A grounded theory study of technology appropriation in anaesthesia

The human-technology nexus is a strong focus of Information Systems (IS) research; however, very few studies have explored this phenomenon in anaesthesia. Anaesthesia has a long history of adoption of technological artifacts, ranging from early apparatus to present-day information systems such as electronic monitoring and pulse oximetry. This prevalence of technology in modern anaesthesia and the rich human-technology relationship provides a fertile empirical setting for IS research. This study employed a grounded theory approach that began with a broad initial guiding question and, through simultaneous data collection and analysis, uncovered a core category of technology appropriation. This emergent basic social process captures a central activity of anaesthestists and is supported by three major concepts: knowledge-directed medicine, complementary artifacts and culture of anaesthesia. The outcomes of this study are: (1) a substantive theory that integrates the aforementioned concepts and pertains to the research setting of anaesthesia and (2) a formal theory, which further develops the core category of appropriation from anaesthesia-specific to a broader, more general perspective. These outcomes fulfill the objective of a grounded theory study, being the formation of theory that describes and explains observed patterns in the empirical field. In generalizing the notion of appropriation, the formal theory is developed using the theories of Karl Marx. This Marxian model of technology appropriation is a three-tiered theoretical lens that examines appropriation behaviours at a highly abstract level, connecting the stages of natural, species and social being to the transition of a technology-as-artifact to a technology-in-use via the processes of perception, orientation and realization. The contributions of this research are two-fold: (1) the substantive model contributes to practice by providing a model that describes and explains the human-technology nexus in anaesthesia, and thereby offers potential predictive capabilities for designers and administrators to optimize future appropriations of new anaesthetic technological artifacts; and (2) the formal model contributes to research by drawing attention to the philosophical foundations of appropriation in the work of Marx, and subsequently expanding the current understanding of contemporary IS theories of adoption and appropriation.

Informed learning: a pedagogical construct attending simultaneously to information use and learning.

The idea of informed learning, applicable in academic, workplace and community settings, has been derived largely from a program of phenomenographic research in the field of information literacy, which has illuminated the experience of using information to learn. Informed learning is about simultaneous attention to information use and learning, where both information and learning are considered to be relational; and is built upon a series of key concepts such as second–order perspective, simultaneity, awareness, and relationality. Informed learning also relies heavily on reflection as a strategy for bringing about learning. As a pedagogical construct, informed learning supports inclusive curriculum design and implementation. This paper reports aspects of the informed learning research agenda which are currently being pursued at the Queensland University of Technology (QUT). The first part elaborates the idea of informed learning, examines the key concepts underpinning this pedagogical construct, and explains its emergence from the research base of the QUT Information Studies research team. The second presents a case, which demonstrates the ongoing development of informed learning theory and practice, through the development of inclusive informed learning for a culturally diverse higher education context.

A framework for successful enterprise systems implementation : preliminary findings from a case study

While critical success factors (CSFs) of enterprise system (ES) implementation are mature concepts and have received considerable attention for over a decade, researchers have very often focused on only a specific aspect of the implementation process or a specific CSF. Resultantly, there is (1) little research documented that encompasses all significant CSF considerations and (2) little empirical research into the important factors of successful ES implementation. This paper is part of a larger research effort that aims to contribute to understanding the phenomenon of ES CSFs, and reports on preliminary findings from a case study conducted at a Queensland University of Technology (QUT) in Australia. This paper reports on an empirically derived CSFs framework using a directed content analysis of 79 studies; from top IS outlets, employing the characteristics of the analytic theory, and from six different projects implemented at QUT.

A Two-stage information filtering based on rough decision rule and pattern mining

Information Overload and Mismatch are two fundamental problems affecting the effectiveness of information filtering systems. Even though both term-based and patternbased approaches have been proposed to address the problems of overload and mismatch, neither of these approaches alone can provide a satisfactory solution to address these problems. This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern-based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experimental results based on the RCV1 corpus show that the proposed twostage filtering model significantly outperforms the both termbased and pattern-based information filtering models.

Optimization problems for controlled mechanical systems : bridging the gap between theory and application

Mechanical control systems have become a part of our everyday life. Systems such as automobiles, robot manipulators, mobile robots, satellites, buildings with active vibration controllers and air conditioning systems, make life easier and safer, as well as help us explore the world we live in and exploit it’s available resources. In this chapter, we examine a specific example of a mechanical control system; the Autonomous Underwater Vehicle (AUV). Our contribution to the advancement of AUV research is in the area of guidance and control. We present innovative techniques to design and implement control strategies that consider the optimization of time and/or energy consumption. Recent advances in robotics, control theory, portable energy sources and automation increase our ability to create more intelligent robots, and allows us to conduct more explorations by use of autonomous vehicles. This facilitates access to higher risk areas, longer time underwater, and more efficient exploration as compared to human occupied vehicles. The use of underwater vehicles is expanding in every area of ocean science. Such vehicles are used by oceanographers, archaeologists, geologists, ocean engineers, and many others. These vehicles are designed to be agile, versatile and robust, and thus, their usage has gone from novelty to necessity for any ocean expedition.

A review of rationale for allocating costs and payments in producing and supplying public sector information PART A of 2 Parts – Chapters 1, 2 and 3) 13 March 2011 version

This work reviews the rationale and processes for raising revenue and allocating funds to perform information intensive activities that are pertinent to the work of democratic government. ‘Government of the people, by the people, for the people’ expresses an idea that democratic government has no higher authority than the people who agree to be bound by its rules. Democracy depends on continually learning how to develop understandings and agreements that can sustain voting majorities on which democratic law making and collective action depends. The objective expressed in constitutional terms is to deliver ‘peace, order and good government’. Meeting this objective requires a collective intellectual authority that can understand what is possible; and a collective moral authority to understand what ought to happen in practice. Facts of life determine that a society needs to retain its collective competence despite a continual turnover of its membership as people die but life goes on. Retaining this ‘collective competence’ in matters of self-government depends on each new generation: • acquiring a collective knowledge of how to produce goods and services needed to sustain a society and its capacity for self-government; • Learning how to defend society diplomatically and militarily in relation to external forces to prevent overthrow of its self-governing capacity; and • Learning how to defend society against divisive internal forces to preserve the authority of representative legislatures, allow peaceful dispute resolution and maintain social cohesion.

User profiling based on folksonomy information in Web 2.0 for personalized recommender systems

Information overload has become a serious issue for web users. Personalisation can provide effective solutions to overcome this problem. Recommender systems are one popular personalisation tool to help users deal with this issue. As the base of personalisation, the accuracy and efficiency of web user profiling affects the performances of recommender systems and other personalisation systems greatly. In Web 2.0, the emerging user information provides new possible solutions to profile users. Folksonomy or tag information is a kind of typical Web 2.0 information. Folksonomy implies the users‘ topic interests and opinion information. It becomes another source of important user information to profile users and to make recommendations. However, since tags are arbitrary words given by users, folksonomy contains a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise makes it difficult to profile users accurately or to make quality recommendations. This thesis investigates the distinctive features and multiple relationships of folksonomy and explores novel approaches to solve the tag quality problem and profile users accurately. Harvesting the wisdom of crowds and experts, three new user profiling approaches are proposed: folksonomy based user profiling approach, taxonomy based user profiling approach, hybrid user profiling approach based on folksonomy and taxonomy. The proposed user profiling approaches are applied to recommender systems to improve their performances. Based on the generated user profiles, the user and item based collaborative filtering approaches, combined with the content filtering methods, are proposed to make recommendations. The proposed new user profiling and recommendation approaches have been evaluated through extensive experiments. The effectiveness evaluation experiments were conducted on two real world datasets collected from Amazon.com and CiteULike websites. The experimental results demonstrate that the proposed user profiling and recommendation approaches outperform those related state-of-the-art approaches. In addition, this thesis proposes a parallel, scalable user profiling implementation approach based on advanced cloud computing techniques such as Hadoop, MapReduce and Cascading. The scalability evaluation experiments were conducted on a large scaled dataset collected from Del.icio.us website. This thesis contributes to effectively use the wisdom of crowds and expert to help users solve information overload issues through providing more accurate, effective and efficient user profiling and recommendation approaches. It also contributes to better usages of taxonomy information given by experts and folksonomy information contributed by users in Web 2.0.

A pattern mining approach for information filtering systems

It is a big challenge to clearly identify the boundary between positive and negative streams for information filtering systems. Several attempts have used negative feedback to solve this challenge; however, there are two issues for using negative relevance feedback to improve the effectiveness of information filtering. The first one is how to select constructive negative samples in order to reduce the space of negative documents. The second issue is how to decide noisy extracted features that should be updated based on the selected negative samples. This paper proposes a pattern mining based approach to select some offenders from the negative documents, where an offender can be used to reduce the side effects of noisy features. It also classifies extracted features (i.e., terms) into three categories: positive specific terms, general terms, and negative specific terms. In this way, multiple revising strategies can be used to update extracted features. An iterative learning algorithm is also proposed to implement this approach on the RCV1 data collection, and substantial experiments show that the proposed approach achieves encouraging performance and the performance is also consistent for adaptive filtering as well.

Privacy by information accountability for e-health systems

Privacy has become one of the main impediments for e-health in its advancement to providing better services to its consumers. Even though many security protocols are being developed to protect information from being compromised, privacy is still a major issue in healthcare where privacy protection is very important. When consumers are confident that their sensitive information is safe from being compromised, their trust in these services will be higher and would lead to better adoption of these systems. In this paper we propose a solution to the problem of patient privacy in e-health through an information accountability framework could enhance consumer trust in e-health services and would lead to the success of e-health services.

The role of information avoidance in everyday-life information behaviors

This paper presents the results from a study of information behaviors in the context of people's everyday lives as part of a larger study of information behaviors (IB). 34 participants from across 6 countries maintained a daily information journal or diary – mainly through a secure web log – for two weeks, to an aggregate of 468 participant days over five months. The text-rich diary data was analyzed using Grounded Theory analysis. The findings indicate that information avoidance is a common phenomenon in everyday life and consisted of both passive avoidance and active avoidance. This has implications for several aspects of peoples' lives including health, finance, and personal relationships.

Identifying and delineating information experience as a research domain : A discussion paper

A line of information and information literacy research has emerged that has a strong focus on information experience. Strengthened understanding, profiling and theorising of information experience as a specific domain of interest to information researchers is required. A focus on information experience is likely to have a major influence on the field, drawing attention to interpretive and experiential forms of research.

Towards an orchestration theory in business transformation management (research in progress)

Business transformations are large-scale organisational change projects that, evidence suggests, are often unsuccessful. This study aims to develop a conceptual model that explains how management services that are required for a business transformation are orchestrated during such a initiative. We classify management services such as (but not limited to) change management, risk management, IT management, financial management, program management and so forth as bearing transformational and/or transactional capabilities in a transformation initiative. We then draw upon three principles of musical composition, namely melody, harmony and rhythm, and illustrate how they apply to the orchestration of management services in the management of business transformations. In order to illustrate our emerging model, we examine the case of Malaysia Airlines, who have managed to successfully turnaround the near-bankrupt organisation beyond survival. We demonstrate how the notions of melody, harmony and rhythm can be used to describe their endeavour. We conclude by discussing next steps of our research.

The Measurement of Information System Use: Preliminary Considerations

DeLone and McLean (1992, p. 16) argue that the concept of “system use” has suffered from a “too simplistic definition.” Despite decades of substantial research on system use, the concept is yet to receive strong theoretical scrutiny. Many measures of system use and the development of measures have been often idiosyncratic and lack credibility or comparability. This paper reviews various attempts at conceptualization and measurement of system use and then proposes a re-conceptualization of it as “the level of incorporation of an information system within a user’s processes.” The definition is supported with the theory of work systems, system, and Key-User-Group considerations. We then go on to develop the concept of a Functional- Interface-Point (FIP) and four dimensions of system usage: extent, the proportion of the FIPs used by the business process; frequency, the rate at which FIPs are used by the participants in the process; thoroughness, the level of use of information/functionality provided by the system at an FIP; and attitude towards use, a set of measures that assess the level of comfort, degree of respect and the challenges set forth by the system. The paper argues that the automation level, the proportion of the business process encoded by the information system has a mediating impact on system use. The article concludes with a discussion of some implications of this re-conceptualization and areas for follow on research.

A strategy for delayed research method selection : deciding between grounded theory and phenomenology

This paper presents a strategy for delayed research method selection in a qualitative interpretivist research. An exemplary case details how explorative interviews were designed and conducted in accordance with a paradigm prior to deciding whether to adopt grounded theory or phenomenology for data analysis. The focus here is to determine the most appropriate research strategy in this case the methodological framing to conduct research and represent findings, both of which are detailed. Research addressing current management issues requires both a flexible framework and the capability to consider the research problem from various angles, to derive tangible results for academia with immediate application to business demands. Researchers, and in particular novices, often struggle to decide on an appropriate research method suitable to address their research problem. This often applies to interpretative qualitative research where it is not always immediately clear which is the most appropriate method to use, as the research objectives shift and crystallize over time. This paper uses an exemplary case to reveal how the strategy for delayed research method selection contributes to deciding whether to adopt grounded theory or phenomenology in the initial phase of a PhD research project. In this case, semi-structured interviews were used for data generation framed in an interpretivist approach, situated in a business context. Research questions for this study were thoroughly defined and carefully framed in accordance with the research paradigm‟s principles, while at the same time ensuring that the requirements of both potential research methods were met. The grounded theory and phenomenology methods were compared and contrasted to determine their suitability and whether they meet the research objectives based on a pilot study. The strategy proposed in this paper is an alternative to the more „traditional‟ approach, which initially selects the methodological formulation, followed by data generation. In conclusion, the suggested strategy for delayed research method selection intends to help researchers identify and apply the most appropriate method to their research. This strategy is based on explorations of data generation and analysis in order to derive faithful results from the data generated.