A decision table method for randomness measurement

Data quality has become a major concern for organisations. The rapid growth in the size and technology of a databases and data warehouses has brought significant advantages in accessing, storing, and retrieving information. At the same time, great challenges arise with rapid data throughput and heterogeneous accesses in terms of maintaining high data quality. Yet, despite the importance of data quality, literature has usually condensed data quality into detecting and correcting poor data such as outliers, incomplete or inaccurate values. As a result, organisations are unable to efficiently and effectively assess data quality. Having an accurate and proper data quality assessment method will enable users to benchmark their systems and monitor their improvement. This paper introduces a granules mining for measuring the random degree of error data which will enable decision makers to conduct accurate quality assessment and allocate the most severe data, thereby providing an accurate estimation of human and financial resources for conducting quality improvement tasks.

Modelling passenger flow at airport terminals : individual agent decision model for stochastic passenger behaviour

Airport system is complex. Passenger dynamics within it appear to be complicate as well. Passenger behaviours outside standard processes are regarded more significant in terms of public hazard and service rate issues. In this paper, we devised an individual agent decision model to simulate stochastic passenger behaviour in airport departure terminal. Bayesian networks are implemented into the decision making model to infer the probabilities that passengers choose to use any in-airport facilities. We aim to understand dynamics of the discretionary activities of passengers.

An ingenious decision support system for remote health monitoring of pregnant women

Maternal deaths have been a critical issue for women living in rural and remote areas. The need to travel long distances, the shortage of primary care providers such as physicians, specialists and nurses, and the closing of small hospitals have been problems identified in many rural areas. Some research work has been undertaken and a few techniques have been developed to remotely measure the physiological condition of pregnant women through sophisticated ultrasound equipment. There are numerous ways to reduce maternal deaths, and an important step is to select the right approaches to achieving this reduction. One such approach is the provision of decision support systems in rural and remote areas. Decision support systems (DSSs) have already shown a great potential in many health fields. This thesis proposes an ingenious decision support system (iDSS) based on the methodology of survey instruments and identification of significant variables to be used in iDSS using statistical analysis. A survey was undertaken with pregnant women and factorial experimental design was chosen to acquire sample size. Variables with good reliability in any one of the statistical techniques such as Chi-square, Cronbach’s á and Classification Tree were incorporated in the iDSS. The decision support system was developed with significant variables such as: Place of residence, Seeing the same doctor, Education, Tetanus injection, Baby weight, Previous baby born, Place of birth, Assisted delivery, Pregnancy parity, Doctor visits and Occupation. The ingenious decision support system was implemented with Visual Basic as front end and Microsoft SQL server management as backend. Outcomes of the ingenious decision support system include advice on Symptoms, Diet and Exercise to pregnant women. On conditional system was sent and validated by the gynaecologist. Another outcome of ingenious decision support system was to provide better pregnancy health awareness and reduce long distance travel, especially for women in rural areas. The proposed system has qualities such as usefulness, accuracy and accessibility.

The applicability of aesthetic knowledge in organizational decision making processes

We argue that aesthetic knowledge, which is a form of tacit knowledge of beauty and related concepts, is an important, yet under-researched, topic in the study of organizational decision making processes. The significance of aesthetic knowledge for decision making processes is derived from its universal application by humans to commonplace practices; its use as the basis of decision criteria in complex situations to which the effective application of logic and reason is difficult; and its role both in assisting cognition in general and in enabling the choice of solutions generated from rational decision making processes. Despite its importance, the empirical research examining the application of aesthetic knowledge in organizational decision making processes is limited. Further detailed study of aesthetic knowledge in the context of organizational decision making processes is required to extend the recent movement in the field aimed at examining the role that extrarational, human-centered factors play in organizational decisions.

Teacher decision making in early childhood education

The study investigated early childhood teacher decision making at the preschool level in the state of Victoria, Australia. Victorian teachers at the preschool level were in an interesting position in 2004. Unlike most other Australian states Victoria did not have a curriculum framework guiding educational content and pedagogy. Consequently, this study was able to take advantage of this situation and examine teacher decision making at a time when early childhood teachers were relatively autonomous in deciding curriculum content. The opportunity to study teacher decision making in this way has since passed, as Victorian preschool teachers are now regulated by newly introduced state and national curricula frameworks. To identify influences affecting teacher decision making three preschool teachers were interviewed and curricula related policies were analysed. The data were analysed using Fairclough’s critical discourse analysis (CDA) technique. Critical discourse analysis enabled a close analysis of influences on teacher decision making illustrating how discourse is legitimated, marginalised, and silenced in certain curricula practices. Critical theory was the underpinning framework used for the study and enabled taken-for-granted understandings to be uncovered within early childhood policies and teacher interviews. Key findings were that despite there not being a government-mandated curricula framework for Victorian preschool education in 2004, teachers were held accountable for their curricula practice. Yet as professionals, early childhood teachers were denied public acknowledgment of their expertise as they were almost invisible in policy. Subsequently, teachers’ authority as professionals with curricula knowledge was diminished. The study found that developmentally appropriate practice (DAP) was a dominant discourse influencing teacher decision making (TDM). It operated as legitimated discourse in the 2004 Victorian preschool context. Additionally, the study found that teacher directed practice was legitimated, marginalised, and silenced by teachers. The findings have implications for early childhood teacher decision making at the practice, research, and policy levels. Findings show that the dominance of the DAP discourse informing teacher decision making limits other ways of thinking and practising.

Management characteristics and the decision to internationalize : exploration of exporters vs. non-exporters within the Chilean wine industry

The objective of this study was to identify key factors differentiating between exporters and non-exporters in the Chilean wine industry. Based on survey data collected from 61 wineries, the findings show that the main barriers for non-exporters are the lack of financial resources, limited quantities of stock for market expansion, management’s lack of knowledge and experience, and the high cost of travelling and participating in trade shows. The results also show that managers have educational levels and international experience exceeding those of other comparable New World wineries. Finally, in developing their main international markets, Chilean wineries did not target psychically close markets as identified in previous wine industry studies

Quantum models of cognition and decision

Much of our understanding of human thinking is based on probabilistic models. This innovative book by Jerome R. Busemeyer and Peter D. Bruza argues that, actually, the underlying mathematical structures from quantum theory provide a much better account of human thinking than traditional models. They introduce the foundations for modelling probabilistic-dynamic systems using two aspects of quantum theory. The first, "contextuality", is a way to understand interference effects found with inferences and decisions under conditions of uncertainty. The second, "entanglement", allows cognitive phenomena to be modelled in non-reductionist ways. Employing these principles drawn from quantum theory allows us to view human cognition and decision in a totally new light...

Wind-energy based path planning for unmanned aerial vehicles using Markov decision processes

Exploiting wind-energy is one possible way to extend flight duration for Unmanned Arial Vehicles. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain time-varying wind fields and plan a path through them. A Gaussian distribution is used to determine uncertainty in the Time-varying wind fields. We use Markov Decision Process to plan a path based upon the uncertainty of Gaussian distribution. Simulation results that compare the direct line of flight between start and target point and our planned path for energy consumption and time of travel are presented. The result is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.

Unstructured processes of strategic decision-making

The author aims at developing a better understanding of unstructured strategic decision making processes and the conditions for achieving successful decision outcomes. Specifically he investigates the processes used to make CRE (Corporate Real Estate) decisions. To reveal the fundamental differences between CRE decision-making in practice and the prescriptive ‘best practice’ advocated in the CRE literature, a study of seven leading Italian management consulting firms is undertaken addressing the aspects of content and process of decisions. This research makes its primary contribution by identifying the importance and difficulty of finding the right balance between problem complexity, process richness and cohesion to ensure a decision-making process that is sufficiently rich and yet quick enough to deliver a prompt outcome. While doing so, the study also provides more empirical evidence to some of the most established theories of decision-making, while reinterpreting their mono-dimensional arguments in a multi-dimensional model of successful decision-making.

Investigation of decision making issues in the use of current clinical information systems

Clinical information systems have become important tools in contemporary clinical patient care. However, there is a question of whether the current clinical information systems are able to effectively support clinicians in decision making processes. We conducted a survey to identify some of the decision making issues related to the use of existing clinical information systems. The survey was conducted among the end users of the cardiac surgery unit, quality and safety unit, intensive care unit and clinical costing unit at The Prince Charles Hospital (TPCH). Based on the survey results and reviewed literature, it was identified that support from the current information systems for decision-making is limited. Also, survey results showed that the majority of respondents considered lack in data integration to be one of the major issues followed by other issues such as limited access to various databases, lack of time and lack in efficient reporting and analysis tools. Furthermore, respondents pointed out that data quality is an issue and the three major data quality issues being faced are lack of data completeness, lack in consistency and lack in data accuracy. Conclusion: Current clinical information systems support for the decision-making processes in Cardiac Surgery in this institution is limited and this could be addressed by integrating isolated clinical information systems.

Using advanced traits of passengers to facilitate route-choice decision-making

Research interest in pedestrian behaviour spans the retail industry, emergency services, urban planners and other agencies. Most models to simulate and model pedestrian movement can be distinguished on the basis of geographical scale, from the micro-scale movement of obstacle avoidance, through the meso-scale of individuals planning multi-stop shopping trips, up to the macro-scale of overall flow of masses of people between places. In this paper, route-choice decision-making model is devised for modelling passengers flow in airport terminal. A set of devised advanced traits of passengers is firstly proposed. Advanced traits take into account a passenger’s cognitive preferences and demonstrate underlying motivations of route-choice decisions. Although the activities of passengers are normally regarded as stochastic and sometimes unpredictable, real scenarios of passenger flows are basically feasible to be compared with virtual simulations in terms of tactical route-choice decision-making. Passengers in the model are as intelligent agents who possess a bunch of initial basic traits and are categorized into five distinguish groups in terms of routing preferences. Route choices are consecutively determined by inferring current advanced traits according to the utility matrix.

A decision support system for sustainable urban development : the integrated land use and transportation indexing model

Broad, early definitions of sustainable development have caused confusion and hesitation among local authorities and planning professionals. This confusion has arisen because loosely defined principles of sustainable development have been employed when setting policies and planning projects, and when gauging the efficiencies of these policies in the light of designated sustainability goals. The question of how this theory-rhetoric-practice gap can be filled is the main focus of this chapter. It examines the triple bottom line approach–one of the sustainability accounting approaches widely employed by governmental organisations–and the applicability of this approach to sustainable urban development. The chapter introduces the ‘Integrated Land Use and Transportation Indexing Model’ that incorporates triple bottom line considerations with environmental impact assessment techniques via a geographic, information systemsbased decision support system. This model helps decision-makers in selecting policy options according to their economic, environmental and social impacts. Its main purpose is to provide valuable knowledge about the spatial dimensions of sustainable development, and to provide fine detail outputs on the possible impacts of urban development proposals on sustainability levels. In order to embrace sustainable urban development policy considerations, the model is sensitive to the relationship between urban form, travel patterns and socio-economic attributes. Finally, the model is useful in picturing the holistic state of urban settings in terms of their sustainability levels, and in assessing the degree of compatibility of selected scenarios with the desired sustainable urban future.