Analysing the complexity of the model-based decision making processes within the industrial management context

PURPOSE The decision-making process plays a key role in organizations. Every decision-making process produces a final choice that may or may not prompt action. Recurrently, decision makers find themselves in the dichotomous question of following a traditional sequence decision-making process where the output of a decision is used as the input of the next stage of the decision, or following a joint decision-making approach where several decisions are taken simultaneously. The implication of the decision-making process will impact different players of the organization. The choice of the decision- making approach becomes difficult to find, even with the current literature and practitioners’ knowledge. The pursuit of better ways for making decisions has been a common goal for academics and practitioners. Management scientists use different techniques and approaches to improve different types of decisions. The purpose of this decision is to use the available resources as well as possible (data and techniques) to achieve the objectives of the organization. The developing and applying of models and concepts may be helpful to solve managerial problems faced every day in different companies. As a result of this research different decision models are presented to contribute to the body of knowledge of management science. The first models are focused on the manufacturing industry and the second part of the models on the health care industry. Despite these models being case specific, they serve the purpose of exemplifying that different approaches to the problems and could provide interesting results. Unfortunately, there is no universal recipe that could be applied to all the problems. Furthermore, the same model could deliver good results with certain data and bad results for other data. A framework to analyse the data before selecting the model to be used is presented and tested in the models developed to exemplify the ideas. METHODOLOGY As the first step of the research a systematic literature review on the joint decision is presented, as are the different opinions and suggestions of different scholars. For the next stage of the thesis, the decision-making process of more than 50 companies was analysed in companies from different sectors in the production planning area at the Job Shop level. The data was obtained using surveys and face-to-face interviews. The following part of the research into the decision-making process was held in two application fields that are highly relevant for our society; manufacturing and health care. The first step was to study the interactions and develop a mathematical model for the replenishment of the car assembly where the problem of “Vehicle routing problem and Inventory” were combined. The next step was to add the scheduling or car production (car sequencing) decision and use some metaheuristics such as ant colony and genetic algorithms to measure if the behaviour is kept up with different case size problems. A similar approach is presented in a production of semiconductors and aviation parts, where a hoist has to change from one station to another to deal with the work, and a jobs schedule has to be done. However, for this problem simulation was used for experimentation. In parallel, the scheduling of operating rooms was studied. Surgeries were allocated to surgeons and the scheduling of operating rooms was analysed. The first part of the research was done in a Teaching hospital, and for the second part the interaction of uncertainty was added. Once the previous problem had been analysed a general framework to characterize the instance was built. In the final chapter a general conclusion is presented. FINDINGS AND PRACTICAL IMPLICATIONS The first part of the contributions is an update of the decision-making literature review. Also an analysis of the possible savings resulting from a change in the decision process is made. Then, the results of the survey, which present a lack of consistency between what the managers believe and the reality of the integration of their decisions. In the next stage of the thesis, a contribution to the body of knowledge of the operation research, with the joint solution of the replenishment, sequencing and inventory problem in the assembly line is made, together with a parallel work with the operating rooms scheduling where different solutions approaches are presented. In addition to the contribution of the solving methods, with the use of different techniques, the main contribution is the framework that is proposed to pre-evaluate the problem before thinking of the techniques to solve it. However, there is no straightforward answer as to whether it is better to have joint or sequential solutions. Following the proposed framework with the evaluation of factors such as the flexibility of the answer, the number of actors, and the tightness of the data, give us important hints as to the most suitable direction to take to tackle the problem. RESEARCH LIMITATIONS AND AVENUES FOR FUTURE RESEARCH In the first part of the work it was really complicated to calculate the possible savings of different projects, since in many papers these quantities are not reported or the impact is based on non-quantifiable benefits. The other issue is the confidentiality of many projects where the data cannot be presented. For the car assembly line problem more computational power would allow us to solve bigger instances. For the operation research problem there was a lack of historical data to perform a parallel analysis in the teaching hospital. In order to keep testing the decision framework it is necessary to keep applying more case studies in order to generalize the results and make them more evident and less ambiguous. The health care field offers great opportunities since despite the recent awareness of the need to improve the decision-making process there are many opportunities to improve. Another big difference with the automotive industry is that the last improvements are not spread among all the actors. Therefore, in the future this research will focus more on the collaboration between academia and the health care sector.

A Belief System's Organization Based on a Computational Model of the Dynamic Context: First Approximation

In this article we present a model of organization of a belief system based on a set of binary recursive functions that characterize the dynamic context that modifies the beliefs. The initial beliefs are modeled by a set of two-bit words that grow, update, and generate other beliefs as the different experiences of the dynamic context appear. Reason is presented as an emergent effect of the experience on the beliefs. The system presents a layered structure that allows a functional organization of the belief system. Our approach seems suitable to model different ways of thinking and to apply to different realistic scenarios such as ideologies.

Towards a standards-based autonomic context management system

Pervasive computing applications must be sufficiently autonomous to adapt their behaviour to changes in computing resources and user requirements. This capability is known as context-awareness. In some cases, context-aware applications must be implemented as autonomic systems which are capable of dynamically discovering and replacing context sources (sensors) at run-time. Unlike other types of application autonomy, this kind of dynamic reconfiguration has not been sufficiently investigated yet by the research community. However, application-level context models are becoming common, in order to ease programming of context-aware applications and support evolution by decoupling applications from context sources. We can leverage these context models to develop general (i.e., application-independent) solutions for dynamic, run-time discovery of context sources (i.e., context management). This paper presents a model and architecture for a reconfigurable context management system that supports interoperability by building on emerging standards for sensor description and classification.

Expanding the evidence within evidence-based healthcare:thinking about the context, acceptability and feasibility of interventions

Evidence-based medicine is crucial to contemporary healthcare. It is dependent on systematic review methodology modelled on an arguably inadequate hierarchy of evidence. There has been a significant increase in medical and health research using qualitative and mixed method designs. The perspective taken in this article is that we need to broaden our evidence base if we are to fully take account of issues of context, acceptability and feasibility in the development and implementation of healthcare interventions. One way of doing this is to use a range of methods that better fit the different aspects of intervention development and implementation. Methods for the systematic review of evidence, other than randomised-controlled trials, are available and there is a readiness to incorporate these other types of evidence into good-practice guidance, but we need a clear methodology to translate these advances in research into the world of policy.

Bringing a construction site into the lab:a context-relevant lab-based evaluation of a multimodal mobile application

Mobile technology has not yet achieved widespread acceptance in the Architectural, Engineering, and Construction (AEC) industry. This paper presents work that is part of an ongoing research project focusing on the development of multimodal mobile applications for use in the AEC industry. This paper focuses specifically on a context-relevant lab-based evaluation of two input modalities – stylus and soft-keyboard v. speech-based input – for use with a mobile data collection application for concrete test technicians. The manner in which the evaluation was conducted as well as the results obtained are discussed in detail.

A gloss composition and context clustering based distributed word sense representation model

In recent years, there has been an increasing interest in learning a distributed representation of word sense. Traditional context clustering based models usually require careful tuning of model parameters, and typically perform worse on infrequent word senses. This paper presents a novel approach which addresses these limitations by first initializing the word sense embeddings through learning sentence-level embeddings from WordNet glosses using a convolutional neural networks. The initialized word sense embeddings are used by a context clustering based model to generate the distributed representations of word senses. Our learned representations outperform the publicly available embeddings on half of the metrics in the word similarity task, 6 out of 13 sub tasks in the analogical reasoning task, and gives the best overall accuracy in the word sense effect classification task, which shows the effectiveness of our proposed distributed distribution learning model.

Reasoning over knowledge-based generation of situations in context spaces to reduce food waste

With the ever-growing amount of connected sensors (IoT), making sense of sensed data becomes even more important. Pervasive computing is a key enabler for sustainable solutions, prominent examples are smart energy systems and decision support systems. A key feature of pervasive systems is situation awareness which allows a system to thoroughly understand its environment. It is based on external interpretation of data and thus relies on expert knowledge. Due to the distinct nature of situations in different domains and applications, the development of situation aware applications remains a complex process. This thesis is concerned with a general framework for situation awareness which simplifies the development of applications. It is based on the Situation Theory Ontology to provide a foundation for situation modelling which allows knowledge reuse. Concepts of the Situation Theory are mapped to the Context Space Theory which is used for situation reasoning. Situation Spaces in the Context Space are automatically generated with the defined knowledge. For the acquisition of sensor data, the IoT standards O-MI/O-DF are integrated into the framework. These allow a peer-to-peer data exchange between data publisher and the proposed framework and thus a platform independent subscription to sensed data. The framework is then applied for a use case to reduce food waste. The use case validates the applicability of the framework and furthermore serves as a showcase for a pervasive system contributing to the sustainability goals. Leading institutions, e.g. the United Nations, stress the need for a more resource efficient society and acknowledge the capability of ICT systems. The use case scenario is based on a smart neighbourhood in which the system recommends the most efficient use of food items through situation awareness to reduce food waste at consumption stage.

Venture Capital for University Spin-Outs Companies in the context of University-based Entrepreneurial Ecosystems: an International Comparison

The objectives are, firstly, to identify the role of the university-focused intermediaries, specifically University-focused Venture Capital Firms (UVCs), in order to explain how they interact at the early stage of University Spin-out Companies (USOs) creation, particularly regarding knowledge sharing. Secondly, to analyse whether they change their position once the USO is developed, in the context of the dynamics of a university-based entrepreneurial ecosystem.

Understanding Red Blood Cell Parameters In The Context Of The Frailty Phenotype: Interpretations Of The Fibra (frailty In Brazilian Seniors) Study.

Frailty and anemia in the elderly appear to share a common pathophysiology associated with chronic inflammatory processes. This study uses an analytical, cross-sectional, population-based methodology to investigate the probable relationships between frailty, red blood cell parameters and inflammatory markers in 255 community-dwelling elders aged 65 years or older. The frailty phenotype was assessed by non-intentional weight loss, fatigue, low grip strength, low energy expenditure and reduced gait speed. Blood sample analyses were performed to determine hemoglobin level, hematocrit and reticulocyte count, as well as the inflammatory variables IL-6, IL-1ra and hsCRP. In the first multivariate analysis (model I), considering only the erythroid parameters, Hb concentration was a significant variable for both general frailty status and weight loss: a 1.0g/dL drop in serum Hb concentration represented a 2.02-fold increase (CI 1.12-3.63) in an individual's chance of being frail. In the second analysis (model II), which also included inflammatory cytokine levels, hsCRP was independently selected as a significant variable. Each additional year of age represented a 1.21-fold increase in the chance of being frail, and each 1-unit increase in serum hsCRP represented a 3.64-fold increase in the chance of having the frailty phenotype. In model II reticulocyte counts were associated with weight loss and reduced metabolic expenditure criteria. Our findings suggest that reduced Hb concentration, reduced RetAbs count and elevated serum hsCRP levels should be considered components of frailty, which in turn is correlated with sarcopenia, as evidenced by weight loss.

A contribution to the phytogeography of Brazilian campos: an analysis based on Poaceae

Twenty areas from eight Brazilian states were compared according to a list of 224 species of Poaceae. In order to determinate affinity patterns between the areas, a binary matrix was submitted to cluster and ordination analysis. The patterns found were then faced to climate and geographic position. The scores corresponding to the areas obtained from the cluster analysis showed a strong correlation to temperature. The scores corresponding to the species suggest a gradient that associates distribution patterns to the photosynthetic pathway (C3 or C4). The current results suggest that the traditional classification of the Southern American grasslands might require some modification in order to be broadly applicable in the Brazilian context.

The ichthyofauna of upper rio Capivari: defining conservation strategies based on the composition and distribution of fish species

Although the rio Capivari basin is recognized as an area of great importance for the ichthyofauna, it lacks virtually every basic requirement for the definition of appropriate conservation strategies, since not even its species composition is known. The objective of this work is to determine the composition and distribution of fish species in the upper rio Capivari basin, relating them to the local physical features, and to evaluate the effectiveness of proposed conservations units, delimited based on areas of native vegetation remains, on the conservation of local ichthyofauna. During 2007, 50 different watercourses were sampled with gillnets, cast nets and kick nets. A total of 1308 individuals belonging to 41 species were captured. Degree of conservation, altitude and width were the parameters that best explained fish species richness. Considering the recently proposed boundaries for potential conservation units in the region only 15 or 20 out of 41 species would be found in the State Park and Environmental Protection Area respectively. In practice, the proposed conservation units would not be effective tools for fish conservation, since it would be located in mountainous areas of high altitude, of headwaters streams and where few species are found. In such context, the conservation of specific stretches of larger rivers is critical.