Modification and development of product concept design based on the product customers life environmental and social habits backgrounds’ diversity requirements

Abstract

Product customers often have varying preferences because they have different environmental and social habits backgrounds’ requirements “customer diversity requirements.” Even for a particular product used in specific place, the requirements of product stakeholders are often differed. It is a challenge to adapt diversity requirements to concepts design of products to satisfying different customers. To address the customer diversity requirements issue, after the analysis of customers information is completed, customers are classified according to their diversity. Then, customer requirements (CRs) and engineering specifications (ESs) that satisfy the CRs are determined. The priorities of CRs are calculated with analytical hierarchy process (AHP) involving a pairwise comparison matrix in the first step and fix-sum method in the second step. Quality function deployment (QFD) relation matrix is utilized to form the relationships intensities of CRs and ESs. ESs satisfaction degree values obtained concerning computation of CRs priorities calculated via AHP, while ESs target degree values obtained concerning computation of CRs priorities calculated via fix-sum method into QFD relation matrix. ESs satisfaction degree compared with ESs targets degree to measure the satisfaction for each customer target individually. The decision on whether the concept design needs further development or modification is made based on the comparison results. A case study of the application of this approach is presented to illustrate the possibilities of the technique in developing or modifying concept design according to customers’ life environmental and social habits background “diversity requirements.” The case proved that technique can adapt products to different environments and that products used by existing customers can be used for new customers or markets (product globalization) instead of being confined to one location. Moreover, the approach is very useful in clarifying the objectives expected by customers for specifying the development or modification of a product concept.

Identification of Demand Type Differences and Their Impact on Consumer Behavior: A Case Study Based on Smart Wearable Product Design

“…Consumer demands can be objectively reflected by summarizing users' evaluations, feedback, and recommendation information about the products [29]. The TF-IDF technology in semantic analysis can be an effective way to deeply understand core consumer demands in the context of e-commerce platforms [30]. TF-IDF is a weighted technique commonly used in information retrieval and data mining in the process of big data semantic analysis, where the values obtained can be used to evaluate the importance of words [31].…”