Questionnaires - Personal Website of Ahmad Othman · 2014-11-04 · –Can pick up non-verbal cues –Relatively high response/cooperation –Special visual aids and scoring devises

Research Methods for Business

1

Chapter 9

Data Collection Methods: Questionnaires

© 2012 John Wiley & Sons Ltd. www.wiley.com/college/sekaran


Questionnaire Design

• DefinitionA questionnaire is a pre-formulated, written set of questions to which the respondent records his answers

• Steps

1. Determine the content of the questionnaire

2. Determine the form of response

3. Determine the wording of the questions

4. Determine the question sequence

5. Write cover letter



1. Questionnaire content

• FrameworkNeed information for all constructs in framework

• Measurement: Operationalizing– Objective construct:

• 1 element/items=> 1 question

– Subjective construct: • multiple elements/items

=> multiple questions



2. Response format

• Closed vs. Open-ended questions– Closed questions

• Helps respondents to make quick decisions

• Helps researchers to code

– Open-ended question• First: unbiased point of view

• Final: additional insights

• Complementary to closed question: for interpretation purpose

• Cfr. Measurement: Response scales



• Avoid double-barreled questions

• Avoid ambiguous questions and words

• Use of ordinary words

• Avoid leading or biasing questions

• Social desirability

• Avoid recall depended questions

3. Question wording



• Use positive and negative statements

– Dresdner delivers high quality banking service

Dresdner has poor customer operational support

– Avoid double negatives

• Limit the length of the questionsRules of thumb:

– < 20 words

– < one full line in print

Question wording



4. Question sequence

Personal and sensitive data at the end© 2012 John Wiley & Sons Ltd.

www.wiley.com/college/sekaran


• The cover letter is the introductory page of the questionnaire

• It includes:

– Identification of the researcher

– Motivation for respondents to fill it in

– Confidentiality

– Thanking of the respondent

5. Cover letter



9

Chapter 7

Data Collection Methods: Introduction and Interviews



Sources of Data

• Primary data: information obtained firsthand by the researcher on the variables of interest for the specific purpose of the study.

• Examples: individuals, focus groups, panels

• Secondary data: information gathered from sources already existing.

• Examples: company records or archives, government publications, industry analyses offered by the media, web sites, the Internet, and so on.



Interviews

• Unstructured interviews:

– the interviewer does not enter the interview setting with a planned sequence of questions to be asked of the respondent.

• Structured interviews:

– Conducted when it is known at the outset what information is needed.

– The interviewer has a list of predetermined questions to be asked of the respondents either personally, through the telephone, or via the computer.



Personal interview

• Advantages– Can clarify doubts about questionnaire

– Can pick up non-verbal cues

– Relatively high response/cooperation

– Special visual aids and scoring devises can be used

• Disadvantages– High costs and time intensive

– Geographical limitations

– Response bias / Confidentiality difficult to be assured

– Some respondents are unwilling to talk to strangers

– Trained interviewers



Telephone interview

• Advantages– Discomfort of face to face is avoided

– Faster / Number of calls per day could be high

– Lower cost

• Disadvantages– Interview length must be limited

– Low response rate

– No facial expressions



Self-administered

• Advantages– Lowest cost option

– Expanded geographical coverage

– Requires minimal staff

– Perceived as more anonymous

• Disadvantages– Low response rate in some modes

– No interviewer intervention possible for clarification

– Cannot be too long or complex

– Incomplete surveys



Projective Methods• Word association techniques:

– Asking the respondent to quickly associate a word with the first thing that comes to mind.

– Often used to get at true attitudes and feelings.

• Thematic apperception tests (TAT):– Call for respondent to weave a story around a picture

that is shown. – To trace patterns and personality characteristics of

respondents.

• Inkblot tests: – Form of motivational research, uses colored inkblots

that are interpreted by respondents.



16

Chapter 8

Data Collection Methods: Observation



Observation

• Observation involves going into ‘the field’, -the factory, the supermarket, the waiting room, the office, or the trading room -watching what workers, consumers, or day traders do, and describing, analyzing, and interpreting what one has seen.



Examples

• Shadowing a Wall Street broker engaged in his daily routine.

• Observing in-store shopping behavior of consumers via a camera.

• Sitting in the corner of an office to observe how a merchant bank trader operates.

• Working in a plant to study factory life.

• Studying the approach skills of sales people disguised as a shopper.



Key dimensions characterizing type of observation

• Controlled versus Uncontrolled Observational Studies

• Participant versus Non-Participant Observation

• Structured versus Unstructured Observational Studies

• Concealed versus Unconcealed observation



Participant Observation

• The participatory aspect:

– Complete participation

– Moderate participation

– Active participation

• To what extent should I participate?



Participant Observation

• The observation aspect

– Obtaining permission

– Finding a ‘sponsor’

– Establishing rapport



What to observe?

• Descriptive observation stage:

– Space

– Objects

– Actors

– Feelings

– Events

Spradly, 1980



What to observe?

• Focused and selective observation stage:– Look for a story line

– Sort out regular from irregular activities

– Look for variation in the storyline

– Look for negative cases or exceptions

– Develop a plan for systematic observation if needed

DeWalt and DeWalt, 2002



Structured observation

• Looks selectively at predetermined phenomena

• Different levels of structure



Coding schemes

• Focus

• Objective

• Ease of use

• Mutually exclusive and collectively exhaustive



Standard Coding Schemes

• Simple checklist

• Sequence record

• Sequence record on time scale



27

Chapter 12

Measurement of Variables: Scaling, Reliability, Validity



Scale

• Scale: tool or mechanism by which individuals are distinguished as to how they differ from one another on the variables of interest to our study.



Nominal Scale

• A nominal scale is one that allows the researcher to assign subjects to certain categories or groups.

• What is your department?

O Marketing O Maintenance O Finance

O Production O Servicing O Personnel

O Sales O Public Relations O Accounting

• What is your gender?

O Male

O Female



Nominal Scale



Ordinal Scale

• Ordinal scale: not only categorizes variables in such a way as to denote differences among various categories, it also rank-orders categories in some meaningful way.

• What is the highest level of education you have completed?O Less than High School O High School/GED Equivalent O College Degree O Masters Degree O Doctoral Degree



Ordinal Scale



Interval Scale

• Interval scale: whereas the nominal scale allows us only to qualitatively distinguish groups by categorizing them into mutually exclusive and collectively exhaustive sets, and the ordinal scale to rank-order the preferences, the interval scale lets us measure the distance between any two points on the scale.



Interval scale

• Circle the number that represents your feelings at this particular moment best. There are no right or wrong answers. Please answer every question.

1. I invest more in my work than I get out of it

I disagree completely 1 2 3 4 5 I agree completely

2. I exert myself too much considering what I get back in return


3. For the efforts I put into the organization, I get much in return




Interval scale



Ratio Scale

• Ratio scale: overcomes the disadvantage of the arbitrary origin point of the interval scale, in that it has an absolute (in contrast to an arbitrary) zero point, which is a meaningful measurement point.

• What is your age?



Ratio Scale



Properties of the Four Scales

• Insert Table 12.1 here



Goodness of Measures



Validity



Reliability

• Reliability of measure indicates extent to which it is without bias and hence ensures consistent measurement across time (stability) and across the various items in the instrument (internal consistency).



Stability

• Stability: ability of a measure to remain the same over time, despite uncontrollable testing conditions or the state of the respondents themselves.– Test–Retest Reliability: The reliability coefficient

obtained with a repetition of the same measure on a second occasion.

– Parallel-Form Reliability: Responses on two comparable sets of measures tapping the same construct are highly correlated.



Internal Consistency

• Internal Consistency of Measures is indicative of the homogeneity of the items in the measure that tap the construct.

– Interitem Consistency Reliability: This is a test of the consistency of respondents’ answers to all the items in a measure. The most popular test of interitem consistency reliability is the Cronbach’s coefficient alpha.

– Split-Half Reliability: Split-half reliability reflects the correlations between two halves of an instrument.



44

Chapter 13

Sampling



Sampling

• Sampling: the process of selecting a sufficient number of elements from the population, so that results from analyzing the sample are generalizable to the population.



Relevant Terms - 1

• Population refers to the entire group of people, events, or things of interest that the researcher wishes to investigate.

• An element is a single member of the population.

• A sample is a subset of the population. It comprises some members selected from it.



Relevant Terms - 2

• Sampling unit: the element or set of elements that is available for selection in some stage of the sampling process.

• A subject is a single member of the sample, just as an element is a single member of the population.



Relevant Terms - 3

• The characteristics of the population such as µ (the population mean), σ (the population standard deviation), and σ2 (the population variance) are referred to as its parameters. The central tendencies, the dispersions, and other statistics in the sample of interest to the research are treated as approximations of the central tendencies, dispersions, and other parameters of the population.



Statistics versus Parameters



Advantages of Sampling

• Less costs

• Less errors due to less fatigue

• Less time

• Destruction of elements avoided



The Sampling Process

• Major steps in sampling:

– Define the population.

– Determine the sample frame

– Determine the sampling design

– Determine the appropriate sample size

– Execute the sampling process



Sampling Techniques

• Probability versus nonprobability sampling

• Probability sampling: elements in the population have a known and non-zero chance of being chosen



Sampling Techniques• Probability Sampling

– Simple Random Sampling

– Systematic Sampling

– Stratified Random Sampling

– Cluster Sampling

• Nonprobability Sampling– Convenience Sampling

– Judgment Sampling

– Quota Sampling



Simple Random Sampling

• Procedure– Each element has a known and equal chance of being selected

• Characteristics– Highly generalizable

– Easily understood

– Reliable population frame necessary



Systematic sampling

• Procedure– Each nth element, starting with random choice of an element

between 1 and n

• Characteristics– Idem simple random sampling

– Easier than simple random sampling

– Systematic biases when elements are not randomly listed



Cluster sampling• Procedure

– Divide of population in clusters

– Random selection of clusters

– Include all elements from selected clusters

• Characteristics– Intercluster homogeneity

– Intracluster heterogeneity

– Easy and cost efficient

– Low correspondence with reality



Stratified sampling

• Procedure– Divide of population in strata

– Include all strata

– Random selection of elements from strata• Proportionate

• Disproportionate

• Characteristics– Interstrata heterogeneity

– Intrastratum homogeneity

– Includes all relevant subpopulations



(Dis)proportionate stratified sampling

• Number of subjects in total sample is allocated among the strata (dis)proportional to the relative number of elements in each stratum in the population

• Disproportionate case:– strata exhibiting more variability are sampled more than proportional

to their relative size

– requires more knowledge of the population, not just relative sizes of strata



Example



Overview



Choice Points in Sampling Design



Tradeoff between precision and confidence

We can increase both confidence and precision by increasing the sample size



Sample size: guidelines

• In general: 30 < n < 500

• Categories: 30 per subcategory

• Multivariate: 10 x number of var’s

• Experiments: 15 to 20 per condition



Sample Size for a Given Population Size


Documents

Questionnaires - Personal Website of Ahmad Othman · 2014-11-04 · –Can pick up non-verbal cues –Relatively high response/cooperation –Special visual aids and scoring devises