代写 Marketing Research and Its Business Application

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FINAL EXAM

(Version A)

Marketing Research and Its Business Application

The University of Hong Kong – Fudan University

MBA (International) Program

(9:00 a.m. ~ 4:30 p.m., February 8, 2015)

Course Instructor: Deqiang ZOU

You are required to submit your answer to the email box of the TA, Miss Nora CHEN (NOT

the public email account for this course), by 4:30 pm, February 8 (Sunday), 2015.

Email: 13210690024@fudan.edu.cn AND coopetition@outlook.com

For successful submission, the student will receive an auto-‐reply as confirmation.

Submission beyond the deadline will be degraded.

Read through the “academic honesty” principles emphasized in the course syllabus (p. 7-‐8)

before your start to work on the exam. Keep these principles seriously in your mind.

For questions relying on analyses with SPSS, do not just copy SPSS outputs as your answer

without any interpretations. In a large sense, your clear-‐cut interpretations of the results count

more.

Before submitting your answers, compress all documents into a “.rar” or “.zip” file, named

in this pattern: “First Name_Last Name (Capital Letters)_Student ID Number.rar”. For example,

“Xiao_ZHANG_2013968794.rar” is the one that Mr. Xiao ZHANG (张潇) would submit. Make sure

all the files that you submit are highly readable and neatly organized into properly named and

structured folders before the compressed document is attached to your email.

For technique issues or possible ambiguity in understanding the questions in the exam, you

may contact Miss Nora CHEN or me directly via email.

After the final exam, you must return the exam paper to Nora before leaving the classroom.

Be professional and good luck!

〓〓 Task 1: (15 points)

Consumers increasingly search for their peers’ reviews for products or services before

making their own purchase decisions. For example, looking up dianping.com has already been

youngsters’ habits for dining out in big cities. People trust their peers better than information in

commercial sources. Therefore, Internet word-‐of-‐mouth (WOM) or online buzz can be critically

valuable to marketers.

Some marketing professors are trying to link the online buzz of movies sequentially released

in US cities to the box office records. With delicate and sophisticated empirical modeling, they

manage to verify the impact of (a) both online buzz volume and (b) valence (positive or negative)

on the sales performance of movies. In this case, it is advisable for marketers to think about the

dollar value of each buzz. After all, online WOM can be a valid means for new customer

acquisition.

In mainland China, nearly 13 million posts were shared in online forums of cars every month

in 2011. Some marketing experts in the industry begin to make some efforts in investigating the

relationships between online buzz and sales in the auto market. Two marketing research

companies “R” and “C” 1 gathered 133,071,049 consumer comments from 2500+ Auto related

web-‐sites and online forums in 2009. For this study, company “C” tracked the Internet WOM

volume and sentiment (i.e., valence, positive vs. negative) of the 42 leading auto brands and over

500+ models in 2009. And, source of 2009 passenger car sales is quoted from “China Association

of Automobile Manufacturers”.

As displayed in Figure 1, for each car model, the share of buzz appears to be positively

correlated to the share of sales. More specifically, a medium correlation (R 2 = 0.4829) was found

between total buzz and car sales for 2009. The sales impact of Internet WOM is more

pronounced for foreign car brands (or joint venture brands) (R 2 = 0.5961) and cars priced over

RMB 200,000 (R 2 = 0.9135).

The two marketing research companies claim another interesting finding which is the

co-‐variation between positive and negative Internet WOM volume (Figure 2).

Furthermore, the relationship between negative buzz volume (Y) and positive buzz volume

(X) is quite strong (Figure 3), which is demonstrated by a linear regression function: Y= -‐11.85 +

0.3323X, with a high coefficient of determination (R 2 = 0.8883). Company “R” and “C” believe it

implies those who are active online generate both positive and negative Internet WOM.

1 For confidential concerns, the names of the two companies are disguised here.

Figure 1: Scatter diagram of “Share of Buzz” vs. “Share of Sales”

Figure 2: Monthly Buzz Volume of Cars in 2009 (Unit: thousand)

Figure 3: Regress Negative Buzz Volume on Positive Buzz Volume (Unit: thousand)

Given all these findings, the company “R” and “C” build up confidence in claiming the power

of Internet WOM, i.e., its impact on sales in dollar terms. They believe some car brands benefited

more from online buzz and buzz marketing than others, in the sense that online buzz related to

these brands contributes higher profit margin. They therefore make a step forward to develop a

novel marketing metric “Internet WOM ROI (Return on Investment)” for some car brands (Table

1). Ranked among the top five by “Revenue per Buzz” (which equals to “Estimated Revenue/

Total Buzz Volume by Post”) were many mid to high price models including Audi A6, VW Passat,

Teana, Honda CR-‐V, and Toyota Camry. These brands outperform their peers with regard to

Internet WOM ROI (Table 1). This newly developed metric aims to connect user generated

contents (UGC) to corporate financial performance.

Questions for you to address

(1.1) How would you evaluate the performance of the metric “Internet WOM ROI” (i.e., revenue

per buzz) newly developed by company “R” and “C”? Given their research methodology, what is

the value of this metric to marketers? (7 points)

(1.2) If you were a marketer in the auto industry, would you believe in the conclusions drawn by

the company “R” and “C”? Why or why not on basis of your analysis of the research design

implemented? (8 points)

Table 1: Unit Dollar Value of Online Buzz for Cars

代写 Marketing Research and Its Business Application

〓〓 Task 2: (15 points)

As the cost of goods increase, manufacturers routinely pass these extra costs on to

consumers through higher prices. A less obvious strategy is to maintain the price, but to reduce

the size of the product. In the latter case, firms have chosen to maintain the sticker price of a

product, but have reduced the quantity contained in that product. Thus, a tin of coffee stays

$2.99, but shrinks from 14.5 ounces to 13 ounces, for an effective price increase of over 10

percent.

Which option is more likely to turn off your customers? Although a simple economic model

of rationality predicts that consumers should be sensitive both to an increase in a product’s price

and a corresponding decrease in a product’s quantity, there are reasons to suspect they are not.

We need to empirically test if consumers are more sensitive to changes in price than to changes

in quantity, or the reverse is true.

Is the firm better off (1) increasing the sticker price of its products or (2) maintaining the

price, but reducing the content contained in its offerings? The answer is not immediately clear.

Your task is to investigate the relative magnitude of consumers’ sensitivity to changes in price

versus quantity by designing an online experiment with Qualtrics.

The scenario that you’ll present to the subjects in the experiment is price increase for a

cereal brand, i.e., Quaker. At present, the sticker price for this product is RMB 20.00 per 1kg in

the standard package 2 . Due to price increase of wheat, the cereal manufacturer has to increase

the unit price of the cereal increases by 25%. This price change is manipulated in a “2

(adjustment frame: price vs. quantity) x 2 (scale: absolute vs. percentage)” between-‐subjects

design.

The latest price is RMB 25.00/kg which can be presented either in a price adjustment frame

(e.g., RMB 25.00 vs. RMB 20.00 per 1kg) or in a quantity adjustment frame (e.g., RMB 20.00 per

1kg vs. 800g). The change in price or quantity can be communicated in either absolute terms

(e.g., the price increases from RMB 20.00 to RMB 25.00, or the package size shrinks from 1kg to

800g) or percentage terms (e.g., the price increases by 25% from RMB 20.00, or the package size

shrinks by 20% from 1kg). Each subject is expected to be randomly assigned to one of these four

conditions (Table 2).

The measurement of dependent variables is the same across the four conditions: (1) the

perceived magnitude of the price change, i.e., does the subject perceive this increase in net price

as big or small; (2) perceived value or performance/price ratio, i.e., does the subject think it is

good value for money to buy the cereal after the price adjustment or not; (3) price fairness

2 http://d1.yihaodianimg.com/t1/2011/09/20/2680647_600x600.jpg

perception, i.e., given the price increase of wheat, does the subject think the price increase of

the cereal is fair to them or not; and (4) purchase likelihood, i.e., how likely is the subject to buy

the cereal at this new price.

Table 2: The Four Between-‐subjects Treatments in the Experiment

Treatment Sticker Price Quantity

1 Increase by RMB 5.00 1 kg

2 Increase by 25% 1 kg

3 RMB 20.00 Shrink by 200g

4 RMB 20.00 Shrink by 20%

Your design must fulfill all the requirements abovementioned. Moreover, make sure the

experiment you design is useable for you as the researcher and friendly to the participants. Last

but not least, ensure you know how to handle the data later collected with the experiment. You

may use the “test survey” function embedded in the “Advanced Options” button, download the

data simulated by Qualtrics and check if the experiment works exactly as you anticipate.

Tasks for you to complete

(2.1) You should name the experiment you design as:

“First Name”_“Last Name (Capital Letters)”_“Student ID Number”_Experiment

For example, the experiment designed by Mr. Xiao ZHANG (张潇) should be named as

follows:

Xiao_ZHANG_2013968794_Experiment

To submit this experiment, click the “My Surveys” button on the top of the web-‐page. Find

the questionnaire you want to submit and click the “Collaborate” button on the right. In the

pop-‐up window, type in the email of Miss Nora CHEN, 09300690039@fudan.edu.cn, then click

“Add”. Tick the “Edit” and “Copy” options, then click “Save”. (12 points)

(2.2) To test if the data collected in the experiment is consistent with our predictions, what type

of statistical analysis would you suggest to conduct? How? (3 points)

〓〓 Task 3: (20 points)

Before handling SPSS analyses in this task, get familiar with the dataset you’ll work with.

1. Data Description

The data supporting this task are stored in “HATCO.sav”, a SPSS data file. The data were

obtained from the HAT Company (HATCO), a large industrial supplier. This dataset contains 100

observations on 14 separate variables. It is an example of a segmentation study for a

business-‐to-‐business situation, specifically a survey of existing customers of HATCO.

Three types of information were collected. The first type is the perception of HATCO on

seven attributes identified in past studies as the most influential in the choice of suppliers. The

respondents, purchasing managers of firms buying from HATCO, rated HATCO on each attribute.

The second type of information relates to actual purchase outcomes, either the evaluations of

each respondent’s satisfaction with HATCO or the percentage of that respondent’s purchase

from HATCO. The third type of information contains general characteristics of the purchasing

companies (e.g., firm size, industry type). A brief description of the dataset variables is provided

in Table 3. A definition of each variable and an explanation of its coding is given in the following

sections.

Table 3 Description of Database Variables

Variable Description Variable Type

Perceptions of HATCO

X 1 Delivery speed Metric

X 2 Price level Metric

X 3 Price flexibility Metric

X 4 Manufacturer’s image Metric

X 5 Overall service Metric

X 6 Salesforce image Metric

X 7 Product quality Metric

Purchase Outcomes

X 9 Usage level Metric

X 10 Satisfaction level Metric

Purchaser Characteristics

X 8 Size of the firm Nonmetric

X 11 Specification buying Nonmetric

X 12 Structure of procurement Nonmetric

X 13 Type of industry Nonmetric

X 14 Type of buying situation Nonmetric

1.1 Perceptions of HATCO

Each of the variables was measured on a graphic rating scale, where a 10-‐centimeter line

was drawn between the endpoints, labeled “Poor” and “Excellent.”

Respondents indicated their perceptions by making a mark anywhere on the line. The mark

was then measured and the distance from 0 (in centimeters) was recorded. The result was a

scale ranging from 0 to 10, rounded to a single decimal place. The seven HATCO attributes rated

by each respondent are as follows:

X 1 Delivery speed— amount of time it takes to deliver the product once an order has

been confirmed

X 2 Price level— perceived level of price charged by product suppliers

X 3 Price flexibility— perceived willingness of HATCO representatives to negotiate price

on all types of purchases

X 4 Manufacturer’s image— overall image of the manufacturer or supplier

X 5 Overall service— overall level of service necessary for maintaining a satisfactory

relationship between supplier and purchaser

X 6 Salesforce image— overall image of the manufacturer’s salesforce

X 7 Product quality— perceived level of quality of a particular product (e.g., performance

yield)

1.2 Purchase Outcomes

Two specific measures were obtained that reflected the outcomes of the respondent’s

purchase relationships with HATCO. These measures include:

X 9 Usage level— how much of the firm’s total product is purchased from HATCO,

measured on a 100-‐point percentage scale, ranging from 0 to 100 percent

X 10 Satisfaction level— how satisfied the purchaser is with past purchases from HATCO,

measured on the same graphic rating scale as perceptions X 1 to X 7

1.3 Purchaser Characteristics

The five characteristics of the responding firms used in the study, some metric and some

nonmetric, are as follows:

X 8 Size of firm— size of the firm relative to others in this market. This variable has two

categories: 1= large, 0= small

Poor Excellent

X 11 Specification buying— extent to which a particular purchaser evaluates each

purchase separately (total value analysis) versus the use of specification buying,

which details precisely the product characteristics desired. This variable has two

categories: 1= employs total value analysis approach, evaluating each purchase

separately; 0= use of specification buying

X 12 Structure of procurement— method of procuring or purchasing products within a

particular company. This variable has two categories: 1= centralized procurement,

0= decentralized procurement

X 13 Type of industry— industry classification in which a product purchaser belongs.

This variable has two categories: 1= industry A, 0= other industries

X 14 Type of buying situation— type of situation facing the purchaser. This variable has

three categories: 1= new task, 2= modified rebuy, 3= straight rebuy

2. Questions for you to address

(3.1) Do the respondents evaluate “Manufacturer’s image” (X 4 ) higher than they do on

“Salesforce image” (X 6 )? (3 points)

(3.2) Do the evaluations on “Overall service” (X 5 ) differ depending on “Size of the firm” (X 8 )?

(3 points)

(3.3) In this survey, is the “Structure of procurement” (X 12 ) related to “Type of buying

situation” (X 14 )? (3 points)

(3.4) Do the three groups defined by “Type of buying situation” (X 14 ) differ in their “Usage

level” (X 9 )? (3 points)

(3.5) Can “Usage level” (X 9 ) and “Satisfaction level” (X 10 ) be explained by evaluations on the

seven attributes (X 1 ~ X 7 ) of HATCO respectively when these ratings are considered

simultaneously? Interpret the results of your analyses. Is multicollinearity a serious problem in

the two multiple linear regression analyses? (8 points)

〓〓 Task 4: (25 points)

Every marketer knows the saying, “perception is reality.” It applies to not only product

perception but also price perception. For example, in sales promotion campaigns of daily

groceries, we hope consumers to perceive the price lower under some conditions even though

the objective prices are held constant. To fulfil this purpose, one viable strategy is to alter the

way in which price information is presented to consumers.

Concerning a sales promotion of 25% price discount for buying two units, we may present it

to consumers either as (a) “25% off for two 3 ”, or (b) “Buy one get one (BOGO) 50% off 4 ”. We are

not sure under which condition consumers may perceive the deal more attractive.

While buying two units of a product in such sales promotion, we may decide on the

monetary expense in one of the two following formats. (i) We may estimate the price for the first

unit, the second unit, respectively. Then, we add them up. This is known as a piecemeal pattern.

(ii) Alternatively, we may estimate the total expense of the two units as a sum directly. This is

known as a holistic pattern.

We are thus interested in the two research questions (RQ) followed:

RQ1: Price communicated in which sales promotion presentation format, i.e., (a) “25% off

for two” or (b) “BOGO 50% off”, is perceived by consumers as lower?

RQ2: Does your conclusion made for RQ1 vary across the (i) piecemeal pattern, and (ii)

holistic pattern? Or, is the conclusion consistent across the two patterns?

I designed an online experiment with Qualtrics to investigate these two research questions.

Students in class 2013GA/GB have participated in it to earn partial course credits. In the

experiment, Nestle instant coffee is used as the stimulus. A 2 (Promotion: (a) “25% off for two”

vs. (b) “BOGO 50% off”) × 2 (Format: (i) piecemeal vs. (ii) holistic) between-‐subjects design has

been applied. Subjects are randomly assigned to one of the four experimental conditions. You

may refer to the four screenshots corresponding to these four conditions in the folder “Task 4”.

Data collected in this experiment (N= 193) are stored in “Data_Instant_Coffee.sav”. The key

variables of interest 5 are as follows:

Promotion: Presentation of the sales promotion. This variable has two categories: 0= (a)

“25% off for two”, 1= (b) “Buy one get one (BOGO) 50% off”.

Format: Format used by the subject to report the total expense. This variable has two

3 买两件，打七五折

4 第二件半价

5 Variable “V1” denotes the ID of each participant.

categories: 0= (i) piecemeal, 1= (ii) holistic

Price_Estimate: Estimate of the total monetary expense (RMB) on buying two boxes of

coffee. In “piecemeal” cases, it is the sum of the two equal numbers typed in by the subject.

In the “holistic” cases, it is exactly the number submitted by the subject.

The question for you to address

(4.1) Use appropriate statistical analyses to address RQ1 and RQ2. Interpret your findings. (6

points)

After completing an online survey, participants were inquired how they feel with receiving

the Economist magazine as a reward. Their feelings are measured in two aspects:

(1) Worthiness. Given the reward and her time and effort devoted to the survey, does the

participant think that it is worthwhile for her to work on this survey? The answer is largely

related to the judgment of value where value can be defined as a ratio, i.e., “Value=

Benefit/Cost”. Therefore, there are three broad ways for us to measure the worthiness of doing

something. (i) Overall rating. Concerning the tradeoff between the cost and benefit, people think

it is a good deal or not. (ii) Benefit rating given the cost involved. In other words, if the

denominator (i.e., cost) in the formula of value has been fixed, how much benefit (i.e.,

numerator) has been perceived? (iii) Cost rating given the benefit received. In other words, if the

numerator (i.e., benefit) in the formula of value has been fixed, how much cost (i.e.,

denominator) incurred has been perceived?

(2) Satisfaction. How satisfied the participants are with receiving the reward for working on

the survey?

Before reporting their worthiness perception and satisfaction, participants were randomly

assigned to one of the following two treatments in a between-‐subjects design.

(1) One issue treatment

This research is part of the course. However, assume it was carried out by a

profit-‐making company. The company is considering offering ONE of the two latest issues

of Economist magazine as reward to the participants.

The listed price of Economist magazine is about US $3.00/ issue.

(2) Two issues treatment

This research is part of the course. However, assume it was carried out by a

profit-‐making company. The company is considering offering TWO issues of the latest

Economist magazine as reward to the participants.

The listed price of Economist magazine is about US $3.00/ issue.

The data collected in this experiment (N= 409) are store in “Data_Magazine.sav”. The key

variables of interest 6 are as follows:

Issues: A participant may receive either one or two issues of the Economist magazine as

the reward. This variable records the experimental treatment assigned to each participant. It

has two categories: 0= one issue, 1= two issues.

Good_Deal_Overall_Rating: It is a 7-‐point Likert scale corresponding to the “(i) Overall

rating” measurement of worthiness. The measurement item used in the questionnaire is

“After trading off the reward and what you spent for this research, do you agree that it is a

good deal to participate in this research?”

Benefit_given_cost: It is a 7-‐point Likert scale corresponding to the “(ii) Benefit rating

given the cost involved” measurement of worthiness. The measurement item used is “Given

the time and effort you spent for this online research, do you agree that such reward is

adequate?”

Cost_given_benefit: It is a 7-‐point Likert scale corresponding to the “(iii) Cost rating

given the benefit received” measurement of worthiness. The measurement item used is

“Given the value of this reward, do you agree that the time and effort you spent for this

online research is worthwhile?”

Satisfaction: It is a 7-‐point scale. The measurement item used in the questionnaire is “If

you would receive the Economist magazine 7 as the reward for taking this research, how

satisfied would you be?”

Questions for you to address

(4.2) Among the three measurements of worthiness, “(i) Overall rating” has usually been

regarded as the golden standard. If so, which of the other two measurements (i.e., “(ii) Benefit

rating given the cost involved” and “(iii) Cost rating given the benefit received”) makes a better

proxy for this golden standard? (4 points)

(4.3) We believe that, if someone perceives more value from receiving a reward, she is more

likely to be satisfied with that reward. Then, which measurement of worthiness (i.e., value

perception) can better predict satisfaction, “(ii) Benefit rating given the cost involved” or “(iii)

Cost rating given the benefit received”? (4 points)

6 Variable “V1” denotes the ID of each participant.

7 Either one issue or two issues

(4.4) The experimenter would like to know if the respondents are more satisfied when they

are rewarded with two rather than one issue of Economist magazine. The experimenter also

guesses male and female respondents may react differently to the reward. Please simultaneously

analyze the main effects of both factors (1) one vs. two issues, and (2) gender (male vs. female),

and their interaction effect on participants’ satisfaction with the reward. Interpret the results. (4

points)

Students in class 2013GA/GB had been asked to take an online survey on how people buy

tablet computers. Besides the conjoint task, each respondent indicated their relative loyalty

toward five tablet computer brands (e.g., Apple iPad, Samsung Galaxy Tab, Lenovo IdeaPad, Asus

EeePad, and Motorola Xoom) in five similarly framed questions. In each question, respondents

were required to speculate what another consumer would do, who’d like to buy “Brand A” but

found that it happened to be out of stock. Given this situation, would this consumer choose to

wait for “Brand A” or switch to some other brands, e.g., “Brand B”, instead?

For example, when “Brand A” is Apple iPad and the other four brands are “Brand B”, this

single answer, multiple choice item is presented to the respondents as follows.

If a consumer plans to buy an Apple iPad, but finds that it is out of stock at the moment.

According to your judgment, in this situation, which tablet computer brand she or he is most

likely to choose?

(1) Wait until Apple iPad is available again

(2) Switch to Samsung Galaxy Tab

(3) Switch to Lenovo IdeaPad

(4) Switch to Asus EeePad

(5) Switch to Motorola Xoom

If a respondent chooses (1), we know that she is loyal to “Apple iPad” because she switches

from “Apple iPad” to “Apple iPad”. However, if she chooses (2), we know that she is not very

loyal to “Apple iPad” because she switches from “Apple iPad” to “Samsung Galaxy Tab”, a

different brand. In other words, we can conclude that “Apple iPad” is competing against

“Samsung Galaxy Tab”, at least for this consumer.

The data (N= 201) are stored in “Data_Switching.sav”, and the two variables 8 related to the

question for you to answer are,

Switch_From: The brand favored by the consumer but not available. This categorical

variable includes five values corresponding to the five brands. It denotes the “Brand A” from

8 In addition, variable “V1” denotes the ID of each participant.

which the consumer would switch the brand choice.

Switch_To: The brand that the consumer would switch to when the favored brand is out

of stock. It denotes the “Brand B” chosen by the consumer. This categorical variable is coded

in the same way as the variable “Switch_From”.

The Question for you to address

(4.5) The responses made in these five questions can reveal the substitutability between these

five brands in the customers’ perspective. Therefore, you can investigate the strength of loyalty

for each brand and the competitive relations between these brands, e.g., the asymmetry in

consumers’ definition of competing brands. Interpret the results and summarize the marketing

management implications. (7 points)

〓〓 Task 5: (25 points)

Totally 210 students of the course MRBA took a full-‐profile rating based conjoint

experiment conducted on Qualtrics platform. Each rated their purchase likelihood for 25 product

profiles of tablet computers. Therefore, 5250 (= 210×25) observations were recorded for these

ratings.

Data Description

In the conjoint experiment, instruction to the respondents follows:

You are invited to make 25 evaluations consecutively. In each evaluation, a tablet

computer is displayed. You are required to type in a whole number ranging from 0 to 100 to

show how likely you would like to buy this tablet computer. Use a scale from 0 to 100, where

0= "not at all likely" and 100 represents "definitely would purchase."

Make sure you make full use of the range of this 0~100 scale, neither focusing on a

narrow segment (e.g., 40~60) nor concentrating solely on the extreme end points (e.g., 0~10

and 90~100).

Concerning the configuration of these tablet computers, you may read through the

following aspects.

[1] Brand: There are totally five brands, namely, Apple iPad, Samsung Galaxy Note,

Lenovo IdeaPad, Asus EeePad, and Motorola Xoom.

[2] Screen Size: The three available screen sizes (the length of the screen diagonal in

inches) are as follows, 5 inches, 7 inches, and 9.7 inches.

[3] Wireless Connectivity: There are three options for wireless connections, namely,

“Wifi”, “Wifi + 3G”, or “Wifi + 4G”.

[4] Storage Capacity: In other words, the memory size. There are five alternatives as

follows, 8G, 16G, 32G, 64G, and 120G.

[5] Free Warranty: Duration of free warranty varies across three levels, i.e., none, 1year,

and 2 years.

[6] Price: The tablet computers are priced at four levels, RMB1000, RMB2000,

RMB3000, and RMB4000.

Take all these six attributes of a tablet computer into consideration before you make the

ratings. Try to be consistent through the ratings.

By combining these attributes with orthogonal design, 25 product profiles are generated.

Check for these product profiles at “Data_Conjoint_Rating_Tablet_Computer.sav”, where the

variable “Profile” denotes the ID of each tablet computer. The specific configuration of each

profile can be figured out by referring to variables “Brand”, “Screen”, “Wireless”, “Storage”,

“Warranty”, and “Price”. In the conjoint task (e.g., the one in Figure 4), these 25 profiles were

presented to each participant 9 in a randomized order. Their ratings were stored in the variable

“Rating”, which records participants’ reply to this question “How likely are you to purchase this

tablet computer? (Use a scale from 0 to 100, where 0 = ‘not at all likely’ and 100 means

‘definitely would buy’).”

Figure 4: Rating task for one product profile in the conjoint experiment

Questions for you to address

(5.1) Given the attributes and attribute levels, demonstrate the 25 profiles used for the

conjoint task based on orthogonal design. Named the SPSS data file containing the configurations

of these products as “Orthogonal_First Name_Last Name (Capital Letters)_Student ID

Number.sav”. For example, “Orthogonal_Xiao_ZHANG_2013968794.sav” is the one that Mr. Xiao

ZHANG (张潇) would submit. (5 points)

Note: Before generating the dataset for the

orthogonal design, tick the checkbox “Reset

random number seed to” and type in the last five

digits of your “Student ID No.”. For instance, Mr.

Xiao ZHANG (张潇) should input “68794” here.

(5.2) Report the part-‐worth for each attribute

levels and the relative importance of each attribute.

Interpret your findings. (5 points)

(5.3) With regard to part-‐worth and relative importance, what is the difference between

female and male participants? What are the marketing implications of your findings? (5 points)

(5.4) Assume there are three tablet computers available in the market (refer to the table

9 Variable “V1” denotes the ID of each respondent.

below). For those who participated in this conjoint task, which product is most favored, which

one is least preferred? (5 points)

Product

Brand

Name

Screen Size

(inches)

Wireless

Connectivity

Storage

Capacity

Free

Warranty

Price

(RMB)

A Apple 9.7 Wifi 16G None 4000

B Asus 7 Wifi+4G 120G 2 years 2000

C Lenovo 9.7 Wifi+3G 64G 1 year 1000

(5.5) After reviewing numerous tablet computers, a consumer sampled in this study is most

interested in “Product I” (refer to the table below). However, this consumer suggests that she

would like to make some modifications on “Product I”, so that “Product II” would better satisfy

her expectation toward an ideal tablet computer. For this customized product, what price would

you propose to her? Make sure this price is low enough to evoke her interest, and high enough

to exploit her consumer surplus. (5 points)

Product

Brand

Name

Screen Size

(inches)

Wireless

Connectivity

Storage

Capacity

Free

Warranty

Price

(RMB)

I Apple 9.7 Wifi+4G 16G 2 years 3000

II Apple 7 Wifi 64G None ?

Note: Submit the Excel spreadsheet supporting your calculation made for question

(5.2)~(5.5). You may name each worksheet according to each question. The spreadsheet should

be named as “Conjoint_First Name_Last Name (Capital Letters)_Student ID Number.xlsx” 10 . For

example, “Conjoint_Xiao_ZHANG_2013968794.xlsx” is the one that Mr. Xiao ZHANG (张潇)

would submit.

10 Earlier version “.xls” Excel spreadsheets are also acceptable.
代写 Marketing Research and Its Business Application