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2022/2023  AO-ASTHO1006U  Big Data in Tourism and Hospitality

English Title
Big Data in Tourism and Hospitality

Course information
Language English
Course ECTS 5 ECTS
Type Mandatory
Level Master
Duration One Quarter
Start time of the course Third Quarter
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
AO Study Board for cand.soc.
Course coordinator
  • Erik Braun - Department of Marketing (Marketing)
Main academic disciplines
  • Information technology
  • Service management
  • Statistics and quantitative methods
Teaching methods
  • Blended learning
Last updated on 16-06-2022

Relevant links
Learning objectives
The learning objectives of this course are:
  • Students get familiar with the basic tenets of big data
  • Students develop reflexive abilities for assessing big data sets
  • Students are aware of big data applications in the tourism and hospitality industry
  • Students are aware of ethical and societal issues associated with big data applications
  • Students have knowledge on how to extract insights from big data
  • Students have knowledge of tools to gather online (big) data
Examination
Big Data in Tourism and Hospitality:
Exam ECTS 5
Examination form Home assignment - written product
Individual or group exam Individual exam
Size of written product Max. 10 pages
Assignment type Written assignment
Duration 2 weeks to prepare
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Spring
Make-up exam/re-exam
Same examination form as the ordinary exam
Course content, structure and pedagogical approach

Aim:

The students develop competencies related to the impact of digitalization and big data on the tourism and hospitality industry. They can identify ethical, societal and managerial aspects of big data. In addition, the course introduces tools for online big data collection and analysis that help to support strategic business decisions.
 

Content:

The course gives insights how digital big data has changed the tourism and hospitality. The first part of the course reviews the impact of big data on businesses and governments. The second part of this blended course introduces tools to collect big data and to extract insights from big data. Students learn these tools through tutorial videos and get feedback in small workshop sessions. Finally, the course reviews business and governmental decision-making on insights derived from big data.
Description of the teaching methods
This course is delivered in a blended learning format. That is, the course combines physical in-class teaching with both prerecorded video as well as 'live' online teaching.
Feedback during the teaching period
Students will receive feedback in the following ways: 1) in-class lectures; 2) in online lectures; 3) during the office hours.
Student workload
Attending class 22 hours
Preparation 67,5 hours
Exam 48 hours
In total 137,5 hours
Expected literature

To be added
Last updated on 16-06-2022