Variabilidade da tendência do desempenho das firmas: uma análise mltinível

Compreender a variabilidade do desempenho entre as firmas e compreender o que leva a desempenhos acima da média e vantagem estão entre as principais questões no campo da estratégia empresarial. Vantagem competitiva é um construto de difícil operacionalização, por seu significado complexo, que dá margem a diferentes interpretações. Entretanto ela é apontada com freqüência como causadora de desempenho acima da média. A variabilidade do desempenho das empresas ao longo do tempo também é uma questão tratada com frequência, especialmente no que se trata dos níveis firma e setor. No entanto, a maior parte dos trabalhos empíricos no campo de estratégia dá apenas uma dimensão a essa variabilidade, estudando-a apenas em termos de média. Uma segunda dimensão, a tendência do desempenho, passa a ser considerada neste estudo, utilizado modelos multinível. Como o desempenho de uma firma evolui ao longo do tempo comporta assim, uma diferente análise, em termos de vantagem competitiva, desvantagem competitiva ou paridade. A comparação deste resultado com aqueles de desempenho médio tornou claro a importância de se analisar o desempenho em duas de suas dimensões: a média e sua tendência.

Driving performance impairments due to hypovigilance on monotonous roads

Drivers' ability to react to unpredictable events deteriorates when exposed to highly predictable and uneventful driving tasks. Highway design reduces the driving task mainly to a lane-keeping manoeuvre. Such a task is monotonous, providing little stimulation and this contributes to crashes due to inattention. Research has shown that driver's hypovigilance can be assessed with EEG measurements and that driving performance is impaired during prolonged monotonous driving tasks. This paper aims to show that two dimensions of monotony - namely road design and road side variability - decrease vigilance and impair driving performance. This is the first study correlating hypovigilance and driver performance in varied monotonous conditions, particularly on a short time scale (a few seconds). We induced vigilance decrement as assessed with an EEG during a monotonous driving simulator experiment. Road monotony was varied through both road design and road side variability. The driver's decrease in vigilance occurred due to both road design and road scenery monotony and almost independently of the driver's sensation seeking level. Such impairment was also correlated to observable measurements from the driver, the car and the environment. During periods of hypovigilance, the driving performance impairment affected lane positioning, time to lane crossing, blink frequency, heart rate variability and non-specific electrodermal response rates. This work lays the foundation for the development of an in-vehicle device preventing hypovigilance crashes on monotonous roads.

Pulse-coupled neural network performance for real-time identification of vegetation during forced landing

Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the a mission should be aborted due to mechanical or other failure. On-board cameras provide information that can be used in the determination of potential landing sites, which are continually updated and ranked to prevent injury and minimize damage. Pulse Coupled Neural Networks have been used for the detection of features in images that assist in the classification of vegetation and can be used to minimize damage to the aerial vehicle. However, a significant drawback in the use of PCNNs is that they are computationally expensive and have been more suited to off-line applications on conventional computing architectures. As heterogeneous computing architectures are becoming more common, an OpenCL implementation of a PCNN feature generator is presented and its performance is compared across OpenCL kernels designed for CPU, GPU and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images obtained during unmanned aerial vehicle trials to determine the plausibility for real-time feature detection.

Pulse-coupled neural network performance for real-time identification of vegetation during forced landing

Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the mission should be aborted due to mechanical or other failure. This article presents a pulse-coupled neural network (PCNN) to assist in the vegetation classification in a vision-based landing site detection system for an unmanned aircraft. We propose a heterogeneous computing architecture and an OpenCL implementation of a PCNN feature generator. Its performance is compared across OpenCL kernels designed for CPU, GPU, and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images to determine the plausibility for real-time feature detection.

Destination Brand Performance Measurement Over Time

With increasing investments being made in brand development by destination marketing organisations (DMO) since the 1990s, including rebranding and repositioning, more research is necessary to enhance understanding of how to effectively monitor destination brand performance over time. This chapter summarises key findings from a study of brand performance of a competitive set of destinations, in their most important market, between 2003 and 2012. Brand performance was measured from the perspective of consumer perceptions, based on the concept of consumer-based brand equity (CBBE). The results indicated almost no change in perceptions of the five destinations over the 10-year period. Due to the commonality of challenges faced by DMOs worldwide, it is suggested the CBBE hierarchy provides destination marketers with a practical tool for evaluating brand performance over time; in terms of measures of effectiveness of past marketing communications, as well as indicators of future performance.

PERFORMANCE EVOLUTION OF PEER TO PEER NETWORKS

This thesis work concerns about the Performance evolution of peer to peer networks, where we used different distribution technique’s of peer distribution like Weibull, Lognormal and Pareto distribution process. Then we used a network simulator to evaluate the performance of these three distribution techniques.During the last decade the Internet has expanded into a world-wide network connecting millions of hosts and users and providing services for everyone. Many emerging applications are bandwidth-intensive in their nature; the size of downloaded files including music and videos can be huge, from ten megabits to many gigabits. The efficient use of network resources is thus crucial for the survivability of the Internet. Traffic engineering (TE) covers a range of mechanisms for optimizing operational networks from the traffic perspective. The time scale in traffic engineering varies from the short-term network control to network planning over a longer time period.Here in this thesis work we considered the peer distribution technique in-order to minimise the peer arrival and service process with three different techniques, where we calculated the congestion parameters like blocking time for each peer before entering into the service process, waiting time for a peers while the other peer has been served in the service block and the delay time for each peer. Then calculated the average of each process and graphs have been plotted using Matlab to analyse the results

Performance configurations over time: implications for growth-and profit-oriented strategies

Entrepreneurship research and practice places emphasis on company growth as a measure of entrepreneurial success. In many cases, there has been a tendency to give growth a very central role, with some researchers even seeing growth as the very essence of entrepreneurship (Cole, 1949; Sexton, 1997; Stevenson & Gumpert, 1991). A large number of empirical studies of the performance of young and/or small firms use growth as the dependent variable (see reviews by Ardishvili, Cardozo, Harmon, & Vadakath, 1998; Delmar, 1997; Wiklund, 1998). By contrast, the two most prominent views of strategic management – strategic positioning (Porter, 1980) and the resource-based view (Barney, 1991; Wernerfelt, 1984) – are both concerned with achieving competitive advantage and regard achieving economic rents and profitability relative to other competitors as the central measures of firm performance. Strategic entrepreneurship integrates these two perspectives and is simultaneously concerned with opportunity seeking and advantage seeking (Hitt, Ireland, Camp, & Sexton, 2002; Ireland, Hitt, & Sirmon, 2003). Consequently, both company growth and relative profitability are together relevant measures of firm performance in the domain of strategic entrepreneurship.

Destination brand performance measurement over time: Tracking consumer perceptions of a competitive set of destinations over a 10 year period

There has been a paucity of research published in relation to the temporal aspect of destination image change over time. Given increasing investments in destination branding, research is needed to enhance understanding of how to monitor destination brand performance, of which destination image is the core construct, over time. This article reports the results of four studies tracking brand performance of a competitive set of five destinations, between 2003 and 2012. Results indicate minimal changes in perceptions held of the five destinations of interest over the 10 years, supporting the assertion of Gartner (1986) and Gartner and Hunt (1987) that destination image change will only occur slowly over time. While undertaken in Australia, the research approach provides DMOs in other parts of the world with a practical tool for evaluating brand performance over time; in terms of measures of effectiveness of past marketing communications, and indicators of future performance.

Magnetism and luminescence evolution due to nitrogen doping in manganese-gallium oxide nanowires

We report a new method for large-scale production of GaMnN nanowires, by annealing manganese-gallium oxide nanowires in flowing ammonia at high temperature. Microstructure analysis indicates that the GaMnN nanowires have wurtzite GaN structure without Mn precipitates or Mn-related second phases. Magnetism evolution due to nitrogen doping in manganese-gallium oxide nanowires was evaluated by magnetic measurements. Magnetic measurement reveals that the magnetization increases with the increase of nitrogen concentration. Ferromagnetic ordering exists in the GaMnN nanowires, whose Curie temperature is above room temperature. Luminescence evolution was investigated by the cathodoluminesence measurement for a single nanowire and photoluminescence measurement in a temperature range between 10 and 300 K. Experimental results indicate that optical properties can be modulated by nitrogen doping in manganese-gallium oxide nanowires. (c) 2005 Elsevier B.V. All rights reserved.

Nonlinear Acoustics in Underwater and Biomedical Applications: Array Performance Degradation and Time Reversal Invariance

This dissertation describes a model for acoustic propagation in inhomogeneous flu- ids, and explores the focusing by arrays onto targets under various conditions. The work explores the use of arrays, in particular the time reversal array, for underwater and biomedical applications. Aspects of propagation and phasing which can lead to reduced focusing effectiveness are described. An acoustic wave equation was derived for the propagation of finite-amplitude waves in lossy time-varying inhomogeneous fluid media. The equation was solved numerically in both Cartesian and cylindrical geometries using the finite-difference time-domain (FDTD) method. It was found that time reversal arrays are sensitive to several debilitating factors. Focusing ability was determined to be adequate in the presence of temporal jitter in the time reversed signal only up to about one-sixth of a period. Thermoviscous absorption also had a debilitating effect on focal pressure for both linear and nonlinear propagation. It was also found that nonlinearity leads to degradation of focal pressure through amplification of the received signal at the array, and enhanced absorption in the shocked waveforms. This dissertation also examined the heating effects of focused ultrasound in a tissue-like medium. The application considered is therapeutic heating for hyperther- mia. The acoustic model and a thermal model for tissue were coupled to solve for transient and steady temperature profiles in tissue-like media. The Pennes bioheat equation was solved using the FDTD method to calculate the temperature fields in tissue-like media from focused acoustic sources. It was found that the temperature-dependence of the medium's background prop- erties can play an important role in the temperature predictions. Finite-amplitude effects contributed excess heat when source conditions were provided for nonlinear ef- fects to manifest themselves. The effect of medium heterogeneity was also found to be important in redistributing the acoustic and temperature fields, creating regions with hotter and colder temperatures than the mean by local scattering and lensing action. These temperature excursions from the mean were found to increase monotonically with increasing contrast in the medium's properties.

On the Performance of Polynomial-time CLIQUE Approximation Algorithms on Very Large Graphs

The performance of a randomized version of the subgraph-exclusion algorithm (called Ramsey) for CLIQUE by Boppana and Halldorsson is studied on very large graphs. We compare the performance of this algorithm with the performance of two common heuristic algorithms, the greedy heuristic and a version of simulated annealing. These algorithms are tested on graphs with up to 10,000 vertices on a workstation and graphs as large as 70,000 vertices on a Connection Machine. Our implementations establish the ability to run clique approximation algorithms on very large graphs. We test our implementations on a variety of different graphs. Our conclusions indicate that on randomly generated graphs minor changes to the distribution can cause dramatic changes in the performance of the heuristic algorithms. The Ramsey algorithm, while not as good as the others for the most common distributions, seems more robust and provides a more even overall performance. In general, and especially on deterministically generated graphs, a combination of simulated annealing with either the Ramsey algorithm or the greedy heuristic seems to perform best. This combined algorithm works particularly well on large Keller and Hamming graphs and has a competitive overall performance on the DIMACS benchmark graphs.