Innovation and Technology Management in Tourism & Hospitality 扫二维码继续学习 二维码时效为半小时

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Technology and advances in computations have enabled effective capture of information values of big data in a timely manner. The future challenges will be to develop tools to analyze the unstructured data which is said to be about 95% of all Big Data. The analytics are being driven by the large consulting companies who see this type of information as being valuable for decision-making, particularly by large companies.

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In relation to human interface design, users’ current existing articulated needs is the prime factor that needs to be considered. Even if the appearance of a design is gorgeous, it is useless due to obstinate functions. According to the study, the best tactic to improve complex, difficult-to-use, and error-prone artifacts is applying cognitive approaches.

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  • The smart destination is an emerging topic in tourism research.
  • To research the smart destination, tourism academia should integrate knowledge from diverse relevant areas, such as information systems, travel behaviors, marketing, urban planning, destination management, and governance, data analytics, and data science.

 

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  • Development of an 'experience typology matrix(矩阵' and an 'experience hierarchy'.
  • Explanation of tourism experience theory as incorporating technology-enhancement.
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  • In the tourism industry, digital storytelling is an effective tool to showcase local culture and authentic experience offered by destinations and to enhance cross-cultural understanding of tourists.
  • Digital storytelling is a creative and effective teaching method that enables students to actively participate in learning and practicing.
  • The students regard digital storytelling as a good learning experience that help them improve their English, computer knowledge as well as teamwork competence.
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  1. The article considers the uses and limitations of big data analysis to enhance forecasting of hotel occupancy rates.
  2. A wider choice of locations and more use of big data analysis is required to test the robustness of the technique.
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  • Prospective users’ needs and abilities are crucial and considerable factors for technology design. 
  • Unknown and incorrect affordances might result in a mistake.
  • With regards to clusters of affordance categorized by time continuity and space embeddedness, and disclosing through diverse media, multifaceted engagements are quite common. 
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客户参与度

  1. Exploration of issues surrounding customer engagement.
  2. Introduction and explanation of 'affordance' as a useful analytical tool.
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