Marketing Research

Námskeið
- 134.6.0 MARA Markaðsrannsóknir
-
Neytendahegðun og markaðsrannsóknir / Markaðsrannsóknir
Lýsing:
For undergraduate, postgraduate and MBA students, this highly successful textbook is an essential guide to Marketing Research. Understand theory and application of marketing research in a European context Marketing Research: Applied Insight, 6th Edition, by Nunan, Birks and Malhotra is the leading marketing research text focused on the key challenges facing marketing research in a European context.
This comprehensive text offers a clear explanation and discussion of concepts, and a wealth of European and international case material showing how researchers apply concepts and techniques. It also integrates with online resources for students including key discussion points. This book supports both qualitative and quantitative research methods through: Introducing the transactional stages of marketing research of problem definition, developing approach and design, data collection, analysis and communicating the research findings Using real research case studies of how companies address specific managerial problems and implement research, as well as real-life marketing situations and exercises to tackle in every chapter Applying marketing research to current marketing challenges such as social media, mobile marketing, customer value, experiential marketing, satisfaction, loyalty, customer equity, brand equity and management, relationship marketing, creativity and design, and socially responsible marketing Pearson, the world’s learning company.
Annað
- Höfundar: David F. Birks, Dan Nunan, Naresh K. Malhotra
- Útgáfa:6
- Útgáfudagur: 2020-02-21
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- Format:Page Fidelity
- ISBN 13: 9781292308746
- Print ISBN: 9781292308722
- ISBN 10: 1292308745
Efnisyfirlit
- Half Title Page
- Title Page
- Copyright Page
- Brief contents
- Contents
- Preface
- Publisher's acknowledgements
- About the authors
- 1 Introduction to marketing research and insight
- Objectives
- Overview
- What does 'marketing research' mean?
- Marketing research in context
- Definition of marketing research
- The global marketing research industry
- Justifying the investment in marketing research
- The future - addressing the marketing research skills gap
- Summary
- Questions
- Exercises
- Notes
- 2 Defining the research problem and developing a research approach
- Objectives
- Overview
- Importance of defining the research problem
- The marketing research brief
- Components of the marketing research brief
- The marketing research proposal
- The process of defining the problem and developing a research approach
- Environmental context of the problem
- Discussions with decision makers
- Interviews with industry experts
- Initial secondary data analyses
- Marketing decision problem and marketing research problem
- Defining the marketing research problem
- Components of the research approach
- Objective/theoretical framework
- Research questions
- Hypothesis
- Summary
- Questions
- Exercises
- Notes
- 3 Research design
- Objectives
- Overview
- Research design definition
- Research design from the decision makers' perspective
- Research design from the participants' perspective
- Research design classification
- Descriptive research
- Causal research
- Relationships between exploratory, descriptive and causal research
- Potential sources of error in research designs
- Summary
- Questions
- Exercises
- Notes
- 4 Secondary data collection and analysis
- Objectives
- Overview
- Defining primary data, secondary data and marketing intelligence
- Advantages and uses of secondary data
- Disadvantages of secondary data
- Criteria for evaluating secondary data
- Classification of secondary data
- Published external secondary sources
- Databases
- Classification of online databases
- Syndicated sources of secondary data
- Syndicated data from households
- Syndicated data from institutions
- Summary
- Questions
- Exercises
- Notes
- 5 Internal secondary data and analytics
- Objectives
- Overview
- Internal secondary data
- Geodemographic data analyses
- Customer relationship management
- Big data
- Web analytics
- Linking different types of data
- Summary
- Questions
- Exercises
- Notes
- 6 Qualitative research: its nature and approaches
- Objectives
- Overview
- Primary data: qualitative versus quantitative research
- Rationale for using qualitative research
- Philosophy and qualitative research
- Ethnographic research
- Grounded theory
- Action research
- Summary
- Questions
- Exercises
- Notes
- 7 Qualitative research: focus group discussions
- Objectives
- Overview
- Classifying qualitative research techniques
- Focus group discussion
- Planning and conducting focus groups
- The moderator
- Other variations of focus groups
- Other types of qualitative group discussions
- Misconceptions about focus groups
- Online focus groups
- Advantages of online focus groups
- Disadvantages of online focus groups
- Summary
- Questions
- Exercises
- Notes
- 8 Qualitative research: in-depth interviewing and projective techniques
- Objectives
- Overview
- In-depth interviews
- Projective techniques
- Comparison between qualitative techniques
- Summary
- Questions
- Exercises
- Notes
- 9 Qualitative research: data analysis
- Objectives
- Overview
- The qualitative researcher
- The process of qualitative data analysis
- Grounded theory
- Content analysis
- Semiotics
- Qualitative data analysis software
- Summary
- Questions
- Exercises
- Notes
- 10 Survey and quantitative observation techniques
- Objectives
- Overview
- Survey methods
- Online surveys
- Telephone surveys
- Face-to-face surveys
- A comparative evaluation of survey methods
- Other survey methods
- Mixed-mode surveys
- Observation techniques
- Observation techniques classified by mode of administration
- A comparative evaluation of the observation techniques
- Advantages and disadvantages of observation techniques
- Summary
- Questions
- Exercises
- Notes
- 11 Causal research design: experimentation
- Objectives
- Overview
- Concept of causality
- Conditions for causality
- Definitions and concepts
- Definition of symbols
- Validity in experimentation
- Extraneous variables
- Controlling extraneous variables
- A classification of experimental designs
- Pre-experimental designs
- True experimental designs
- Quasi-experimental designs
- Statistical designs
- Laboratory versus field experiments
- Experimental versus non-experimental designs
- Application: test marketing
- Summary
- Questions
- Exercises
- Notes
- 12 Measurement and scaling: fundamentals, comparative and non-comparative scaling
- Objectives
- Overview
- Measurement and scaling
- Scale characteristics and levels of measurement
- Primary scales of measurement
- A comparison of scaling techniques
- Comparative scaling techniques
- Non-comparative scaling techniques
- Itemised rating scales
- Itemised rating scale decisions
- Multi-item scales
- Scale evaluation
- Choosing a scaling technique
- Mathematically derived scales
- Summary
- Questions
- Exercises
- Notes
- 13 Questionnaire design
- Objectives
- Overview
- Questionnaire definition
- Questionnaire design process
- Specify the information needed
- Specify the type of interviewing method
- Determine the content of individual questions
- Overcoming the participant's inability and unwillingness to answer
- Choose question structure
- Choose question wording
- Arrange the questions in proper order
- Identify the form and layout
- Reproduce the questionnaire
- Eliminate problems by pilot-testing
- Summarising the questionnaire design process
- Designing surveys across cultures and countries
- Summary
- Questions
- Exercises
- Notes
- 14 Sampling: design and procedures
- Objectives
- Overview
- Sample or census
- The sampling design process
- A classification of sampling techniques
- Non-probability sampling techniques
- Probability sampling techniques
- Choosing non-probability versus probability sampling
- Summary of sampling techniques
- Issues in sampling across countries and cultures
- Summary
- Questions
- Exercises
- Notes
- 15 Sampling: determining sample size
- Objectives
- Overview
- Definitions and symbols
- The sampling distribution
- Statistical approaches to determining sample size
- The confidence interval approach
- Multiple characteristics and parameters
- Other probability sampling techniques
- Adjusting the statistically determined sample size
- Calculation of response rates
- Non-response issues in sampling
- Summary
- Questions
- Exercises
- Notes
- 16 Survey fieldwork
- Objectives
- Overview
- The nature of survey fieldwork
- Survey fieldwork and the data-collection process
- Selecting survey fieldworkers
- Training survey fieldworkers
- Recording the answers
- Supervising survey fieldworkers
- Evaluating survey fieldworkers
- Fieldwork and online research
- Fieldwork across countries and cultures
- Summary
- Questions
- Exercises
- Notes
- 17 Social media research
- Objectives
- Overview
- What do we mean by 'social media'?
- The emergence of social media research
- Approaches to social media research
- Accessing social media data
- Social media research methods
- Research with image and video data
- Limitations of social media research
- Summary
- Questions
- Exercises
- Notes
- 18 Mobile research
- Objectives
- Overview
- What is a mobile device?
- Approaches to mobile research
- Guidelines specific to mobile marketing research
- Key challenges in mobile research
- Summary
- Questions
- Exercises
- Notes
- 19 Data integrity
- Objectives
- Overview
- The data integrity process
- Checking the questionnaire
- Editing
- Coding
- Transcribing
- Cleaning the data
- Statistically adjusting the data
- Selecting a data analysis strategy
- Data integrity across countries and cultures
- Practise data analysis with SPSS
- Summary
- Questions
- Exercises
- Notes
- 20 Frequency distribution, cross-tabulation and hypothesis testing
- Objectives
- Overview
- Frequency distribution
- Statistics associated with frequency distribution
- A general procedure for hypothesis testing
- Cross-tabulations
- Statistics associated with cross-tabulation
- Hypothesis testing related to differences
- Parametric tests
- Non-parametric tests
- Practise data analysis with SPSS
- Summary
- Questions
- Exercises
- Notes
- 21 Analysis of variance and covariance
- Objectives
- Overview
- Relationship among techniques
- One-way ANOVA
- Statistics associated with one-way ANOVA
- Conducting one-way ANOVA
- Illustrative applications of one-way ANOVA
- n-way ANOVA
- Analysis of covariance (ANCOVA)
- Issues in interpretation
- Repeated measures ANOVA
- Non-metric ANOVA
- Multivariate ANOVA
- Practise data analysis with SPSS
- Summary
- Questions
- Exercises
- Notes
- 22 Correlation and regression
- Objectives
- Overview
- Product moment correlation
- Partial correlation
- Non-metric correlation
- Regression analysis
- Bivariate regression
- Statistics associated with bivariate regression analysis
- Conducting bivariate regression analysis
- Multiple regression
- Statistics associated with multiple regression
- Conducting multiple regression analysis
- Multicollinearity
- Relative importance of predictors
- Cross-validation
- Regression with dummy variables
- Analysis of variance and covariance with regression
- Practise data analysis with SPSS
- Summary
- Questions
- Exercises
- Notes
- 23 Discriminant and logit analysis
- Objectives
- Overview
- Basic concept of discriminant analysis
- Relationship of discriminant and logit analysis to ANOVA and regression
- Discriminant analysis model
- Statistics associated with discriminant analysis
- Conducting discriminant analysis
- Conducting multiple discriminant analysis
- Stepwise discriminant analysis
- The logit model
- Conducting binary logit analysis
- Practise data analysis with SPSS
- Summary
- Questions
- Exercises
- Notes
- 24 Factor analysis
- Objectives
- Overview
- Basic concept
- Factor analysis model
- Statistics associated with factor analysis
- Conducting factor analysis
- Applications of common factor analysis
- Practise data analysis with SPSS
- Summary
- Questions
- Exercises
- Notes
- 25 Cluster analysis
- Objectives
- Overview
- Basic concept
- Statistics associated with cluster analysis
- Conducting cluster analysis
- Applications of non-hierarchical clustering
- Applications of TwoStep clustering
- Clustering variables
- Practise data analysis with SPSS
- Summary
- Questions
- Exercises
- Notes
- 26 Multidimensional scaling and conjoint analysis
- Objectives
- Overview
- Basic concepts in MDS
- Statistics and terms associated with MDS
- Conducting MDS
- Assumptions and limitations of MDS
- Scaling preference data
- Correspondence analysis
- Relationship among MDS, factor analysis and discriminant analysis
- Basic concepts in conjoint analysis
- Statistics and terms associated with conjoint analysis
- Conducting conjoint analysis
- Assumptions and limitations of conjoint analysis
- Hybrid conjoint analysis
- Practise data analysis with SPSS
- Summary
- Questions
- Exercises
- Notes
- 27 Structural equation modelling and path analysis
- Objectives
- Overview
- Basic concepts in SEM
- Statistics and terms associated with SEM
- Foundations of SEM
- Conducting SEM
- Higher-order CFA
- Relationship of SEM to other multivariate techniques
- Application of SEM: first-order factor model
- Application of SEM: second-order factor model
- Path analysis
- Software to support SEM
- Summary
- Questions
- Exercises
- Notes
- 28 Communicating research findings
- Objectives
- Overview
- Why does communication of research findings matter?
- Importance of the report and presentation
- Preparation and presentation process
- Report preparation
- Guidelines for graphs
- Report distribution
- Digital dashboards
- Infographics
- Oral presentation
- Research follow-up
- Summary
- Questions
- Exercises
- Notes
- 29 Business-to-business (b2b) marketing research
- Objectives
- Overview
- What is b2b marketing and why is it important?
- The distinction between b2b and consumer marketing
- Concepts underlying b2b marketing research
- Implications of the differences between business and consumer purchases for researchers
- The growth of competitive intelligence
- The future of b2b marketing research
- Summary
- Questions
- Exercises
- Notes
- 30 Research ethics, privacy and trust
- Objectives
- Overview
- Ethics in marketing research
- Professional ethics codes
- Ethics in the research process
- Ethics in data collection
- Data analysis
- Ethical communication of research findings
- Key issues in research ethics: informed consent
- Key issues in research ethics: maintaining respondent trust
- Key issues in research ethics: anonymity and privacy
- Key issues in research ethics: sugging and frugging
- Summary
- Questions
- Exercises
- Notes
- Glossary
- Subject Index
- Name Index
- Index of Organisations
- Back Cover
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