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Grace McCarthy
Researcher at University of Wollongong
Publications - 65
Citations - 1101
Grace McCarthy is an academic researcher from University of Wollongong. The author has contributed to research in topics: Coaching & Context (language use). The author has an hindex of 17, co-authored 62 publications receiving 825 citations. Previous affiliations of Grace McCarthy include University of Manchester.
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Transforming business using digital innovations: the application of AI, blockchain, cloud and data analytics
TL;DR: This study explores digital business transformation through the lens of four emerging technology fields: artificial intelligence, blockchain, cloud and data analytics (i.e., ABCD), finding wide-reaching and diverse applications among a variety of vertical sectors.
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Using Internet based paraphrasing tools: Original work, patchwriting or facilitated plagiarism?
Ann M Rogerson,Grace McCarthy +1 more
TL;DR: Students placing trust in online paraphrasing tools as an easy way of complying with the requirement for originality in submissions are at risk in terms of the quality of the output generated and possibly of not achieving the learning outcomes as they may not fully understand the information they have compiled.
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Managerial coaching: challenges, opportunities and training
Grace McCarthy,Julia Milner +1 more
TL;DR: In this article, the authors provide insights into the growing practice of managerial coaching and highlight the importance of adequate training of managers in coaching skills as an important issue for organizations to tackle.
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Algorithmic bias in data-driven innovation in the age of AI
Shahriar Akter,Grace McCarthy,Shahriar Sajib,Katina Michael,Yogesh K. Dwivedi,Yogesh K. Dwivedi,John D'Ambra,Kathy Ning Shen +7 more
TL;DR: In this paper, the authors explore the sources of algorithmic biases across the data-driven innovation process using a systematic literature review, thematic analysis and a case study on the Robo-Debt scheme in Australia.
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Intelligent decision system and its application in business innovation self assessment
TL;DR: It is demonstrated that IDS is a flexible tool capable of handling different types of data in self-assessment, including uncertain and incomplete data, and providing a wide range of information including scores, performance diversity, strength and weakness profile and graphics.