Identifying Relationships Between Eco-innovation and Product Success - Technology Management for Sustainable Production and Logistics - page 178

4 Methodology for Forecasting Success of a Product

The proposed method aims to improve a new product development in order to
increase the chances for the eco-product success after its launch. This approach
assumes that on the basis of previous projects it is possible to identify the relation-
ships between project parameters and product success, and use them to indicate
the possible directions for products that are in the development process. One of the
characteristics of the developed approach is that it takes into account qualitative
and quantitative data and enables the identification of relationships in an enormous
database. For seeking relationships in large datasets, artificial neural networks
(ANNs) have been chosen. In turn, for description of the qualitative data, fuzzy set
theory has been used.
Figure 3 presents the procedure for identifying the factors that have impacted
on product success and forecasting the success of products that are in the develop-
ment process.

4.1 Fuzzy Numbers for Measuring Implementation
of Eco-innovation

Measurement of eco-innovation implementation is based on a questionnaire that
includes closed-ended questions concerning, for instance, potential barriers to
communication during project execution such as lack of trust among project team

Fig. 3 Project performance
evaluation model

Indicators for evaluating project environment

Qualitative data

Quantitative data

Fuzzy sets

Normalization

ANNs

Forecasting / what-if analysis