Customer Requirement Driving New Product Concept Generation Method Based on Naïve Bayes Cluster and RST

2012 ◽  
Vol 490-495 ◽  
pp. 2160-2164
Author(s):  
Li Lin ◽  
Gang Guo
Keyword(s):  
Product Development ◽  
New Product Development ◽  
Rough Set Theory ◽  
Naive Bayes ◽  
New Product ◽  
Naïve Bayes ◽  
New Method ◽  
Concept Design ◽  
Concept Generation ◽  
Product Concept

Product concept generation and concept design are major activities for obtaining an optimal concept in new product development (NPD). A customer requirements driving new product concept generation method is addressed in this paper. This study proposes a new method to generate product concept, through which NPD team acquire customers’ requirement and product attributes. The new method is based on integrating of Naïve Bayes cluster and rough set theory (RST). It takes marketing strategy, business strategy into consideration, which makes new product development more effective compared with the traditional method. We believe that the proposed method will have a positive significance on the future new product development

Reliability and Accuracy of Bootstrap and Monte Carlo Methods for Demand Distribution Modeling

2011 ◽  
Author(s):  
Swithin S. Razu ◽  
Shun Takai
Keyword(s):  
Monte Carlo ◽  
Product Development ◽  
Conjoint Analysis ◽  
New Product Development ◽  
Demand Uncertainty ◽  
New Product ◽  
Product Development Process ◽  
Choice Data ◽  
Product Concept ◽  
Demand Distribution

Estimation of demand is one of the most important tasks in new product development. How customers come to appreciate and decide to purchase a new product impacts demand and hence profit of the product. Unfortunately, when designers select a new product concept early in the product development process, the future demand of the new product is not known. Conjoint analysis is a statistical method that has been used to estimate a demand of a new product concept from customer survey data. Although conjoint analysis has been increasingly incorporated in design engineering as a method to estimate a demand of a new product design, it has not been fully employed to model demand uncertainty. This paper demonstrates and compares two approaches that use conjoint analysis data to model demand uncertainty: bootstrap of respondent choice data and Monte Carlo simulation of utility estimation errors. Reliability of demand distribution and accuracy of demand estimation are compared for the two approaches in an illustrative example.

UNDERSTANDING LINEAR AND NONLINEAR ASPECTS OF PRODUCT CONCEPT DEVELOPMENT FROM THE ORGANISATIONAL INTERPRETATION PERSPECTIVE

2016 ◽  
Vol 20 (02) ◽  
pp. 1650027
Author(s):  
MANABU MIYAO
Keyword(s):  
Product Development ◽  
New Product Development ◽  
New Product ◽  
Linear Process ◽  
Concept Development ◽  
Stage Model ◽  
Nonlinear Characteristics ◽  
Product Concept ◽  
And Function ◽  
Interpretation Systems

The product concept is crucial in new product development (NPD) because it represents an NPD project’s goal. In this context, most prior studies have regarded product concept development as a linear process but some recent studies have revealed that it also has nonlinear characteristics. The objective of this paper is to explore why this inconsistency has arisen and to develop a model and theory that illustrate both aspects of product concept development. To achieve this, we adopt the perspective of organisational interpretation systems (Daft and Weick (1984). Toward a model of organisations as interpretation systems. Academy of Management Review, 9(2), 289–295) and explore eight product development cases. Consequently, we develop a three-stage model and find that the linearity or nonlinearity of product concept development is determined by each NPD team’s assumption about the environment. We also consider product innovativeness and function equivocality, and establish that these are related to the NPD teams’ assumptions about the environment.

Evaluating the Discriminatory Value and Reliability of Ideation Metrics for Their Application to Concept Development and Prototyping

2017 ◽  
Author(s):  
Jessica Menold ◽  
Kathryn Jablokow ◽  
Timothy Simpson ◽  
Rafael Seuro
Keyword(s):  
Product Development ◽  
New Product Development ◽  
New Product ◽  
Concept Development ◽  
Product Development Process ◽  
Concept Generation ◽  
Market Place ◽  
Design Changes ◽  
The Impact ◽  
Original Concept

Approximately half of new product development projects fail in the market place. Within the product development process, prototyping represents the largest sunk cost; it also remains the least researched and understood. While researchers have recently started to evaluate the impact of formalized prototyping methods and frameworks on end designs, these studies have typically evaluated the success or failure of these methods using binary metrics, and they often evaluate only the design’s technical feasibility. Intuitively, we know that a product’s success or failure in the marketplace is determined by far more than just the product’s technical quality; and yet, we have no clear way of evaluating the design changes and pivots that occur during concept development and prototyping activities, as an explicit set of rigorous and informative metrics to evaluate ideas after concept selection does not exist. The purpose of the current study was to investigate the discriminatory value and reliability of ideation metrics originally developed for concept generation as metrics to evaluate functional prototypes and related concepts developed throughout prototyping activities. Our investigation revealed that new metrics are needed in order to understand the translation of product characteristics, such as originality, novelty, and quality, from original concept through concept development and prototyping to finalized product.

An Approach to Modeling Customer Preference Uncertainty by Applying Bootstrap to Choice-Based Conjoint Analysis Data

2010 ◽  
Author(s):  
Swithin S. Razu ◽  
Shun Takai
Keyword(s):  
Product Development ◽  
Conjoint Analysis ◽  
New Product Development ◽  
Market Share ◽  
New Product ◽  
Analysis Data ◽  
Product Development Process ◽  
Product Concept ◽  
Customer Preference ◽  
Market Shares

Analysis of customer preferences is among the most important tasks in a new product development. How customers come to appreciate and decide to purchase a new product affects the products market share and therefore its success or failure. Unfortunately, when designers select a product concept early in the product development process, customer preference response to the new product is unknown. Conjoint analysis is a statistical marketing tool that has been used to estimate market shares of new product concepts by analyzing data on the product ratings, rankings or concept choices of customers. This paper proposes an alternative to traditional conjoint analysis methods that provide point estimates of market shares. It proposes two approaches to model market share uncertainty; bootstrap and binomial inference applied to choice-based conjoint analysis data. The proposed approaches are demonstrated and compared using an illustrative example.

Longitudinal Study of Learning Outcomes in a New Product Development Class

2007 ◽  
Author(s):  
Corie L. Cobb ◽  
Alice M. Agogino ◽  
Sara L. Beckman
Keyword(s):  
Longitudinal Study ◽  
Product Development ◽  
Learning Outcomes ◽  
New Product Development ◽  
Work Experience ◽  
New Product ◽  
Lessons Learned ◽  
Team Work ◽  
User Needs ◽  
Concept Generation

This paper reports on a longitudinal study of lessons learned from a graduate-level New Product Development course taught at the University of California at Berkeley, comparing lessons learned by students during the course with alumni perceptions one to ten years after graduation. Previous research on student learning outcomes in New Product Development (NPD) found that on the last day of class students identify working in multifunctional teams and understanding user needs as their most important lessons learned. This study raises the question of whether or not students maintain the same emphasis on learning outcomes once they have moved on to careers in industry. To answer this question, we conducted 21 in-depth interviews with alumni who took the course between 1995–2005 and are now working in industry. A qualitative and quantitative analysis of the alumni interviews reveals that former students still highly value what they learned about team work and understanding user needs, but see more value in tools for concept generation, prototyping, and testing after gaining work experience. The results reaffirm the value of engaging students in multidisciplinary design projects as a vehicle for developing the professional skills needed in today’s competitive new product development environment.

New methodology for product development process using structured tools

2020 ◽  
pp. 095440542097122
Author(s):  
Carlos Relvas ◽  
António Ramos
Keyword(s):  
Product Development ◽  
New Product Development ◽  
Development Process ◽  
New Product ◽  
Development Cooperation ◽  
Product Development Process ◽  
Concept Generation ◽  
Systematic Method ◽  
Development Team ◽  
Future Developments

The product development is a multidisciplinary process but also involves different areas of knowledge ranging from creativity in concept generation to refinement of design and finally the validation of the product. There are different approaches that attempt to define the best product development process, and thereby establishes a reliable method for efficiently transforming ideas into products. The use of a method that systematically establishes a work process seems to be highly advantageous, not only because it defines a critical and guiding path of work, organizing the tasks and their results, but also facilitates the communication of the development team. The methodology can provide records and other graphic documents that allow the development team to access these for future developments. The work presented here is the development of a systematic method supported by the use of structured tools to support the decisions, data processing and transposition of the same to the project in the approach to the new Product Development process. This research methodology was introduced and already implemented in projects at Department of Mechanical Engineering, University of Aveiro. The work developed on it, both at the level of the students’ project and in the work of Development cooperation with companies presented good results. This method result in a structured way to transforming ideas into products.

Adaptive Text Extraction for New Product Development

2009 ◽  
Author(s):  
Thomas Y. Lee
Keyword(s):  
Product Development ◽  
New Product Development ◽  
Quality Function Deployment ◽  
New Product ◽  
User Needs ◽  
Product Reviews ◽  
Concept Generation ◽  
Product Attributes ◽  
Traditional Methods ◽  
Text Extraction

The first step in product design and development involves concept generation. Concept generation involves identifying customer needs and then mapping those needs onto a set of product attributes (specifications). Traditional methods for concept generation involve focus groups, surveys, and anthropological studies to assess user needs. Techniques, like Quality Function Deployment (QFD), then guide designers in relating needs to explicit product specifications. In this paper, we propose to augment traditional methods for concept generation by automatically processing user generated online product reviews. We apply adaptive text extraction methods to automatically learn user needs and product attributes. Association rule mining is used to learn the mapping between needs and attributes. We summarize results from prior work for independently learning user needs and attribute specifications from product reviews and then discuss the application of these methods to concept generation for new product development.

Pitching at the Fuzzy Front-End: Authentically Assessing New Product Development

2021 ◽  
Vol 29 (1) ◽  
pp. 54-65
Author(s):  
Teegan Green ◽  
Jay Weerawardena
Keyword(s):  
Academic Success ◽  
Product Development ◽  
New Product Development ◽  
Social Constructivism ◽  
Authentic Assessment ◽  
New Product ◽  
Teaching Staff ◽  
Product Concept ◽  
Fuzzy Front End ◽  
Front End

Managing the “fuzzy front-end” (FFE) of new product development (NPD) is critical for NPD success. To simulate this reality, we tasked self-selecting undergraduate teams of four to six students with developing a substantially innovative new product concept. Integrating Vygotskian and Piagetian perspectives on social constructivism and experiential learning, we designed an authentic assessment pushing students into the FFE of NPD, featuring a live pitch to an expert industry panel. Pre-and-post survey results suggest students prefer authentic assessment infused with real-world learning experiences such as the pitch. Encouragingly, students perceived less usefulness over time for animate (e.g., teaching staff) and inanimate (e.g., textbooks) resources, indicating increased reliance on oneself post-assessment. Qualitative characteristics noted by students were group work, academic success, and the degree of challenge. Our approach is relevant for educators seeking to infuse their teaching—and enthuse students—with authentic assessment, addressing limitations of teacher-centered andragogy.

Preliminary Design of Amorphous Products

2006 ◽  
Author(s):  
Kurt A. Beiter ◽  
Tae G. Yang ◽  
Kos Ishii
Keyword(s):  
Product Development ◽  
New Product Development ◽  
Value Chain ◽  
Business Processes ◽  
New Product ◽  
Preliminary Design ◽  
Concept Generation ◽  
Physical Systems ◽  
Amorphous Systems ◽  
Key Points

This paper addresses the early design and development of amorphous systems. As competitive differentiators, many companies are focusing on amorphous systems comprised of primarily non-physical components, such as software, firmware, and service or business processes. This paper contrasts the development of amorphous systems with that of traditional physical systems. Whereas many tools used in new product development do apply to amorphous systems, the process and the tools need adaptation. The key points are: 1) Modeling of the system using “solution elements” instead of parts, 2) Preliminary concept generation based on use scenarios, and 3) Early consideration of the business model in the context of a complex value chain. The paper presents our proposed 10 step guide to amorphous product development and illustrates it with a “smart refrigerator” example, as well as citing the guide’s deployment in industry.

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