# Application of Quality Function Deployment for Product Design Concept Selection
## 1 Introduction  
Firms develop new products in order to remain competitive and expand their market share. Thus, according to [PERSON] et al. new product development (NPD) is a vital function and critical process to remain competitive in the highly competitive environment [1]. Additionally, [PERSON] [2] tells that as the selected design concept highly contributes the success of the final product and directly affects the following development stages, new concept selection is one of the most important decision-making activities during NPD. [PERSON] et al. confirms that despite of its importance, concept selection is difficult because it requires complex multi criteria decision making (MCDM) with many factors, ranging from customer needs to constraints of the enterprise [3]. [PERSON] (2013) selected and reviewed 154 journal articles on product design concept selection and evaluation for the period 1986-2012 [4]. The methods used were individual, including total cost approach, multiple attribute utility theory, total cost of ownership (TCO), AHP, data envelopment analysis, and mathematical programming techniques. Among them, TCO was the most prevalent approach, followed by AHP. Because of this finding,Bhutta and [PERSON] (2012) compared TCO and AHP comprehensively [4]. They revealed that AHP can provide a more robust tool for decision makers to select and evaluate customer's requirements for product design with respect to qualitative and quantitative criteria, instead of cost data only considered in TCO. [PERSON] et al. (2019) selected and reviewed 70 journal articles on product design concept selection and evaluation for the period 2000-2018 [5]. Several approaches have been proposed for product design concept selection, such as using AHP, analytic network process (ANP), case-based reasoning (CBR), data envelopment analysis (DEA), fuzzy set theory, genetic algorithm (GA), mathematical programing, simple multi-attribute rating technique (SMART), and their integrations. For business-to-business (B2B) products, design concept selection directly contributes to the final quality of the product and the company business reputation--this is the opinion of [PERSON] [6]. B2B products have unique characteristics which are different from business-to-customer (B2C) products. B2B products have long-term relationships with fewer but larger buyers that have high demands for products with quality, price, as well as function that meet definite customer requirements (CR). In this study, we focus on methods to comprehensively evaluate and select new design concepts from the perspective of B2B products. We propose a hybrid approach with two evaluation factors, concept competitiveness (V\({}_{comp}\)) and design development efficiency (V\({}_{eff}\)) on the basis of CR. Concept competitiveness represents the product's relative strong points in functional performance and market price. We apply the integrated approach with quality function deployment (QFD) and analytic hierarchy process (AHP) to evaluate the concept competitiveness (V\({}_{comp}\)). On the other hand, as the quality and productivity are completely depending on the design concept, it is necessary to assess each design concept's relative level in terms of efficiency of input and output. Design development efficiency (V\({}_{eff}\)) represents the relative efficiency among the new concepts. We adopt data envelopment analysis (DEA) to assess the V\({}_{eff}\). We combine these evaluation results and the combined score as the final score for each new design alternative. Recently, the combined AHP-QFD approach has been applied to many areas, including higher education, for example [PERSON] and [PERSON] in 1998; [PERSON] and [PERSON] in 1998; [PERSON] and [PERSON] in 2012 tell that for the best knowledge of the authors, this approach has not yet been applied for product design concept selection problem [7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20].