数据收集
概念化
数据质量
质量(理念)
市场调研
营销
过程(计算)
数据科学
业务
计算机科学
社会学
服务(商务)
人工智能
哲学
操作系统
认识论
社会科学
作者
Zachary Moore,Dana E. Harrison,Joe F. Hair
标识
DOI:10.1177/14707853211052183
摘要
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.
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