IDEAS home Printed from https://ideas.repec.org/p/oxf/wpaper/830.html
   My bibliography  Save this paper

On the Motivations for the Dual-Use of Electronic and Traditional Cigarettes

Author

Abstract

We apply a classical economic categorization of preferences to identify the motivations of dual-users of electronic and traditional cigarettes. The responses of 2,406 U.S. adults (including 413 dual-users) in 2015 were collected using a novel online survey along with a follow-up in 2016 of 143 of these adults (68 dual-users). A sizeable minority of 37% of dual-users reported viewing electronic and conventional cigarettes primarily as complements. Of those who had never smoked or used electronic cigarettes, only 27% thought the complementarity motive would be primary. Dual-user motivations were associated with quit-attempt, cessation methods, gender and age. One year on, there was a positive relationship between the level of complementarity in the dual-user’s motives and their change in self-reported cigarette consumption. It is concluded that the application of a canonical economic classification of preferences may reveal important heterogeneities among the dual-user population.

Suggested Citation

  • Daniel Sgroi, 2017. "On the Motivations for the Dual-Use of Electronic and Traditional Cigarettes," Economics Series Working Papers 830, University of Oxford, Department of Economics.
  • Handle: RePEc:oxf:wpaper:830
    as

    Download full text from publisher

    File URL: https://ora.ox.ac.uk/objects/uuid:c9dcdf58-ca0f-4d6e-8f3d-967d7adf6b71
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. John Horton & David Rand & Richard Zeckhauser, 2011. "The online laboratory: conducting experiments in a real labor market," Experimental Economics, Springer;Economic Science Association, vol. 14(3), pages 399-425, September.
    2. Steve Berry & Ahmed Khwaja & Vineet Kumar & Andres Musalem & Kenneth Wilbur & Greg Allenby & Bharat Anand & Pradeep Chintagunta & W. Hanemann & Przemek Jeziorski & Angelo Mele, 2014. "Structural models of complementary choices," Marketing Letters, Springer, vol. 25(3), pages 245-256, September.
    3. Ilyana Kuziemko & Michael I. Norton & Emmanuel Saez & Stefanie Stantcheva, 2015. "How Elastic Are Preferences for Redistribution? Evidence from Randomized Survey Experiments," American Economic Review, American Economic Association, vol. 105(4), pages 1478-1508, April.
    4. Neil Stewart & Christoph Ungemach & Adam J. L. Harris & Daniel M. Bartels & Ben R. Newell & Gabriele Paolacci & Jesse Chandler, "undated". "The Average Laboratory Samples a Population of 7,300 Amazon Mechanical Turk Workers," Mathematica Policy Research Reports f97b669c7b3e4c2ab95c9f805, Mathematica Policy Research.
    5. Neil Stewart & Christoph Ungemach & Adam J. L. Harris & Daniel M. Bartels & Ben R. Newell & Gabriele Paolacci & Jesse Chandler, 2015. "The average laboratory samples a population of 7,300 Amazon Mechanical Turk workers," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 10(5), pages 479-491, September.
    6. Gabriele Paolacci & Jesse Chandler & Panagiotis G. Ipeirotis, 2010. "Running experiments on Amazon Mechanical Turk," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 5(5), pages 411-419, August.
    7. Berinsky, Adam J. & Huber, Gregory A. & Lenz, Gabriel S., 2012. "Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk," Political Analysis, Cambridge University Press, vol. 20(3), pages 351-368, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Antonio A. Arechar & Simon Gächter & Lucas Molleman, 2018. "Conducting interactive experiments online," Experimental Economics, Springer;Economic Science Association, vol. 21(1), pages 99-131, March.
    2. Christ, Margaret H. & Vance, Thomas W., 2018. "Cascading controls: The effects of managers’ incentives on subordinate effort to help or harm," Accounting, Organizations and Society, Elsevier, vol. 65(C), pages 20-32.
    3. Capraro, Valerio & Schulz, Jonathan & Rand, David G., 2019. "Time pressure and honesty in a deception game," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 79(C), pages 93-99.
    4. Lefgren, Lars J. & Sims, David P. & Stoddard, Olga B., 2016. "Effort, luck, and voting for redistribution," Journal of Public Economics, Elsevier, vol. 143(C), pages 89-97.
    5. Cherry, Todd L. & McEvoy, David M. & Westskog, Hege, 2019. "Cultural worldviews, institutional rules and the willingness to participate in green energy programs," Resource and Energy Economics, Elsevier, vol. 56(C), pages 28-38.
    6. Rebecca R Carter & Analisa DiFeo & Kath Bogie & Guo-Qiang Zhang & Jiayang Sun, 2014. "Crowdsourcing Awareness: Exploration of the Ovarian Cancer Knowledge Gap through Amazon Mechanical Turk," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-10, January.
    7. Brañas-Garza, Pablo & Capraro, Valerio & Rascón-Ramírez, Ericka, 2018. "Gender differences in altruism on Mechanical Turk: Expectations and actual behaviour," Economics Letters, Elsevier, vol. 170(C), pages 19-23.
    8. Masha Shunko & Julie Niederhoff & Yaroslav Rosokha, 2018. "Humans Are Not Machines: The Behavioral Impact of Queueing Design on Service Time," Management Science, INFORMS, vol. 64(1), pages 453-473, January.
    9. Atalay, Kadir & Bakhtiar, Fayzan & Cheung, Stephen & Slonim, Robert, 2014. "Savings and prize-linked savings accounts," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 86-106.
    10. Cantarella, Michele & Strozzi, Chiara, 2019. "Workers in the Crowd: The Labour Market Impact of the Online Platform Economy," IZA Discussion Papers 12327, Institute of Labor Economics (IZA).
    11. Azzam, Tarek & Harman, Elena, 2016. "Crowdsourcing for quantifying transcripts: An exploratory study," Evaluation and Program Planning, Elsevier, vol. 54(C), pages 63-73.
    12. Keela S. Thomson & Daniel M. Oppenheimer, 2016. "Investigating an alternate form of the cognitive reflection test," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 11(1), pages 99-113, January.
    13. Chirvi, Malte & Schneider, Cornelius, 2020. "Preferences for wealth taxation: Design, framing and the role of partisanship," arqus Discussion Papers in Quantitative Tax Research 260, arqus - Arbeitskreis Quantitative Steuerlehre.
    14. Hannah Van Borm & Ian Burn & Stijn Baert, 2019. "What Does a Job Candidate’s Age Signal to Employers?," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 19/984, Ghent University, Faculty of Economics and Business Administration.
    15. Joseph A. Johnson & Jochen Theis & Adam Vitalis & Donald Young, 2020. "The Influence of Firms' Emissions Management Strategy Disclosures on Investors' Valuation Judgments†," Contemporary Accounting Research, John Wiley & Sons, vol. 37(2), pages 642-664, June.
    16. Gandullia, Luca & Lezzi, Emanuela & Parciasepe, Paolo, 2020. "Replication with MTurk of the experimental design by Gangadharan, Grossman, Jones & Leister (2018): Charitable giving across donor types," Journal of Economic Psychology, Elsevier, vol. 78(C).
    17. Tella, Rafael Di & Rotemberg, Julio J., 2018. "Populism and the return of the “Paranoid Style”: Some evidence and a simple model of demand for incompetence as insurance against elite betrayal," Journal of Comparative Economics, Elsevier, vol. 46(4), pages 988-1005.
    18. David J. Freeman & Guy Mayraz, 2019. "Why choice lists increase risk taking," Experimental Economics, Springer;Economic Science Association, vol. 22(1), pages 131-154, March.
    19. Tim Straub & Henner Gimpel & Florian Teschner & Christof Weinhardt, 2015. "How (not) to Incent Crowd Workers," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 57(3), pages 167-179, June.
    20. David Johnson & John Barry Ryan, 2020. "Amazon Mechanical Turk workers can provide consistent and economically meaningful data," Southern Economic Journal, John Wiley & Sons, vol. 87(1), pages 369-385, July.

    More about this item

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:oxf:wpaper:830. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Anne Pouliquen) The email address of this maintainer does not seem to be valid anymore. Please ask Anne Pouliquen to update the entry or send us the correct email address. General contact details of provider: http://edirc.repec.org/data/sfeixuk.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.