Analysis of Factors Affecting Restaurant Businesses

Course Name: Principles of Marketing
Course ID: MKT 201
Section: 0001
Date of Submission: August 13, 2012

-------------------------------------------------
Prepared By: 1. NusratJahan ID: 10204101 Serial: 22 2. RahnumaAkram Sabah ID:10204043 Serial:14 3. AbantiSaha ID:10204080 Serial:18 4. RatulRaihan ID: 5. Nazir Ahmed Zihad ID:10204036 Serial:12

-------------------------------------------------
Summary

Over the years, numbers of people having foods at restaurants are increasing. As a result, number of restaurants has also increased with the demand. Busy life of city inhabitants compels to have meals at restaurants rather cooking at home. With the passage of time, peoples also became aware about the food quality, environment and interior design of restaurants.

Previous research conducted on consumers has shown that location has been a factor influencing a consumer’s decision to go to a restaurant. It has also shown that locational variables such as environment and packet quality have been considered important to consumers. Consumer demographics if affects the consumer perception then it may affect the consumer’s decision to go to a restaurant. The correlation between different locational variables we found out by calculating Pearson’s correlation coefficient and effect of the demographic features on consumer preference was found out through cross tabulation. The results were tested for significance by calculating probabilities (2 tailed) and by performing a chi squared test respectively.
-------------------------------------------------
Importance
For the Owner:
With increasing popularity of restaurants, more and more consumers are going to restaurants in order to eat. Considering the large population of Dhaka which is currently15, 414,000 (Cox 2012) restaurants have a highly profitable market. Regardless of whether the restaurants are small or big, they are highly profitable. As a result, anyone who has enough money to rent a one floor space can earn a lot of money through the restaurant business. The profit earned may be so large that the owner may even expand his or her business.

For the Customer:
The number of working parents and single parents are increasing day by day who find it hard to prepare food after coming from work. For such parents buying food from restaurant is most convenient. Restaurants provide a variety of food which the consumers may not be able to cook. In addition, consumers are able to throw parties at restaurants and fully enjoy themselves without having to worry about serving the guests and washing the dishes. For young consumers, especially teenagers who find it uneasy to talk openly with their friends in front of their parents at home, restaurants give them a chance to communicate openly with their friends in the absence of their parents.

For the Employees:
Considering the increase in the popularity of restaurants, this popularity has resulted in a dramatic increase in the number of establishments as shown in (Soriano, 2002), mentioned in the previous research section of this paper. As the number of establishments increased the need for employees serving consumers have also increased. Therefore, the popularity of restaurants has increased the demand for workers which in turn increased the rate of employment. Hence restaurants have given many unemployed a job from which they can earn a living for themselves and for their families.

For the Government& Economy:

As we have seen earlier, the popularity of restaurants have resulted in an increased demand for workers which in turn have increased the rate of employment. Therefore, by reducing unemployment in the country restaurants have indirectly helped improving the economy of the nation. Also, as the number of businesses increases, the chance of the government to reap out taxes from these businesses increases. These taxes can then be utilised in the welfare of humans by building schools, hospitals, etc. thereby further improving the economy.

-------------------------------------------------
Previous Studies

Increasing amount of people take food home from restaurants:
Over the years increasing number of people prefer food from restaurants than from home, as a result the number of restaurants established has also increased. A study conducted by the Spanish Federation of Restaurants, Cafeterias and Bars showed that there has been a dramatic increase in the number of establishments from 21536 in 1975 ,27381 in 1980, 37227 in 1985, 50055 in 1995 and 59475 in 1996 (Soriano, 2001). (Stewart et al., 2004) as cited in (Boyce, Broz , Binkley, 2008)mentioned that there has been a 58 per cent increase in the profits of restaurants, up to $152billion from 1992 to 2002 due to increasing demand of food from restaurants. From the above information we can understand how dramatically the demand for restaurants increased which in turn increased the number of establishment. The reason behind this increase is due to an increasing amount of single working people, dual income families with and without children who buy food five times a week due to time unavailability (Binkley, Ghiselli, 2005) as cited in (Boyce, Broz , Binkley, 2008)

Location affecting consumer decisions:
An experiment conducted by (Koo, Tao, Yeung 1999) showed that for family meals responded did not want to go to the outlying islands and family meal customers preferred to go restaurants located in urban areas. From this example of family meal customers we can observe that location is a factor influencing consumers to go to specific restaurants. If location is inappropriate according to the consumers, they might prefer not to go to the restaurants, not matter how good it is if the location is not appropriate according to their perception.

Consumers concerned with packet quality:
Sheridan(2003) as cited in (Boyce, Broz , Binkley, 2008) mentioned that Applebee’s curbside service’s traditional white polystyrene clamshell containers were replaced with current the heavy plastic bases with clear, sealable lids since consumers believed that the containers did not keep the food warm, had a tendency to leak and easily damaged by sharp utensils. From the above we can see that consumers want high quality packets that will keep the food undamaged and warm. (Falkman, 2002) as cited in (Boyce, Broz , Binkley, 2008)mentioned that there has been an annual increase of 5 percent compared to the typical growth of 1 to 2 percent in the use of foodservice disposable packaging by both chain quick service and full service restaurants. This means there has been a gradual improvement in package quality. Since, changes in businesses are tied with consumer demand; the change in packaging may be the result of consumers demanding higher quality packaging.

Environment acting as a marketing tool:
(Horeco 2000) as cited in (Soriano 2002) mentioned that “ambience,simple décor, may give restaurants a competitive edge” and(Dulen1998) as cited in (Soriano2002) said “The importance of a comfortable atmosphere is increasing with time”. Also, (Belman 1996) as cited in (Soriano, 2002) stated “Today, the most important thing is design and concept” .Therefore we can conclude that the environment of a restaurant plays a vital role in the success of a restaurant and people nowadays want more than just food.

Demographic profiles of consumers affecting decision making:
“Consumers’ perception can influence an individual to choose a restaurant when age, gender and their income play a significant mediating role” (Dube et al., 1994; Lee and Hing, 1995; Johns and Tyas, 1996; Fu and Parks, 2001; Tam, 2004;Schiffman and Kanuk, 2000; Wagar and Lindqvist, 2010; Alalaakkola, 1996; Alexander,1947; Nysveen et al., 2005; Kotler and Keller, 2006; Mitchell and Walsh, 2004; Gutkowska et al., 2001) as cited (Rahman2012) suggests that if demographic features intervenes into a consumers perception, it can influence a consumer to choose a specific restaurant.

-------------------------------------------------
Methodology:

Nature of Research:
The type of research conducted was mainly descriptive in nature. It included both qualitative and quantitative research. For the qualitative part, qualitative variables such as gender, religion, location, occupation, etc where related to factors such as restaurant preference, service quality etc. For the quantitative part, the participants were asked a number of questions to which they had to rate on a scale of five ranging from high disagreement to high agreement.
Questionnaire Design:
Sample & Sampling technique:
Using convenience sampling a group of 447 participants were selected and surveyedby 40 students of the 1st section of the Principles of Marketing class of BracUniversity. The survey was conducted on July 2012. The sample included an equal proportion of people belonging to the four following age groups: below 21, 21-30, 31-45 and above 45, which the students choose according to their convenience.
Data quality control:
In order to assure that the response from the participants were correct we included negative questions which were exactly contrary to questions asked before. This was done to check whether the respondents were actually reading the questions and answering or just merely choosing the options randomly.

Analysis:
After the data collection was successfully conducted, a cluster analysis was performed on the variables i.e. the variables which were similar in some way were grouped to form smaller clusters and then analysed. A bi-variate analysis i.e. an analysis done using two variables at a time was conducted using Pearson’s correlation and cross tabulation. All the results obtainedwerethen were checked for a significance of 0.05 or less. Results with significance of greater than 0.05 were not taken into consideration when drawing a conclusion.

-------------------------------------------------
Result & Discussion
Correlation amongst variables related to location:
Source: www.wikepedia.org

From the above data,we can see that a statistically significant (<0.05) relation exists between government rules with packet quality, sponsorship, restaurant not being available and delivery time. Although a small correlation i.e. from 0.1 to 0.3 exists between government rules and the 4 other variables, there is greatest correlation (0.307) between government rules and sponsorship. This may be the result of the government rules regarding sponsorship e.g. if the government introduces special tax laws on sponsorship then the amount of sponsorship for restaurants will decrease. There exists a statistically insignificant relation (>0.5) between government rules with type of delivery and environment. This may be because the restaurant management decides on how they will deliver their product to the customers rather than the government. The government also does not decide on the lighting, temperature etc. of the restaurant so there is no correlation.

The data also indicate a statistically significant (<0.05) relation between packet quality and sponsorship, delivery time and type of delivery. There is a medium correlation (0.3 to 0.5) between packet quality with delivery time and type of delivery. However, there is small correlation (0.197) between packet quality and sponsorship. The reason for this may be that depending on the quality of the packets restaurants need to decide on the delivery type and time. For example, if the packet quality is such that it keeps the foods warm for a sustained period then the restaurant can extent the delivery time longer. Similarly if the packets are strong, then restaurants do not require a very careful delivery.

A statistically significant relation (<0.05) is indicated by the above data among sponsorship with restaurant not being available, delivery time and type of delivery. Compared to the other 2 variables, more correlation (0.207) exists between sponsorship and restaurant not being available. Lack of sponsorship may be the reason why people are unable to open good restaurants. There is no statistically significant correlation of sponsorship with restaurant environment may be because sponsors do not intervene on how the restaurants should decide on their interior etc.

There is a significant relation only between restaurants not being availableand delivery time. There is no significant correlation between restaurants not being available with type of delivery and environment (0.591 & 0.809 respectively). This may be because a good environment of a restaurant does not necessarily indicate that the restaurant is good.

Delivery time and type has a statistically significant relation (0.000) with a small positive correlation of 0.264. Depending on the type of delivery provided the delivery time is likely to vary. On the contrary, there is no significant relation (0.103) between delivery time and environment. The restaurant environment is not a factor for deciding on the delivery time. Lastly, there is no significant relation (0.496) between type of delivery and environment. Like the above reason, the environment of a restaurant is not a decisional factor for deciding on the type of delivery implemented.

Cross tabulation of consumer response and demographic variables:

1. Gender:

Crosstab | | | | | | | | Cluster Number of Case | Total | | Chi-Square Tests | | | 1 | 2 | 3 | | | | Value | df | Asymp. Sig. (2-sided) | gender | f | 0 | 88 | 98 | 186 | | Pearson Chi-Square | 3.129a | 2 | .209 | | m | 1 | 103 | 155 | 259 | | Likelihood Ratio | 3.489 | 2 | .175 | Total | | 1 | 191 | 253 | 445 | | N of Valid Cases | 445 | | |

In crosstab, we can see that the majority of both male and female gave a higher order response for restaurant preference. For males, the number was 155 and for females it was 98. If we consider the percentages, 52% of females and 59% of males gave a higher order response for restaurant preference. As male and female responses are close in percentage, we can conclude that restaurant preference is independent of gender.

From Chi-square test, it is also seen that there is no relation between gender and restaurant preference as the level of significance is greater than 0.05. The reason may be that now-a-days there is equality amongst males and females as a result they both have say in choosing restaurants.

2. Age: Crosstab | | | | | | | | Cluster Number of Case | Total | | | | | | | | 1 | 2 | 3 | | | Chi-Square Tests | age | 1 | 0 | 56 | 46 | 102 | | | Value | df | Asymp. Sig. (2-sided) | | 2 | 0 | 56 | 82 | 138 | | Pearson Chi-Square | 12.934a | 6 | .044 | | 3 | 0 | 45 | 59 | 104 | | Likelihood Ratio | 12.510 | 6 | .052 | | 4 | 1 | 34 | 66 | 101 | | Linear-by-Linear Association | 5.831 | 1 | .016 | Total | | 1 | 191 | 253 | 445 | | N of Valid Cases | 445 | | |

In the crosstab, we can see that maximum people of 2nd, 3th and4th age group gave a higher order response for restaurant preference but for only one age group (1st) maximum people gave a moderate response. The reason may be that people of the 1st age group belong to the dependent segment who does not earn money. They have different tastes and preferences than people of other age groups. In the higher order responses we can see that with the respondent’s age restaurant preference increases gradually with the 2nd age groups value exceptionally high as maximum samples were taken. Thereby, age has a relation with restaurant preference.

In Chi-square chart, we also see a relationship between age and restaurant preference (significance <0.05). This may be because with age the tendency of individual to eat in a restaurant increases.

3. Occupation:

Crosstab | | | | | | | | Cluster Number of Case | Total | | | | | | | | 1 | 2 | 3 | | | Chi-Square Tests | occupation | b | 1 | 21 | 33 | 55 | | | Value | df | Asymp. Sig. (2-sided) | | o | 0 | 35 | 53 | 88 | | Pearson Chi-Square | 9.785a | 6 | .134 | | s | 0 | 101 | 114 | 215 | | Likelihood Ratio | 6.878 | 6 | .332 | Total | | 1 | 191 | 253 | 445 | | N of Valid Cases | 445 | | |

The crosstab data shows that restaurant preference is independent of occupation since the majority of all occupational categories gave a high order response of restaurant preference.

From the Chi-square chart, it is also seen that there is no relation between gender and restaurant preference. Nowadays there are an increasing number of working parents who find it hard to cook food at home. As a result they buy food from restaurants. These people buy food from restaurants regardless of their profession.

4. Family Members: | | | | | | Crosstab | | | | | | | | Cluster Number of Case | Total | | | | | | | | 1 | 2 | 3 | | | Chi-Square Tests | Family members | 2 | 0 | 21 | 27 | 48 | | | Value | df | Asymp. Sig. (2-sided) | | 3 | 0 | 49 | 57 | 106 | | Pearson Chi-Square | 4.572a | 6 | .600 | | 4 | 0 | 63 | 100 | 163 | | Likelihood Ratio | 4.594 | 6 | .597 | | 5 | 1 | 58 | 69 | 128 | | Linear-by-Linear Association | .012 | 1 | .914 | Total | | 1 | 191 | 253 | 445 | | N of Valid Cases | 445 | | |

The crosstab shows that families with any number of members from 2 to 5 have given a higher order response. In the higher response, no trend is seen. Therefore there is no relation between family members and restaurant preference.

Chi-square test also shows no relation between family members and restaurant preference. The reason may be that regardless of the number of family members they have, people who want to go to restaurants will go to restaurants.

5. Educational Qualification:

Crosstab | | | | | | | | Cluster Number of Case | Total | | | | | | | | 1 | 2 | 3 | | | Chi-Square Tests | EducationQualification | 1 | 0 | 16 | 8 | 24 | | | Value | df | Asymp. Sig. (2-sided) | | 2 | 0 | 60 | 55 | 115 | | Pearson Chi-Square | 15.137a | 6 | .019 | | 3 | 1 | 64 | 98 | 163 | | Likelihood Ratio | 15.373 | 6 | .018 | | 4 | 0 | 51 | 92 | 143 | | Linear-by-Linear Association | 11.806 | 1 | .001 | Total | | 1 | 191 | 253 | 445 | | N of Valid Cases | 445 | | |

For the first two groups the majority of respondents gave a moderate response and for the remaining groups the majority of respondents gavea high order response. Therefore, restaurant preference varies with educational qualification.

This relation is also found in chi-square test result. The reason may be that with educational qualification a person’s living standard changes which in turn changes a person’s taste and preference.

6. Marital status:

Crosstab | | | | | | | | Cluster Number of Case | Total | | Chi-Square Tests | | | 1 | 2 | 3 | | | | Value | df | Asymp. Sig. (2-sided) | marital | m | 1 | 76 | 135 | 212 | | Pearson Chi-Square | 9.135a | 2 | .010 | | u | 0 | 115 | 118 | 233 | | Likelihood Ratio | 9.558 | 2 | .008 | Total | | 1 | 191 | 253 | 445 | | N of Valid Cases | 445 | | |

In the crosstab we see that the majority of both married and unmarried has given higher order response for restaurant preference. The number of married respondents was 212 of which 135 of them highly prefer restaurants. The number of unmarried respondents was 233 of which 118 of them prefer restaurants highly. This means that 64% of married respondents and 62% of unmarried respondentsgave a high order response. Hence, there is no relation between restaurant preference and marital status.

However, from the chi-square test we see that there is relationship in between marital status and restaurant preference which is 0.010.The result may be different because married couples may want to go to restaurants with a good environment or with 2 people tables. If this is true, marital status does affect restaurantpreference

7. Religion: Crosstab | | | | | | | | Cluster Number of Case | Total | | Chi-Square Tests | | | 1 | 2 | 3 | | | | Value | df | Asymp. Sig. (2-sided) | religion | 1 | 1 | 184 | 244 | 429 | | Pearson Chi-Square | 2.171a | 4 | .704 | | 2 | 0 | 4 | 8 | 12 | | Likelihood Ratio | 2.232 | 4 | .693 | | 3 | 0 | 3 | 1 | 4 | | Linear-by-Linear Association | .259 | 1 | .611 | Total | | 1 | 191 | 253 | 445 | | N of Valid Cases | 445 | | |

In the crosstab we find that most of the people of different religion have given higher order response for restaurant preference. The number of Muslim respondents was 429 of which 244 of them i.e. 56% gave the higher order response. Similarly,8 out of 12 Hindurespondentsi.e. 66% gave a higher order response for restaurant preference. These figures show no trend so there is no relation between restaurant preferenceand religion.

The chi-square test also shows no relationship (significance 0.704) between restaurant preference and religion.

People’s stereotypic impression about people of other religion no more exists, so people from other religions feel free to go to any restaurant.

8. Family income:

Crosstab | | | | | | | | Cluster Number of Case | Total | | | | | | | | 1 | 2 | 3 | | | | | | | Family Income | 1 | 0 | 4 | 1 | 5 | | | | | | | 2 | 0 | 10 | 19 | 29 | | | | | | | 3 | 0 | 39 | 38 | 77 | | Chi-Square Tests | | 4 | 0 | 38 | 49 | 87 | | | Value | df | Asymp. Sig. (2-sided) | | 5 | 0 | 26 | 33 | 59 | | Pearson Chi-Square | 9.075a | 12 | .696 | | 6 | 0 | 26 | 38 | 64 | | Likelihood Ratio | 9.121 | 12 | .693 | | 7 | 1 | 48 | 75 | 124 | | Linear-by-Linear Association | 1.282 | 1 | .257 | Total | | 1 | 191 | 253 | 445 | | N of Valid Cases | 445 | | |

In the crosstab we see that regardless of income respondents want to go restaurant. For people, with an income below 20000, 19 out of 29 have given higher order response in restaurant preference. Similarly people, with an income more than 1, 00, 000, 75 out of 124 people have given higher order response. So from responses of people with differentincome levels we can see that no relation between restaurant preference and income level exists.

The chi-square test also shows no relationship between restaurant preference and income level.
The reason may be that restaurants have become so popular that people of all income groups prefer to go to restaurants.

9. Monthly expenditure: Crosstab | | | | | | | | Cluster Number of Case | Total | | | | | | | | 1 | 2 | 3 | | | | | | | Monthly expenditure | 1 | 0 | 65 | 66 | 131 | | | | | | | 2 | 0 | 50 | 65 | 115 | | | | | | | 3 | 0 | 38 | 46 | 84 | | Chi-Square Tests | | 4 | 0 | 17 | 35 | 52 | | | Value | df | Asymp. Sig. (2-sided) | | 5 | 0 | 11 | 18 | 29 | | Pearson Chi-Square | 37.041a | 12 | .000 | | 6 | 1 | 2 | 13 | 16 | | Likelihood Ratio | 18.064 | 12 | .114 | | 7 | 0 | 8 | 10 | 18 | | Linear-by-Linear Association | 3.704 | 1 | .054 | Total | | 1 | 191 | 253 | 445 | | N of Valid Cases | 445 | | |

In the crosstab we can see that majority of respondents with different monthly expenditure have given higher orderof response for restaurant preference regardless of monthly expenditure. Therefore, we see no relationship between restaurant preference and monthly expenditure.

The chi-square test shows a strong relation between restaurant preference and monthly expenditure. The results may differ because the people who are more prone to spend a lot of money is more likely to go to more expensive restaurants compared to someone who is less prone to spending a lot of money.

-------------------------------------------------
Limitations
The samples taken the students of Brac University were taken using convenience sampling. These samples may not be representative of the entire restaurant going population of Dhaka. In addition, the experiment had not been repeated to check whether similar results were obtained or not.
-------------------------------------------------
Conclusion& Managerial Implications

Gender, occupation, family members, religion and family income does not affect restaurant preference of consumers. However age and educational qualification has a relation with restaurant preference. For marital status and monthly expenditure, results from cross tabulation and chi-squared test show conflicting relations i.e. if one shows a relation, the other does not. Therefore the whether marital status and monthly expenditure has a relation with restaurant preference is not clear through the experiment carried out. In addition, all values of correlation obtained which were statistically significant were either small or medium; no strong correlation existed between any locational variables.

This research will help managers understand which particular variables under demographic characteristics affect a consumer’s restaurant preference. It will also enable managers to understand the amount of relation that exists between different restaurant locations related variables.

-------------------------------------------------
References

Janice Boyce, Charles C. Broz, Margaret Binkley, (2008),"Consumer perspectives: take-out packaging andfood safety", British Food Journal, Vol. 110 Iss: 8 pp. 819 - 828

Domingo Ribeiro Soriano, (2002),"Customers' expectations factors in restaurants: The situation in Spain",
International Journal of Quality & Reliability Management, Vol. 19 Iss: 8 pp. 1055 – 1067

Cox, Wendell. (2012), World Urban Areas Population and Density: A 2012 Update[WWW].Newgeography.com Available from: www.newgeography.com/content/002808-world-urban-areas-population-and-density-a-2012-update [Accessed on 12/08/12 8.21pm]

L.C. Koo, Fredrick K.C. Tao, John H.C Yeung, (1999),"Preferential segmentation of restaurant attributes through conjoint analysis", International Journal of Contemporary Hospitality Management, Vol. 11 Iss: 5 pp. 242 – 253

Muhammad SabbirRahman, (2012),"Dynamics of consumers' perception, demographic characteristics andconsumers' behavior towards selection of a restaurant: an exploratory study on Dhaka city consumers", Business Strategy Series,Vol. 13 Iss: 2 pp. 75 - 88