scholarly journals Differential Perceptions Of Auditing Terms

2011 ◽  
Vol 5 (3) ◽  
pp. 20 ◽  
Author(s):  
Pearl Tan ◽  
Hian Chye Koh ◽  
Aik Meng Low
Keyword(s):  
Cluster Analysis ◽  
Group Differences ◽  
Audit Report ◽  
Analysis Techniques ◽  
Dimensional Scaling ◽  
Expectation Gap ◽  
And Cluster Analysis ◽  
Multi Dimensional Scaling

This paper investigates the differences in the relative perceptions of auditing terms among groups of accountants, bankers and students. Perceptual models were constructed using multi-dimensional scaling and cluster analysis techniques. The models derived therefrom indicate that there are no major inter-group differences in the relative perceptions of auditing terms. This study does not therefore support the hypothesis that the expectation gap between users and preparers of the audit report are caused by semantical problems.

The Intellectual Structure of Decision Support Systems Research (1969-1989)

2010 ◽  
pp. 284-317
Author(s):  
Sean Eom
Keyword(s):  
Cluster Analysis ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Optimal Number ◽  
Intellectual Structure ◽  
Dimensional Scaling ◽  
And Cluster Analysis ◽  
Author Cocitation ◽  
Multi Dimensional Scaling

This is the capstone chapter that shows how the concepts, tools, and techniques discussed in each of the previous chapters can be applied in conducting author cocitation analysis using a real data in the DSS area. The step-by-step procedures are shown in detail from the preparation of data file in Excel format and importing the file to the SAS system for multivariate statistical analysis. This chapter also guides the readers through the process of analyzing the results of principal components analysis, cluster analysis, and multi-dimensional scaling. The chapter also shows how to apply different criteria to select the optimal number of factor solutions, cluster solutions, and evaluating the acceptability of multi-dimensional scaling outputs. This chapter reports part of the intellectual structure of the DSS field by means of an empirical assessment of the DSS literature over the period 1969 through 1989. Three multivariate data analysis tools (factor analysis, multidimensional scaling, and cluster analysis) are applied to an author cocitation frequency matrix derived from a large database file of comprehensive DSS literature over the same period. Four informal clusters of decision support systems (DSS) research subspecialties and a reference discipline were uncovered. Four of these represent DSS research subspecialties—foundations, model/data management, user-interface/individual differences, and group support systems. One other conceptual grouping defines a reference discipline of DS—organizational science.

scholarly journals A Computerized Text and Cluster Analysis Approach to Psychotherapy Talk

2020 ◽  
Vol 9 (1) ◽  
pp. 4-25
Author(s):  
Dennis Tay
Keyword(s):  
Cluster Analysis ◽  
Agglomerative Hierarchical Clustering ◽  
Analytic Thinking ◽  
Future Directions ◽  
Analysis Techniques ◽  
Entry Points ◽  
And Cluster Analysis ◽  
Language Styles ◽  
Computer Text ◽  
Qualitative Exploration

This paper illustrates an analytical approach combining LIWC, a computer text-analytic application, with cluster analysis techniques to explore ‘language styles’ in psychotherapy across sessions in time. It categorizes session transcripts into distinct clusters or styles based on linguistic (di)similarity and relates them to sessional progression, thus providing entry points for further qualitative exploration. In the first step, transcripts of four illustrative therapist-client dyads were scored under ten LIWC variables including ‘analytic thinking’, ‘clout’, ‘authenticity’, ‘emotional tone’, and pronoun types. In the next step, agglomerative hierarchical clustering uncovered distinct session clusters that are differently distributed in each dyad. The relationships between these clusters and the chronological progression of sessions were then further discussed in context as contrastive exemplars. Applications, limitations and future directions are highlighted.

Weed community structure in spring-seeded crops in Manitoba

1991 ◽  
Vol 71 (4) ◽  
pp. 1069-1080 ◽  
Author(s):  
A. G. Thomas ◽  
M. R. T. Dale
Keyword(s):  
Cluster Analysis ◽  
Community Structure ◽  
Weed Ecology ◽  
Analysis Techniques ◽  
Temperature And Precipitation ◽  
Weed Communities ◽  
Geographic Regions ◽  
Production Practices ◽  
Using Data ◽  
And Cluster Analysis

The phytosociological structure of weed communities in spring wheat, barley, oats, flax, and canola was investigated using data collected during a 3-yr survey of 1384 fields in Manitoba. Fields were surveyed during July and August, after the application of all herbicides. Association and cluster analysis techniques, using the presence or absence of species in a field, were employed to distinguish co-occurring groups of species. Only a small number of significant positive and negative associations were found between species and only minor clusters with a few species were formed at low similarity levels. These results indicated that the weed community was composed of species responding to conditions more or less independently of each other. A comparison of weed associations among the five crops and four geographic regions in the province indicated that the weed community structure was determined largely by climatic variables. The pattern of weed association in the four geographic regions was correlated with differences in temperature and precipitation during the spring and summer. The lack of floristic differentiation was attributed to the fact that production practices were similar for the five spring-seeded crops. Key words: Weed communities, weed ecology, cluster analysis, association analysis

Configurational and conformational classification of pyranose sugars

2008 ◽  
Vol 64 (1) ◽  
pp. 57-65 ◽  
Author(s):  
A. Collins ◽  
A. Parkin ◽  
G. Barr ◽  
W. Dong ◽  
C. J. Gilmore ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Gas Phase ◽  
Clustering Analysis ◽  
Quantum Chemical ◽  
Higher Dimensions ◽  
Crystalline Solid ◽  
Dimensional Scaling ◽  
Multi Dimensional Scaling ◽  
Significant Factors

Automated cluster analysis is used to examine the conformation and configuration of pyranose sugars. Previous findings on this issue are confirmed, importantly from an analysis that requires no prior knowledge of the significant factors determining the conformational classification. The findings on the conformations adopted in the crystalline solid state are found to be different to existing quantum chemical calculations performed for D-glucose in the gas phase, but consistent with empirically determined conformations in the solution state. The use of this clustering analysis in studying chirality in the determined structures is discussed, as is the ability of this type of method to examine higher dimensions within the metric multi-dimensional scaling formalism.

scholarly journals Segmenting the tourism market using perceptual and attitudinal mapping

2012 ◽  
Vol 48 (No. 1) ◽  
pp. 36-48
Author(s):  
Orth UR ◽  
J. Turečková
Keyword(s):  
Market Segmentation ◽  
A Posteriori ◽  
The Czech Republic ◽  
Analysis Techniques ◽  
Strategic Design ◽  
Dimensional Scaling ◽  
Marketing Activities ◽  
Southern Moravia ◽  
Segmentation Task ◽  
Multi Dimensional Scaling

Decreasing numbers of tourists to the Czech Republic point at a weakening competitive position of Czech destinations during the most recent years. For many communities, tourism may be a short-lived economic dream when understanding of tourists´ perceptions and travel motives is lacking. The two objectives pursued in this study are 1) an identification of the positions of competing destinations and 2) an a-posteriori segmentation with psychographic variables. Market segmentation becomes the crucial factor in the strategic design process of target marketing. Like many other markets, tourism markets do not respond homogeneously to marketing activities. Subdividing visitors into useful groups may provide a basis for competitive advantage. Our study establishes taxonomy of visitors to Southern Moravia. The study tries to overcome well-known insufficiencies of single segmentation approaches by exploiting the advantage of the multivariate nature of combined push factors, pull factors, and other factors of more restrictive nature (i.e. time and money). The segmentation task employs multivariate data analysis techniques such as factor analysis, cluster analysis and multi-dimensional scaling. Recent research on the European Vacation Style Typology is incorporated.

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