Identifying Relationships Between Eco-innovation and Product Success - Technology Management for Sustainable Production and Logistics - page 179

members, resistance to sharing information among members, effectiveness of team
discussions, etc. The survey aims to identify the attitudes of employees towards
implementation of green methods in organizational, manufacturing, and designing
processes. Inquiries for measuring eco-innovation implementation are presented in
Table 2 .
The statements of respondents result from subjective judgments and are usually
specified in the imprecise form, for example, as the following phrases: “strongly
agree”, “agree”, “neither agree nor disagree”, “disagree”, “strongly disagree”. A
respondent can choose one or more of these linguistic variables. If a respondent
chooses a limited number of linguistic variables to answer to a question, then the
fuzzy set theory can be used to evaluate the implementation of eco-innovation.
Moreover, the answers from team members may differ significantly depending on
the individual perceptions or personality of the respondent (Relich and Jakabova
2013 ). Therefore, the evaluation is conducted in an uncertain and fuzzy envi-
ronment. Compared to traditional binary sets (where variables may take on true
or false values), fuzzy logic variables may have a value that ranges in degree
between 0 and 1. Fuzzy logic has been extended to handle the concept of partial
truth, where the value may range between completely true and completely false.
The notion of truth can be considered as a means of representing and reasoning
with partial knowledge which is closer to human subjective judgments that precise
statements.
Fuzzy set theory is based on the concept of fuzzy set membership, where the
membership functions are used to calculate the degree of membership of a fuzzy
eco-innovation metric (indicator) to different sets, expressed by linguistic terms
such as e.g. very low, low, medium, high, and very high (see Fig. 4 ). The shape of
a fuzzy number and the scale of a linguistic variable depends on the user's needs.
In this study, a subjective judgement concerning level of indicator is assigned to
the scale from 1 to 5.
Traditional questionnaires concerning implementation of eco-innovation usu-
ally include a checklist for answers, and allow the respondent to choose only one
answer for each item. However, problems arise when the respondent has more
than one answer. Asking the respondent to make only one decision for each item
may result in the data becoming inaccurate. Hence, to improve the traditional
survey, this research proposes the use of fuzzy logic. An improvement over the
Fig. 4 Membership function