An integrated QFD framework with multiple formatted and incomplete preferences: A sustainable supply chain application

• The objective of the paper is to apply an extended QFD methodology in sustainable supply chain (SSC).
• The paper examines the main elements of SSC and how they serve as a foundation for an evaluation framework.
• A new GDM approach that takes multiple preference formats and incomplete information into account is introduced.
• To assess the validity of the proposed approach, a case study conducted at HAVI Logistics-Turkey is presented.

Merging sustainable development with the business, and taking goals into account from its three dimensions (i.e., economic, environmental and social) which are derived from customer and stakeholder requirements have been a potential source of competitive differentiation for firms. Academic and corporate interest in sustainable supply chain (SSC) management has also risen considerably in recent years. This paper examines the components and elements of SSC management and how they serve as a foundation for an evaluation framework. By using quality function deployment (QFD) as a product/system planning and improvement tool, an effective SSC structure can be obtained. QFD uses a matrix called the “House of Quality” (HoQ), and constructing the HoQ is a critical step in the application of QFD as it translates customer requirements into engineering characteristics. However, participants of HoQ construction sessions tend to provide information about their individual judgments in multiple formats such as numerically or linguistically depending on their different knowledge, experience, culture and circumstance. Furthermore, they can generate incomplete preferences which are challenging to assess in a consistent way. Therefore, the objective of this study is to apply an extended QFD methodology in SSC by introducing a new group decision making (GDM) approach that takes multiple preference formats and incomplete information into account and fusions different formats of expressions into one uniform group decision by means of the fuzzy set theory. To assess the validity of the proposed approach, a case study conducted at HAVI Logistics-Turkey is also presented in the paper.