23 resultados para Socialist Systems and Transitional Economies: Performance and Prospects
Resumo:
Thanks to decades of research, gait analysis has become an efficient tool. However, mainly due to the price of the motion capture systems, standard gait laboratories have the capability to measure only a few consecutive steps of ground walking. Recently, wearable systems were proposed to measure human motion without volume limitation. Although accurate, these systems are incompatible with most of existing calibration procedures and several years of research will be necessary for their validation. A new approach consisting of using a stationary system with a small capture volume for the calibration procedure and then to measure gait using a wearable system could be very advantageous. It could benefit from the knowledge related to stationary systems, allow long distance monitoring and provide new descriptive parameters. The aim of this study was to demonstrate the potential of this approach. Thus, a combined system was proposed to measure the 3D lower body joints angles and segmental angular velocities. It was then assessed in terms of reliability towards the calibration procedure, repeatability and concurrent validity. The dispersion of the joint angles across calibrations was comparable to those of stationary systems and good reliability was obtained for the angular velocities. The repeatability results confirmed that mean cycle kinematics of long distance walks could be used for subjects' comparison and pointed out an interest for the variability between cycles. Finally, kinematics differences were observed between participants with different ankle conditions. In conclusion, this study demonstrated the potential of a mixed approach for human movement analysis.
Resumo:
One of the key emphases of these three essays is to provide practical managerial insight. However, good practical insight, can only be created by grounding it firmly on theoretical and empirical research. Practical experience-based understanding without theoretical grounding remains tacit and cannot be easily disseminated. Theoretical understanding without links to real life remains sterile. My studies aim to increase the understanding of how radical innovation could be generated at large established firms and how it can have an impact on business performance as most businesses pursue innovation with one prime objective: value creation. My studies focus on large established firms with sales revenue exceeding USD $ 1 billion. Usually large established firms cannot rely on informal ways of management, as these firms tend to be multinational businesses operating with subsidiaries, offices, or production facilities in more than one country. I. Internal and External Determinants of Corporate Venture Capital Investment The goal of this chapter is to focus on CVC as one of the mechanisms available for established firms to source new ideas that can be exploited. We explore the internal and external determinants under which established firms engage in CVC to source new knowledge through investment in startups. We attempt to make scholars and managers aware of the forces that influence CVC activity by providing findings and insights to facilitate the strategic management of CVC. There are research opportunities to further understand the CVC phenomenon. Why do companies engage in CVC? What motivates them to continue "playing the game" and keep their active CVC investment status. The study examines CVC investment activity, and the importance of understanding the influential factors that make a firm decide to engage in CVC. The main question is: How do established firms' CVC programs adapt to changing internal conditions and external environments. Adaptation typically involves learning from exploratory endeavors, which enable companies to transform the ways they compete (Guth & Ginsberg, 1990). Our study extends the current stream of research on CVC. It aims to contribute to the literature by providing an extensive comparison of internal and external determinants leading to CVC investment activity. To our knowledge, this is the first study to examine the influence of internal and external determinants on CVC activity throughout specific expansion and contraction periods determined by structural breaks occurring between 1985 to 2008. Our econometric analysis indicates a strong and significant positive association between CVC activity and R&D, cash flow availability and environmental financial market conditions, as well as a significant negative association between sales growth and the decision to engage into CVC. The analysis of this study reveals that CVC investment is highly volatile, as demonstrated by dramatic fluctuations in CVC investment activity over the past decades. When analyzing the overall cyclical CVC period from 1985 to 2008 the results of our study suggest that CVC activity has a pattern influenced by financial factors such as the level of R&D, free cash flow, lack of sales growth, and external conditions of the economy, with the NASDAQ price index as the most significant variable influencing CVC during this period. II. Contribution of CVC and its Interaction with R&D to Value Creation The second essay takes into account the demands of corporate executives and shareholders regarding business performance and value creation justifications for investments in innovation. Billions of dollars are invested in CVC and R&D. However there is little evidence that CVC and its interaction with R&D create value. Firms operating in dynamic business sectors seek to innovate to create the value demanded by changing market conditions, consumer preferences, and competitive offerings. Consequently, firms operating in such business sectors put a premium on finding new, sustainable and competitive value propositions. CVC and R&D can help them in this challenge. Dushnitsky and Lenox (2006) presented evidence that CVC investment is associated with value creation. However, studies have shown that the most innovative firms do not necessarily benefit from innovation. For instance Oyon (2007) indicated that between 1995 and 2005 the most innovative automotive companies did not obtain adequate rewards for shareholders. The interaction between CVC and R&D has generated much debate in the CVC literature. Some researchers see them as substitutes suggesting that firms have to choose between CVC and R&D (Hellmann, 2002), while others expect them to be complementary (Chesbrough & Tucci, 2004). This study explores the interaction that CVC and R&D have on value creation. This essay examines the impact of CVC and R&D on value creation over sixteen years across six business sectors and different geographical regions. Our findings suggest that the effect of CVC and its interaction with R&D on value creation is positive and significant. In dynamic business sectors technologies rapidly relinquish obsolete, consequently firms operating in such business sectors need to continuously develop new sources of value creation (Eisenhardt & Martin, 2000; Qualls, Olshavsky, & Michaels, 1981). We conclude that in order to impact value creation, firms operating in business sectors such as Engineering & Business Services, and Information Communication & Technology ought to consider CVC as a vital element of their innovation strategy. Moreover, regarding the CVC and R&D interaction effect, our findings suggest that R&D and CVC are complementary to value creation hence firms in certain business sectors can be better off supporting both R&D and CVC simultaneously to increase the probability of generating value creation. III. MCS and Organizational Structures for Radical Innovation Incremental innovation is necessary for continuous improvement but it does not provide a sustainable permanent source of competitiveness (Cooper, 2003). On the other hand, radical innovation pursuing new technologies and new market frontiers can generate new platforms for growth providing firms with competitive advantages and high economic margin rents (Duchesneau et al., 1979; Markides & Geroski, 2005; O'Connor & DeMartino, 2006; Utterback, 1994). Interestingly, not all companies distinguish between incremental and radical innovation, and more importantly firms that manage innovation through a one-sizefits- all process can almost guarantee a sub-optimization of certain systems and resources (Davila et al., 2006). Moreover, we conducted research on the utilization of MCS along with radical innovation and flexible organizational structures as these have been associated with firm growth (Cooper, 2003; Davila & Foster, 2005, 2007; Markides & Geroski, 2005; O'Connor & DeMartino, 2006). Davila et al. (2009) identified research opportunities for innovation management and provided a list of pending issues: How do companies manage the process of radical and incremental innovation? What are the performance measures companies use to manage radical ideas and how do they select them? The fundamental objective of this paper is to address the following research question: What are the processes, MCS, and organizational structures for generating radical innovation? Moreover, in recent years, research on innovation management has been conducted mainly at either the firm level (Birkinshaw, Hamel, & Mol, 2008a) or at the project level examining appropriate management techniques associated with high levels of uncertainty (Burgelman & Sayles, 1988; Dougherty & Heller, 1994; Jelinek & Schoonhoven, 1993; Kanter, North, Bernstein, & Williamson, 1990; Leifer et al., 2000). Therefore, we embarked on a novel process-related research framework to observe the process stages, MCS, and organizational structures that can generate radical innovation. This article is based on a case study at Alcan Engineered Products, a division of a multinational company provider of lightweight material solutions. Our observations suggest that incremental and radical innovation should be managed through different processes, MCS and organizational structures that ought to be activated and adapted contingent to the type of innovation that is being pursued (i.e. incremental or radical innovation). More importantly, we conclude that radical can be generated in a systematic way through enablers such as processes, MCS, and organizational structures. This is in line with the findings of Jelinek and Schoonhoven (1993) and Davila et al. (2006; 2007) who show that innovative firms have institutionalized mechanisms, arguing that radical innovation cannot occur in an organic environment where flexibility and consensus are the main managerial mechanisms. They rather argue that radical innovation requires a clear organizational structure and formal MCS.
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Due to various contexts and processes, forensic science communities may have different approaches, largely influenced by their criminal justice systems. However, forensic science practices share some common characteristics. One is the assurance of a high (scientific) quality within processes and practices. For most crime laboratory directors and forensic science associations, this issue is conditioned by the triangle of quality, which represents the current paradigm of quality assurance in the field. It consists of the implementation of standardization, certification, accreditation, and an evaluation process. It constitutes a clear and sound way to exchange data between laboratories and enables databasing due to standardized methods ensuring reliable and valid results; but it is also a means of defining minimum requirements for practitioners' skills for specific forensic science activities. The control of each of these aspects offers non-forensic science partners the assurance that the entire process has been mastered and is trustworthy. Most of the standards focus on the analysis stage and do not consider pre- and post-laboratory stages, namely, the work achieved at the investigation scene and the evaluation and interpretation of the results, intended for intelligence beneficiaries or for court. Such localized consideration prevents forensic practitioners from identifying where the problems really lie with regard to criminal justice systems. According to a performance-management approach, scientific quality should not be restricted to standardized procedures and controls in forensic science practice. Ensuring high quality also strongly depends on the way a forensic science culture is assimilated (into specific education training and workplaces) and in the way practitioners understand forensic science as a whole.
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In this discussion, after a few general comments, I will propose a systems reading of the intervention so elegantly described by Kaija Puura. I will draw parallels between the therapeutic and the family groups as framing-developing systems and formalize the steps taken by the family toward healing under the influence of the therapist's team. En esta discusión, después de algunos comentarios generales, propongo una lectura sistemática de la intervención tan elegantemente descrita por Kaija Puura. Buscaré paralelos entre los grupos terapéuticos y de familia como sistemas de desarrollo enmarcado y formalizaré los pasos tomados por la familia hacia la cicatrización bajo la influencia del equipo del terapista. Après quelques commentaires généraux, je proposerai dans cette discussion une lecture systémique de l'intervention si élégamment décrite par Kaija Puura. J'établirai des parallèles entre les groupes thérapeutiques et familiaux en tant que systèmes d'encadrement-développement et je formaliserai les étapes de guérison franchies par la famille grâce à l'influence de l'équipe thérapeutique. In dieser Diskussion, werde ich nach einigen allgemeineren Aussagen, eine systemische Lesart der von Kaija Puura so eingängig beschriebenen Intervention vorschlagen. Ich werde darin Parallelen zwischen der therapeutischen und Rahmengebenden Familiengruppen ziehen, und die Schritte der Familien hin zu einer Heilung unter dem Einfluss des Therapeutenteams formalisieren.
Resumo:
Dans cette thèse, nous étudions les aspects comportementaux d'agents qui interagissent dans des systèmes de files d'attente à l'aide de modèles de simulation et de méthodologies expérimentales. Chaque période les clients doivent choisir un prestataire de servivce. L'objectif est d'analyser l'impact des décisions des clients et des prestataires sur la formation des files d'attente. Dans un premier cas nous considérons des clients ayant un certain degré d'aversion au risque. Sur la base de leur perception de l'attente moyenne et de la variabilité de cette attente, ils forment une estimation de la limite supérieure de l'attente chez chacun des prestataires. Chaque période, ils choisissent le prestataire pour lequel cette estimation est la plus basse. Nos résultats indiquent qu'il n'y a pas de relation monotone entre le degré d'aversion au risque et la performance globale. En effet, une population de clients ayant un degré d'aversion au risque intermédiaire encoure généralement une attente moyenne plus élevée qu'une population d'agents indifférents au risque ou très averses au risque. Ensuite, nous incorporons les décisions des prestataires en leur permettant d'ajuster leur capacité de service sur la base de leur perception de la fréquence moyenne d'arrivées. Les résultats montrent que le comportement des clients et les décisions des prestataires présentent une forte "dépendance au sentier". En outre, nous montrons que les décisions des prestataires font converger l'attente moyenne pondérée vers l'attente de référence du marché. Finalement, une expérience de laboratoire dans laquelle des sujets jouent le rôle de prestataire de service nous a permis de conclure que les délais d'installation et de démantèlement de capacité affectent de manière significative la performance et les décisions des sujets. En particulier, les décisions du prestataire, sont influencées par ses commandes en carnet, sa capacité de service actuellement disponible et les décisions d'ajustement de capacité qu'il a prises, mais pas encore implémentées. - Queuing is a fact of life that we witness daily. We all have had the experience of waiting in line for some reason and we also know that it is an annoying situation. As the adage says "time is money"; this is perhaps the best way of stating what queuing problems mean for customers. Human beings are not very tolerant, but they are even less so when having to wait in line for service. Banks, roads, post offices and restaurants are just some examples where people must wait for service. Studies of queuing phenomena have typically addressed the optimisation of performance measures (e.g. average waiting time, queue length and server utilisation rates) and the analysis of equilibrium solutions. The individual behaviour of the agents involved in queueing systems and their decision making process have received little attention. Although this work has been useful to improve the efficiency of many queueing systems, or to design new processes in social and physical systems, it has only provided us with a limited ability to explain the behaviour observed in many real queues. In this dissertation we differ from this traditional research by analysing how the agents involved in the system make decisions instead of focusing on optimising performance measures or analysing an equilibrium solution. This dissertation builds on and extends the framework proposed by van Ackere and Larsen (2004) and van Ackere et al. (2010). We focus on studying behavioural aspects in queueing systems and incorporate this still underdeveloped framework into the operations management field. In the first chapter of this thesis we provide a general introduction to the area, as well as an overview of the results. In Chapters 2 and 3, we use Cellular Automata (CA) to model service systems where captive interacting customers must decide each period which facility to join for service. They base this decision on their expectations of sojourn times. Each period, customers use new information (their most recent experience and that of their best performing neighbour) to form expectations of sojourn time at the different facilities. Customers update their expectations using an adaptive expectations process to combine their memory and their new information. We label "conservative" those customers who give more weight to their memory than to the xiv Summary new information. In contrast, when they give more weight to new information, we call them "reactive". In Chapter 2, we consider customers with different degree of risk-aversion who take into account uncertainty. They choose which facility to join based on an estimated upper-bound of the sojourn time which they compute using their perceptions of the average sojourn time and the level of uncertainty. We assume the same exogenous service capacity for all facilities, which remains constant throughout. We first analyse the collective behaviour generated by the customers' decisions. We show that the system achieves low weighted average sojourn times when the collective behaviour results in neighbourhoods of customers loyal to a facility and the customers are approximately equally split among all facilities. The lowest weighted average sojourn time is achieved when exactly the same number of customers patronises each facility, implying that they do not wish to switch facility. In this case, the system has achieved the Nash equilibrium. We show that there is a non-monotonic relationship between the degree of risk-aversion and system performance. Customers with an intermediate degree of riskaversion typically achieve higher sojourn times; in particular they rarely achieve the Nash equilibrium. Risk-neutral customers have the highest probability of achieving the Nash Equilibrium. Chapter 3 considers a service system similar to the previous one but with risk-neutral customers, and relaxes the assumption of exogenous service rates. In this sense, we model a queueing system with endogenous service rates by enabling managers to adjust the service capacity of the facilities. We assume that managers do so based on their perceptions of the arrival rates and use the same principle of adaptive expectations to model these perceptions. We consider service systems in which the managers' decisions take time to be implemented. Managers are characterised by a profile which is determined by the speed at which they update their perceptions, the speed at which they take decisions, and how coherent they are when accounting for their previous decisions still to be implemented when taking their next decision. We find that the managers' decisions exhibit a strong path-dependence: owing to the initial conditions of the model, the facilities of managers with identical profiles can evolve completely differently. In some cases the system becomes "locked-in" into a monopoly or duopoly situation. The competition between managers causes the weighted average sojourn time of the system to converge to the exogenous benchmark value which they use to estimate their desired capacity. Concerning the managers' profile, we found that the more conservative Summary xv a manager is regarding new information, the larger the market share his facility achieves. Additionally, the faster he takes decisions, the higher the probability that he achieves a monopoly position. In Chapter 4 we consider a one-server queueing system with non-captive customers. We carry out an experiment aimed at analysing the way human subjects, taking on the role of the manager, take decisions in a laboratory regarding the capacity of a service facility. We adapt the model proposed by van Ackere et al (2010). This model relaxes the assumption of a captive market and allows current customers to decide whether or not to use the facility. Additionally the facility also has potential customers who currently do not patronise it, but might consider doing so in the future. We identify three groups of subjects whose decisions cause similar behavioural patterns. These groups are labelled: gradual investors, lumpy investors, and random investor. Using an autocorrelation analysis of the subjects' decisions, we illustrate that these decisions are positively correlated to the decisions taken one period early. Subsequently we formulate a heuristic to model the decision rule considered by subjects in the laboratory. We found that this decision rule fits very well for those subjects who gradually adjust capacity, but it does not capture the behaviour of the subjects of the other two groups. In Chapter 5 we summarise the results and provide suggestions for further work. Our main contribution is the use of simulation and experimental methodologies to explain the collective behaviour generated by customers' and managers' decisions in queueing systems as well as the analysis of the individual behaviour of these agents. In this way, we differ from the typical literature related to queueing systems which focuses on optimising performance measures and the analysis of equilibrium solutions. Our work can be seen as a first step towards understanding the interaction between customer behaviour and the capacity adjustment process in queueing systems. This framework is still in its early stages and accordingly there is a large potential for further work that spans several research topics. Interesting extensions to this work include incorporating other characteristics of queueing systems which affect the customers' experience (e.g. balking, reneging and jockeying); providing customers and managers with additional information to take their decisions (e.g. service price, quality, customers' profile); analysing different decision rules and studying other characteristics which determine the profile of customers and managers.
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This book comprises two volumes and builds on the findings of the DISMEVAL project (Developing and validating DISease Management EVALuation methods for European health care systems), funded under the European Union's (EU) Seventh Framework Programme (FP7) (Agreement no. 223277). DISMEVAL was a three-year European collaborative project conducted between 2009 and 2011. It contributed to developing new research methods and generating the evidence base to inform decision-making in the field of chronic disease management evaluation (www.dismeval.eu). In this book, we report on the findings of the project's first phase, capturing the diverse range of contexts in which new approaches to chronic care are being implemented and evaluating the outcomes of these initiatives using an explicit comparative approach and a unified assessment framework. In this first volume, we describe the range of approaches to chronic care adopted in 12 European countries. By reflecting on the facilitators and barriers to implementation, we aim to provide policy-makers and practitioners with a portfolio of options to advance chronic care approaches in a given policy context.
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OBJECTIVES: Immunohistochemistry (IHC) has become a promising method for pre-screening ALK-rearrangements in non-small cell lung carcinomas (NSCLC). Various ALK antibodies, detection systems and automated immunostainers are available. We therefore aimed to compare the performance of the monoclonal 5A4 (Novocastra, Leica) and D5F3 (Cell Signaling, Ventana) antibodies using two different immunostainers. Additionally we analyzed the accuracy of prospective ALK IHC-testing in routine diagnostics. MATERIALS AND METHODS: Seventy-two NSCLC with available ALK FISH results and enriched for FISH-positive carcinomas were retrospectively analyzed. IHC was performed on BenchMarkXT (Ventana) using 5A4 and D5F3, respectively, and additionally with 5A4 on Bond-MAX (Leica). Data from our routine diagnostics on prospective ALK-testing with parallel IHC, using 5A4, and FISH were available from 303 NSCLC. RESULTS: All three IHC protocols showed congruent results. Only 1/25 FISH-positive NSCLC (4%) was false negative by IHC. For all three IHC protocols the sensitivity, specificity, positive (PPV) and negative predictive values (NPV) compared to FISH were 96%, 100%, 100% and 97.8%, respectively. In the prospective cohort 3/32 FISH-positive (9.4%) and 2/271 FISH-negative (0.7%) NSCLC were false negative and false positive by IHC, respectively. In routine diagnostics the sensitivity, specificity, PPV and NPV of IHC compared to FISH were 90.6%, 99.3%, 93.5% and 98.9%, respectively. CONCLUSIONS: 5A4 and D5F3 are equally well suited for detecting ALK-rearranged NSCLC. BenchMark and BOND-MAX immunostainers can be used for IHC with 5A4. True discrepancies between IHC and FISH results do exist and need to be addressed when implementing IHC in an ALK-testing algorithm.
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Bloodstream infections and sepsis are a major cause of morbidity and mortality. The successful outcome of patients suffering from bacteremia depends on a rapid identification of the infectious agent to guide optimal antibiotic treatment. The analysis of Gram stains from positive blood culture can be rapidly conducted and already significantly impact the antibiotic regimen. However, the accurate identification of the infectious agent is still required to establish the optimal targeted treatment. We present here a simple and fast bacterial pellet preparation from a positive blood culture that can be used as a sample for several essential downstream applications such as identification by MALDI-TOF MS, antibiotic susceptibility testing (AST) by disc diffusion assay or automated AST systems and by automated PCR-based diagnostic testing. The performance of these different identification and AST systems applied directly on the blood culture bacterial pellets is very similar to the performance normally obtained from isolated colonies grown on agar plates. Compared to conventional approaches, the rapid acquisition of a bacterial pellet significantly reduces the time to report both identification and AST. Thus, following blood culture positivity, identification by MALDI-TOF can be reported within less than 1 hr whereas results of AST by automated AST systems or disc diffusion assays within 8 to 18 hr, respectively. Similarly, the results of a rapid PCR-based assay can be communicated to the clinicians less than 2 hr following the report of a bacteremia. Together, these results demonstrate that the rapid preparation of a blood culture bacterial pellet has a significant impact on the identification and AST turnaround time and thus on the successful outcome of patients suffering from bloodstream infections.