Comparing mental models of prospective users of the sustainable nanotechnology decision support system
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Mental modelling analysis can be a valuable tool in understanding and bridging cognitive values in multi-stakeholders’ communities. It is especially true in situation of emerging risks where significant uncertainty and competing objectives could result in significant difference in stakeholder perspective on the use of new materials and technologies. This paper presents a mental modelling study performed among prospective users of an innovative decision support system for safe and sustainable development of nano-enabled products. These users included representatives of industry and regulators, as well as several insurance specialists and researchers. We present methodology and tools for comparing stakeholder views and objectives in the context of developing a decision support system.
KeywordsNanomaterials Decision support Mental model Industry Regulators
We gratefully acknowledge the contributions of the participants during the stakeholder engagement activities reported here, and the constructive comments of two anonymous reviewers. The research leading to these results has received funding from the European Union Seventh Framework Programme [FP7/2007–2013] under EC-GA No. 604305 ‘SUN’. This publication reflects the views only of the authors, and the European Commission cannot be held responsible for any use, which may be made of the information contained therein.
Compliance with ethical standards
Human and animals rights
We have not performed any experiments on humans and/or animals for which prior approval of an ethics board or similar body is required.
Informed consent was obtained from all individual participants included in the study. All respondents have been offered the option to respond anonymously. All published results are presented in anonymised form.
- Malsch I, Subramanian V, Semenzin E, Hristozov D, Marcomini A (2015c) Collective decision making on risk management and sustainable manufacturing of nanomaterials and the role of decision support tools. In: Proceedings of the 5th STS Italia conference: a matter of design: making society through science and technology, pp 1115–1130Google Scholar
- Morgan MG, Fischhoff B, Bostrom A, Atman CJ (2002) Risk communication: a mental models approach. Cambridge University Press, BostonGoogle Scholar
- Nersessian NJ, Newstetter WC, Kurz-Milcke E, Davies JA (2003) Mixed-method approach to studying distributed cognition in evolving environments. In: Paper presented at the proceedings of the international conference on learning sciences, pp 307–314Google Scholar
- Subramanian V, Semenzin E, Hristozov D, Zabeo A, Malsch I, McAlea E, Murphy F, Mullins M, van Harmelen T, Ligthart T, Linkov I, Marcomini A (2016) Sustainable nanotechnology decision support system: bridging risk management, sustainable innovation and risk governance. J Nanopart Res 18:89. doi: 10.1007/s11051-016-3375-4 CrossRefGoogle Scholar
- van Harmelen T, Zondervan-van den Beuken EK, Brouwer DH, Kuijpers E, Fransman W, Buist HB, Ligthart TN, Hincapié I, Hischier R, Linkov I, Nowack B, Studer J, Hilty L, Som C (2016) LICARA nanoSCAN—a tool for the self-assessment of benefits and risks of nanoproducts. Environ Int 91:150–160. doi: 10.1016/j.envint.2016.02.021 (Epub 2016 Mar 5) CrossRefGoogle Scholar
- Wood MD, Thorne S, Kovacs D, Butte G, Linkov I (2017) Mental modelling approach risk management application case studies. Risk systems and decisions. Springer, New YorkGoogle Scholar