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Modern analysis of customer surveys : with applications using R / edited by Ron S. Kenett, Silvia Salini

Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Statistics in Practice Ser ; v.116Publisher: Chichester : John Wiley & Sons, 2011Edition: Online-AusgDescription: Online-Ressource (1 online resource (1 v.))ISBN:
  • 9781283333122
  • 9781119961161
  • 1283333120
  • 9780470971284
Subject(s): Genre/Form: Additional physical formats: 0470971282 | 9780470971284 | 1283332442 | Erscheint auch als: Modern analysis of customer surveys. Druck-Ausgabe. Chichester : Wiley, 2012. XXIV, 500 S.DDC classification:
  • 658.83402855282
  • 658.8/3402855282 23
RVK: RVK: QW 300LOC classification:
  • HF5415.335
  • HF5415.335 .M63 2011
Online resources:
Contents:
Cover; Statistics in Practice; Title Page; Copyright; Dedication; Foreword; Preface; Contributors; Part I: BASIC ASPECTS OF CUSTOMER SATISFACTION SURVEY DATA ANALYSIS; 1: Standards and classical techniques in data analysis of customer satisfaction surveys; 1.1 Literature on customer satisfaction surveys; 1.2 Customer satisfaction surveys and the business cycle; 1.3 Standards used in the analysis of survey data; 1.4 Measures and models of customer satisfaction; 1.5 Organization of the book; 1.6 Summary; 2: The ABC annual customer satisfaction survey; 2.1 The ABC company
2.2 ABC 2010 ACSS: Demographics of respondents2.3 ABC 2010 ACSS: Overall satisfaction; 2.4 ABC 2010 ACSS: Analysis of topics; 2.5 ABC 2010 ACSS: Strengths and weaknesses and decision drivers; 2.6 Summary; Appendix; 3: Census and sample surveys; 3.1 Introduction; 3.2 Types of surveys; 3.3 Non-sampling errors; 3.4 Data collection methods; 3.5 Methods to correct non-sampling errors; 3.6 Summary; 4: Measurement scales; 4.1 Scale construction; 4.2 Scale transformations; Acknowledgements; 5: Integrated analysis; 5.1 Introduction; 5.2 Information sources and related problems; 5.3 Root cause analysis
5.4 SummaryAcknowledgement; 6: Web surveys; 6.1 Introduction; 6.2 Main types of web surveys; 6.3 Economic benefits of web survey research; 6.4 Non-economic benefits of web survey research; 6.5 Main drawbacks of web survey research; 6.6 Web surveys for customer and employee satisfaction projects; 6.7 Summary; 7: The concept and assessment of customer satisfaction; 7.1 Introduction; 7.2 The quality-satisfaction-loyalty chain; 7.3 Customer satisfaction assessment: Some methodological considerations; 7.4 The ABC ACSS questionnaire: An evaluation; 7.5 Summary
Appendix: SERVQUAL dimensions and items8: Missing data and imputation methods; 8.1 Introduction; 8.2 Missing-data patterns and missing-data mechanisms; 8.3 Simple approaches to the missing-data problem; 8.4 Single imputation; 8.5 Multiple imputation; 8.6 Model-based approaches to the analysis of missing data; 8.7 Addressing missing data in the ABC annual customer satisfaction survey: An example; 8.8 Summary; Acknowledgements; 9: Outliers and robustness for ordinal data; 9.1 An overview of outlier detection methods; 9.2 An example of masking; 9.3 Detection of outliers in ordinal variables
9.4 Detection of bivariate ordinal outliers9.5 Detection of multivariate outliers in ordinal regression; 9.6 Summary; Part II: MODERN TECHNIQUES IN CUSTOMER SATISFACTION SURVEY DATA ANALYSIS; 10: Statistical inference for causal effects; 10.1 Introduction to the potential outcome approach to causal inference; 10.2 Assignment mechanisms; 10.3 Inference in classical randomized experiments; 10.4 Inference in observational studies; 11: Bayesian networks applied to customer surveys; 11.1 Introduction to Bayesian networks; 11.2 The Bayesian network model in practice; 11.3 Prediction and explanation
11.4 Summary
Summary: Customer survey studies deals with customers, consumers and user satisfaction from a product or service. In practice, many of the customer surveys conducted by business and industry are analyzed in a very simple way, without using models or statistical methods. Typical reports include descriptive statistics and basic graphical displays. As demonstrated in this book, integrating such basic analysis with more advanced tools, provides insights on non-obvious patterns and important relationships between the survey variables. This knowledge can significantly affect the conclusions derived from a survey. Key features: Provides an integrated, case-studies based approach to analysing customer survey data. Presents a general introduction to customer surveys, within an organization's business cycle. Contains classical techniques with modern and non standard tools. Focuses on probabilistic techniques from the area of statistics/data analysis and covers all major recent developments. Accompanied by a supporting website containing datasets and R scripts. Customer survey specialists, quality managers and market researchers will benefit from this book as well as specialists in marketing, data mining and business intelligence fields.Summary: Intro -- Modern Analysis of Customer Surveys -- Contents -- Foreword -- Preface -- Contributors -- PART I BASIC ASPECTS OF CUSTOMER SATISFACTION SURVEY DATA ANALYSIS -- 1 Standards and classical techniques in data analysis of customer satisfaction surveys -- 1.1 Literature on customer satisfaction surveys -- 1.2 Customer satisfaction surveys and the business cycle -- 1.3 Standards used in the analysis of survey data -- 1.4 Measures and models of customer satisfaction -- 1.4.1 The conceptual construct -- 1.4.2 The measurement process -- 1.5 Organization of the book -- 1.6 Summary -- References -- 2 The ABC annual customer satisfaction survey -- 2.1 The ABC company -- 2.2 ABC 2010 ACSS: Demographics of respondents -- 2.3 ABC 2010 ACSS: Overall satisfaction -- 2.4 ABC 2010 ACSS: Analysis of topics -- 2.5 ABC 2010 ACSS: Strengths and weaknesses and decision drivers -- 2.6 Summary -- References -- Appendix -- 3 Census and sample surveys -- 3.1 Introduction -- 3.2 Types of surveys -- 3.2.1 Census and sample surveys -- 3.2.2 Sampling design -- 3.2.3 Managing a survey -- 3.2.4 Frequency of surveys -- 3.3 Non-sampling errors -- 3.3.1 Measurement error -- 3.3.2 Coverage error -- 3.3.3 Unit non-response and non-self-selection errors -- 3.3.4 Item non-response and non-self-selection error -- 3.4 Data collection methods -- 3.5 Methods to correct non-sampling errors -- 3.5.1 Methods to correct unit non-response errors -- 3.5.2 Methods to correct item non-response -- 3.6 Summary -- References -- 4 Measurement scales -- 4.1 Scale construction -- 4.1.1 Nominal scale -- 4.1.2 Ordinal scale -- 4.1.3 Interval scale -- 4.1.4 Ratio scale -- 4.2 Scale transformations -- 4.2.1 Scale transformations referred to single items -- 4.2.2 Scale transformations to obtain scores on a unique interval scale -- Acknowledgements -- References -- 5 Integrated analysis.PPN: PPN: 809462591Package identifier: Produktsigel: ZDB-26-MYL | ZDB-30-PBE | ZDB-30-PAD | ZDB-30-PQE
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