ACCY231 2025 Final Assessment - Business Research Report
Important: Assessment 3 - Business Research Report is the final assessment for this subject.
The Minimum Performance Requirement applies:
To be eligible to pass this subject, students must complete all assessment tasks for this subject. In addition, you must achieve a total mark of 50% or over for all assessment tasks and obtain a minimum of 50% in the final examination or major piece of assessment (where there is no final exam).
In accordance with the General Course Rules where a student gains a mark of 50 or greater and does not meet the specified level in an assessment task required to pass the subject, a Technical Fail (TF) grade for the subject will appear on their Academic Transcript. Where a Technical Fail is given, the following applies:
• Failure of the subject;
• a TF without a mark will be granted;
• a TF will be presented on the student's academic transcript;
• The allocated mark of 49 will be used as the WAM calculation for subjects at all levels.
Submission and Academic Consideration:
The final assessment needs to be submitted via links in the subject’s Moodle sites in two (2) parts:
1. submit the business report in word format (.docx) via Turnitin
2. submit the dashboard in excel format (.xlsx) via a separate file drop box
The due date for Assessment 3 is Saturday 15 Nov (submission link closed at 5:00pm). For late submission, an academic extension must be applied and approved. Reasonable grounds for consideration must be clearly stated in the applications. Final grades will be released later for late submissions. Late submission without approved academic consideration will not be accepted and a zero will be awarded for the assessment.
Post-exam Consultations:
Post-exam consultation time will be announced in Moodle and via SOLS email once confirmed, after the UOW’s official release of 2025 Spring results.
Background
Big data technology has transformed industries beyond finance, enabling firms to harness vast datasets for innovation, efficiency, and competitiveness. By applying advanced analytics, machine learning, and AI-driven models, organizations in sectors such as retail, healthcare, and manufacturing can optimize supply chains, predict customer needs, and improve product development (George et al., 2016). For example, big data allows retailers to personalize marketing strategies, hospitals to enhance diagnostic accuracy, and manufacturers to implement predictive maintenance, thereby minimizing downtime and costs (Wamba et al., 2017).
The ongoing wave of digital transformation is driving financial firms to invest heavily in cloud computing, Internet of Things (IoT), and blockchain applications to strengthen operational agility and customer engagement (Akter et al., 2019). These technologies not only streamline business processes but also create new revenue models and competitive advantages in increasingly data-driven markets. Moreover, automation and AI reduce reliance on manual tasks, improving efficiency and scalability. At the same time, data-driven insights empower firms to make more informed strategic decisions, manage risks proactively, and deliver superior customer experiences—ultimately boosting profitability, customer loyalty, and long-term sustainability.
In addition to improving financial performance, digitalisation can play a crucial role in enhancing a firm's Environmental, Social, and Governance (ESG) performance (Lu et al., 2024). By leveraging digital technologies, such as cloud-based solutions and big data analytics, firms can monitor and reduce their carbon footprint and optimize energy consumption. For example, the adoption of paperless operations and digital reporting systems reduces waste and promotes sustainability. Furthermore, digital platforms enable better transparency in governance practices and compliance with regulatory frameworks. On the social front, digital tools can enhance customer data protection and cybersecurity measures, thereby strengthening customer trust. Through digital innovation, firms can not only achieve operational efficiency but also contribute to sustainable development and corporate social responsibility.
References:
Akter, S., Bandara, R., Hani, U., Wamba, S. F., Foropon, C., & Papadopoulos, T. (2019). Analytics-based decision-making for service systems: A qualitative study and agenda for future research. International Journal of Information Management, 48, 85–95.
George, G., Osinga, E. C., Lavie, D., & Scott, B. A. (2016). Big data and data science methods for management research. Academy of Management Journal, 59(5), 1493–1507.
Lu, Y., Xu, C., Zhu, B., & Sun, Y. (2024). Digitalization transformation and ESG performance: Evidence from China. Business Strategy and the Environment, 33(2), 352-368.
Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J. F., Dubey, R., & Childe, S. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356–365.
Business Research Report Instructions
Topic: Australian Firm’s Digitalisation, Financial Performance, and ESG Rating.
Data Collection:
1. Conduct research on a ASX firm below, based by the LAST DIGIT of your student number:
|
No.
|
Company Name
|
ASX
Code
|
Main Business
|
|
1
|
AGL Energy
|
AGL
|
Utilities
|
|
2
|
BHP Group
|
BHP
|
Material/Natural Resources
|
|
3
|
BRAMBLES
|
BXB
|
Supply-chain Logistics
|
|
4
|
CSL
|
CSL
|
Pharmaceutical/Biotech
|
|
5
|
CSR
|
CSR
|
Construction
|
|
6
|
HARVEY NORMAN HOLDINGS
|
HVN
|
Retail
|
|
7
|
QANTAS AIRWAYS
|
QAN
|
Transportation
|
|
8
|
RESMED CDI
|
RMD
|
Healthcare/Medical Devices
|
|
9
|
TELSTRA GROUP
|
TLS
|
Telecommunication
|
|
10
|
WOOLWORTHS GROUP
|
WOW
|
Consumer Staples
|
2. Conduct research to gather information in relation to the firm’s innovation & digital transformation (you can find information in annual reports, the company’s website, announcements, news articles, or other reports).
3. Extract the company’s 2017 – 2023 financial data from the DatAnalysis database (accessible from UOW library portal). ESG Rating data from the Refinitiv database will be provided (accessible from the Moodle Site).
Report Content:
1. Introduction, including the purpose and the scope of the report
2. The firm’s digitalisation process – e.g., whether new technologies are adopted, or new models are used to improve product sells or services.
3. A one-page Dashboard (vertical or horizontal), highlighting the company’s key financial and ESG performances from 2017 to 2023. (Techniques to obtain data, preparing the data in excel, and creating a Dashboard using excel will be covered in week 6-12 tutorials). The Dashboard needs to be produced using Microsoft Excel. A screenshot of the Dashboard needs to be included in the Business Report, the Excel workbook will need to be submitted separately.
• The dashboard should contain a variety of tables and charts (between 4 -6 are appropriate)
• It should have some interactivity, and clearly presenting trends and patterns.
4. Discuss whether the firm’s financial performance and ESG ratings benefited from the digitalisation approaches, by referring to the dashboard, as well as using other supportive evidence.
5. Conclusions and recommendations
Formatting Requirements
Length: 2,500 words (+/- 10%), excluding references and appendixes. Please include the word count at the end of the report.
Font: Size 12, Times New Roman, Arial, or Calibri
Linespacing: 1.5
For a suggested format of a Business Research Report, please check the Learning Development website:
https://documents.uow.edu.au/content/groups/public/@web/@stsv/@ld/documents/doc/uow195 620.pdf
Please appropriately reference all sources, including academic articles, media reports, and company reports or websites. You CANNOT use Wikipedia, Investopedia, or uncredited website sources of a similar nature. Please check UOW Library website for UOW Harvard Referencing Guide
http://uow.libguides.com/refcite/uowharvard
Not sure what charts to use? Checkhttps://datavizcatalogue.com/
The use of Generative AI tools, including ChatGPT, Bard, or any other AI-based content creation platforms, to assist in preparing the final assessment is strictly prohibited. All submitted work must reflect the student's original thinking, research, and analytical skills. Any content generated through AI will be considered a violation of academic integrity and may lead to serious consequences, including plagiarism penalties or disciplinary action in accordance with the university's academic misconduct policy. Students are encouraged to seek support from instructors or academic resources if they require assistance with their assessments.
Marking Criteria
85% - 100%: An outstanding report. The student will have performed a detailed analysis of the problem area. There should be clear evidence of relevant background research that is rigorous and in- depth. The report should be superbly organised, presented, and lucidly written.
70% - 84%: Students will show a thorough understanding and appreciation of the investigated problem. The student will have performed a detailed analysis of the problem area. There should be good evidence of relevant background research. The report should display excellent organisational and presentational skills.
60% - 69%: Students will show a clear understanding of the technical and professional issues involved and have analysed the problem area. There should be evidence of relevant background research. Some issues may have been overlooked. The report should be organised and written to a reasonable standard.
50% - 59%: The report should demonstrate that the student has some familiarity with the knowledge area. The presentation and organization of the report should be reasonably clear. There may be some signs of weakness, but overall the grasp of the topic should be sound.
40% - 49%: The report will indicate a basic understanding of the investigated problem and how to organize and present the work in the report, but will not have gone much beyond this. There may well be signs of confusion.
30% - 39%: There should be some work towards understanding the problem area, but significant issues are likely to be neglected. There may be significant errors or misconceptions in the report.
15% - 29%: The report may contain some correct and relevant material, but most issues are neglected or are covered incorrectly. There should be some signs of appreciation of the report requirements.
0% - 14%: Very little or nothing that is correct and relevant and there is no real appreciation of the report requirements.