Assessing the User Resistance to Recommender Systems in Exhibition
AbstractUnder the paradigm shift toward smart tourism, the exhibition industry is making efforts to introduce innovative technologies that can provide more diverse and valuable experiences to attendees. However, various new information technologies have failed in a market in practice due to the user’s resistance against it. Since innovative technology, such as booth recommender systems (BRS), is changing, creating uncertainty among consumers, consumer’s resistance to innovative technology can be considered a normal reaction. Therefore, it is important for a company to understand the psychological aspect of the consumer’s resistance and make measures to overcome the resistance. Accordingly, based on the model of Kim and Kankanhalli (2009), by applying the perceived value, the technology acceptance model, and the status quo bias theory, this study focused on the importance of self-efficacy and technical support in the context of using BRS. To do this purpose, a total of 455 survey data that was collected from “Korea franchise exhibition” attendees were used to analyze the proposed model. Structural equation modeling was applied for data analysis. The result shows that perceived value was affected by relative advantage and switching cost, also switching cost reduced the perceived value. However, self-efficacy reduced the switching cost, thereby decreasing the resistance of exhibition attendees. In addition, technical support increased the relative advantage switching cost and the perceived value. Exhibition attendee’s resistance was significantly negatively affected by perceived value, and positively affected by switching cost. The results will provide balanced viewpoints between the relative advantage and switching cost for exhibition marketers, helping to strengthen the competitiveness in terms of sustainable tourism of exhibition. View Full-Text
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Koo, C.; Chung, N.; Ham, J. Assessing the User Resistance to Recommender Systems in Exhibition. Sustainability 2017, 9, 2041.
Koo C, Chung N, Ham J. Assessing the User Resistance to Recommender Systems in Exhibition. Sustainability. 2017; 9(11):2041.Chicago/Turabian Style
Koo, Chulmo; Chung, Namho; Ham, Juyeon. 2017. "Assessing the User Resistance to Recommender Systems in Exhibition." Sustainability 9, no. 11: 2041.
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