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UID:

Umfang: 2 CD , Beih. (15 S.)

Originaltitel: Die Rose vom Liebesgarten

Anmerkung: Text des Beih. in dt. Sprache

Sprache: Deutsch

Schlagwort(e): CD

Mehr zum Autor: Grun, James 1868-1928

Mehr zum Autor: Pfitzner, Hans 1869-1949

UID:

Umfang: 159 S.

Ausgabe: Vollständiger Klavierauszug mit Text

Sprache: Deutsch

Mehr zum Autor: Grun, James 1868-1928

Mehr zum Autor: Pfitzner, Hans 1869-1949

UID:

Umfang: 159 S

Ausgabe: Vollst. Klavierauszug mit Text vom Komp.

Originaltitel: Der arme Heinrich

Anmerkung: Text dt.

Sprache: Deutsch

Mehr zum Autor: Grun, James 1868-1928

Mehr zum Autor: Pfitzner, Hans 1869-1949

UID:

Umfang: 161 S.

ISBN: 9783423251556

Sprache: Deutsch

UID:

Umfang: 255 S.

Ausgabe: Klavier-Auszug mit Text vom Komp. (rev. von Felix Wolfes)

Originaltitel: Die Rose vom Liebesgarten

Anmerkung: Uraufführung: 1901 , Text dt.

Sprache: Deutsch

Schlagwort(e): Musiktheater ; Oper ; Klavierauszug

Mehr zum Autor: Grun, James 1868-1928

Mehr zum Autor: Pfitzner, Hans 1869-1949

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Ausgabe: Für tiefe Stimme (B dur)

Serie: 3 Lieder, op. 5 / Hans Pfitzner No. 1

Sprache: Unbestimmte Sprache

Mehr zum Autor: Grun, James 1868-1928

Mehr zum Autor: Pfitzner, Hans 1869-1949

UID:

Umfang: 5 S

Ausgabe: Klavierpartitur

In: No. 2

Sprache: Unbestimmte Sprache

Mehr zum Autor: Grun, James 1868-1928

Mehr zum Autor: Pfitzner, Hans 1869-1949

UID:

Umfang: 1 electronic resource (xxi, 324 pages) : , illustrations.

ISBN: 9789811088179 , 9811088179 , 9789811342486 , 9811342482 , 9789811088186 , 9811088187

Serie: Management for professionals,

Inhalt: MACHINE-GENERATED SUMMARY NOTE: "This open access book offers something for everyone working with market segmentation: practical guidance for users of market segmentation solutions; organisational guidance on implementation issues; guidance for market researchers in charge of collecting suitable data; and guidance for data analysts with respect to the technical and statistical aspects of market segmentation analysis. Even market segmentation experts will find something new, including an approach to exploring data structure and choosing a suitable number of market segments, and a vast array of useful visualisation techniques that make interpretation of market segments and selection of target segments easier. The book talks the reader through every single step, every single potential pitfall, and every single decision that needs to be made to ensure market segmentation analysis is conducted as well as possible. All calculations are accompanied not only with a detailed explanation, but also with R code that allows readers to replicate any aspect of what is being covered in the book using R, the open-source environment for statistical computing and graphics."

Anmerkung: MACHINE-GENERATED CONTENTS NOTE: Part I. Introduction.- Chapter 1. Market segmentation.- Chapter 2. Market segmentation analysis.- Part II. Ten steps of market segmentation analysis.- Chapter 3. STEP 1: Deciding (not) to segment.- Chapter 4. STEP 2: Specifying the ideal target segment.- Chapter 5. STEP 3: Collecting data.- Chapter 6. STEP 4: Exploring data.- Chapter 7. STEP 5: Extracting segments.- Chapter 8. STEP 6: Profiling segments.- Chapter 9. STEP 7: Describing segments.- Chapter 10. STEP 8: Selecting (the) target segment(s).- Chapter 11. STEP 9: Customising the marketing mix.- Chapter 12. STEP 10: Evaluation and monitoring.

Sprache: Englisch

Schlagwort(e): Handbooks and manuals

URL: FULL

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Umfang: 1 online resource (332 pages)

Ausgabe: 1st ed.

ISBN: 9789811088186

Serie: Management for Professionals Series

Anmerkung: Intro -- Preface -- References -- Contents -- List of Figures -- List of Tables -- Part I Introduction -- 1 Market Segmentation -- 1.1 Strategic and Tactical Marketing -- 1.2 Definitions of Market Segmentation -- 1.3 The Benefits of Market Segmentation -- 1.4 The Costs of Market Segmentation -- References -- 2 Market Segmentation Analysis -- 2.1 The Layers of Market Segmentation Analysis -- 2.2 Approaches to Market Segmentation Analysis -- 2.2.1 Based on Organisational Constraints -- 2.2.2 Based on the Choice of (the) SegmentationVariable(s) -- 2.3 Data Structure and Data-Driven Market Segmentation Approaches -- 2.4 Market Segmentation Analysis Step-by-Step -- References -- Part II Ten Steps of Market Segmentation Analysis -- 3 Step 1: Deciding (not) to Segment -- 3.1 Implications of Committing to Market Segmentation -- 3.2 Implementation Barriers -- 3.3 Step 1 Checklist -- References -- 4 Step 2: Specifying the Ideal Target Segment -- 4.1 Segment Evaluation Criteria -- 4.2 Knock-Out Criteria -- 4.3 Attractiveness Criteria -- 4.4 Implementing a Structured Process -- 4.5 Step 2 Checklist -- References -- 5 Step 3: Collecting Data -- 5.1 Segmentation Variables -- 5.2 Segmentation Criteria -- 5.2.1 Geographic Segmentation -- 5.2.2 Socio-Demographic Segmentation -- 5.2.3 Psychographic Segmentation -- 5.2.4 Behavioural Segmentation -- 5.3 Data from Survey Studies -- 5.3.1 Choice of Variables -- 5.3.2 Response Options -- 5.3.3 Response Styles -- 5.3.4 Sample Size -- 5.4 Data from Internal Sources -- 5.5 Data from Experimental Studies -- 5.6 Step 3 Checklist -- References -- 6 Step 4: Exploring Data -- 6.1 A First Glimpse at the Data -- 6.2 Data Cleaning -- 6.3 Descriptive Analysis -- 6.4 Pre-Processing -- 6.4.1 Categorical Variables -- 6.4.2 Numeric Variables -- 6.5 Principal Components Analysis -- 6.6 Step 4 Checklist -- References , 7 Step 5: Extracting Segments -- 7.1 Grouping Consumers -- 7.2 Distance-Based Methods -- 7.2.1 Distance Measures -- 7.2.2 Hierarchical Methods -- Example: Tourist Risk Taking -- 7.2.3 Partitioning Methods -- 7.2.3.1 k-Means and k-Centroid Clustering -- 7.2.3.2 ``Improved'' k-Means -- 7.2.3.3 Hard Competitive Learning -- 7.2.3.4 Neural Gas and Topology Representing Networks -- 7.2.3.5 Self-Organising Maps -- 7.2.3.6 Neural Networks -- 7.2.4 Hybrid Approaches -- 7.2.4.1 Two-Step Clustering -- 7.2.4.2 Bagged Clustering -- 7.3 Model-Based Methods -- 7.3.1 Finite Mixtures of Distributions -- 7.3.1.1 Normal Distributions -- 7.3.1.2 Binary Distributions -- 7.3.2 Finite Mixtures of Regressions -- Example: Australian Travel Motives -- 7.3.3 Extensions and Variations -- 7.4 Algorithms with Integrated Variable Selection -- 7.4.1 Biclustering Algorithms -- Example: Australian Vacation Activities -- 7.4.2 Variable Selection Procedure for Clustering BinaryData (VSBD) -- Example: Australian Travel Motives -- 7.4.3 Variable Reduction: Factor-Cluster Analysis -- 7.5 Data Structure Analysis -- 7.5.1 Cluster Indices -- 7.5.1.1 Internal Cluster Indices -- 7.5.1.2 External Cluster Indices -- 7.5.2 Gorge Plots -- 7.5.3 Global Stability Analysis -- Example: Tourist Risk Taking -- 7.5.4 Segment Level Stability Analysis -- 7.5.4.1 Segment Level Stability Within Solutions -- 7.5.4.2 Segment Level Stability Across Solutions -- 7.6 Step 5 Checklist -- References -- 8 Step 6: Profiling Segments -- 8.1 Identifying Key Characteristics of Market Segments -- 8.2 Traditional Approaches to Profiling Market Segments -- 8.3 Segment Profiling with Visualisations -- 8.3.1 Identifying Defining Characteristics of MarketSegments -- 8.3.2 Assessing Segment Separation -- 8.4 Step 6 Checklist -- References -- 9 Step 7: Describing Segments -- 9.1 Developing a Complete Picture of Market Segments , 9.2 Using Visualisations to Describe Market Segments -- 9.2.1 Nominal and Ordinal Descriptor Variables -- 9.2.2 Metric Descriptor Variables -- 9.3 Testing for Segment Differences in Descriptor Variables -- 9.4 Predicting Segments from Descriptor Variables -- 9.4.1 Binary Logistic Regression -- 9.4.2 Multinomial Logistic Regression -- 9.4.3 Tree-Based Methods -- 9.5 Step 7 Checklist -- References -- 10 Step 8: Selecting (the) Target Segment(s) -- 10.1 The Targeting Decision -- 10.2 Market Segment Evaluation -- 10.3 Step 8 Checklist -- References -- 11 Step 9: Customising the Marketing Mix -- 11.1 Implications for Marketing Mix Decisions -- 11.2 Product -- 11.3 Price -- 11.4 Place -- 11.5 Promotion -- 11.6 Step 9 Checklist -- References -- 12 Step 10: Evaluation and Monitoring -- 12.1 Ongoing Tasks in Market Segmentation -- 12.2 Evaluating the Success of the Segmentation Strategy -- 12.3 Stability of Segment Membership and Segment Hopping -- 12.4 Segment Evolution -- Example: Winter Vacation Activities -- 12.5 Step 10 Checklist -- References -- A Case Study: Fast Food -- A.1 Step 1: Deciding (not) to Segment -- A.2 Step 2: Specifying the Ideal Target Segment -- A.3 Step 3: Collecting Data -- A.4 Step 4: Exploring Data -- A.5 Step 5: Extracting Segments -- A.5.1 Using k-Means -- A.5.2 Using Mixtures of Distributions -- A.5.3 Using Mixtures of Regression Models -- A.6 Step 6: Profiling Segments -- A.7 Step 7: Describing Segments -- A.8 Step 8: Selecting (the) Target Segment(s) -- A.9 Step 9: Customising the Marketing Mix -- A.10 Step 10: Evaluation and Monitoring -- B R and R Packages -- B.1 What Is R? -- B.1.1 A Short History of R -- B.1.2 R Packages -- B.1.3 Quality Control -- B.1.4 User Interfaces for R -- B.2 R Packages Used in the Book -- B.2.1 MSA -- B.2.2 flexclust -- B.2.3 flexmix -- B.2.4 Other Packages -- C Data Sets Used in the Book , C.1 Tourist Risk Taking -- C.2 Winter Vacation Activities -- C.3 Australian Vacation Activities -- C.4 Australian Travel Motives -- C.5 Fast Food -- Glossary -- References -- Index

Weitere Ausg.: Print version Dolnicar, Sara Market Segmentation Analysis Singapore : Springer Singapore Pte. Limited,c2018 ISBN 9789811088179

Sprache: Englisch

Schlagwort(e): Electronic books

URL: Full-text  ((OIS Credentials Required))

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Umfang: 597 Seiten , Illustrationen

Ausgabe: Lizenzausgabe

Anmerkung: Lizenz des Langen-Müller Verlags, München

Sprache: Deutsch

Schlagwort(e): Operette ; Geschichte

URL: Inhaltsverzeichnis

Mehr zum Autor: Grun, Bernard 1901-1972