Business Information Systems - Conference Items

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    A boundary spanning perspective of practical impact: The case of IS practitioner doctorates
    (Association for Information Systems, 2022) McCarthy, Stephen; Scholta, Hendrik; Hausvik, Geir Inge; Busch, Peter André
    IS research often seeks to deliver practical impact, in addition to the traditional requirement for theoretical contribution. While an admirable goal, it is nevertheless a challenging prospect, as key questions remain around how to best facilitate a relationship between IS academic and practitioner communities. To explore this question, our paper investigates boundary spanning by ‘practitioner doctorates’ - PhD students with professional experience who seek to span the fields of academia and practice during their research. Drawing on in-depth interviews with practitioner doctorates, our findings point towards several factors for practical impact such as researcher legitimacy, expectation management, and adapting to changes in industry requirements. In doing so, we contribute towards an understanding of engaged scholarship in IS and take steps towards addressing the dearth of research on doctoral studies in the IS field to date.
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    A roadmap to Artificial Intelligence: Navigating core impacts to successfully transform organisations
    (Academic Conferences International Limited, 2022-11-17) Treacy, Stephen
    Artificial Intelligence (AI) is a highly disruptive technology that will have major effects on the business world over the coming years. It has the potential to allow companies to achieve major efficiency gains and a more productive workforce through automating existing processes, providing deeper levels of analytics, providing better customer support, and increasing security. On the other hand, it may lead to lower staff levels and a drop in existing employee morale. Given the complexities of these projects, AI will only benefit organisations if they understand its capabilities in addition to its shortcomings. This investigation addresses the predicted impact on skills, roles and employee morale of artificial intelligence on the workforce of the future as AI continues to become more prevalent in our society. We investigate these impacts of AI specifically across four key industries by engaging in interviews with experts in the field to answer two research questions: (i) What are the core impacts of introducing AI systems in the workplace?, and; (ii) How can organisations develop AI projects for successful transformation? The inclusion strategy for this research were professionals who were highly knowledgeable in the area, and from our findings we were able to identify several impacts that AI made to companies developing these projects; namely employment levels, workforce morale, and process efficiency. With these insights, we subsequently developed a roadmap which contains the recommended steps and decisions that are necessary for successfully introducing AI to an organisation. This roadmap visualises the key decisions and steps that are critical for any AI based initiative for organisations, which will provide practitioners with a higher level of understanding of what is expected, in addition to enabling more effective collaboration with the system developers. Furthermore, this roadmap allows organisations to take a positive and proactive approach to designing these systems with their workforce in mind and to prepares them for the implications with the development, deployment, and use of these AI systems.
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    Information quality and data management within a pervasive medical environment
    (Massachusetts Institute of Technology, 2008-12) O'Donoghue, John; Herbert, John; Sammon, David; Barton, John
    Next generation pervasive medical domains will be made up of numerous quantities of autonomous: processing, communicating and sensing devices. These may include personal digital assistants (PDA) wireless sensor networks (WSN) or of a patient centric importance, Body Area Networks (BAN). Before any data management task may be executed, the context or situation of the user and their environment needs to be taken into account. This large paradigm shift from centralised decision making networks to remote autonomy create new challenges within the information quality community, particularly how to collect, correlate and disseminate this new information pool in an intelligent manner. Presented in this paper are the findings of the Data Management System-Data Consistency Model (DMS-DCM) software architecture within a pervasive medical environment. Five data management experiments were conducted to evaluate the DMS DCM’s effect on information quality.
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    Plausible pictures for data governance: A narrative network approach
    (Association for Information Systems, 2022-05) Wibisono, Arif; Sammon, David; Heavin, Ciara
    Workaround-centric data activities (WCDA) can impact data integrity/quality. Despite this, one can view WCDA as an enhancement to organisational Data Governance (DG) maturity. However, these WCDA are primarily undocumented and poorly understood. Therefore, we need a means of creating plausible pictures for DG â by modelling WCDA visually. This study draws on the theory of organisational routines to develop WCDA modelling rules. It is the first study to leverage the Narrative Network (NN) approach as a conceptual lens to model WCDA visually. We identify five WCDA modelling rules: 1) a narrative fragment must come from a process actor, 2) a narrative fragment has three attributes: actor, action & resource, 3) all attributes in a narrative fragment establish the action type, 4) a narrative fragment must contain a data activity, and 5) a narrative fragment data activity must follow a standard naming convention. In conclusion, we discuss the advantages of our approach.
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    A triple bottom-line typology of technical debt: Supporting decision-making in cross-functional teams
    (University of Hawai'i at Manoa, 2022-01-04) Greville, Mark; O'Raghallaigh, Paidi; McCarthy, Stephen
    Technical Debt (TD) is a widely discussed metaphor in IT practice focused on increased short-term benefit in exchange for long-term ‘debt’. While it is primarily individuals or groups inside IT departments who make the decisions to take on TD, we find that the effects of TD stretch across the entire organisation. Decisions to take on TD should therefore concern a wider group. However, business leaders have traditionally lacked awareness of the effects of what they perceive to be ‘technology decisions’. To facilitate TD as group-based decision-making, we review existing literature to develop a typology of the wider impacts of TD. The goal is to help technologists, non-technologists, and academics have a broader and shared understanding of TD and to facilitate more participatory and transparent technology-related decision making. We extend the typology to include a wider ‘outside in’ perspective and conclude by suggesting areas for further research.