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Anitas Kitchen Restaurant Customer Survey - Case Study Example

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The paper "Anita’s Kitchen Restaurant Customer Survey" is an outstanding example of a management case study. Customer satisfaction of visitors to Anita’s restaurant was measured in terms of age and gender. We develop the following hypothesis. H0: Gender does not impact on customer satisfaction at Anita’s restaurant. H1: Gender has an impact on customer satisfaction at Anita’s restaurant…
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Anita’s Kitchen Restaurant Customer Survey Name: Tutor: Course: Date: 2.0 Findings and discussion 2.1 Customer satisfaction Customer satisfaction of visitors to Anita’s restaurant was measured in terms of age and gender. We develop the following hypothesis. H0: Gender does not impact on customer satisfaction at Anita’s restaurant H1: Gender has impact on customer satisfaction at Anita’s restaurant Table 1: Gender and customer satisfaction From the table 1 above, 74% (74) of the males were satisfied with services offered at Anita’s restaurant. On the other hand, 56.6% (99) of the females were not satisfied over services offered at Anita’s restaurant. This implies that most of the male customers were satisfied of the food and services offered at Anita’s restaurant while female customers were not. From the chi-square tests above, the hypothesis was statistically significant (p=0.000) meaning that we reject the null hypothesis and accept the alternative hypothesis that gender has impact on satisfaction of customers at Anita’s restaurant. Regarding the impact of age on satisfaction of customers at Anita’s restaurant, crosstabs were used and Pearson chi-square was used to test the following hypothesis; H0: Age does not impact on customer satisfaction at Anita’s restaurant H1: Age has impact on customer satisfaction at Anita’s restaurant From Appendix VI, 13% (13) of the customers aged 18-25 years were not satisfied with the services offered at Anita’s restaurant. Most of the customers aged 26-34 years 11.9% (13) and those aged 35-49 years 69.7% (76) were not sure if they were satisfied with the services offered. Majority of those aged 50-59 years 47.6%(20) and those aged over 60 years 7.1%(3) were not satisfied at all over services offered at Anita’s restaurant. This shows that the younger age group of less than 25 years was satisfied with the services while the older customers of over 50 years were not satisfied over services offered. The statistic was significant based on chi-square test (p=0.000) and the variable showed weak to moderate association. The null hypothesis is rejected and the alternative accepted that age has impact on satisfaction of customers. 2.2 Perception of quality of services at Anita’s restaurant Table 2: Perception of services at Anita’s restaurant From the table above, customers consider food quality (μ=1.61; SD=0.743) as the most important (also see figure 3 in the appendices) followed by price (μ=2.34; SD=1.143). The least considered as a problem were service (μ=2.73; SD=1.028) and atmosphere (μ=3.34; SD=0.719). This implies that customers have a problem with food quality which should be immediately improved and price of food should be amended. 2.3 Characteristics of satisfied customers As shown in Appendix VI, there was statistical significance at (p=0.000) which means that the variables were related. Customers expressed satisfaction with Anita’s restaurant services were more likely to return (r=0.751; p=0.000) to the restaurant in future (Also see Appendix VI). They were also likely to recommend (r=0.668; p=0.000) to the friends and relatives. Furthermore, the statistics showed that satisfied customers had weak negative relationship with the likelihood to patronage Anita’s kitchen restaurant (r=-2.85; p=0.000). This shows that satisfied customers were not in a position to patronage the restaurant. From the table, it is evident that satisfied customers are; Likely to recommend to their friends and family Likely to return to the restaurant in future 2.4 Target market Anita’s restaurant targets university students, families and young professionals. The following hypothesis was formulated; H0: Young professionals are more likely to patronage Anita’s kitchen restaurant H1: Young professionals are less likely to patronage Anita’s kitchen restaurant Figure 1: Age group that frequent Anita’s restaurant From the figure above, it is the older professionals 57.7% (64) who frequently patronage Anita’s Kitchen restaurant. This was statistically significant (p=0.000) and the variables were associated as shown in the symmetric measures (Phi=0.630; see table 10). We reject the null hypothesis and accept the alternative hypothesis that young people (professionals) are less likely to patronage Anita’s kitchen restaurant in two or more times a month. Similarly, in the table below, the following hypothesis were adopted; H0: Families are more likely to patronage Anita’s kitchen restaurant H1: Families are less likely to patronage Anita’s kitchen restaurant Figure 2: Ability of families to patronage the restaurant As shown in the figure above, people with no children (likely singles) frequently patronage 86.5% (96) Anita’s kitchen restaurant two or more times in a month compared to those who had children. Again, the result was statistically significant for p=0.000 and phi = 0.604 where variables had close association (see table 11). We reject the null hypothesis and accept the alternative hypothesis that families are less likely to patronage Anita’s kitchen restaurant. This implies that Anita’s kitchen restaurant has been targeting the wrong market of families and young professionals. The restaurant will have to look for a different niche especially singles and the older professionals who are looking for healthier and fat free foods. 2.5 Loyal sub-groups of customers The sub-groups to be considered to be loyal to Anita’s kitchen restaurant are; Birmingham residents and income groups. The following hypothesis was formulated; H0: Birmingham residents are not likely to return to Anita’s restaurant H1: Birmingham residents are likely to return to Anita’s restaurant Most of the residents of Birmingham 92.1 (152) were not sure if they would return to Anita’s restaurant. This was not statistically significant (p=0.772). We therefore accept the null hypothesis that Birmingham residents are not likely to return to Anita’s restaurant. On the other hand, income groups were tested if there was a relationship between income level and loyalty (likelihood of returning to the restaurant). Table 3: Correlation matrix From the table above, at p=0.01, there was no significant relationship between income level and the likelihood to return. This implies that the levels of income do not influence individuals to return to the same restaurant. In conclusion, the study found that the older age group, being the major visitors to the restaurant, was not satisfied with food quality and the price of food. The study also found that Anita’s restaurant has been targeting the wrong market of young professionals and families who least frequent the restaurant. 3.0 Limitations This study succeeded in having a significant number of participants that eliminated, to a larger extent, errors in sampling. Research limitation in most cases applies to academic research where it is impossible to control all the variables (Strauss & Corbin, 2008). However, a number of limitations were observed. First, the study was limited by scope and location which was confined to the city of Birmingham. Being an inner city in the UK, it is probable that it has homogenous population which may not provide enough evidence of diversity in the respondents. Secondly, the study data collection instrument did not capture the origin or nationality of respondents. This is because the study is about food preparation and service to people of different cultures and nationalities. Thirdly, the study instrument was administered through convenience sampling yet it was a quantitative study which required more randomized samples. On the other hand, qualitative studies study people’s culture, language, behavior and attitudes (Saunders et al., 2015). The study also had potential application of different analytical methods, not used, to answer a given research question such as factor analysis (Appendix II). However, some of the findings were not significant yet it does not imply a falsehood. For example, the study found that young people were not likely to return to Anita’s kitchen restaurant yet the restaurant has been earning sufficient revenue from this target market. Besides, the study found that income level does not influence the capacity of customers to return to the restaurant. This may not be true because people with low income may find the prices more affordable and can visit the restaurant more frequently. The study did not capture the intention of Anita’s restaurant to make strategic decisions of expanding to different towns in the UK. In this study, the target respondents were not specified to be past customers yet the questionnaires were administered to any resident of Birmingham. This is because the instrument seemed to capture perceptions on satisfaction and loyalty but not appropriate to be used for the basis of expansion. In that case, another survey will be suitable to be administered in the target towns to understand how residents will respond to its services. Moreover, it would be important that Anita restaurant considers areas with diversity, especially where Asian nationalities live when making decisions to expand. There are suggestions to changes in sampling methods, data collection instrument and analysis. First, to understand satisfaction and loyalty, the sampling method can use systematic sampling where past customers are contacted and requested to respond to the questionnaire. Secondly, interviews can be included in the future studies separately to capture the mood and opinions of loyal customers. Questionnaires in this study were designed to also work as interview schedules (question 22-24) which made it difficult for research assistants and the respondents to understand. Interviews are interactive and allow the interviewer to probe for more information and observe the mood and emotions of the interviewee (Creswell, 2014). Conversely, questionnaires are more appropriate to collect data from a large group of respondents because it comprises standardized and structured questions (Neuman, 2003). Third, future study can utilize time series to show the seasonality of customers and as well as revenues. This will help Anita’s restaurant to know what periods of the year have peaks and those with troughs. Future research can investigate the effect of Anita’s restaurant brand proposition on revenue performance. This will help the company to discover its brand image, positioning and targeting initiatives. References Creswell, J.W. (2014). Research design: Qualitative and mixed methods approaches. London: Sage Publications. Neuman, W.L. (2003). Social Research Methods, Pearson Education. Saunders, M., Lewis, P. & Thornhill, A. (2015). Research Methods for Business Student. Sixth Edition, Pearson Education Limited, Harlow, England. Strauss, A. & Corbin, J. (2008). Basics of qualitative research: Ground theory procedures and techniques, (2nd ed.). Newbury Park, CA: Sage. Appendices Appendix I: Customer satisfaction levels Appendix II: Factor analysis of lifestyle measures Appendix III: Perception of food quality among customers Appendix IV: Family patronage of Anitas’s restaurant Appendix V: Age group that patronage Anita’s restaurant Appendix VI: Impact of age on customer satisfaction Appendix VII: Characteristics of satisfied customers Appendix VIII: Residency and the likelihood of return to the restaurant Read More
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