SMU Marketing Research Ch-9

7/28/2019 SMU Marketing Research Ch-9

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UNIT 9 DATA PROCESSING AND PRELIMINARY DATA

ANALYSIS

Structure

9.1 Introduction

Objectives

9.2 Survey field work and Data collection

9.3 Nature and scope of data preparation

9.4 Editing

9.5 Coding

9.6 Data entry

9.7 Data cleaning

9.8 Preliminary data analysis

9.9 Assessing for normality and outliers

9.10 Summary

9.11 Glossary

9.12 Terminal Questions

9.13 Answers

9.14 Case Study

9.1 INTRODUCTION

In the earlier unit you must have learnt about the concept of Hypothesis, itsprocess, Test of Significance of a Mean-large Sample, Test of Significance

of Difference between Two Standard Deviations (Large Sample), and Testof Significance of Difference between Two Means (Large Sample). Furtheryou have studied about the Test of Significance of a Sample, Proportion, _Test of Significance of Difference between Two Sample Proportions,Student's T Distribution, Kruskal-Wallis Test. In the end you have learntKolmogorov-Simrnov Test. In this unit you will study about the dataprocessing and preliminary data analysis process.

Sikkim Manipal University Page No. 1

Marketing Management Unit 1


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After collecting the data for the questionnaire, data preparation and analysisis done. Data preparation process has the direct impact upon the quality ofthe researcher analysis. This unit discusses the data collection processwhich initiates with checking the complete questionnaire thoroughly. Thendata editing and coding terms are used. Data editing means to scrutinize thedata among irrelevant and relevant data. Data coding is the process ofgiving numberings and symbol to the edited data. After that data cleaning isused in which different statistical software are used. A preliminary dataanalysis is done after doing the cleaning of the data.

In this unit you will focus on the fieldwork and the process of data collection.When the data is collected you will be able to learn about the concept of

editing and coding. Further you will be aware about how to use differentstatistical software in the data preparation process. After data coding andediting next step is data cleaning. Then before doing the final analysis of thedata, a proper check on the data is to be done. Further you will know aboutthe preliminary data analysis like normality and outlier check.

Objectives

After studying this unit, you should be able to:

describe the nature and scope of data preparation

learn the data editing, coding and cleaning step

know about the preliminary data analysis

ass the normality and outliers concept

CASELET

Nielsens Internet Survey: Does it Carry Any Weight?The Nielsen Media Research Company, a longtime player in

television-related marketing research has come under fire from the

various TV networks for its surveying techniques. Additionally, in

another potentially large, new revenue business, Internet surveying,

Nielsen is encountering serious questions concerning the validity of

its survey results. Due to the tremendous impact of electronic




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commerce on the business world, advertisers need to know howmany people are doing business on the Internet in order to decide if

it would be lucrative to place their ads online.

Nielsen performed a survey for Commerce Net, a group of

companies that includes Sun Microsystems and American Express,

to help determine the number of total users on the Internet.

Nielsens research stated that 37 million people over the age of 16

have access to the Internet and 24 million have used the Net in the

last three months. Where statisticians believe the numbers are

flawed is in the weighting used to help match the sample to thepopulation. Weighting must be used to prevent research from being

skewed toward one demographic segment.

The Nielsen survey was weighted for gender but not for education

which may have skewed the population toward educated adults.

Nielsen then proceeded to weight the survey by age and income

after they had already weighted it for gender. Statisticians also feel

that this is incorrect because weighting must occur simultaneously,

not in separate calculations. Nielsen does not believe the concerns

about their sample are legitimate and feel that they have not erred inweighting the survey. However, due to the fact that most third

parties have not endorsed Nielsens methods, the validity of their

research remains to be established.

Activity 1

Enter the relevant data by using the 10 samples of your

questionnaire.

9.2 SURVEY FIELD WORK AND DATA COLLECTION

Primary data and surveys are normally used in different areas of marketingproblems and the best option to collect these primary data is the surveymethod. Fieldwork is thus needed to collect the primary data in marketingresearch. This is very rare instance in the field of marketing especially incorporate research case that the person who designed the research rarelycollects the primary data. A specialized agency or the person in theresearch department normally collects this kind of data for the researchstudy. There are lots of problems and issue concerning with this fieldwork.




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These problems are only occurred when a proper recruitment procedure innot followed.

Data collection process can be categorized as follows:1. Select the fieldworkers2. Train them3. Supervise them4. Evaluate their fieldwork as well themselves

Before selecting any fieldworker, an analyst must determine the suitability ofthe fieldwork for a particular study. This seems very critical in situationswhen personal and telephonic interviews are conducted. However

respondents may feel comfortable when they interact with the fieldworkerson telephonic. In many cases, an analyst dont bother the working of theirfieldworkers which can prove to be an adverse impact on quality of datacollected as well as on overall response rate also. Thus, it is to be notifiedthat an analyst must train their fieldworkers related to the pattern andobjectives of the questionnaire. It is normally seen that fieldworkers are notproperly aware about the questionnaire process. This situation appears sueto lack of proper training. Due to this reason fieldworkers my feel unable toconduct the interviews in a proper and efficient manner. Researchers havedeveloped some guidelines for their fieldworkers related to the research asfollows:

1. Firstly go through with the questionnaire thoroughly2. Put up the question in the same sequence as they appear in the

questionnaire3. Use the wording exactly the same as in the questionnaire4. Repeat or vocalize the question which is not understood by your

respondents5. Read the questions in a slow motion always6. Put up every possible and applicable question7. Follow all the instructions properly and carefully

While examining the research techniques, researcher must train theirfieldworkers too. Examining or probing process helps the researcher in

encouraging the respondent and making focus on a specific problem orissue. If they are not trained properly then it can create biasness in theprocess. There are lots of probing techniques involved in the research asfollows:

1. Drawing out clarification2. Questions to be repeated3. Respondents reply to be repeated4. Respondents should be reassured and boosted5. A pause should be used or it can also be termed as silent probe




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6. Sometimes ask neutral questions or comments alsoThe process of how to collect the respondents response and how to windup the interview session, it must be trained to the fieldworkers politely. Asthis training gives rise to a normal worker to a trained fieldwork. And thistrained fieldworker can become the good asset for the research process intotality in comparison to those who feel disengagement with the wholeprocess.It is to be noted that these fieldworkers are given their payment on hourly ordaily basis and in many cases. Due to this reason their motivation ratio toconduct the efficient interviews may not be as high as a researcher lookingacross the whole process. In this situation supervision influence is also highwith the help of which a researcher can look after the control on their

fieldworkers whether they are following the techniques and proceduresaccording to their training. Supervision plays a vital role in these kinds ofsituations. This helps the researcher in keeping a tab or close watch on theethical standards used in this field as well as on cheating or fraud casesalso.Another issue related to the fieldwork is to evaluate the fieldwork andfieldworkers. In terms of the authentication of the interviews conducted,evaluation the fieldwork is very significant issue. To check the authenticity, aresearcher can call 10-15% of the respondents taken in the sample to checkwhether fieldworkers conducted the interviews properly. Supervisor can putup various questions also from the same questionnaire to make aconfirmation of the data authenticity. There are various measures toevaluate the fieldworkers like their response rates, total cost incurred andthe quality of data collected while conducting the interviews.

Self Assessment questions

1. Secondary data and surveys are normally used in different areas ofmarketing problems and the best option to collect these primary data is thesurvey method

2. A _____________ agency or the person in the research departmentnormally collects this kind of data for the research study.

9.3 NATURE AND SCOPE OF DATA PREPARATION

Data collection term is very important in the whole marketing researchprocess. The data which fieldworkers collect is known as raw data whichfurther needs to be organized and systematized in a well proper way. Rawdata may be inaccurate, incomplete, and crude and scattered in variousformats of data collection. The researcher must keep in mind various




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measures like editing, coding, classification and tabulating to organize thedata in a proper order to analyse it further.After collecting the data, next step of researcher is to give attention on dataanalysis. Once the final data has been collected, researcher can initiate theanalysis process instantly. The steps are as follows:

Figure: 9.1; process of Data preparation

These above steps help in collecting the data for analysis. This processplays a very significant role in collecting the data in a correct way. If thecollected data is not relevant as per the requirement then it can hamper aresearchers objectives. Simultaneously manager can make wrong decisiontoo.

Self Assessment questions3. Data collection term is very important in the whole marketing promotionprocess. (True/False)

4. Raw data may be inaccurate, incomplete, and crude and scattered invarious formats of data collection. (True/False)

EDITIN

G

CODING

ENTRY

CLEANING




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9.4 EDITINGAfter collecting the raw data with the help of the questionnaire, the first stepin data preparation process is to do editing. Edition is done to detect theerrors and omissions while collecting the data and then helps in convertinginto the correct form. Editing also specifies the quality standards to beachieved in a proper way. The main objective of editing is to generateaccurate, complete and well arranged data which further helps in simplifyingthe coding step of data processingIt will be apparent in some cases that the questionnaire entry is entered inthe wrong place. Such kind of errors or mistakes could have happened atthe time of recording or interpreting the data. When the researcher finds littleinformation missing or inappropriate then he has three options:

a) While doing review of other information, a researcher can detect theexact answer for the missing information. A researcher can do thisthing only in those cases where he already aware about the correctanswer.

b) When researcher finds the answer in terms of no answer orunknown then he can strike out the answer by considering it clearlyinappropriate. But if your sample size is small in nature then thismethod doesnt found successful. As striking out answer can betaken in otherwise sense like it can generate that information ismissing and analysis of this answer should not be done.

c) To get data authentication, researcher can make direct contact to thesample respondents. This option is chosen in those cases whererespondents have plenty of time and money also.

There are other major problems also in the process of editing like fakenessin an interview. Such kinds of interviews which are fake are hard to come inlimelight and if these interviews involve tick boxes, it becomes very difficultto spot out. They can only be captured in editing stage. The best option totrack out those interviews that are fake is to add some open-endedquestions in your questionnaire. Then it becomes difficult to fake. If fakingoccurs then the researcher finds different response pattern in otherquestions. To eliminate this issue, editor must analyse the interviewers

instruments used by him.


5. After collecting the raw data with the help of the questionnaire, the firststep in data preparation process is to do:

(i) Formatting (ii) Editing (iii) Processing (iv) Collecting.




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6. There are other major problems also in the process of editing like fakingof an:

(i) Questionnaire (ii) answer (iii) interview (iv) coding

9.5 CODING

Coding is the second step of data preparation. Coding is the process bywhich some numbers or symbols are assigned to the responses in theediting data of the questionnaire. These responses are further collected in agroup or categories which ensure their depthness and exclusivity. In thisnumerical values are assigned to each respondents response for eachquestion during the research survey. At the time of classification of the datasome data is lost but this classification is very important for the datapreparation process. It is better to not to use the word Male or Female foridentification instead M or F . the variable could be as follows:

Male- 1

Female- 2 or 0 and 1

In the same sense coding of Likert Scale is done as: Strongly disappointed- 1

Disappointment- 2

Neither disappointed nor agree-3

Agree-4

Strongly agree-5

This coded language makes the overall analysis more interpretable asmostly all the numbers are understood easily with the help of thesestatistical softwares. Coding helps in scrutinizing the huge data into a lotwhich makes simpler for the researcher to interpret the meaning. In codinglanguage, when a set of partitioned data is structured it is known ascategories and when some rules and policies are framed to partition thedata it is known as categorization. To develop this coding structure for thequestionnaire, there is one easiest option namely codebook.




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For example: 103103042 8394199101911010310305 1124232130110110103104063 92221241000110

A codebook is a set of all the variables used in the study and it alsospecifies how these rules and policies are applicable to the variable. Thiscodebook is normally used by the researcher and their staff as a guidewhich helps in making data entry less prone to mistakes and error. Duringanalysis with the help of this guide, positions of variables can be easilylocated in the data file. The contents of the codebook includes as follows:

Question serial number

Variable name

Location of the variable code

Descriptive response options of the respondents

Note: it is not necessary that every code book is computerized. It can behand made also. Another thing to be noted that variable can be alpha (A-Z)or numeric (0-9).There is certainty in the close ended questions of coding. Thus it is to be

notified that it becomes easier to analyse the coding close ended questions.Because these questions are more predetermined and structured in nature.However, these questions are tricky as well as respondents answers maybe staggering in nature.

Format of Codebook

School identification code

Student identification code

1. Are you a boy or a girl? (Tick one number)Boy .............................................. 1

Girl .............................................. 2

2. How old are you? (Put in your age in years)

....................................................... years




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3. How often do you eat each of the following meals? (Tick one numberon each line)

Not 1 or 2 times 3 or 4 times Every

at all a week a week day

(a) Morning meal 1 2 3

4

(b) Lunch 1 2 3

4

(c) Evening meal 1 2 3

4

4. Are there any books where you live that you could read which are not

your

school books? (Tick one number)

Yes .............................................. 1

No .............................................. 2 If No, go to question 6.

5. If Yes, how often do you read these books? (Tick one number)

Always.......................................... 3

Sometimes................................... 2

Never............................................ 1

6. If Yes, how many books are there in your home? (Tick one

number)

None............................................. 1

1 to 10 books............................. 2

11 to 50 books........................... 3

More than 50 books................. 4

7. Do you have the following things in your home? (Tick one number on

each line)

Do not have this Have one or more




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(a) Radio 0 1

(b) TV 0 1

(c) Table to Write on 0 1

(d) Bicycle 0 1

(e) Electricity 0 1

(f) Running Water 0 1

(g) Daily Newspaper 0 1

Source:http://www.unesco.org/iiep/PDF/TR_Mods/Qu_Mod10.pdf


7. __________ is the second step of data preparation

8. A factbook is a set of all the variables used in the study and it alsospecifies how these rules and policies are applicable to the variable.(True/False)

9.6 DATA ENTRY

After doing the coding to the information, next step of data preparation is tomake data entry. This is done with the help of applying statistical softwarepackage. Data entry can be divided into various methods as follows:

Manual data entry

This is the common method generally used by the researchers whohave shortage of time while preparing data. Thus researcher createsthe data file immediately by using keyboarding and then save it in aminimal space of hard drive. When there is large number of dataentry files then this method is highly prone to error.

Optical scannersWhen there is large scale of study or where the large number of datais to be entered then this optical scanners are used. In this method,character recognition or optical mark recognition of questionnairetakes place with the help of scanner. After that data is converted intoa statistical output with the help of computer.

By using these methods, the overall efficiency and effectiveness of dataentry is achieved.


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For example: in case of CATI or CAPI, data is directed stored in the memoryof the computer due to which there is no requirement for data entry atfurther stage.

Now a days trend becomes changed and advanced. Many organisationsuse electronic devices like PDAs.

For example: utility of Tablet PCs and new Tech savvy Mobiles havechanges the older methods of data entry.


9. _______________ is the common method generally used by theresearchers who have shortage of time while preparing data

10. Researcher creates the data file immediately by using keyboarding andthen save it in a minimal space of hard drive.(True/False)

9.7 DATA CLEANING

The next and the final stage of data preparation is data cleaning. Datacleaning is the process of detecting errors and consistency checks and thenmaking a proper treatment of missing responses. Data cleaning can be

done by checking each variable properly.

Check each variable for the data: Check the variables which are logicallyinconsistent or considered as out of range. This kind of data can hamper theoverall process of analysis thus it must be rectified on time. To rectify thisinconsistent data, most advance statistical packages are used which providecorrect output for the analysis. You must keep in mind that there should be aclose supervision on these inconsistent data as sometimes there isconfusion of inconsistency which further represents legitimate response.

This is a common activity found in most of the research surveys. Itoccurs because of two reasons:a) Whether the respondent has given ambiguous response to the

interviewer or,b) Recording of the respondents record is improper

Thus in such cases, data cleaning helps in analyzing the missingvalue. If the ratio of missing value is 10% more then it can createmajor problems for the researcher in data analysis. For treatingmissing values, four options are used as follows:




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a) Convert the missing value with a neutral valueb) Convert an assigned response by following a pattern of

respondents responsesc) Delete the cases where missing responses of respondents are

discarded from the analysis.d) Delete pair wise, where the complete responses provided by the

respondents for specific variables are included.All the different procedures have their different responses in data cleaning.Thus, a researcher must take care of every point during cleaning of thedata. Also the process of data cleaning should not be very large.


11. Data _____ is the process of detecting errors and consistency checksand then making a proper treatment of missing responses.12. Data cleaning helps in analyzing the missing value.(True/False)

9.8 PRELIMINARY DATA ANALYSIS

In the earlier sections of this unit you learnt how responses are coded andentered. This process provides valuable information while creating thenumerical summaries.

For example: the data which is missing related to the respondent may be

detected with the help of this process.

In this stage of preliminary data analysis, all the problems are rectifiedwhether it can be mis-coded, out of range, extreme values or any otherproblem related to the data preparation. Once the data cleaning process isdone efficiently, a researcher can complete the journey of data analysis.Here you should focus on the first step of data analysis which is related todescriptive analysis.Descriptive statistics is the process which describes the features orcharacteristics of the data. This method further helps in making the analysisfor the violations of the assumptions of statistical techniques. Descriptiveanalysis also traces out the specific research questions. In this method, lot

of advance statistical tests are used which are very sensitive to dataviolation. These tests further create a clear picture in the mind of researcherto track the exact position of the violation of data.




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Figure 9.2: Statistical methodsSource: finntrack.co.uk

These tests include:

Mean

Range of scores

Standard deviation

Skewness and kurtosis

By using frequencies and exploration command in SPSS, this kind of

statistics can be obtained. SPSS is a name of Software. In the whole world,SPSS is commonly used statistical software package. There are other lot ofsoftware packages like this which includes SAS, Strata and Minitab etc.

To analyse these purposes, researcher normally use the primary scale ofmeasurements which can be further categorized into two parts.

a) Categorical variables or non-metric data

b) Continuous variables or metric data

Categorical data is that data which includes nominal and ordinal scalebased variables.

For example: marital status, gender etc.

Continuous variables include the variables of interval and ratio scale based.

For example: weight, height, temperature, distance, speed and more on.




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Descriptive statistics method is used for both categorical and continuousvariables. It is applicable to SPSS kind of programmes also. This statisticsgive information related to the frequency and percentages. For example: fora single variable how many times a specific data happen like number ofmales and females respondents. For continuous variables, descriptive datagive information related to mean, standard deviation, skewness andkurtosis.Self Assessment questions

13. ______ statistics is the process which describes the features orcharacteristics of the data.

14. Categorical data is that data which includes ______ and _______scalebased variables.

9.9 ASSESSING FOR NORMALITY AND OUTLIERS

A researcher has to presume this thing that the data collected from therespondents is normal and free of outliers.

For example: if on a bell curve data is plotted, then mostly the strength ofdata appears in the middle. And as you move here and there, strength ofdata will decrease accordingly either side in a proportional trend. Innormality situation, the other methods of statistics also provide some

information.

These methods are skewness and kurtosis.

Positive skewness indicates the data points or strength on the left

side of the bell curve which indicates low value.

Negative skewness indicates the data points cluster on the higher

side or on the right side of the bell curve.

On the other hand positive kurtosis indicates the data points

collected at the center with long thin tails.

Negative kurtosis indicates the values below 0 where the data points

are relatively flat.In normality, SPSS also provide various techniques. The result or outputprovided by this technique has few things to look as follows:




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Source: virtual-pharma-research.comFigure:9.3: SPSS method

a) 5% trimmed mean, there are lot of extreme values in the data basein case where there is a huge difference between 5% trimmed meanand original mean.

b) This technique also provide information related to skewness and

kurtosisc) Normality is indication in the situation where the test of normality has

0.05 or more than this significance value. You should note this thingthat in case of having large sample of data, this method givesindication that data is non-normal.

d) In normality, histograms indicate visual representation of the data tobe distributed.

e) To identify the outliers, box plots are used in this method. In SPSS,the cases which found as outliers will be specified in other mode likeit can be marked as small rounds at the corner of the box plot areas.

If a researcher wants to rectify the anomalies in the data collection then he

has to use these tests of normality and outliers.


15. A researcher has to presume this thing that the data collected from therespondents is normal and free of outliers. (True/False)




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16. ______ kurtosis indicates the values below 0 where the data points arerelatively flat.

Activity 2Assume yourself as Logistic manager of XYZ Company. Prepare acodebook for your company.

9.10 SUMMARY

Let us recapitulate the important concepts discussed in this unit:

This unit explains major two aspects of the process of marketing

research as data preparation and preliminary data analysis.

After designing the questionnaire, researcher collects the primarydata which requires the involvement of the fieldworkers.

Researcher has to be specific while doing the selection, training and

supervision of their fieldworkers. Because it directly affect the qualityof the data collection.

After collecting the data by fieldworkers, the researcher has to go for

the next stage which includes editing and coding of the data.

Editing and coding plays a major part in data preparation process

though both steps are tedious in nature as well.

Both editing and coding steps are very helpful for the researcher in

eliminating the anomalies with the data by using data cleaning

method. After doing data cleaning the researcher analyse the data in

normality sense.

For normality and outliers, the researcher must use different kind of

descriptive statistical tests.

After doing normality and outlier tests, preliminary data is analysed

then researcher start hypothesis testing.

9.11 GLOSSARY

Raw data: The data which fieldworkers collect is known as raw data which

further needs to be organized and systematized in a well proper way.Editing: It is done to detect the errors and omissions while collecting the

data and then help in converting into the correct form.

Coding: It is the process by which some numbers or symbols are assigned

to the responses of the questionnaire editing part.




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Data cleaning: It is the process of detecting errors and consistency checksand then making a proper treatment of missing responses.

Descriptive statistics: This is the process which describes the features or

characteristics of the data.

9.12 TERMINAL QUESTIONS

1. Discuss the concept of data editing.

2. Explain the process of data preparation.

3. What is the nature and scope of data preparation?

4. Discuss the concept of data entry and data cleaning.

5. What kinds of statistical software are used in data analysis?

6. Elaborate the concept of preliminary data analysis.

7. How would you assess the normality and outliers concept in data

preparation process?

9.13 ANSWERS

Self-Assessment Questions

1. False

2. Specialized

3. False

4. True

5. ii)

6. iii)

7. Coding

8. False

9. Manual data entry




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10. True

11. Cleaning

12. True

13. Descriptive

14. Nominal, ordinal

15. True

16. Negative

Terminal questions

1. After collecting the raw data with the help of the questionnaire, the

first step in data preparation process is to do editing..Refer 9.4

2. The steps are as follows:.Refer 9.3-9.7

3. Data collection term is very important in the whole marketing

research process.Refer 9.3

4. After doing the coding to the information, next step of data

preparation is to make data entry..Refer 9.6 & 9.7

5. Descriptive statistics is the process which describes the features or

characteristics of the data..Refer 9.8

6. In the earlier sections of this unit you learnt how responses are

coded and entered.. Refer 9.8

7. A researcher has to presume this thing that the data collected fromthe respondents is normal and free of outliers..Refer 9.9

9.14 CASE STUDY

Actuarial Firm Needed to Reduce Data Preparation Costs

A global actuarial firm was taking too much time preparing census data for

valuations and needed to reduce costs.

The Partner




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This project established a partnership with a global actuarial and benefitsconsulting firm

The Challenge

A global actuarial and benefits consulting firm was taking too much time

preparing census data for actuarial valuations and wanted to reduce their

costs. Their business was growing and they needed a tool that could more

easily consolidate data, reconcile differences from prior years and produce

comprehensive analysis reports before sending the data to their valuation

systems. They also needed a tool that was flexible enough to adapt to

various data formats and tailor data validation criteria for each client tofacilitate correction of data problems.

The Approach

Our Professional Services Group used Applaud-Benefits to build acustomized solution for the actuarial firm.

The solution that we built with Applaud gave the firm everything on their

wish list:

They were able to access client data easily and in any format and

identify data anomalies quickly using profiling and analysis tools.

Since matching the current data to the prior year's data was always a

problem, the solution included the capability to match records on four

different criteria: Social Security number, employee ID, employee

name, and a combination of first initial, birth date, and hire date

(looking for a female that was married or divorced since last year).

Comprehensive reports identified each match as well as non-match

participants.

The firm wanted to roll the tool out to their offices around the globe.

The tool had to be flexible enough to easily handle a wide range of

data validation routines that its actuaries and consultants needed in

the field. We incorporated over 75 data validation routines that could

be selectively turned on or off, depending on each client's

requirements.




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In addition, the system made it easy to produce many types ofreports including experience reports, age/service reports and many

other types of analysis reports.

In the end, data was reformatted and exported to the firm's valuation

systems.

The Success

The solution took only 12 weeks to design, develop and test. The firm's

ongoing cost of data preparation was greatly reduced and their data quality

improved dramatically, which ultimately led to a significantly higher level of

client satisfaction.

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Questions:

1. Elaborate the case in detail.

2. What is the main issue discussed in the case?

3. What method is adopted to solve that issue?

4. How success is achieved to recover the issue?

REFERENCES

Boyd, H., R. Westfall, and S. Stasch (1989), Marketing research: Text andCases. Boston:Irwin.(1989), Marketing research: Text and Cases. Boston:Irwin.Reichheld, F. (1996), "Learning From Customer Defections," HarvardBusiness Review, 74(March-April), 56-69.




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Shukla, P. (2002), "Managing Customer Expectations: The Ethical Way," inEthics inManagement: Emerging Issues in the New Millennium, B. Prajapati(Ed.). North GujaratUniversity, India.Malhotra, N. (2004b), Marketing Research: An Applied Orientation. New

Jersey: PearsonEducation.Aaker, D. and G. Day (1980), MarketingResearch. New York: John Wiley & Sons.Malhotra, N. and D. Birks (2003), Marketing Research: An AppliedApproach. London:Prentice Hall.

E-References

www.bookboon.com 27/06/2012, 5.30 pm

http://www.unesco.org/iiep/PDF/TR_Mods/Qu_Mod10.pdf

28/06/2012, 2.30 pm


http://www.bookboon.com/http://www.bookboon.com/

SMU Marketing Research Ch-9

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