Capture Customer Requirements Research Articles

Big consumer opinion data understanding for Kano categorization in new product development

Big consumer opinion data provide valuable information about customer preferences. These online opinions facilitate designers to capture customer requirements (CRs) and understand customer satisfaction (CS) for new product development (NPD). A visible gap between practical significance and research studies is to uncover nonlinear relations between CRs and CS and derive strategic suggestions. Accordingly, a framework for online CRs Kano categorization is proposed. Firstly, both explicit and implicit features are extracted from opinionate texts to better capture CRs. Secondly, to evaluate the impact of CRs on the overall CS, a multi-layer neural network is invited, in which the impact from both positive and negative opinions over each product feature are distinguished. Finally, according to the estimated impact, CRs are categorized by a Kano Model based approach. To evaluate the effectiveness of the proposed framework, a case study that analyzes a large number of phone reviews is presented. Categories of studies were benchmarked to demonstrate the competitiveness of utilized approaches. This study is argued to disclose complex relations between CRs and the overall CS as well as strategic improvement suggestions by online opinion analysis. It enlightens designers to infer constructive strategies from big consumer opinion data for market-driven NPD.

An Interactive Tool for Collaboration and Knowledge Sharing of Customer Needs in the Conceptual Phase

AbstractThis paper aims to research how the use of an interactive tool can facilitate collaboration, knowledge sharing and enhance the understanding of customer needs in conceptual phase at a global shipbuilding company. An effective conceptual phase depends on collaboration and mutual understanding of customer needs to capture customer requirements and transform them into a base of design‐document. Lack of early common understanding can result in increased project cost or in worst‐case loss of contract. We used action research as an approach for our study and developed and implemented an interactive tool in a case at the company. In‐depth interviews and root‐cause analysis were used to determine the pain‐points of the as‐is situation. A feedback survey was used to evaluate the performance and result of the interactive tool. The results indicate that the interactive tool contributes to a better overview of ongoing projects, increased knowledge sharing, and enhanced common understanding.

Research on Capturing of Customer Requirements Based on Innovation Theory

Abstract To exactly and effectively capture customer requirements information, a new customer requirements capturing modeling method was proposed. Based on the analysis of function requirement models of previous products and the application of technology system evolution laws of the Theory of Innovative Problem Solving (TRIZ), the customer requirements could be evolved from existing product designs, through modifying the functional requirement unit and confirming the direction of evolution design. Finally, a case study was provided to illustrate the feasibility of the proposed approach.

An associative classification-based recommendation system for personalization in B2C e-commerce applications

It has been recognized that e-commerce and mass customization will emerge as a primary style of manufacturing. The main challenge for such a paradigm originates from difficulties in personalization - providing support for customers to find the most valuable products that match their heterogeneous needs. Traditional approaches to the personalization problem adopt pre-defined formats to describe the customer requirements. This always leads to distortion in eliciting requirement information and thus inaccurate recommendations. Knowledge discovery lends itself to dealing with semi-structured data and makes it possible to capture customer requirements more accurately. This paper proposes an associative classification-based recommendation system for personalization in B2C e-commerce applications. Knowledge discovery techniques are applied to support personalization according to an inner established model that anticipates customer heterogeneous requirements. The framework and methodology of the associative classification-based recommendation system have been addressed. The system analysis, design, and implementation issues in an Internet programming environment are presented. The feasibility of the proposed recommendation system has been validated with a prototype for personalization in mobile phone B2C e-commerce applications.

A reconfigurable platform in support of one-of-a-kind product development

In recent years, a variety of Internet-based systems has been developed for the purpose of Rapid One-of-a-Kind or customized Product Development (ROKPD). They can be applied in different stages of the product development process such as to rapidly capture customer requirements, and help produce high-quality products at low cost and short lead-time. Many of the systems, however, do not support rapid adaptation or dynamic reconfiguration of systems and tools for supporting ROKPD in a distributed manufacturing environment. To the authors’ knowledge, the infrastructure of such a reconfigurable platform for supporting distributed manufacturing has never been directly studied. This paper proposes an Internet-based reconfigurable ROKP platform that has been prototyped to serve as a substrate for integrating innovative tools and systems for One-of-a-Kind Production (OKP) companies in New Zealand. The main emphasis of this paper is to investigate how to build the Internet-based reconfigurable ROKPD platform and to design appropriate intelligent tools and systems for the purpose of rapidly and economically producing OKP products in the global environment. A number of recent developments are discussed, including the four open-domain infrastructure of the ROKPD platform, Internet-based data management systems, an integrated product data environment and a cost/lead time control tool.

An operational model for structuring the requirements generation process

Product quality is directly related to how well that product meets the customer’s needs and intents. Therefore, the ability to capture customer requirements correctly and succinctly is paramount. Unfortunately, within most software development frameworks requirements elicitation, recording and evaluation are some of the more ill-defined and least structured activities. To help address such inadequacies, we propose a requirements generation model (RGM) that (a) decomposes the conventional “requirements analysis” phase into sub-phases which focus and refine requirement generation activities, (b) bounds and structures those activities to promote a more effective generation process, and (c) implements a monitoring methodology to assist in detecting deviations from well-defined procedures intended to support the generation of requirements that meet the customer’s intent. The RGM incorporates “lessons learned” from a preliminary study that concentrated on identifying where and how miscommunication and requirements omission occur. An industry study (also reported in this paper) attests to the effectiveness of the RGM. The results of that study indicate that the RGM helps (a) reduce the late discovery of requirements, (b) reduce the slippage in milestone completion dates, and (c) increase customer and management satisfaction levels.

Improving the Front End of the Software-Development Process for Large-Scale Systems

For large-scale systems, diverse customer needs must be communicated and translated into precise implementations that are consistent with the existing system. Typically, we have relied on English-language text as a communications medium. But requirements written in English are often imprecise, and translating them into a finished product is largely a manual effort. As a result, the front end of the software development process — from analysis of customer requirements to high-level design — is generally time consuming, labor intensive, and error prone. In this paper, we discuss ways to apply computer-aided software-engineering technologies to the front-end process. We discuss ways to capture customer requirements in a machine-processable form where they can be reviewed, revised, analyzed, and refined into clear, unambiguous descriptions of what needs to be done and how to do it. Our goal in applying new and existing technologies is to mechanize much of the front-end process and thus reduce development costs and improve product quality.