Academic discipline and risk perception of technologies: An empirical study
This article brings together two areas of research: studies on risk perception of technologies and studies on vocational/career choice. This is an important link since decisions concerning technologies are influenced by decision makers' risk perceptions and these in turn may be related to educational and career paths. We analyze students of different academic disciplines with regard to their risk perception of four technologies. The aim is to find out whether there is a relationship between area of study (as a precursor of vocational and career choice) and risk perception of technologies regarding health, environment and society. The four technologies under study are renewable energies, genetic engineering, nanotechnology and information and communication technologies (ICT). Key results are: irrespective of academic discipline risk of genetic engineering on average is rated highest and renewable energies lowest. This holds for all the risks studied (environmental, health, societal risks). On average, students from different academic disciplines differ in their risk perception. Factor analyses show that common dimensions of risk are the technologies and not the kind of risk. Regression analyses show that the variables influencing perceived risks vary between the technological fields.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Alba, Joseph W & Hutchinson, J Wesley, 2000. " Knowledge Calibration: What Consumers Know and What They Think They Know," Journal of Consumer Research, Oxford University Press, vol. 27(2), pages 123-56, September.
- John H. Roberts & Glen L. Urban, 1988. "Modeling Multiattribute Utility, Risk, and Belief Dynamics for New Consumer Durable Brand Choice," Management Science, INFORMS, vol. 34(2), pages 167-185, February.
- Kim, Jerry W. & Higgins, Monica C., 2007. "Where do alliances come from?: The effects of upper echelons on alliance formation," Research Policy, Elsevier, vol. 36(4), pages 499-514, May.
- Mark Elchardus & Bram Spruyt, 2009. "The Culture of Academic Disciplines and the Sociopolitical Attitudes of Students: A Test of Selection and Socialization Effects," Social Science Quarterly, Southwestern Social Science Association, vol. 90(2), pages 446-460.
- Rabik Ar Chatterjee & Jehoshua Eliashberg, 1990. "The Innovation Diffusion Process in a Heterogeneous Population: A Micromodeling Approach," Management Science, INFORMS, vol. 36(9), pages 1057-1079, September.
When requesting a correction, please mention this item's handle: RePEc:eee:respol:v:40:y:2011:i:3:p:487-499. 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: (Shamier, Wendy)
If references are entirely missing, you can add them using this form.