Qa For Business - Cafe
This document was uploaded by user and they confirmed that they have the permission to share it. If you are author or own the copyright of this book, please report to us by using this DMCA report form. Report DMCA
Overview
Download & View Qa For Business - Cafe as PDF for free.
More details
- Words: 6,069
- Pages: 33
2008
Quantitative Analysis for Business
Group 1: The Great Bear
HCM International University Linh Trung – Thu Duc – HCMC
Application Project INSTRUCTOR DR. HO THANH PHONG GROUP ONE
HO CHI MINH INTERNATIONAL UNIVERSITY BUSINESS ADMINSTRATION DERPARTMENT
QUANTITATIVE ANALYSIS FOR BUSINESS PROJECT INSTRUCTOR DR. HO THANH PHONG
Members of group 1. 2.
Le Minh Hai BA060089 Vo Le Duy BA060087
3. 4. 5. 6.
Vu Thanh Cong BA060052 Nguyen Anh Huy Vu BA060117 Vu Duc Giang BA060088 Nguyen Thi Kim Thao BA060105
Ho Chi Minh City, Vietnam July 7, 2008
Table of Contents A.
INTRODUCTION ...............................................................................................................1
B. 1. 2.
LITERATURE REVIEW....................................................................................................2 The Analytic Hierarchy Process ............................................................................................. 2 Software Selection by Using AHP .......................................................................................... 2
C. CRITERIA FOR SELECTING BUSINESS .........................................................................4 3. Analysis Capital: ........................................................................................................................... 4 For lease:............................................................................................................................................... 5 For Coffee-Food: ................................................................................................................................ 5 For The Fashion Shop: ..................................................................................................................... 7 4. Analysis the Break-event:......................................................................................................... 9 For lease:............................................................................................................................................... 9 For Coffee-Food: ............................................................................................................................. 10 For Fashion Shop:........................................................................................................................... 10 5. Description of Risk criterion ................................................................................................ 12 D. 6. 7. 8. 9.
APPLYING THE AHP .................................................................................................... 12 Structuring the Data ................................................................................................................ 12 Creating Pair-wise Comparison Matrix ............................................................................ 13 Determining Normalized Weights ..................................................................................... 13 Synthesize the Priorities ........................................................................................................ 16
E. CONCLUSIONS .................................................................................................................. 16 F.
REFERENCES..................................................................................................................... 17
G. APPENDIX.......................................................................................................................... 18 10. Simulation................................................................................................................................. 18 Fashion Shop .................................................................................................................................... 18 Cafe-Food Restaurant ................................................................................................................... 20 11. Survey result ............................................................................................................................ 23 Direct Survey and Online Survey ............................................................................................. 23
Preamble Quantitative Analysis for Management course is a useful subject for student. After studying this course, we have a change to apply the theoretical knowledge in a real situation. Though this project we studied: -
How to work in group. How to make the survey. Describe the quantitative analysis approach.
-
Describe the use of modeling in QA. Use computers and spreadsheet models to perform QA. Discuss possible problems in using quantitative analysis.
We highly appreciate this course. We would like thank: Associate Pro. Ho Thanh Phong Mr. Ho Nhat Quang Mr. Nguyen Hoang Minh Ms. Ha Thi Thanh Binh Ms. Nguyen Canh Tien BA students The managers and employees of Zenta coffee-food restaurant, Highland coffee shop, Hi-end coffee shop, KFC, Thoi Trang Moi fashion shop, Ninomax fashion shop…that help us finish this project.
Abstract In reality, everybody has to face the tradeoffs. Every day, even every second, we have to make many decisions. But, life is very complicated. Thus, making decision becomes more difficult than ever before. In fact, decision-making in field of business investment becomes more and more complex due to aggressive fluctuation of global economy, conflicting goals, continuous change of society. In this study, we discover the adequacy of Analytic Hierarchy Process to support decision making process. AHP is valuable even when being applied in case of conflicting goals, multiple criteria, with purpose to select the most suitable project from a set of alternatives. In this case, we you AHP analysis to select a highest priority project to make investing decision. To determine final decision, every alternative is carefully evaluated, which is based on 3 criteria. In this study, we consider AHP really works well and profoundly contributes to our decision process.
Quantitative Analysis for Business
Quantitative Analysis for Business APPLICATION PROJECT
A. INTRODUCTION The event of joining into WTO has help the Viet Nam economy become much better. After entering the world-wide market, there are many foreign business organizations have come to the country ,and that creates more jobs available to the Vietnamese employees, especially for graduated students. Applying for a job and working for some company is a common thought of most business students nowadays. And another way for business students to apply their all know ledges that learnt from schools is opening their own businesses. This is much interesting, much better for both the students and the economy as a whole as well. But wellinvesting is always difficult. In the case of having a business premises in the Dinh Tien Hoang street, district 1, HCM city, we could use that premises for renting, a cafeteria, or a fashion shop. Renting will give us a stable income with almost no risk, but you may be much richer if we are successful in the cafeteria or fashion shop investments. What is our decision? How is the decision made ?
Making the optimal decision among these kinds of investments may depend on the assesment of the objective, measurable criteria and subjective criteria. The investing decision requires not only considering the objectives, but also considering tangible or intangible factors or criteria affecting the final decision, and making the priorities among those criteria can be hard. It is suggested that the three components that drive the investing decision for the case are capital, profit and risk. The capital refers how much you should pay out to make your business ready for work, while the reference of the profit is the amount of money we can obtain. The risk consists on many kinds of risks that normally belong to two groups of business risk and economic risk.
The analytic hierarchy process (AHP) is a widely-used multi-criteria decision method introduced by Saaty. The AHP structures the decision problems into the hierarchy and evaluate multi-criteria tangible and intangible factors systematically. Page 1
The AHP has been applied to numerous fields that include business investment decisions.
The objectives of this paper is to propose a framework of decision criteria for evaluating and selecting kind of investing in this case based on the analytic hierarchy process.
The rest of the paper is organized as follows: section 2 gives an overview of the AHP methodology. Section 3 describes the selection criteria for the business investment. The applying of the AHP for evaluating and ranking criteria presented in section 4. Finally, section 5 includes conclusions of the case and necessary comments.
B. LITERATURE REVIEW 1. The Analytic Hierarchy Process AHP first developed by Saaty resolves decision-making problems by structuring each problem into a hierarchy with different levels of criteria. Pair-wise comparisons are performed with the criteria in a hierarchy by means of scale of measurement. The scale of relative importance measurement consists of judgments ranging from equal importance to extreme importance (equal, moderate, essential or strong, demonstrated, extreme) corresponding to the numerical judgments (1,3, 5, 7, 9) and compromises (2, 4, 6, 8) between these values The decision-maker needs to judge the relative importance of each criterion and then specify a preference on each criterion for decision alternatives. The AHP method involves four steps to solve a decision problem : Step 1: Structuring the decision problem The first step involves developing a hierarchical structure of the problem. The number of levels in the hierarchy depends on the complexity of the decision problem. The typical hierarchy of the AHP model consists of focus, criteria, sub-criteria and
Page 2
alternatives . The highest level of the hierarchy is the overall goal or focus. The intermediate levels consist of the criteria and sub-criteria for judging the alternatives. The need of intermediate levels depends on the decision problem and experiences of the AHP and domain knowledge for decision makers. The bottom level of the hierarchy contains alternatives from which the choice is to be made. There should not include too many criteria in a hierarchy . Step 2: Creating pair-wise comparison matrix Creating a pair-wise comparison matrix is an attempt to find the relative importance among the criteria. The nine-point scale is used to obtain a concise pair-wise comparison of all criteria at each level of the hierarchy . The pair-wise comparison judgments are made with respect to elements of one level of hierarchy given the element of the next higher level of hierarchy, starting from the top level down to the bottom level. For a group decision setting, every team member assigns his or her own pair-wise comparison. Four methods can combine the individual pair-wise comparison matrix to obtain the consensus pair-wise comparison matrix for the entire team: consensus; vote or compromise; geometric mean approach, and separate models or players . Step 3: Determining normalized weights The eigenvector derived from the matrix created in Step 2 measures of relative importance among the criteria and is used to determine the normalized and unique priority weights for each criterion. In order to check the consistency in setting priorities for pair-wise comparison with respect to criteria, the AHP uses a consistency ratio to measure the consistency of judgments. Saaty suggested the consistency ratio should be 0.1 or less. Step 4: Synthesize the priorities The final step is to synthesize the solution for the decision problem - to obtain the set of overall priorities for alternatives. The normalized local priority weights of criteria and sub-criteria obtained from Step 3 are aggregated to produce global composite weights which used to evaluate decision alternatives.
2. Software Selection by Using AHP
Page 3
To the case, decision-making in the business investment becomes more complex due to conflicting objectives ( e.g., low capital, high profit) and difficulties in assessing the multi-criteria. Different decision -makers may have different decisions. The case’s result limited to the business decision applications of the AHP. However, it demonstrates the diversity of the business investing decision applications where the AHP is used. Selecting the best
Capital
Profit
Risk
Economical Risk
For Rent
Cafeteria
Business Risk
Fashion Shop
Figure: The hierarchy for the business investing problem
C. CRITERIA FOR Selecting BUSINESS 3. Capital Analysis: One of the most important factors affect capital is location because high level of spending on business premises. Its expense directly influences profitability of a business. It might also influence which kind of business we should or should not invest, even, location will decide how much should be invested in that business. In the case that we have a business premises in the Dinh Tien Hoang Street, district 1, Ho Chi Minh City. This place is close to some big streets such as Nguyen Thi Minh Khai, Dien Bien Phu, Mac Dinh Chi, Vo Thi Sau, etc, which are considered as the center area of HCM
Page 4
city. There are many offices, high schools, universities, coffee shops, cafeteria shops, fashion shops in those streets. Therefore, it is the favorable sector for doing business. Owning this business premises is a competitive advantage. So, how to use this one to get highest profit is the main task. There are 3 alternatives to be considered: For rent, coffeefood, and fashion shop. To come up with decision, we evaluate which is most important, most suitable in those 3 alternatives. For lease: In order to attract people to rent (lease), our business premises should have good facilities. To adopt this goal, we have to renew business premises. And the expected cost for this plan is 300,000,000 vnđ. For this kind of business, we invest only once. Hence, the start-up cost = 300,000,000 vnđ For Coffee-Food: After investigating the surrounding environment of business premises, we realized that there were many offices, universities, high schools, etc. But there were few places for officers and students at the break times and few restaurants serving demand of breakfast and lunch of customer. Hence we decide Coffee-Food Restaurant as an alternative in our business plan. After determining the kind of business, we define the scale of project. This does mean we It means what prices will be suitable and what style. We made the survey people around this location then we get: The style of Coffee-Food
The average price per unit
Page 5
Drink
Breakfast Food
Lunch Food
Page 6
*Source1: Direct Survey and Online Survey From all of above information, we can define the scale of our Coffee-Food is medium level to attract customers have medium income and students. Then we can use the simulation method for some Coffee-Food has the scale like this to estimate the Demand Now we can decide how much we should invest on each of factors of the start-up-cost. The start-up cost = Cost of construction + Cost of decoration + COGS at 1 st week + Miscellaneous cost + Unexpected Cost - Cost of construction: because the probability of garden style is higher so we choose the architecture is garden. Then we estimate the cost of it is 1,400,000,000 vnđ - Cost of decoration: include cost of furniture, pictures, music instruments…Then we estimate the cost of it is 400,000,000vnđ. - Cost of goods sold at the 1st week: According to result of the simulation data from the 7 first dayys, we have the COGS for the 7 first days is 33,504,000 vnđ. - Unexpected cost: 16,496,000 vnđ - Miscellaneous cost: Promotion gifts, banner, advertising…Then we estimate the cost of it is 50,000,000vnđ. The start-up cost =1,400,000,000 + 400,000,000 + 33,504,000 + 16,496,000 + 50,000,000 = 1,900,000,000 vnđ For The Fashion Shop: We will explain why we choose Fashion Shop for our multiple business plans. Depend on our observation around our business premises, we realize that there are not only have some advantages like Fashion Shop but also have many fashion shops along this street. Moreover, to avoid the traffic jam at the rush hours, this way seems to be the best choice for people who are living in Binh Thanh district and Go Vap district. After determine the kind of business, we define the scale of project. It means what prices will be suitable and what style. We made the survey people around this location then we get: Probability of each price customer willing to buy Clothes
1
Appendix: Survey Result
Page 7
Trousers
*Source2: Direct Survey and Online Survey
From all of above information, we can define the scale of our Fashion shop. Then we can use the simulation method for some Fashion Shop has the scale like this to estimate the Demand Now we can decide how much we should invest on each of factors of the start-up-cost. The start-up cost = Cost of construction + Cost of decoration + COGS of the first month + Miscellaneous cost + Unexpected Expense
2
Appendix: Survey Result
Page 8
- Cost of construction: Because the architecture of a fashion shop is simpler. So we do need to rebuilt, we can renew it. By this way we can save a lot of fund. Then we estimate the cost of it is 170,000,000vnđ - Cost of decoration: include cost of furniture, shefts, clothes-hangers, music instruments…Then we estimate the cost of it is 65,000,000vnđ. - Cost of good sold of the 2 first weeks: According to result of the simulation data from the first month, we have the COGS 164,391,500 vnđ. - Unexpected expense: 25,608,500 vnđ - Miscellaneous cost: Promotion gifts, banner, advertising…Then we estimate the cost of it is 20,000,000vnđ. The start-up cost = 170,000,000 + 65,000,000 + 164,391,500 + 25,608,500 + 20,000,000 = 400,000,000vnđ
Start-up-cost
For Rent 300,000,000vnđ
Coffee-Food 1,900,000,000vnđ
Fashion Shop 400,000,000vnđ
4. Analysis the Break-event: Payback period is also one of the factor influence the decision making for business. For lease: The average price for lease of my premises is $2200 per month. Normally, we will receive payment for at least one year or more than one year– it depends on how long the contract does. Hence, Gross Profit
= 2800 x 12 x 16,800
= 564,480,000 vnđ
Income Tax
= 20.8% x 564,480,000
= 117,411,840 vnđ
Net Income
= 447,068,160 vnđ
Star-up-cost = 300,000,000 vnđ Therefore, the pay pack period equal 1 month.
Page 9
For Coffee-Food: After simulating 3 coffee shops and fast-food, we estimate the number of coffee and food selling per year by using the simulation method. Star-up-cost: we calculated on the analysis capital part. There are the cost of construction, decoration, miscellaneous, unexpected cost and operation cost for first week Sale: basing our projected coffee and food sales, we generate a conservative estimated by calculating the total number of customers. Then basing on the price we got from survey we can calculate the sale for each year. Cost of Goods Sold: the cost of goods sold for coffee-food related products was determined by the retail profit analysis. We assume that cost of coffee is 40% of the selling price. The cost of lunch and breakfast per unit is 60% of selling price. Salaries expense: we intend to hire eighteen full-time employees and ten part-time employees include: manager, cashier, cook, waiters, waitress, security guards… The average wage per full-time employee is 1,400,000vnđ/month and part-time employee is 700,000vnđ/month. Other operating expense: including electricity bills, water bills, gas, phone, internet, unexpected cost… Income tax: is 10% total income from continuing operations before income tax. Financial Sheet Start-up Cost
1,900,000,000.00
Net sale
3,543,360,000.00
Cost of Good sold
1,624,320,000.00
Gross profit
1,919,040,000.00
Operating Expenses Salaries Rent Other operating expenses Income from continuing operations before income tax Income tax Net income
388,800,000.00 144,000,000.00
532,800,000.00 1,386,240,000.00 138,624,000.00 1,247,616,000.00
For Fashion Shop:
Page 10
After simulating 3 fashion shops, we estimate the number of clothes and trousers selling per year by using the simulation method. Star-up-cost: we calculated on the analysis capital part. There are the cost of construction, decoration, miscellaneous, unexpected cost and operation cost for first week Sale: basing our projected clothes and trousers sales, we generate a conservative estimated by calculating the total number of customers. Then basing on the price for each product that we got from survey, we can calculate the sale for each year. Cost of Goods Sold: the cost of goods sold for coffee-food related products was determined by the retail profit analysis. We assume that cost of clothes is 70% of the selling price. The cost of trousers is 65% of selling price. Salaries expense: we intend to hire ten full-time employees and seven part-time employees include: manager, cashier, sellers, security guards… The average wage per full-time employee is 1,600,000vnđ/month and part-time employee is 800,000vnđ/month. Other operating expense: including electricity bills, water bills, unexpected cost… Income tax: is 10% total income from continuing operations before income tax. Financial Sheet Start-up Cost
400,000,000.00
Sale
2,689,284,000.00
Cost of Goods sold
1,890,470,400.00
Gross profit
893,300,400.00
Operating Expenses Salaries
259,200,000.00
Rent
-
Other operating expenses
66,000,000.00
Income from continuing operations before income tax
325,200,000.00 568,100,400.00
Income tax
56,810,040.00
Net income
511,290,360.00
Paypack period Start-up Cost
400,000,000.00 /Year
Net income
511,290,360.00 /Year
Paypack period (Start-up Cost /Net income )
Payback period (months)
0.78 Year 9.39 Month
For lease 1
Coffee-Food 19
Fashion Shop 10
Page 11
5. Description of Risk criterion The third criterion used to evaluate 3 alternatives is risk. Like many other criteria, risk has
5.
a very big influence in a business’s success, including business risk and economical risk. Business risk is the internal risk which comes from the inside of a business. In running a 5. business like a cafeteria or a fashion shop, the most internal risk a business has to face is
5. Management. A good management can lever the success of a business. For instance, good attitude, good behavior of employees can satisfy customer or high quality of product can
5.
reach or exceed customer’s need. Therefore, a good management can help a business to improve its competitive advantages, and to increase its position in the market as well. In
5.
contrast, a weak management is a barrier to a business. It is the reason of financial loss, bad employee’s behavior, and low quality product. Hence, it negatively affects reputation and 5. prestige of company in resulting. A weak management profoundly harms a business’s
5. reduces its ability to compete with others. When operating, a business faces not strength; only internal risk but also the risk from the outside of the company, which is called as
5.
“economical risk”. A business cannot control this type of risk, but in order to survive and develop, it has to itself adapt to the change of economy. The most reason of economical
5.
risk is the inflation which directly affects on a business. For instance, when inflation occurs, 5. the price of every goods suddenly increases; customer tends to pay less to save their money. As a result, the demand for goods decreases. In this case, a business faces
5. problems such as the profit decreases while spending on employees’ wage, price of many material increases simultaneously. Hence, a business finds many difficulties in competing
5.
with others and developing. For those reasons, risk is one of the most important criteria need be carefully evaluated when making decision to select the highest priority project.
5.
D. APPLYING THE AHP 5. The AHP modeling process involves four steps, namely, structuring the decision problem, creating 5. pair wise comparison matrix, determining normalized weights and synthesize the priorities.
5. 6. Structuring the Data 5. Page 12
5.
System Selection Problem The survey was pre-tested with the IU’s teachers and students to ensure that all the criteria were well formulated and properly understood. These respondents all have experience in QA. We tried to ask both students and teachers who give us general points of view about this case. The respondents in the pre-test were interviewed to discuss the selection criteria in more detail and reformulate the AHP hierarchy. We always receive a objective opinion from them that make the result of survey fairly and more accuracy. We also constructed the sub-criteria of Risk to specify the risk criterion and to give weight of risk for each alternative in next steps.
7. Creating Pair-wise Comparison Matrix It is very hard to collect data from people who is lack of experience about Quantitative Analysis, because they cannot responds as well as our expectation. A questionnaire including all criteria and sub-criteria of the nine levels AHP hierarchy was designed to collect the pair-wise comparison matrices. The questionnaire was composed of two sections. The first section includes all criteria and sub-criteria in which we asked participants about pair-wise comparison and guide them to select carefully and most appropriate with their idea. The second section included these matrixes to rate all criteria for each alternatives. As the result, we have five matrices. The collected data were then analyzed and normalized. We construct an average criterion comparison as following: CAPITAL
PROFIT
RISK
CAPITAL
1
2.075
2.53
PROFIT
0.483
1
1.51
RISK
0.395
0.662
1
8. Determining Normalized Weights In this part, the pair-wise comparison matrices obtained from experts are combined by using the mean approach. The consistency ratio (CR) of each pair-wise comparison matrix is also shown. It can be found that the CR values are far less than 0.1, the value suggested by Saaty. This indicates that the experts’ opinions are consistent in measuring the pair-wise comparison judgments. Besides, the CR values between matrices filled out by the same experts are also less than 0.1. This implies that the data in each questionnaire are consistent. Firstly, we are going to check this result of the survey by calculating the consistency ration (CR):
Page 13
Normalize values: The number in the matrix is divided by their respective column totals as follow: CAPITAL 1.597 0.771 0.63
CAPITAL PROFIT RISK
PROFIT 1.667 0.803 0.531
RISK 1.505 0.898 0.595
Find the average of the various rows from the matrix as follows: AVERAGE 1.589 0.824 0.585
CAPITAL PROFIT RISK
We move to determine the vector consistency by multiplying the pair-wise matrix with average column: CAPITAL PROFIT
RISK
CAPITAL
1
2.075
2.53
PROFIT
0.483
1
1.51
0.824
RISK
0.395
0.662
1
0.585
X
1.589
The result: 4.778 2.474 1.761 We move to determine the consistency index (CI) 4.778/1.589 2.474/0.824 1.761/0.585
3.006 3.002 3.010
Page 14
The average value of consistency vector: =3.006
CI CR
n n 1
= (3.006-3)/(3-1)=0.003
CI = (0.003/0.58)=0.00517 RI
Since 0< CR < 0.1, we accept this result. Do similarly, we also calculate the CR of the table of sub-criteria of risk, we see that: ECONOMICAL 1 0.684
ECONOMICAL BUSINESS
BUSINESS 1.46 1
For two factors in this matrix are always right. After calculating the CR, we have priority table for each criteria: For three criteria: CAPITAL PROFIT RISK
CAPITAL 1 0.483 0.395
PROFIT 2.075 1 0.662
RISK 2.53 1.51 1
PRIORITY 0.526 0.281 0.193
For two risk criteria: ECONOMICAL BUSINESS
ECONOMICAL 1 0.684
BUSINESS 1.46 1
PRIORITY 0.594 0.406
In conclusion, we can do similarly for many times to find out the lowest consistency ratio for criteria. However in this case we have a careful survey and guideline that give us objective opinion about our criteria, that is why the consistency ratio is pretty low in acceptable interval that is smaller than 0.1. Finally we use this result to get a general and objective view about our case.
Page 15
9. Synthesize the Priorities Another important part is to give weight for each alternative and make decision. After calculating the normalized priority weights for each pair-wise comparison matrix of the AHP hierarchy, the next step is to synthesize the local priority weights of criteria and subcriteria for obtaining the set of global composite priorities. In this case, the scale for PROFIT, Capital scale, we take it by calculating the percentage of each criterion in total then inversing them, for risk scale, we take it by combination between risk priority above and CAPITAL, scale with CAPITAL relates to economic risk and PROFIT relates to business risk as we take the sum of product of CAPITAL and economic risk and product of PROFIT and business risk. Basing on the analysis of CAPIATAL and PROFIT, and risk description, risk survey and the dependence of risk from CAPITAL and PROFIT, we can give factor evaluation for each alternative as following: Factor FOR RENT CAFETERIA FASHION SHOP
CAPITAL 8.695 1.368 6.493
PROFIT 2.45 6.95 3.24
RISK 6.16 3.63 5.17
Then, we have result table: Factor FOR RENT CAFETERIA FASHION SHOP Priority
CAPITAL 8.695 1.368 6.493 0.526
PROFIT 2.45 6.95 3.24 0.281
RISK 6.16 3.63 5.17 0.193
Result 6.45 3.37 5.32
Look at the result table above, the final decision should be FOR RENT alternative.
E. CONCLUSIONS Nowadays, decision making becomes more and more complicated for businessman. Every decision makers have to deal with dramatically increasing alternatives, many conflicting goals due to aggressive fluctuation of global economy. Thus, most of decision is multiplecriteria decision. In this paper, we find out adequacy of AHP to support decision making. A framework of 3 criteria was used to evaluate AHP. 7
Page 16
Quantitative Analysis for Business
F. REFERENCES
Barry Render & Ralph M. Stair, Jr. & Michael E. Hanna. Quantitative Analysis for Management, 8E Textbook www.wikipedia.com http://www.bplans.com/Sample_Business_Plans
Page 17
Quantitative Analysis for Business
G. APPENDIX 10.
Simulation
Fashion Shop Clothes Demand Table Number of Demand
Prob.
Lower
Cum.
Demand
Total
5
0.17
0
0.17
16
80
6
0.2
0.17
0.37
25
150
9
0.3
0.37
0.67
29
261
4
0.13
0.67
0.8
35
140
3
0.1
0.8
0.9
48
144
2
0.07
0.9
0.97
54
108
1
0.03
0.97
1
80
80
30
1
Price (x1000VNĐ )
Average Price (x1000VNĐ )
963 Prob.
Demand
Sale (x1000VNĐ )
70-150
110
0.5
481.5
52965
150-250
200
0.36
346.68
69336
250-350
300
0.14
134.82
40446
963
162747
Total
Price per unit (x1000VNĐ) `
169
Trousers Demand Table Number of Demand
Prob.
Lower
Cum.
Demand
Total
7
0.23
0
0.23
7
49
8
0.27
0.23
0.5
9
72
6
0.2
0.5
0.7
11
66
3
0.1
0.7
0.8
15
45
3
0.1
0.8
0.9
18
54
2
0.07
0.9
0.97
20
40
0.97
1
22
1
0.03
30
1
Price (x1000VNĐ )
Average Price (x1000VNĐ )
22 348
Prob.
Demand
Sale (x1000VNĐ )
100-150
125
0.14
48.72
6090
150-200
175
0.57
198.36
34713
200-300
250
0.21
73.08
18270
300-400
350
0.07
24.36
8526
344.52
67599
Price per unit (x1000VNĐ) `
196
Page 18
Average price of Clothes
169000
Average price of Trousers
196000
Percent expense Clothes
0.7
Percent expense Trousers
0.65
Day
Ran. No1
Clothes
Ran. No2
Trousers
COGS
1
0.08
16.00
0.44
9
3,039,400.00
4,468,000.00
1,428,600.00
2
0.74
35.00
0.77
15
6,051,500.00
8,855,000.00
2,803,500.00
3
0.64
29.00
0.80
18
5,723,900.00
8,429,000.00
2,705,100.00
4
0.17
25.00
0.28
9
4,104,100.00
5,989,000.00
1,884,900.00
5
0.01
16.00
0.00
7
2,784,600.00
4,076,000.00
1,291,400.00
6
0.01
16.00
0.98
22
4,695,600.00
7,016,000.00
2,320,400.00
7
0.23
25.00
0.71
15
4,868,500.00
7,165,000.00
2,296,500.00
8
0.13
16.00
0.54
11
3,294,200.00
4,860,000.00
1,565,800.00
9
0.42
29.00
0.55
11
4,832,100.00
7,057,000.00
2,224,900.00
10
0.09
16.00
0.76
15
3,803,800.00
5,644,000.00
1,840,200.00
11
0.17
25.00
0.65
11
4,358,900.00
6,381,000.00
2,022,100.00
12
0.48
29.00
0.66
11
4,832,100.00
7,057,000.00
2,224,900.00
13
0.77
35.00
0.87
18
6,433,700.00
9,443,000.00
3,009,300.00
14
0.99
80.00
0.40
9
10,610,600.00
15,284,000.00
4,673,400.00
15
0.06
16.00
0.74
15
3,803,800.00
5,644,000.00
1,840,200.00
16
0.18
25.00
0.75
15
4,868,500.00
7,165,000.00
2,296,500.00
17
0.54
29.00
0.67
11
4,832,100.00
7,057,000.00
2,224,900.00
18
0.89
48.00
0.23
9
6,825,000.00
9,876,000.00
3,051,000.00
19
0.56
29.00
0.82
18
5,723,900.00
8,429,000.00
2,705,100.00
20
0.40
29.00
0.55
11
4,832,100.00
7,057,000.00
2,224,900.00
21
0.43
29.00
0.52
11
4,832,100.00
7,057,000.00
2,224,900.00
22
0.92
54.00
0.29
9
7,534,800.00
10,890,000.00
3,355,200.00
23
0.39
29.00
0.31
9
4,577,300.00
6,665,000.00
2,087,700.00
24
0.73
35.00
1.00
22
6,943,300.00
10,227,000.00
3,283,700.00
25
0.10
16.00
0.90
20
4,440,800.00
6,624,000.00
2,183,200.00
26
0.39
29.00
0.32
9
4,577,300.00
6,665,000.00
2,087,700.00
27
0.01
16.00
0.05
7
2,784,600.00
4,076,000.00
1,291,400.00
28
0.65
29.00
0.59
11
4,832,100.00
7,057,000.00
2,224,900.00
29
0.77
35.00
0.37
9
5,287,100.00
7,679,000.00
2,391,900.00
30
0.70
35.00
0.90
20
Total
Net sale
Gross profit
6,688,500.00
9,835,000.00
3,146,500.00
152,816,300.00
223,727,000.00
70,910,700.00
Page 19
Financial Sheet Start-up Cost
400,000,000.00
Sale
2,689,284,000.00
Cost of Goods sold
1,890,470,400.00
Gross profit
893,300,400.00
Operating Expenses Salaries
259,200,000.00
Rent
-
Other operating expenses
66,000,000.00
Income from continuing operations before income tax
325,200,000.00 568,100,400.00
Income tax Net income
56,810,040.00 511,290,360.00
Pay pack period Start-up Cost
400,000,000.00
Net income
511,290,360.00
Pay pack period (months)
9.39
Cafe-Food Restaurant Drink Demand Table Number of Times
Total
Prob.
Lower
Cum.
Demand
6
0.2
0
0.2
180
9
0.3
0.2
0.5
280
7
0.23
0.5
0.73
300
5
0.17
0.73
0.9
320
3
0.1
0.9
1
350
30
1
Lunch Food Demand Table Number of Times
Total
Prob.
Lower
Cum.
Demand
4
0.13
0
0.13
50
4
0.13
0.13
0.27
70
5
0.17
0.27
0.43
100
9
0.3
0.43
0.73
120
8
0.27
0.73
1
150
30
1
Page 20
Average price Drinks
24000.00
Foods
28000.00
Expenses percentage Drink
0.4
Food
0.6
Day
Ran. No1
Drink
Ran. No2
Food
COGS
Net sale
Gross profit
50
4,200,000.00
9,800,000.00
5,600,000.00
1
0.94
350
0.03
2
0.45
280
0.15
70
3,864,000.00
8,680,000.00
4,816,000.00
4,248,000.00
8,520,000.00
4,272,000.00
3
0.05
180
0.78
150
4
0.95
350
0.8
150
5,880,000.00
12,600,000.00
6,720,000.00
5
0.56
300
0.84
150
5,400,000.00
11,400,000.00
6,000,000.00
5,208,000.00
10,920,000.00
5,712,000.00
6
0.42
280
0.81
150
7
0.23
280
0.44
120
4,704,000.00
10,080,000.00
5,376,000.00
8
0.38
280
0.36
100
4,368,000.00
9,520,000.00
5,152,000.00
9
0.4
280
0.18
70
3,864,000.00
8,680,000.00
4,816,000.00
10
0.76
320
0.03
50
3,912,000.00
9,080,000.00
5,168,000.00
11
0.92
350
0.02
50
4,200,000.00
9,800,000.00
5,600,000.00
12
0.9
350
0.33
100
5,040,000.00
11,200,000.00
6,160,000.00
13
0.59
300
0.83
150
5,400,000.00
11,400,000.00
6,000,000.00
14
0.88
320
0.17
70
4,248,000.00
9,640,000.00
5,392,000.00
15
0.79
320
0.92
150
5,592,000.00
11,880,000.00
6,288,000.00
16
0.23
280
0.13
70
3,864,000.00
8,680,000.00
4,816,000.00
17
0.67
300
0.42
100
4,560,000.00
10,000,000.00
5,440,000.00
18
0.58
300
0.04
50
3,720,000.00
8,600,000.00
4,880,000.00
4,704,000.00
10,080,000.00
5,376,000.00
19
0.46
280
0.65
120
20
0.23
280
0.72
120
4,704,000.00
10,080,000.00
5,376,000.00
21
0.57
300
0.11
50
3,720,000.00
8,600,000.00
4,880,000.00
3,744,000.00
7,680,000.00
3,936,000.00
11,760,000.00
6,384,000.00
22
0.13
180
0.62
120
23
0.91
350
0.62
120
5,376,000.00
24
0.05
180
0.32
100
3,408,000.00
7,120,000.00
3,712,000.00
25
0.91
350
0.74
150
5,880,000.00
12,600,000.00
6,720,000.00
26
0.29
280
0.94
150
5,208,000.00
10,920,000.00
5,712,000.00
27
0.22
280
0.1
50
3,528,000.00
8,120,000.00
4,592,000.00
28
0.16
180
0.39
100
3,408,000.00
7,120,000.00
3,712,000.00
29
0.39
280
0.01
50
3,528,000.00
8,120,000.00
4,592,000.00
30
0.99
350
0.78
150
Total
5,880,000.00
12,600,000.00
6,720,000.00
135,360,000.00
295,280,000.00
159,920,000.00
Page 21
Financial Sheet Start-up Cost
1,900,000,000.00
Net sale
3,543,360,000.00
Cost of Good sold
1,624,320,000.00
Gross profit
1,919,040,000.00
Operating Expenses Salaries
388,800,000.00
Rent
-
Other operating expenses
144,000,000.00
Income from continuing operations before income tax Income tax
532,800,000.00 1,386,240,000.00 138,624,000.00
Net income
1,247,616,000.00
Paypack period Start-up Cost
1,900,000,000.00 /Year
Net income
1,247,616,000.00/ Year
Paypack period (Start-up Cost /Net income )
1.52 Year or 18.27 Month
Page 22
11.
Survey result
Direct Survey and Online Survey Frequency Table Xin hoi muc do mua sam cua anh/chi nhu the nao
Frequency Valid
Percent
Valid Percent
Cumulative Percent
Moi tuan 1 lan.
5
5.0
5.0
5.0
Moi thang 1 lan.
15
15.0
15.0
20.0
2-3 lan mot nam.
10
10.0
10.0
30.0
70
70.0
70.0
100.0
100
100.0
100.0
Thich thi mua (khong co ke hoach). Total
Moi lan mua sam anh chi thuong mua bao nhieu quan/ao
Frequency Valid
Percent
Valid Percent
Cumulative Percent
1-3 quan/ao.
85
85.0
85.0
85.0
3-5 quan/ao.
15
15.0
15.0
100.0
100
100.0
100.0
Total
Moi mot ao thuong tri gia bao nhieu
Frequency Valid
Percent
Valid Percent
Cumulative Percent
70.000-150.000
50
50.0
50.0
50.0
150.000-200.000
36
36.0
36.0
86.0
200.000-300.000
14
14.0
14.0
100.0
100
100.0
100.0
Total
Moi mot quan thuong tri gia bao nhieu
Frequency Valid
Percent
Valid Percent
Cumulative Percent
100.000 - 150.000
14
14.0
14.0
14.0
150.000 - 200.000
59
59.0
59.0
73.0
Page 23
200.000 - 300.000 Gia khac Total
20
20.0
20.0
93.0
7
7.0
7.0
100.0
100
100.0
100.0
Anh chi thuong thich su dung hang xuat xu tu dau
Frequency Valid
Percent
Valid Percent
Cumulative Percent
Viet Nam.
20
20.0
20.0
20.0
Trung Quoc/ Hong Kong
40
40.0
40.0
60.0
10
10.0
10.0
70.0
30
30.0
30.0
100.0
100
100.0
100.0
Hang hieu ( Louis Vuiton, Tommy, Gap, Lacoste…). Y kien khac Total
Truoc tinh trang lam phat hien nay, gia tieu dung leo thang thi nhu cau mua sam cua anh chi co giam bot hay khong
Frequency Valid
Percent
Valid Percent
Cumulative Percent
Khong anh huong
11
11.0
11.0
11.0
Rat it anh huong
42
42.0
42.0
53.0
Kha anh huong
32
32.0
32.0
85.0
Kha anh huong
15
15.0
15.0
100.0
100
100.0
100.0
Total
Ban thich quan cafe-food co kien truc nhu the nao?
Frequency Valid
Percent
Valid Percent
Cumulative Percent
Kien truc mo
64
64.0
64.0
64.0
Kien truc hien dai
36
36.0
36.0
100.0
100
100.0
100.0
Total
Anh/chi co thuong den quan cafe-food vao nhung luc nao
Frequency Valid
Moi ngay
10
Percent
Valid Percent 10.0
11.1
Cumulative Percent 11.1
Page 24
Missing
1 – 3 lan/tuan
30
30.0
33.3
44.4
3 - 5 lan/tuan
15
15.0
16.7
61.1
1 – 2 lan/thang
35
35.0
38.9
100.0
Total
90
90.0
100.0
System
10
10.0
100
100.0
Total
Muc dich anh/chi di den quan cafe-food de
Frequency
Percent
Valid Percent
Valid
1
85
85.0
Missing
System
15
15.0
100
100.0
Total
Cumulative Percent
100.0
100.0
Anh/chi co thuong den quan cafe-food vao nhung luc nao
Frequency
Percent
Valid Percent
Valid
1
20
20.0
Missing
System
80
80.0
100
100.0
Total
Cumulative Percent
100.0
100.0
Muc dich anh/chi di den quan cafe-food de
Frequency
Percent
Valid Percent
Valid
1
20
20.0
Missing
System
80
80.0
100
100.0
Total
Cumulative Percent
100.0
100.0
Chi phi cho moi hoa don cua anh/chi thuong la bao nhieu tren 1 nguoi cho thuc uong
Frequency Valid
Percent
Valid Percent
Cumulative Percent
< 20.000
18
18.0
18.0
18.0
30.000 - 35.000
19
19.0
19.0
37.0
1
1.0
1.0
38.0
62
62.0
62.0
100.0
100
100.0
100.0
> 50.000 20.000 - 25.000 Total
Page 25
Neu quan cafe-food gan cong ty anh/chi co phuc vu them thuc an sang va com trua van phong, anh/chi co san sang su dung dich vu do khong
Frequency Valid
Percent
Valid Percent
Cumulative Percent
Dong y
86
86.0
86.0
86.0
Khong dong y
14
14.0
14.0
100.0
100
100.0
100.0
Total
Theo anh/chi gia cho thuc an sang bao nhieu la hop ly
Frequency Valid
Percent
Valid Percent
Cumulative Percent
10.000 - 15.000
36
36.0
36.0
36.0
15.000 - 20.000
63
63.0
63.0
99.0
20.000 - 25.000
1
1.0
1.0
100.0
100
100.0
100.0
Total
Theo anh/chi gia cho mot suat com trua van phong la hop ly
Frequency Valid
Percent
Valid Percent
Cumulative Percent
15.000 - 20.000
30
30.0
30.0
30.0
20.000 - 25.000
64
64.0
64.0
94.0
25.000 - 30.000
6
6.0
6.0
100.0
100
100.0
100.0
Total
Truoc tinh trang lam phat hien nay, gia tieu dung leo thang thi nhu cau mua sam cua anh chi co giam bot hay khong
Frequency Valid
Percent
Valid Percent
Cumulative Percent
Khong anh huong
12
12.0
12.0
12.0
Rat it anh huong
20
20.0
20.0
32.0
Kha anh huong
63
63.0
63.0
95.0
Rat anh huong
5
5.0
5.0
100.0
100
100.0
100.0
Total
Page 26
Page 27
Quantitative Analysis for Business
Group 1: The Great Bear
HCM International University Linh Trung – Thu Duc – HCMC
Application Project INSTRUCTOR DR. HO THANH PHONG GROUP ONE
HO CHI MINH INTERNATIONAL UNIVERSITY BUSINESS ADMINSTRATION DERPARTMENT
QUANTITATIVE ANALYSIS FOR BUSINESS PROJECT INSTRUCTOR DR. HO THANH PHONG
Members of group 1. 2.
Le Minh Hai BA060089 Vo Le Duy BA060087
3. 4. 5. 6.
Vu Thanh Cong BA060052 Nguyen Anh Huy Vu BA060117 Vu Duc Giang BA060088 Nguyen Thi Kim Thao BA060105
Ho Chi Minh City, Vietnam July 7, 2008
Table of Contents A.
INTRODUCTION ...............................................................................................................1
B. 1. 2.
LITERATURE REVIEW....................................................................................................2 The Analytic Hierarchy Process ............................................................................................. 2 Software Selection by Using AHP .......................................................................................... 2
C. CRITERIA FOR SELECTING BUSINESS .........................................................................4 3. Analysis Capital: ........................................................................................................................... 4 For lease:............................................................................................................................................... 5 For Coffee-Food: ................................................................................................................................ 5 For The Fashion Shop: ..................................................................................................................... 7 4. Analysis the Break-event:......................................................................................................... 9 For lease:............................................................................................................................................... 9 For Coffee-Food: ............................................................................................................................. 10 For Fashion Shop:........................................................................................................................... 10 5. Description of Risk criterion ................................................................................................ 12 D. 6. 7. 8. 9.
APPLYING THE AHP .................................................................................................... 12 Structuring the Data ................................................................................................................ 12 Creating Pair-wise Comparison Matrix ............................................................................ 13 Determining Normalized Weights ..................................................................................... 13 Synthesize the Priorities ........................................................................................................ 16
E. CONCLUSIONS .................................................................................................................. 16 F.
REFERENCES..................................................................................................................... 17
G. APPENDIX.......................................................................................................................... 18 10. Simulation................................................................................................................................. 18 Fashion Shop .................................................................................................................................... 18 Cafe-Food Restaurant ................................................................................................................... 20 11. Survey result ............................................................................................................................ 23 Direct Survey and Online Survey ............................................................................................. 23
Preamble Quantitative Analysis for Management course is a useful subject for student. After studying this course, we have a change to apply the theoretical knowledge in a real situation. Though this project we studied: -
How to work in group. How to make the survey. Describe the quantitative analysis approach.
-
Describe the use of modeling in QA. Use computers and spreadsheet models to perform QA. Discuss possible problems in using quantitative analysis.
We highly appreciate this course. We would like thank: Associate Pro. Ho Thanh Phong Mr. Ho Nhat Quang Mr. Nguyen Hoang Minh Ms. Ha Thi Thanh Binh Ms. Nguyen Canh Tien BA students The managers and employees of Zenta coffee-food restaurant, Highland coffee shop, Hi-end coffee shop, KFC, Thoi Trang Moi fashion shop, Ninomax fashion shop…that help us finish this project.
Abstract In reality, everybody has to face the tradeoffs. Every day, even every second, we have to make many decisions. But, life is very complicated. Thus, making decision becomes more difficult than ever before. In fact, decision-making in field of business investment becomes more and more complex due to aggressive fluctuation of global economy, conflicting goals, continuous change of society. In this study, we discover the adequacy of Analytic Hierarchy Process to support decision making process. AHP is valuable even when being applied in case of conflicting goals, multiple criteria, with purpose to select the most suitable project from a set of alternatives. In this case, we you AHP analysis to select a highest priority project to make investing decision. To determine final decision, every alternative is carefully evaluated, which is based on 3 criteria. In this study, we consider AHP really works well and profoundly contributes to our decision process.
Quantitative Analysis for Business
Quantitative Analysis for Business APPLICATION PROJECT
A. INTRODUCTION The event of joining into WTO has help the Viet Nam economy become much better. After entering the world-wide market, there are many foreign business organizations have come to the country ,and that creates more jobs available to the Vietnamese employees, especially for graduated students. Applying for a job and working for some company is a common thought of most business students nowadays. And another way for business students to apply their all know ledges that learnt from schools is opening their own businesses. This is much interesting, much better for both the students and the economy as a whole as well. But wellinvesting is always difficult. In the case of having a business premises in the Dinh Tien Hoang street, district 1, HCM city, we could use that premises for renting, a cafeteria, or a fashion shop. Renting will give us a stable income with almost no risk, but you may be much richer if we are successful in the cafeteria or fashion shop investments. What is our decision? How is the decision made ?
Making the optimal decision among these kinds of investments may depend on the assesment of the objective, measurable criteria and subjective criteria. The investing decision requires not only considering the objectives, but also considering tangible or intangible factors or criteria affecting the final decision, and making the priorities among those criteria can be hard. It is suggested that the three components that drive the investing decision for the case are capital, profit and risk. The capital refers how much you should pay out to make your business ready for work, while the reference of the profit is the amount of money we can obtain. The risk consists on many kinds of risks that normally belong to two groups of business risk and economic risk.
The analytic hierarchy process (AHP) is a widely-used multi-criteria decision method introduced by Saaty. The AHP structures the decision problems into the hierarchy and evaluate multi-criteria tangible and intangible factors systematically. Page 1
The AHP has been applied to numerous fields that include business investment decisions.
The objectives of this paper is to propose a framework of decision criteria for evaluating and selecting kind of investing in this case based on the analytic hierarchy process.
The rest of the paper is organized as follows: section 2 gives an overview of the AHP methodology. Section 3 describes the selection criteria for the business investment. The applying of the AHP for evaluating and ranking criteria presented in section 4. Finally, section 5 includes conclusions of the case and necessary comments.
B. LITERATURE REVIEW 1. The Analytic Hierarchy Process AHP first developed by Saaty resolves decision-making problems by structuring each problem into a hierarchy with different levels of criteria. Pair-wise comparisons are performed with the criteria in a hierarchy by means of scale of measurement. The scale of relative importance measurement consists of judgments ranging from equal importance to extreme importance (equal, moderate, essential or strong, demonstrated, extreme) corresponding to the numerical judgments (1,3, 5, 7, 9) and compromises (2, 4, 6, 8) between these values The decision-maker needs to judge the relative importance of each criterion and then specify a preference on each criterion for decision alternatives. The AHP method involves four steps to solve a decision problem : Step 1: Structuring the decision problem The first step involves developing a hierarchical structure of the problem. The number of levels in the hierarchy depends on the complexity of the decision problem. The typical hierarchy of the AHP model consists of focus, criteria, sub-criteria and
Page 2
alternatives . The highest level of the hierarchy is the overall goal or focus. The intermediate levels consist of the criteria and sub-criteria for judging the alternatives. The need of intermediate levels depends on the decision problem and experiences of the AHP and domain knowledge for decision makers. The bottom level of the hierarchy contains alternatives from which the choice is to be made. There should not include too many criteria in a hierarchy . Step 2: Creating pair-wise comparison matrix Creating a pair-wise comparison matrix is an attempt to find the relative importance among the criteria. The nine-point scale is used to obtain a concise pair-wise comparison of all criteria at each level of the hierarchy . The pair-wise comparison judgments are made with respect to elements of one level of hierarchy given the element of the next higher level of hierarchy, starting from the top level down to the bottom level. For a group decision setting, every team member assigns his or her own pair-wise comparison. Four methods can combine the individual pair-wise comparison matrix to obtain the consensus pair-wise comparison matrix for the entire team: consensus; vote or compromise; geometric mean approach, and separate models or players . Step 3: Determining normalized weights The eigenvector derived from the matrix created in Step 2 measures of relative importance among the criteria and is used to determine the normalized and unique priority weights for each criterion. In order to check the consistency in setting priorities for pair-wise comparison with respect to criteria, the AHP uses a consistency ratio to measure the consistency of judgments. Saaty suggested the consistency ratio should be 0.1 or less. Step 4: Synthesize the priorities The final step is to synthesize the solution for the decision problem - to obtain the set of overall priorities for alternatives. The normalized local priority weights of criteria and sub-criteria obtained from Step 3 are aggregated to produce global composite weights which used to evaluate decision alternatives.
2. Software Selection by Using AHP
Page 3
To the case, decision-making in the business investment becomes more complex due to conflicting objectives ( e.g., low capital, high profit) and difficulties in assessing the multi-criteria. Different decision -makers may have different decisions. The case’s result limited to the business decision applications of the AHP. However, it demonstrates the diversity of the business investing decision applications where the AHP is used. Selecting the best
Capital
Profit
Risk
Economical Risk
For Rent
Cafeteria
Business Risk
Fashion Shop
Figure: The hierarchy for the business investing problem
C. CRITERIA FOR Selecting BUSINESS 3. Capital Analysis: One of the most important factors affect capital is location because high level of spending on business premises. Its expense directly influences profitability of a business. It might also influence which kind of business we should or should not invest, even, location will decide how much should be invested in that business. In the case that we have a business premises in the Dinh Tien Hoang Street, district 1, Ho Chi Minh City. This place is close to some big streets such as Nguyen Thi Minh Khai, Dien Bien Phu, Mac Dinh Chi, Vo Thi Sau, etc, which are considered as the center area of HCM
Page 4
city. There are many offices, high schools, universities, coffee shops, cafeteria shops, fashion shops in those streets. Therefore, it is the favorable sector for doing business. Owning this business premises is a competitive advantage. So, how to use this one to get highest profit is the main task. There are 3 alternatives to be considered: For rent, coffeefood, and fashion shop. To come up with decision, we evaluate which is most important, most suitable in those 3 alternatives. For lease: In order to attract people to rent (lease), our business premises should have good facilities. To adopt this goal, we have to renew business premises. And the expected cost for this plan is 300,000,000 vnđ. For this kind of business, we invest only once. Hence, the start-up cost = 300,000,000 vnđ For Coffee-Food: After investigating the surrounding environment of business premises, we realized that there were many offices, universities, high schools, etc. But there were few places for officers and students at the break times and few restaurants serving demand of breakfast and lunch of customer. Hence we decide Coffee-Food Restaurant as an alternative in our business plan. After determining the kind of business, we define the scale of project. This does mean we It means what prices will be suitable and what style. We made the survey people around this location then we get: The style of Coffee-Food
The average price per unit
Page 5
Drink
Breakfast Food
Lunch Food
Page 6
*Source1: Direct Survey and Online Survey From all of above information, we can define the scale of our Coffee-Food is medium level to attract customers have medium income and students. Then we can use the simulation method for some Coffee-Food has the scale like this to estimate the Demand Now we can decide how much we should invest on each of factors of the start-up-cost. The start-up cost = Cost of construction + Cost of decoration + COGS at 1 st week + Miscellaneous cost + Unexpected Cost - Cost of construction: because the probability of garden style is higher so we choose the architecture is garden. Then we estimate the cost of it is 1,400,000,000 vnđ - Cost of decoration: include cost of furniture, pictures, music instruments…Then we estimate the cost of it is 400,000,000vnđ. - Cost of goods sold at the 1st week: According to result of the simulation data from the 7 first dayys, we have the COGS for the 7 first days is 33,504,000 vnđ. - Unexpected cost: 16,496,000 vnđ - Miscellaneous cost: Promotion gifts, banner, advertising…Then we estimate the cost of it is 50,000,000vnđ. The start-up cost =1,400,000,000 + 400,000,000 + 33,504,000 + 16,496,000 + 50,000,000 = 1,900,000,000 vnđ For The Fashion Shop: We will explain why we choose Fashion Shop for our multiple business plans. Depend on our observation around our business premises, we realize that there are not only have some advantages like Fashion Shop but also have many fashion shops along this street. Moreover, to avoid the traffic jam at the rush hours, this way seems to be the best choice for people who are living in Binh Thanh district and Go Vap district. After determine the kind of business, we define the scale of project. It means what prices will be suitable and what style. We made the survey people around this location then we get: Probability of each price customer willing to buy Clothes
1
Appendix: Survey Result
Page 7
Trousers
*Source2: Direct Survey and Online Survey
From all of above information, we can define the scale of our Fashion shop. Then we can use the simulation method for some Fashion Shop has the scale like this to estimate the Demand Now we can decide how much we should invest on each of factors of the start-up-cost. The start-up cost = Cost of construction + Cost of decoration + COGS of the first month + Miscellaneous cost + Unexpected Expense
2
Appendix: Survey Result
Page 8
- Cost of construction: Because the architecture of a fashion shop is simpler. So we do need to rebuilt, we can renew it. By this way we can save a lot of fund. Then we estimate the cost of it is 170,000,000vnđ - Cost of decoration: include cost of furniture, shefts, clothes-hangers, music instruments…Then we estimate the cost of it is 65,000,000vnđ. - Cost of good sold of the 2 first weeks: According to result of the simulation data from the first month, we have the COGS 164,391,500 vnđ. - Unexpected expense: 25,608,500 vnđ - Miscellaneous cost: Promotion gifts, banner, advertising…Then we estimate the cost of it is 20,000,000vnđ. The start-up cost = 170,000,000 + 65,000,000 + 164,391,500 + 25,608,500 + 20,000,000 = 400,000,000vnđ
Start-up-cost
For Rent 300,000,000vnđ
Coffee-Food 1,900,000,000vnđ
Fashion Shop 400,000,000vnđ
4. Analysis the Break-event: Payback period is also one of the factor influence the decision making for business. For lease: The average price for lease of my premises is $2200 per month. Normally, we will receive payment for at least one year or more than one year– it depends on how long the contract does. Hence, Gross Profit
= 2800 x 12 x 16,800
= 564,480,000 vnđ
Income Tax
= 20.8% x 564,480,000
= 117,411,840 vnđ
Net Income
= 447,068,160 vnđ
Star-up-cost = 300,000,000 vnđ Therefore, the pay pack period equal 1 month.
Page 9
For Coffee-Food: After simulating 3 coffee shops and fast-food, we estimate the number of coffee and food selling per year by using the simulation method. Star-up-cost: we calculated on the analysis capital part. There are the cost of construction, decoration, miscellaneous, unexpected cost and operation cost for first week Sale: basing our projected coffee and food sales, we generate a conservative estimated by calculating the total number of customers. Then basing on the price we got from survey we can calculate the sale for each year. Cost of Goods Sold: the cost of goods sold for coffee-food related products was determined by the retail profit analysis. We assume that cost of coffee is 40% of the selling price. The cost of lunch and breakfast per unit is 60% of selling price. Salaries expense: we intend to hire eighteen full-time employees and ten part-time employees include: manager, cashier, cook, waiters, waitress, security guards… The average wage per full-time employee is 1,400,000vnđ/month and part-time employee is 700,000vnđ/month. Other operating expense: including electricity bills, water bills, gas, phone, internet, unexpected cost… Income tax: is 10% total income from continuing operations before income tax. Financial Sheet Start-up Cost
1,900,000,000.00
Net sale
3,543,360,000.00
Cost of Good sold
1,624,320,000.00
Gross profit
1,919,040,000.00
Operating Expenses Salaries Rent Other operating expenses Income from continuing operations before income tax Income tax Net income
388,800,000.00 144,000,000.00
532,800,000.00 1,386,240,000.00 138,624,000.00 1,247,616,000.00
For Fashion Shop:
Page 10
After simulating 3 fashion shops, we estimate the number of clothes and trousers selling per year by using the simulation method. Star-up-cost: we calculated on the analysis capital part. There are the cost of construction, decoration, miscellaneous, unexpected cost and operation cost for first week Sale: basing our projected clothes and trousers sales, we generate a conservative estimated by calculating the total number of customers. Then basing on the price for each product that we got from survey, we can calculate the sale for each year. Cost of Goods Sold: the cost of goods sold for coffee-food related products was determined by the retail profit analysis. We assume that cost of clothes is 70% of the selling price. The cost of trousers is 65% of selling price. Salaries expense: we intend to hire ten full-time employees and seven part-time employees include: manager, cashier, sellers, security guards… The average wage per full-time employee is 1,600,000vnđ/month and part-time employee is 800,000vnđ/month. Other operating expense: including electricity bills, water bills, unexpected cost… Income tax: is 10% total income from continuing operations before income tax. Financial Sheet Start-up Cost
400,000,000.00
Sale
2,689,284,000.00
Cost of Goods sold
1,890,470,400.00
Gross profit
893,300,400.00
Operating Expenses Salaries
259,200,000.00
Rent
-
Other operating expenses
66,000,000.00
Income from continuing operations before income tax
325,200,000.00 568,100,400.00
Income tax
56,810,040.00
Net income
511,290,360.00
Paypack period Start-up Cost
400,000,000.00 /Year
Net income
511,290,360.00 /Year
Paypack period (Start-up Cost /Net income )
Payback period (months)
0.78 Year 9.39 Month
For lease 1
Coffee-Food 19
Fashion Shop 10
Page 11
5. Description of Risk criterion The third criterion used to evaluate 3 alternatives is risk. Like many other criteria, risk has
5.
a very big influence in a business’s success, including business risk and economical risk. Business risk is the internal risk which comes from the inside of a business. In running a 5. business like a cafeteria or a fashion shop, the most internal risk a business has to face is
5. Management. A good management can lever the success of a business. For instance, good attitude, good behavior of employees can satisfy customer or high quality of product can
5.
reach or exceed customer’s need. Therefore, a good management can help a business to improve its competitive advantages, and to increase its position in the market as well. In
5.
contrast, a weak management is a barrier to a business. It is the reason of financial loss, bad employee’s behavior, and low quality product. Hence, it negatively affects reputation and 5. prestige of company in resulting. A weak management profoundly harms a business’s
5. reduces its ability to compete with others. When operating, a business faces not strength; only internal risk but also the risk from the outside of the company, which is called as
5.
“economical risk”. A business cannot control this type of risk, but in order to survive and develop, it has to itself adapt to the change of economy. The most reason of economical
5.
risk is the inflation which directly affects on a business. For instance, when inflation occurs, 5. the price of every goods suddenly increases; customer tends to pay less to save their money. As a result, the demand for goods decreases. In this case, a business faces
5. problems such as the profit decreases while spending on employees’ wage, price of many material increases simultaneously. Hence, a business finds many difficulties in competing
5.
with others and developing. For those reasons, risk is one of the most important criteria need be carefully evaluated when making decision to select the highest priority project.
5.
D. APPLYING THE AHP 5. The AHP modeling process involves four steps, namely, structuring the decision problem, creating 5. pair wise comparison matrix, determining normalized weights and synthesize the priorities.
5. 6. Structuring the Data 5. Page 12
5.
System Selection Problem The survey was pre-tested with the IU’s teachers and students to ensure that all the criteria were well formulated and properly understood. These respondents all have experience in QA. We tried to ask both students and teachers who give us general points of view about this case. The respondents in the pre-test were interviewed to discuss the selection criteria in more detail and reformulate the AHP hierarchy. We always receive a objective opinion from them that make the result of survey fairly and more accuracy. We also constructed the sub-criteria of Risk to specify the risk criterion and to give weight of risk for each alternative in next steps.
7. Creating Pair-wise Comparison Matrix It is very hard to collect data from people who is lack of experience about Quantitative Analysis, because they cannot responds as well as our expectation. A questionnaire including all criteria and sub-criteria of the nine levels AHP hierarchy was designed to collect the pair-wise comparison matrices. The questionnaire was composed of two sections. The first section includes all criteria and sub-criteria in which we asked participants about pair-wise comparison and guide them to select carefully and most appropriate with their idea. The second section included these matrixes to rate all criteria for each alternatives. As the result, we have five matrices. The collected data were then analyzed and normalized. We construct an average criterion comparison as following: CAPITAL
PROFIT
RISK
CAPITAL
1
2.075
2.53
PROFIT
0.483
1
1.51
RISK
0.395
0.662
1
8. Determining Normalized Weights In this part, the pair-wise comparison matrices obtained from experts are combined by using the mean approach. The consistency ratio (CR) of each pair-wise comparison matrix is also shown. It can be found that the CR values are far less than 0.1, the value suggested by Saaty. This indicates that the experts’ opinions are consistent in measuring the pair-wise comparison judgments. Besides, the CR values between matrices filled out by the same experts are also less than 0.1. This implies that the data in each questionnaire are consistent. Firstly, we are going to check this result of the survey by calculating the consistency ration (CR):
Page 13
Normalize values: The number in the matrix is divided by their respective column totals as follow: CAPITAL 1.597 0.771 0.63
CAPITAL PROFIT RISK
PROFIT 1.667 0.803 0.531
RISK 1.505 0.898 0.595
Find the average of the various rows from the matrix as follows: AVERAGE 1.589 0.824 0.585
CAPITAL PROFIT RISK
We move to determine the vector consistency by multiplying the pair-wise matrix with average column: CAPITAL PROFIT
RISK
CAPITAL
1
2.075
2.53
PROFIT
0.483
1
1.51
0.824
RISK
0.395
0.662
1
0.585
X
1.589
The result: 4.778 2.474 1.761 We move to determine the consistency index (CI) 4.778/1.589 2.474/0.824 1.761/0.585
3.006 3.002 3.010
Page 14
The average value of consistency vector: =3.006
CI CR
n n 1
= (3.006-3)/(3-1)=0.003
CI = (0.003/0.58)=0.00517 RI
Since 0< CR < 0.1, we accept this result. Do similarly, we also calculate the CR of the table of sub-criteria of risk, we see that: ECONOMICAL 1 0.684
ECONOMICAL BUSINESS
BUSINESS 1.46 1
For two factors in this matrix are always right. After calculating the CR, we have priority table for each criteria: For three criteria: CAPITAL PROFIT RISK
CAPITAL 1 0.483 0.395
PROFIT 2.075 1 0.662
RISK 2.53 1.51 1
PRIORITY 0.526 0.281 0.193
For two risk criteria: ECONOMICAL BUSINESS
ECONOMICAL 1 0.684
BUSINESS 1.46 1
PRIORITY 0.594 0.406
In conclusion, we can do similarly for many times to find out the lowest consistency ratio for criteria. However in this case we have a careful survey and guideline that give us objective opinion about our criteria, that is why the consistency ratio is pretty low in acceptable interval that is smaller than 0.1. Finally we use this result to get a general and objective view about our case.
Page 15
9. Synthesize the Priorities Another important part is to give weight for each alternative and make decision. After calculating the normalized priority weights for each pair-wise comparison matrix of the AHP hierarchy, the next step is to synthesize the local priority weights of criteria and subcriteria for obtaining the set of global composite priorities. In this case, the scale for PROFIT, Capital scale, we take it by calculating the percentage of each criterion in total then inversing them, for risk scale, we take it by combination between risk priority above and CAPITAL, scale with CAPITAL relates to economic risk and PROFIT relates to business risk as we take the sum of product of CAPITAL and economic risk and product of PROFIT and business risk. Basing on the analysis of CAPIATAL and PROFIT, and risk description, risk survey and the dependence of risk from CAPITAL and PROFIT, we can give factor evaluation for each alternative as following: Factor FOR RENT CAFETERIA FASHION SHOP
CAPITAL 8.695 1.368 6.493
PROFIT 2.45 6.95 3.24
RISK 6.16 3.63 5.17
Then, we have result table: Factor FOR RENT CAFETERIA FASHION SHOP Priority
CAPITAL 8.695 1.368 6.493 0.526
PROFIT 2.45 6.95 3.24 0.281
RISK 6.16 3.63 5.17 0.193
Result 6.45 3.37 5.32
Look at the result table above, the final decision should be FOR RENT alternative.
E. CONCLUSIONS Nowadays, decision making becomes more and more complicated for businessman. Every decision makers have to deal with dramatically increasing alternatives, many conflicting goals due to aggressive fluctuation of global economy. Thus, most of decision is multiplecriteria decision. In this paper, we find out adequacy of AHP to support decision making. A framework of 3 criteria was used to evaluate AHP. 7
Page 16
Quantitative Analysis for Business
F. REFERENCES
Barry Render & Ralph M. Stair, Jr. & Michael E. Hanna. Quantitative Analysis for Management, 8E Textbook www.wikipedia.com http://www.bplans.com/Sample_Business_Plans
Page 17
Quantitative Analysis for Business
G. APPENDIX 10.
Simulation
Fashion Shop Clothes Demand Table Number of Demand
Prob.
Lower
Cum.
Demand
Total
5
0.17
0
0.17
16
80
6
0.2
0.17
0.37
25
150
9
0.3
0.37
0.67
29
261
4
0.13
0.67
0.8
35
140
3
0.1
0.8
0.9
48
144
2
0.07
0.9
0.97
54
108
1
0.03
0.97
1
80
80
30
1
Price (x1000VNĐ )
Average Price (x1000VNĐ )
963 Prob.
Demand
Sale (x1000VNĐ )
70-150
110
0.5
481.5
52965
150-250
200
0.36
346.68
69336
250-350
300
0.14
134.82
40446
963
162747
Total
Price per unit (x1000VNĐ) `
169
Trousers Demand Table Number of Demand
Prob.
Lower
Cum.
Demand
Total
7
0.23
0
0.23
7
49
8
0.27
0.23
0.5
9
72
6
0.2
0.5
0.7
11
66
3
0.1
0.7
0.8
15
45
3
0.1
0.8
0.9
18
54
2
0.07
0.9
0.97
20
40
0.97
1
22
1
0.03
30
1
Price (x1000VNĐ )
Average Price (x1000VNĐ )
22 348
Prob.
Demand
Sale (x1000VNĐ )
100-150
125
0.14
48.72
6090
150-200
175
0.57
198.36
34713
200-300
250
0.21
73.08
18270
300-400
350
0.07
24.36
8526
344.52
67599
Price per unit (x1000VNĐ) `
196
Page 18
Average price of Clothes
169000
Average price of Trousers
196000
Percent expense Clothes
0.7
Percent expense Trousers
0.65
Day
Ran. No1
Clothes
Ran. No2
Trousers
COGS
1
0.08
16.00
0.44
9
3,039,400.00
4,468,000.00
1,428,600.00
2
0.74
35.00
0.77
15
6,051,500.00
8,855,000.00
2,803,500.00
3
0.64
29.00
0.80
18
5,723,900.00
8,429,000.00
2,705,100.00
4
0.17
25.00
0.28
9
4,104,100.00
5,989,000.00
1,884,900.00
5
0.01
16.00
0.00
7
2,784,600.00
4,076,000.00
1,291,400.00
6
0.01
16.00
0.98
22
4,695,600.00
7,016,000.00
2,320,400.00
7
0.23
25.00
0.71
15
4,868,500.00
7,165,000.00
2,296,500.00
8
0.13
16.00
0.54
11
3,294,200.00
4,860,000.00
1,565,800.00
9
0.42
29.00
0.55
11
4,832,100.00
7,057,000.00
2,224,900.00
10
0.09
16.00
0.76
15
3,803,800.00
5,644,000.00
1,840,200.00
11
0.17
25.00
0.65
11
4,358,900.00
6,381,000.00
2,022,100.00
12
0.48
29.00
0.66
11
4,832,100.00
7,057,000.00
2,224,900.00
13
0.77
35.00
0.87
18
6,433,700.00
9,443,000.00
3,009,300.00
14
0.99
80.00
0.40
9
10,610,600.00
15,284,000.00
4,673,400.00
15
0.06
16.00
0.74
15
3,803,800.00
5,644,000.00
1,840,200.00
16
0.18
25.00
0.75
15
4,868,500.00
7,165,000.00
2,296,500.00
17
0.54
29.00
0.67
11
4,832,100.00
7,057,000.00
2,224,900.00
18
0.89
48.00
0.23
9
6,825,000.00
9,876,000.00
3,051,000.00
19
0.56
29.00
0.82
18
5,723,900.00
8,429,000.00
2,705,100.00
20
0.40
29.00
0.55
11
4,832,100.00
7,057,000.00
2,224,900.00
21
0.43
29.00
0.52
11
4,832,100.00
7,057,000.00
2,224,900.00
22
0.92
54.00
0.29
9
7,534,800.00
10,890,000.00
3,355,200.00
23
0.39
29.00
0.31
9
4,577,300.00
6,665,000.00
2,087,700.00
24
0.73
35.00
1.00
22
6,943,300.00
10,227,000.00
3,283,700.00
25
0.10
16.00
0.90
20
4,440,800.00
6,624,000.00
2,183,200.00
26
0.39
29.00
0.32
9
4,577,300.00
6,665,000.00
2,087,700.00
27
0.01
16.00
0.05
7
2,784,600.00
4,076,000.00
1,291,400.00
28
0.65
29.00
0.59
11
4,832,100.00
7,057,000.00
2,224,900.00
29
0.77
35.00
0.37
9
5,287,100.00
7,679,000.00
2,391,900.00
30
0.70
35.00
0.90
20
Total
Net sale
Gross profit
6,688,500.00
9,835,000.00
3,146,500.00
152,816,300.00
223,727,000.00
70,910,700.00
Page 19
Financial Sheet Start-up Cost
400,000,000.00
Sale
2,689,284,000.00
Cost of Goods sold
1,890,470,400.00
Gross profit
893,300,400.00
Operating Expenses Salaries
259,200,000.00
Rent
-
Other operating expenses
66,000,000.00
Income from continuing operations before income tax
325,200,000.00 568,100,400.00
Income tax Net income
56,810,040.00 511,290,360.00
Pay pack period Start-up Cost
400,000,000.00
Net income
511,290,360.00
Pay pack period (months)
9.39
Cafe-Food Restaurant Drink Demand Table Number of Times
Total
Prob.
Lower
Cum.
Demand
6
0.2
0
0.2
180
9
0.3
0.2
0.5
280
7
0.23
0.5
0.73
300
5
0.17
0.73
0.9
320
3
0.1
0.9
1
350
30
1
Lunch Food Demand Table Number of Times
Total
Prob.
Lower
Cum.
Demand
4
0.13
0
0.13
50
4
0.13
0.13
0.27
70
5
0.17
0.27
0.43
100
9
0.3
0.43
0.73
120
8
0.27
0.73
1
150
30
1
Page 20
Average price Drinks
24000.00
Foods
28000.00
Expenses percentage Drink
0.4
Food
0.6
Day
Ran. No1
Drink
Ran. No2
Food
COGS
Net sale
Gross profit
50
4,200,000.00
9,800,000.00
5,600,000.00
1
0.94
350
0.03
2
0.45
280
0.15
70
3,864,000.00
8,680,000.00
4,816,000.00
4,248,000.00
8,520,000.00
4,272,000.00
3
0.05
180
0.78
150
4
0.95
350
0.8
150
5,880,000.00
12,600,000.00
6,720,000.00
5
0.56
300
0.84
150
5,400,000.00
11,400,000.00
6,000,000.00
5,208,000.00
10,920,000.00
5,712,000.00
6
0.42
280
0.81
150
7
0.23
280
0.44
120
4,704,000.00
10,080,000.00
5,376,000.00
8
0.38
280
0.36
100
4,368,000.00
9,520,000.00
5,152,000.00
9
0.4
280
0.18
70
3,864,000.00
8,680,000.00
4,816,000.00
10
0.76
320
0.03
50
3,912,000.00
9,080,000.00
5,168,000.00
11
0.92
350
0.02
50
4,200,000.00
9,800,000.00
5,600,000.00
12
0.9
350
0.33
100
5,040,000.00
11,200,000.00
6,160,000.00
13
0.59
300
0.83
150
5,400,000.00
11,400,000.00
6,000,000.00
14
0.88
320
0.17
70
4,248,000.00
9,640,000.00
5,392,000.00
15
0.79
320
0.92
150
5,592,000.00
11,880,000.00
6,288,000.00
16
0.23
280
0.13
70
3,864,000.00
8,680,000.00
4,816,000.00
17
0.67
300
0.42
100
4,560,000.00
10,000,000.00
5,440,000.00
18
0.58
300
0.04
50
3,720,000.00
8,600,000.00
4,880,000.00
4,704,000.00
10,080,000.00
5,376,000.00
19
0.46
280
0.65
120
20
0.23
280
0.72
120
4,704,000.00
10,080,000.00
5,376,000.00
21
0.57
300
0.11
50
3,720,000.00
8,600,000.00
4,880,000.00
3,744,000.00
7,680,000.00
3,936,000.00
11,760,000.00
6,384,000.00
22
0.13
180
0.62
120
23
0.91
350
0.62
120
5,376,000.00
24
0.05
180
0.32
100
3,408,000.00
7,120,000.00
3,712,000.00
25
0.91
350
0.74
150
5,880,000.00
12,600,000.00
6,720,000.00
26
0.29
280
0.94
150
5,208,000.00
10,920,000.00
5,712,000.00
27
0.22
280
0.1
50
3,528,000.00
8,120,000.00
4,592,000.00
28
0.16
180
0.39
100
3,408,000.00
7,120,000.00
3,712,000.00
29
0.39
280
0.01
50
3,528,000.00
8,120,000.00
4,592,000.00
30
0.99
350
0.78
150
Total
5,880,000.00
12,600,000.00
6,720,000.00
135,360,000.00
295,280,000.00
159,920,000.00
Page 21
Financial Sheet Start-up Cost
1,900,000,000.00
Net sale
3,543,360,000.00
Cost of Good sold
1,624,320,000.00
Gross profit
1,919,040,000.00
Operating Expenses Salaries
388,800,000.00
Rent
-
Other operating expenses
144,000,000.00
Income from continuing operations before income tax Income tax
532,800,000.00 1,386,240,000.00 138,624,000.00
Net income
1,247,616,000.00
Paypack period Start-up Cost
1,900,000,000.00 /Year
Net income
1,247,616,000.00/ Year
Paypack period (Start-up Cost /Net income )
1.52 Year or 18.27 Month
Page 22
11.
Survey result
Direct Survey and Online Survey Frequency Table Xin hoi muc do mua sam cua anh/chi nhu the nao
Frequency Valid
Percent
Valid Percent
Cumulative Percent
Moi tuan 1 lan.
5
5.0
5.0
5.0
Moi thang 1 lan.
15
15.0
15.0
20.0
2-3 lan mot nam.
10
10.0
10.0
30.0
70
70.0
70.0
100.0
100
100.0
100.0
Thich thi mua (khong co ke hoach). Total
Moi lan mua sam anh chi thuong mua bao nhieu quan/ao
Frequency Valid
Percent
Valid Percent
Cumulative Percent
1-3 quan/ao.
85
85.0
85.0
85.0
3-5 quan/ao.
15
15.0
15.0
100.0
100
100.0
100.0
Total
Moi mot ao thuong tri gia bao nhieu
Frequency Valid
Percent
Valid Percent
Cumulative Percent
70.000-150.000
50
50.0
50.0
50.0
150.000-200.000
36
36.0
36.0
86.0
200.000-300.000
14
14.0
14.0
100.0
100
100.0
100.0
Total
Moi mot quan thuong tri gia bao nhieu
Frequency Valid
Percent
Valid Percent
Cumulative Percent
100.000 - 150.000
14
14.0
14.0
14.0
150.000 - 200.000
59
59.0
59.0
73.0
Page 23
200.000 - 300.000 Gia khac Total
20
20.0
20.0
93.0
7
7.0
7.0
100.0
100
100.0
100.0
Anh chi thuong thich su dung hang xuat xu tu dau
Frequency Valid
Percent
Valid Percent
Cumulative Percent
Viet Nam.
20
20.0
20.0
20.0
Trung Quoc/ Hong Kong
40
40.0
40.0
60.0
10
10.0
10.0
70.0
30
30.0
30.0
100.0
100
100.0
100.0
Hang hieu ( Louis Vuiton, Tommy, Gap, Lacoste…). Y kien khac Total
Truoc tinh trang lam phat hien nay, gia tieu dung leo thang thi nhu cau mua sam cua anh chi co giam bot hay khong
Frequency Valid
Percent
Valid Percent
Cumulative Percent
Khong anh huong
11
11.0
11.0
11.0
Rat it anh huong
42
42.0
42.0
53.0
Kha anh huong
32
32.0
32.0
85.0
Kha anh huong
15
15.0
15.0
100.0
100
100.0
100.0
Total
Ban thich quan cafe-food co kien truc nhu the nao?
Frequency Valid
Percent
Valid Percent
Cumulative Percent
Kien truc mo
64
64.0
64.0
64.0
Kien truc hien dai
36
36.0
36.0
100.0
100
100.0
100.0
Total
Anh/chi co thuong den quan cafe-food vao nhung luc nao
Frequency Valid
Moi ngay
10
Percent
Valid Percent 10.0
11.1
Cumulative Percent 11.1
Page 24
Missing
1 – 3 lan/tuan
30
30.0
33.3
44.4
3 - 5 lan/tuan
15
15.0
16.7
61.1
1 – 2 lan/thang
35
35.0
38.9
100.0
Total
90
90.0
100.0
System
10
10.0
100
100.0
Total
Muc dich anh/chi di den quan cafe-food de
Frequency
Percent
Valid Percent
Valid
1
85
85.0
Missing
System
15
15.0
100
100.0
Total
Cumulative Percent
100.0
100.0
Anh/chi co thuong den quan cafe-food vao nhung luc nao
Frequency
Percent
Valid Percent
Valid
1
20
20.0
Missing
System
80
80.0
100
100.0
Total
Cumulative Percent
100.0
100.0
Muc dich anh/chi di den quan cafe-food de
Frequency
Percent
Valid Percent
Valid
1
20
20.0
Missing
System
80
80.0
100
100.0
Total
Cumulative Percent
100.0
100.0
Chi phi cho moi hoa don cua anh/chi thuong la bao nhieu tren 1 nguoi cho thuc uong
Frequency Valid
Percent
Valid Percent
Cumulative Percent
< 20.000
18
18.0
18.0
18.0
30.000 - 35.000
19
19.0
19.0
37.0
1
1.0
1.0
38.0
62
62.0
62.0
100.0
100
100.0
100.0
> 50.000 20.000 - 25.000 Total
Page 25
Neu quan cafe-food gan cong ty anh/chi co phuc vu them thuc an sang va com trua van phong, anh/chi co san sang su dung dich vu do khong
Frequency Valid
Percent
Valid Percent
Cumulative Percent
Dong y
86
86.0
86.0
86.0
Khong dong y
14
14.0
14.0
100.0
100
100.0
100.0
Total
Theo anh/chi gia cho thuc an sang bao nhieu la hop ly
Frequency Valid
Percent
Valid Percent
Cumulative Percent
10.000 - 15.000
36
36.0
36.0
36.0
15.000 - 20.000
63
63.0
63.0
99.0
20.000 - 25.000
1
1.0
1.0
100.0
100
100.0
100.0
Total
Theo anh/chi gia cho mot suat com trua van phong la hop ly
Frequency Valid
Percent
Valid Percent
Cumulative Percent
15.000 - 20.000
30
30.0
30.0
30.0
20.000 - 25.000
64
64.0
64.0
94.0
25.000 - 30.000
6
6.0
6.0
100.0
100
100.0
100.0
Total
Truoc tinh trang lam phat hien nay, gia tieu dung leo thang thi nhu cau mua sam cua anh chi co giam bot hay khong
Frequency Valid
Percent
Valid Percent
Cumulative Percent
Khong anh huong
12
12.0
12.0
12.0
Rat it anh huong
20
20.0
20.0
32.0
Kha anh huong
63
63.0
63.0
95.0
Rat anh huong
5
5.0
5.0
100.0
100
100.0
100.0
Total
Page 26
Page 27
Related Documents
Qa For Business - Cafe
November 2019 19
Qa For Business - Phuc - Oversea
November 2019 8
Qa
November 2019 66
Qa
November 2019 54
Qa
December 2019 54
Qa
June 2020 27More Documents from ""
Sprabf2.pdf
April 2020 22
Statistics For Business 3
November 2019 22
Recruiting Toolkit
June 2020 29
Introduction To Sife Vietnam_2009
June 2020 8
2009 Sife Vietnam_poster
June 2020 10