Data

Erik Mooi, Marko Sarstedt and Irma Mooi-Reci
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Erik Mooi: University of Melbourne
Marko Sarstedt: Otto-von-Guericke-University
Irma Mooi-Reci: University of Melbourne

Chapter 3 in Market Research, 2018, pp 27-50 from Springer

Abstract: Abstract In market research, data is critical. Testing, measuring, improving, or creating new goods and services are difficult, or even impossible, without product and customer data. We discuss the different types of data, how they are constructed, and their attributes. We subsequently discuss the advantages and disadvantages of primary and secondary data and what each type allows you to do. We show you how to assess data’s validity and reliability, and discuss the implications that measurement errors can have for your data’s quality. We conclude with a discussion of important concepts, such as population, probability and non-probability sampling, and the relevance of sample size for market research.

Keywords: Armstrong and Overton procedure; Case; Census; Constant; Construct; Construct validity; Content validity; Criterion validity; Dependence of observations; Discriminant validity; Equidistance; Face validity; Formative constructs; Index; Index construction; Internal consistency reliability; Inter-rater reliability; Items; Latent concept; Latent variable; Measurement scaling; Multi-item constructs; Net Promoter Score (NPS); Nomological validity; Non-probability sampling; Observation; Operationalization; Population; Predictive validity; Primary data; Probability sampling; Qualitative data; Quantitative data; Reflective constructs; Reliability; Sample size; Sampling; Sampling error; Scale development; Secondary data; Single-item constructs; Test-retest reliability; Unit of analysis; Validity; Variable (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sptchp:978-981-10-5218-7_3

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DOI: 10.1007/978-981-10-5218-7_3

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