Ürün geliştirme sürecinde çok amaçlı karar verme yaklaşımı

The globalization of the economies diminishes the differences between local and foreign products/ services. Nowadays, both the number of the product/ service providers and also the variety of the place of the origins are increasing. Consequently, the firms are facing a tough competition while trying to keep and increasing their market shares. Unavoidably, the firms began to look out for the little differentiations which will ensure their success over their competitors. Thus, they are developing products/services tailor-made for their customers. The main idea behind all these efforts is to determine somehow the requirements of the customers and to ensure that, the products produced and the services provided will satisfy these needs. In this work, an application in the area of elearning, which is a term recently established following the late developments in the area of the networks like the Internet, is proposed. E-learning can be basically defined as, the transformation from the face-to-face conventional education into distance based, independent from time and place education form. Its main difference from the conventional education is that, previously the academics controlled the pace, place, time and the presentation of the education, whereas, now, e-education gave the control of these attributes to the learners. As the decision makers are the learners during the e-learning process, new development procedures should be prepared differing from the procedures of conventional type of learning. In order to ensure the satisfaction of the customers with the new developments, their needs should be known forehand. Additionally the attention of the customer could only be kept alive, not only by satisfying their current needs, but also foreseeing their future needs, when developing the products/services. Thus, in this study, Quality Function Deployment (QFD), which is one of these key design activities, is used to solve the product definition problem during the new product development process. The aim is, to study, evaluate and suggest improvements for the e-learning applications in Turkey, in order to satisfy the customers. The QFD methodology, which will be used to develop e-learning products, is defined as, a customeroriented design tool with cross-functional team members used to develop new products/ services or to improve current products/services regarding the needs and the requirements of the customers. QFD tries to satisfy the customers at the initial production stage, namely the design stage, preventing corrective actions to be made after the product has been produced. QFD starts after the development team consisting of team members from all the divisions of the organization reaches a consensus in the identification of the Customer Needs (CNs), which will be used during the design process. This data, will be used to establish the ‘house of quality’, which is a king planning matrix transforming the CNs into measurable Product Technical Requirements (PTRs). During the development process, both the needs meaningless and the needs crucial for the customers are distinguished to ensure to remove or include them according these finding. In order to categorize the needs as mentioned, the inner dependencies among the CNs, the relationships between the CNs and the PTRs and lastly the inner dependencies among the PTRs should be measured. According to these relationships, it will be foreseen, how and in which direction, a modification in the design of the product could affect the CNs. The proposed approach tries to solve the problem of measuring the CNs and requirements which are usually expressed in customers’ own phrases. It consists of fuzzy logic theory integrated with Analytic Network Process (ANP), Compromise Programming (CP), linear regression and Goal Programming (GP) methods. The ANP is used to identify the importance ratings of the PTRs which will maximize the satisfaction of the CNs, with regard to the relationship between and among the CNs and the PTRs. The CP employed identifies the ideal and the anti-ideal performance values for the CNs and the distances from them for each product in the market. As the distances for each CN are summed, the distance value indicating the performance of this product is defined. Fuzzy linear regression is integrated to the model to integrate the relationships between the CNs and the PTRs into the GP model. The GP model uses the best products distance value as the goal along with the budget limitation of the organization. The solution to the optimization model defines the target PTR performance values to be the best product in the market by satisfying the customers.