Claims:1. The study identified the impact of organized retailers on employees, customers and profits.
2. Organized retailers of food and groceries adversely affect customers and the profits of traditional retailers.
3. There is no evidence of a decline in overall employment in the traditional retail sector as a result of the entry of organized retailers.
4. Ideal location for traditional retailers, their personal relationship with individual clients, credit facilities they provide and additional services that are suitable for organized retailers. The organized retail sector offers a one stop shopping, good environment, attractive display, fly area, various advertising strategies, pleasant vendors etc.
5. The study found that the respondent was more satisfied with the organized retail design when comparing the organized and traditional retail design. The reason for this visit is not necessarily for shopping, but for the purpose of reducing pleasure and stress but the traditional retail sector focuses only on price.
, Description:The present invention relates to carry out a detailed study of the impact of organized retailers on traditional retailers, with a special focus on the food and grocery industry. To accomplish this important purpose, the specific objectives are set.
[02] BACKGROUND OF THE INVENTION

Indian retail is dominated by many small retailers such as local Grana stores, owner-owned general stores, chemists, shoe stores, clothing stores, pan and beedi stores, handcart dealers, and sidewalk vendors until the so-called "traditional retail". Over the past 3-4 years, many organized retailers have entered the metropolis and other major cities opening stores in a variety of modern styles. In this section, respondents were asked about the effects of organized retailers on traditional retailers. .
[03] SUMMARY OF THE PRESENT INVENTION
The main conclusions drawn from the results of the study are illustrated here. The study identified the impact of organized retailers on employees, customers and profits. Organized retailers of food and groceries adversely affect customers and the profits of traditional retailers. There is no evidence of a decline in overall employment in the traditional retail sector as a result of the entry of organized retailers. There has been some competitive response from traditional retailers with improved business practices and improved technology. They want to change the business to suit modern times, but they do not have enough evidence to change. Most traditional retailers want to continue to compete in the retail business, but they are opposed to children engaging in this retail business. Ideal location for traditional retailers, their personal relationship with individual clients, credit facilities they provide and additional services that are suitable for organized retailers. The organized retail sector offers a one stop shopping, good environment, attractive display, fly area, various advertising strategies, pleasant vendors etc. The study found that the respondent was more satisfied with the organized retail design when comparing the organized and traditional retail design. , The reason for this visit is not necessarily for shopping, but for the purpose of reducing pleasure and stress but the traditional retail sector focuses only on price.
DETAILED DESCRIPTION OF THE INVENTION

Profile of Respondents
Before entering into the analysis based on the objectives, it is pertinent to examine the profile of the selected sample respondents. The sample size of this study was 475 traditional retailers from three major cities in Tamil Nadu. The profiles of the sample respondents are given below.
Distance -wise Classification of Sample Respondents
To ensure that the traditional retailer model extends across the catchment area of organized retailers, the distance scale was used to select traditional stores that are "near" and "round" and "far". Masonry. The catchment area for organized retailers in cities in India is five kilometers, using standard industry norms. Table 1 shows the distance-wise classification of selected sample respondents.
Table 1 Distance-wise Classification of Sample Respondents
Distance Number Percent
Nearest 220 46.1
Around 182 38.1
Far away 73 15.8
Total 475 100.0
From Table 1, it is clear that out of 475 sample respondents taken for analysis, 219 (46.1%) respondents were from the adjoining area and 181 (38.1%) respondents about 75 (15.8%) were from far away. In the distance. They identify the traditional retail sector in the study. Thus a total of 475 people have been selected for the study.
Demographic Profile of the Respondents
The demographic profile of the sample respondents, which comprises the age and educational qualification wise classification of traditional retailers.
Table 2 Age of Owner
Age of owner (Years) Number Percent
20-35 94 19.4
36-45 187 39.6
46-65 129 27.4
more than 65 65 13.7
Total 475 100.0

Table 3 Educational Qualification
Educational qualification Number Percent
No formal schooling 107 22.7
Up to 5 th standard 76 15.8
Up to 10th standard 186 38.9
Up to 12th standard 86 18.3
Graduate 20 4.2
Total 475 100.0
Stores Profile
Type of Stores
Traditional food and grocery stores include grocery stores, general stores and vegetable stores. The table shows the type of traditional retail stores based on distance criteria.
Table 4 Type of Stores

Type of stores Distance from organized retail store
Nearest Around Far away
Grocery store 82 (36.1%) 42 (22.7%) 20 (25.3%)
General store 76 (35.2%) 64 (35.9%) 29 (40.0%)
Fruit/vegetable stores 62 (28.8%) 74 (41.4%) 25 (34.7%)
Total 220 (100.0%) 180 (100.0%) 75 (100.0%)

Table 4 shows the Chi square value of p with .021 as 11.546. Since the p value is less than 0.05 the null hypothesis is rejected at 5% of significance. Therefore, it was concluded that there is a significant correlation between the type of stores and their distance from the organized retail store. Most of the nearby stores are grocery stores, fruit / vegetable stores around the stores and distant retail stores general stores.
Type of Business
There are two types of business models, retail and retail and wholesale. In stores where goods are primarily sold to end-customers, also known as retail stores and retail cum wholesale, they sell goods for industrial, commercial or corporate purposes, including end-customers. Table 5 shows the business type of traditional stores based on distance criteria.
Table 5 Type of Business
Type of business Distance from organized retail store
Nearest Around Far away
Retail 209 (95.4%) 126 (69.6%) 63 (82.7%)
Retail cum wholesale 11 (4.6%) 54 (30.4%) 12 (17.3%)
220 (100.0%) 180 (100.0%) 75 (100.0%)
Chi-Square value =48.193, df= 2, p value = .000

The result of the analysis shows the value of Chi squared with p value .000 as 48.193. Since the p value is less than 0.01 the null hypothesis is rejected at 1% of significance. It has therefore been decided that there is a significant correlation between the business type of traditional stores and their distance from the organized retail store. The density of retail stores is higher in the vicinity than in the surrounding and remote areas
Number of Employees
The table 6 shows the total number of employees (Now) working in the traditional retail stores on the basis of distance criteria.
Table 6 Number of Employees (Now)

Number Distance
Nearest Around Far away
No employees 80 (36.1%) 56 (30.4%) 33 (42.7%)
One 136 (63.0%) 55 (30.9%) 25 (34.7%)
Two 3 (0.9%) 70 (38.1%) 17 (22.7%)
Three 0 (0.0%) 2 (0.6%) 0 (0.0%)
Total 219 (100.0%) 181 (100.0%) 75 (100.0%)
Chi-Square value =103.560, df =6, p value = .000
Table 6 shows the Chi square value of p with .000.000 as 103.560. Since the p value is less than 0.01 the null hypothesis is rejected at 1% of significance. Therefore, it has been decided that there is a significant correlation between the number of employees working in a traditional retail store and their distance from the organized retail store. The number of employees working in nearby stores is less than in nearby and remote stores.
Number of Employees (Before Five Years)
The table 7 shows the number of employees working in the traditional retail store before five years on the basis of distance criteria.
Table 7 Number of Employees (Before Five Years)

Number Distance
Nearest Around Far away
No employees 109 (49.3%) 67 (36.5%) 35 (45.3%)
One 56 (26.0%) 93 (51.9%) 36 (49.3%)
Two 54 (24.7%) 21 (11.6%) 4 (5.3%)
Total 219 (100.0%) 181 (100.0%) 75 (100.0%)
Chi square value =39.722, df=4, p value= .000
The Chi square value as 39.722 with the p value .000. Hence it is concluded that there is significant association between number of employees working in traditional retail stores before five years and their distance from organized retail store.
Number of Hired Employees (Now)
The table 8 shows the number of hired employees working in traditional retail stores on the basis of distance criteria.
Table 8 Number of Hired Employees (Now)

Number Distance from organized retail store
Nearest Around Far away
No employees 120 (54.3%) 70 (38.1%) 37 (48.0%)
One 98 (45.2%) 96 (53.6%) 34 (46.7%)
Two 1 (0.5%) 15 (8.3%) 4 (5.3%)
Total 219 (100%) 181 (100%) 75 (100%)
Chi-Square value =21.742, df=4, p value= .000
The Chi square result (Chi square value =21.742, df=4, p value =.000) Shows a significant correlation between the number of employees employed in traditional retail stores (now) and their distance from the organized retail store. The number of employees hired at traditional retail stores is found to be lower at nearby retail stores than at near and far retail stores.
Number of Hired employees (Before Five Years)
The table 9 shows the hired employees working in traditional retail stores before five years on the basis of distance criteria.
Table 9 Hired Employees (Before Five Years)

Number Distance
Nearest Around Far away
No hired employees 166 (75.3%) 134 (73.5%) 71 (93.3%)
One 37 (17.4%) 43 (24.3%) 4 (6.7%)
Two 16 (7.3%) 4 (2.2%) 0 (0.0%)
Total 219 (100.0%) 181 (100.0%) 75 (100.0%)
The table 9 shows the Chi square value as 22.016 with the p value .000. Since the p value is less than 0.01 the null hypothesis is rejected at the 1% level of significance, there is a correlation between the number of employees hired to work in traditional retail stores five years ago and their distance from the organized retail store. Comparing the number of employees before and after five years, it is clear that there has been an increase in the number of employees employed in retail stores in the vicinity, in and around..
Number of Family Employees (Now)
The table 10 shows the number of family employees working in the traditional retail stores on the basis of distance criteria.
Table 10 Number of Family Employees (Now)

Number Distance from organized retail store
Nearest Around Far away
No family employees 173 (80.0%) 113 (61.9%) 59 (77.3%)
One 42 (20.0%) 67 (37.6%) 16 (22.7%)
Two 0 (0.0%) 1 (0.6%) 0 (0.0%)
Total 215 (100.0%) 181 (100.0%) 75 (100.0%)
Chi-Square value =18.150, df=4, p value =.001

The result shows the Chi square value as 18.150 with the p value .000. Since the p value is less than 0.01, the null hypothesis is rejected at the 1% level of significance. It has therefore been concluded that there is a significant correlation between the number of family employees working in traditional retail outlets (now) and their distance from organized retail outlets. From the above analysis it is clear that traditional retailers do not want more employees from the family.
Number of Family Employees (Before Five Years)
The table 11 shows the family employees working in traditional retail stores before five years on the basis of distant criteria.
Table 11 Number of Family Employees (Before Five Years)

Number Distance
Nearest Around Far away
No employees 148 (67.1%) 107 (58.9%) 24 (30.7%)
One 47 (21.9%) 64 (36.1%) 47 (64.0%)
Two 24 (11.0%) 9 (5.0%) 4 (5.3%)
Total 219 (100%) 180 (100.0%) 75 (100.0%)
Chi square value = 47. 487, df=4, p value = .000
The Chi square value as 47.487 with the p value .000, since the p value is less than 0.01 the null hypothesis is rejected at the 1% level of significance. It has therefore been concluded that there is a significant correlation between the number of employees working in traditional retail outlets five years ago based on distance criteria. Comparing the number of employees five years ago and beyond, it is clear that the number of family employees in nearby, nearby and remote retail stores has decreased. From the above analysis it has also been found that traditional retailers prefer hired employees more than family employees as they were five years ago.
Reason for Decreasing Employees
From the above analysis, it is clear that the number of employees in the traditional retail store reduced for last five years. The table 12 shows the reasons for decreasing employment in traditional retail stores.
Table 12 Reason for Decreasing Employees

Reasons Distance
Nearest Around Far away
Less profit 64 (64.3%) 4 (6.5%) 4 (18.8%)
Change to organized retail store 18 (19.4%) 12 (28.3%) 3 (25.0%)
Change to traditional retail store 11 (10.2%) 30 (63.0%) 7 (37.5%)
Demand more remuneration 5 (6.1%) 0 (2.2%) 2 (18.8%)
Total 98 (100.0%) 46 (100.0%) 16 (100.0%)
Chi square value = 64.674, df = 6, p value = .000
The table 12 shows the Chi square value as 64.674 with the p value .000. Since the p value is less than 0.01 the null hypothesis is rejected at the 1% level of significance, there is a significant correlation between the reduction of staff in traditional retail stores and their distance from the organized retail store. It has therefore been decided that there is no direct link between the reduction in the staff of traditional retailers and the appearance of organized retail outlets.
Impact on Customers per Day
This section discusses the impact of organized retailers on traditional day-to-day customers of traditional retailers. For this purpose, the researcher compares the number of clients before and after five years. The differences between the two models help establish the impact of traditional retailers on the day-to-day customers of organized retailers.
Number of Customers (Now)
The table 13 shows the number of customers per day of traditional retail stores on the basis of distance criteria.
Table 13 Number of Customers (Now)

Number Distance
Nearest Around Far away
Less than 15 12 (5.0%) 29 (15.5%) 0 (0.0%)
16-30 193 (88.6%) 54 (30.4%) 20 (25.3%)
31-50 14 (6.4%) 84 (46.4%) 55 (74.7%)
51-75 0 (0.0%) 13 (7.2%) 0 (0.0%)
More than 75 0 (0.0%) 1 (0.6%) 0 (0.0%)
Total 219 (100%) 181 (100%) 75 (100%)
Chi square value = 215.941, df = 8, p value = .000
The result shows that the Chi square value as 215.941with the p value .000. Since the p value is less than 0.01 the null hypothesis is rejected at the 1% level of significance. Therefore, it was concluded that there is a significant correlation between the distance between the customers of traditional retail stores and the distance from the organized retail store. It is clear from the above study that the number of customers is less for nearby stores than for surrounding and remote stores.
Number of Customers (Before Five Years)
The table 14 shows the number of customers per day of traditional retailers before five years on the basis of distance criteria.
Table 14 Number of Customers (Before Five Years)
Number Distance
Nearest Around Far away
Less than 15 9 (3.7%) 9 (4.4%) 5 (5.3%)
16-30 27 (12.8%) 93 (51.9%) 53 (72.0%)
31-50 182 (82.6%) 79 (43.1%) 17 (22.7%)
51-75 1 (0.9%) 0 (0.0%) 0 (0.0%)
More than 75 0 (0.0%) 0 (0.6%) 0 (0.0%)
Total 219 (100.0%) 181 (100.0%) 75 (100.0%)
Chi square value = 120.646, df =8, p value= .000
The table 14 shows the Chi square value as 120.646 with the p value .000. Since the p value is less than 0.01 the null hypothesis is rejected at the 1% level of significance. There is a correlation between the customer per day of traditional retailers five years ago and their distance from the organized retail store. So, five years ago, the number of customers at nearby and remote stores was high. From Tables 4.14 and 4.15, it is clear that there is a significant decrease in the number of customers at nearby retail stores. To find the exact difference between the groups, ANOVA tests were performed.
Table 15 Average Percentage of Customers Visit in the Store per Day (Before Five Years)
Distance N Mean SD F-value
Nearest 220 38.94 7.35
8.055 (0.000**)
Around 180 30.35 8.63
Far away 75 25.68 7.76
Total 475 33.57 9.47
**Significant at 1% level
The result found that p value is less than .01, so there is significant difference between the average number of customers per day of traditional retailers before five years and their distance from organized retail store.
Table 16 Average Percentage of Customers Visit in the Store (Now)

Distance N Mean SD F-value
Nearest 220 28.25 27.38
102.467 (0.000**)
Around 180 34.37 13.20
Far away 75 37.99 7.27
Total 475 32.12 20.89
**Significant at 1% level
The result found that p value is less than .01, there is a significant difference between the average number of customers per day of traditional retailers and their distance from the organized retail store. The average percentage of customers who come to the store per day is lower at nearby stores.
Table 17 Percentage Change in the Number of Customers for the Last Five Years
Distance N Mean (%) SD F-value
Nearest 220 -25.91 69.052

66.728 (0.000**)
Around 180 19.71 51.08
Far away 75 60.26 49.28
Total 475 5.08 67.60
**Significant at 1% level
The p value is less than .01, so it is concluded that there is significant difference between the change in the number of customers of traditional retailers for the last five years and their distance from organized retail store.
Table 18 Change in the Number of Customers for the Last Five Years

Distance Decrease Increase Total
Number Percentage Number Percentage Number Percentage
Nearest 206 93.61 15 6.39 220 100
Around 65 36.46 114 63.54 180 100
Far away 10 13.33 65 86.67 75 100
Total 281 59.16 194 40.84 475 100
Chi-Square value = 211.33, df = 2, p = 0.000

The Chi-Square result shows that p value is less than .01. It has therefore been decided that there is a significant difference between the change in the number of customers in the traditional retail store over the last five years and their distance from the organized retail store. As a result, over the past five years, the number of customers at nearby stores has dropped dramatically. It is therefore concluded that organized retailers have an impact on the number of customers of traditional retailers in the vicinity.
Reason for Decreasing Customers
From the above analysis, it is clear that the number of customers decreased for the last five years for the nearest stores. The table 19 shows the reasons for decreasing customers for the nearest, around and far away retail stores.
Table 19 Reason for Decreasing Customers

Reason Distance
Nearest Around Far away
Change to organized retail stores 206 (100.0%) 31 (45.45%) 0 (0.0%)
Change to other traditional retail stores 0 (0.0%) 35 (54.55%) 10 (100.0%)
Total 205 (100.0%) 66 (100.0%) 10 (100.0%)
Chi square value =120.599, df=2, p value .000

The table 19 shows the Chi square value as 120.599 with the p value .000. Since the p value is less than 0.01 the null hypothesis is rejected at the 1% level of significance. It has therefore been decided that there is a significant correlation between the decline of customers of traditional retailers and their distance from the organized retail outlet. Therefore, it was concluded that organized retailers have a negative effect on the number of customers of nearby stores.
Impact on Regular Customers
This section discusses the impact of organized retailers on the regular customers of traditional retailers. For this purpose, the researcher compares the number of regular customers five years ago and beyond. The differences found between the two models help to establish the impact of organized retailers on the regular customers of traditional retailers.
Number of Regular Customers
The table 20 shows the number of regular customers of traditional retail store based on their distance from organized retail store.
Table 20 Number of Regular Customers (Now)

Number Distance
Nearest Around Far away
Less than 10 160 (72.6%) 73 (39.8%) 17 (21.3%)
11-25 59 (27.4%) 89 (49.7%) 58 (78.7%)
26-40 0 (0.0%) 18 (9.4%) 0 (0.0%)
41-70 0 (0.0%) 1 (1.1%) 0 (0.0%)
Total 219 (100.0%) 181 (100.0%) 75 (100.0%)
Chi square value = 103.054, df=6, p value= .000
The Chi square value as 103.054 with the p value .000. Since the p value is less than 0.01 the null hypothesis is rejected at the 1% level of significance. It has therefore been decided that there is a significant correlation between the number of regular customers of traditional retailers and their distance from the organized retail store. Distance retailers have more regular customers than nearby and surrounding retail stores.
Number of Regular Customers before Five Years
The table 21 shows the number of regular customers of traditional retailers before five years on the basis of distance criteria.
Table 21 Number of Regular Customers before Five Years

Number Distance
Nearest Around Far away
Less than 10 34 (15.1%) 64 (34.8%) 53 (69.3%)
11-25 145 (66.7%) 111 (61.9%) 22 (30.7%)
26-40 40 (18.3%) 4 (2.2%) 0 (0.0%)
41-70 0 (0.0%) 2 (1.1%) 0 (0.0%)
Total 219 (100.0%) 181 (100.0%) 75 (100.0%)
Chi square value = 105.727, df=6, p value =.000

The table 21 shows the Chi square value as 105.727 with the p value .000. Since the p value is less than 0.01 the null hypothesis is rejected at the 1% level of significance. It was therefore decided five years ago that there was a significant correlation between the regular customers of traditional retailers and their distance from the organized retail store. Nearby retail stores have a larger number of regular customers than nearby and remote retail stores. From the two analyzes above, it is clear that the number of regular customers for nearby stores has decreased. For the past five years ANOVA trials have been conducted for a clear conclusion about the change in the regular customer base of traditional retailers.
Table 22 Average Percentage of Regular Customers per Day
Distance N Mean SD F-value
Nearest 220 10.94 4.86
46.904 (0.000**)
Around 180 17.48 7.97
Far away 75 17.69 4.84
Total 475 14.50 7.03
** Significant at 1% level
The result found that the p value is less than .01, so there is significant difference between the average percentage of regular customers per day and their distance from organized retail store. The average percentage of regular customers per day is less in nearest stores.
Table 23 Average % of Regular Customers per Day before Five Years
Distance N Mean SD F-value
Nearest 220 21.22 8.50
66.180 (0.000**)
Around 180 16.93 7.11
Far away 75 11.62 6.29
Total 475 18.07 8.38
** Significant at 1% level
The p value is less than .01, so it is concluded that there is significant difference between the change in the number of regular customers of traditional retailers before five years and their distance from organized retail store. The average percentage of regular customers before five years is high in the nearest stores followed by around and far away stores.
Table 24 Percentage Increase in Regular Customers for the Last Five Years
Distance N Mean SD F-value
Nearest 220 -39.68 37.65
126.32 (0.000**)
Around 180 23.13 77.34
Far away 75 94.85 95.38
Total 475 5.49 81.66
** Significant at 1% level
The mean score of around stores is 23.13 and far away store is 94.85, there is increment in the regular customers of far away stores followed by around stores.
Table 25 Distance Based Changes in Regular Customers

Distance Decrease Increase Total
Number Percentage Number Percentage Number Percentage
Nearest 194 88.13 27 11.87 220 100
Around 95 53.04 84 46.96 180 100
Far away 23 29.33 54 70.67 76 100
Total 310 65.47 163 34.53 474 100
Chi-Square = 105.434, df = 2, p = 0.000
The Chi square value as 105.434 with the p value .000. Since the p value is less than 0.01 the null hypothesis is rejected at the 1% level of significance. It has therefore been decided that there is a significant correlation between the number of regular customers of traditional retailers and their distance from the organized retail store. Through analysis, it is clear that the regular customers of the nearby shops have decreased, but the regular customers of the surrounding and remote stores have increased over the last five years. It is clear from this study that organized retailers have affected the regular customers of traditional retailers in the vicinity.
Socioeconomic Profile of Customers
Researchers compare the socio-economic profile of clients five years ago and beyond. The differences between the two models help customers establish the impact of organized retail.
Socioeconomic Profile of Customers
The table 26 shows the socio economic profile of customers of traditional retailers and their distance from organized retailers.
Table 26 Socioeconomic Profile of Customers

Socioeconomic profile Distance
Nearest Around Far away
Middle level 11 (4.6%) 85 (46.4%) 45 (58.7%)
Lower level 208 (95.4%) 96 (53.6%) 30 (41.3%)
Total 219 (100.0%) 181 (100.0%) 75 (100.0%)
Chi square value =122.068, df=2, p value =.000
The table 26 shows the Chi square value as 122.068 with the p value .000. There is a significant correlation between the socio-economic profile of traditional retail store customers and their distance from the organized retail store. Therefore, the socio-economic profile of most customers in nearby and surrounding stores is low, but in remote retail stores, it is moderate.
Socioeconomic Profile of Customers (Before Five Years)
The table 27 shows the socio economic profile of customers of traditional retail store before five years and their distance from organized retailers.
Table 27 Socioeconomic Profile of Customers (Before Five Years)

Socioeconomic profile Distance
Nearest Around Far away
High level 9 (3.7%) 2 (0.6%) 1 (0.0%)
Middle level 208 (95.4%) 176 (97.8%) 43 (58.7%)
Lower level 2 (0.9%) 3 (1.7%) 31 (41.3%)
Total 219 (100.0%) 181 (100.0%) 75 (100.0%)
Chi square value =150.724, df=4, p value= .000
The table 27 shows the Chi square value as 150.724 with the p value .000. It was therefore decided five years ago that there was a correlation between the socio-economic profile of the customers of traditional retail outlets and their distance from the organized retailers. Five years ago, the socio-economic profile of the majority of customers at traditional retail stores was mediocre. From the analysis of the socio-economic profile of the customers, it is clear that the socio-economic profile of the customers of the nearby and nearby shops has been shifted from the middle to the lower level.
Impact on Profit
Traditional retailers, which are close to organized retailers, experienced a decline in their business size and profitability in the early years after the entry of large organized retailers. This division deals with the effect of organized retailers on the profits of traditional retailers.
Average Daily Profit
Table 28 analyzes the average daily profits of traditional retail outlets and their distance from the organized retail outlet. To find out the impact of organized retailers on the average daily profit of traditional retailers, the researcher compared current profits to profits from five years ago. The difference refers to the impact on profit.
Table 28 Average Daily Profit (Now)
Daily profit Distance
Nearest Around Far away
less than 250 6 (2.3%) 15 (7.7%) 0 (0.0%)
251-500 145 (66.7%) 37 (21.0%) 5 (5.3%)
501-1000 68 (31.1%) 50 (27.6%) 54 (73.3%)
1001-2000 0 (0.0%) 41 (22.7%) 16 (21.3%)
2001-4000 0 (0.0%) 38 (21.0%) 0 (0.0%)
Total 219 (100.0%) 181 (100.0%) 75 (100.0%)
Chi square value = 233.744, df=8, p value =.000

The table 28 shows the Chi square value as 233.744 with the p value .000. Since the p value is less than 0.01 the null hypothesis is rejected at the 1% level of significance. There is a significant correlation between the average daily profit of traditional retail stores and their distance from the organized retail store. It has been decided that the average daily profit of the nearest store is less as compared to the nearest and remote stores.
Average Daily Profit before Five Years
The table 29 shows the average daily profit of traditional retailers before five years on the basis of distance criteria.
Table 29 Average Daily Profit before Five Years
Daily profit Distance
Nearest Around Far away
Less than 250 3 (0.9%) 0 (0.0%) 0 (0.0%)
251-500 19 (9.1%) 29 (15.5%) 49 (64.0%)
501-1000 158 (72.6%) 110 (61.3%) 13 (18.7%)
1001-2000 39 (17.4%) 38 (20.4%) 5 (5.3%)
2001-4000 0 (0.0%) 4(2.8%) 8 (12.0%)
Total 219 (100.0%) 181 (100.0%) 75 (100.0%)
Chi square value = 150.839, df=8, p value= .000
The above table shows the Chi square value as 150.839 with the p value .000. There is a significant correlation between the average daily profit of traditional retailers five years ago in terms of distance measurements. Five years ago, it was decided that the profit of the nearest store would be higher compared to the nearest and remote stores. ANOVA trials were conducted to obtain a clear conclusion about the change in the profits of traditional retailers over the past five years.
Table 30 Present Average Profit per Day in the Shop
Distance N Mean SD F-value
Nearest 220 444.20 156.05
83.239 (0.000**)
Around 180 1230.66 943.98
Far away 75 864.00 344.99
Total 475 810.168 705.71
** Significant at 1% level
Since the p value is less than 0.01 the null hypothesis is rejected at the 1% level of significance. It was concluded that there is a significant difference in the average profit of traditional retail outlets in terms of distance from the organized retail outlet. The average profit per day is lower than nearby and remote stores.
Table 31 Average Profit per Day in the Shop before Five Years
Distance N Mean SD F-value
Nearest 220 880.14 369.82
0.266 (p=0.767)
Around 180 842.93 461.85
Far away 75 876.00 920.32
Total 475 865.30 525.78
The result found that there is no significant difference between average profit per day of traditional stores before five years and their distance from organized retail store.
Table 32 Percentage Changes in the Profit per Day for the Last Five Years
Distance N Mean SD F-value
Nearest 220 -44.7258 24.26
33.383 (0.000**)
Around 180 69.5227 228.21
Far away 75 42.5173 52.72
Total 475 12.5841 152.90
** Significant at 1% level
Since the p value is less than 0.01, the null hypothesis is rejected at the 1% level of significance. There is significant difference between the changes in average profit per day of traditional stores for the last five years and their distance from organized retail store.
Table 33 Average Profit per Day for the Last Five Years

Distance Decrease Increase Total
Number Percentage Number Percentage Number Percentage
Nearest 213 96.80 8 3.20 220 100
Around 85 47.51 94 52.49 180 100
Far away 15 20.00 60 80.00 75 100
Total 313 65.89 162 34.11 475 100
Chi-Square value = 190.60, df = 2, p = 0.000
The Chi square value as 190.60 with the p value .000. Since the p value is less than 0.01, the null hypothesis is rejected at the 1% level of significance. It has therefore been concluded that there is a significant correlation between the changes in average profit per day over the past five years and their distance from the organized retail outlet. From the analysis, it is clear that the daily profit of the nearby stores has decreased, but for the surrounding and remote stores, the profit has increased over the last five years. It is clear from this study that organized retailers are affected by the profits of traditional retailers nearby area.
Reasons for Decreasing Average Daily Profit
It is clear that the profit of the nearest store has decreased as compared to the profit of the previous five years, but in the surrounding and remote stores, there is a significant increase in the profit. The reasons for the decline in average daily profits in this area were discussed.
Table 34 Reasons for Decreasing Average Daily Profit
Reasons Distance
Nearest Around Far away
Competition from organized retailers 210 (96.8%) 34 (53.2%) 0 (0.0%)
Competition from traditional retailer 6 (3.2%) 25 (41.9%) 13 (100.0%)
Reduce value of money 0 (0.0%) 3 (4.8%) 0 (0.0%)
Total 216 (100.0%) 62 (100.0%) 13 (100.0%)

The Chi square result shows that the p value is less than 0.01 the null hypothesis is rejected at the 1% level of significance. Hence it is concluded that there is significant association between reasons for decreasing daily profit of traditional retailers and their distance from organized retail stores.
Profit per Month
The unorganized retailers operating in the vicinity of modern retail stores have indeed felt an impact in terms of decline in sales and profit margins. The table 35 shows the monthly profit of traditional retailers on the basis of distance criteria.
Table 35 Profit per Month
Profit Distance
Nearest Around Far away
Less than 3000 3 (0.9%) 25 (13.3%) 0 (0.0%)
3001-5000 120 (55.3%) 12 (7.2%) 5 (5.3%)
5001-7000 80 (36.1%) 19 (9.9%) 26 (36.0%)
7001-15000 16 (7.8%) 17 (9.9%) 32 (41.3%)
15001-25000 0 (0.0%) 54 (30.4%) 12 (17.3%)
More than 25000 0 (0.0%) 52 (29.3%) 0 (0.0%)
Total 219 (100.0%) 181 (100.0%) 75 (100.0%)
Chi square value 356.958, df=10, p value .000

The result shows the Chi square value as 356.958 with the p value .000. Since the p value is less than 0.01 the null hypothesis is rejected at the 1% level of significance. Therefore, it has been concluded that there is a significant correlation between the percentage of average monthly profit of traditional stores and their distance from organized retail stores. Monthly profits of nearby traditional stores are lower than those of nearby and remote stores.
Profit per Month before Five Years
To find the effect of organized retailers on traditional retailers' profits, the researcher compares current profits with profits from five years ago Table 36 shows the monthly profits of traditional retailers five years ago.
Table 36 Profit per Month before Five Years
Average Profit Distance
Nearest Around Far away
Less than 3000 0 (0.0%) 0 (0.0%) 5 (5.3%)
3001-5000 19 (8.2%) 33 (17.7%) 25 (34.7%)
5001-7000 94 (42.5%) 16 (9.4%) 29 (33.3%)
7001-15000 88 (39.7%) 89 (48.6%) 0 (0.0%)
15001-25000 20 (9.6%) 38 (21.5%) 9 (13.3%)
More than 25000 0 (0.0%) 5 (2.8%) 10 (13.3%)
Total 219 (100.0%) 181 (100.0%) 75 (100.0%)
Chi square value = 161.439, df=10, p value =.000

The table 4.37 shows the Chi square value as 161.439 with the p value .000. Since the p value is less than 0.01, the null hypothesis is rejected at the 1% level of significance. There is a significant correlation between the average profit for a month five years ago and the distance from the organized retail store. From the comparison of the two tables above, it is clear that the average profit of the nearby stores has decreased after the arrival of the organized retailers.
Reasons for Decreasing Average Monthly Income
The table 37 shows the reasons for decreasing average monthly income
Table 37 Reasons for Decreasing Average Monthly Income

Reason Distance
Nearest Around Far away
Competition from organized retailers 214 (100.0%) 40 (62.9%) 0 (0.0%)
Competition from traditional retailer 0 (0.0%) 22 (37.1%) 13 (100.0%)
Total 214 (100.0%) 62 (100.0%) 13 (100.0%)
Chi square value=156.936, df=2, p=.000

The chi square result shows that there is significant association between the average monthly income of traditional retailers and their distance from organized retailers.