E-book readers have been successful in the United States. However, American e-books have not been launched in the Korean market yet, even though some Korean companies have launched their own products. American e-book readers need to identify which features are required for successful entry into the Korean market. This study aims to examine the attributes of e-book readers relevant to Koreans' preferences. It also aims to find key factors for an e-book reader to succeed in the Korean market. Out of many attributes of e-book readers, four attributes were selected by the Kano model for conjoint analysis. Based on the responses of young Koreans living in Seoul, 13 profiles were created, all of which are combinations of the selected attributes. Empirical results suggest that Koreans prefer an e-book reader that includes multi-media functions, a wi-fi connection, a resistive touch screen, and a display mixing e-ink with color TFT-LCD. Analyses also reveal that a reader's commuting time makes a difference in the importance they place on such attributes. Using choice simulation with the results of the study, the demands of e-books are forecasted. The findings can assist foreign companies, such as Amazon.com, to understand Koreans' preferences better and identify attributes most advantageous for entering the Korean e-book market. The findings also aid in forecasting the demands of e-book readers in the Korean market. Conjoint analysis procedures are some of the best tools available for determining the importance or relative value of attributes of complex environments from the user's point of view. Conjoint analysis has been employed for the first time in Korea in this study to explore the importance of such attributes to e-book readers.
Bibliographical noteFunding Information:
The corresponding author’s work was financially supported by the Ministry of Knowledge Economy (MKE) and Korea Institute for Advancement in Technology (KIAT) through the Workforce Development Program in Strategic Technology.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Artificial Intelligence