961 resultados para constructive alignment


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Intellectual assets have attained continuous attention in the academic field, as they are vital sources of competitive advantage and organizational performance in the contemporary knowledge intensive business environment. Intellectual capital measurement is quite thoroughly addressed in the accounting literature. However, the purpose of the measurement is to support the management of intellectual assets, but the reciprocal relationship between measurement and management has not been comprehensively considered in the literature. The theoretical motivation for this study rose from this paradox, as in order to maximise the effectiveness of knowledge management the two initiatives need to be closely integrated. The research approach of this interventionist case study is constructive. The objective is to develop the case organization’s knowledge management and intellectual capital measurement in a way that they would be closely integrated and the measurement would support the management of intellectual assets. The case analysis provides valuable practical considerations about the integration and related issues as the case company is a knowledge intensive organization in which the know-how of the employees is the central competitive asset and therefore, the management and measurement of knowledge are essential for its future success. The results suggest that the case organization is confronting challenges in managing knowledge. In order to appropriately manage knowledge processes and control the related risks, support from intellectual capital measurement is required. However, challenges in measuring intellectual capital, especially knowledge, could be recognized in the organization. By reflecting the knowledge management situation and the constructed strategy map, a new intellectual measurement system was developed for the case organization. The construction of the system as well as its indicators can be perceived to contribute to the literature, emphasizing of the importance of properly considering the organization’s knowledge situation in developing an intellectual capital measurement system.

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The purpose of this study is to identify opportunities to match marketing communication message strategies with the target audience characteristics in the Chinese luxury market entry context. Therefore, consumer behaviour and psychographic marketing segmentation fields are being reviewed in a holistic view in order to identify the similarities and connection points. Through the analysis of the messages in advertisements placed in a certain luxury and fine living magazine, message creation strategies are being anticipated.

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The objective of this study was to increase understanding of the link between the identification of required HR competences and competence management alignment with business strategy in a Finnish, global company employing over 8,000 people and about 100 HR professionals. This aim was approached by analyzing the data collected in focus group interviews using a grounded theory method and in parallel reviewing the literature of strategic human resource management, competence-based strategic management, strategy and foresight. The literature on competence management in different contexts dismisses in-depth discussions on the foresight process and individuals are often forgotten in strategic frameworks. However, corporate foresight helps in the detection of emerging opportunities for innovations and in the implementation of strategy. The empirical findings indicate a lack of strategic leadership and an alignment with HR and business. Accordingly, the most important HR competence areas identified were the need for increasing business understanding and enabling change. As a result, the study provided a holistic model for competence foresight, which introduces HR professionals as strategic change agents in the role of organizational futurists at the heart of the company: facilitating competence foresight and competence development on individual as well as organizational levels, resulting in an agile organization with increased business understanding, sensitive sensors and adaptive actions to enable change.

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The overall purpose of this master's thesis is to investigate the existence of business-IT alignment trap in Finnish IT organizations. The alignment trap refers to the inability of IT investments to deliver the expected business benefits. The basis for this investigation is due to the previous knowledge that high level of IT alignment practice with very low efficacy in an organization can lead to alignment trap. The theory which was established on the dimensions of IT-alignment and efficacy of IT as a whole with considerations for cost reduction and revenue growth benefits. This study explored the same dimensions with the previous study but identified additional benefit (profitability). The study was conducted using the Finnish IT barometer data from different IT organizations. A quantitative research method was used in conducting this study which was built on positivist philosophical stance. The empirical data is based on survey data, an excerpt from the Finnish IT barometer data that captured the annual survey results of IT significance to Finnish organizations as evaluated by business and IT professionals. The survey data comprised of 249 respondents and their responses were categorized into high and low IT intensive which form the basis of the statistical analysis conducted. Overall, five analyses were conducted using the variables of cost reductions, revenue growth and profitability in the 2x2 matrix dimensions of IT alignment and efficacy of IT, grouped into alignment trap, maintenance zone, well-oiled IT and IT-enabled growth. The empirical results, revealed a partial existence of alignment trap in Finnish IT organizations. This is due to a very minute number of organizations that were ensnared in the alignment trap zone on the analyses conducted. Although they recorded considerable high performances in terms of revenue growth rate with IT spending below the average companies, their profitability was considered very low. Generally it was observed that Finnish IT organizations with high efficacy of IT practices had good performances, while those with low efficacy of IT experienced low performances, especially in the aspect of profitability, regardless of the degree of IT alignment. The study proposes that organizations should improve on practices that enhance effectiveness of IT more in order for them to realize the full benefits of IT and to avoid alignment trap.

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Wind power is a rapidly developing, low-emission form of energy production. In Fin-land, the official objective is to increase wind power capacity from the current 1 005 MW up to 3 500–4 000 MW by 2025. By the end of April 2015, the total capacity of all wind power project being planned in Finland had surpassed 11 000 MW. As the amount of projects in Finland is record high, an increasing amount of infrastructure is also being planned and constructed. Traditionally, these planning operations are conducted using manual and labor-intensive work methods that are prone to subjectivity. This study introduces a GIS-based methodology for determining optimal paths to sup-port the planning of onshore wind park infrastructure alignment in Nordanå-Lövböle wind park located on the island of Kemiönsaari in Southwest Finland. The presented methodology utilizes a least-cost path (LCP) algorithm for searching of optimal paths within a high resolution real-world terrain dataset derived from airborne lidar scannings. In addition, planning data is used to provide a realistic planning framework for the anal-ysis. In order to produce realistic results, the physiographic and planning datasets are standardized and weighted according to qualitative suitability assessments by utilizing methods and practices offered by multi-criteria evaluation (MCE). The results are pre-sented as scenarios to correspond various different planning objectives. Finally, the methodology is documented by using tools of Business Process Management (BPM). The results show that the presented methodology can be effectively used to search and identify extensive, 20 to 35 kilometers long networks of paths that correspond to certain optimization objectives in the study area. The utilization of high-resolution terrain data produces a more objective and more detailed path alignment plan. This study demon-strates that the presented methodology can be practically applied to support a wind power infrastructure alignment planning process. The six-phase structure of the method-ology allows straightforward incorporation of different optimization objectives. The methodology responds well to combining quantitative and qualitative data. Additional-ly, the careful documentation presents an example of how the methodology can be eval-uated and developed as a business process. This thesis also shows that more emphasis on the research of algorithm-based, more objective methods for the planning of infrastruc-ture alignment is desirable, as technological development has only recently started to realize the potential of these computational methods.

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One hundred and five primarily Caucasian undergraduate couples were tested to study the phenomenon of attitude alignment, or the way in which individuals change their opinions to achieve greater attitudinal congruence with their romantic partners, and the hypotheses that relationship closeness, affect, attachment, social desirability, and centrality are each related to attitude alignment for individuals in close couples. The couples filled out an attitude questionnaire consisting of 50 issues in which they were asked to give their attitude on a scale from 1 to 9 as well as to rate the centrality, or importance, of that issue on a scale from 1 to 9. Before discussing four of these issues with each other - 2 were more central to the man and less central, or peripheral, to the woman, whereas the other 2 were central to the woman and peripheral to the man - the individuals completed established measures of relationship closeness, affect, attachment, and social desirability. The couples then filled out the identical attitudes questionnaire again, and their answers on the four discussion issues were compared to their prediscussion answers to determine whether attitude alignment had occurred. There were two experimental groups: a social desirability group, where the couples were told it was natural and normal to disagree with their partners, and a control group. Results indicated that attitude alignment did significantly occur across all couples, but most other variables - including centrality, relationship closeness, and affect - did not predict attitude alignment behaviour. As well, the social desirability experimental groups did not significantly differ on attitude alignment behaviours, but higher scores on the social desirability scale, specifically self-deception, significantly predicted higher attitude alignment scores across all couples. Large differences between individuals' frequency.

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Variations in different types of genomes have been found to be responsible for a large degree of physical diversity such as appearance and susceptibility to disease. Identification of genomic variations is difficult and can be facilitated through computational analysis of DNA sequences. Newly available technologies are able to sequence billions of DNA base pairs relatively quickly. These sequences can be used to identify variations within their specific genome but must be mapped to a reference sequence first. In order to align these sequences to a reference sequence, we require mapping algorithms that make use of approximate string matching and string indexing methods. To date, few mapping algorithms have been tailored to handle the massive amounts of output generated by newly available sequencing technologies. In otrder to handle this large amount of data, we modified the popular mapping software BWA to run in parallel using OpenMPI. Parallel BWA matches the efficiency of multithreaded BWA functions while providing efficient parallelism for BWA functions that do not currently support multithreading. Parallel BWA shows significant wall time speedup in comparison to multithreaded BWA on high-performance computing clusters, and will thus facilitate the analysis of genome sequencing data.

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Amartya Sen’s capability approach is, on the one hand, in line with universalism such as exhibited in Martha Nussbaum’s capabilities approach and Len Doyal and Ian Gough’s human need theory. On the other hand, his approach puts priority on people’s “self-evaluation” of capabilities and needs. The latter emphasis makes his approach distinctly sensitive to people’s differences such as gender, ethnicity, disability, sexual orientation, etc.. One could ask, however, how successfully the former commitment to universalism relates to this latter feature that places importance on taking difference seriously. This question is especially relevant with respect to global justice and gender, for example. To offer a potential answers to this question is main goal of this paper.

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This paper investigates certain methods of training adopted in the Statistical Machine Translator (SMT) from English to Malayalam. In English Malayalam SMT, the word to word translation is determined by training the parallel corpus. Our primary goal is to improve the alignment model by reducing the number of possible alignments of all sentence pairs present in the bilingual corpus. Incorporating morphological information into the parallel corpus with the help of the parts of speech tagger has brought around better training results with improved accuracy

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In Statistical Machine Translation from English to Malayalam, an unseen English sentence is translated into its equivalent Malayalam sentence using statistical models. A parallel corpus of English-Malayalam is used in the training phase. Word to word alignments has to be set among the sentence pairs of the source and target language before subjecting them for training. This paper deals with certain techniques which can be adopted for improving the alignment model of SMT. Methods to incorporate the parts of speech information into the bilingual corpus has resulted in eliminating many of the insignificant alignments. Also identifying the name entities and cognates present in the sentence pairs has proved to be advantageous while setting up the alignments. Presence of Malayalam words with predictable translations has also contributed in reducing the insignificant alignments. Moreover, reduction of the unwanted alignments has brought in better training results. Experiments conducted on a sample corpus have generated reasonably good Malayalam translations and the results are verified with F measure, BLEU and WER evaluation metrics.

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A new information-theoretic approach is presented for finding the pose of an object in an image. The technique does not require information about the surface properties of the object, besides its shape, and is robust with respect to variations of illumination. In our derivation, few assumptions are made about the nature of the imaging process. As a result the algorithms are quite general and can foreseeably be used in a wide variety of imaging situations. Experiments are presented that demonstrate the approach registering magnetic resonance (MR) images with computed tomography (CT) images, aligning a complex 3D object model to real scenes including clutter and occlusion, tracking a human head in a video sequence and aligning a view-based 2D object model to real images. The method is based on a formulation of the mutual information between the model and the image called EMMA. As applied here the technique is intensity-based, rather than feature-based. It works well in domains where edge or gradient-magnitude based methods have difficulty, yet it is more robust than traditional correlation. Additionally, it has an efficient implementation that is based on stochastic approximation. Finally, we will describe a number of additional real-world applications that can be solved efficiently and reliably using EMMA. EMMA can be used in machine learning to find maximally informative projections of high-dimensional data. EMMA can also be used to detect and correct corruption in magnetic resonance images (MRI).