General Information
This subject explores the dynamic intersection of technology and tourism, examining how digital innovations are reshaping travel experiences, destination management, and industry operations. It introduces frameworks to inform digital innovation strategy, including technology adoption; diffusion of innovations; the risks associated with digital technologies and how to manage these responsibly. A range of technologies used by tourists and/or tourism operators will be explored, from mobile apps and smart systems to artificial intelligence and virtual reality. Through case studies and hands-on activities, students will evaluate digital technologies in tourism from an end-user perspective and propose technological solutions to enhance the tourist experience and/or improve the operational efficiency of tourism organisations.
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Details
Academic unit: Bond Business School Subject code: HRTM12-215 Subject title: Digital Innovation in Tourism Subject level: Undergraduate Semester/Year: September 2026 Credit points: 10.000 -
Delivery & attendance
Timetable: https://bond.edu.au/timetable Delivery mode: Standard Workload items: - Forum: x12 (Total hours: 24) - Forum
- Forum: x12 (Total hours: 24) - Forum
- Personal Study Hours: x12 (Total hours: 72) - Recommended study time & reviewing materials
Attendance and learning activities: Attendance at all class sessions is expected. Students are expected to notify the instructor of any absences with as much advance notice as possible. BBS uses a self and peer-evaluation system to support students engaged in group-based assessments. Students are expected to provide this feedback in a timely fashion as part of their assessment. The information gathered is used by the educator as partial evidence of equitable contributions by all group members and helps to determine individual marks for group assessments. -
Resources
Prescribed resources: No Prescribed resources.
After enrolment, students can check the Books and Tools area in iLearn for the full Resource List.iLearn@Bond & Email: Class recordings: The primary workload items for this subject will be recorded for the purpose of revision.
These recordings are not a substitute for attending classes. Students are encouraged to attend all sessions as there may be instances where a session is not recorded due to the presence of a guest speaker, the inclusion of sensitive or protected content, or technical issues. Students are advised not to rely solely on these recordings for revision.
See the Recording policy for further details.
| Academic unit: | Bond Business School |
|---|---|
| Subject code: | HRTM12-215 |
| Subject title: | Digital Innovation in Tourism |
| Subject level: | Undergraduate |
| Semester/Year: | September 2026 |
| Credit points: | 10.000 |
| Timetable: | https://bond.edu.au/timetable |
|---|---|
| Delivery mode: | Standard |
| Workload items: |
|
| Attendance and learning activities: | Attendance at all class sessions is expected. Students are expected to notify the instructor of any absences with as much advance notice as possible. BBS uses a self and peer-evaluation system to support students engaged in group-based assessments. Students are expected to provide this feedback in a timely fashion as part of their assessment. The information gathered is used by the educator as partial evidence of equitable contributions by all group members and helps to determine individual marks for group assessments. |
| Prescribed resources: | No Prescribed resources. After enrolment, students can check the Books and Tools area in iLearn for the full Resource List. |
|---|---|
| iLearn@Bond & Email: | |
| Class recordings: | The primary workload items for this subject will be recorded for the purpose of revision. These recordings are not a substitute for attending classes. Students are encouraged to attend all sessions as there may be instances where a session is not recorded due to the presence of a guest speaker, the inclusion of sensitive or protected content, or technical issues. Students are advised not to rely solely on these recordings for revision. See the Recording policy for further details. |
Enrolment requirements
| Requisites: |
Nil |
|---|---|
| Restrictions: |
Nil |
Assurance of learning
Assurance of Learning means that universities take responsibility for creating, monitoring and updating curriculum, teaching and assessment so that students graduate with the knowledge, skills and attributes they need for employability and/or further study.
At Bond University, we carefully develop subject and program outcomes to ensure that student learning in each subject contributes to the whole student experience. Students are encouraged to carefully read and consider subject and program outcomes as combined elements.
Program Learning Outcomes (PLOs)
Program Learning Outcomes provide a broad and measurable set of standards that incorporate a range of knowledge and skills that will be achieved on completion of the program. If you are undertaking this subject as part of a degree program, you should refer to the relevant degree program outcomes and graduate attributes as they relate to this subject.
Subject Learning Outcomes (SLOs)
On successful completion of this subject the learner will be able to:
- Describe key factors tourism operators should consider in their digital innovation strategy.
- Explain the impact of a range of technologies on tourist behaviour and business operators.
- Evaluate the effectiveness and limitations of digital tourism technologies from an end-user perspective.
- Discuss the risks and ethical issues associated with digital technologies along with how these can be responsibly managed.
- Recommend digital technology solutions to address a problem or improve the end user experience for tourists and/or tourism operators.
- Communicate key issues and/or recommendations regarding digital innovation effectively using appropriate professional formats.
Generative Artificial Intelligence in Assessment
The University acknowledges that Generative Artificial Intelligence (Gen-AI) tools are an important facet of contemporary life. Their use in assessment is considered in line with students’ development of the skills and knowledge which demonstrate learning outcomes and underpin study and career success. Instructions on the use of Gen-AI are given for each assessment task; it is your responsibility to adhere to these instructions.
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Assessment details
Type Task % Timing* Outcomes assessed AI category Computer-aided Test (Closed) A closed book test of key concepts, frameworks and issues from classes in Weeks 1-3. 15.00% Week 5 1, 2, 4 Written Report Students will write a report which evaluates the effectiveness of one or more digital application(s) of their choice, relevant to the tourism industry. 25.00% Week 7 2, 3, 4 Oral Pitch An oral pitch delivered by students individually. 30.00% Week 12 3, 5, 6 Case Analysis Students will analyse and prepare for three case studies prior to relevant classes. They will then contribute to class discussions about each case and ultimately make recommendations relevant to the context of each case. 30.00% Ongoing 1, 2, 3, 4, 5, 6 - * Assessment timing is indicative of the week that the assessment is due or begins (where conducted over multiple weeks), and is based on the standard University academic calendar
- C = Students must reach a level of competency to successfully complete this assessment.
AI Categories
Ai Prohibited: Learning to develop AI-free knowledge and skills.
Ai Supported: Learning with the help of AI as directed.
Ai Focussed: Learning AI expertise and mastery as directed.
Refer to the assessment task sheet for specific AI instructions and review the Bond University Gen-AI Guide.
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Assessment criteria
Assessment criteria
High Distinction 85-100 Outstanding or exemplary performance in the following areas: interpretative ability; intellectual initiative in response to questions; mastery of the skills required by the subject, general levels of knowledge and analytic ability or clear thinking. Distinction 75-84 Usually awarded to students whose performance goes well beyond the minimum requirements set for tasks required in assessment, and who perform well in most of the above areas. Credit 65-74 Usually awarded to students whose performance is considered to go beyond the minimum requirements for work set for assessment. Assessable work is typically characterised by a strong performance in some of the capacities listed above. Pass 50-64 Usually awarded to students whose performance meets the requirements set for work provided for assessment. Fail 0-49 Usually awarded to students whose performance is not considered to meet the minimum requirements set for particular tasks. The fail grade may be a result of insufficient preparation, of inattention to assignment guidelines or lack of academic ability. A frequent cause of failure is lack of attention to subject or assignment guidelines. Quality assurance
For the purposes of quality assurance, Bond University conducts an evaluation process to measure and document student assessment as evidence of the extent to which program and subject learning outcomes are achieved. Some examples of student work will be retained for potential research and quality auditing purposes only. Any student work used will be treated confidentially and no student grades will be affected.
| Type | Task | % | Timing* | Outcomes assessed | AI category |
|---|---|---|---|---|---|
| Computer-aided Test (Closed) | A closed book test of key concepts, frameworks and issues from classes in Weeks 1-3. | 15.00% | Week 5 | 1, 2, 4 | |
| Written Report | Students will write a report which evaluates the effectiveness of one or more digital application(s) of their choice, relevant to the tourism industry. | 25.00% | Week 7 | 2, 3, 4 | |
| Oral Pitch | An oral pitch delivered by students individually. | 30.00% | Week 12 | 3, 5, 6 | |
| Case Analysis | Students will analyse and prepare for three case studies prior to relevant classes. They will then contribute to class discussions about each case and ultimately make recommendations relevant to the context of each case. | 30.00% | Ongoing | 1, 2, 3, 4, 5, 6 |
- * Assessment timing is indicative of the week that the assessment is due or begins (where conducted over multiple weeks), and is based on the standard University academic calendar
- C = Students must reach a level of competency to successfully complete this assessment.
AI Categories
Ai Prohibited: Learning to develop AI-free knowledge and skills.
Ai Supported: Learning with the help of AI as directed.
Ai Focussed: Learning AI expertise and mastery as directed.
Refer to the assessment task sheet for specific AI instructions and review the Bond University Gen-AI Guide.
Assessment criteria
| High Distinction | 85-100 | Outstanding or exemplary performance in the following areas: interpretative ability; intellectual initiative in response to questions; mastery of the skills required by the subject, general levels of knowledge and analytic ability or clear thinking. |
|---|---|---|
| Distinction | 75-84 | Usually awarded to students whose performance goes well beyond the minimum requirements set for tasks required in assessment, and who perform well in most of the above areas. |
| Credit | 65-74 | Usually awarded to students whose performance is considered to go beyond the minimum requirements for work set for assessment. Assessable work is typically characterised by a strong performance in some of the capacities listed above. |
| Pass | 50-64 | Usually awarded to students whose performance meets the requirements set for work provided for assessment. |
| Fail | 0-49 | Usually awarded to students whose performance is not considered to meet the minimum requirements set for particular tasks. The fail grade may be a result of insufficient preparation, of inattention to assignment guidelines or lack of academic ability. A frequent cause of failure is lack of attention to subject or assignment guidelines. |
Quality assurance
For the purposes of quality assurance, Bond University conducts an evaluation process to measure and document student assessment as evidence of the extent to which program and subject learning outcomes are achieved. Some examples of student work will be retained for potential research and quality auditing purposes only. Any student work used will be treated confidentially and no student grades will be affected.
Study Information
Policy on late submission and extensions
A late penalty will be applied to all overdue assessment tasks unless an extension is granted by the subject coordinator. The standard penalty will be 10% of marks awarded to that assessment per day late with no assessment to be accepted seven days after the due date. Where a student is granted an extension, the penalty of 10% per day late starts from the new due date.
Additional subject information
As part of the requirements for Business School quality accreditation, the Bond Business School employs an evaluation process to measure and document student assessment as evidence of the extent to which program and subject learning outcomes are achieved. Some examples of student work will be retained for potential research and quality auditing purposes only. Any student work used will be treated confidentially and no student grades will be affected.
Subject curriculum
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Digital Innovation and Experience Design
The role of digital innovations in shaping tourism experiences and operations is introduced. Students will explore frameworks for managing innovation, examine factors that influence technology adoption and diffusion within the industry, and learn techniques for designing and mapping service experiences that enhance customer engagement.
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Responsible adoption of tourism technologies and digital ethics
The risks and ethical considerations associated with digital technologies in tourism and hospitality are explored. Students will learn strategies for responsibly managing digital risks and ethical dilemmas, while exploring the human-technology interface to ensure people remain at the heart of service experiences.
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Digital Destination Marketing
Developing effective social media strategies for tourism brands to engage audiences and build loyalty is essential! Students will explore techniques for SEO to optimize trip planning and examine the role of user-generated content in shaping online reputation and trust within the tourism sector.
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The AI Revolution: What it means for tourism
The core principles of artificial intelligence are introduced along with the ways it is transforming industries worldwide, including tourism. Students will examine the drivers behind AI adoption, its benefits for innovation and efficiency, and the ethical, social, and operational challenges it presents.
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Digital tools for travel itinerary planning
The use of AI-powered tools in pre-trip travel planning is explored, including features in online travel agency platforms, AI-driven recommendation systems, and price prediction technologies. Students will also examine how virtual reality applications enhance the pre-visit phase by enabling immersive destination previews and influencing traveller’ decision-making.
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Enhancing the tourist experience through technology
This topic explores digital tools that enhance the visitor experience, including destination and travel apps that support seamless journeys. Students will examine the role of AI technologies such as chatbots and translation tools in creating personalised interactions and investigate how virtual reality applications enrich site interpretation and cultural storytelling.
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Smart destinations
The concept of ‘smart’ destinations is introduced along with how smart technologies can support both visitor experiences and destination management. Students will explore smart mobility solutions for real-time travel planning and examine the role of the Internet of Things (IoT) in creating connected, personalized experiences for travellers.
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Digital technologies in tourism at work
This topic examines the role of digital tools in transforming workplace operations within tourism and hospitality. It will consider various technologies used by tourism employees to maximise work efficiencies. As well as considering existing operational technologies, students will also explore how newer AI technologies, including intelligent agents and recruitment tools, can enhance workforce productivity and decision-making while addressing emerging challenges in digital workforce management.
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Digital Intelligence for Tourism
The power of predictive analytics in shaping tourism strategies and decision-making is considered. Students will explore AI-driven tools for demand forecasting and dynamic pricing, as well as sentiment analysis techniques that help businesses understand traveller perceptions and improve service delivery.
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Future trends and innovation in tourism
This final topic explores emerging technology trends and innovations shaping the future of tourism and hospitality. Students will also consolidate their learning and prepare for their final presentations.