Evaluation of Kano-like Models Defined for Using Data Extracted from Online Sources

Abstract

The Kano model is a frequently used method to classify user preferences according to their importance, and by doing so support requirements prioritization. To implement the Kano model, a representative set of users must answer for each feature under evaluation a functional and dysfunctional question. Unfortunately, finding and interviewing users is difficult and time-consuming. Thus, the core idea of our proposed approach is to extract automatically opinions about product features from online open sources (e.g., Q & A sites, App reviews, etc.) and to feed them into the Kano questionnaire to prioritize software requirements following the principles of the Kano model. One problem with our proposed approach is how to pair input extracted from the internet into paired answers to the functional dysfunctional questions. This problem arises because the reviews and comments from online sources that we plan to transform into answers to either the functional or dysfunctional question are usually unpaired. Therefore, the aim of this study is to find a method that produces results resembling those of the traditional Kano model although we only retrieve partial information. We propose two Kano-like models, i.e., the Half- and the Deformed-Kano model, for unpaired answers to functional and dysfunctional questions. In order to analyze the performance of the two proposed models as compared to that of the traditional Kano model, we run several simulations with synthetic data. Then we compare the simulation results to see which Kano-like model produces results that are similar to those of the traditional Kano model. The simulation results show that on average both the Half-Kano and Deformed-Kano models on average generate feature categorizations similar to those of the traditional Kano model. However, only the Deformed-Kano model generates the same range of categorizations as the traditional Kano model. The Deformed-Kano can be used as an approximation of the traditional Kano model when the input is unpaired or partly missing.