ORCID Profile
0000-0003-4316-8017
Current Organisation
Monash University - Caulfield Campus
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Publisher: Elsevier BV
Date: 06-2021
Publisher: Elsevier BV
Date: 03-2009
Publisher: Springer Science and Business Media LLC
Date: 27-11-2010
Publisher: Elsevier BV
Date: 09-2003
Publisher: Springer Berlin Heidelberg
Date: 1998
Publisher: Association for Information Systems
Date: 2019
DOI: 10.17705/1CAIS.04628
Publisher: Springer Berlin Heidelberg
Date: 1994
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: SAGE Publications
Date: 06-2005
DOI: 10.1057/PALGRAVE.JIT.2000038
Abstract: An organization depends on quality information for effective operations and decisionmaking. However, there is still no agreement as to how quality should be defined in terms of specific quality categories and criteria. Proposed information quality frameworks have limitations with respect to either consistency, resulting from a non-theoretical approach to framework development, or scope, considering only objective but not subjective information quality perspectives. In this paper, we describe a unique research approach to framework development that addresses these problems and compare it to those used previously for other frameworks. Semiotic theory, the philosophical theory of signs, is used to ensure rigor and scope. It provides a theoretical basis for framework structure - quality categories and their criteria - and for integrating objective and subjective quality views. Empirical refinement based on academic, practitioner, and end-user focus groups is then used to ensure relevance.
Publisher: Elsevier
Date: 2004
Publisher: IEEE
Date: 2014
Publisher: Elsevier BV
Date: 07-2014
Publisher: Elsevier BV
Date: 05-2012
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.
Publisher: Elsevier BV
Date: 09-2017
Publisher: Informa UK Limited
Date: 08-2012
Publisher: Elsevier BV
Date: 12-2015
Publisher: Informa UK Limited
Date: 02-01-2015
Publisher: Association for Information Systems
Date: 2021
DOI: 10.17705/1CAIS.04936
Publisher: Informa UK Limited
Date: 2011
Publisher: Association for Computing Machinery (ACM)
Date: 07-2004
Abstract: Using an object or entity class to represent a composite provides straightforward answers, making this approach superior to the use of relationship classes or associations.
Publisher: Elsevier BV
Date: 06-2018
Publisher: Association for Computing Machinery (ACM)
Date: 10-2003
Abstract: Theories of ontology lead to improved conceptual models and help ensure they are indeed faithful representations of their focal domains.
Publisher: Association for Information Systems
Date: 2019
DOI: 10.17705/1CAIS.04434
Publisher: SAGE Publications
Date: 12-2000
Publisher: IGI Global
Date: 04-2010
Abstract: How classes of things and properties in general should be represented in conceptual models is a fundamental issue. For ex le, proponents of object-role modelling argue that no distinction should be made between the two constructs, whereas proponents of entity-relationship modelling argue the distinction is important but provide ambiguous guidelines about how the distinction should be made. In this paper, the authors use ontological theory and cognition theory to provide guidelines about how classification should be represented in conceptual models. The authors experimented to test whether clearly distinguishing between classes of things and properties in general enabled users of conceptual models to better understand a domain. They describe a cognitive processing study that examined whether clearly distinguishing between classes of things and properties in general impacts the cognitive behaviours of the users. The results support the use of ontologically sound representations of classes of things and properties in conceptual modelling.
Publisher: IGI Global
Date: 2005
DOI: 10.4018/978-1-59140-339-5.CH002
Abstract: This chapter examines how ontological theory can be used to predict how alternative conceptual modelling representations affect end-user understanding of these representations. Specifically, it examines how ontological theory can be used to show how part-whole relations (composites) and things and properties can be best represented to enhance understanding of these real-world phenomena. We report the outcomes of two experiments that provide evidence to support the ontologically sound representation of part-whole relations and things and properties. We also discuss the outcomes of a cognitive process tracing study that explains why the ontologically sound representation of things and properties is more easily understood. In essence, our empirical research provides evidence to support the use of ontology as a theoretical basis to guide conceptual modelling practices.
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