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Citation |
Yates D, Speer J. Int. J. Drug Policy 2018; 59: 63-66. |
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Affiliation |
University of Denver, Business Information & Analytics, 2101 S. University Blvd Suite 580, Denver, CO 80208 United States. Electronic address: Jessica_speer@hotmail.com. |
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Copyright |
(Copyright © 2018, Elsevier Publishing) |
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DOI |
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PMID |
30015248 |
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Abstract |
With the State of California legalizing recreational cannabis sales on January 1, 2018, the regulatory process is once more in the forefront of cannabis research. Colorado, often held up as a model of legalization policy, was the first state to implement retail sale of recreational cannabis on January 1st, 2014. However, a combination of subsequent under-regulation and over-regulation, inconsistently applied across issues such as retail licencing, chemical testing, cannabis derivatives, municipality approval for growers, and financing, have not only held back the industry in Colorado but also negatively impacted public health, oversight, and have potentially increased the availability of illegal cannabis. We argue that a data-analytic approach to the industry is potentially the most effective way to resolve these concerns, since in the absence of consistent and reliable data, policymakers are apt to satisfy individual policy concerns without considering the industry as a whole. In this paper we present a data-analytic framework for the cannabis industry, offering a theoretically-driven justification for our approach, and describe implications for research on drug and information policy. The framework may serve as a model for other states or countries contemplating cannabis legalisation. As four new states legalised recreational cannabis in 2016, the implications of this research for policymakers has dramatically increased. Language: en |
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Keywords |
Cannabis; Colorado; Data analytics; Marijuana; Policy; Regulation; TOE framework; Testing |