Validating the design science research roadmap : through the lens of "the idealised model for theory development"

Design Science Research (DSR) has emerged as an important approach in Information Systems (IS) research. However, DSR is still in its genesis and has yet to achieve consensus on even the fundamentals, such as what methodology / approach to use for DSR. While there has been much effort to establish DSR methodologies, a complete, holistic and validated approach for the conduct of DSR to guide IS researcher (especially novice researchers) is yet to be established. Alturki et al. (2011) present a DSR ‘Roadmap’, making the claim that it is a complete and comprehensive guide for conducting DSR. This paper aims to further assess this Roadmap, by positioning it against the ‘Idealized Model for Theory Development’ (IM4TD) (Fischer & Gregor 2011). The IM4TD highlights the role of discovery and justification and forms of reasoning to progress in theory development. Fischer and Gregor (2011) have applied IM4TD’s hypothetico-deductive method to analyze DSR methodologies, which is adopted in this study to deductively validate the Alturki et al. (2011) Roadmap. The results suggest that the Roadmap adheres to the IM4TD, is reasonably complete, overcomes most shortcomings identified in other DSR methodologies and also highlights valuable refinements that should be considered within the IM4TD.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Eliciting Expert Knowledge in Conservation Science

Expert knowledge is used widely in the science and practice of conservation because of the complexity of problems, relative lack of data, and the imminent nature of many conservation decisions. Expert knowledge is substantive information on a particular topic that is not widely known by others. An expert is someone who holds this knowledge and who is often deferred to in its interpretation. We refer to predictions by experts of what may happen in a particular context as expert judgments. In general, an expert-elicitation approach consists of five steps: deciding how information will be used, determining what to elicit, designing the elicitation process, performing the elicitation, and translating the elicited information into quantitative statements that can be used in a model or directly to make decisions. This last step is known as encoding. Some of the considerations in eliciting expert knowledge include determining how to work with multiple experts and how to combine multiple judgments, minimizing bias in the elicited information, and verifying the accuracy of expert information. We highlight structured elicitation techniques that, if adopted, will improve the accuracy and information content of expert judgment and ensure uncertainty is captured accurately. We suggest four aspects of an expert elicitation exercise be examined to determine its comprehensiveness and effectiveness: study design and context, elicitation design, elicitation method, and elicitation output. Just as the reliability of empirical data depends on the rigor with which it was acquired so too does that of expert knowledge.

Challenging the authority of the autopsy in coronial investigations

The central purpose of this chapter is to address the tension between legal and medical discourses within the coronial/medico-legal system. In the context of a death investigation, medical expertise, manifest through the knowledge gained in an internal autopsy, is positioned as contributing the more valuable facts of the case, especially when contrasted with the evidence gathered at the scene of the death. We challenge this taken for granted understanding of medical knowledge in three ways: first, we examine the aspects of the history, philosophy and consequences of the processes by which the medical model gained its current dominance; second, we challenge the assumption that internal autopsy adds value to the death investigation, by utilising data from our own research in Australia; and finally, we engage with the debate about the purpose of a coronial/medico-legal investigation and role of an internal autopsy within that system.

Proteomics science & society : the role of knowledge translation in moving towards clinical applications

Background: Outside the mass-spectrometer, proteomics research does not take place in a vacuum. It is affected by policies on funding and research infrastructure. Proteomics research both impacts and is impacted by potential clinical applications. It provides new techniques & clinically relevant findings, but the possibilities for such innovations (and thus the perception of the potential for the field by funders) are also impacted by regulatory practices and the readiness of the health sector to incorporate proteomics-related tools & findings. Key to this process is how knowledge is translated. Methods: We present preliminary results from a multi-year social science project, funded by the Canadian Institutes of Health Research, on the processes and motivations for knowledge translation in the health sciences. The proteomics case within this wider study uses qualitative methods to examine the interplay between proteomics science and regulatory and policy makers regarding clinical applications of proteomics. Results: Adopting an interactive format to encourage conference attendees’ feedback, our poster focuses on deficits in effective knowledge translation strategies from the laboratory to policy, clinical, & regulatory arenas. An analysis of the interviews conducted to date suggests five significant choke points: the changing priorities of funding agencies; the complexity of proteomics research; the organisation of proteomics research; the relationship of proteomics to genomics and other omics sciences; and conflict over the appropriate role of standardisation. Conclusion: We suggest that engagement with aspects of knowledge translation, such as those mentioned above, is crucially important for the eventual clinical application ofproteomics science on any meaningful scale.

Editorial : promoting integrated development for smart and sustainable built environment

Purpose – This purpose of this paper is to introduce the new Smart and Sustainable Built Environment (SASBE) journal to readers by discussing the background and underlying principles of its establishment, the editorial visions, and the range of papers selected in this first issue. It will encourage readers and potential authors to consider the need for integrated approaches to sustainability problems, to take on emerging challenges in the built environment and to join the SASBE journal in finding and promoting optimum solutions. Design/methodology/approach – This paper explores the evolving nature of sustainability, the recent trends of sustainability endeavours in built environment and the current knowledge gaps. The need to bridge these gaps is then discussed in the context of suggested remedies and justifications. This leads to the development of a smart and sustainable built environment as a R&D philosophy for world researchers as part of their interactions with professional bodies and agencies such as CIB, UNEP and iiSBE, and the establishment of the SASBE journal. Findings – Sustainable development in the built environment requires holistic thinking and decision making and innovative solutions that enhance sustainability and result in mutually beneficial outcomes for all stakeholders. A dedicated forum, through the journal of SASBE, is much needed for the exploration, discussion, debate, and promotion of these integrated approaches. Originality/value – Through presenting an overview of the current issues and identifying gaps in the understanding and pursuit of sustainability in the built environment, this paper suggests potential areas for future research and practice as well as possible topics for authors to make new contributions.

Malay Kingship in Kedah : Religion, Trade, and Society

The book probes and examines traditional sources of royal power and control, as well as indigenous socio-political systems in the Malay world. It is focused on the north-western Malaysian Sultanate of Kedah which is acknowledged as the oldest unbroken independent kingship line in the ‘Malay and Islamic world’ with 1,000 years of history. Little scholarly attention has been paid to its pre-modern history, society, religion, system of government and unique geographic situation, potentially controlling both land and sea lines of communication into the remainder of Southeast Asia. It will thus provide the first comprehensive treatment in English, or other languages, on Kedah’s pre-modern and nineteenth century historiography and can provide a foundation for comparative studies of the various Malay states which is presently lacking. The proposed book also sheds much needed light on a range of important topics in Malay history including: Kedah and the northern Melaka Straits history, colonial expansion and rivalry, Southeast Asian history and politics, interregional migration and the influence of the sea peoples or orang laut, traditional Malay socio-political and economic life, Islamic influences and the course of Thai-Malay relations. The book attempts to offer a new understanding, not only of Kedah, but of the political and cultural development of the entire Malay world and of its relationships with the broader forces in both its continental and maritime settings. It argues that Kedah does not seem to follow, and in fact, often seems to contradict what has been commonly been accepted as the “typical model” of the traditional Malay state. Thus it concludes that the ruling dynasty has historically exploited a wide range of unique environmental conditions, local traditions, global spiritual trends and economic forces to preserve and strengthen its political position. The scope and theme of book The Kedah Sultanate is the oldest unbroken independent kingship lines in the “Malay world” with 1,000 years of history, and arguably one of the oldest in the Islamic world. In this study I examine key geopolitical and spiritual attributes of Malay kingship that have traditionally cemented the ruler, the peoples, and the environment. Brief description of the primary audience for the book: There is little written in English or Malay on Kedah’s pre twentieth century history. The available sources only look at certain aspects of Kedah’s history, are outdated or are confined to a specific period often outside the scope of the book. It is therefore anticipated that the readership and market for the book includes: • Scholars of Southeast Asian history, Islam, kingship, trade. • Academics & Historians (including: Asian, Thai history, Islamic, Maritime, Persian, South Asian, Southeast Asian and Colonial) • Libraries • Students, particularly those in Malaysia (especially the states of Kedah, Perlis and Penang), Thailand and Singapore. • Universities • Scholars and students in Political Science & International Relations

Practical considerations for integrating alternate reality gaming into science education

In this article, I present my experience with integrating an alternate reality gaming (ARG) framework into a pre-service science teacher education course. My goal is to provide an account of my experiences that can inform other science education practitioners at the tertiary and secondary levels that wish to adopt a similar approach in their classes. A game was designed to engage pre-service teachers with issues surrounding the declining enrolments in science, technology, engineering and mathematics disciplines (i.e., the STEM crisis; Tytler, 2007) and ways of re-engaging learners with STEM subjects. The use of ARG in science education is highly innovative. Literature on the use of ARG for educational purposes is scarce so in the article I have drawn on a range of available literature on gaming and ARG to define what it is and to suggest how it can be included in school science classrooms.

Traffic-related fine and ultrafine particle exposures of professional drivers and illness : An opportunity to better link exposure science and epidemiology to address an occupational hazard?

Exposures to traffic-related air pollution (TRAP) can be particularly high in transport microenvironments (i.e. in and around vehicles) despite the short durations typically spent there. There is a mounting body of evidence that suggests that this is especially true for fine (b2.5 μm) and ultrafine (b100 nm, UF) particles. Professional drivers, who spend extended periods of time in transport microenvironments due to their job, may incur exposures markedly higher than already elevated non-occupational exposures. Numerous epidemiological studies have shown a raised incidence of adverse health outcomes among professional drivers, and exposure to TRAP has been suggested as one of the possible causal factors. Despite this, data describing the range and determinants of occupational exposures to fine and UF particles are largely conspicuous in their absence. Such information could strengthen attempts to define the aetiology of professional drivers' illnesses as it relates to traffic combustion-derived particles. In this article, we suggest that the drivers' occupational fine and UF particle exposures are an exemplar case where opportunities exist to better link exposure science and epidemiology in addressing questions of causality. The nature of the hazard is first introduced, followed by an overview of the health effects attributable to exposures typical of transport microenvironments. Basic determinants of exposure and reduction strategies are also described, and finally the state of knowledge is briefly summarised along with an outline of the main unanswered questions in the topic area.

From IKEA model to the lean construction concept: A solution to implementation

The productivity of the construction industry worldwide has been declining over the past forty years. One approach to improving the situation is by the introduction of lean construction. The IKEA model has also been shown to be beneficial when used in the construction context. A framework is developed in which the lean construction concept is embodied within the IKEA model by integrating Virtual Prototyping (VP) technology and its implementation is described and evaluated through a real-life case implementing the lean production philosophy. The operational flows of the IKEA model and lean construction are then compared to analyze the feasibility of IKEA-based lean construction. It is concluded that the successful application of the IKEA model in this context will promote the implementation of lean construction and improve the efficiency of the industry.

Reputation modelling in citizen science for environmental acoustic data analysis

Citizen Science projects are initiatives in which members of the general public participate in scientific research projects and perform or manage research-related tasks such as data collection and/or data annotation. Citizen Science is technologically possible and scientifically significant. However, as the gathered information is from the crowd, the data quality is always hard to manage. There are many ways to manage data quality, and reputation management is one of the common approaches. In recent year, many research teams have deployed many audio or image sensors in natural environment in order to monitor the status of animals or plants. The collected data will be analysed by ecologists. However, as the amount of collected data is exceedingly huge and the number of ecologists is very limited, it is impossible for scientists to manually analyse all these data. The functions of existing automated tools to process the data are still very limited and the results are still not very accurate. Therefore, researchers have turned to recruiting general citizens who are interested in helping scientific research to do the pre-processing tasks such as species tagging. Although research teams can save time and money by recruiting general citizens to volunteer their time and skills to help data analysis, the reliability of contributed data varies a lot. Therefore, this research aims to investigate techniques to enhance the reliability of data contributed by general citizens in scientific research projects especially for acoustic sensing projects. In particular, we aim to investigate how to use reputation management to enhance data reliability. Reputation systems have been used to solve the uncertainty and improve data quality in many marketing and E-Commerce domains. The commercial organizations which have chosen to embrace the reputation management and implement the technology have gained many benefits. Data quality issues are significant to the domain of Citizen Science due to the quantity and diversity of people and devices involved. However, research on reputation management in this area is relatively new. We therefore start our investigation by examining existing reputation systems in different domains. Then we design novel reputation management approaches for Citizen Science projects to categorise participants and data. We have investigated some critical elements which may influence data reliability in Citizen Science projects. These elements include personal information such as location and education and performance information such as the ability to recognise certain bird calls. The designed reputation framework is evaluated by a series of experiments involving many participants for collecting and interpreting data, in particular, environmental acoustic data. Our research in exploring the advantages of reputation management in Citizen Science (or crowdsourcing in general) will help increase awareness among organizations that are unacquainted with its potential benefits.