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Plan For Primary And Secondary Data Collection

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Questions:

Task 1

1.1 Plan for primary and secondary data collection

1.2 Survey methodology and the sampling frame

1.3 Questionnaire for the given problem

1.4 Information for decision making using representative values

1.5 Analysis of results in drawing valid conclusions

1.6 Analysis of data using measures of dispersion

1.7 Recommendations and conclusion based on quartiles, percentiles and correlation coefficient

Task 2

2.1 Calculations using spreadsheet charts (line, pie, bar, histogram and scatter) and presentation

2.2 Trend lines in graphs to assist the forecasting business information

2.3 Formal business report

2.4 Information processing tools

2.5 Project planning and critical path method

2.6 Financial tools in evaluating the financial viability

 

 

Answers:

Introduction

In this report it will be analysed that whether it is possible for a restaurant to open a second branch in London. For doing this the researcher has used various statistical and financial tools and techniques in the feasibility study of the hotel (Carlson and Wu, 2011).There was primary and secondary data which was collected for the qualitative and the quantitative information that will help in analysing the project form different aspects. There was a project management technique and analysis which was done and through that critical path method of the project was also evaluated. Finally the several financial techniques which were applied in assessing the possibility of the project has been evaluated due to which a specified plan of action could have been followed.

Task 1

1.1 Plan for primary and secondary data collection

In this project there was primary and secondary data collection done based on the requirement of the topic. There are several advantages of collecting primary data as it quantitatively describes the pattern and movement based on which the conclusions of the project was drawn. It helps in addressing specific issues and allows the organization to analyze based on the current situation (Shata, 2012). There is greater control of the research in case of primary data analysis as because the marketer can decide on issues like number of respondents or the age group along with the timeframe for completing the project. The funds for the research is spend efficiently and the information collected by the marketer is their own and is generally not shared with others. In this report the primary data has been collected based on the questionnaire which has been given to the common people who visit restaurants. The researcher has collected the details from the database of several hotels and based on that an online survey has been done which would help the respondents to answer conveniently from the place they feel comfortable with (Mendelsohn, 2012).

The issue with primary research is the cost and the time it consumes in collecting the data where the secondary research scores better. The researcher has used a large number of sources in collecting and evaluating the data which will help them in improving the qualitative part of the research. In this analysis there have been lot of books, journals, and websites that have been used.  There are certain advantages in the secondary data collection techniques which include ease of accessibility, low cost and also help in the clarification of the research questions. As this is a hotel which is looking to open up a new branch in London hence the hospitality sector journals and websites of several industry analysts as well as expert interviews in the newspaper articles and websites were thoroughly followed. This has helped the researcher in identifying the key areas like demographics, financial condition as well as food habits of the people which would be the ultimate deciding factors in opening up of a hotel chain.

 

1.2 Survey methodology and the sampling frame

The survey methodology which was adopted in this study was an online questionnaire which was send to the clients which had five questions in it (Wang and Zou, 2013). The positivism philosophy was followed throughout the study as because it helps in interpreting the current theories in finding out a suitable solution based on the given problem. Deductive method was used along with descriptive technique so that detailing can be done while doing this project. The exploratory and explanatory methods were not used because of the fact that it generally targets scientific research which has the potential in creating something new. The sampling frame which was used includes 50 respondents who were of the age group between 18 and 35 who are the local people as well was expatriates based in and around London. The specification was done so as to focus more on the mindset of the people in the current city. The descriptive method will bring out the estimated outcomes which the organization will require in the future oriented decision-making process (Mendelsohn, 2012). The respondents had different educational backgrounds, profession, ethnicity as well as choice of parameters based on which they judge the service quality of a hotel. There was a stratified sampling technique which was used as because there are a number of distinct categories based on which the frame is arranged. It has been previously argued that stratified sampling techniques can lead to more efficient statistical figures and results.

1.3 Questionnaire for the given problem

Q1) Do you visit a hotel frequently?

OPTIONS

NO OF RESPONDENTS

TOTAL RESPONDENTS

RESPONSE %

Strongly Agree

6

50

12

Agree

18

50

36

Neutral

10

50

20

Disagree

8

50

16

Strongly Disagree

8

50

16

 

Q2)  Are you satisfied with the service delivery of the hotel that you visit most?

OPTIONS

NO OF RESPONDENTS

TOTAL RESPONDENTS

RESPONSE %

Strongly Agree

7

50

14

Agree

14

50

28

Neutral

11

50

22

Disagree

16

50

32

Strongly Disagree

2

50

4

 

Q3) How far do you think that the quality of the food is satisfactory in compared to the price that you pay for?

OPTIONS

NO OF RESPONDENTS

TOTAL RESPONDENTS

RESPONSE %

Strongly Agree

8

50

16

Agree

19

50

38

Neutral

7

50

14

Disagree

12

50

24

Strongly Disagree

4

50

8

 

Q4) Would you change your preference if you had better options?

OPTIONS

NO OF RESPONDENTS

TOTAL RESPONDENTS

RESPONSE %

Strongly Agree

14

50

28

Agree

14

50

28

Neutral

7

50

14

Disagree

8

50

16

Strongly Disagree

7

50

14

 

Q5) How far do you feel that the hotel industry in London is at par with other global cities?

OPTIONS

NO OF RESPONDENTS

TOTAL RESPONDENTS

RESPONSE %

Strongly Agree

10

50

20

Agree

12

50

24

Neutral

5

50

10

Disagree

16

50

32

Strongly Disagree

7

50

14

 

1.4 Information for decision making using representative values

The decisions which were taken based on the information that was available from the questionnaires that were given to the respondents based on the online format. Decisions which are taken based on the calculations and numerical figures helps in analysing the issues in depth and also makes prospective sensible buying decisions through which the error making and uncertainties actually reduce by a large extent (Carlson and Wu, 2011).

 

1.5 Analysis of results in drawing valid conclusions

In the survey method it was found that 24% of the respondents agreed to the fact that the hotel industry in London is quite robust enough in compared to the other cities and more than half of the respondents also were of the opining that they would be changing their preferences if better options would be available. 36% of the respondents said that they visit hotels very frequently which is an advantage of the hotel industry as a whole.38% of them said that they were quite satisfied with the quality of food which has been given but expects new varieties as well. Variance measures how far there is a change or variation within a particular series... In case of strongly agree it was found that the variance is 10 while the standard deviation is 3.1622. This indicates that the average squared difference from the mean is 10 and hence the deviation is (10-6.8378) which is the required answer.

1.6 Analysis of data using measures of dispersion

 

Strongly Agree

Agree

Neutral

Disagree

Strongly Disagree

 

6

18

10

8

8

 

7

14

11

16

2

 

8

19

7

13

4

 

14

14

7

8

7

 

10

12

5

16

7

Variance

10

8.8

6

16.2

6.3

Standard Deviation

3.16227766

2.966479

2.44949

4.024922

2.50998008

 

Variance measures how far there is a spread out within a set of numbers. The variance of zero indicates that the values are identical. In case of strongly agree it was found that the variance is 10 while the standard deviation is 3.1622. This indicates that the average squared difference from the mean is 10 and hence the deviation is (10-6.8378) which is the required answer. The overall response have been positive but there have been fluctuation on the basis of the disagree column which has shown volatile trends because of the different ranges of the questions that have been asked to them.

1.7 Recommendations and conclusion based on quartiles, percentiles and correlation coefficient

 

Strongly Agree

Agree

Neutral

Disagree

Strongly Disagree

 

6

18

10

8

8

 

7

14

11

16

2

 

8

19

7

13

4

 

14

14

7

8

7

 

10

12

5

16

7

Quartile

6

12

5

8

2

Percentile

7.2

14

7

9

4.6

Correlation Coefficient

-0.506351701

0.309646

-0.12679

-0.63351

-0.633508129

 

Quartile is generally divided into four equal parts where if the measurement falls to the right of the upper quartile then it is in the top 25% of the data. In this report it was found out that the agree percentage falls in the top quartile between (10-14) deciding it has an utility measure of the overall study (Manly, 2007).

Percentile is any of the 99 values which help in dividing a sorted out data into 100 equal parts so that each of the part represents 1/100 of the data set. In agree we find that it is 16 which means that more than 84% of the sample. It is also used in the non-referenced tests. The 93rd percentile in the strongly disagree category tells us that only 7% people have disagreed It gives a very accurate picture of the bandwidth (Shata, 2012).

Correlation Coefficient is a measure of the linear correlation between the two variables X and Y which gives a value between +1 and -1 where 1 is the positive correlation and -1 is negative correlation while 0 has no correlation. It is widely used in the science to measure the degree of the linear dependence within the two variables. Here for strongly agree the correlation is 0.506 negative while for agree it has been 0.309 (Wang and Zou, 2013).

 

Task 2

2.1 Calculations using spreadsheet charts (line, pie, bar, histogram and scatter) and presentation

Histogram

Histogram

Histogram is the graphical representation of the data distribution as it estimates the probability distribution of a continues variable. From here we can analyse that most of the respondents had a very positive viewpoint on the opening up of the new hotel industrtry.

Bar-graph

Bar-graph

The bar graph is rectangular charts which can be structured and drawn both vertically and horizontally. In this report it has been clearly established that the percentage of the respondents who have given negative views is proportionately quite less in compared to positive views.

Pie-chart

Pie-chart

Pie-chart is a circular graph which shows and compares data that is divided into sectors based on the numerical proportions (Manly, 2007). Sometimes when the data are very close then it becomes increasingly difficult to differentiate between the various sectors.

Scatter graph

Scatter graph

The scatter graph is a kind of the mathematical diagram which generally makes use of the Cartesian coordinates in trying to display the values for two separate variables in a group of data.

2.2 Trend lines in graphs to assist the forecasting business information

Line graph: Based on the concepts of graph theory the line graph of an undirected graph G represents the adjacent edges as well as they are bipartite which includes multigraphs which would also include line graphs or weighted graphs.

Trend lines in graphs

2.3 Formal business report

It has been found from the formal business report that there is huge prospect in the hotel and hospitality sector in London as because it is still not that much developed when talking about the restaurant industry. There has been an overall positive response from the customers based on the fact that they expect a lot of more varieties in the food segment and as the frequency of the visits are rising hence the demand of the customers has been that with economic pricing polices the restaurants should be able to provide quality food as well as variations. More than fifty percent of the respondents were of the opinion that they would change their taste of the hotels and preferences if provided with a good option.

2.4 Information processing tools

There were several information processing tools which have been used in the decision making process. This includes the improved IT infrastructure for the decision-making process as well as trying to increase more and more analytical tools for improving the technical outcomes of the report. Strategic, operational and tactical all three segments can be improved based on the change in the digital tools. In operational level the hotel can keep a database of the regular day-to-day expense that is taking place. In the strategic level the hotel can do a competitor analysis to find out what are the areas in which the other organizations are doing better than them and can accordingly improve them. Budget creation for the whole year as well as maintain the supply chain management the information from several sources will be required.

2.5 Project planning and critical path method

Activity

Preceding

Duration (Wks)

Float

Start

None

0

0

A

Start

1

1

B

Start

3

2

C

Start

5

0

D

A

9

1

E

B,C

2

0

F

C

3

5

G

D

4

1

H

E

8

0

I

F

2

5

End

G,H,I

0

0


Table 1: Table showing the critical path method

The critical path method is an algorithm for scheduling a set of project activities. CPM calculates the longest path of the planned activities to the logical end points where the earliest and of the projects and the latest starts and finishes off which helps in determining the critical activities where the total float is used.

 

2.6 Financial tools in evaluating the financial viability

YEAR

RATE

INITIAL INVESTMENT

PRESENT VALUE

0

10%

50000

$179,266.76

1

10%

45000

$147,193.44

2

10%

42000

$116,912.78

3

10%

37000

$86,604.06

4

10%

35000

$58,264.46

5

10%

32000

$29,090.91

NPV

IRR

YEAR

RATE

INITIAL INVESTMENT

IRR

0

10%

50000

7%

1

10%

45000

7%

2

10%

42000

7%

3

10%

37000

7%

4

10%

35000

7%

5

10%

32000

7%

 

In the two different methods of capital investment techniques it was found that the hotel will be able to improve on its profit sharing ratio to manage the continuity of the assignment. With an initial investment of $50000 the hotel will be able to earn more than thrice within its third and fourth year which is quite profitable. The IRR of the project is 7% which means that utilising the market rate and interest this amount of interest is possible because of the fact that as time grows the principle amount or the equity part will be reduced while the debt will go up. The biggest advantage of using this method is that the present value of the future income can be known as because the discounting factor is utilised. The challenges in using this methods would be the fact that for long-term projects the discounting factor keeps on changing which is not taken into account for NPV.

In case of internal rate of return the values of two different projects are being compared and evaluated but the main problem in this is that the method of calculation is very complicated.

Recommendation

It was found from the analysis that the prospect of opening up of a hotel in the city of London is a very good investment proposal as because the deviation from the expected outcome is not much as well as there are issues regarding the quality of food and pricing policy of the hotels that will give it an added advantage.

 

Reference List

Books

Brotby, W. (2009). Information security management metrics. Boca Raton: CRC Press..

Mendelsohn, L. (2012). Trend Forecasting with Intermarket Analysis. Hoboken: Wiley.

Plummer, T. (2010). Forecasting financial markets. London: Kogan Page.

Zhang, Z. (2014). Finance - Fundamental Problems and Solutions. Dordrecht: Springer

Journals

Carlson, K. and Wu, J. (2011). “The Illusion of Statistical Control: Control Variable Practice in Management Research”. Organizational Research Methods, 15(3), pp.413-435

GAO, X., XU, G. and ZHONG, Y. (2010). “Software process control model based on critical path method”. Journal of Computer Applications, 30(10), pp.2745-2748

Grigoletto, M. and Lisi, F. (2011). “Practical implications of higher moments in risk management”. Stat Methods Appl, 20(4), pp.487-506

Lee, S. (2014). “The Critical Path Search Based on Dual-Path Competition Method”. kiitr, 12(9)

Manly, B. (2007). “Using Statistical Methods for Water Quality Management: Issues, Problems, and Solutions”. Journal of the American Statistical Association, 102(479), pp.1080-1080

Shata, O. (2012). “Teaching Software Engineering: A Critical Path Method”. IJCCE, pp.151-154

Wang, Y. and Zou, J. (2013). “Statistical methods for large portfolio risk management”. Statistics and Its Interface, 6(4), pp.477-485

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