Description
This is presentation explains the feasibility study on setting up restaurant.
Marketing Research
“Feasibility Study for setting up non-South Indian Restaurant in Manipal”
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Introduction:
Restaurants in Manipal: Manipal, better known as education town of India is located in the district of Udupi which is famous for its south Indian cuisine. Also due to huge student population from various parts of country and abroad in Manipal non-south Indian restaurants in this region are also prospering. Student population which ranges form 18,000-22,000 can often be found in many of these restaurants in Manipal especially during weekends. All the cuisine from North Indian to Mughlai, fast food to sea food, Chinese to Continental is available in Manipal and they have a sufficient customer base to serve. Non South Indian Restaurant: With ever increasing student population from various parts of the country in Manipal, the restaurant business is an attractive business opportunity for an entrepreneur. There are some existing restaurants in Manipal who have been serving to these needs for a long time. These restaurants differ from each other on various parameters such as: ? ? ? Type of food they serve Price Ambience of the restaurant
Except these parameters the students also look for other parameters such as Hygiene, Proximity to College/Hostel and additional services provided (ex-Home Delivery, Night Canteen) According to the need of the student, he/she selects a restaurant and often they become a regular customer of that restaurant. Hence these factors are important for any restaurant as they may become a point of difference for the success of the business. Products/Services Offered: Restaurants in Manipal offer different products/Services to the student population. These services range from type of food they offer to the price. Each of these restaurants caters to different need and often these services become the USP of the restaurant. In our feasibility study we specifically asked this question to the owners of the restaurant and they come up with mixed answers. Some believed that their Multiple Cuisine was their USP and some believed ambience as their USP.
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Rationale of the Project: The rationale behind this feasibility study was to do a need-gap analysis of non-south Indian restaurant in Manipal and the positioning strategy that an entrepreneur should aim. Objective of the Project: “Profile the current eateries catering to the non-Kannada students of Manipal. Undertake a feasibility study for setting up a non-South Indian restaurant in Manipal” The objective of our project was to find the feasibility of setting up a non-south Indian restaurant specifically for the student of Manipal. This required us to collect data from both the students as well as the various restaurants in Manipal. The reason for collecting the data from both the student as well as restaurant was to find the perception of both the parties. Also this helped as to do need-gap analysis. Scope of the Project: This feasibility study was restricted for only Manipal Students and not the local people of Manipal/Udupi. The scope of the study was for the restaurants hence canteens/mess is not included in the study.
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Research Method and Procedures:
The research methodology is a mix of both quantitative and qualitative analysis. We aim to gather responses and quantify them to find the feasibility of Kannada eateries in Manipal. The qualitative aspect would be the gathering of aspired data and opinions regarding Kannada joints in Manipal. Keeping in mind the research objective we formulated a set of dummy findings which would help us devise our questionnaire and the direction of our research. We identified the following set of dummy findings Dummy findings: 1) The demographics based on Kannada and Non-Kannada students 2) The profile of eateries based on Kannada, Non-Kannada and mixed 3) Count of students which visit Non-Kannada eateries and their demographics 4) The frequency with which sample visit Non-Kannada eateries 5) The timings when most revenue is generated and the cuisine type which generates maximum revenue 6) Revenue generator during non-peak seasons (holidays, vacation, college holidays) 7) The additional services which are preferred by the students (home delivery, music, bar etc) 8) The additional services offered by the restaurant owners 9) The need-gap analysis 10) Perception of the students towards the existing Non-Kannada eateries present in Manipal in terms of taste, price, ambience, additional services, hygiene 11) The timings of the restaurant and the difference between Kannada and Non-Kannada eateries on this parameter 12) The impact of location on the popularity of the eatery Based on the above dummy findings we decided to target the restaurants and student population in Manipal. The strategy for data collection would be same for both through questionnaire but the questions would be different and then we would correlate the responses using research tools like SPSS
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The questions contain data where in we have captured the data regarding their nationality, region of origin, hence capturing demographics required for student profiling (Ref Appendix-I) We also profiled the restaurants in the same manner (Ref. Appendix –II)
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Data Analysis and Findings:
A set of analysis were carried out on the data obtained through the questionnaire.
One-Way ANOVA The objective of this test is to find out how the cuisine preference varies among the respondents based on the zone (North, East, South and West) of India where there hometown belongs to . The test is made under the assumption that the food preferences or the type of food available within the zones would be similar. For example, in South India common set of foods like dosa, idli, sambar, South Indian Fish Curry etc are available which are popular in entire South India. Moreover, we had classified the restaurant categories as South Indian and non-South Indian. So dividing the respondents based on zones would be a better option. The respondents we got belonged to states West Bengal, Orissa, Maharashtra, Gujarat, Delhi, Bihar, Uttar Pradesh, Chhattisgarh, Madhya Pradesh, Haryana, Jharkhand, Rajasthan, Tamil Nadu, Karnataka, Kerala and Pondicherry. So the classifications into zones are as follows: ? EAST ? WEST
- West Bengal, Orissa - Maharashtra, Gujarat
? NORTH - Delhi, Bihar, Uttar Pradesh, Chhattisgarh, Madhya Pradesh, Haryana, Jharkhand, Rajasthan ? SOUTH - Tamil Nadu, Karnataka, Kerala and Pondicherry
The cuisines were classified as Chinese, Continental, Fast food, Multi cuisine, South Indian and North Indian. The respondents were asked to rank on the basis of their preference. The screen shot of the relevant questions for this analysis from the questionnaire we uploaded in surveymonkey is attached below
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Now the after classifying the respondents based on zones, the zones are codified as EAST - 1, WEST – 2, NORTH – 3, SOUTH – 4. So with one-way ANOVA we can answer the following questions. Is there any significant difference in preference among different zones for a particular cuisine? What is the average ranking given by each zone for a particular cuisine?
The Rankings we got for Chinese, Continental, Fast food, Multi cuisine, South Indian and North Indian cuisines for each respondent are tabulated with their corresponding zone codes. The analysis for one-way ANOVA is done in SPSS. The rankings we obtained for various cuisines are given in the dependent list and the zone code is given as the factor.
OUTPUT
ANOVA Sum of Squares Chinese Between Groups 3.671 df 3 Mean Square 1.224 F .601 Sig. .618
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Within Groups Total NorthIndian Between Groups Within Groups Total Continental Between Groups Within Groups Total SouthIndian Between Groups Within Groups Total Fastfood Between Groups Within Groups Total Multicuisine Between Groups Within Groups Total
85.546 89.217 28.696 58.283 86.978 8.227 85.686 93.913 53.393 104.542 157.935 5.312 95.993 101.304 4.632 120.172 124.804
42 45 3 42 45 3 42 45 3 42 45 3 42 45 3 42 45
2.037
9.565 1.388
6.893
.001
2.742 2.040
1.344
.273
17.798 2.489
7.150
.001
1.771 2.286
.775
.515
1.544 2.861
.540
.658
The null hypothesis is that there is no significant difference in cuisine preference among each zone. For 95% confidence level this null hypothesis is accepted for Chinese, Continental, Fast Food and Multicuisine. That is there is no significant difference
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between their preferences among different zones. But for South Indian and North Indian cuisines the null hypothesis is rejected for 95% confidence level as the significance level is .001. So there is a significant difference among the preference of north Indian and south Indian cuisines among different zones. Descriptives 95% Confidence Interval for Mean Std. N Chinese 1 2 3 4 Total NorthIn 1 dian 2 3 4 Total Contine 1 ntal 2 3 4 Total SouthIn 1 7 8 14 17 46 7 8 14 17 46 7 8 14 17 46 7 Mean Deviation Std. Error Lower Bound 2.57 3.00 3.14 3.41 3.13 1.43 2.38 1.07 2.88 2.02 4.00 3.12 3.93 4.35 3.96 5.43 1.134 1.414 1.027 1.770 1.408 .787 1.408 .267 1.576 1.390 1.633 1.246 1.685 1.169 1.445 .787 .429 .500 .275 .429 .208 .297 .498 .071 .382 .205 .617 .441 .450 .284 .213 .297 1.52 1.82 2.55 2.50 2.71 .70 1.20 .92 2.07 1.61 2.49 2.08 2.96 3.75 3.53 4.70 Upper Bound 3.62 4.18 3.74 4.32 3.55 2.16 3.55 1.23 3.69 2.43 5.51 4.17 4.90 4.95 4.39 6.16 Minimu Maxim m 1 2 2 1 1 1 1 1 1 1 2 1 2 2 1 4 um 4 6 5 6 6 3 5 2 6 6 6 5 6 6 6 6
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dian
2 3 4 Total
8 14 17 46 7 8 14 17 46 7 8 14 17 46
3.00 4.79 2.82 3.85 4.00 3.38 3.00 3.59 3.43 3.57 4.50 4.07 3.71 3.93
1.852 1.251 1.879 1.873 1.528 1.598 1.359 1.583 1.500 1.397 1.690 1.269 2.054 1.665
.655 .334 .456 .276 .577 .565 .363 .384 .221 .528 .598 .339 .498 .246
1.45 4.06 1.86 3.29 2.59 2.04 2.22 2.77 2.99 2.28 3.09 3.34 2.65 3.44
4.55 5.51 3.79 4.40 5.41 4.71 3.78 4.40 3.88 4.86 5.91 4.80 4.76 4.43
1 2 1 1 2 1 1 1 1 1 2 3 1 1
6 6 6 6 6 5 5 6 6 5 6 6 6 6
Fastfoo 1 d 2 3 4 Total Multicui 1 sine 2 3 4 Total
We already found out that significant difference between zones is observed for North Indian and South Indian cuisines where as the other cuisines exhibit almost similar preference in all zones. For Chinese cuisines we can see that the preference among zones is almost same. The preference rankings range from a least rank of 3.41(South zone represented by 4) to a maximum rank of 2.57(East zone represented by 1) with a mean ranking of 3.13 across all zones. Since the mean ranking is 3.13 out of 6 we can interpret that Chinese cuisine is liked by the population here.
For Continental cuisines we can see that the preference among zones is almost same. The preference rankings range from a least rank of 4.35(South zone represented by 4) to a
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maximum rank of 3.12(East zone represented by 1) with a mean ranking of 3.96 across all zones. Since the mean ranking is 3.96 out of 6 we can interpret that the preference of Continental cuisine is not that good.
For Fast food cuisines we can see that the preference among zones is almost same. The preference rankings range from a least rank of 4.00(East zone represented by 1) to a maximum rank of 3.00(West zone represented by 4) with a mean ranking of 3.43 across all zones. Since the mean ranking is 3.43 out of 6 we can interpret that the preference of Fast Food cuisine is pretty ok.
For Multi Cuisine we can see that the preference among zones is almost same. The preference rankings range from a least rank of 4.50(West zone represented by 1) to a maximum rank of 3.57(South zone represented by 4) with a mean ranking of 3943 across all zones. Since the mean ranking is 3.93 out of 6 we can interpret that the preference of Multi Cuisine is not that good.
For South Indian food we can see that there is a significant difference in preference given by different zones. The preference rankings range from a least rank of 5.43(East zone represented by 1) to a maximum rank of 2.82(South zone represented by 4) with a mean ranking of 3.85 across all zones. The ranking given by West zone is 3.00 and North zone is 4.79. The mean is coming to be 3.85 which prove that south Indian food is not among the highly preferred food category in Manipal. Moreover the highest rank is only 2.82 given by South Indian people, which proves that even South Indians didn’t rank it as their number one choice.
For North Indian food we can see that there is a significant difference in preference given by different zones. The preference rankings range from a least rank of 2.88(South zone represented by 4) to a maximum rank of 1.07(North zone represented by 3) with a mean ranking of 2.02 across all zones. The ranking given by West zone is 2.88 and East zone is 1.43. The mean is coming to be 2.02 which prove that north Indian food is the highly preferred food category in Manipal. Moreover the lowest rank is only 2.88 given
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by South Indian people, which proves that even South Indians consider North Indian food on par with South Indian food. The food categories are listed based on their mean rankings below
Mean Food Category North Indian foods Chinese foods Fast foods South Indian foods Multi cuisine Continental foods 3.96 3.85 3.93 2.02 3.13 3.43 Ranking
We can see that North Indian, Chinese and Fast foods are ranked above South Indian foods, even though 37% of the respondents constitute south Indian people. FACTOR ANALYSIS Here we use two sets of data. One is filled by the students who rank various factors they prefer in a restaurant. The factors are mainly Taste, Price, Cuisine Availability, Ambience, hygiene, Proximity to college and additional services (bar, dance floor etc).
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Similarly , the same set of factors were ranked by the restaurant owners based on their perception of what students feel is important. We did factor analysis for both these data.
Factor analysis result for student preference data
Total Variance Explained Extraction Sums of Squared Com pon ent 1 2 3 4 5 6 Total 2.087 1.492 .982 .843 .789 .646 Initial Eigenvalues % of Variance 29.815 21.312 14.028 12.040 11.275 9.222 Cumulative % 29.815 51.127 65.155 77.195 88.469 97.691 Total 2.087 1.492 Loadings % of Cumula Total 2.016 1.563 Rotation Sums of Squared Loadings % of Variance Cumula tive %
Variance tive % 29.815 29.815 21.312 51.127
28.804 28.804 22.324 51.127
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Total Variance Explained Extraction Sums of Squared Com pon ent 1 2 3 4 5 6 7 Total 2.087 1.492 .982 .843 .789 .646 .162 Initial Eigenvalues % of Variance 29.815 21.312 14.028 12.040 11.275 9.222 2.309 Cumulative % 29.815 51.127 65.155 77.195 88.469 97.691 100.000 Total 2.087 1.492 Loadings % of Cumula Total 2.016 1.563 Rotation Sums of Squared Loadings % of Variance Cumula tive %
Variance tive % 29.815 29.815 21.312 51.127
28.804 28.804 22.324 51.127
Extraction Method: Principal Component Analysis.
We have two components for which the eigen values are above 1. So the total 7 factors can be classified into 2 components.
Rotated Component Matrixa Component 1 Taste Price AvailabilityCuisine Ambience Hygiene -.225 .219 .373 .621 .239 2 .676 -.449 .529 -.083 .718
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proximitytohostel Additionalservicesprovi ded
.736 .891
-.162 .275
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
Under component 1 we have factor s “additional services”, “proximity to hostel”, ambience, cuisine availability making significant impact of 0.891, 0.736 and 0.621 respectively. Under component 2 we have factors “hygiene”, “taste” making significant impact of 0.718, 0.676 respectively. Cuisine availability also comes under component 2 with a value of 0.529. Price doesn’t have any impact on both components and doesn’t contribute to any variation. So we can conclude that according to students important factors are “additional Services”, “Proximity to hostel” and “Ambience”. This is followed by “hygiene” and “taste”.
Factor analysis result for restaurant owner’s perception about student preference
Total Variance Explained Extraction Sums of Initial Eigen values Compo nent 1 2 3 Total 1.929 1.645 1.287 % of Variance 32.152 27.410 21.450 Cumulativ e% 32.152 59.562 81.012 Squared Loadings % of Total Variance 1.929 1.645 1.287 Cumulat ive % Total 1.825 1.570 1.466 Rotation Sums of Squared Loadings % of Variance 30.418 26.168 24.426 Cumulative % 30.418 56.586 81.012
32.152 32.152 27.410 59.562 21.450 81.012
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4 5 6
.758 .244 .137
12.637 4.060 2.290
93.650 97.710 100.000
Extraction Method: Principal Component Analysis.
We have three components for which the eigen values are above 1. So the total 6 factors can be classified into 3 components. Rotated Component Matrixa Component 1 Taste Price Cuisineavailabilit y Ambience Hygiene Additionalservice s -.125 .098 .668 -.146 .885 .741 2 .752 .934 -.087 -.047 -.241 .255 3 -.399 .139 .568 .962 -.195 -.012
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 4 iterations. Under component 1 we have factors “Hygiene”, “Additional Services”, “ cuisine availability” making significant impact of 0.885,.0.741 and 0.668 respectively. Under component 2 we have
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factors “Price”, “taste” making significant impact of 0.934, 0.752 respectively. Under component 3 we have factor “Ambience”, making significant impact of 0.962. So we can conclude that restaurant owners perceive important factors to be “Hygiene”, “Additional Services”, “cuisine availability”. This is followed by “Price”, “taste” and “ambience”. We can finally conclude that factors like “Additional services”, Hygiene and taste are perceived important by both students and restaurant owners. But Restaurant owners consider “price” as an important factor for students turn out, but that is not the case with students, they don’t consider price as an important factor, if other facilities are available. Perceptual Mapping: Perceptual mapping is similar to multidimensional scaling, where we try to understand how the respondents or the potential customers perceive the product or a particular brand based on a set of attributes. There are two ways to do perceptual mapping – by using factor analysis and by using discriminant analysis. Here using perceptual mapping using discriminant analysis let us analyse how the respondents perceive the three different kinds of eateries such as South Indian, North Indian/Moghlai and Multi Cuisine based on the following attributes: Taste, Price, Hygiene, Ambience, Available Cuisine and Additional Service. Data was collected from 46 respondents and each respondent were asked to rate each kind of eatery for all the attributes. This means there is a total of 46 x 3 responses. All the attributes were measured on a 5-point Likert scale (0 – very poor to 4 – excellent). This means that a higher value has a better rating. Discriminant Analysis Output: Let us have a look at the Discriminant Analysis output. Then we shall draw a Perceptual map between the two functions and find out how the attributes are perceived. The Group Statistics shows the mean value and its standard deviation for different attributes (all the values are on Likert scale) and Eatery Type. Hotel Types are represented as follows: 1 – South Indian
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2 – North Indian / Moghlai 3 – Multi Cuisine Group Statistics Valid N (listwise) Hotel_Type 1 Taste Price Availability_Cuisine Ambience Hygiene Additional_Services 2 Taste Price Availability_Cuisine Ambience Hygiene Additional_Services 3 Taste Price Availability_Cuisine Ambience Hygiene Additional_Services Total Taste Price Mean 2.35 2.87 1.98 1.65 1.76 1.30 2.89 2.00 2.63 2.80 2.52 2.13 2.46 1.87 2.52 2.54 2.43 2.07 2.57 2.25 Std. Deviation .795 .833 .931 .875 .794 .866 .795 .869 .771 .687 .691 .885 .936 .909 .809 .780 .688 .879 .871 .973 Unweighted 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 138 138 Weighted 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 138.000 138.000
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Availability_Cuisine Ambience Hygiene Additional_Services
2.38 2.33 2.24 1.83
.881 .923 .797 .948
138 138 138 138
138.000 138.000 138.000 138.000
The Wilk’s Lambda describes how significant is the discriminant function. The value lies between 0 and 1. Closer the value to 0 means higher the significant. Here, we see that the Wilk’s Lambda is 0.450. Hence the function is considerably significant.
Wilks' Lambda Test of Function(s) 1 through 2 2 Wilks' Lambda .450 .944 Chi-square 105.745 7.622 df 12 5 Sig. .000 .178
The table below shows that the Eigen value is 1.097. This is also a significant value, thus meaning that the model is good. Eigen Values Functio Eigenvalu n 1 2 e 1.097a .059a Canonical % of Variance Cumulative % Correlation 94.9 5.1 94.9 100.0 .723 .236
a. First 2 canonical discriminant functions were used in the analysis.
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The standardized canonical discriminant function coefficients are tabulated below. Using the coefficients for the attributes, the perceptual map is drawn. From the table below, it is seen that in Function 1, the Price is a significant factor since its coefficient has the highest magnitude. Similarly, Taste is a significant factor in Function 2.
Standardized Canonical Discriminant Function Coefficients Function 1 Taste Price Availability_Cuisine Ambience Hygiene Additional_Services .409 -.965 .165 .364 .248 .173 2 1.111 .062 -.463 .408 -.516 -.116
The coordinates for the Hotel type are given below. It is plotted in the Canonical Discriminant Function, we see that the three types of eateries (here: mentioned as Hotel_Type 1, 2 and 3) lie in three separate quadrants, though the North Indian and Multi Cuisine lie too closely. We can conclude that people perceive distinctly about the three eateries. The Canonical Discriminant Function graph also shows the plots for each response for each eatery.
Functions at Group Centroids Function Hotel_Type 1 2 3 1 -1.458 .855 .603 2 .034 .276 -.310
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Functions at Group Centroids Function Hotel_Type 1 2 3 1 -1.458 .855 .603 2 .034 .276 -.310
Unstandardized canonical discriminant functions evaluated at group means
From the perceptual map plotted for Eatery type and its attributes, we can infer the following:
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1. South Indian eateries lie close to the Pricing line. This means that the people who go to South Indian eateries are concerned about the price of the food. This is evident because the food is charged low compared to any other type of eateries. 2. North Indian eateries lie closer to the Taste line and Ambience line. This means that the people who go to the North Indian eateries are more concerned about the taste of the food and the ambience of the hotel than any other attributes. 3. The Multi Cuisine eateries lie close to the Hygiene line, cuisine availability and additional services (like attached Bar, TV, pool/snooker, etc). This means that the people perceive Multi Cuisines to be more hygienic and also expects a larger variety of food to be available. It is also not surprising that the pricing line and the multi cuisine lie in two opposite quadrants!
Perceptual Map of Eatery type and Attributes Taste
1.2 1 0.8 0.6 Function 1 0.4 South Indian -1 -0.2 Multi Cuisine -0.4 -0.6 Function 2 0.2 0 -2 0 North Indian/Moghlai 1 Price Availability_Cuisine Ambience Hygiene Additional_Services
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Conclusions and Recommendations:
? Since North Indian foods are preferred by both North Indians and South Indians equally, and North Indian food, Chinese, Fast food are ranked above south Indian foods; we conclude that it is very much feasible to start a non- south Indian Eatery in Manipal. ? From the factor analysis findings, we can conclude that instead of having a low price we have to go for additional services, proximity to location, ambience, hygiene and taste in order to attract the student crowd of Manipal. ? From perceptual mapping we can conclude that food pricing is a major factor while opening a South Indian eatery. It is also seen from the survey that people prefer South Indian eateries for breakfast more than any other eatery. Similarly Multi Cuisine restaurants are expected to have wider choices of cuisines (a bigger menu) along with additional facilities like attached bar or TV or pool/snooker board, etc. The attributes that are important for opening a North Indian eatery is (or the customers are particular about) the taste of the food and the ambience of the hotel.
Limitations:
1. The number of responses was 46. This was mainly due to the time constraint available for the survey. The results could have been predicted even better had the response size been higher. 2. Some of the responses were filled for the sake of attempting the survey and the respondents did not pay attention to give true figure. This was mainly due to fatigue caused to the respondents as they had already attempted similar online survey. Hence some of the responses did not truly represent the expected output although the final output gave a true picture. 3. Some of the responses collected from the eatery owners were reluctant in sharing certain data such as Monthly sales and Price range of the food available in their eatery.
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Appendices:
Questionnaire for Students: 1. Which university/college ________________________________________ 2. Gender : Male ( ) Female ( )
3. Nationality: __________ 4. If Indian, which state do you belong to? ______________________________ 5. How often do you eat outside food (other than hostel mess) in a week? Please tick any one. Daily 3-5 times 1-2 times Never
6. Rate the following services provided by restaurants/hotels/eateries on a scale of 1-5 (1 – most important and 5-least important) Services Home delivery Timeliness Bar Television/ Live telecast Dance floor Timing (Opening and closing) Desserts Mode of payments (Credit card, cash etc.) 1 2 3 4 5
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MKRH Project 7. Which are the places you frequent for meals and when? (Tick more than 1 if applicable.) Eatery types Pure South-Indian eateries (eg. Pangal, Anupam, Andhra mess, Annapurna, Samudra,Fishland) Non-South Indian eateries (eg. Hang Yo CTF, tasty bites, snack shack, Saiba, China Valley, Paratha Point, Dollops, Guzzlers, Rajasthani mess, Parmesh mess, Basil, Dominoes, Lil' chef, Cosmo café) Mixed Cuisine (eg. Atithi, KC café, Food court,Dollops) If others, specify Breakfast Lunch
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Dinner
8. Which cuisine is preferred by you? Rank them in the order of your preference (1- Highest, 7Lowest) Type of cuisine Chinese Moghlai/ North Indian Continental South-Indian Fast food Multi cuisine Rank
9. Which of the following factors are the criteria for selection of restaurant? Rate them in the order of importance (1- Highest, 7- Lowest) Selection criteria Taste Price Availability Cuisine Rank
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10. Rate the eateries on a scale of 1-5 based on the factors mentioned. (1- Excellent and 5- Very Poor)? 1 Excellent 2 Good 3 Satisfactory 4 Bad 5 Very poor
Types of Eateries Taste South Indian eateries (Pangal, Anupam, Andhra mess, Annapurna,Samudra, Fishland) Price
Factors
Availability Cuisine Ambience Hygiene Additional services Taste Price Availability Cuisine Ambience Hygiene Additional services Taste Price Availability Cuisine Ambience Hygiene Additional services
Non South Indian eateries (HangYo,Guzzlers,Basil, Tastybites, SnackShack, Saiba, ChinaValley,Dominoes ParathaPoint, Rajasthani/Bihari mess, LilChef, CosmoCafé)
Mixed Cuisine (Atithi, KC café, Food court, Dollops,)
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MKRH Project Questionnaire for Restaurant/ Hotel/ Eateries:
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1) Name of the establishment: _________________________ 2) Location: _________________________________ 3) What are the Cuisines offered by you? (Tick wherever applicable) Type of cuisine Chinese Moghlai/ North Indian Continental South-Indian Fast food Multi cuisine 4) What are the timings of your restaurant? ___________________________________ 5) Which cuisine according to you generates more sales? a. South Indian b. Others c. Both generate almost same revenue
6) When do you generate maximum sales? Breakfast Lunch Snacks Dinner 7) What is the USP of your restaurant?__________________________________________
8) What are the additional services provided by you? (Tick whichever applicable) Services Home delivery Timeliness 27
MKRH Project Bar Television Dance floor Timing (Opening and closing) Mode of payments (Credit card, cash etc.)
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9) Which of the factors according to you are preferred by the students? (Rank them in order of importance, 1- Highest and 7- Lowest) Factors Taste Price Availability Cuisine Ambience Hygiene Additional services provided 10) Please specify the range of price offered on your menu. 11) Which cuisine sells more in non-peak season? a. South Indian b. Others _______ _______ Rank
c. Both generate almost same revenue
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We visited different places in Manipal to get the responses for our research purpose. We surveyed a total of 46 students of which 39 were male and 7 were female. Since, our research needs students from different regions; we tried to get respondents from all the four regions i.e. east, west, north and south. We managed to get maximum respondents from south and north regions but could not get more respondents from east and west regions. Following graphs and table show the demographical and geographical details of our respondents: Region North East South West No. of Respondents 14 7 17 8
Zone
North East South West
14, 31% 8, 17% 7, 15%
17, 37%
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Gender
Male Female
7, 15%
39, 85%
We decided to obtain the data for consuming food outside by students from all the regions. It helped us find their behaviour on eating outside. Results show that it is very important finding to decide on feasibility of opening a new restaurant. We can see 74% of the respondents eat at outside eateries 1 to 3 times per week and 22% of total eat 4 to 6 times per week. We have these data region-wise, which can help decide demand of food preferred by students from different regions.
Frequency of eating outside per week Never 1 - 3 times 4- 6 times Daily
North 0 10 4 0
East 0 6 1 0
South 1 12 4 0
West 1 6 1 0
Total 2 34 10 0
Percentage 4% 74% 22% 0%
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Weekly outside food consumption
35 30 25 20 15 10 5 0 Never 1 - 3 times 4- 6 times Daily West South East North
We collected the data on preference of food by students for breakfast, lunch and dinner. We allowed them to mark more than one option. This would avoid in getting biased or incorrect preferences for a particular food. We have found most of the students prefer to have non-south Indian and multi-cuisine food for their lunch and dinner and prefer south Indian food for their breakfast. These data is really important to decide offering to be made to attract most of the customers for all the meals. Type of food South Indian Non-south Indian Multi-cuisine Others Breakfast 23 3 3 2 Lunch 14 24 17 3 Dinner 15 42 36 5 Total 52 69 56 10
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Preferred food for breakfast
South Indian Non-south Indian Multi-cuisine Others
10% 10%
6%
74%
Preferred food for lunch
South Indian Non-south Indian 5% 29% 24% Multi-cuisine Others
42%
Preferred food for dinner
South Indian Non-south Indian 5% 15% 37% 43% Multi-cuisine Others
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We collected the data on preference of students for visiting different eateries in Manipal. We have listed below number of students who ranked an eatery their first preference. Few students ranked two eateries as their first preference. We have found maximum students would prefer to eat at Mughlai or North Indian restaurants followed by south Indian restaurants. Count of students who listed as first preference 4 25 1 8 4 6
Eatery Chinese Mughlai/ North Indian Continental South-Indian Fast food Multi cuisine
Most preferred eatery
Chinese South-Indian Mughlai/ North Indian Fast food Continental Multi cuisine
8%
13%
8%
17% 52%
2%
While finding for the eateries and food students like the most, we need to know the reasons for their preferences. This can be very well captured by collecting data on preference given by students to various attributes pertaining to food and eatery. We found majority of the students’ ranked taste as their first preference followed by consideration of price. In our perceptual analysis we have observed that non-south Indian food scores highest on taste. This can be seen from two different tables that most of the students prefer to go Mughlai/North Indian eateries and rank taste first. Similarly, perceptual analysis indicates that south Indian food is perceived cheapest among all the foods in consideration. We can understand from these tables that many students prefer south Indian meals in breakfast because they want to spend less on it.
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Attribute Taste Price Availability Cuisine Ambience Hygiene Proximity to college/hostel Additional services provided
Most important factor
Taste Availability Cuisine Hygiene 5% 5% 2% 20% 14% 54% Price Ambience Proximity to college/hostel
a
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doc_917697011.docx
This is presentation explains the feasibility study on setting up restaurant.
Marketing Research
“Feasibility Study for setting up non-South Indian Restaurant in Manipal”
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Introduction:
Restaurants in Manipal: Manipal, better known as education town of India is located in the district of Udupi which is famous for its south Indian cuisine. Also due to huge student population from various parts of country and abroad in Manipal non-south Indian restaurants in this region are also prospering. Student population which ranges form 18,000-22,000 can often be found in many of these restaurants in Manipal especially during weekends. All the cuisine from North Indian to Mughlai, fast food to sea food, Chinese to Continental is available in Manipal and they have a sufficient customer base to serve. Non South Indian Restaurant: With ever increasing student population from various parts of the country in Manipal, the restaurant business is an attractive business opportunity for an entrepreneur. There are some existing restaurants in Manipal who have been serving to these needs for a long time. These restaurants differ from each other on various parameters such as: ? ? ? Type of food they serve Price Ambience of the restaurant
Except these parameters the students also look for other parameters such as Hygiene, Proximity to College/Hostel and additional services provided (ex-Home Delivery, Night Canteen) According to the need of the student, he/she selects a restaurant and often they become a regular customer of that restaurant. Hence these factors are important for any restaurant as they may become a point of difference for the success of the business. Products/Services Offered: Restaurants in Manipal offer different products/Services to the student population. These services range from type of food they offer to the price. Each of these restaurants caters to different need and often these services become the USP of the restaurant. In our feasibility study we specifically asked this question to the owners of the restaurant and they come up with mixed answers. Some believed that their Multiple Cuisine was their USP and some believed ambience as their USP.
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Rationale of the Project: The rationale behind this feasibility study was to do a need-gap analysis of non-south Indian restaurant in Manipal and the positioning strategy that an entrepreneur should aim. Objective of the Project: “Profile the current eateries catering to the non-Kannada students of Manipal. Undertake a feasibility study for setting up a non-South Indian restaurant in Manipal” The objective of our project was to find the feasibility of setting up a non-south Indian restaurant specifically for the student of Manipal. This required us to collect data from both the students as well as the various restaurants in Manipal. The reason for collecting the data from both the student as well as restaurant was to find the perception of both the parties. Also this helped as to do need-gap analysis. Scope of the Project: This feasibility study was restricted for only Manipal Students and not the local people of Manipal/Udupi. The scope of the study was for the restaurants hence canteens/mess is not included in the study.
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Research Method and Procedures:
The research methodology is a mix of both quantitative and qualitative analysis. We aim to gather responses and quantify them to find the feasibility of Kannada eateries in Manipal. The qualitative aspect would be the gathering of aspired data and opinions regarding Kannada joints in Manipal. Keeping in mind the research objective we formulated a set of dummy findings which would help us devise our questionnaire and the direction of our research. We identified the following set of dummy findings Dummy findings: 1) The demographics based on Kannada and Non-Kannada students 2) The profile of eateries based on Kannada, Non-Kannada and mixed 3) Count of students which visit Non-Kannada eateries and their demographics 4) The frequency with which sample visit Non-Kannada eateries 5) The timings when most revenue is generated and the cuisine type which generates maximum revenue 6) Revenue generator during non-peak seasons (holidays, vacation, college holidays) 7) The additional services which are preferred by the students (home delivery, music, bar etc) 8) The additional services offered by the restaurant owners 9) The need-gap analysis 10) Perception of the students towards the existing Non-Kannada eateries present in Manipal in terms of taste, price, ambience, additional services, hygiene 11) The timings of the restaurant and the difference between Kannada and Non-Kannada eateries on this parameter 12) The impact of location on the popularity of the eatery Based on the above dummy findings we decided to target the restaurants and student population in Manipal. The strategy for data collection would be same for both through questionnaire but the questions would be different and then we would correlate the responses using research tools like SPSS
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The questions contain data where in we have captured the data regarding their nationality, region of origin, hence capturing demographics required for student profiling (Ref Appendix-I) We also profiled the restaurants in the same manner (Ref. Appendix –II)
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Data Analysis and Findings:
A set of analysis were carried out on the data obtained through the questionnaire.
One-Way ANOVA The objective of this test is to find out how the cuisine preference varies among the respondents based on the zone (North, East, South and West) of India where there hometown belongs to . The test is made under the assumption that the food preferences or the type of food available within the zones would be similar. For example, in South India common set of foods like dosa, idli, sambar, South Indian Fish Curry etc are available which are popular in entire South India. Moreover, we had classified the restaurant categories as South Indian and non-South Indian. So dividing the respondents based on zones would be a better option. The respondents we got belonged to states West Bengal, Orissa, Maharashtra, Gujarat, Delhi, Bihar, Uttar Pradesh, Chhattisgarh, Madhya Pradesh, Haryana, Jharkhand, Rajasthan, Tamil Nadu, Karnataka, Kerala and Pondicherry. So the classifications into zones are as follows: ? EAST ? WEST
- West Bengal, Orissa - Maharashtra, Gujarat
? NORTH - Delhi, Bihar, Uttar Pradesh, Chhattisgarh, Madhya Pradesh, Haryana, Jharkhand, Rajasthan ? SOUTH - Tamil Nadu, Karnataka, Kerala and Pondicherry
The cuisines were classified as Chinese, Continental, Fast food, Multi cuisine, South Indian and North Indian. The respondents were asked to rank on the basis of their preference. The screen shot of the relevant questions for this analysis from the questionnaire we uploaded in surveymonkey is attached below
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Now the after classifying the respondents based on zones, the zones are codified as EAST - 1, WEST – 2, NORTH – 3, SOUTH – 4. So with one-way ANOVA we can answer the following questions. Is there any significant difference in preference among different zones for a particular cuisine? What is the average ranking given by each zone for a particular cuisine?
The Rankings we got for Chinese, Continental, Fast food, Multi cuisine, South Indian and North Indian cuisines for each respondent are tabulated with their corresponding zone codes. The analysis for one-way ANOVA is done in SPSS. The rankings we obtained for various cuisines are given in the dependent list and the zone code is given as the factor.
OUTPUT
ANOVA Sum of Squares Chinese Between Groups 3.671 df 3 Mean Square 1.224 F .601 Sig. .618
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Within Groups Total NorthIndian Between Groups Within Groups Total Continental Between Groups Within Groups Total SouthIndian Between Groups Within Groups Total Fastfood Between Groups Within Groups Total Multicuisine Between Groups Within Groups Total
85.546 89.217 28.696 58.283 86.978 8.227 85.686 93.913 53.393 104.542 157.935 5.312 95.993 101.304 4.632 120.172 124.804
42 45 3 42 45 3 42 45 3 42 45 3 42 45 3 42 45
2.037
9.565 1.388
6.893
.001
2.742 2.040
1.344
.273
17.798 2.489
7.150
.001
1.771 2.286
.775
.515
1.544 2.861
.540
.658
The null hypothesis is that there is no significant difference in cuisine preference among each zone. For 95% confidence level this null hypothesis is accepted for Chinese, Continental, Fast Food and Multicuisine. That is there is no significant difference
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between their preferences among different zones. But for South Indian and North Indian cuisines the null hypothesis is rejected for 95% confidence level as the significance level is .001. So there is a significant difference among the preference of north Indian and south Indian cuisines among different zones. Descriptives 95% Confidence Interval for Mean Std. N Chinese 1 2 3 4 Total NorthIn 1 dian 2 3 4 Total Contine 1 ntal 2 3 4 Total SouthIn 1 7 8 14 17 46 7 8 14 17 46 7 8 14 17 46 7 Mean Deviation Std. Error Lower Bound 2.57 3.00 3.14 3.41 3.13 1.43 2.38 1.07 2.88 2.02 4.00 3.12 3.93 4.35 3.96 5.43 1.134 1.414 1.027 1.770 1.408 .787 1.408 .267 1.576 1.390 1.633 1.246 1.685 1.169 1.445 .787 .429 .500 .275 .429 .208 .297 .498 .071 .382 .205 .617 .441 .450 .284 .213 .297 1.52 1.82 2.55 2.50 2.71 .70 1.20 .92 2.07 1.61 2.49 2.08 2.96 3.75 3.53 4.70 Upper Bound 3.62 4.18 3.74 4.32 3.55 2.16 3.55 1.23 3.69 2.43 5.51 4.17 4.90 4.95 4.39 6.16 Minimu Maxim m 1 2 2 1 1 1 1 1 1 1 2 1 2 2 1 4 um 4 6 5 6 6 3 5 2 6 6 6 5 6 6 6 6
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dian
2 3 4 Total
8 14 17 46 7 8 14 17 46 7 8 14 17 46
3.00 4.79 2.82 3.85 4.00 3.38 3.00 3.59 3.43 3.57 4.50 4.07 3.71 3.93
1.852 1.251 1.879 1.873 1.528 1.598 1.359 1.583 1.500 1.397 1.690 1.269 2.054 1.665
.655 .334 .456 .276 .577 .565 .363 .384 .221 .528 .598 .339 .498 .246
1.45 4.06 1.86 3.29 2.59 2.04 2.22 2.77 2.99 2.28 3.09 3.34 2.65 3.44
4.55 5.51 3.79 4.40 5.41 4.71 3.78 4.40 3.88 4.86 5.91 4.80 4.76 4.43
1 2 1 1 2 1 1 1 1 1 2 3 1 1
6 6 6 6 6 5 5 6 6 5 6 6 6 6
Fastfoo 1 d 2 3 4 Total Multicui 1 sine 2 3 4 Total
We already found out that significant difference between zones is observed for North Indian and South Indian cuisines where as the other cuisines exhibit almost similar preference in all zones. For Chinese cuisines we can see that the preference among zones is almost same. The preference rankings range from a least rank of 3.41(South zone represented by 4) to a maximum rank of 2.57(East zone represented by 1) with a mean ranking of 3.13 across all zones. Since the mean ranking is 3.13 out of 6 we can interpret that Chinese cuisine is liked by the population here.
For Continental cuisines we can see that the preference among zones is almost same. The preference rankings range from a least rank of 4.35(South zone represented by 4) to a
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maximum rank of 3.12(East zone represented by 1) with a mean ranking of 3.96 across all zones. Since the mean ranking is 3.96 out of 6 we can interpret that the preference of Continental cuisine is not that good.
For Fast food cuisines we can see that the preference among zones is almost same. The preference rankings range from a least rank of 4.00(East zone represented by 1) to a maximum rank of 3.00(West zone represented by 4) with a mean ranking of 3.43 across all zones. Since the mean ranking is 3.43 out of 6 we can interpret that the preference of Fast Food cuisine is pretty ok.
For Multi Cuisine we can see that the preference among zones is almost same. The preference rankings range from a least rank of 4.50(West zone represented by 1) to a maximum rank of 3.57(South zone represented by 4) with a mean ranking of 3943 across all zones. Since the mean ranking is 3.93 out of 6 we can interpret that the preference of Multi Cuisine is not that good.
For South Indian food we can see that there is a significant difference in preference given by different zones. The preference rankings range from a least rank of 5.43(East zone represented by 1) to a maximum rank of 2.82(South zone represented by 4) with a mean ranking of 3.85 across all zones. The ranking given by West zone is 3.00 and North zone is 4.79. The mean is coming to be 3.85 which prove that south Indian food is not among the highly preferred food category in Manipal. Moreover the highest rank is only 2.82 given by South Indian people, which proves that even South Indians didn’t rank it as their number one choice.
For North Indian food we can see that there is a significant difference in preference given by different zones. The preference rankings range from a least rank of 2.88(South zone represented by 4) to a maximum rank of 1.07(North zone represented by 3) with a mean ranking of 2.02 across all zones. The ranking given by West zone is 2.88 and East zone is 1.43. The mean is coming to be 2.02 which prove that north Indian food is the highly preferred food category in Manipal. Moreover the lowest rank is only 2.88 given
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by South Indian people, which proves that even South Indians consider North Indian food on par with South Indian food. The food categories are listed based on their mean rankings below
Mean Food Category North Indian foods Chinese foods Fast foods South Indian foods Multi cuisine Continental foods 3.96 3.85 3.93 2.02 3.13 3.43 Ranking
We can see that North Indian, Chinese and Fast foods are ranked above South Indian foods, even though 37% of the respondents constitute south Indian people. FACTOR ANALYSIS Here we use two sets of data. One is filled by the students who rank various factors they prefer in a restaurant. The factors are mainly Taste, Price, Cuisine Availability, Ambience, hygiene, Proximity to college and additional services (bar, dance floor etc).
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Similarly , the same set of factors were ranked by the restaurant owners based on their perception of what students feel is important. We did factor analysis for both these data.
Factor analysis result for student preference data
Total Variance Explained Extraction Sums of Squared Com pon ent 1 2 3 4 5 6 Total 2.087 1.492 .982 .843 .789 .646 Initial Eigenvalues % of Variance 29.815 21.312 14.028 12.040 11.275 9.222 Cumulative % 29.815 51.127 65.155 77.195 88.469 97.691 Total 2.087 1.492 Loadings % of Cumula Total 2.016 1.563 Rotation Sums of Squared Loadings % of Variance Cumula tive %
Variance tive % 29.815 29.815 21.312 51.127
28.804 28.804 22.324 51.127
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Total Variance Explained Extraction Sums of Squared Com pon ent 1 2 3 4 5 6 7 Total 2.087 1.492 .982 .843 .789 .646 .162 Initial Eigenvalues % of Variance 29.815 21.312 14.028 12.040 11.275 9.222 2.309 Cumulative % 29.815 51.127 65.155 77.195 88.469 97.691 100.000 Total 2.087 1.492 Loadings % of Cumula Total 2.016 1.563 Rotation Sums of Squared Loadings % of Variance Cumula tive %
Variance tive % 29.815 29.815 21.312 51.127
28.804 28.804 22.324 51.127
Extraction Method: Principal Component Analysis.
We have two components for which the eigen values are above 1. So the total 7 factors can be classified into 2 components.
Rotated Component Matrixa Component 1 Taste Price AvailabilityCuisine Ambience Hygiene -.225 .219 .373 .621 .239 2 .676 -.449 .529 -.083 .718
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proximitytohostel Additionalservicesprovi ded
.736 .891
-.162 .275
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
Under component 1 we have factor s “additional services”, “proximity to hostel”, ambience, cuisine availability making significant impact of 0.891, 0.736 and 0.621 respectively. Under component 2 we have factors “hygiene”, “taste” making significant impact of 0.718, 0.676 respectively. Cuisine availability also comes under component 2 with a value of 0.529. Price doesn’t have any impact on both components and doesn’t contribute to any variation. So we can conclude that according to students important factors are “additional Services”, “Proximity to hostel” and “Ambience”. This is followed by “hygiene” and “taste”.
Factor analysis result for restaurant owner’s perception about student preference
Total Variance Explained Extraction Sums of Initial Eigen values Compo nent 1 2 3 Total 1.929 1.645 1.287 % of Variance 32.152 27.410 21.450 Cumulativ e% 32.152 59.562 81.012 Squared Loadings % of Total Variance 1.929 1.645 1.287 Cumulat ive % Total 1.825 1.570 1.466 Rotation Sums of Squared Loadings % of Variance 30.418 26.168 24.426 Cumulative % 30.418 56.586 81.012
32.152 32.152 27.410 59.562 21.450 81.012
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4 5 6
.758 .244 .137
12.637 4.060 2.290
93.650 97.710 100.000
Extraction Method: Principal Component Analysis.
We have three components for which the eigen values are above 1. So the total 6 factors can be classified into 3 components. Rotated Component Matrixa Component 1 Taste Price Cuisineavailabilit y Ambience Hygiene Additionalservice s -.125 .098 .668 -.146 .885 .741 2 .752 .934 -.087 -.047 -.241 .255 3 -.399 .139 .568 .962 -.195 -.012
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 4 iterations. Under component 1 we have factors “Hygiene”, “Additional Services”, “ cuisine availability” making significant impact of 0.885,.0.741 and 0.668 respectively. Under component 2 we have
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factors “Price”, “taste” making significant impact of 0.934, 0.752 respectively. Under component 3 we have factor “Ambience”, making significant impact of 0.962. So we can conclude that restaurant owners perceive important factors to be “Hygiene”, “Additional Services”, “cuisine availability”. This is followed by “Price”, “taste” and “ambience”. We can finally conclude that factors like “Additional services”, Hygiene and taste are perceived important by both students and restaurant owners. But Restaurant owners consider “price” as an important factor for students turn out, but that is not the case with students, they don’t consider price as an important factor, if other facilities are available. Perceptual Mapping: Perceptual mapping is similar to multidimensional scaling, where we try to understand how the respondents or the potential customers perceive the product or a particular brand based on a set of attributes. There are two ways to do perceptual mapping – by using factor analysis and by using discriminant analysis. Here using perceptual mapping using discriminant analysis let us analyse how the respondents perceive the three different kinds of eateries such as South Indian, North Indian/Moghlai and Multi Cuisine based on the following attributes: Taste, Price, Hygiene, Ambience, Available Cuisine and Additional Service. Data was collected from 46 respondents and each respondent were asked to rate each kind of eatery for all the attributes. This means there is a total of 46 x 3 responses. All the attributes were measured on a 5-point Likert scale (0 – very poor to 4 – excellent). This means that a higher value has a better rating. Discriminant Analysis Output: Let us have a look at the Discriminant Analysis output. Then we shall draw a Perceptual map between the two functions and find out how the attributes are perceived. The Group Statistics shows the mean value and its standard deviation for different attributes (all the values are on Likert scale) and Eatery Type. Hotel Types are represented as follows: 1 – South Indian
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2 – North Indian / Moghlai 3 – Multi Cuisine Group Statistics Valid N (listwise) Hotel_Type 1 Taste Price Availability_Cuisine Ambience Hygiene Additional_Services 2 Taste Price Availability_Cuisine Ambience Hygiene Additional_Services 3 Taste Price Availability_Cuisine Ambience Hygiene Additional_Services Total Taste Price Mean 2.35 2.87 1.98 1.65 1.76 1.30 2.89 2.00 2.63 2.80 2.52 2.13 2.46 1.87 2.52 2.54 2.43 2.07 2.57 2.25 Std. Deviation .795 .833 .931 .875 .794 .866 .795 .869 .771 .687 .691 .885 .936 .909 .809 .780 .688 .879 .871 .973 Unweighted 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 46 138 138 Weighted 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 46.000 138.000 138.000
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Availability_Cuisine Ambience Hygiene Additional_Services
2.38 2.33 2.24 1.83
.881 .923 .797 .948
138 138 138 138
138.000 138.000 138.000 138.000
The Wilk’s Lambda describes how significant is the discriminant function. The value lies between 0 and 1. Closer the value to 0 means higher the significant. Here, we see that the Wilk’s Lambda is 0.450. Hence the function is considerably significant.
Wilks' Lambda Test of Function(s) 1 through 2 2 Wilks' Lambda .450 .944 Chi-square 105.745 7.622 df 12 5 Sig. .000 .178
The table below shows that the Eigen value is 1.097. This is also a significant value, thus meaning that the model is good. Eigen Values Functio Eigenvalu n 1 2 e 1.097a .059a Canonical % of Variance Cumulative % Correlation 94.9 5.1 94.9 100.0 .723 .236
a. First 2 canonical discriminant functions were used in the analysis.
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The standardized canonical discriminant function coefficients are tabulated below. Using the coefficients for the attributes, the perceptual map is drawn. From the table below, it is seen that in Function 1, the Price is a significant factor since its coefficient has the highest magnitude. Similarly, Taste is a significant factor in Function 2.
Standardized Canonical Discriminant Function Coefficients Function 1 Taste Price Availability_Cuisine Ambience Hygiene Additional_Services .409 -.965 .165 .364 .248 .173 2 1.111 .062 -.463 .408 -.516 -.116
The coordinates for the Hotel type are given below. It is plotted in the Canonical Discriminant Function, we see that the three types of eateries (here: mentioned as Hotel_Type 1, 2 and 3) lie in three separate quadrants, though the North Indian and Multi Cuisine lie too closely. We can conclude that people perceive distinctly about the three eateries. The Canonical Discriminant Function graph also shows the plots for each response for each eatery.
Functions at Group Centroids Function Hotel_Type 1 2 3 1 -1.458 .855 .603 2 .034 .276 -.310
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Functions at Group Centroids Function Hotel_Type 1 2 3 1 -1.458 .855 .603 2 .034 .276 -.310
Unstandardized canonical discriminant functions evaluated at group means
From the perceptual map plotted for Eatery type and its attributes, we can infer the following:
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1. South Indian eateries lie close to the Pricing line. This means that the people who go to South Indian eateries are concerned about the price of the food. This is evident because the food is charged low compared to any other type of eateries. 2. North Indian eateries lie closer to the Taste line and Ambience line. This means that the people who go to the North Indian eateries are more concerned about the taste of the food and the ambience of the hotel than any other attributes. 3. The Multi Cuisine eateries lie close to the Hygiene line, cuisine availability and additional services (like attached Bar, TV, pool/snooker, etc). This means that the people perceive Multi Cuisines to be more hygienic and also expects a larger variety of food to be available. It is also not surprising that the pricing line and the multi cuisine lie in two opposite quadrants!
Perceptual Map of Eatery type and Attributes Taste
1.2 1 0.8 0.6 Function 1 0.4 South Indian -1 -0.2 Multi Cuisine -0.4 -0.6 Function 2 0.2 0 -2 0 North Indian/Moghlai 1 Price Availability_Cuisine Ambience Hygiene Additional_Services
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Conclusions and Recommendations:
? Since North Indian foods are preferred by both North Indians and South Indians equally, and North Indian food, Chinese, Fast food are ranked above south Indian foods; we conclude that it is very much feasible to start a non- south Indian Eatery in Manipal. ? From the factor analysis findings, we can conclude that instead of having a low price we have to go for additional services, proximity to location, ambience, hygiene and taste in order to attract the student crowd of Manipal. ? From perceptual mapping we can conclude that food pricing is a major factor while opening a South Indian eatery. It is also seen from the survey that people prefer South Indian eateries for breakfast more than any other eatery. Similarly Multi Cuisine restaurants are expected to have wider choices of cuisines (a bigger menu) along with additional facilities like attached bar or TV or pool/snooker board, etc. The attributes that are important for opening a North Indian eatery is (or the customers are particular about) the taste of the food and the ambience of the hotel.
Limitations:
1. The number of responses was 46. This was mainly due to the time constraint available for the survey. The results could have been predicted even better had the response size been higher. 2. Some of the responses were filled for the sake of attempting the survey and the respondents did not pay attention to give true figure. This was mainly due to fatigue caused to the respondents as they had already attempted similar online survey. Hence some of the responses did not truly represent the expected output although the final output gave a true picture. 3. Some of the responses collected from the eatery owners were reluctant in sharing certain data such as Monthly sales and Price range of the food available in their eatery.
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Appendices:
Questionnaire for Students: 1. Which university/college ________________________________________ 2. Gender : Male ( ) Female ( )
3. Nationality: __________ 4. If Indian, which state do you belong to? ______________________________ 5. How often do you eat outside food (other than hostel mess) in a week? Please tick any one. Daily 3-5 times 1-2 times Never
6. Rate the following services provided by restaurants/hotels/eateries on a scale of 1-5 (1 – most important and 5-least important) Services Home delivery Timeliness Bar Television/ Live telecast Dance floor Timing (Opening and closing) Desserts Mode of payments (Credit card, cash etc.) 1 2 3 4 5
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MKRH Project 7. Which are the places you frequent for meals and when? (Tick more than 1 if applicable.) Eatery types Pure South-Indian eateries (eg. Pangal, Anupam, Andhra mess, Annapurna, Samudra,Fishland) Non-South Indian eateries (eg. Hang Yo CTF, tasty bites, snack shack, Saiba, China Valley, Paratha Point, Dollops, Guzzlers, Rajasthani mess, Parmesh mess, Basil, Dominoes, Lil' chef, Cosmo café) Mixed Cuisine (eg. Atithi, KC café, Food court,Dollops) If others, specify Breakfast Lunch
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Dinner
8. Which cuisine is preferred by you? Rank them in the order of your preference (1- Highest, 7Lowest) Type of cuisine Chinese Moghlai/ North Indian Continental South-Indian Fast food Multi cuisine Rank
9. Which of the following factors are the criteria for selection of restaurant? Rate them in the order of importance (1- Highest, 7- Lowest) Selection criteria Taste Price Availability Cuisine Rank
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10. Rate the eateries on a scale of 1-5 based on the factors mentioned. (1- Excellent and 5- Very Poor)? 1 Excellent 2 Good 3 Satisfactory 4 Bad 5 Very poor
Types of Eateries Taste South Indian eateries (Pangal, Anupam, Andhra mess, Annapurna,Samudra, Fishland) Price
Factors
Availability Cuisine Ambience Hygiene Additional services Taste Price Availability Cuisine Ambience Hygiene Additional services Taste Price Availability Cuisine Ambience Hygiene Additional services
Non South Indian eateries (HangYo,Guzzlers,Basil, Tastybites, SnackShack, Saiba, ChinaValley,Dominoes ParathaPoint, Rajasthani/Bihari mess, LilChef, CosmoCafé)
Mixed Cuisine (Atithi, KC café, Food court, Dollops,)
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MKRH Project Questionnaire for Restaurant/ Hotel/ Eateries:
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1) Name of the establishment: _________________________ 2) Location: _________________________________ 3) What are the Cuisines offered by you? (Tick wherever applicable) Type of cuisine Chinese Moghlai/ North Indian Continental South-Indian Fast food Multi cuisine 4) What are the timings of your restaurant? ___________________________________ 5) Which cuisine according to you generates more sales? a. South Indian b. Others c. Both generate almost same revenue
6) When do you generate maximum sales? Breakfast Lunch Snacks Dinner 7) What is the USP of your restaurant?__________________________________________
8) What are the additional services provided by you? (Tick whichever applicable) Services Home delivery Timeliness 27
MKRH Project Bar Television Dance floor Timing (Opening and closing) Mode of payments (Credit card, cash etc.)
Group-3
9) Which of the factors according to you are preferred by the students? (Rank them in order of importance, 1- Highest and 7- Lowest) Factors Taste Price Availability Cuisine Ambience Hygiene Additional services provided 10) Please specify the range of price offered on your menu. 11) Which cuisine sells more in non-peak season? a. South Indian b. Others _______ _______ Rank
c. Both generate almost same revenue
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MKRH Project
Group-3
We visited different places in Manipal to get the responses for our research purpose. We surveyed a total of 46 students of which 39 were male and 7 were female. Since, our research needs students from different regions; we tried to get respondents from all the four regions i.e. east, west, north and south. We managed to get maximum respondents from south and north regions but could not get more respondents from east and west regions. Following graphs and table show the demographical and geographical details of our respondents: Region North East South West No. of Respondents 14 7 17 8
Zone
North East South West
14, 31% 8, 17% 7, 15%
17, 37%
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MKRH Project
Group-3
Gender
Male Female
7, 15%
39, 85%
We decided to obtain the data for consuming food outside by students from all the regions. It helped us find their behaviour on eating outside. Results show that it is very important finding to decide on feasibility of opening a new restaurant. We can see 74% of the respondents eat at outside eateries 1 to 3 times per week and 22% of total eat 4 to 6 times per week. We have these data region-wise, which can help decide demand of food preferred by students from different regions.
Frequency of eating outside per week Never 1 - 3 times 4- 6 times Daily
North 0 10 4 0
East 0 6 1 0
South 1 12 4 0
West 1 6 1 0
Total 2 34 10 0
Percentage 4% 74% 22% 0%
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MKRH Project
Group-3
Weekly outside food consumption
35 30 25 20 15 10 5 0 Never 1 - 3 times 4- 6 times Daily West South East North
We collected the data on preference of food by students for breakfast, lunch and dinner. We allowed them to mark more than one option. This would avoid in getting biased or incorrect preferences for a particular food. We have found most of the students prefer to have non-south Indian and multi-cuisine food for their lunch and dinner and prefer south Indian food for their breakfast. These data is really important to decide offering to be made to attract most of the customers for all the meals. Type of food South Indian Non-south Indian Multi-cuisine Others Breakfast 23 3 3 2 Lunch 14 24 17 3 Dinner 15 42 36 5 Total 52 69 56 10
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MKRH Project
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Preferred food for breakfast
South Indian Non-south Indian Multi-cuisine Others
10% 10%
6%
74%
Preferred food for lunch
South Indian Non-south Indian 5% 29% 24% Multi-cuisine Others
42%
Preferred food for dinner
South Indian Non-south Indian 5% 15% 37% 43% Multi-cuisine Others
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MKRH Project
Group-3
We collected the data on preference of students for visiting different eateries in Manipal. We have listed below number of students who ranked an eatery their first preference. Few students ranked two eateries as their first preference. We have found maximum students would prefer to eat at Mughlai or North Indian restaurants followed by south Indian restaurants. Count of students who listed as first preference 4 25 1 8 4 6
Eatery Chinese Mughlai/ North Indian Continental South-Indian Fast food Multi cuisine
Most preferred eatery
Chinese South-Indian Mughlai/ North Indian Fast food Continental Multi cuisine
8%
13%
8%
17% 52%
2%
While finding for the eateries and food students like the most, we need to know the reasons for their preferences. This can be very well captured by collecting data on preference given by students to various attributes pertaining to food and eatery. We found majority of the students’ ranked taste as their first preference followed by consideration of price. In our perceptual analysis we have observed that non-south Indian food scores highest on taste. This can be seen from two different tables that most of the students prefer to go Mughlai/North Indian eateries and rank taste first. Similarly, perceptual analysis indicates that south Indian food is perceived cheapest among all the foods in consideration. We can understand from these tables that many students prefer south Indian meals in breakfast because they want to spend less on it.
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MKRH Project Count of students who listed as first preference 30 11 1 3 8 3 0
Group-3
Attribute Taste Price Availability Cuisine Ambience Hygiene Proximity to college/hostel Additional services provided
Most important factor
Taste Availability Cuisine Hygiene 5% 5% 2% 20% 14% 54% Price Ambience Proximity to college/hostel
a
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doc_917697011.docx