986 resultados para Indicate


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Should new ventures stick to their knitting once they start commercialising or should they engage in frequent changes of their business idea? In this paper we argue that new ventures still need to learn their way in the early phases of commercialisation and that changes are good, but subject to two important contingencies. First is that changes should be aimed at enhancing uniqueness, which in turn enhances new venture performance. Second is that our results show that changes have limited affect on uniqueness and performance for entrepreneurs aiming at maximising opportunities, but that changing the business idea has a significant positive impact for entrepreneurs focusing on minimising losses. Our findings indicate that entrepreneurs aiming at minimising losses may offset their initial disadvantages by engaging in a series of adaptations of the business idea to gain higher performance and a more unique product offering.

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Recent research has begun to address and even compare nascent entrepreneurship and nascent corporate entrepreneurship. An opportunity based view holds great potential to integrate both streams of research, but also presents challenges in how we define corporate entrepreneurship. We extend (corporate) entrepreneurship literature to the opportunity identification phase by providing a framework to classify different types of corporate entrepreneurship. Through analysis of a large dataset on nascent (corporate) entrepreneurship (PSEDII) we show that these corporate entrepreneurs differ largely from each other in terms of human capital. Prior studies have indicated that independent and corporate entrepreneurs pursue different types of opportunities and utilize different strategies. Our findings from the opportunity identification phase challenge those differences and seem to indicate a difference between the opportunities corporate entrepreneurs identify versus the opportunities they exploit.

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Increasing awareness of the benefits of stimulating entrepreneurial behaviour in small and medium enterprises has fostered strong interest in innovation programs. Recently many western countries have invested in design innovation for better firm performance. This research presents some early findings from a study of companies which participated in an holistic approach to design innovation, where the outcomes include better business performance and better market positioning in global markets. Preliminary findings from in-depth semi-structured interviews indicate the importance of firm openness to new ways of working and developing new processes of strategic entrepreneurship. Implications for theory and practice are discussed.

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The emerging theory of ‘bricolage’ as a resource behaviour represents an attempt to address the central entrepreneurship research problem of making systematic sense of entrepreneurs that sometimes manage to create significant new economic activity under what appears to be severe resource constraints (Baker & Nelson 2005). However, despite growing interest in bricolage there is little large scale empirical evidence about the effectiveness and outcomes of using bricolage processes while developing innovative outcomes in nascent and young firms. In this research we test bricolage using different forms of innovation using data from the Comprehensive Australian Study of Entrepreneurial Emergence (CAUSEE) project. Our results indicate overall positive results of bricolage with all forms of innovativeness. A discussion of the results and recommended future research is provided.

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This paper presents a material model to simulate load induced cracking in Reinforced Concrete (RC) elements in ABAQUS finite element package. Two numerical material models are used and combined to simulate complete stress-strain behaviour of concrete under compression and tension including damage properties. Both numerical techniques used in the present material model are capable of developing the stress-strain curves including strain softening regimes only using ultimate compressive strength of concrete, which is easily and practically obtainable for many of the existing RC structures or those to be built. Therefore, the method proposed in this paper is valuable in assessing existing RC structures in the absence of more detailed test results. The numerical models are slightly modified from the original versions to be comparable with the damaged plasticity model used in ABAQUS. The model is validated using different experiment results for RC beam elements presented in the literature. The results indicate a good agreement with load vs. displacement curve and observed crack patterns.

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The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation and can also improve productivity and enhance system’s safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. Although a variety of prognostic methodologies have been reported recently, their application in industry is still relatively new and mostly focused on the prediction of specific component degradations. Furthermore, they required significant and sufficient number of fault indicators to accurately prognose the component faults. Hence, sufficient usage of health indicators in prognostics for the effective interpretation of machine degradation process is still required. Major challenges for accurate longterm prediction of remaining useful life (RUL) still remain to be addressed. Therefore, continuous development and improvement of a machine health management system and accurate long-term prediction of machine remnant life is required in real industry application. This thesis presents an integrated diagnostics and prognostics framework based on health state probability estimation for accurate and long-term prediction of machine remnant life. In the proposed model, prior empirical (historical) knowledge is embedded in the integrated diagnostics and prognostics system for classification of impending faults in machine system and accurate probability estimation of discrete degradation stages (health states). The methodology assumes that machine degradation consists of a series of degraded states (health states) which effectively represent the dynamic and stochastic process of machine failure. The estimation of discrete health state probability for the prediction of machine remnant life is performed using the ability of classification algorithms. To employ the appropriate classifier for health state probability estimation in the proposed model, comparative intelligent diagnostic tests were conducted using five different classifiers applied to the progressive fault data of three different faults in a high pressure liquefied natural gas (HP-LNG) pump. As a result of this comparison study, SVMs were employed in heath state probability estimation for the prediction of machine failure in this research. The proposed prognostic methodology has been successfully tested and validated using a number of case studies from simulation tests to real industry applications. The results from two actual failure case studies using simulations and experiments indicate that accurate estimation of health states is achievable and the proposed method provides accurate long-term prediction of machine remnant life. In addition, the results of experimental tests show that the proposed model has the capability of providing early warning of abnormal machine operating conditions by identifying the transitional states of machine fault conditions. Finally, the proposed prognostic model is validated through two industrial case studies. The optimal number of health states which can minimise the model training error without significant decrease of prediction accuracy was also examined through several health states of bearing failure. The results were very encouraging and show that the proposed prognostic model based on health state probability estimation has the potential to be used as a generic and scalable asset health estimation tool in industrial machinery.

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China is one of Asia’s many rapidly-motorising nations and recent increases in private-vehicle ownership have been coupled with an escalation in novice drivers. Several pieces of road safety legislation have been introduced in recent decades in China. While managing the legal aspects of road use is important, social influences on driver behaviour may offer alternative avenues to alter behaviour, particularly in a culture where such factors carry high importance. This paper reports qualitative research with Beijing drivers to investigate social influence factors that have, to date, received little attention in the literature. Findings indicated that family members, friends, and driving instructors appear influential on driver behaviour and that some newly licensed drivers seek additional assistance to facilitate the transition from learning to drive in a controlled environment to driving on the road in complex conditions. Strategies to avoid detection and penalties for inappropriate road use were described, many of which involved the use of a third person. These findings indicate potential barriers to implementing effective traffic enforcement and highlight the importance of understanding culturally-specific social factors relating to driver behaviour.

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Aim To identify relationships between preventive activities, psychosocial factors and leg ulcer recurrence in patients with chronic venous leg ulcers. Background Chronic venous leg ulcers are slow to heal and frequently recur, resulting in years of suffering and intensive use of health care resources. Methods A prospective longitudinal study was undertaken with a sample of 80 patients with a venous leg ulcer recruited when their ulcer healed. Data were collected from 2006–2009 from medical records on demographics, medical history and ulcer history; and from self-report questionnaires on physical activity, nutrition, preventive activities and psychosocial measures. Follow-up data were collected via questionnaires every three months for 12 months after healing. Median time to recurrence was calculated using the Kaplan-Meier method. A Cox proportional-hazards regression model was used to adjust for potential confounders and determine effects of preventive strategies and psychosocial factors on recurrence. Results: There were 35 recurrences in a sample of 80 participants. Median time to recurrence was 27 weeks. After adjustment for potential confounders, a Cox proportional hazards regression model found that at least an hour/day of leg elevation, six or more days/week in Class 2 (20–25mmHg) or 3 (30–40mmHg) compression hosiery, higher social support scale scores and higher General Self-Efficacy scores remained significantly associated (p<0.05) with a lower risk of recurrence, while male gender and a history of DVT remained significant risk factors for recurrence. Conclusion Results indicate that leg elevation, compression hosiery, high levels of self-efficacy and strong social support will help prevent recurrence.

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The current research aimed to profile off-road riders to identify specific sub-groups in relation to their risk-related behaviours and perceptions. A total of 235 adults from the Australian state of Queensland who had ridden a motorcycle or ATV off-road in the last 12 months were recruited. A cluster analysis was applied to the survey data. Two distinct clusters of riders were identified, which corresponded with the self-report of injury from an off-road riding crash in the prior 12 months. The injured cluster had a significantly higher mean risk propensity and use of safety equipment, though did not differ on self-reported risk taking. The injured cluster as a whole included a higher percentage of males, was younger, and rode more often for recreational or competitive purposes than the non-crash involved cluster. The results indicate that the crash cluster may be both more aware of the potential risks of riding and more willing to ride in a riskier manner.

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The economic environment of today can be characterized as highly dynamic and competitive if not being in a constant flux. Globalization and the Information Technology (IT) revolution are perhaps the main contributing factors to this observation. While companies have to some extent adapted to the current business environment, new pressures such as the recent increase in environmental awareness and its likely effects on regulations are underway. Hence, in the light of market and competitive pressures, companies must constantly evaluate and if necessary update their strategies to sustain and increase the value they create for shareholders (Hunt and Morgan, 1995; Christopher and Towill, 2002). One way to create greater value is to become more efficient in producing and delivering goods and services to customers, which can lead to a strategy known as cost leadership (Porter, 1980). Even though Porter (1996) notes that in the long run cost leadership may not be a sufficient strategy for competitive advantage, operational efficiency is certainly necessary and should therefore be on the agenda of every company. ----- ----- ----- Better workflow management, technology, and resource utilization can lead to greater internal operational efficiency, which explains why, for example, many companies have recently adopted Enterprise Resource Planning (ERP) Systems: integrated softwares that streamline business processes. However, as today more and more companies are approaching internal operational excellence, the focus for finding inefficiencies and cost saving opportunities is moving beyond the boundaries of the firm. Today many firms in the supply chain are engaging in collaborative relationships with customers, suppliers, and third parties (services) in an attempt to cut down on costs related to for example, inventory, production, as well as to facilitate synergies. Thus, recent years have witnessed fluidity and blurring regarding organizational boundaries (Coad and Cullen, 2006). ----- ----- ----- The Information Technology (IT) revolution of the late 1990’s has played an important role in bringing organizations closer together. In their efforts to become more efficient, companies first integrated their information systems to speed up transactions such as ordering and billing. Later collaboration on a multidimensional scale including logistics, production, and Research & Development became evident as companies expected substantial benefits from collaboration. However, one could also argue that the recent popularity of the concepts falling under Supply Chain Management (SCM) such as Vendor Managed Inventory, Collaborative Planning, Replenishment, and Forecasting owe to the marketing efforts of software vendors and consultants who provide these solutions. Nevertheless, reports from professional organizations as well as academia indicate that the trend towards interorganizational collaboration is gaining wider ground. For example, the ARC Advisory Group, a research organization on supply chain solutions, estimated that the market for SCM, which includes various kinds of collaboration tools and related services, is going to grow at an annual rate of 7.4% during the years 2004-2008, reaching to $7.4 billion in 2008 (Engineeringtalk 2004).

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It is known that the depth of focus (DOF) of the human eye can be affected by the higher order aberrations. We estimated the optimal combinations of primary and secondary Zernike spherical aberration to expand the DOF and evaluated their efficiency in real eyes using an adaptive optics system. The ratio between increased DOF and loss of visual acuity was used as the performance indicator. The results indicate that primary or secondary spherical aberration alone shows similar effectiveness in extending the DOF. However, combinations of primary and secondary spherical aberration with different signs provide better efficiency for expanding the DOF. This finding suggests that the optimal combinations of primary and secondary spherical aberration may be useful in the design of optical presbyopic corrections. © 2011 Elsevier Ltd. All rights reserved.

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The hydrodynamic behaviour of a novel flat plate photocatalytic reactor for water treatment is investigated using CFD code FLUENT. The reactor consists of a reactive section that features negligible pressure drop and uniform illumination of the photocatalyst to ensure enhanced photocatalytic efficiency. The numerical simulations allowed the identification of several design issues in the original reactor, which include extensive boundary layer separation near the photocatalyst support and regions of flow recirculation that render a significant portion of the reactive area. The simulations reveal that this issue could be addressed by selecting the appropriate inlet positions and configurations. This modification can cause minimal pressure drop across the reactive zone and achieves significant uniformization of the tested pollutant on the photocatalyst surface. The influence of roughness elements type has also been studied with a view to identify their role on the distribution of pollutant concentration on the photocatalyst surface. The results presented here indicate that the flow and pollutant concentration field strongly depend on the geometric parameters and flow conditions.

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A new immobilized flat plate photocatalytic reactor for wastewater treatment has been proposed in this study to avoid subsequent catalyst removal from the treated water. The reactor consists of an inlet, reactive section where catalyst is coated and an outlet parts. In order to optimize the fluid mixing and reactor design, this study aims to investigate the influence of baffles and its arrangement on the flat plate reactor hydrodynamics using computational fluid dynamics (CFD) simulation. For simulation, an array of baffles acting as turbulence promoters is inserted in the reactive zone of the reactor. In this regard, results obtained from the simulation of a baffled- flat plate photoreactor hydrodynamics for different baffle positions, heights and intervals are presented utilizing RNG k-ε turbulence model. Under the conditions simulated, the qualitative flow features, such as the development and separation of boundary layers, vortex formation, the presence of high shear regions and recirculation zones, and the underlying mechanism are examined. The influence of various baffle sizes on the distribution of pollutant concentration is also highlighted. The results presented here indicate that the spanning of recirculation increases the degree of interfacial distortion with a larger interfacial area between fluids which results in substantial enhancement in fluid mixing. The simulation results suggest that the qualitative and quantitative properties of fluid dynamics in a baffled reactor can be obtained which provides valuable insight to fully understand the effect of baffles and its arrangements on the flow pattern, behaviour, and feature.

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Crystal growth of bulk CdTe in short-duration microgravity is performed by the unidirectional cooling method. The largest growth grains in microgravity samples are 4X2mm. The cooling profiles indicate undercooling melts in microgravity. Cooling melt samples in microgravity generate strong gradient of temperature due to stop thermal convections. Temperature distribution in the melt is calculated by the one-dimensional equation of heat conduction, and about 100 K-undercooling is considered to occur at the cooling surface.

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This study uses dosimetry film measurements and Monte Carlo simulations to investigate the accuracy of type-a (pencil-beam) dose calculations for predicting the radiation doses delivered during stereotactic radiotherapy treatments of the brain. It is shown that when evaluating doses in a water phantom, the type-a algorithm provides dose predictions which are accurate to within clinically relevant criteria, gamma(3%,3mm), but these predictions are nonetheless subtly different from the results of evaluating doses from the same fields using radiochromic film and Monte Carlo simulations. An analysis of a clinical meningioma treatment suggests that when predicting stereotactic radiotherapy doses to the brain, the inaccuracies of the type-a algorithm can be exacerbated by inadequate evaluation of the effects of nearby bone or air, resulting in dose differences of up to 10% for individual fields. The results of this study indicate the possible advantage of using Monte Carlo calculations, as well as measurements with high-spatial resolution media, to verify type-a predictions of dose delivered in cranial treatments.