Simalto

It can be applied to predicting which of the alternative combinations of optional service benefits provided by a local authority,[1] state or national government in their annual budget would meet with the ‘maximum’ approval of a target population.

[citation needed] This staged prioritization of options was first developed by John Green while he was the international market research manager at Xerox in London in the mid-1970s.

A simpler questionnaire, where the respondent only allocated a single total budget across many of the various matrix options available, to build his ‘personal specification’, was used by Ford Motor Company in Detroit in the late 1940s.

More recently this single stage budget allocation approach has been used by many manufacturers on their web-sites to collect a given respondents preferred specification having been shown the costs of different options.

The algorithms required for the modelling predictions of SIMALTO data enabling potential market share calculations and needs-based analysis were first created in the early 1980s, with major improvements and extended capabilities introduced in 2000.

The questionnaire can be presented by an interviewer face-to-face with the respondent, or in a ‘focus-group’ situation where all participants individually completed the various SIMALTO stages under the guidance of a single moderator.

[citation needed] The limit on the number of attributes is not constrained by mathematical issues, but rather dictated by common sense of what a respondent can sensibly deal with in a particular product field and in a reasonable time period.

This disadvantage means that 20 is a realistic maximum attribute number on the web, unless respondents are sufficiently motivated (by product interest and/or incentives) to spend longer than 20 minutes completing the questionnaire.

The method most frequently used is based on expert system rules linked to neural net logic and genetic algorithm theory.