225 resultados para LMC CLUSTERS


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Much of the literature on clusters has focused on the economic advantages of clusters and how these can be achieved in terms of competition, regional development and local spillovers. Some studies have focused at the level of the individual firm however human resource management (HRM) in individual clustered firms has received scant attention. This paper innovatively utilises the extended Resource Based View (RBV) of the firm as a framework to conceptualise the human resource processes of individual firms within a cluster. RBV is argued as a useful tool as it explains external rents outside a firm’s boundaries. The paper concludes that HRM can assist in generating rents for firms and clusters more broadly when the function supports valuable interfirm relationships important for realising inter-firm advantages.

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Examined whether discrete working memory deficits underlie positive, negative and disorganised symptoms of schizophrenia. 52 outpatients (mean age 37.5 yrs) with schizophrenia were studied using items drawn from the Positive and Negative Syndrome Scale (PANSS). Linear regression and correlational analyses were conducted to examine whether symptom dimension scores were related to performance on several tests of working memory function. Severity of negative symptoms correlated with reduced production of words during a verbal fluency task, impaired ability to hold letter and number sequences on-line and manipulate them simultaneously, reduced performance during a dual task, and compromised visuospatial working memory under distraction-free conditions. Severity of disorganisation symptoms correlated with impaired visuospatial working memory under conditions of distraction, failure of inhibition during a verbal fluency task, perseverative responding on a test of set-shifting ability, and impaired ability to judge the veracity of simple declarative statements. The present study provides evidence that the positive, negative and disorganised symptom dimensions of the PANSS constitute independent clusters, associated with unique patterns of working memory impairment.

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This paper considers the history of the cluster concept in urban economic geography, and its relationship to recent debates about creative cities. It then looks at the role that universities can play in the development of a creative cluster, as well as some of the potential pitfalls.

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This article investigates underlying constraints within China’s creative economy. Drawing on two studies of creative clusters in Suzhou and Foshan, it identifies the importance of knowledge transfer and internationalization to the generation of higher value-added products and services. Both examples illustrate relationships between resources, activities, routines and entrepreneurship. The article argues that the examples notwithstanding, the vast majority of what is accounted for in data collection as China’s creative industries are more appropriately cultural industries. The focus on cultural industries drives local development and increases land values but the benefits are rarely dispersed internationally or into the broader economy.

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The transformation of China's urban landscape has witnessed a boom in cultural adaptation, namely the adaptation of a Western idea, the creative cluster. This chapter examines the formatting of hundreds of creative clusters-art centres, animation bases, cultural zones, and incubators. The cluster has important implications for how we understand China going forward into the second decade of the 21st century. The cluster phenomenon has resulted in to a substantive remaking of the social contract, between officials, entrepreneurs, local residents, academics-and most significantly cultural producers. However, these processes of adaption are mostly driven by real estate developers working in partnership with local government officials. Cut and paste design is the fast road to completion. In this sense, the description 'creative' may well be redundant.

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The creative industries are important because they are clustered at the point of attraction for a billion or more young people around the world. They're the drivers of demographic, economic and political change. They start from the individual talent of the creative artist and the individual desire and aspiration of the audience. These are the raw materials for innovation, change and emergent culture, scaled up to form new industries and coordinated into global markets based on social networks.

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Multivariate methods are required to assess the interrelationships among multiple, concurrent symptoms. We examined the conceptual and contextual appropriateness of commonly used multivariate methods for cancer symptom cluster identification. From 178 publications identified in an online database search of Medline, CINAHL, and PsycINFO, limited to articles published in English, 10 years prior to March 2007, 13 cross-sectional studies met the inclusion criteria. Conceptually, common factor analysis (FA) and hierarchical cluster analysis (HCA) are appropriate for symptom cluster identification, not principal component analysis. As a basis for new directions in symptom management, FA methods are more appropriate than HCA. Principal axis factoring or maximum likelihood factoring, the scree plot, oblique rotation, and clinical interpretation are recommended approaches to symptom cluster identification.

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The aim of this paper is to advance understandings of the processes of cluster-building and evolution, or transformative and adaptive change, through the conscious design and reflective activities of private and public actors. A model of transformation is developed which illustrates the importance of actors becoming exposed to new ideas and visions for industrial change by political entrepreneurs and external networks. Further, actors must be guided in their decision-making and action by the new vision, and this requires that they are persuaded of its viability through the provision of test cases and supportive resources and institutions. In order for new ideas to become guiding models, actors must be convinced of their desirability through the portrayal of models as a means of confronting competitive challenges and serving the economic interests of the city/region. Subsequent adaptive change is iterative and reflexive, involving a process of strategic learning amongst key industrial and political actors.

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Advances in symptom management strategies through a better understanding of cancer symptom clusters depend on the identification of symptom clusters that are valid and reliable. The purpose of this exploratory research was to investigate alternative analytical approaches to identify symptom clusters for patients with cancer, using readily accessible statistical methods, and to justify which methods of identification may be appropriate for this context. Three studies were undertaken: (1) a systematic review of the literature, to identify analytical methods commonly used for symptom cluster identification for cancer patients; (2) a secondary data analysis to identify symptom clusters and compare alternative methods, as a guide to best practice approaches in cross-sectional studies; and (3) a secondary data analysis to investigate the stability of symptom clusters over time. The systematic literature review identified, in 10 years prior to March 2007, 13 cross-sectional studies implementing multivariate methods to identify cancer related symptom clusters. The methods commonly used to group symptoms were exploratory factor analysis, hierarchical cluster analysis and principal components analysis. Common factor analysis methods were recommended as the best practice cross-sectional methods for cancer symptom cluster identification. A comparison of alternative common factor analysis methods was conducted, in a secondary analysis of a sample of 219 ambulatory cancer patients with mixed diagnoses, assessed within one month of commencing chemotherapy treatment. Principal axis factoring, unweighted least squares and image factor analysis identified five consistent symptom clusters, based on patient self-reported distress ratings of 42 physical symptoms. Extraction of an additional cluster was necessary when using alpha factor analysis to determine clinically relevant symptom clusters. The recommended approaches for symptom cluster identification using nonmultivariate normal data were: principal axis factoring or unweighted least squares for factor extraction, followed by oblique rotation; and use of the scree plot and Minimum Average Partial procedure to determine the number of factors. In contrast to other studies which typically interpret pattern coefficients alone, in these studies symptom clusters were determined on the basis of structure coefficients. This approach was adopted for the stability of the results as structure coefficients are correlations between factors and symptoms unaffected by the correlations between factors. Symptoms could be associated with multiple clusters as a foundation for investigating potential interventions. The stability of these five symptom clusters was investigated in separate common factor analyses, 6 and 12 months after chemotherapy commenced. Five qualitatively consistent symptom clusters were identified over time (Musculoskeletal-discomforts/lethargy, Oral-discomforts, Gastrointestinaldiscomforts, Vasomotor-symptoms, Gastrointestinal-toxicities), but at 12 months two additional clusters were determined (Lethargy and Gastrointestinal/digestive symptoms). Future studies should include physical, psychological, and cognitive symptoms. Further investigation of the identified symptom clusters is required for validation, to examine causality, and potentially to suggest interventions for symptom management. Future studies should use longitudinal analyses to investigate change in symptom clusters, the influence of patient related factors, and the impact on outcomes (e.g., daily functioning) over time.

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Goals of work: The aim of this secondary data analysis was to investigate symptom clusters over time for symptom management of a patient group after commencing adjuvant chemotherapy. Materials and methods: A prospective longitudinal study of 219 cancer outpatients conducted within 1 month of commencing chemotherapy (T1), 6 months (T2), and 12 months (T3) later. Patients' distress levels were assessed for 42 physical symptoms on a clinician-modified Rotterdam Symptom Checklist. Symptom clusters were identified in exploratory factor analyses at each time. Symptom inclusion in clusters was determined from structure coefficients. Symptoms could be associated with multiple clusters. Stability over time was determined from symptom cluster composition and the proportion of symptoms in the initial symptom clusters replicated at later times. Main results Fatigue and daytime sleepiness were the most prevalent distressing symptoms over time. The median number of concurrent distressing symptoms approximated 7, over time. Five consistent clusters were identified at T1, 2, and T3. An additional two clusters were identified at 12 months, possibly due to less variation in distress levels. Weakness and fatigue were each associated with two, four, and five symptom clusters at T1, T2, and T3, respectively, potentially suggesting different causal mechanisms. Conclusion: Stability is a necessary attribute of symptom clusters, but definitional clarification is required. We propose that a core set of concurrent symptoms identifies each symptom cluster, signifying a common cause. Additional related symptoms may be included over time. Further longitudinal investigation is required to identify symptom clusters and the underlying causes.

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That the cultural industries are highly networked and operate in clusters is now well established. The notion of cluster is linked to the idea of place-based advantage with cultural industries gaining competitive advantage from mobilising the resources of places to compete in global markets. ‘Place’ in the cultural industries is frequently taken to be the city where city is seen as the key resource for cultural industry clusters and a primary point of intervention for cultural industry policy in creative city policy making. In this article I want to look at some of the implications of these moves for both academic research and policy discussion. The reasons for this emphasis on policy relates to some large questions of urban governance and cultural politics surrounding the proactive government of clusters which are raised by recent work on the cultural industries, notably by Alan Scott.

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In 2005 the Shanghai municipal government adopted the notion of ‘creative industries’ as part of their economic development strategy. At the same time, they officially recognized a number of ‘Creative Industry Clusters’ (CIC) in the city; over the next five years these official clusters grew to over ninety in number. The active promotion of CIC by the local state can thus been seen as central to its adoption of the creative industries agenda, in turn part of its aspiration to become a modern, global metropolis. In the first part of this paper we look at the emergence of the creative industry agenda in China, making some general observations about the need to place such policy transfer in its specific context. We suggest how this agenda might be understood in the national context of china’s economic and cultural policy development. In the second we give a critical account of the development of the creative industries agenda in Shanghai and its relationship to that for CIC. We argue that this agenda had more to do with real estate development than the promotion of a ‘creative milieu’ or ‘ecosystem’, and we also give some reasons as to why this was the case. In the third section we provide some new evidence to suggest the increasing disjunction between CIC and such a wider ‘creative milieu’. In the final section we suggest some new ways in which these CIC might be approached by local government in Shanghai