Modeling stakeholder preferences with probabilistic inversion

Rabin Neslo; Fiorenza Micheli; Carrie V Kappel; Kimberly A Selkoe; Benjamin S Halpern; Roger M Cooke

doi:10.1007/978-1-4020-9026-4_17

Modeling stakeholder preferences with probabilistic inversion

Rabin Neslo, Fiorenza Micheli, Carrie V Kappel, Kimberly A Selkoe, Benjamin S Halpern, Roger M Cooke

Management Science

Research output: Chapter in Book/Report/Conference proceeding › Other chapter contribution

Abstract

A panel of 64 experts ranked 30 scenarios of human activities according to their impacts on coastal ecosystems. Experts were asked to rank the five scenarios posing the greatest threats and the five scenarios posing the least threats. The goal of this study was to find weights for criteria that adequately model these stakeholders’ preferences and can be used to predict the scores of other scenarios. Probabilistic inversion (PI) techniques were used to quantify a model of ecosystem vulnerability based on five criteria. Distinctive features of this approach are:
1. A model of the stakeholder population as a joint distribution over the criteria weights is obtained. This distribution is found by minimizing relative information with respect to a noninformative starting distribution, but makes no further assumptions about the interactions between the weights for different criteria. Criteria distributions with dependence emerge from the fitting procedure.
2. The multicriteria preference model can be empirically validated with expert preferences not used in fitting the model.

Original language	English
Title of host publication	Real-Time and Deliberative Decision Making
Subtitle of host publication	Application to Emerging Stressors
Editors	Igor Linkov, Elizabeth Ferguson, Victor S. Magar
Publisher	Springer
Pages	265-284
Number of pages	20
ISBN (Print)	9781402090257
DOIs	https://doi.org/10.1007/978-1-4020-9026-4_17
Publication status	Published - 2009

Publication series

Name	NATO Science for Peace and Security Series C: Environmental Security
Publisher	Springer

Keywords

probabilistic inversion
environmental economics
environmental management
environmental risk

Access to Document

10.1007/978-1-4020-9026-4_17

Cite this

Neslo, R., Micheli, F., Kappel, C. V., Selkoe, K. A., Halpern, B. S., & Cooke, R. M. (2009). Modeling stakeholder preferences with probabilistic inversion. In I. Linkov, E. Ferguson, & V. S. Magar (Eds.), Real-Time and Deliberative Decision Making: Application to Emerging Stressors (pp. 265-284). (NATO Science for Peace and Security Series C: Environmental Security). Springer. https://doi.org/10.1007/978-1-4020-9026-4_17

@inbook{d1e2c46ee3d54e45960413023a0868cc,

title = "Modeling stakeholder preferences with probabilistic inversion",

abstract = "A panel of 64 experts ranked 30 scenarios of human activities according to their impacts on coastal ecosystems. Experts were asked to rank the five scenarios posing the greatest threats and the five scenarios posing the least threats. The goal of this study was to find weights for criteria that adequately model these stakeholders{\textquoteright} preferences and can be used to predict the scores of other scenarios. Probabilistic inversion (PI) techniques were used to quantify a model of ecosystem vulnerability based on five criteria. Distinctive features of this approach are:1. A model of the stakeholder population as a joint distribution over the criteria weights is obtained. This distribution is found by minimizing relative information with respect to a noninformative starting distribution, but makes no further assumptions about the interactions between the weights for different criteria. Criteria distributions with dependence emerge from the fitting procedure.2. The multicriteria preference model can be empirically validated with expert preferences not used in fitting the model.",

keywords = "probabilistic inversion, environmental economics, environmental management, environmental risk",

author = "Rabin Neslo and Fiorenza Micheli and Kappel, {Carrie V} and Selkoe, {Kimberly A} and Halpern, {Benjamin S} and Cooke, {Roger M}",

year = "2009",

doi = "10.1007/978-1-4020-9026-4_17",

language = "English",

isbn = "9781402090257",

series = "NATO Science for Peace and Security Series C: Environmental Security",

publisher = "Springer",

pages = "265--284",

editor = "Igor Linkov and Elizabeth Ferguson and Magar, {Victor S.}",

booktitle = "Real-Time and Deliberative Decision Making",

}

Neslo, R, Micheli, F, Kappel, CV, Selkoe, KA, Halpern, BS & Cooke, RM 2009, Modeling stakeholder preferences with probabilistic inversion. in I Linkov, E Ferguson & VS Magar (eds), Real-Time and Deliberative Decision Making: Application to Emerging Stressors. NATO Science for Peace and Security Series C: Environmental Security, Springer, pp. 265-284. https://doi.org/10.1007/978-1-4020-9026-4_17

Modeling stakeholder preferences with probabilistic inversion. / Neslo, Rabin; Micheli, Fiorenza; Kappel, Carrie V et al.
Real-Time and Deliberative Decision Making: Application to Emerging Stressors. ed. / Igor Linkov; Elizabeth Ferguson; Victor S. Magar. Springer, 2009. p. 265-284 (NATO Science for Peace and Security Series C: Environmental Security).

Research output: Chapter in Book/Report/Conference proceeding › Other chapter contribution

TY - CHAP

T1 - Modeling stakeholder preferences with probabilistic inversion

AU - Neslo, Rabin

AU - Micheli, Fiorenza

AU - Kappel, Carrie V

AU - Selkoe, Kimberly A

AU - Halpern, Benjamin S

AU - Cooke, Roger M

PY - 2009

Y1 - 2009

N2 - A panel of 64 experts ranked 30 scenarios of human activities according to their impacts on coastal ecosystems. Experts were asked to rank the five scenarios posing the greatest threats and the five scenarios posing the least threats. The goal of this study was to find weights for criteria that adequately model these stakeholders’ preferences and can be used to predict the scores of other scenarios. Probabilistic inversion (PI) techniques were used to quantify a model of ecosystem vulnerability based on five criteria. Distinctive features of this approach are:1. A model of the stakeholder population as a joint distribution over the criteria weights is obtained. This distribution is found by minimizing relative information with respect to a noninformative starting distribution, but makes no further assumptions about the interactions between the weights for different criteria. Criteria distributions with dependence emerge from the fitting procedure.2. The multicriteria preference model can be empirically validated with expert preferences not used in fitting the model.

AB - A panel of 64 experts ranked 30 scenarios of human activities according to their impacts on coastal ecosystems. Experts were asked to rank the five scenarios posing the greatest threats and the five scenarios posing the least threats. The goal of this study was to find weights for criteria that adequately model these stakeholders’ preferences and can be used to predict the scores of other scenarios. Probabilistic inversion (PI) techniques were used to quantify a model of ecosystem vulnerability based on five criteria. Distinctive features of this approach are:1. A model of the stakeholder population as a joint distribution over the criteria weights is obtained. This distribution is found by minimizing relative information with respect to a noninformative starting distribution, but makes no further assumptions about the interactions between the weights for different criteria. Criteria distributions with dependence emerge from the fitting procedure.2. The multicriteria preference model can be empirically validated with expert preferences not used in fitting the model.

KW - probabilistic inversion

KW - environmental economics

KW - environmental management

KW - environmental risk

U2 - 10.1007/978-1-4020-9026-4_17

DO - 10.1007/978-1-4020-9026-4_17

M3 - Other chapter contribution

SN - 9781402090257

T3 - NATO Science for Peace and Security Series C: Environmental Security

SP - 265

EP - 284

BT - Real-Time and Deliberative Decision Making

A2 - Linkov, Igor

A2 - Ferguson, Elizabeth

A2 - Magar, Victor S.

PB - Springer

ER -

Neslo R, Micheli F, Kappel CV, Selkoe KA, Halpern BS, Cooke RM. Modeling stakeholder preferences with probabilistic inversion. In Linkov I, Ferguson E, Magar VS, editors, Real-Time and Deliberative Decision Making: Application to Emerging Stressors. Springer. 2009. p. 265-284. (NATO Science for Peace and Security Series C: Environmental Security). doi: 10.1007/978-1-4020-9026-4_17

Modeling stakeholder preferences with probabilistic inversion

Abstract

Publication series

Keywords

Access to Document

Fingerprint

Cite this