ORCID Profile
0000-0002-9572-812X
Current Organisations
Università degli Studi di Palermo
,
University of Melbourne
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Business and Management | Investment and Risk Management | Corporate Governance and Stakeholder Engagement | Auditing and Accountability | Accounting, Auditing and Accountability | Health Information Systems (Incl. Surveillance) | Business Information Systems (Incl. Data Processing) | Organisational Behaviour | Innovation And Technology Management
ANZSRC Socio-Economic Objective (SEO)
Technological and organisational innovation | Management and productivity issues not elsewhere classified | Finance and investment services | Health and support services not elsewhere classified | Finance Services | Investment Services (excl. Superannuation) | Rural health |
Related Links
Publications
On the Role of Process Mining in Business Process Compliance
Publisher: Elsevier BV
Date: 2022
DOI: 10.2139/SSRN.4081558
Is Financial Reporting Still Useful? Australian Evidence
Publisher: Wiley
Date: 03-2019
DOI: 10.1111/ABAC.12152
Towards an integrated view of IT value measurement
Publisher: Elsevier BV
Date: 03-2010
Why did they do that? Variability in routine transactions
Publisher: Emerald
Date: 27-02-2009
DOI: 10.1108/09593840910937517
Abstract: The purpose of this paper is to provide a frank reflection on the authors' journey in applying social theory to understand the routine use of a transaction‐processing system in a rich field context. Inspired by a perplexing initial observation, the program of research moved quickly from one of more traditional positivist methods (experiments and surveys) to case study research. The case study involved observation and comparative analysis of the routine use of a reservation system across a large franchised accommodation chain. As a reflective essay, the key findings relate to the research process itself. The essence of the findings is that applying social theory is itself a social process. The paper finds that insight can come from understanding the routine use of IT as a social artefact, not just from studying crises or latest innovations.
Towards Ethical Big Data Artifacts: A Conceptual Design
Publisher: Hawaii International Conference on System Sciences
Date: 2018
Diagnosing decision quality
Publisher: Elsevier BV
Date: 04-2008
Cognition Matters: Enduring Questions in Cognitive IS Research
Publisher: Association for Information Systems
Date: 04-2012
DOI: 10.17705/1JAIS.00290
Enablers and Mechanisms: Practices for Achieving Synergy with Business Analytics
Publisher: Hawaii International Conference on System Sciences
Date: 2017
Data governance and the secondary use of data: The board influence
Publisher: Elsevier BV
Date: 06-2023
Explanations as Discourse
Publisher: Australian Journal of Information Systems
Date: 16-03-2020
Abstract: Big data analytics uses algorithms for decision-making and targeting of customers. These algorithms process large-scale data sets and create efficiencies in the decision-making process for organizations but are often incomprehensible to customers and inherently opaque in nature. Recent European Union regulations require that organizations communicate meaningful information to customers on the use of algorithms and the reasons behind decisions made about them. In this paper, we explore the use of explanations in big data analytics services. We rely on discourse ethics to argue that explanations can facilitate a balanced communication between organizations and customers, leading to transparency and trust for customers as well as customer engagement and reduced reputation risks for organizations. We conclude the paper by proposing future empirical research directions.
More Enduring Questions in Cognitive IS Research: A Reply
Publisher: Association for Information Systems
Date: 12-2012
DOI: 10.17705/1JAIS.00317
Knowledge matters: Restrictiveness and performance with decision support
Publisher: Elsevier BV
Date: 11-2010
Personalizing to product category knowledge: exploring the mediating effect of shopping tools on decision confidence
Publisher: IEEE
Date: 2004
Large-scale analysis of interindividual variability in single and paired-pulse TMS data: results from the ‘Big TMS Data Collaboration’
Publisher: Cold Spring Harbor Laboratory
Date: 26-01-2021
DOI: 10.1101/2021.01.24.428014
Abstract: Interin idual variability of single and paired-pulse TMS data has limited the clinical and experimental applicability of these methods. This study brought together over 60 TMS researchers to create the largest known s le of in idual participant single and paired-pulse TMS data to date, enabling a more comprehensive evaluation of factors driving response variability. 118 corresponding authors provided deidentified in idual TMS data. Mixed-effects regression investigated a range of in idual and study level variables for their contribution to variability in response to single and pp TMS data. 687 healthy participant’s TMS data was pooled across 35 studies. Target muscle, pulse waveform, neuronavigation use, and TMS machine significantly predicted an in idual’s single pulse TMS litude. Baseline MEP litude, M1 hemisphere, and biphasic AMT significantly predicted SICI response. Baseline MEP litude, test stimulus intensity, interstimulus interval, monophasic RMT, monophasic AMT, and biphasic RMT significantly predicted ICF response. Age, M1 hemisphere, and TMS machine significantly predicted motor threshold. This large-scale analysis has identified a number of factors influencing participants’ responses to single and paired pulse TMS. We provide specific recommendations to increase the standardisation of TMS methods within and across laboratories, thereby minimising interin idual variability in single and pp TMS data. 687 healthy participant’s TMS data was pooled across 35 studies Significant relationships between age and resting motor threshold Significant relationships between baseline MEP litude and SICI/ICF
Reconceptualizing synergy to explain the value of business analytics systems
Publisher: SAGE Publications
Date: 02-2019
Abstract: How can we use synergy to explain the value created by business analytics systems? In this article, we conceptualize and operationalize two important aspects of synergy: namely, the synergistic relationship and the synergistic outcome. We explore the enablers and mechanisms that are involved in a synergistic relationship between business analytics systems and customer relationship management systems and define it as the ability of systems to work together, span their boundaries and complement each other. Synergistic outcomes are the new business analytics–enabled customer relationship management systems that emerge from the synergistic relationship between business analytics systems and customer relationship management systems. Taking a whole system perspective, business analytics–enabled customer relationship management systems comprise the components and the emergent properties that arise from their interaction (e.g. the ability to cross-sell and up-sell based on advanced computational methods), in which the emergent properties are new because they do not exist in the in idual components. We develop a research model that uses Synergistic Relationship and Synergistic Outcomes to explain the business value created by business analytics systems and customer relationship management systems, and we test this model using a survey of 201 managers in Australia and the United States. We find that the synergistic relationship plays a significant role in the creation of business analytics–enabled customer relationship management systems and subsequently business value. Business analytics–enabled customer relationship management systems—comprising business analytics systems, customer relationship management systems and their emergent properties—contribute to transactional, informational and strategic value. This goes beyond the value created by the business analytics and customer relationship management systems in idually, as measured through statistical interaction.
Configuring Relationships between Analytics and Business Domain Groups for Knowledge Integration
Publisher: Association for Information Systems
Date: 2023
DOI: 10.17705/1JAIS.00782
Abstract: To realize value from their wealth of digital data, organizations are investing in data-driven organizational initiatives—efforts in which they must draw expertise in data, algorithms, and visualization together with knowledge and skills in business domains such as marketing and human resources. However, they face the challenge of crossing the knowledge ide between analytics groups and business groups. Exploring relationships between the two groups in 37 data-driven organizational initiatives, we develop a configuration-based model that explains analytics and businessdomain knowledge integration through the lens of synergy. Our configurational analyses revealed five configurations of relationships between the two, which bring about two distinct change outcomes: “dedicated data groups” and “multidisciplinary teams” lead to the emergence of new datadriven ways to work, and “analytics institutionalization,” “analytics resource optimization,” and “networked communities” produce convergence, through the sharing of data-driven ways to work. Each configuration displays a distinct element of the core processes identified (“developing group connectedness,” “exchanging analytics and business domain knowledge,” and “incentivizing organizational data use”) and yields either an emergence or convergence of data-driven ways of working. The findings demonstrate how data-driven organizational initiatives can benefit from a pervasive form of organizing that entwines analytics groups and business groups such that their members’ tools, mindsets, and behaviors are merged to profoundly change ways of working. Together, these findings and the configurational methodology used provide a nuanced picture of how organizations integrate the requisite specialist knowledge across domains to realize value from data.
Personalization and choice behavior
Publisher: Association for Computing Machinery (ACM)
Date: 31-10-2008
Abstract: Online merchants use personalization technologies to gain knowledge of an in idual customer and then generate preference-matched web content for the customer. Among the various types of personalization technologies, this research focuses on personalization engines that generate preference-matched content based on a customer's prior transactions. Extant research in this area has focused on how to maximize knowledge mined from transaction logs to generate content that is highly similar to the customer's past revealed preferences. However, it remains an empirical question as to whether the content closely matched with previous transactions is most likely to influence choice behavior. In this study, we postulate that the content closely matched with previous transactions may not be the most influential in biasing a customer. In the consideration and choice process, an in idual's personality traits play a pivotal role in moderating the effect of personalized content. Drawing on research in marketing, we examine three key personality traits: need for cognition variety seeking, and need for uniqueness and explore their effects on choice behavior in the context of transaction-driven personalization. Research hypotheses are tested with over 2,000 pre-selected subjects in an online experiment based on a ringtone download website. We find that in idual personality traits moderate content consideration and choice. Theoretical and practical implications of the findings are discussed.
Acceptance of post-adoption unanticipated is usage
Publisher: Association for Computing Machinery (ACM)
Date: 20-08-2012
Abstract: Information Systems (IS), as social artifacts, are open to interpretation during use. This flexibility creates opportunities for in iduals to use systems in unanticipated ways to better fit particular tasks. Yet such unanticipated usage is counter to the use of IS as vehicles for managerial control and ensuring consistency in transaction processing across organizations. To effectively manage this tension a structured appreciation of post-adoption IS usage in its social context is required. Through a case study of users in a large Australian accommodation chain we develop a taxonomy of system usage, exploring unanticipated usage to meet workplace demands, its underlying motivations, implications for transaction processing consistency and ultimately operational and/or managerial decision making.
An Exploratory Model of Decision Quality and its Antecedents for Category Novices Using Multiple-Stage Shopping Engines
Publisher: Indiana University Press
Date: 2005
Enhancing the Business Value of Business Intelligence: The Role of Shared Knowledge and Assimilation
Publisher: American Accounting Association
Date: 07-2013
DOI: 10.2308/ISYS-50563
Abstract: Business intelligence (BI) systems have attracted significant interest from senior executives and consultants for their ability to exploit organizational data and provide operational and strategic benefits through improved management control systems. A large body of literature indicates that organizations have largely failed to use their business intelligence investments effectively to exploit the wealth of data they capture in their ERP systems. As a result, BI has too often failed to support organizations' managerial decision making at both the strategic and operational levels and, thus, failed to enhance business value. Whether and how organizations achieve business benefits from their BI investments remains unclear. This study draws on the strategic alignment and IT assimilation literature to develop a research model that theorizes the importance of BI systems assimilation, and the need for shared knowledge among the strategic and operational levels as the drivers of BI business value. Results from the study confirm the crucial role of BI assimilation in translating organizational resources into capabilities that enhance the business value of BI. The findings also contribute evidence on the importance of shared domain knowledge and the interrelations between senior business, IT executives, and operational-level managers for enhancing BI assimilation.
Handbook of Service Science, Volume II
Publisher: Springer International Publishing
Date: 2019
Why Do Banks Find Business Process Compliance so Challenging? An Australian Perspective
Publisher: Springer International Publishing
Date: 2022
A Framework for Relationships in Outsourcing: Contract Management Archetypes
Publisher: Hawaii International Conference on System Sciences
Date: 2017
On the Ethical Implications of Big Data in Service Systems
Publisher: Springer International Publishing
Date: 17-10-2018
Evolving innovations through design and use
Publisher: Association for Computing Machinery (ACM)
Date: 12-2008
Implementing AASB 15 revenue from contracts with customers: the preparer perspective
Publisher: Emerald
Date: 07-05-2019
Abstract: This study aims to examine the implementation of AASB 15 Revenue from Contracts with Customers to provide insight into preparers’ perspectives on the challenges, costs and benefits experienced in implementing a new and complex standard. The study uses a survey of 143 financial statement preparers engaged in implementing AASB 15. The results reveal significant variation in the approach to, and progress in, implementing AASB 15. The study provides evidence of the role of proprietary costs in implementing a new standard and suggests that preparers adopt a more pragmatic view of the nature of compliance compared to standard-setters. The evidence in this study strongly suggests that there is little to be gained in deferring effective dates for new standards. It suggests that standard-setters can motivate entities by framing a standard in terms of how it improves the business itself, rather than from a compliance framing. This study provides a rare perspective on the actual implementation experience of preparers confronted with the introduction of a new standard. Such a perspective is of value to standard-setters and preparers and offers insight to researchers that cannot be gained from traditional capital market archival approaches.
Discovering Potential and Realizing Value from Information Technology Investments
Publisher: Informa UK Limited
Date: 03-2000
Measuring the effects of business intelligence systems: The relationship between business process and organizational performance
Publisher: Elsevier BV
Date: 09-2008
Ethical Issues in Big Data Analytics: A Stakeholder Perspective
Publisher: Association for Information Systems
Date: 2019
DOI: 10.17705/1CAIS.04434
Related Organisations
University Of Minnesota Twin Cities
Location: United States of America
Related Funding Activities
Linkage Projects - Grant ID: LP130100106
Start Date: 06-2014
End Date: 12-2016
Amount: $100,000.00
Funder: Australian Research Council
View Funded ActivityLinkage Projects - Grant ID: LP100100068
Start Date: 08-2010
End Date: 08-2013
Amount: $110,000.00
Funder: Australian Research Council
View Funded ActivityLinkage Projects - Grant ID: LP0774949
Start Date: 2007
End Date: 12-2010
Amount: $182,000.00
Funder: Australian Research Council
View Funded Activity