Identification of Noisy Variables for Nonmetric and Symbolic Data in Cluster Analysis

Walesiak, Marek; Dudek, Andrzej

doi:10.1007/978-3-540-78246-9_11

Cited by 4 publications

(1 citation statement)

References 8 publications

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“…As a consequence, companies were grouped using a cluster analysis based on selected variables. Given the ordinal nature of the scale for measuring these traits, the selection of variables for the process of grouping was carried out with the use of the modified HINoV algorithm [ 17 ], where adjusted Rand index was applied. In this algorithm variables showing the highest topri values have the strongest contribution to discovering the cluster structure of enterprises.…”

Section: Methodsmentioning

confidence: 99%

Management practices and their relation to success of Polish SMEs: The empirical verification

Wojciech

2021

PLoS ONE

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Purpose The aim of the paper is to identify management practices that are characteristic for SMEs that achieve market success measured by their business performance in last their years of their operation analyze the relationships between management practices applied in small and medium-sized enterprises and their success measured by their business performance drawing on the data from 2710 SMEs operating on the Polish market. Approach/Methodology/Design A cluster analysis was used to distinguish homogenous SME groups in view of their management practices. We examined differences between groups in terms of their business performance. The HINoV algorithm allowed six variables to be selected out of 32 management practices chosen initially for testing, with these variables providing the basis for grouping. Modal values and medians were calculated for 17 business performance measures in the three clusters produced. The subsequent analysis of those findings was focused on capturing significant differences. Findings In the group of 2710 Polish SMEs, it was possible to verify that there existed an association between management practices in the field of modern HRM, computer systems supporting management and the company’s economic performance, as measured by an increase in net revenue and number of customers over the last three years. In clusters where the above mentioned practices were appreciated, modal and median values of the increase reported in net revenue and number of customers were significantly higher. Practical implications The research has shown that at a time marked by a shortage of highly skilled personnel one should pay particular attention to building an integrated and committed team of workers and to employee empowerment. The research has also shown that SME managers monitor only a fraction of basic business performance measures, which may prove to be a major risk to SMEs. Originality/Value Previous studies have been largely conducted in a fragmentary manner, i.e. they were concerned with the relationships between the application of some practices (strategic management, BPR, entrepreneurial orientation, monitoring, etc.) and selected business effectiveness measures. In this paper, the research covered SME management practices from a variety of areas which were then compared with the entrepreneurs’ assessment as to whether the company’s economic condition changed over the last three years. It is also the first attempt in post-socialist economies to identify those SME management practices that are related to better economic results.

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Section: Methodsmentioning

confidence: 99%

Management practices and their relation to success of Polish SMEs: The empirical verification

Wojciech

2021

PLoS ONE

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Ensemble Clustering of Symbolic Data in Identification of Innovation of European Union Countries

Pełka¹

2017

Ekonometria

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JEL Classification: O39; C38; C87 Streszczenie: Innowacje odgrywają coraz to większą rolę w nowoczesnej gospodarce rynkowej. Pozwalają one odnosić korzyści wszystkim obywatelom (producentom, konsumentom i pracownikom). Innowacje mają także kluczowe znaczenie dla poprawy jakości życia, tworzenia lepszych miejsc pracy, a także szeroko rozumianego rozwoju społeczeństwa ekologicznego. Polityka innowacyjności stanowi istotny element polityki na poziomie zarówno krajów, jak i samej Unii Europejskiej. Celem artykułu jest zaprezentowanie przykładu zastosowania podejścia wielomodelowego danych symbolicznych (z zastosowaniem macierzy współwystąpień i metody k-medoidów) w klasyfikacji krajów Unii Europejskiej pod względem ich innowacyjności. W części empirycznej wykorzystano pakiety clusterSim oraz symbolicDA programu R do wykonania obliczeń. W wyniku zastosowania podejścia wielomodelowego zidentyfikowano strukturę czterech różnych klas.

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A hierarchy of selection pressures determines the organization of the T cell receptor repertoire

et al. 2022

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We systematically examine the receptor repertoire in T cell subsets in young, adult, and LCMV-infected mice. Somatic recombination generates diversity, resulting in the limited overlap between nucleotide sequences of different repertoires even within the same individual. However, statistical features of the repertoire, quantified by the V gene and CDR3 k-mer frequency distributions, are highly conserved. A hierarchy of immunological processes drives the evolution of this structure. Intra-thymic divergence of CD4+ and CD8+ lineages imposes subtle but dominant differences observed across repertoires of all subpopulations in both young and adult mice. Differentiation from naive through memory to effector phenotype imposes an additional gradient of repertoire diversification, which is further influenced by age in a complex and lineage-dependent manner. The distinct repertoire of CD4+ regulatory T cells is more similar to naive cells in young mice and to effectors in adults. Finally, we describe divergent (naive and memory) and convergent (CD8+ effector) evolution of the repertoire following acute infection with LCMV. This study presents a quantitative framework that captures the structure of the repertoire in terms of its fundamental statistical properties and describes how this structure evolves as individual T cells differentiate, migrate and mature in response to antigen exposure.

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Identification of Noisy Variables for Nonmetric and Symbolic Data in Cluster Analysis

Cited by 4 publications

References 8 publications

Management practices and their relation to success of Polish SMEs: The empirical verification

Management practices and their relation to success of Polish SMEs: The empirical verification

Ensemble Clustering of Symbolic Data in Identification of Innovation of European Union Countries

A hierarchy of selection pressures determines the organization of the T cell receptor repertoire

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