Discovery Early Career Researcher Award - Grant ID: DE220101597
Funder
Australian Research Council
Funding Amount
$360,264.00
Summary
Empowering Users to Protect their Personal Privacy on Social Media. This Information Systems project aims to take a bold approach to finally overcome the paradoxical inertia of people who care about their privacy but do not protect it. This project integrates different psychological theories proposing a paradigm shift expecting to generate new knowledge in privacy research, which can currently neither explain nor provide means to overcome the vexing issue. Expected outcomes of the project includ ....Empowering Users to Protect their Personal Privacy on Social Media. This Information Systems project aims to take a bold approach to finally overcome the paradoxical inertia of people who care about their privacy but do not protect it. This project integrates different psychological theories proposing a paradigm shift expecting to generate new knowledge in privacy research, which can currently neither explain nor provide means to overcome the vexing issue. Expected outcomes of the project include a privacy behaviour model (PIM), privacy training program and system design solutions. This should offer substantial benefits as it integrates privacy research and guides behavioural models beyond Information Systems, provide means to solve the paradox, guide legislation and the privacy consent mechanism design.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160100548
Funder
Australian Research Council
Funding Amount
$298,000.00
Summary
Conceptualizing and Measuring Digital Service Quality. The project aims to understand customer quality perceptions of digital services, and the factors, such as customer's own skill-levels, that help people to optimise their experiences. Public and private organisations are pushing customers from face-to-face to digital service and self-service models, sometimes offering no alternatives (eg many travel visas can only be obtained online). E-commerce research suggests up to 80 per cent of service ....Conceptualizing and Measuring Digital Service Quality. The project aims to understand customer quality perceptions of digital services, and the factors, such as customer's own skill-levels, that help people to optimise their experiences. Public and private organisations are pushing customers from face-to-face to digital service and self-service models, sometimes offering no alternatives (eg many travel visas can only be obtained online). E-commerce research suggests up to 80 per cent of service users will sometimes struggle with online transactions. In the worst case, people may be excluded from accessing important services. Insights from this research are expected to help public and private organisations to deliver high-quality digital services that empower service users.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240100269
Funder
Australian Research Council
Funding Amount
$448,117.00
Summary
Maintaining Human Expertise in an AI-driven World. While information systems with artificial intelligence are increasingly used to support or automate work tasks, this can come at a cost to the development and retention of essential skills in workers. Skill erosion can jeopardise safety and fairness in contexts where humans' skills are needed. This innovative project leverages systems thinking, case studies and action design research to investigate how leveraging artificial intelligence shapes w ....Maintaining Human Expertise in an AI-driven World. While information systems with artificial intelligence are increasingly used to support or automate work tasks, this can come at a cost to the development and retention of essential skills in workers. Skill erosion can jeopardise safety and fairness in contexts where humans' skills are needed. This innovative project leverages systems thinking, case studies and action design research to investigate how leveraging artificial intelligence shapes workers' skills. Its expected outcomes include a new systems theory of skill erosion and organisational guidelines for managing artificial intelligence. These can help organisations maximise human potential by striking a balance between relying on automation and maintaining workers' skills. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120100776
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Designing process models to support communication and decision-making. This project will develop guidelines to assist analysts in describing business processes by identifying theoretical factors of process model quality. The outcomes will make it easier to make informed decisions about process re-design, business innovation or software development, thus contributing to project cost savings and better processes.
Discovery Early Career Researcher Award - Grant ID: DE210100160
Funder
Australian Research Council
Funding Amount
$423,000.00
Summary
Information Extraction from Large-scale Low-quality Data. Information extraction which identifies entities and relations from data is a key technology that lays the foundation for understanding the semantics of data. This project aims to investigate the problem of information extraction by innovatively exploring the informality and temporal evolution of data. It expects to develop novel techniques for reliable, efficient, and scalable information discovery from large-scale low-quality data. Expe ....Information Extraction from Large-scale Low-quality Data. Information extraction which identifies entities and relations from data is a key technology that lays the foundation for understanding the semantics of data. This project aims to investigate the problem of information extraction by innovatively exploring the informality and temporal evolution of data. It expects to develop novel techniques for reliable, efficient, and scalable information discovery from large-scale low-quality data. Expected outcomes include a set of collective, contextualised, and temporal-aware algorithms for information extraction and integration, built on top of effective indexing and in-parallel processing. This project is anticipated to benefit a considerable number of data-driven intelligence-based applications.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140100215
Funder
Australian Research Council
Funding Amount
$394,752.00
Summary
Searching Activity Trajectories for Intention Oriented Recommendations. The ubiquitous fusion of social network services and Global Positioning System-enabled mobile devices has generated large-scale activity trajectory data representing the footprint of people's daily activities. It presents an unprecedented opportunity to build highly intelligent recommendation systems. Existing approaches that merely focus on the location aspect of trajectories are limited in their ability to understand genui ....Searching Activity Trajectories for Intention Oriented Recommendations. The ubiquitous fusion of social network services and Global Positioning System-enabled mobile devices has generated large-scale activity trajectory data representing the footprint of people's daily activities. It presents an unprecedented opportunity to build highly intelligent recommendation systems. Existing approaches that merely focus on the location aspect of trajectories are limited in their ability to understand genuine preferences from travel histories, due to lack of consideration for activity information as well as the associated semantics and context. This project aims to address these issues and provide effective recommendations by considering both users’ intention and collective behavioural knowledge inferred from activity trajectories.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230101033
Funder
Australian Research Council
Funding Amount
$420,154.00
Summary
Scalable and Lightweight On-Device Recommender Systems. This project aims to address the resource-intensive and non-resilient nature of existing cloud-based personalised recommendation services. This project expects to generate new knowledge in the intersection of on-device machine learning and recommender systems. The expected outcomes include a novel auto-deployment platform that can efficiently customise a model for each user device's configuration, supporting on-device recommendation and mod ....Scalable and Lightweight On-Device Recommender Systems. This project aims to address the resource-intensive and non-resilient nature of existing cloud-based personalised recommendation services. This project expects to generate new knowledge in the intersection of on-device machine learning and recommender systems. The expected outcomes include a novel auto-deployment platform that can efficiently customise a model for each user device's configuration, supporting on-device recommendation and model updates with tiny computational footprints. The benefits of these outcomes will position Australia at the forefront of AI and give numerous businesses the tools needed to deploy innovative business systems with a secure and cost-effective advantage.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160100509
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Effective Recommendation for Web of Things. This project seeks to generate novel techniques for the efficient recommendation of things by the smart use of information generated from the ‘Internet of things’. The ‘Internet of things’ will connect billions of physical things over the web, which will offer exciting capabilities to improve the quality of human lives. This project focuses on effective recommendation of things of interest, and aims to develop new techniques and a set of software tools ....Effective Recommendation for Web of Things. This project seeks to generate novel techniques for the efficient recommendation of things by the smart use of information generated from the ‘Internet of things’. The ‘Internet of things’ will connect billions of physical things over the web, which will offer exciting capabilities to improve the quality of human lives. This project focuses on effective recommendation of things of interest, and aims to develop new techniques and a set of software tools for effectively and proactively discovering and recommending things. The result of this project may underpin applications (eg smart cities) that will contribute to Australian society and the national economy.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE180100251
Funder
Australian Research Council
Funding Amount
$368,446.00
Summary
Trust-aware internet of things service recommendation. This project aims to develop innovative techniques and tools to recommend Internet of Things resources as services for trustworthy and cost-effective applications. Internet of Things connects billions of physical things over the Web, offering exciting opportunities to improve life quality and reshape human society. The project is expected to underpin innovative applications like smart home, urban computing, and mobile social sensing, which c ....Trust-aware internet of things service recommendation. This project aims to develop innovative techniques and tools to recommend Internet of Things resources as services for trustworthy and cost-effective applications. Internet of Things connects billions of physical things over the Web, offering exciting opportunities to improve life quality and reshape human society. The project is expected to underpin innovative applications like smart home, urban computing, and mobile social sensing, which can significantly contribute to Australian society and the national economy. It also holds the potential to place Australia at the forefront of research and development in the vibrant and growing area of trustworthy Internet of Things.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240101364
Funder
Australian Research Council
Funding Amount
$445,591.00
Summary
Governing Industrial Data Ecosystems: Open Innovation in a Digital Economy. This project aims to investigate how governance mechanisms incentivise multilateral data-sharing to enable open innovation in industrial data ecosystems. Based on a rigorous multi-method study at ecosystem, firm and managerial levels, a framework of generative open innovation to govern multilateral data sharing will be developed. By addressing data-sharing barriers at all levels, the framework helps create collective val ....Governing Industrial Data Ecosystems: Open Innovation in a Digital Economy. This project aims to investigate how governance mechanisms incentivise multilateral data-sharing to enable open innovation in industrial data ecosystems. Based on a rigorous multi-method study at ecosystem, firm and managerial levels, a framework of generative open innovation to govern multilateral data sharing will be developed. By addressing data-sharing barriers at all levels, the framework helps create collective value at the ecosystem level and capture a portion of that value at the firm and managerial levels. This should enable participants in industrial data ecosystems to share data confidently and unlock the full potential of open innovation for Australia’s digital economy, with estimated benefits of $315bn over the next decade. Read moreRead less