56.768
Rotation Sums of Squared Loadings % of Varianc e 17.611 14.118 13.695 11.344 Cumulati ve % 17.611 31.729 45.424 56.768
Total 2.709 1.666 1.239 1.199
Total 2.113 1.694 1.643 1.361
Extraction Method: Principal Component Analysis.
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Method used for rotated matrix:
Further table 16.3 shows the extraction sum of squared loadings of the scale for measuring the satisfaction level construct. However, a careful look at the table 16.3 shows that 56.768% variance is not uniformly distributed across all components where only the first components accounts for 17.611% of variance. Thus, in order for the variance to be uniformly distributed across all the components a rotation of the components matrix is required. Components matrix is the loadings of various variables to the extracted components .
Varimax rotation: This is an orthogonal method of factor rotation that minimizes the number of variables with higher loadings on a factor, thereby enhancing the interpretability of the factors. Interpretation is done by identifying the variables that have very high loadings on the same component. These factors can then be interpreted in terms of the Variables that load highly on it. Table 16.4 shows the rotated component matrix. The relationship between the observed variables and the newly produced factors is revealed in the form of factor loadings. These are the coefficients within the matrix that indicate the importance of the factor. These loading have the lower limit of -1.0 and an upper limit of +1.0. For better data reduction those variables that had the factor loadings more than 0.55 were considered under each factor. Fortunately, all the variables have the factor loading more than 0.55 so all the 12 variables are considered for loading on extracted 4 factors. From the table 16.4 it can be seen that 11 variables are clubbed in 4 different factors.
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Table No – 16.4 : Rotated Component Matrix(a) Component 1 Grocery Electronics Packaged foods Snacks & biscuits Cosmetics Clothing Health care Handlooms Vegetables/fruits Jewellery Sports/toys Stationary -0.330 0.378 -0.064 -0.037 0.379 0.097 0.003 0.288 0.201 0.651 0.766 0.755 2 0.116 0.111 0.043 -0.057 0.274 0.734 0.788 0.581 -0.031 0.247 0.168 -0.029 3 0.041 -0.193 0.815 0.801 0.459 0.070 0.038 -0.087 0.218 0.142 -0.080 -0.026 4 0.591 0.566 0.078 0.075 -0.142 -0.003 0.012 0.256 0.720 0.233 -0.096 0.108
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 5 iterations.
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Naming the factors:
1. Complementary Items It includes 3 variables that are:- Jewellery, Sports/toys, Stationary. 2. Household Products It includes 3 variables that are:-Clothing, Healthcare &Handloom. 3. Foods & Snacks It includes 2 variables that are:- Packaged food, Snacks and biscuits. 4. Basic Goods It includes 3 variables that are:- Grocery, Electronics, Vegetables.
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FINDINGS AND CONCLUSION
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FINDINGS
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Majority of customers are influenced by one stop shopping facility, to visit organized retail stores. On the other hand staff courtesy and extra services do not influence much to customers. Most of the Customers preferred to buy snakes and biscuits, packaged foods and grocery items from organized retail stores. On the other hand jwellery, sports/toys, vegetables/fruits, and handloom items are least preferred by the customers. There is no strong influence of Advertisements by organized retail stores on customers. Majority of customers do impulse buying, when they visit retail stores but not every time. Majority of respondents do not prefer to buy private labeled products, as the data indicates 61.5% of the respondents said “Never” for the preference towards private labeled products. Majority of customers (Who buys private labeled products) buy Grocery items under private labeled brand. Majority of users of private labeled products are satisfied Customers find Snakes and biscuits as the cheapest products then other products in organized retail stores. There is no influence of Age, Gender and Income of the respondents on his/her preference for purchasing private labeled products. There is an influence of Occupation of the respondents on his/her preference for purchasing private labeled products. Through Factor Analysis among 12 variables 11 variables can be clubbed into 4 variables
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CONCLUSION
On the basis of data gathered and analysis done we can conclude that, ? People prefer to purchase day to day products from organized retail stores. ? There is less influence of advertisements on customers. ? Majority of the respondents are doing impulse buying. ? People prefer to purchase private labeled products. ? “One stops shopping” is the highly influencing factor to the customers of organized retailing stores, for doing shopping from those stores.
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doc_147771145.pdf
Factors affecting organized Retail Stores
INTRODUCTION OF INDUSTRY
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Overview
The Indian retail industry is divided into organized and unorganized sectors. Organized retailing refers to trading activities undertaken by licensed retailers, that is, those who are registered for sales tax, income tax, etc. These include the corporate-backed hypermarkets and retail chains, and also the privately owned large retail businesses. Unorganized retailing, on the other hand, refers to the traditional formats of low-cost retailing, for example, the local kirana shops, owner manned general stores, paan /beedi shops, convenience stores, hand cart and pavement vendors, etc. India?s retail sector is wearing new clothes and with a three-year compounded annual growth rate of 46.64 per cent, retail is the fastest growing sector in the Indian economy. Traditional markets are making way for new formats such as departmental stores, hypermarkets, supermarkets and specialty stores. The Indian retail sector is highly fragmented with 97 per cent of its business being run by the unorganized retailers like the traditional family run stores and corner stores.
Over the past few years, the retail sales in India are hovering around 33-35 per cent of GDP as compared to around 20 per cent in the US. The table gives the picture of India?s retail trade as compared to the US and China.
The last few years witnessed immense growth by this sector, the key drivers being changing consumer profile and demographics, increase in the number of international brands available in the Indian market, economic implications of the Government increasing urbanization, credit availability, improvement in the infrastructure, increasing investments in technology and real estate
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building a world class shopping environment for the consumers. In order to keep pace with the increasing demand, there has been a hectic activity in terms of entry of international labels, expansion plans, and focus on technology, operations and processes. International retailers see India as the last retailing frontier left as the China?s retail sector is becoming saturated. However, the Indian Government restrictions on the FDI are creating ripples among the international players like Walmart, Tesco and many other retail giants struggling to enter Indian markets. As of now the Government has allowed only 51 per cent FDI in the sector to „one-brand? shops like Nike, Reebok etc.
However, other international players are taking alternative routes to enter the Indian retail market indirectly via strategic licensing agreement, franchisee agreement and cash and carry wholesale trading (since 100 per cent FDI is allowed in wholesale trading).
Current Status :
India?s retail industry accounts for 10 percent of its GDP and 8 percent of the employment to reach $17 billion by 2010.
The Indian retail market is estimated at US$ 350 billion. But organized retail is estimated at only US$ 8 billion. However, the opportunity is huge-by 2010, organized retail is expected to grow at 6 per cent by 2010 and touch a retail business of $ 17 billion as against its current growth level of 3 per cent which at present is estimated to be $ 6 billion, according to the Study undertaken by The Associated Chambers of Commerce and Industry of India (ASSOCHAM). Indian retailing is clearly at a tipping point. India is currently the ninth largest retail market in the world. And it is names of small towns like Dehradun, Vijayawada, Lucknow and Nasik that will power India up the rankings soon.
Organized retail in India has the potential to add over Rs. 2,000 billion (US$45 billion) business by the Year 2010 generating employment for some 2.5
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million people in various retail operations and over 10 million additional workforce in retail support activities including contract production & processing, supply chain & logistics, retail real estate development & management etc. It is estimated that it will cross the $650-billion mark by 2011, with an already estimated investment of around $421 billion slated for the next four years.
Transition from Traditional to Modern Retailing :
With a share of over 95 per cent of total retail revenues, traditional retailing continues to be the backbone of the Indian retail industry. Over 12 million small and medium retail outlets exist in India, the highest in any country.
Traditional retail formats are highly popular in small towns and cities with primary presence of neighborhood “kirana” stores, push-cart vendors, “melas” and “mandis”. Modern/organized retailing is growing at an aggressive pace in urban India, fuelled by burgeoning economic activity. Increasing number of domestic and international players are setting up base in the country and expanding their business to tap this growing market.
Increasing Penetration of Organized Retail :
Organized retail in India is largely restricted to the urban and semi-urban regions, with consumer exposure to modern retailing formats like malls and stand-alone stores, etc., for specific product categories.
Clothing and textiles/apparel segment dominates the organized retail sector with revenues worth US$ 4.76 billion, contributing to over 36 per cent of the organized retail pie.
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Apparel is one of the fastest growing verticals, with higher number of domestic and foreign brands, and increasing consumer willingness to pay for quality.
Footwear has the highest organized retail penetration, primarily due to players like Bata India Pvt. Ltd. And Liberty, with wide distribution network and customer confidence.
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SWOT Analysis of Organized Retail Stores : Strengths :
? Demographic favor ? Rising disposable income ? Increase in number of people in earner category. ? Urbanization ? Shopping convenience ? Low labor cost of skilled ones. ? Changing consumer habits and lifestyles. ? Plastic card revolution. ? Greater availability of quality retail space.
Weakness :
? Policy related issues ? Limited consumer insight ? Inadequate human resources ? Taxation hurdle ? Underdeveloped supply chain
Opportunities :
? Potential for investment. ? Sectors with high growth potential. ? Fastest growing formats. ? Rural retail. ? Wholesale trading. ? E-retailing ? Retail franchising
Threats:
? Political issues. ? Social issues.
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? Inflation. ? Lack of differentiation among the malls that are coming. ? Poor inventory turns and stock availability measures.
Types of retail stores :
It is in retailing that very drastic changes have occurred during the last twodecades. Some institutions have disappeared whereas newer ones have been added. This process of deletion / addition still continues in newer forms. There is large scale retailing shops together with very small units, both working simultaneously. They have from hawkers and peddlers, who have no permanent place, to well organized, settled retail shops like chain stores, departmental stores, etc. The institutions carrying on the retail business can be classified as under. ? ? ? In-store Retailing Non-Store Retailing Franchising
In-store Retailing 1. Hyper market 2. Department Stores 3. Super Markets 4. Discount Houses 5. Chain Stores or 6. Multiple Shops Non-Store Retailing 1. Direct Selling 2. Telemarketing 3. Online Retailing 4. Automatic vending 5. Direct Marketing Franchising
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Key Players in Indian Retail Sector :
? AV Birla Group has a strong presence in apparel retail and owns renowned brands like Allen Solly, Louis Phillipe, Trouser Town, Van Heusen and Peter England. The company has investment plans to the tune of Rs 8000 – 9000 crores till 2010. ? Trent is a subsidiary of the Tata group; it operates lifestyle retail chain, book and music retail chain, consumer electronics chain etc. Westside, the lifestyle retail chain registered a turnover of Rs 3.58 mn in 2006 ? ? Landmark Group invested Rs. 300 crores to expand Max chain, and Rs 100 crores on Citymax 3 star hotel chain. Lifestyle International is their international brand business. ? K Raheja Corp Group has a turnover of Rs 6.75 billion which is expected to cross US$100 million mark by 2010. Segments include books, music and gifts, apparel, entertainment etc. ? Reliance has more than 300 Reliance Fresh stores; they have multiple formats and their sale is expected to be Rs 90,000 crores ($20 billion) by 2009-10. ? Pantaloon Retail has 450 stores across the country and revenue of over Rs. 20 billion and is expected to touch 30 million by 2010. Segments include Food & grocery, e-tailing, home solutions, consumer electronics, entertainment, shoes, books, music & gifts, health & beauty care services.
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BIG BAZAAR:
The Big Bazaar is formed by the CEO of Future Group, Mr. Kishore Biyani on jan-2001. The Group does not promise more than what it gives. Their basic attraction is linked to affordability, is their Unique Selling Price. In 2001 the group opened its first store on VIP Road, Calcutta, which was the primary departmental store offering regulated services for parking, steel, ships, clothes, electronics, etc. under one roof at competitive prices. Big Bazaar has been a huge hit with the lower middle and middle class people as a large customer base. Big Bazaar is a chain of supermarkets in India, which takes account of every family's needs and requirements. This dealer is a subsidiary of Future Group, trousers Retail India Ltd. and is a response to the U.S. Wal-Mart. Big Bazaar has released its doors to fashion, general merchandise as sports goods, cutlery, crockery, cutlery, and home furnishings, etc. at best economical price.
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D – MART :
D Mart, R K Damani - promoted retail chain on 2002, is planning to go national in the next couple of months, by opening stores in „key? cities such as Bangalore, Delhi and Hyderabad. The nine-year-old chain would add at least 25 stores in the next one year to its existing 33 stores in Maharashtra and Gujarat, said an executive with D Mart. The retailer recently opened a 25,000 sq ft store in Hyderabad. R K Damani is one of the biggest stock market investors in the country. Though D Mart was among the few retailers who owned properties rather than leasing these out, it is also looking at taking properties on rent to increase its footprint. D Mart?s expansion plan coincides with the plans of other retail majors, such as Bharti Retail and Reliance Retail, who have already hit the expansion trial, following recovery in economy and consumer spending. According to consultants, D Mart?s slow expansion became a boon for it as last year?s economic slowdown proved painful for retailers, especially for the mid-size ones, as customers curbed spending to save cash.
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RELIANCE FRESH:
Reliance Fresh is the convenience store format which forms part of the retail business of Reliance Industries of India which is headed by Mukesh Ambani, and started on october-2006. Reliance plans to invest in excess of Rs 25000 crores in the next 4 years in their retail division. The company already has in excess of 560 reliance fresh outlets across the country. These stores sell fresh fruits and vegetables, staples, groceries, fresh juice bars and dairy products. A typical Reliance Fresh store is approximately 3000-4000 square feet and caters to a catchment area of 2–3 km. Post launch, in a dramatic shift in its positioning and mainly due to the circumstances prevailing in UP, West Bengal and Orissa, it was mentioned recently in news dailies that, Reliance Retail is moving out of stocking fruits and vegetables. Reliance Retail has decided to minimize its exposure in the fruit and vegetable business and position Reliance Fresh as a pure play super market focusing on categories like food, FMCG, home, consumer durables, IT and wellness , with food accounting for the bulk of the business. When the first Reliance Fresh store opened in Hyderabad last October, not only did the company said the store?s main focus would be fresh produce like fruits and vegetables at a much lower price, but also spoke at length about its “farm-to-fork?? theory. The idea the company spoke about was to source from farmers and sell directly to the consumer removing middlemen out of the way.
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Challenges for Organized Retail Stores :
The challenges facing the Indian organized retail sector are various and these are stopping the Indian retail industry from reaching its full potential. The behavior pattern of the Indian consumer has undergone a major change.
This has happened for the Indian consumer is earning more now, western influences, women working force is increasing, desire for luxury items and better quality. He now wants to eat, shop, and get entertained under the same roof. All these have lead the Indian organized retail sector to give more in order to satisfy the Indian customer.
The biggest challenge facing the Indian organized retail sector is the lack of retail space. With real estate prices escalating due to increase in demand from the Indian organized retail sector, it is posing a challenge to its growth.
Trained manpower shortage is a challenge facing the organized retail sector in India. The Indian retailers have difficulty in finding trained person and also have to pay more in order to retain them. This again brings down the Indian retailers profit levels. The Indian government has allowed 51% foreign direct investment (FDI) in the India retail sector to one brand shops only. This have made the entry of global retail giants to organized retail sector in India difficult. This is a challenge being faced by the Indian organized retail sector. But the global retail giants like Tesco, Wal-Mart, and Metro AG are entering the organized retail sector in India indirectly through franchisee agreement and cash and carry wholesale trading. Many Indian companies are also entering the
Indian organized retail sector like Reliance Industries Limited, Pantaloons, and Bharti-Telecoms. But they are facing stiff competition from these global retail giants. As a result discounting is becoming an accepted practice. This too brings down the profit of the Indian retailers. All these are posing as challenges facing the Indian organized retail sector.
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SURVEY OF LITERATURE
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SURVEY OF LITERATURE
Mathew Joseph and Manisha Gupta - September 2008: The Indian retail sector is booming and modernizing rapidly in line with India?s economic growth. In this review the author talked about the impact of organized retailing on traditional retailing. With the increase in number of various formats for shopping like malls, departmental stores, hypermarkets etc the Indian consumer?s preferences are changing towards and that ?s the reason foreign investors like the king of retail Wal-Mart also came into the Indian retail ground in collaboration with Bharti. There is a huge untapped market is present in India right now which contains a number of opportunities for retailers.
Organized Vs Unorganized retailing:
The concept of retail is comparatively very old in Indian context. Before anybody knew about what retail is, we had kirana stores, medical stores and lot many other stores working surprisingly well all over the country.
Recently with the entrance of big players like Wal-Mart or Reliance, people are getting idea of the traditional stores going to be vanished. But just to remind us, we should never forget how deep rooted is this old concept. The very modern organized stores have taken the idea of retailing nowhere else than from these old shops. To establish a successful retail chain almost all the giants are doing its of market research on these traditional stores. Now to understand what is so unique about it, we should see how they actually work.
The tradition stores are shops where the various product available are the range of product really required by the visiting customers. They cautiously take care of the choice of the customers and bring the product which is demanded by them. They try to satisfy them with the wide range and at the same time maintain a good relationship to retain them and consequently convert them into their loyal customer. These owners also study the emerging
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trend in the market bring the latest goods to their stores and then learn how is it actually affecting the sales of theirs. Although there stores have comparatively less product range the selection made is quite relevant. As a result with less SKUs (store keeping unit)they are able to maintain a large profit from it.
Now coming to the recently evolved organized sector, the USP of these stores is the large width and depth of the SKUs in them. Accessibility of the customers to the product and choice in selecting them often leads to compulsive buying of the product. Let it be Big Bazaar or more the very arrangements and display processing often tempts the customer to buy the products least required.
Having looked at their features let us now find the loopholes of such model. However good is the ambience and wide is the product range, when it comes the selling price of the various goods, traditional shops are always more efficient than these newly evolved stores. These retail shop lacking the interaction with the customers have miserably failed in building base with loyal customer. No matter how much the companies talk about CRM
(customer relationship management), when it comes to the implementation they endeavor it only through the discount sales driven by their profit motive.
Private labeling:
A private label can be defined as a brand name owned by a retailer or wholesaler for a line or variety of items under control or exclusive distribution (euro monitor, 1998). A private label is characterized by a product produced, improved, processed, packed or distributed exclusively by the organization that has the brand control (AC Nielson,2002). Retailer private labels are often also referred as owned labels, store brands, or distributer-owned brands.
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Global growth and scenario of the private label: In an international review, the Boston consultancy growth(2003) revels that in countries such as UK, Belgium, Germany, France, Spain, Italy, and the USA, the share of store brands increased substantially between 1997and 2002, in some cases to over 30%. According to A.C.Nielsen(2001) and agricultural and agri-food, Canada (2001) countries as diverse as Canada, Australia, Philippines, Hong Kong, Mexico, Chile have experienced the same phenomenon of private labeled growth.
Objectives of introducing the private label
Retailer with own labels as well as planning to have their own labels, target strategic objectives in their business plan. Primary objectives of introducing private labels are as follows. ? To get better bargaining power while negotiating with national brand manufacturers ? To provide better value to customers in terms of product offerings with lower mark ups?. ? To increase profitability on a gradual basis. ? To create powerful own labels in order to gain more market share. ? To enhance store image. ? To create store loyalty through unique private label offerings.
Impulse Buying:
An impulse purchase or impulse buy is an unplanned decision to buy a product or service, made just before a purchase. One who tends to make such purchases is referred to as an impulse purchaser or impulse buyer.
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Research findings suggest that emotions and feelings play a decisive role in purchasing, triggered by seeing the product or upon exposure to a well crafted promotional message. Marketers and retailers tend to exploit these impulses which are tied to the basic want for instant gratification. For example, a shopper in a supermarket might not specifically be shopping for confectionary. However, candy, gum, mints and chocolate are prominently displayed at the checkout aisles to trigger impulse buyers to buy what they might not have otherwise considered. Alternatively, impulse buying can occur when a potential consumer spots something related to a product that stirs a particular passion in them, such as seeing a certain country's flag on the cover of a certain DVD. Sale items are displayed in much the same fashion. Impulse buying can also extend to so-called "big ticket" items such as automobiles and home appliances. Automobiles in particular are as much an emotional purchase as a rational one. This in turn leads auto dealers all over the world to market their products in a rapid-fire, almost carnival-like manner designed to appeal to emotion over reason. Impulse buying disrupts the normal decision making models in consumers' brains. The logical sequence of the consumers' actions is replaced with an irrational moment of self gratification. Impulse items appeal to the emotional side of consumers. Some items bought on impulse are not considered functional or necessary in the consumers' lives. Preventing impulse buying involves techniques such as setting budgets before shopping and taking time out before the purchase is made. A study published in the June 2008 issue of the Journal of Consumer Research suggests that consumers are more susceptible to making impulsive purchases for one brand over another if they are distracted while shopping. In the study, Central Michigan University Psychology professor Bryan Gibson surveyed college students by measuring their preference for a variety of soft drinks, including Coke and Pepsi. Results of Gibson's study found that implicit
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attitudes, or those that people may not be conscious of and able to verbally express, predicted product choice only when participants were presented with a cognitive task, suggesting that implicit product attitudes may play a greater role in product choice when the consumer is distracted or making an impulse purchase.
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IMPORTANCE OF THE STUDY
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IMPORTANCE OF THE STUDY:
Study will indicate the preference level of the customers towards organized retail stores. Study will indicate the factors which influences more to customers to visit the organized retail stores. Study will reflect impulse buying behavior of customers. The study will indicate weather private label products are preferred or not. Study will also indicate which products are sold more under private labeled brand as well as satisfaction level of customers towards it.
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OBJECTIVES OF THE STUDY
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OBJECTIVES OF THE STUDY:
? To study the factors influencing customers to prefer organized retail stores. ? To study the preference level, of products to be purchased by customers from organized retail stores.
? To study impulse buying behavior of the customers in organized retail stores. ? To study the buying behavior of customers towards private labeled products of organized retail stores.
? To know the satisfaction level of customers towards private labeled brands.
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RESEARCH METHEDOLOGY
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Research Design;-
? Descriptive Research We have used descriptive research design for our study. The objective of descriptive research is to describe the existing problem or a situation to provide insights and understanding. The analysis of primary data is qualitative and the research is most reliable on primary data .
Limitation of the Study;-
? Respondents may give biased answers for the required data. ? Some respondents had also not given their personal details so it is not possible to get other data from those if needed. ? Samples are suspected by the researcher, so it is as per convenience and suspecting skill of us.
Sources of data:-
Primary sources :
? Information by customers of organized retail stores.
Secondary sources :
? Secondary data was collected from the internet, journals, magazines, articles and previous project reports.
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Data Collection Method:The survey was conducted through structured questionnaire method of data collection.
Population:The population of the entire research is customers of the organized retail stores in VVnagar, Anand, and Baroda cities.
Sampling Method:Sample design is a definite plan of obtaining some items from the whole population. In this survey we have used convenience sampling as our sampling method.
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SAMPLING FRAME
1. Sampling Technique
Convenience-Non probability sampling (A non probability sampling technique is that in which each element in the population does not have an equal chance of getting selected)
2. Sample Unit
Person who visits the Organized Retail Stores .
3. Sample size
200 respondents
4. Method
Personal interview through Questionnaire.
5. Data analysis method
Graphical method.
6. Area of survey
Anand, V.V.nagar and Baroda.
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DATA ANAYSIS AND INTERPRITATION
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Distribution of respondents
(1) Gender wise Distribution:
Table No – 1 CATEGORY TOTAL PERCENTAGE MALE 107 53.5 FEMALE 93 46.5 Graph No – 1
As the graph indicates around 47% of all respondents are female and rest are male. Which indicates that the ratio of male and female is almost 1:1
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(2) Age wise Distribution:
Table No – 2 category Total 0-26 26-35 36-45 above 45 Graph No – 2 percentage 93 43 37 27 46.5 21.5 18.5 13.5
As the graph represents about 46.5% of respondents fall into the age category of 0-26.
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(3) Occupation wise Distribution:
Table No – 3 Column1 Student Housewife Service Business Others Graph No – 3 total percentage 72 36 33 16.5 69 34.5 20 10 6 3
As the graph indicates majority of our respondents fall into category of students and service that is 36% and 34.5% simultaneously.
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(4) Income wise Distribution:
Table No – 4 INCOME 0-2 lacs 2-3 lacs 3-4 lacs 4-5 lacs Graph No – 4 TOTAL PERCENTAGE 78 39 46 23 36 18 40 20
As the graph indicates majority of our respondents fall into income category of 0-2 lacs that is 39%.
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Question wise Analysis of the Data
Q-1: How frequently do you visit the retail stores?
Table No – 5 CATEGORY TOTAL PERCENTAGE FREQUENTLY 40 20 FORTNIGHTLY 24 12 WEEKLY 50 25 MONTHLY 86 43 Graph No – 5
As the graph represents 43% of the respondents visited the retail store monthly, 25% of the respondents visited the retail store weekly, 20% of the respondents visited the retail store frequently, and 12% of the respondents visited the retail store.
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Q-2 : Choose from the following for which you visit the retail stores?
Table No – 6 CATEGORY Shopping Price Entertainment Time pass Graph No – 6 TOTAL PERCENTAGE 166 83 85 42.5 51 25.5 58 29
As the graph represents 83% of the respondents visited the retail stores for shopping, 42.5% of the respondents visited the retail store for comparison of price, 25.5% of the respondent visited for entertainment and 29% of the respondent visited for time pass.
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Q-3 : What are the factors which influence you to visit the retail stores?
Table No – 7 CATEGORY Ambience One stop Staff courtesy Extra service Product variety Price New product Graph No – 7 TOTAL PERCENTAGE 83 41.5 144 72 22 11 15 7.5 109 54.5 85 42.5 78 39
As the graph represents 72% of the respondents visit the retail store for one stop shopping, 54.5% of the respondents visit for product variety, 42.5% of the respondents visit for price, 39% visit for new product availability, 11% visit for staff courtesy and 7.5% of the respondents visited for extra service.
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Q-5 : Show your preference level from purchasing the following product category from the retail stores. (Data in percentage)
Table No – 8 HIGHLY CATEGORY PREFERED Grocery Electrics Packaged foods Snacks & biscuits Cosmetics Clothing Health care Handlooms Vegetables/Fruits Jewellery Sports/Toys Stationary Graph No – 8 NOT PREFERED PREFERED 32 47 21 5.5 26 68 46 42 12 62 15 16.5 9.5 3.5 4 2 7 9 29.5 42.5 49.5 39 28 32 15 34 31 8 42.5 34 51.5 68.5 64 83 59 60
As per the graph indicates snacks & biscuits (62%) and packet food products(46%) are highly preferred by the respondents, whereas grocery(47%), cosmetics(42.5%), clothing(49.5%) fall in preferred category and electronics items(68%), health care(51.5%), vegetables/fruits(64%), sports/toys(59%), stationary items(60%) fall in not preferred category.
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Q-6 : Does advertisement influence you to visit the retail store?
Table No – 9 ADVERTISEMENT TOTAL EVERYTIME SOMETIME NEVER PERCENTAGE 25 12.5 111 55.5 64 32
Graph No – 9
As the graph indicates 55.5% of respondents are influenced by advertisement „sometime?, 32% respondents are „never? influenced by advertisement, 12.5% respondents are „every time? influenced to visit the retail stores.
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Q-7 : Do you purchase the product which you have not planned before visiting the retail stores?
Table No – 10 UNPLANNED EVERYTIME SOMETIME NEVER Graph No – 10 TOTAL PERCENTAGE 51 25.5 125 62.5 23 11.5
As per the graph indicates 62.5% of the respondent?s sometime purchase the products, 25.5% of the respondents purchase the product every time, 11.5% of the respondents never purchases the products.
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Q-8 : Choose from the product category which you find cheaper in the retail stores.
Table No – 11 CATEGORY TOTAL Grocery Electrics Packaged foods Snacks & biscuits Cosmetics Clothing Health care Handlooms Vegetables/Fruits Jewellery Sports/Toys Stationary PERCENTAGE 108 54 6 3 56 28 149 15 43 1 3 12 0 3 3 74.5 7.5 21.5 0.5 1.5 6 0 1.5 1.5
Graph No – 11
As the graph represents 74.5% of the respondents choose snacks and biscuits finds cheaper than other products.
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Q-9 : Do you buy the products which are sold at retail store under their own brand?
Table No – 12 PRIVATE BRAND EVERYTIME SOMETIME NEVER Graph No – 12 TOTAL PERCENTAGE 5 2.5 72 36 123 61.5
As the graph represents about 61.5% of respondents never preferred the products which are private labeled, 36% of the respondents sometime preferred and 2.5% respondents every time preferred the private label products.
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Q-10 : From the following give preference to the product categories you purchase under the name of retail stores.
Table No – 13 CATEGORY TOTAL Grocery Electrics Packaged foods Snacks & biscuits Cosmetics Clothing Health care Handlooms Vegetables/Fruits Jewellery Sports/Toys Stationary Graph No – 13 PERCENTAGE 44 22 6 3 28 14 24 7 19 1 3 6 3 3 8 12 3.5 9.5 0.5 1.5 3 1.5 1.5 4
As the graph indicates majority of respondents preferred grocery i.e. 22%, on the other hand healthcare (0.5%), handlooms-jwellery-sports/toys (1.5%) are least preferred. While packaged foods (14%), snacks and biscuits (12%), clothing (9.5%) are averagely preferred by the respondents.
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Q-11 : Choose satisfaction level for the retail stores own labeled products.
Table No – 14 SATISFACTION LEVEL HIGHLY SATISFIED SATISFIED NEUTRAL DISSATISFIED HIGHLY DISSATISFIED Graph No – 14 TOTAL 3 56 17 1 0 PERCENTAGE 1.5 28 8.5 0.5 0
As the graph indicates from about 200 respondents only 77 number of respondents preferred private labeled products among which 28% of the respondents are satisfied with the private labeled products, 8.5% respondents are neutral and 1.5% of the respondents are highly satisfied.
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CROSS TABULATION AND CHI-SQUARE TEST
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CROSS TABULATION AND CHI SQUARE TEST
CROSS TABULATION : In this part simultaneous analysis of two variables is carried out through cross tabulation. Hypotheses testing are also included in this part.
CHI SQARE TESTING : To check the association between two variables statistically, chi square test is performed. Although there are no assumptions made as to the shape of the data distribution for this nonparametric technique, there are restrictions on its application. As a rule of thumb, if the degree of freedom is greater than one, not more than 20% of the cells should have expected frequencies of less than 5. If this requirement can?t be made researcher should attempt to combined cells, until it confirms to this rule, but only if the combination would not render the data meaningless. As per this rule for the data in tables 15.1.1,15.2.1,15.3.1,15.4.1 (for testing chi square of private labeling with age, gender, occupation, income) has been changed and cells has been merged.
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Age and private labeling
Table No – 15.1.1 : Age * Private Brand Cross tabulation private brand Every time 2 0 1 2 5
Never Age below26 26-35 36-45 above 46 Total 51 29 25 18 123
Sometimes 40 14 11 7 72
Total 93 43 37 27 200
As the above table indicates that requirement of chi -square is not fulfilled so, the data has been merged and then chi square test is applied.
Hypothesis : H0 : there is no association between the age of the respondents and his/her preference for purchasing private labeled products. H1 : there is association between the age of the respondents and his/her preference for purchasing private labeled products.
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Table No – 15.1.2 : Age * Private Brand Cross tabulation private brand Never Age below 26 26-35 36-45 above 45 Total 51 29 25 18 123 sometimes &every time 42 14 12 9 77 Total 93 43 37 27 200
Table No – 15.1.3 : Chi-Square Test Value Pearson Chi-Square Likelihood Ratio No. of Valid Cases Df Asymp. Sig. (2sided) 0.353 0.352
3.264(a) 3 3.266 200 3
a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 10.40.
Conclusion:
As indicated in the table, value of the chi-square test is >.05 so, we failed to reject our null hypothesis. So, there is no association between the age of the respondents and his/her preference for purchasing private labeled products.
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Gender and private labeling
Table No – 15.2.1 : Gender * Private Brand Cross tabulation private brand Every time 1 4 5
Never Gender Femal e Male Total 56 67 123
sometime 36 36 72
Total 93 107 200
As the above table indicates that requirement of chi -square is not fulfilled so, the data has been merged and then chi square test is applied.
Hypothesis : H0 : there is no association between the gender of the respondents and his/her preference for purchasing private labeled products. H1 : there is association between the gender of the respondents and his/her preference for purchasing private labeled products.
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Table No – 15.2.2 : Gender * Private Brand Cross tabulation private brand Sometimes & Never every time Gender Male Female Total 67 56 123 40 37 77
Total 107 93 200
Table No – 15.2.3 : Chi-Square Tests Asymp. Sig. (2-sided) 0.728 0.840 0.728 Exact Sig. (2-sided) Exact Sig. (1-sided)
Value df Pearson Chi-Square .121(b) 1 Continuity Correction(a) 0.041 1 Likelihood Ratio 0.121 1 Fisher's Exact Test 0.772 0.420 N of Valid Cases 200 a. Computed only for a 2x2 table b. 0 cells (.0%) have expected count less than 5. The minimum expected count is 35.81. Conclusion: As indicated in the table, value of the chi-square test is >.05 so, we failed to reject our null hypothesis. There no is association between the gender of the respondents and his/her preference for purchasing private labeled products.
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Occupation and private labeling
Table No – 15.3.1 : Occupation * Private Brand Cross tabulation private brand Every sometime time 34 14 15 7 2 72 2 1 1 1 0 5
Never Occupation Student 36
Total 72 33 69 20 6 200
housewife 18 service business others Total 53 12 4 123
As the above table indicates that requirement of chi -square is not fulfilled so, the data has been merged and then chi square test is applied.
Hypothesis : H0 : there is no association between the occupation of the respondents and his/her preference for purchasing private labeled products. H1 : there is association between the occupation of the respondents and his/her preference for purchasing private labeled products.
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Table No – 15.3.2 : Occupation * Private Brand Cross tabulation private brand sometimes &every time Total 36 15 16 8 2 77 72 33 69 20 6 200
Never Occupation Student 36
housewife 18 service business others Total 53 12 4 123
Table No – 15.3.3 : Chi-Square Tests Asymp. Sig. (2sided) 0.020 0.017
Value Pearson Chi-Square Likelihood Ratio No. of Valid Cases
Df
11.614(a) 4 12.004 200 4
a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is 2.31.
Conclusion As indicated in the table, value of the chi-square test is <.05 so, null hypothesis is rejected. There is association between the occupation of the respondents and his/her preference for purchasing private labeled products.
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Income and private labeling
Table No – 15.4.1: Income * Private Brand Cross tabulation private brand Every time 3 1 0 1 5
Never Income 0-2 lacs 2-3 lacs 3-4 lacs Above 4 lacs Total 48 31 18 26 123
sometime 27 14 18 13 72
Total 78 46 36 40 200
As the above table indicates that requirement of chi -square is not fulfilled so, the data has been merged and then chi square test is applied.
Hypothesis : H0 : there is no association between the income of the respondents and his/her preference for purchasing private labeled products. H1 : there is association between the income of the respondents and his/her preference for purchasing private labeled products.
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Table No – 15.4.2 : Income * Private Brand Cross tabulation private brand sometimes &every time 30 15 18 14 77
Never Income 0-2 lacs 2-3 lacs 3-4 lacs above 4 lacs Total 48 31 18 26 123
Total 78 46 36 40 200
Table No – 15.4.3 : Chi-Square Tests Asymp. Sig. (2sided) 0.409 0.414
Value Pearson Chi-Square Likelihood Ratio No. of Valid Cases 2.892(a) 2.855 200
df 3 3
a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 13.86.
Conclusion As indicated in the table, value of the chi-square test is >.05 so, we fail to reject null hypothesis. There is no association between the income of the respondents and his/her preference for purchasing private labeled products.
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FACTOR ANALYSIS
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Factor Analysis:
One of the most widely used interdependency techniques for data reduction is factor analysis. According to Luck and Rubin1, factor analysis seeks to identify a set of dimensions that is not readily observed in a large set of variables. The analysis summarizes a majority of the information in the data set in terms of relatively new few categories, known as factors. Two basic reasons for using factor analysis are (i) to simplify a set of data by reducing a large number of measures (in which some may be interrelated causing multicollinearity) for a set of respondents to a smaller manageable number of factors (which are not interrelated) that still retain most of the information found in the original data set and (ii) to identify the underlying structure of the data in which a large number of variables may really be measuring a small number of basic characteristics of the sample.
Bartlett’s test of sphericity
Bartlett?s test of sphericity is a test statistic used to examine the hypothesis that the variables are uncorrelated in the population. In other words, the population correlation matrix is an identity matrix; each variable correlates perfectly with itself but has no correlation with the other variables under study2. As shown in Table 16.1, for the 12 variables under study, the significance value of Bartlett?s Test is 0.000, this leads to rejection of the idea that the correlation matrix is identity matrix.
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Kaiser-Meyer-Olkin Test for Sampling Adequacy :
The Kaiser-Meyer-Olkin (KMO) measure for sampling adequacy is an index used to examine the appropriateness of factor analysis. It compares the magnitudes of observed correlation coefficients to magnitude of partial correlation coefficients. The KMO value varies from 0 to 1. High value (between 0.5 and 1.0) indicates factor analysis is appropriate. Small values of KMO Statistic indicate that correlations between pair of variables cannot be explained by other variables, and hence, factor analysis is not suitable. As shown in table 16.1, The KMO value found for this study is 0.671, which is nearer to 1. Hence, this value is acceptable and justifies the appropriateness of factor analysis.
Table No – 16.1 : KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity Approx. Chi-Square Df Sig. 0.671 357.629 66 0.000
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Communalities
Communality is the amount of variance a variable can explain with all the factors being considered. This is also the percentage of total variance explained by the common factors3. The method selected for conducting the factor analysis here is Principal Component Analysis. In this method the total variance in the data is considered. The initial communalities for Principal Component Analysis are 1. However, the primary concern is the extracted communalities, which are achieved after extraction of factors. The communalities can be found mathematically by squaring the factor loading of a variable across all factors and then summing these figures. This term may be interpreted as a measure of “uniqueness”. For the present study communalities are calculated with computer software and are as shown in Table 16.2 A low communality figure indicates that the variable is statistically independent and cannot be combined with other variables. A look at table16.2, shows that the extracted communalities are high (greater than 0.5), and hence, acceptable for all the Variables.
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Table No – 16.2 : Communalities Initial Grocery Electronics Packet goods Snacks & biscuits Cosmetics Clothing Health care Handlooms Vegetables/1ruits Jewellery Sports/toys Stationary 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 Extraction 0.473 0.513 0.676 0.651 0.450 0.553 0.622 0.493 0.608 0.559 0.630 0.584
Extraction Method: Principal Component Analysis.
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Variance explained
It is required that the scale constructed and the components extracted should be able to explain maximum variance in the data. For this, an analysis of the Eigen values is required. Eigen value represents the total variance explained by each factor. Table 16.3 shows the Eigen values of all the variables that can be extracted. A maximum of 12 components can be extracted as there are 12 variables. The table also shows the cumulative variance. However, it is required that the maximum amount of variance should be explained in minimum number of components – for this reason extraction of the components is required. Only those factors are extracted for which the Eigen values are greater than one. For the present study, one of the factors having the Eigen value of 1.199which is very nearer to one, is also considered as a factor. Thus, the factors extracted in the study are five in number and together contribute 56.768% of total variance. This is a fair percentage of variance to be explained and assumes of the appropriateness of the factor analysis. Thus extracting four dimensions from a total of 12 variables for measuring the satisfaction level is good by all means.
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Table No – 16.3 : Total Variance Explained
Initial Eigen values Compo nent Total 1 2 3 4 5 6 7 8 9 10 11 12 2.709 1.666 1.239 1.199 0.928 0.827 0.773 0.660 0.595 0.514 0.496 0.394 % of Varianc e 22.572 13.883 10.322 9.990 7.735 6.894 6.443 5.502 4.957 4.281 4.136 3.285 Cumul ative % 22.572 36.455 46.777 56.768 64.502 71.396 77.839 83.342 88.298 92.579 96.715 100.00
Extraction Sums of Squared Loadings % of Varian ce 22.572 13.883 10.322 9.990 Cumul ative % 22.572 36.455 46.777 56.768
Rotation Sums of Squared Loadings % of Varianc e 17.611 14.118 13.695 11.344 Cumulati ve % 17.611 31.729 45.424 56.768
Total 2.709 1.666 1.239 1.199
Total 2.113 1.694 1.643 1.361
Extraction Method: Principal Component Analysis.
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Method used for rotated matrix:
Further table 16.3 shows the extraction sum of squared loadings of the scale for measuring the satisfaction level construct. However, a careful look at the table 16.3 shows that 56.768% variance is not uniformly distributed across all components where only the first components accounts for 17.611% of variance. Thus, in order for the variance to be uniformly distributed across all the components a rotation of the components matrix is required. Components matrix is the loadings of various variables to the extracted components .
Varimax rotation: This is an orthogonal method of factor rotation that minimizes the number of variables with higher loadings on a factor, thereby enhancing the interpretability of the factors. Interpretation is done by identifying the variables that have very high loadings on the same component. These factors can then be interpreted in terms of the Variables that load highly on it. Table 16.4 shows the rotated component matrix. The relationship between the observed variables and the newly produced factors is revealed in the form of factor loadings. These are the coefficients within the matrix that indicate the importance of the factor. These loading have the lower limit of -1.0 and an upper limit of +1.0. For better data reduction those variables that had the factor loadings more than 0.55 were considered under each factor. Fortunately, all the variables have the factor loading more than 0.55 so all the 12 variables are considered for loading on extracted 4 factors. From the table 16.4 it can be seen that 11 variables are clubbed in 4 different factors.
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Table No – 16.4 : Rotated Component Matrix(a) Component 1 Grocery Electronics Packaged foods Snacks & biscuits Cosmetics Clothing Health care Handlooms Vegetables/fruits Jewellery Sports/toys Stationary -0.330 0.378 -0.064 -0.037 0.379 0.097 0.003 0.288 0.201 0.651 0.766 0.755 2 0.116 0.111 0.043 -0.057 0.274 0.734 0.788 0.581 -0.031 0.247 0.168 -0.029 3 0.041 -0.193 0.815 0.801 0.459 0.070 0.038 -0.087 0.218 0.142 -0.080 -0.026 4 0.591 0.566 0.078 0.075 -0.142 -0.003 0.012 0.256 0.720 0.233 -0.096 0.108
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 5 iterations.
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Naming the factors:
1. Complementary Items It includes 3 variables that are:- Jewellery, Sports/toys, Stationary. 2. Household Products It includes 3 variables that are:-Clothing, Healthcare &Handloom. 3. Foods & Snacks It includes 2 variables that are:- Packaged food, Snacks and biscuits. 4. Basic Goods It includes 3 variables that are:- Grocery, Electronics, Vegetables.
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FINDINGS AND CONCLUSION
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FINDINGS
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Majority of customers are influenced by one stop shopping facility, to visit organized retail stores. On the other hand staff courtesy and extra services do not influence much to customers. Most of the Customers preferred to buy snakes and biscuits, packaged foods and grocery items from organized retail stores. On the other hand jwellery, sports/toys, vegetables/fruits, and handloom items are least preferred by the customers. There is no strong influence of Advertisements by organized retail stores on customers. Majority of customers do impulse buying, when they visit retail stores but not every time. Majority of respondents do not prefer to buy private labeled products, as the data indicates 61.5% of the respondents said “Never” for the preference towards private labeled products. Majority of customers (Who buys private labeled products) buy Grocery items under private labeled brand. Majority of users of private labeled products are satisfied Customers find Snakes and biscuits as the cheapest products then other products in organized retail stores. There is no influence of Age, Gender and Income of the respondents on his/her preference for purchasing private labeled products. There is an influence of Occupation of the respondents on his/her preference for purchasing private labeled products. Through Factor Analysis among 12 variables 11 variables can be clubbed into 4 variables
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CONCLUSION
On the basis of data gathered and analysis done we can conclude that, ? People prefer to purchase day to day products from organized retail stores. ? There is less influence of advertisements on customers. ? Majority of the respondents are doing impulse buying. ? People prefer to purchase private labeled products. ? “One stops shopping” is the highly influencing factor to the customers of organized retailing stores, for doing shopping from those stores.
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