2010Wiley International Encyclopedia of MarketingRequires access

Comparative Evaluation of Survey Methods

Tuo Wang

Open publisher page 1 citations

Abstract

Abstract A researcher has the option of choosing a method from a menu of different methods of doing surveys: face‐to‐face interview at home or mall‐intercept interview, mail survey, online survey, and telephone survey. Each of these methods is characterized by distinct advantages and disadvantages. The major criteria used to evaluate these methods are response time in collecting data, cost of obtaining data per respondent, quality of data obtained from each method, and flexibility in designing the survey, including incorporation of audio/video materials. The mall‐intercept interview and web surveys are recommended when the data are needed within a short period of time. Web surveys are also the least expensive method of collecting survey data. On the other hand, the face‐to‐face interview has been shown to generate the highest quality of data. Face‐to‐face interviews, followed by web surveys, are also very flexible in terms of adapting the data collection process to the special needs of the research project and the characteristics of survey respondents. Therefore, a researcher has to decide what is important in a given study regarding the four dimensions and choose a method that best meets the desired criteria of the research project.

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Abstract A researcher has the option of choosing a method from a menu of different methods of doing surveys: face‐to‐face interview at home or mall‐intercept interview, mail survey, online survey, and telephone survey. Each of these methods is characterized by distinct advantages and disadvantages. The major criteria used to evaluate these methods are response time in collecting data, cost of obtaining data per respondent, quality of data obtained from each method, and flexibility in designing the survey, including incorporation of audio/video materials. The mall‐intercept interview and web surveys are recommended when the data are needed within a short period of time. Web surveys are also the least expensive method of collecting survey data. On the other hand, the face‐to‐face interview has been shown to generate the highest quality of data. Face‐to‐face interviews, followed by web surveys, are also very flexible in terms of adapting the data collection process to the special needs of the research project and the characteristics of survey respondents. Therefore, a researcher has to decide what is important in a given study regarding the four dimensions and choose a method that best meets the desired criteria of the research project.

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Available abstract

Abstract A researcher has the option of choosing a method from a menu of different methods of doing surveys: face‐to‐face interview at home or mall‐intercept interview, mail survey, online survey, and telephone survey. Each of these methods is characterized by distinct advantages and disadvantages. The major criteria used to evaluate these methods are response time in collecting data, cost of obtaining data per respondent, quality of data obtained from each method, and flexibility in designing the survey, including incorporation of audio/video materials. The mall‐intercept interview and web surveys are recommended when the data are needed within a short period of time. Web surveys are also the least expensive method of collecting survey data. On the other hand, the face‐to‐face interview has been shown to generate the highest quality of data. Face‐to‐face interviews, followed by web surveys, are also very flexible in terms of adapting the data collection process to the special needs of the research project and the characteristics of survey respondents. Therefore, a researcher has to decide what is important in a given study regarding the four dimensions and choose a method that best meets the desired criteria of the research project.

Key concepts: Respondent, Survey methodology, Flexibility (engineering), Data collection, Computer science, Survey data collection, Quality (philosophy), Data quality

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