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Project Leads and Team
Funding Information
Project BackgroundEmployers increasingly use online job advertisements and social networking sites to communicate their skill requirements. These postings offer a rich source of up-to-date information about the competencies needed in the accounting and finance professions. Traditional employer surveys, while useful, are limited by voluntary participation and predefined competency lists, making them less effective at capturing emerging digital skill requirements. This project analyses online job advertisements from Hong Kong and Singapore to gain an updated understanding of the knowledge and skills employers expect from both fresh graduates and experienced professionals in the fields of accounting and finance. Project AimThe project aims to identify the professional knowledge and skills currently in demand for accounting and finance roles by analysing large samples of online job advertisements using natural language processing (NLP) techniques. |
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Prof. Shaojun Zhang Associate Professor, School of Accounting and Finance |
Project Objectives / Research Plan
- Analyse three samples of online job advertisements:
- PolyU Job Board postings (2019–2023)
- Quarterly samples from a major recruitment website (February, May, August, November 2023)
- A purchased dataset of Singapore job vacancies (2012–2022)
- Apply NLP techniques to identify the skills employers specify in accounting and finance job advertisements.
- Compare skill requirements between Hong Kong and Singapore.
- Compare skill requirements between experienced professionals and fresh graduates.
- Identify trends in digital skill requirements over time across the three samples.
Project Progress
- The three sets of samples of job advertisements have been collected.
- NLP analysis has been applied to identify skills in the text.
- Findings were presented at the 38th Education and Student Development Salon on 30 September 2025.
Findings
- Demand for generic competencies and technical skills remains relatively stable over time.
- Between 20% and 30% of job postings across all samples require digital skills.
- The Singapore dataset shows a gradual long term increase in demand for digital skills.
- Digital skill requirements differ between the Hong Kong/Singapore samples, and the PolyU sample. This is because many jobs in the Hong Kong/Singapore samples require skills mainly acquired through work experience and were advertised to experienced candidates rather than fresh graduates.
- Accounting and finance roles require substantially different sets of digital skills.
- Skill requirements shift gradually over time but can change abruptly, as seen in 2020.
Implications
- The findings provide updated knowledge about employer expectations for accounting and finance professionals in Hong Kong and Singapore.
- The results complement traditional employer surveys and offer useful insights for tertiary institutions designing curricula and educational programmes to strengthen students’ skill sets for the digital economy.
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Project Leads and Team
Funding Information
Project BackgroundArtificial intelligence and machine learning are increasingly central to business applications. Firms must decide how to acquire the capabilities needed to develop machine learning algorithms. Traditionally, organisations either outsource development to vendors or build in house teams. This project examines a third channel: algorithm markets. Algorithm markets exist in two forms. In seller oriented markets, developers post their algorithms or models for customers to adopt; while in buyer oriented markets, customers post their problems and data for developers to solve. These markets differ from traditional commodities or crowdsourced services because algorithms often require customisation and operate under unique constraints. Project AimTo manage algorithm markets effectively, this project will study mechanisms of these algorithm markets. In particular, the project aims to investigate how code, data, and pre trained models influence the operations of in algorithm markets. |
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Prof. Xin Li Professor, Department of Management and Marketing |
Project Objectives / Research Plan
- Examine how code representation affects algorithm consumer behaviour.
- Analyse how datasets influence algorithm developer behaviour.
- Explore how pre-trained models affect the dynamics of both consumers and developers.
Project Progress
- The project has been approved but has not yet started.
