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Background Recent progress in genome data collection and analysis technologies has led to a surge of direct-to-consumer (DTC) genetic testing services. Owing to the clinical value and sensitivity of genomic data, as well as uncertainty and hearsay surrounding business practices of DTC genetic testing service providers, DTC genetic testing has faced significant criticism by researchers and practitioners. Research in this area has centered on ethical and legal implications of providing genetic tests directly to consumers, but we still lack a more profound understanding of how businesses in the DTC genetic testing markets work and provide value to different stakeholders. Objective The aim of this study was to address the lack of knowledge concerning business models of DTC genetic testing services by systematically identifying the salient properties of various DTC genetic testing service business models as well as discerning dominant business models in the market. Methods We employed a 3-phased research approach. In phase 1, we set up a database of 277 DTC genetic testing services. In phase 2, we drew on these data as well as conceptual models of DTC genetic testing services and iteratively developed a taxonomy of DTC genetic testing service business models. In phase 3, we used a 2-stage clustering method to cluster the 277 services that we identified during phase 1 and derived 6 dominant archetypes of DTC genetic testing service business models. Results The contributions of this research are 2-fold. First, we provided a first of its kind, systematically developed taxonomy of DTC genetic testing service business models consisting of 15 dimensions in 4 categories. Each dimension comprises 2 to 5 characteristics and captures relevant aspects of DTC genetic testing service business models. Second, we derived 6 archetypes of DTC genetic testing service business models named as follows: (1) low-cost DTC genomics for enthusiasts, (2) high-privacy DTC genomics for enthusiasts, (3) specific information tests, (4) simple health tests, (5) basic low-value DTC genomics, and (6) comprehensive tests and low data processing. Conclusions Our analysis paints a much more complex business landscape in the DTC genetic testing market than previously anticipated. This calls for further research on business models and their effects that underlie DTC genetic testing services and invites specific regulatory interventions to protect consumers and level the playing field.

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Although spam email messages have been the primary source of cybercrime since the early Internet era, there is no quick fix to this problem. Governments have established anti‐spam legislation, but surprisingly, there has been no measurement of policy impact. This study aims to fill the gap by utilizing a quasi‐experimental setting in South Korea, where the anti‐spam policy was substantially amended in November 2014. A significant change was in the default setting, switching from an opt‐out to an opt‐in scheme, which required that commercial email senders obtain recipients' prior consent. Also, the law notably escalated the deterrent penalties for perpetrators. To empirically examine the policy effectiveness, we use a large‐scale data set of 5.61 billion spam emails originating from over 38,000 spammers in 226 countries during twenty months in 2014–2015. Our findings suggest that the amended policy adopting the opt‐in scheme decreased the volume of spam originating from Korea by 16.1%. The expected economic gain from the increased productivity of recipients is 7.649 million USD per year. This study contributes to the literature by highlighting that a well‐designed policy can lower cybersecurity incidents that threaten organizations, operations, and individuals. Our finding also provides important implications for policymakers and managers in designing effective policies with data‐driven evidence.