Academic Experts in Travel Technology and Analytics

Academic Experts in Travel Technology and Analytics

Travel Technology and Analytics (MS)

The interdisciplinary Master of Science in Travel Technology and Analytics, offered jointly by the College of Engineering and Computer Science (Departments of Computer Science; Industrial Engineering and Management Systems; Civil, Environmental, and Construction Engineering) and the Rosen College of Hospitality Management (Departments of Tourism, Events, and Attractions; Hospitality Services), introduces graduate students to the technical aspects of big data analytics, including predictive analytics, algorithm design and models for SMART-cities, SMART-technologies and travel systems, and service systems quality engineering, in the specific context of global travel and tourism.

Click HERE to learn more about the degree program.

 

Read about the Master of Science in Travel Technology and Analytics in UCF Today!

Applicants must apply online: https://applynow.graduate.ucf.edu/apply/
Questions? Please email:  traveltech@ucf.edu
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Special Insight in Travel Technology and Analytics: Hotel Industry

What will the hotel industry look like after coronavirus COVID-19? Libardo Lambrano, Senior Manager, Marketing Performance & Insights for Hilton and a Master’s degree grad from Rosen College shares what he knows. Read his article.

Meet the Rosen College Academic Experts Below!

Co-creating Values through Mobile Technologies

Hospitality is a customer-oriented service sector, in which customers are involved to co-create with service providers to achieve the optimal customer experience. The proliferation of mobile technologies diversifies the approaches to engaging consumers with value co-creation activities in the service delivery process. Check the following article explaining the factors that entice Generation Y consumers to engage in co-creation activities using mobile technology.

Zhang, T.C., Lu, C., & Kizildag, M. (2017). Engaging Generation Y to Co-Create Through Mobile Technology. International Journal of Electronic Commerce, 21, 489-516.

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Leveraging Human Touch
in Service Interactions

Dr. Murat Hancer

The ever-increasing adoption of technology and automation radically changing the nature of service delivery. The role of human touch, introducing hospitable service as an enhancement for value creation in service organizations is an important phenomenon in the service industry. Check the following article for the presentation of a four-configuration model to illustrate dimensions which arise from the confluence of different degrees of relationship orientation – shared mental models held by the host organization (self- or other-oriented), and guests’ service preferences (transactional or relational).

Solnet, D., Subramony, M. Ford, R., Golubovskaya, M. Kang, H. & Hancer, M. (2019). Leveraging Human Touch in Service Interactions: Lessons from Hospitality. Journal of Service Management, 30 (3), 392-409.

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Utilitarian and Hedonic Value
in the Context of Mobile Hotel Booking  

Dr. Ahmet Ozturk

With the increase in the advancements and popularity of mobile technologies, mobile devices have become ideal companions for travelers, allowing them not only to access information and services but also to do booking while they are on the move. Check the following article examining the factors that affect mobile hotel booking users’ utilitarian and hedonic value perceptions and their continued usage intentions.

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Travel analytics:
Understanding how destination choice and business clusters are connected based on social media data

Dr. Arthur Huang

Understanding how destination choice and business clusters are connected is of great importance for designing sustainable cities, fostering flourishing business clusters, and building livable communities. As sharing locations and activities on social media platforms becomes increasingly popular, such data can reveal destination choice and activity space which can shed light on human-environment relationships. This research models the relationship between characteristics of business clusters and check-in activities from Los Angeles County, California. Business clusters are analyzed via two lenses: the supply side and the demand side. Spatial and statistical analyses are performed to understand how land use and transportation network features affect the popularity of the identified clusters and their relationships.

Huang, A., Gallegos, L., & Lerman, K. (2017). Travel analytics: Understanding how destination choice and business clusters are connected based on social media data. Transportation Research Part C: Emerging Technologies, 77, 245-256.

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Connecting Electronic
Word-of-Mouth with Brand Success

Dr. Tingting Zhang

Social media and mobile technologies are key to information sharing, especially among people born after 1981 –Generation Y cohort. User-generated content (UGC) in the form of hospitality/tourism products or services reviews posted on digital platforms such as TripAdvisor or Twitter has become the defining factor leading to a purchase by prospective customers. Check the following article exploring the factors that influence Generation Y’s use of social media and mobile technologies to share positive or negative hospitality experiences:

Zhang T, Omran BA, Cobanoglu C. Generation Y’s positive and negative eWOM: use of social media and mobile technology. (2017). International Journal of Contemporary Hospitality Management. 29(2), 732-762.

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A network model of neighborhoods’ happiness: A big data perspective

Happiness has been increasingly recognized as a fundamental component of public health. Understanding how various exogenous variables shape happiness has great theoretical and practical significance. Traditional research has used survey-based approach or controlled experiment to examine a variety of stimuli such as personal traits, life events, environment, and social networks. By applying big data analytics, this research advanced this understanding by examining the relationship between happiness reflected on social media platforms and the neighborhood environment. This research integrated geo-tagged social media data and physical environment data, and drew on methods from machine learning, network science, spatial analysis, and statistics to test new hypotheses. A network of happiness was built at the neighborhood level.

Huang (2019). A network model of neighborhoods’ happiness: A big data perspective. Working Paper. Presented at the 1st International Conference on Smart Tourism, Smart City, and Enabling Technologies. May 1-4, Orlando, Florida, USA.