Models for predicting perception of an item of interest

A method utilizing a two-step moving scale survey to create a predictive model, the method comprising:

• creating a two-step moving scale survey capable of being utilized to collect quantitative survey data about an item of interest;
• performing the two-step moving scale survey to collect the quantitative survey data about the item of interest;
• determining at least one related measurable property that is associated with the item of interest;
• measuring the at least one related measurable property that is associated with the item of interest;
• relating the quantitative survey data about the item of interest obtained from the two-step moving scale survey to the measurement of the at least one related measurable property;
• and
• creating a model to predict the results of the two-step moving scale survey.

A two-step moving scale survey system capable of allowing response bias and measurement error in surveys to be evaluated, the system comprising:

• a means for creating a two-step moving scale survey capable of being utilized to collect quantitative survey data about an item of interest;
• a means for performing the two-step moving scale survey to collect the quantitative survey data about the item of interest;
• a means for determining at least one related measurable properties that is associated with the item of interest;
• a means for measuring the at least one related measurable property that is associated with the item of interest relating the results of the performed two-step moving scale survey to at least one predetermined measurable related property;
• a means for relating the quantitative survey data about the item of interest obtained from the two-step moving scale survey to the measurement of the at least one related measurable property;
• and
• a means for creating a model to predict the results of the two-step moving scale survey.

A method for predicting human perception of an item of interest, the method comprising:

• determining a relationship between perceived properties of the item of interest and predetermined measurable properties associated with the item of interest;
• creating a model that defines the relationship between the perceived properties of the item of interest and the predetermined measurable properties associated with the item of interest;
• measuring the predetermined measurable properties associated with the item of interest;
• and
• utilizing the model and the measurements of the predetermined measurable properties associated with the item of interest to predict the human perception of the item of interest.

A method for predicting human perception of one or more scratches on an automotive component, the method comprising:

• determining a relationship between physical scratch properties and measurable optical properties associated with the scratches;
• creating a model that defines the relationship between the physical scratch properties and the measurable optical properties associated with the scratches;
• measuring the measurable optical properties associated with the scratches;
• utilizing the model and the measurements of the measurable optical properties to predict the human perception of the scratches.

A method of predicting human perception of an item of interest, the method comprising:

• defining an item of interest that requires predicting human perception thereof;
• identifying a model capable of predicting the human perception of the item of interest;
• measuring predetermined measurable properties associated with the human perception of the item of interest;
• entering the measurements of the predetermined measurable properties into the model;
• and
• allowing the model to predict the human perception of the item of interest.