Unit outline_

EMBA6006: Challenging Business Models

Intensive April - May, 2025 [Block mode] - Castlereagh St, Sydney

The biggest challenge facing most businesses today is that they don't anticipate the changes in their market environment that fundamentally threaten the way they do what they do. This applies to the government sector and not-for-profits as much as it does to for-profit businesses. How do businesses ensure that they renew themselves before they become obsolete This unit of study is the culmination of the previous four Executive MBA units of study, combining entering new markets, incorporating cutting edge technology and using leadership and management foundations to challenge existing business models. We look at existing businesses that have managed this transformation well and examine those that haven't. Students obtain an understanding of how organisations can adapt to disruption. We examine a variety of technological advances such as robotics, nanotechnology, machine learning and artificial intelligence to see how they have transformed business models. We examine how to access, analyse and utilise the massive amount of data that is available. We also examine the impact of technology on the workforce, and the future of work. A major project on a progressive organisation enables students to apply what they have learned to this organisation's transformation.The module takes place in two locations relevant to the chosen project.

Unit details and rules

Academic unit Management Education
Credit points 12
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

EMBA6000

Available to study abroad and exchange students

No

Teaching staff

Coordinator Massimo Garbuio, massimo.garbuio@sydney.edu.au
The census date for this unit availability is 2 May 2025
Type Description Weight Due Length
Presentation group assignment AI Allowed Interim team project presentation
Oral presentation
10% Week 02
Due date: 12 May 2025 at 09:00

Closing date: 12 May 2025
15 Minutes
Outcomes assessed: LO1 LO2 LO4
Presentation group assignment AI Allowed Final team project presentation
Oral presentation
40% Week 02
Due date: 15 May 2025 at 23:59

Closing date: 15 May 2025
25 Minutes
Outcomes assessed: LO1 LO2 LO4
Assignment AI Allowed Reflective report
Report
50% Week 08
Due date: 09 Jun 2025 at 23:59

Closing date: 14 Jun 2025
4000 words
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6
group assignment = group assignment ?
AI allowed = AI allowed ?

Assessment summary

  • Interim team project presentation: Each team will present project analyses and conclusions to date, previewing the presentation they are planning for the final day of the module. The focus at this stage will be on explaining:  

1.    the underlying business problem(s) and opportunities identified 
2.    the process the team has followed thus far, the information gathered, and next steps. 

  • Final team project presentation: The project will involve pre-departure deskwork, research on the topic prior to the unit, on-the-ground analyses during the two-week module, and preparation of a presentation. Presentations should overview the project and indicate its scope, summarize the analyses completed, and suggest key conclusions and insights gained. 
    A 'Presentation Pack' summarising the team's research, analysis and recommendations should be included in the submission in the form of an Appendix/Data Pack.

  • Reflective report: In this report you are asked to reflect on one or more of the key themes that emerged from the module, assess their relevance to the leadership challenges that you face, and explain how the experience of this module has influenced the way that you will approach these challenges in your workplace.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 

Distinction

75 - 84

Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.

Credit

65 - 74

Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school.

Pass

50 - 64

Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Use of generative artificial intelligence (AI) and automated writing tools

Except for supervised exams or in-semester tests, you may use generative AI and automated writing tools in assessments unless expressly prohibited by your unit coordinator. 

For exams and in-semester tests, the use of AI and automated writing tools is not allowed unless expressly permitted in the assessment instructions. 

The icons in the assessment table above indicate whether AI is allowed – whether full AI, or only some AI (the latter is referred to as “AI restricted”). If no icon is shown, AI use is not permitted at all for the task. Refer to Canvas for full instructions on assessment tasks for this unit. 

Your final submission must be your own, original work. You must acknowledge any use of automated writing tools or generative AI, and any material generated that you include in your final submission must be properly referenced. You may be required to submit generative AI inputs and outputs that you used during your assessment process, or drafts of your original work. Inappropriate use of generative AI is considered a breach of the Academic Integrity Policy and penalties may apply. 

The Current Students website provides information on artificial intelligence in assessments. For help on how to correctly acknowledge the use of AI, please refer to the  AI in Education Canvas site

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

According to University and Business School policies.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

WK Topic Learning activity Learning outcomes
Week 01 Note the following schedule is subject to change. Sunday 4 May: AM: Intro to Unit – Nagoya and the University of Sydney, Digital vs. Digitized; PM: 1.1 Digital Business Models, Project Work Block teaching (9 hr) LO1 LO2 LO3 LO4
Monday 5 May: Kyoto cultural visit Block teaching (9 hr) LO5
Tuesday 6 May: AM: 1.2 Pathways to Future Ready, Panel with a Nagoya academic and a practitioner; PM: Extended Digital Business Model discussions Block teaching (9 hr) LO1 LO2 LO3 LO4
Wednesday 7 May: AM: Geopolitical session (Nagoya); PM: Company visits Block teaching (9 hr) LO1 LO2 LO3 LO5
Thursday 8 May: Company visits Block teaching (9 hr) LO1 LO2 LO3 LO4 LO5
Friday 9 May: AM: 5.1 The Aging Workforce (Nagoya), 5.2 The Future Ready Workforce; PM: 5.3 Applied cases and diagnostic, 5.4 How do workforce regulations in Japan impact the ability for firms to build a future-ready workforce Block teaching (9 hr) LO1 LO2 LO3 LO4 LO5
Saturday 10 May: AM: Travel; PM: Project work Block teaching (9 hr) LO1 LO2 LO3 LO4 LO5
Week 02 Monday 12 May: AM: Interim Presentations; PM: Spotlight Block teaching (9 hr) LO1 LO2 LO3 LO4 LO5
Tuesday 13 May: AM: Entrepreneurship in Japan; PM: Project Work Block teaching (9 hr) LO1 LO2 LO3 LO4 LO5
Wednesday 14 May: AM: Entrepreneurship in Japan; PM: Project Work Block teaching (9 hr) LO1 LO2 LO3 LO4 LO5
Thursday 15 May: Project Work Block teaching (9 hr) LO1 LO2 LO3 LO4 LO5 LO6
Friday 16 May: AM: Final Presentations; PM: Debrief and student feedback Block teaching (9 hr) LO1 LO2 LO3 LO4 LO5 LO6

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 12 credit point unit, this equates to roughly 240-300 hours of student effort in total.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. understand the characteristics of an industry that is mature and in decline and how this is linked to under-performance in an organisation
  • LO2. identify some of the ways in which managers and leaders can generate turnaround and renewal in an industry
  • LO3. examine an industry in detail from buyer and supplier point of view
  • LO4. be able to develop customer-centric responses to business challenges
  • LO5. demonstrate ability to work effectively with companies from a different culture and worldview
  • LO6. draw parallels between the current and future challenges facing an industry examined during the module and the strategic challenges you are facing or will face in your professional life.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

No changes have been made since this unit was last offered.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

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