Weighing it up

Your results based on your preferences

We've crunched the numbers and scored the boat paints according to the preferences you just entered. The bar chart shows your product scores. Hover over the bars to see the drivers that most influenced the result for you.

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Now have a look at how your results compare to what our other users prefer:

Your perspective
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Find the product that's right for you

Multi-criteria decision analysis

This page helps you decide on the right type of antifouling hull paint for your boat. That may be easy to do if you're only looking at price and effectiveness.

Our comparison tool is based on the results of a study commissioned by the State of Washington (read more about it here). This Alternatives Assessment does not make a recommendation what product to use - but once we know what's important to you, we can help you with that.

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Full product info

Product Performance

Normalized criteria utility scores (more = better)

Comparisons can get messy when you also factor the paints' various environmental effects into your decision. Just look at the product preferences for some example users.

View other users' preferences

Sustainability, compliance, cost & growth at Makersite

At Makersite, we are building the platform that connects teams with the data, apps, and expertise they need to make, buy and sell great products. Launched in 2016, Makersite is already the largest database on the web on how products are made and used, their supply chains, risks, and eco-impacts. Teams around the world use Makersite to innovate, become sustainable, and learn from each other along the way.

We have launched this website (productview.info) as a spin-off to showcase the power of the Makersite platform for customers. This page uses Makersite data and Makersite's multi-criteria decision analysis tool which enables the comparison of arbitrary products across multiple dimensions. Sign up for free and try it out yourself at global.makersite.app!

All rights reserved for productview.info @ Makersite

Our method

Multi-criteria decision analysis with pairwise criteria preference inference.

The boat paint comparison presented here is a decision problem in 7 dimensions (the criteria Price, Performance, Human Hazard, Biocide Exposure, Environment, Boatyard CoCs, and VOC Exposure). The model we use is a linear utility aggregation model.

To understand the model, have a look at its 3 main parts:

  1. For each dimension, each product's data is converted to a utility score between 0 and 100 (100 being the best).
  2. The user makes pairwise comparisons of the dimensions. The pairwise information is used to compute weights for each of the dimensions (the higher the weight, the more relevant the dimension).
  3. For each product, the product utilities are summed up across the 7 dimensions, weighted by the dimensional weights computed in the previous step.

This leads to the products' final utility scores (out of 100) that are displayed in the bar chart on the results page. Here are the details of the three steps above:

Utilities.

Except for the performance dimension, the smaller the raw data, the better score it receives. For example, smaller biocide exposure is ranked better than larger biocide exposure. In each of these categories, the "worst" input data (i.e. the largest) is assigned a utility of 1. The value 0 receives a utility of 100. Between 0 and the largest value, we use a linear map from raw data to utilities. The only exception is the performance dimension. Here, a score of 0 has utility 0, a score of 5 has utility 100, and everything in between is mapped linearly.

Pairwise comparisons.

Each of the pairwise comparison sliders allows the user to specify that one dimension is more important to them than the other by a factor of up to 8. These inputs are then combined with the existing setting (starting from a uniform prior) by computing the closest consistent set of dimension weights (computing the eigenvalues of the linear problem). In this part, we are following a method known as the Analytic Hierarchy Process. You can find some more information on it here.

Ranking.

In the last step, the products' dimensional utilities are combined into a total product utility by using the weights obtained in the last step. This is just a simple weighted sum. The higher the total utility, the better the result. So we use the total product utility to determine your favorites.

What do other people prefer?

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The data underlying the comparison

Our comparison tool is based on the results of a study conducted by Northwest Green Chemistry and Washinton State's Department of Ecology. You can read more about the study on Northwest Green Chemistry's homepage and access the actual study here.

In order to make the various dimensions easily comparable, we have carefully aggregated the study's resulting data into the table below.

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