Mining customer product reviews for product development: A summarization process

This research set out to identify and structure from online reviews the words and expressions related to customers' likes and dislikes to guide product development. Previous methods were mainly focused on product features. However, reviewers express their preference not only on product features. In this paper, based on an extensive literature review in design science, the authors propose a summarization model containing multiples aspects of user preference, such as product affordances, emotions, usage conditions. Meanwhile, the linguistic patterns describing these aspects of preference are discovered and drafted as annotation guidelines. A case study demonstrates that with the proposed model and the annotation guidelines, human annotators can structure the online reviews with high inter-agreement. As high inter-agreement human annotation results are essential for automatizing the online review summarization process with the natural language processing, this study provides materials for the future study of automatization.

Mining Changes in User Expectation Over Time From Online Reviews

Customers post online reviews at any time. With the timestamp of online reviews, they can be regarded as a flow of information. With this characteristic, designers can capture the changes in customer feedback to help set up product improvement strategies. Here we propose an approach for capturing changes of user expectation on product affordances based on the online reviews for two generations of products. First, the approach uses a rule-based natural language processing method to automatically identify and structure product affordances from review text. Then, inspired by the Kano model which classifies preferences of product attributes in five categories, conjoint analysis is used to quantitatively categorize the structured affordances. Finally, changes of user expectation can be found by applying the conjoint analysis on the online reviews posted for two successive generations of products. A case study based on the online reviews of Kindle e-readers downloaded from amazon.com shows that designers can use our proposed approach to evaluate their product improvement strategies for previous products and develop new product improvement strategies for future products.

Assessing the differences between numerical methods, CAD evaluations and real experiments for the assessement of reach envelopes of the human body

Numerical models and computer-aided modeling software are tools commonly used to assess the accessibility of an environment, based on static human body dimensions. In this paper, the limits of validity of these approaches are assessed by comparing the reach envelopes obtained by these methods to those obtained experimentally. First, the accessibility areas of forty adult subjects, which may correspond to the distance of reachability of products, were evaluated by performing an accessibility task comprising 168 reach points. Second, anthropometric characteristics of participants were recorded and used to perform the reach assessment by a numerical method, and then by a CAD-based analysis, where the reach was predicted using the software's maximum reach-envelope generation. In spite of the simple nature of the presented design problem (two-dimensional), the results show important differences between the three methods. The study of the number of reached points shows that the CAD-based assessment provides more accurate results than the numerical model. Nevertheless, the shapes envelopes comparison indicates that the maximum reach envelopes obtained with the CAD analysis are not always consistent with those obtained experimentally, closely linked to the hand location. Results indicate that the CAD model used to obtain maximum reaches gave predictions that underestimate the reach ability.