Resale value is an important aspect to be addressed when companies aim to shift from one-sale models to Product Service Systems (PSS). In the initial stages of the PSS design process, it is beneficial to predict how the mechanical features of the PSS hardware will impact resale value, so to orient business strategy decisions accordingly. The objective of this work is to propose a methodology to model the resale value of road compaction equipment using data mining techniques. By scrapping and merging data sets from the machine manufacturer and from dealers of second-hand machines, the work discusses how the derived correlations may be used to populate value models for early stage decision making.
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