scholarly journals Virtual Reality Based Conjoint Analysis for Early Customer Integration in Industrial Product Development

Procedia CIRP ◽  
2014 ◽  
Vol 25 ◽  
pp. 61-68 ◽  
Author(s):  
Klaus Backhaus ◽  
Jonas Jasper ◽  
Katharina Westhoff ◽  
Jürgen Gausemeier ◽  
Michael Grafe ◽  
...  
Author(s):  
Swithin S. Razu ◽  
Shun Takai

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.


Author(s):  
Hyeji Kim ◽  
Jing Chen ◽  
Euiyoung Kim ◽  
Alice M. Agogino

Conjoint analysis has proven to be a useful method for decomposing and estimating consumer preference for each attribute of a product or service through evaluations of sets of different versions of the product with varying attribute levels. The predictive value of conjoint analysis is confounded, however, by increasing market uncertainties and changes in user expectations. We explore the use of scenario-based conjoint analysis in order to complement qualitative design research methods in the early stages of concept development. The proposed methodology focuses on quantitatively assessing user experiences rather than product features to create experience-driven products, especially in cases in which the technology is advancing beyond consumer familiarity. Rather than replace conventional conjoint analysis for feature selection near the end of the product development cycle, our method broadens the scope of conjoint analysis so that this powerful measurement technique can be applied in the early stage of design to complement qualitative research and drive strategic directions for developing product experiences. We illustrate on a new product development case study of a flexible wearable for parent-child communication and tracking as an example of scenario-based conjoint analysis implementation. The results, limitations, and findings are discussed in more depth followed by future research directions.


Author(s):  
Swithin S. Razu ◽  
Shun Takai

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.


2013 ◽  
Vol 19 (1) ◽  
pp. 164-178 ◽  
Author(s):  
이민수 ◽  
kim young sik ◽  
Choi Soo Keun ◽  
김기쁨

Author(s):  
G. Drieux ◽  
J.-C. Le´on ◽  
N. Chevassus ◽  
F. Guillaume

The Digital Mock-Up (DMU), which is a comprehensive numerical model describing the final manufactured product, is today widely used in the industry (like the automotive and aeronautic industries) to support the concurrent engineering organizations and processes. On the other hand, simulation helps in the development of a product for design decision making or validation purposes. It allows to determine, with the appropriate level of accuracy, the behavior of the future product under a specific environment or set of exterior actions. Virtual Reality (VR) applications are simulations where the focus is on immersion and interaction with the product. However, there is still lacks in the integration of simulation within the product development phases. In particular the link between the DMU and the numerical models for simulation in the large is often hardly achieved. For some types of simulation, it is even inexistent. In this paper, we propose a new object, the Downstream Digital Mock-Up (DDMU), based on a polyhedral representation, and we show that it can be a support for the integration of a subset of simulation activities within the product development process by making the link between the DMU and these simulations. In the particular case of VR, we show that this object is particularly adapted. One particularity of the DDMU is to be prepared for a specific target application, defined by its objectives and the context in which it is immersed.


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