Understanding the user - why, what and how?

Explains the need, importance, purposes and scope of user studies, discusses procedure for conducting sound user studies together with associated problems of research like selection of problem, formulation of hypothesis, design of study, sampling strategy, data collection methods, scaling techniques, pilot study, processing and analysis of data, testing of hypothesis, interpretation, drawing inferences, communication and dissemination of results and finally concludes by highlighting methodological flaws and gaps in user studies

Globalization of Production and the Competitiveness of Small and Medium-sized Enterprises in Asia and the Pacific: Trends and Prospects

This final section reviews the requirements for increasing the competitiveness prospects of Asia-Pacific SMEs within the context of the challenges of the globalization of production, and seeks to provide some specific recommendations on how SME development in the region could be taken in new and potentially fruitful directions. These recommendations seek to address the core question running through this research paper, namely: what can usefully be done to increase the competitive performance of Asia-Pacific SMEs?SMEs, competitiveness, Asia, Pacific, policy, recommendations

Finite state automata: Dynamic task environments in problem solving research.

This paper presents a new research paradigm for analysing human learning in dynamic task environments based on the theory of finite-state automata. Some of the advantages of the approach are outlined. (1) It is possible to design classes of formally well-described dynamic task environments instead of idiosyncratic microworlds that are difficult if not impossible to compare. (2) The approach suggests assumptions about the mental representation of a discrete dynamic system. (3) The finite-state automata formalism suggests systematic and appropriate diagnostic procedures. (4) Using finite-state automata to design dynamic task environments, one does not have to give up the "ecological validity" appeal of computer-simulated scenarios. An experiment on the utility of an external memory support system with system complexity and type of memory support as independent variables is reported to illustrate the application of the formal framework. Systematically derived dependent variables reflect both system knowledge and control performance. The results suggest that the benefits due to the availability of the external aid vary as a function of the complexity of the task. Also, using reaction time measurements, priming phenomena have been found that point to the importance of sequentiality in the representation of discrete systems. It is concluded that the approach, although not entirely new in experimental psychology, awaits further exploration in research on human learning in dynamic task environments and promises to be a stimulating paradigm for both basic and applied research

Trade Facilitation Negotiations in the WTO: Implications for Bangladesh and Other Least Developed and Developing Countries

This paper provides an overview of how trade facilitation has been addressed in the WTO to date, and how this may affect Bangladesh’s negotiating strategy on trade facilitation in the upcoming Cancun Ministerial and beyond. The paper also defines the term “trade facilitation”, reviews the development of trade facilitation in the international community apart from the WTO, and examines the work that has taken place on the issue in the WTO including the current state of play in trade facilitation discussions. Apart from providing an overview of WTO provisions that are relevant to trade facilitation, as a part of the Doha Development Agenda (DDA), and summarising the proposals that various WTO members have made for enhancing trade facilitation in the WTO, the paper addresses some of the implementation issues WTO members face with respect to trade facilitation. It further examines the implications of trade facilitation negotiations on Bangladesh and other least developed and developing countries, and how these will shape the negotiating strategies and policies of these countries.Trade Facilitation, WTO, LDC, Bangladesh

Understanding the user - why, what and how?

Explains the need, importance, purposes and scope of user studies, discusses procedure for conducting sound user studies together with associated problems of research like selection of problem, formulation of hypothesis, design of study, sampling strategy, data collection methods, scaling techniques, pilot study, processing and analysis of data, testing of hypothesis, interpretation, drawing inferences, communication and dissemination of results and finally concludes by highlighting methodological flaws and gaps in user studies

BiplotGUI: Interactive Biplots in R

Biplots simultaneously provide information on both the samples and the variables of a data matrix in two- or three-dimensional representations. The BiplotGUI package provides a graphical user interface for the construction of, interaction with, and manipulation of biplots in R. The samples are represented as points, with coordinates determined either by the choice of biplot, principal coordinate analysis or multidimensional scaling. Various transformations and dissimilarity metrics are available. Information on the original variables is incorporated by linear or non-linear calibrated axes. Goodness-of-fit measures are provided. Additional descriptors can be superimposed, including convex hulls, alpha-bags, point densities and classification regions. Amongst the interactive features are dynamic variable value prediction, zooming and point and axis drag-and-drop. Output can easily be exported to the R workspace for further manipulation. Three-dimensional biplots are incorporated via the rgl package. The user requires almost no knowledge of R syntax.

Principles for data analysis workflows

Traditional data science education often omits training on research workflows: the process that moves a scientific investigation from raw data to coherent research question to insightful contribution. In this paper, we elaborate basic principles of a reproducible data analysis workflow by defining three phases: the Exploratory, Refinement, and Polishing Phases. Each workflow phase is roughly centered around the audience to whom research decisions, methodologies, and results are being immediately communicated. Importantly, each phase can also give rise to a number of research products beyond traditional academic publications. Where relevant, we draw analogies between principles for data-intensive research workflows and established practice in software development. The guidance provided here is not intended to be a strict rulebook; rather, the suggestions for practices and tools to advance reproducible, sound data-intensive analysis may furnish support for both students and current professionals

Post-Acceptance of Electronic Medical Records: Evidence from a Longitudinal Field Study

Many studies investigating post-acceptance of electronic medical records (EMR) assume that healthcare professionals exclusively base their continuance behavior on reasoned actions. While rational considerations certainly affect the intention to use an EMR, it does not fully explain the definitive user continuance behavior. Evidence exists that also subliminal effects such as habits and emotions play an important role. Consequently, we propose to investigate post-acceptance of EMR applying three different, but complementary views: (i) continuance behavior as result of reasoned actions, (ii) continuance behavior as result of emotional responses, and (iii) continuance behavior as result of habitual responses. The results from a longitudinal field study showed that automatic behavior, enabled by sufficient facilitating conditions and a good task-technology-fit, as well as positive emotions considerably affected healthcare professionals EMR continuance behavior. It also showed that a user’s computer literacy level didn’t play a significant role regarding the post-acceptance behavior

Doctor of Philosophy

dissertationClinical decision support systems (CDSS) and electronic health records (EHR) have been widely adopted but do not support a high level of reasoning for the clinician. As a result, workflow incongruity and provider frustrations lead to more errors in reasoning. Other successful fields such as defense, aviation, and the military have used task complexity as a key factor in decision support system development. Task complexity arises during the interaction of the user and the tasks. Therefore, in this dissertation I have utilized different human factor methods to explore task complexity factors to understand their utility in health information technology system design. The first study addresses the question of generalizing complexity through a clinical complexity model. In this study, we integrated and validated a patient and task complexity model into a clinical complexity model tailored towards healthcare to serve as the initial framework for data analysis in our subsequent studies. The second study addresses the question of the coping strategies of infectious disease (ID) clinicians while dealing with complex decision tasks. The study concluded that clinicians use multiple cognitive strategies that help them to switch between automatic cognitive processes and analytical processes. The third study identified the complexity contributing factors from the transcripts of the observations conducted in the ID domain. The clinical complexity model developed in the first study guided the research for identifying the prominent complexity iv factors to recommend innovative healthcare technology system design. The fourth study, a pilot exploratory study, demonstrated the feasibility of developing a population information display from querying real complex patient information from an actual clinical database as well as identifying the ideal features of population information display. In summary, this dissertation adds to the knowledge about how clinicians adapt their information environment to deal with complexity. First, it contributes by developing a clinical complexity model that integrates both patient and task complexity. Second, it provides specific design recommendations for future innovative health information technology systems. Last, this dissertation also suggests that understanding task complexity in the healthcare team domain may help to better design of interface system

Transitioning to a Data Driven Mental Health Practice: Collaborative Expert Sessions for Knowledge and Hypothesis Finding

The surge in the amount of available data in health care enables a novel, exploratory research approach that revolves around finding new knowledge and unexpected hypotheses from data instead of carrying out well-defined data analysis tasks. We propose a specification of the Cross Industry Standard Process for Data Mining (CRISP-DM), suitable for conducting expert sessions that focus on finding new knowledge and hypotheses in collaboration with local workforce. Our proposed specification that we name CRISP-IDM is evaluated in a case study at the psychiatry department of the University Medical Center Utrecht. Expert interviews were conducted to identify seven research themes in the psychiatry department, which were researched in cooperation with local health care professionals using data visualization as a modeling tool. During 19 expert sessions, two results that were directly implemented and 29 hypotheses for further research were found, of which 24 were not imagined during the initial expert interviews. Our work demonstrates the viability and benefits of involving work floor people in the analyses and the possibility to effectively find new knowledge and hypotheses using our CRISP-IDM method