Chapter 10 Questionnaire Design

Chapter Objectives explain why it is important for managers or business researchers to know how to design good questionnaires identify the types of information included in a questionnaire design questionnaires to tap different variables evaluate questionnaires, distinguishing the ‘good’ and ‘bad’ questions therein identify and minimise the biases in collecting data with questionnaires discuss how a pilot study can be used to prove the structure of a questionnaire discuss the advantages and disadvantages of the different ways of administering questionnaires

Why are questionnaires important? Managers and business practitioners must: have a working knowledge of the common business research processes with limited knowledge they could run a high risk of potential litigation be aware of the weaknesses of the resultant data from that limited questionnaire be able to understand & intepret the analysis need to know when to call in experts to provide assistance

Definition of a Questionnaire A questionnaire is a pre-formulated written set of questions to which respondents record their answers, usually within closely defined alternatives

Example of a Questionnaire

When to Use a Questionnaire When the researcher knows precisely what information is needed When large numbers of people are to be reached in different geographical regions When groups of people can be assembled in a convenient location (eg conference rooms) to whom questionnaires can be administered, and collected immediately

Advantages of Questionnaires Helps a researcher or manager obtain data fairly easily Information from questionnaires is easily coded Benefits the scientific community if the measures are well validated and reliable Often is a catharsis for respondents

Impact of Other Aspects of a Survey on Questionnaire Design

Principles of Questionnaire Design Principles of wording Principles of measurement General appearance Questionnaire administration & testing

Principles of Wording To minimise bias: Content and purpose of questions Language and wording of the questionnaire Type and form of questions Biases in questions Sequencing of questions Classification data or personal information

Content and Purpose of Questions To get at objective facts or subjective feelings and perceptions?

Language and Wording of the Questionnaire Would the respondent understand the words in the questionnaire? Are the questions ambiguous? Are there double-barrelled questions? Are the questions leading? Are there recall-dependent questions? Any social desirability? Does the length of the question exceed 20 words or one line of print?

Type of Questions Open-ended questions Freedom to answer the question any way one wants Could pose problems for researcher in coding the response Closed questions –Alternatives that are mutually exclusive and collectively exhaustive, given Respondent can make a quick decision Easy to intepret and code

Form of Questions Should be positively and negatively worded to reduce response bias or halo effects

Sequencing of Questions The Funnel Approach From general to specific questions From easy to difficult questions

The Funnel Approach

Classification Data – Personal Information or Demographic Data Decisions on: Name, number required? (anonymity) What info required? (income, marital status, etc needed?) Age, income, etc, should a range be given? If so, what are the appropriate ranges? –Eg, 40 Should personal info be at beginning or end of questionnaire?

General Appearance of the Questionnaire Introduction to respondents Instructions and organising questions Demographic data Sensitive personal data Open-ended question at end Concluding the questionnaire

Introduction to respondents identity of researcher purpose of survey establish rapport motivate repsondents confidentiality & anonymity summarised results distribution and/or publication of results courteous note, thanks

Pre-testing Questionnaires Face validity Content validity Pilot study –With sample of respondents from target population –Ideal research design Factor analysis –Reality – less than ideal –Collecting and analysing data Eg, SPSS or Excel

Gathering the Data Personally administered questionnaires Mail questionnaires Electronic questionnaires

Multimethods of Data Collection Data from different sources and through different methods could improve the “goodness” of the data Interview Observation Questionnaire Same source and other source data Objective measures (physical measurement, counting, etc) –Eg, performance data – get from all the above sources. See how they correlate.

Advantages and Disadvantages of Personal or Face-to-face Inteviews