Data Quality Assurance Begins Before Data Collection and Never Ends: What Marketing Researchers Absolutely Need to Remember. (November 2021)

• Record Type: Journal Article
• Authors: Moore, Zachary; Harrison, Dana E.; Hair, Joe
• Other Names: Kostyk Alena guest-editor.; Zhou Wenkai guest-editor.; Hyman Michael R. guest-editor.; Paas Leo guest-editor.
• Is Part Of: International journal of market research. Volume 63:Number 6(2021)
• Page Start: 693
• Page End: 714
• Publication Date: 2021-11
• Subjects: self-administered questionnaires -- data quality -- survey design -- research methods -- marketing research -- sampling -- statistical analysis -- structural equation modeling -- research design -- survey research -- big data -- data analytics -- secondary data; Marketing research -- Periodicals; 658.8305
• DOI: 10.1177/14707853211052183
• Languages: English
• ISSNs: 1470-7853

Abstract

Data quality has become an area of increasing concern in marketing research. Methods of collecting data, types of data analyzed, and data analytics techniques have changed substantially in recent years. It is important, therefore, to examine the current state of marketing research, and particularly self-administered questionnaires. This paper provides researchers important advice and rules of thumb for crafting high quality research in light of the contemporary changes occuring in modern marketing data collection practices. This is accomplished by a proposed six-step research design process that ensures data quality, and ultimately research integrity, are established and maintained throughout the research process—from the earliest conceptualization and design phases, through data collection, and ultimately the reporting of results. This paper provides a framework, which if followed, will result in reduced headaches for researchers and more robust results for decision makers.