-------- Weitergeleitete Nachricht -------- Betreff: [AISWorld] [AJIS] New Article Published: Development of a Theoretical Framework to Investigate Alignment of Big Data in Healthcare through a Social Representation Lens Datum: Mon, 15 Jan 2018 21:14:23 +0000 Von: John Lamp john.lamp@deakin.edu.au An: ISHoDs (IS-hods@list.utas.edu.au) IS-hods@list.utas.edu.au, ISAus (IS-Aus@list.utas.edu.au) IS-Aus@list.utas.edu.au, ISWorld aisworld@lists.aisnet.org

Hi,

The Australasian Journal of Information Systems has just published its latest article.

Weerasinghe, K., Pauleen, D., Scahill, S., & Taskin, N. (2018). Development of a Theoretical Framework to Investigate Alignment of Big Data in Healthcare through a Social Representation Lens. Australasian Journal of Information Systems, 22. doi: http://dx.doi.org/10.3127/ajis.v22i0.1617

Abstract The aim of this paper is to develop a theoretical framework grounded in the literature, which can be used to explore the influence of big data on business-IT alignment in the healthcare context. Increasingly the availability of information systems in healthcare delivery and service management results in massive amounts of complex data that have the 3V characteristics of big data (i.e. volume, variety, velocity). Use of big-healthcare-data has been identified as bringing significant benefits to the healthcare sector from improved decision making through to population health analysis. Although the technical dynamics around big data such as analytics and infrastructure requirements are extensively researched, less attention has been given to social dynamics such as peoples' experience, understanding and perceived usefulness of this data. To address this gap, the paper uses social representation theory as a methodological lens to develop a theoretical framework to study the social dynamics around big data and its use in the healthcare context. The selected case for this development is the New Zealand healthcare sector and an approach using multi-level macro, meso, and micro analysis is taken. Use of social representation theory as a methodological lens to develop a theoretical framework is a novel approach. Such a theoretical framework will be useful as a foundation for carrying out on-going empirical research on big data to understand its influence on business-IT alignment in the healthcare context.

Keywords big data; healthcare; business-IT alignment; social representation theory; New Zealand healthcare; healthcare information systems

-=-=-=- Call for Papers

AJIS publishes high quality contributions to the global Information Systems (IS) discipline with an emphasis on theory and practice on the Australasian context.

Topics cover core IS theory development and application (the nature of data, information and knowledge; formal representations of the world, the interaction of people, organisations and information technologies; the analysis, design and deployment of information systems; the impacts of information systems on individuals, organisations and society), IS domains (e-business, e-government, e-learning, e-law, etc) and IS research approaches.

Research and conceptual development based in a very wide range of epistemological methods are welcomed.

All manuscripts undergo double blind reviewing by at least 2 well qualified reviewers. Their task is to provide constructive, fair, and timely advice to authors and editor.

AJIS welcomes research and conceptual development of the IS discipline based in a very wide range of epistemologies. Different types of research paper need to be judged by different criteria. Here are some assessment criteria that may be applied:

* Relevance - topic or focus is part of the IS discipline. * Effectiveness - paper makes a significant contribution to the IS body of knowledge. * Impact - paper will be used for further research and/or practice. * Uniqueness - paper is innovative, original & unique. * Conceptual soundness - theory, model or framework made explicit. * Argument - design of the research or investigation is sound; methods appropriate. * Clarity - Topic is clearly stated; illustrations, charts & examples support content. * Reliability - data available; replication possible. * References - sound, used appropriately, and sufficient - appropriate AJIS articles referenced * Style - appropriate language, manuscript flows.

This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.

AJIS has been published since 1993 and appears in the Index of Information Systems Journals, is ranked "A" by both the Australian Council of Professors and Heads of Information Systems and the Australian Business Deans' Council.

In addition to web distribution, AJIS is distributed by EBSCO, it is listed in Cabell's International Directory and is indexed by EBSCO, Elsevier, Scopus and the Directory of Open Access Journals.

Thanks for the continuing interest in our work,

Cheers John @JohnWLamp ORCID: 0000-0003-1891-0400 ResearcherID: A-3227-2008 ISNI: 0000 0003 5074 9223 Scopus AuthorID: 9840309500

Index of Information Systems Journals http://lamp.infosys.deakin.edu.au/journals/ Editor-in-Chief, Australasian Journal of Information Systems http://journal.acs.org.au/index.php/ajis/

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-- Dr John Lamp Associate Professor Department of Information Systems and Business Analytics, Deakin Business School [dea_webbanner_dbsmission_amend04.web]

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