18,857 research outputs found

    Development of a Taxonomy to be used by Business-IT Alignment Researchers

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    The nexus between Business and IT research is complex. Due to extended research over time, the context of business-IT alignment has resulted in many different conceptualisations that can be applied to ongoing research. It is challenging to select and adopt a suitable approach to study business-IT alignment across any given field due to the variability of the existing conceptualisations. This study reviews the existing literature to identify alignment conceptualisations and contributes to both theory and practice. Theoretically, through the uncovering of gaps in the literature a taxonomy has been developed which can be used as a guide to select an appropriate alignment lens for business-IT alignment studies. In practice, it is expected that this taxonomy will be beneficial for conceptualising the structure and philosophies underpinning future alignment studies. To validate the taxonomy, the paper presents a case study in healthcare applying the developed taxonomy to investigate alignment of big data in health

    Alignment of Big Data Perceptions Across Levels in Healthcare: The case of New Zealand

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    Big data and related technologies have the potential to transform healthcare sectors by facilitating improvements to healthcare planning and delivery. Big data research highlights the importance of aligning big data implementations with business needs to achieve success. In one of the first studies to examine the influence of big data on business-IT alignment in the healthcare sector, this paper addresses the question: how do stakeholders’ perceptions of big data influence alignment between big data technologies and healthcare sector needs across macro, meso, and micro levels in the New Zealand (NZ) healthcare sector? A qualitative inquiry was conducted using semi-structured interviews to understand perceptions of big data across the NZ healthcare sector. An application of a novel theory, Theory of Sociotechnical Representations (TSR), is used to examine people’s perceptions of big data technologies and their applicability in their day-to-day work. These representations are analysed at each level and then across levels to evaluate the degree of alignment. A social dimension lens to alignment was used to explore mutual understanding of big data across the sector. The findings show alignment across the sector through the shared understanding of the importance of data quality, the increasing challenges of privacy and security, and the importance of utilising modern and new data in measuring health outcomes. Areas of misalignment include the differing definitions of big data, as well as perceptions around data ownership, data sharing, use of patient-generated data and interoperability. Both practical and theoretical contributions of the study are discussed

    Alignment of big data perceptions in New Zealand healthcare : a thesis presented in partial fulfilment of the requirement for the degree of Doctor of Philosophy in Management at Massey University, Albany, New Zealand

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    The growing use of information systems (IS) in the healthcare sector, on top of increasing patient populations, diseases and complicated medication regimens, is generating enormous amounts of unstructured and complex data that have the characteristics of ‘big data’. Until recent times data driven approaches in healthcare to make use of large volumes of complex healthcare data were considered difficult, if not impossible, because available technology was not mature enough to handle such data. However, recent technological developments around big data have opened promising avenues for healthcare to make use of its big-healthcare-data for more effective healthcare delivery, in areas such as measuring outcomes, population health analysis, precision medicine, clinical care and research and development. Being a recent IT phenomenon, big data research has leaned towards technical dynamics such as analytics, data security and infrastructure. However, to date, the social dynamics of big data (such as peoples’ understanding and their perceptions of its value, application, challenges and the like) have not been adequately researched. This thesis addresses the research gap through exploring the social dynamics around the concept of big data at the level of policy-makers (identified as the macro level), funders and planners (identified as the meso level), and clinicians (identified as the micro level) in the New Zealand (NZ) healthcare sector. Investigating and comparing social dynamics of big data across these levels is important, as big data research has highlighted the importance of business-IT alignment to the successful implementation of big data technologies. Business-IT alignment is important and can be investigated through many different dimensions. This thesis adopts a social dimension lens to alignment, which promotes investigating alignment through people’s understanding of big data and its role in their work. Taking a social dimension lens to alignment fits well with the aim of this thesis, which is to understand perceptions around the notion of big data technologies that could influence the alignment of big data in healthcare policy and practice. With this understanding, the research question addressed is: how do perceptions of big data influence alignment across macro, meso, and micro levels in the NZ healthcare sector? This thesis is by publication with four research articles that answer these questions as a body of knowledge. A qualitative exploratory approach was taken to conduct an empirical study. Thirty-two in-depth interviews with policy makers, senior managers and physicians were conducted across the NZ healthcare sector. Purposive and snowball sampling techniques were used. The interviews were transcribed verbatim and analysed using general inductive thematic analysis. Data were first analysed within each group (macro, meso, and micro) to understand perceptions of big data, then across groups to understand alignment. In order to investigate perceptions, Social Representations Theory (SRT), a theory from social psychology, was used as the basis for data collection. However, data analysis led to the decision to integrate SRT with Sociotechnical Systems Theory (SST), a well-known IS theory. This integration of SRT with SST developed the Theory of Sociotechnical Representations (TSR), which is a key theoretical contribution of this research. The thesis presents the concept and application of TSR, by using it to frame the study’s findings around perceptions of big data across macro, meso and micro levels of the NZ healthcare sector. The practical contribution of this thesis is the demonstration of areas of alignment and misalignment of big data perceptions across the healthcare sector. Across the three levels, alignment was found in the shared understanding of the importance of data quality, the increasing challenges of privacy and security, and the importance of new types of data in measuring health outcomes. Aspects of misalignment included the differing definitions of big data, as well as perceptions around data ownership, data sharing, use of patient-generated data and interoperability. While participants identified measuring outcomes, clinical decision making, population health, and precision medicine as potential areas of application for big data technologies, the three groups expressed varying levels of interest, which could cause misalignment issues with implications for policy and practice

    ERP implementation methodologies and frameworks: a literature review

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    Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history

    Alignment of Big Data Perceptions Across Levels in Healthcare: The case of New Zealand

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    Big data and related technologies have the potential to transform healthcare sectors by facilitating improvements to healthcare planning and delivery. Big data research highlights the importance of aligning big data implementations with business needs to achieve success. In one of the first studies to examine the influence of big data on business-IT alignment in the healthcare sector, this paper addresses the question: how do stakeholders’ perceptions of big data influence alignment between big data technologies and healthcare sector needs across macro, meso, and micro levels in the New Zealand (NZ) healthcare sector? A qualitative inquiry was conducted using semi-structured interviews to understand perceptions of big data across the NZ healthcare sector. An application of a novel theory, Theory of Sociotechnical Representations (TSR), is used to examine people’s perceptions of big data technologies and their applicability in their day-to-day work. These representations are analysed at each level and then across levels to evaluate the degree of alignment. A social dimension lens to alignment was used to explore mutual understanding of big data across the sector. The findings show alignment across the sector through the shared understanding of the importance of data quality, the increasing challenges of privacy and security, and the importance of utilising modern and new data in measuring health outcomes. Areas of misalignment include the differing definitions of big data, as well as perceptions around data ownership, data sharing, use of patient-generated data and interoperability. Both practical and theoretical contributions of the study are discussed

    Transformation through Big Data Analytics: a Qualitative Enquiry in Healthcare

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    With an aim to understand transformation around big data analytics, this paper first investigates the literature to explore elements of change around big data. The research comprises a qualitative enquiry in the New Zealand healthcare context to understand how professionals across the sector view this transformation. Healthcare sectors are increasingly adopting big data technologies to improve healthcare delivery and management. However, for sectors like healthcare, big data brings significant changes in terms of technology architecture, infrastructure, skills, and organisational structure changes. Security measures and policy changes are also apparent. Using a deductive approach to data analysis, it confirms the important elements identified in the literature around big data transformation and highlights the relationships between these elements of change. The paper uses Sociotechnical Systems Theory as the underlying theoretical foundation for this study. The findings of this research contribute to policy and practice in healthcare

    The Coevolution of Organizational Routines and IT Systems in IT-enabled Organizational Transformation

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    This paper proposes a conceptual framework to study the phenomenon of IT-enabled Organizational Transformation (IT-enabled OT) as a coevolution process of organizational routines and a new IT system to understand IT-enabled OT in a holistic and integrated manner by investigating how actors perceive, interpret, appropriate and enact the new IT system in their work routines. It allows the examination of the reciprocal interactions between different aspects of organizational routines and a new IT system. The framework emphasizes appropriation where the actors use the new IT system in a different manner than intended by its designers, and enactment where the logic of the new IT system is locally adopted through planned as well as unplanned actions. The conceptualization of IT-enabled OT as a coevolution process of organizational routines and a new IT system enhances our understanding of how change unfolds in the organization during the implementation and use of a new IT syste

    Does perceived organisational support influence career intentions?:The qualitative stories shared by UK early career doctors

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    Our thanks to all those FP2 doctors who participated in the interviews. Our thanks also to the Foundation Programme Directorate staff in the Scotland Deanery, NHS Education for Scotland, for sending out the email correspondence to the two regions involved in the interviews. No patients or any members of the public were involved in this study. Funding: Our thanks go to NHS Education for Scotland for funding Gillian Scanlan’s programme of work through the Scottish Medical Education Research Consortium (SMERC) and for funding the open-access fee for this paper.Peer reviewedPublisher PD

    UNDERSTANDING THE ROLE OF POWER IN INTERDISCIPLINARY, UNDERGRADUATE, STUDENT TEAMS: A CRITICAL DISCOURSE ANALYSIS

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    This dissertation is a cultural studies project that aims to understand how power manifests and influences knowledge construction between students working in an undergraduate, interdisciplinary, collaborative learning environment. Power – which holds the potential to empower and/or silence students - is intrinsic in social interaction and therefore inherent in collaboration. Exploring how power influences new knowledge construction in undergraduate, collaborative learning environments has the potential to uncover what type of interactions are valued and integrated or marginalized and excluded as part of these communicative exchanges.The purpose of this dissertation is thus not only to improve student learning within collaborative contexts, but also to further the implications to teaching that could help advance interdisciplinary communication and new knowledge construction. To explore these dynamics, a two part analysis employing James Gee’s approach to critical discourse analysis was applied to archival data collected from an undergraduate interdisciplinary course entitled, Clinical Immersion at Disciplinary Interfaces (CIDI). This unique, interdisciplinary course required teams composed of chemical engineering and nursing students to develop a prototype of innovative technology that addressed real-world problems in the healthcare profession.The findings emphasize that the manifestation of power and its influence on knowledge construction was primarily accomplished via students’ association with a specific disciplinary cultural model. The affiliation to a specific disciplinary cultural model determined several of the ways in which students engaged within particular social contexts embedded within the CIDI course including: how they positioned themselves (as either insiders or outsiders within that space); their expectations regarding how they understood that space and made situated meanings; and ultimately, their perceived ability to contribute within that space based on their fluency of the associated social language or Discourses. Utilizing a cultural studies lens, scholarship from this field of study is integrated to emphasize how manifestations of power impacted the context of the CIDI course in three ways: through space, language, and disciplinary beliefs. Five pedagogical implications are underscored as part of the concluding remarks

    Conducting Social Cognition Research in IS: A Methodology for Eliciting and Analyzing Social Representations

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    This paper presents a methodology for socio-cognitive research based on the theory of social representations. Elements of the methodology include:1) data elicitation through free word association; 2) content analysis/coding to identify key concepts in the social representation; 3) analysis of the structure of the representation using analysis of similarity and core/periphery analysis; 4) correspondence analysis to place the concepts on a perceptual space; and 5) interpretation of the social representation. The methodology is demonstrated in use through a study examining early sense-making about electronic health records (EHRs). Analysis of qualitative survey data from 190 students identified 22 concepts forming the social representation. Merits of the methodology are discussed, including its potential value for investigations based on technology frames of reference (TFR), the social construction of technology (SCOT) and organizing visions for IT innovations
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