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From Wikipedia, the free encyclopedia

1000minds
1000Minds Logo 2013 square.png
Developer(s)1000minds Ltd
Initial release2002 (2002)
Operating systemWeb application
Available inEnglish
TypeDecision-making software, Business intelligence, Conjoint analysis, Choice modelling
LicenseProprietary; usually free for academic researchers and students
Websitewww.1000minds.com

1000minds is a web application for decision-making and conjoint analysis supplied by 1000minds Ltd since 2002.[1][2][3][4][5]

1000minds implements the PAPRIKA method to help business, government and non-profit users to make decisions based on considering multiple objectives or criteria (i.e., multi-criteria decision making). 1000minds conjoint analysis involves surveying people about their preferences with respect to the relative importance of features or attributes characterizing products or other objects of interest.

In addition, a free consumer-oriented web application based on 1000minds technology to help with ‘everyday’ decision-making, known as MeenyMo, was released in 2016.[2][6]

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Transcription

Contents

Overview

1000minds helps with decisions that involve ranking, prioritizing or choosing between alternatives when multiple objectives or criteria need to be considered simultaneously (i.e., multi-criteria decision making). Depending on the application, budgets or other scarce resources can also be allocated across competing alternatives in pursuit of maximum 'value for money'.[1][2][3]

The PAPRIKA method is used to determine the relative importance of criteria or attributes and rank alternatives.[7] Invented by Franz Ombler and Paul Hansen at the University of Otago,[8] the PAPRIKA method is based on pairwise comparisons, as illustrated in the accompanying image.

Example of a 1000minds pairwise comparison
Example of a 1000minds pairwise comparison

1000minds is also for group decision-making, involving potentially 100s or 1000s of participants – working together or individually with their results aggregated.

1000minds conjoint analysis surveys are for discovering consumers’ or other stakeholders’ preferences with respect to the relative importance – represented by ‘part-worth utilities’ or ‘weights’ – of the features or attributes characterizing products or other objects of interest (i.e., choice modelling, conjoint analysis and discrete choice).[4][5]

Applications

As well as business, government and non-profit organizations, as evidenced by the citations below, 1000minds is used for research at over 180 universities worldwide, including for teaching.[9] 1000minds (originally branded as Point Wizard) and several of its applications have won or been a finalist for a number of innovation awards.[10][11][12][13][14]

Areas in which 1000minds is used include the following notable examples.

Health

Environment

Urban planning and waste management

Breeding

Policy-making research

Management and accounting

Information and communication technology (ICT)

Miscellaneous

References

  1. ^ a b Weistroffer, H. Roland; Li, Yan (2016). Multiple Criteria Decision Analysis Software. Multiple Criteria Decision Analysis. International Series in Operations Research & Management Science. 233. Springer, New York, NY. pp. 1301–1341. doi:10.1007/978-1-4939-3094-4_29. ISBN 978-1-4939-3093-7.
  2. ^ a b c Oleson, S. (2016), "Decision analysis software survey", OR/MS Today, 43 (5)
  3. ^ a b Amoyal, J. (2018), "Decision analysis software survey", OR/MS Today, 45 (5)
  4. ^ a b c Smith, K. F.; Fennessy, P. F. (2011). "The use of conjoint analysis to determine the relative importance of specific traits as selection criteria for the improvement of perennial pasture species in Australia". Crop and Pasture Science. 62 (4): 355–65. doi:10.1071/CP10320.
  5. ^ a b c Isma', Salim Al; ili, N.A.; Li, Mengxiang; Shen, Jun; He, Qiang (2016). "Cloud computing adoption decision modelling for SMEs: a conjoint analysis". International Journal of Web and Grid Services. 12 (3): 296. doi:10.1504/ijwgs.2016.079157.
  6. ^ Fielding, D.; Hansen, P., eds. (August 2016). "Better decision-making!". EcoNZ (37): 7.
  7. ^ Hansen, P.; Ombler, F. (2008). "A new method for scoring additive multi-attribute value models using pairwise rankings of alternatives". Journal of Multi-Criteria Decision Analysis. 15 (3–4): 87–107. doi:10.1002/mcda.428.
  8. ^ Scott, L. (April 2008), "Minds over Matter", North and South, pp. 28–29
  9. ^ "Universities – 1000Minds". 1000Minds. Retrieved 10 July 2017.
  10. ^ "Dunedin's 1000Minds wins award in Sydney". The National Business Review. 2 May 2007. Archived from the original on 2017-11-10. Retrieved 10 July 2017.
  11. ^ "1000Minds". consensus.com.au. Retrieved 10 July 2017.
  12. ^ "TUANZ announces Innovation Awards finalists". Computerworld New Zealand. Retrieved 10 July 2017.
  13. ^ Day, Stacey. "Valid, transparent and fair decision-making processes for access to elective health care • Health Improvement and Innovation Resource Centre". www.hiirc.org.nz. Retrieved 10 July 2017.
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