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SURVEY RESEARCH

SURVEY RESEARCH 11
Master of Information Technology Program Faculty of Computer Science University of Indonesia SURVEY RESEARCH RESEARCH METHODOLOGY CLASS Lecturer : RIRI SATRIA Date : November 10, 2009 DEFINITION OF SURVEY RESEARCH Survey: •  A method of primary data collection based on communication with a representative sample of individuals (called respondents). Key Concepts in the Definition 1.  Primary data 2.  Communication 3.  Sample 4.  Representative Master of Information Technology Program Faculty of Computer Science University of Indonesia •  Survey research is one of the most important areas of measurement in applied social research. •  The broad area of survey research encompasses any measurement procedures that involve asking questions of respondents. •  A "survey" can be anything form a short paperandpencil feedback form to an intensive oneonone indepth interview. Master of Information Technology Program Faculty of Computer Science University of Indonesia THE LOGIC OF SAMPLING AND MEASUREMENT 4 Master of Information Technology Program Faculty of Computer Science University of Indonesia ADVANTAGES AND DISADVANTAGES OF SURVEYS Advantages: Speed – Faster data collection than other methods Cost Relatively inexpensive data collection Accuracy – Survey data can be very accurate if sampling is properly done Efficiency – Measured as a ration of accuracy to cost, surveys are generally very efficient data collection methods Disadvantages: Survey error – Potentially large sources of error in surveys Communication Problems Each of the different communication survey methods has its own unique problems. Master of Information Technology Program Faculty of Computer Science University of Indonesia CLASSIFYING SURVEY RESEARCH METHODS 1.  By method of communication. a)  Personal Interviews b)  Telephone interviews c)  Selfadministered interviews 2.  By degree of structure and disguise. a)  Structured disguised b)  Structured undisguised c)  Unstructured disguised d)  Unstructured undisguised 3.  By time frame (Temporal classification). a)  Crosssectional surveys b)  Longitudinal surveys Master of Information Technology Program Faculty of Computer Science University of Indonesia CLASSIFYING SURVEYS BY DEGREE OF STRUCTURE AND DISGUISE Structured Unstructured Example: Typical Example: survey Undisguised descriptive survey with openended (Direct) with straightforward, questions to structured questions. discover “new” answers. Example: survey Example: projection Disguised interview to measure techniques used (Indirect) ERP product brand mostly for A’s image versus exploratory competitive brand’s research. or brand recall (unaided recall). Master of Information Technology Program Faculty of Computer Science University of Indonesia TEMPORAL CLASSIFICATION OF SURVEY RESEARCH 1.  Crosssectional studies: studies in which various segments of a population are sampled and data collected at a single point in time. 2.  Longitudinal studies: studies in which data are collected at different points in time using: a)  successive (different) samples in a tracking study or cohort study. b)  the same sample in a panel study (user panels, developer panels, etc). Master of Information Technology Program Faculty of Computer Science University of Indonesia •  Population issue –  Can the population be enumerated –  Is the population literate –  Are there language issues –  Will the population cooperate –  What are the geographic restrictions •  Sampling issues –  What data is available –  Can respondents be found –  Who is the respondent –  Can all members of population be sampled –  Are response rates likely to be a problem Master of Information Technology Program Faculty of Computer Science University of Indonesia •  Questioning issues –  What types of questions can be asked –  How complex will the questions be –  Will screening questions be needed –  Can question sequence be controlled –  Will long response scales be used –  Will long response scales be used •  Content and Bias issues –  What are your constructs Master of Information Technology Program Faculty of Computer Science University of Indonesia GENERAL PROBLEM OF MEASUREMENT RELIABILITY VALIDITY Reliability –  Refers to the replicability of the measurement procedure to yield consistent results Validity –  Refers to the extent to which the measurement procedure actually measures the concept that it is intended to measure 11 Master of Information Technology Program Faculty of Computer Science University of Indonesia CLOSEDENDED QUESTIONS Advantages –  Quick easy for respondents –  Less articulate are not at a disadvantage –  Response choices can clarify alternatives –  Fewer irrelevant answers –  Easy to code and analyse Disadvantages –  Responses suggest ideas (e.g., No opinion/knowledge still give opinion) –  Frustrates respondents if categories are not exhaustive –  Misinterpretation goes unnoticed –  Complex issues forced into simple categories –  Recency effects 12 Master of Information Technology Program Faculty of Computer Science University of Indonesia OPENENDED QUESTIONS •  Advantages –  Permits detail, clarification –  Unanticipated answers –  Reveals the logic behind a respondent’s response •  Disadvantages –  Generalization or comparison difficult –  Coding and statistical analysis difficult –  Irrelevant answers possible –  Bias towards educated 13 Master of Information Technology Program Faculty of Computer Science University of Indonesia CATEGORIES OF SURVEY RESEARCH ERRORS Master of Information Technology Program Faculty of Computer Science University of Indonesia CATEGORIES OF SURVEY ERROR 1.  Random Sampling Error – Statistical fluctuation due to chance variations in elements selected for the sample. 2.  Systematic (NonSampling) Error – Error resulting from: –  imperfections in the research design that leads to respondent error, –  mistakes in executing the research. Often leads to sample bias – the tendency of sample results to deviate in one particular direction 1.  Respondent Error – Sample biases that result from the respondent action (response bias) or inaction (nonresponse bias) 2.  Administrative Error – Error caused by improper administration (execution) of the research tasks Master of Information Technology Program Faculty of Computer Science University of Indonesia CATEGORIES OF RESPONDENT ERROR 1.  Nonresponse Error – The statistical difference between the results of a survey in which the sample includes only those who responded (answered the questions) and a survey that would include those who failed to respond. Reasons include: (a) notathome, (b) refusal, or c) selfselection 2.  Response bias – Bias that occurs when those who respond tend to answer questions in a way that misrepresents the truth consciously (deliberate falsification) or unconsciously (unconscious misrepresentation) Reasons for Deliberate falsification Reasons for unconscious misrepre. 1. To appear intelligent 1. Question format or content 2. To conceal personal information 2. Interview situation 3. To avoid embarrassment 3. Misunderstanding the question 4. To get rid of the interviewer 4. Forgetting exact details 5. To please the interviewer 5. Unexpected question 6. Inability to express feelings Master of Information Technology Program Faculty of Computer Science University of Indonesia CATEGORIES OF RESPONSE BIAS 1.  Acquiescence bias – tendency to agree with everything the interviewer says 2.  Extremity bias – tendency to use extremes when responding to questions 3.  Interviewer bias – tendency of interviewer’s presence to affect respondent’s answers 4.  Auspices bias – tendency for knowledge of who is sponsoring the research to affect respondents’ answers 5.  Social desirability bias – tendency for respondents to give socially acceptable answers rather than the truth Master of Information Technology Program Faculty of Computer Science University of Indonesia CATEGORIES OF ADMINISTRATIVE ERROR 1.  Sample Selection Error – Error caused by improper sample design or sampling procedure 2.  Interviewer Error – Errors caused by interviewers making mistakes when performing their tasks 3.  Interviewer Cheating – Errors caused by interviewers filling in fake answers to questions or falsifying entire questionnaires 4.  Data Processing Error – Errors caused by incorrect data entry, computer programming, or other procedural errors during data analysis Master of Information Technology Program Faculty of Computer Science University of Indonesia CONSTRUCTING A GOOD QUESTIONNAIRE GENERAL ADVICE •  Use social conversation as a guide to both question construction and questionnaire design •  Questions should be straight to the point •  One thing per question •  Avoid jargon, slang, abbreviations •  Avoid asking about vague future intentions or hypothetical questions •  Avoid wording that is influential or offensive •  If little is known use open questions; otherwise closedended questions with exhaustive and mutually exclusive response categories are typically better •  Borrow questions from existing literature •  Pretest 19 Master of Information Technology Program Faculty of Computer Science University of Indonesia Master of Information Technology Program Faculty of Computer Science University of Indonesia THANK YOU for your attention
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