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Crowdsourcing has emerged as a preferred data collection methodology for advertising and social science researchers because these samples avoid the higher costs associated with professional panel data. Yet, there are ongoing concerns about data quality for online sources. This research examines differences in data quality for an advertising experiment across five popular online data sources, including professional panels and crowdsourced platforms. Effects of underlying mechanisms impacting data quality, including response satisficing, multitasking, and effort, are examined. As proposed, a serial mediation model shows that data source is, directly and indirectly, related to these antecedents of data quality. Satisficing is positively related to multitasking and negatively related to effort, and both mediators (in parallel) extend to data quality, indicating that the indirect effects on data quality through these mediating variables are significant. In general, a vetted MTurk sample (i.e., CloudResearch Approved) produces higher quality data than the other four sources. Regardless of the data source, researchers should utilize safeguards to ensure data quality. Safeguards and other strategies to obtain high-quality data from online samples are offered. [ABSTRACT FROM AUTHOR]

Public policy is part of the fabric of advertising with respect to both research and practice. The strong relationship between advertising and public policy has important implications for consumers, businesses, and federal and state agencies. Advertising laws and regulations can influence business practices just as advertising research can impact regulatory decisions. The purpose of this article is to highlight research at the intersection of advertising and public policy and then to identify specific future research needs that have the potential to contribute significantly to advertising research and practice. [ABSTRACT FROM AUTHOR]