Marketing Research, Global Edition
Námskeið
- VIÐ511G Markaðsrannsóknir
Ensk lýsing:
For courses in global marketing. Marketing Research: The Fundamentals The Eighth Edition of Marketing Research continues to provide students with a “nuts and bolts” introduction to the field of marketing research. Intended for students with no prior background in marketing research, the book teaches the basic fundamental statistical models needed to analyze market data.
Lýsing:
For courses in global marketing. A conceptual approach and introduction to the field of marketing research Written with an emphasis on the practical application of marketing research methods, Marketing Research teaches the basic fundamental statistical techniques needed to analyse market data. The 9th Edition has been updated to offer the most current insights on forces shaping marketing research, including the widespread adoption of infographics, a pronounced shift toward mobile marketing research, and the impact of big data.
Additionally, an updated and integrated case study throughout the text helps students relate the material to the real world -- and their future careers. The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps.
Annað
- Höfundar: Alvin C. Burns, Ronald F. Bush
- Útgáfa:9
- Útgáfudagur: 2019-08-21
- Hægt að prenta út 2 bls.
- Hægt að afrita 2 bls.
- Format:Page Fidelity
- ISBN 13: 9781292318097
- Print ISBN: 9781292318042
- ISBN 10: 1292318090
Efnisyfirlit
- Title Page
- Copyright Page
- Brief Contents
- Contents
- Preface
- Chapter 1 Introduction to Marketing Research
- 1‐1 Marketing Research Is Part of Marketing
- The Philosophy of the Marketing Concept Guides Managers’ Decisions
- Creating the “Right” Marketing Strategy
- 1‐2 What Is Marketing Research?
- Is it Marketing Research or Market Research?
- The Function of Marketing Research
- 1‐3 What Are the Uses of ‐Marketing Research?
- Identifying Market Opportunities and Problems
- Generating, Refining, and Evaluating Potential Marketing Actions
- Selecting Target Markets
- Product Research
- Pricing Research
- Promotion Research
- Distribution Research
- Monitoring Marketing Performance
- Improving Marketing as a Process
- Marketing Research Is Sometimes Wrong
- 1‐4 The Marketing Information System
- Components of an MIS
- Internal Reports System
- Marketing Intelligence System
- Marketing Decision Support System (DSS)
- Marketing Research System
- Components of an MIS
- 1‐1 Marketing Research Is Part of Marketing
- 1‐5 Job Skills
- Summary
- Key Terms
- Review Questions/Applications
- Case 1.1 Starbucks and Tea Sales
- Case 1.2 Integrated Case: Auto Concepts
- Endnotes
- 2‐1 Evolution of an Industry
- Earliest Known Studies
- Why Did the Industry Grow?
- The 20th Century Led to a “Mature Industry”
- Marketing Research in the 21st Century
- 2‐2 Who Conducts Marketing Research?
- Client‐Side Marketing Research
- Supply‐Side Marketing Research
- 2‐3 The Industry Structure
- Firm Size by Revenue
- Types of Firms and Their Specialties
- Industry Performance
- 2‐4 Challenges to the Marketing Research Industry
- The Need to Incorporate Innovative and Evolving Sources of Data and Methods
- The Need to Effectively Communicate Insights
- The Need to Hire Talented and Skilled Employees
- 2‐5 Industry Initiatives
- Best Practices
- Maintaining Public Credibility of Research
- Monitoring Industry Trends
- Improving Ethical Conduct
- 2‐6 Industry Standards and Ethics
- Certification of Qualified Research Professionals
- Continuing Education
- 2‐7 A Career in Marketing Research
- Where You’ve Been and Where You’re Headed!
- Summary
- Key Terms
- Review Questions/Applications
- Case 2.1 Pinnacle Research
- Endnotes
- 3‐1 The Marketing Research Process
- The 11‐Step Process
- Caveats to a Step‐by‐Step Process
- Why 11 Steps?
- Not All Studies Use All 11 Steps
- Steps Are Not Always Followed in Order
- Introducing “Where We Are”
- Step 1: Establish the Need for Marketing Research
- The Information Is Already Available
- The Timing Is Wrong
- Costs Outweigh the Value
- Step 2: Define the Problem
- Step 3: Establish Research Objectives
- Step 4: Determine Research Design
- Step 5: Identify Information Types and Sources
- Step 6: Determine Methods of Accessing Data
- Step 7: Design Data Collection Forms
- Step 8: Determine the Sample Plan and Size
- Step 9: Collect Data
- Step 10: Analyze Data
- Step 11: Communicate the Insights
- 3‐2 Defining the Problem
- 1. Recognize the Problem
- Failure to Meet an Objective
- Identification of an Opportunity
- 2. Understand the Background of the Problem
- Conduct a Situation Analysis
- Clarify the Symptoms
- Determine the Probable Causes of the Symptom(s)
- 3. Determine the Decision Alternatives
- 4. Formulate the Problem Statement
- 1. Recognize the Problem
- 3‐3 Research Objectives
- Using Hypotheses
- Defining Constructs
- 3‐4 Action Standards
- Impediments to Problem Definition
- 3‐5 The Marketing Research Proposal
- Ethical Issues and the Research Proposal
- Summary
- Key Terms
- Review Questions/Applications
- Case 3.1 Aging Population in Malaysia
- Case 3.2 Integrated Case: Auto Concepts
- Endnotes
- 4‐1 Research Design
- Why Is Knowledge of Research Design Important?
- 4‐2 Three Types of Research Design
- Research Design: A Caution
- 4‐3 Exploratory Research
- Uses of Exploratory Research
- Gain Background Information
- Define Terms
- Clarify Problems and Hypotheses
- Establish Research Priorities
- Methods of Conducting Exploratory Research
- Secondary Data Analysis
- Experience Surveys
- Case Analysis
- Focus Groups
- Uses of Exploratory Research
- Classification of Descriptive Research Studies
- Experiments
- Experimental Design
- Before‐After Testing
- A/B Testing
- How Valid Are Experiments?
- Types of Experiments
- Types of Test Markets
- Standard Test Market
- Controlled Test Markets
- Simulated Test Markets
- Selecting Test‐Market Regions
- Pros and Cons of Test Marketing
- 5‐1 Big Data
- 5‐2 Primary Versus Secondary Data
- Uses of Secondary Data
- 5‐3 Classification of Secondary Data
- Internal Secondary Data
- External Secondary Data
- Published Sources
- Official Statistics
- Data Aggregators
- Advantages of Secondary Data
- Disadvantages of Secondary Data
- Incompatible Reporting Units
- Mismatched Measurement Units
- Unusable Class Definitions
- Outdated Data
- What Was the Purpose of the Study?
- Who Collected the Information?
- What Information Was Collected?
- How Was the Information Obtained?
- How Consistent Is the Information with Other Information?
- Syndicated Data
- Packaged Services
- Syndicated Data
- Packaged Services
- Measuring Consumer Attitudes and Opinions
- Identifying Segments
- Monitoring Media Usage and Promotion Effectiveness
- Tracking Sales
- Types of Social Media Information
- Reviews
- Tips
- New Uses
- Competitor News
- Advantages and Disadvantages of Social Media Data
- Tools to Monitor Social Media
- 6‐1 Quantitative, Qualitative, and Mixed Methods Research
- Types of Mixed Methods
- 6‐2 Observation Techniques
- Types of Observation
- Direct Versus Indirect
- Covert Versus Overt
- Structured Versus Unstructured
- In Situ Versus Invented
- Appropriate Conditions for the Use of Observation
- Advantages of Observational Data
- Limitations of Observational Data
- Types of Observation
- 6‐3 Focus Groups
- How Focus Groups Work
- Online Focus Groups
- Operational Aspects of Traditional Focus Groups
- How Many People Should Be in a Focus Group?
- Who Should Be in the Focus Group?
- How Many Focus Groups Should Be Conducted?
- How Should Focus Group Participants Be Recruited and Selected?
- Where Should a Focus Group Meet?
- When Should the Moderator Become Involved in the Research Project?
- How Are Focus Group Results Used?
- What Other Benefits Do Focus Groups Offer?
- Advantages of Focus Groups
- Disadvantages of Focus Groups
- When Should Focus Groups Be Used?
- When Should Focus Groups Not Be Used?
- Some Objectives of Focus Groups
- 6‐4 Ethnographic Research
- Mobile Ethnography
- Netnography
- 6‐5 Marketing Research Online Communities
- 6‐6 Other Qualitative Research Techniques
- In‐Depth Interviews
- Protocol Analysis
- Projective Techniques
- Word‐Association Test
- Sentence‐Completion Test
- Picture Test
- Cartoon or Balloon Test
- Role‐Playing Activity
- Neuromarketing
- Neuroimaging
- Eye Tracking
- Facial Coding
- The Controversy
- Still More Qualitative Techniques
- 6‐7 The Analysis of Qualitative Data
- Steps for Analyzing Qualitative Data
- Using Electronic Tools to Analyze Qualitative Data
- Summary
- Key Terms
- Review Questions/Applications
- Case 6.1 Mumuni Advertising Agency
- Case 6.2 Integrated Case: Auto Concepts
- Endnotes
- 7‐1 Advantages of Surveys
- 7‐2 Modes of Data Collection
- Data Collection and Impact of Technology
- Person‐Administered Surveys
- Advantages of Person‐Administered Surveys
- Disadvantages of Person‐Administered Surveys
- Computer‐Assisted, Person‐Administered Surveys
- Advantages of Computer‐Assisted Surveys
- Disadvantages of Computer‐Assisted Surveys
- Self‐Administered Surveys
- Advantages of Self‐Administered Surveys
- Disadvantages of Self‐Administered Surveys
- Computer‐Administered Surveys
- Advantages of Computer‐Administered Surveys
- Disadvantage of Computer‐Administered Surveys
- Mixed‐Mode Surveys
- Advantage of Mixed‐Mode Surveys
- Disadvantages of Mixed‐Mode Surveys
- Person‐Administered/Computer‐Assisted Interviews
- In‐Home Surveys
- Mall‐Intercept Surveys
- In‐Office Surveys
- Telephone Surveys
- Computer‐Administered Interviews
- Fully Automated Survey
- Online Surveys
- Self‐Administered Surveys (Without Computer Presence)
- Group Self‐Administered Survey
- Drop‐Off Survey
- Mail Survey
- Advantages of Using a Panel Company
- Fast Turnaround
- High Quality
- Database Information
- Targeted Respondents
- Integrated Features
- Disadvantages of Using a Panel Company
- Not Random Samples
- Overused Respondents
- Cost
- Top Panel Companies
- How Fast Is the Data Collection?
- How Much Does the Data Collection Cost?
- How Good Is the Data Quality?
- Other Considerations
- 8‐1 Basic Measurement Concepts
- 8‐2 Types of Measures
- Nominal Measures
- Ordinal Measures
- Scale Measures
- 8‐3 Interval Scales Commonly Used in Marketing Research
- The Likert Scale
- The Semantic Differential Scale
- The Stapel Scale
- Slider Scales
- Two Issues with Interval Scales Used in Marketing Research
- The Scale Should Fit the Construct
- 8‐4 Reliability and Validity of Measurements
- 8‐5 Designing a Questionnaire
- The Questionnaire Design Process
- 8‐6 Developing Questions
- Four Do’s of Question Wording
- The Question Should Be Focused on a Single Issue or Topic
- The Question Should Be Brief
- The Question Should Be Grammatically Simple
- The Question Should Be Crystal Clear
- Four Do Not’s of Question Wording
- Do Not “Lead” the Respondent to a Particular Answer
- Do Not Use “Loaded” Wording or Phrasing
- Do Not Use a “Double‐Barreled” Question
- Do Not Use Words That Overstate the Case
- Four Do’s of Question Wording
- The Introduction
- Who Is Doing the Survey?
- What Is the Survey About?
- How Did You Select Me?
- Motivate Me to Participate
- Am I Qualified to Take Part?
- Question Flow
- Question Creation
- Skip and Display Logic
- Data Collection and Creation of Data Files
- Ready‐Made Respondents
- Data Analysis, Graphs, and Downloading Data
- Coding the Questionnaire
- Pretesting the Questionnaire
- 9‐1 Basic Concepts in Samples and Sampling
- Population
- Census
- Sample and Sample Unit
- Sample Frame and Sample Frame Error
- Sampling Error
- 9‐2 Why Take a Sample?
- 9‐3 Probability Versus Nonprobability Sampling Methods
- 9‐4 Probability Sampling Methods
- Simple Random Sampling
- The Random Device Method
- The Random Numbers Method
- Advantages and Disadvantages of Simple Random Sampling
- Simple Random Sampling Used In Practice
- Systematic Sampling
- Why Systematic Sampling Is “Fair”
- Disadvantage of Systematic Sampling
- Cluster Sampling
- Area Sampling as a Form of Cluster Sampling
- Disadvantage of Cluster (Area) Sampling
- Stratified Sampling
- Working with Skewed Populations
- Accuracy of Stratified Sampling
- How to Apply Stratified Sampling
- Simple Random Sampling
- Convenience Samples
- Chain Referral Samples
- Purposive Samples
- Quota Samples
- Online Panel Samples
- River Samples
- Email List Samples
- 10‐1 Sample Size Axioms
- 10‐2 The Confidence Interval Method of Determining Sample Size
- Sample Size and Accuracy
- P and Q: The Concept of Variability
- The Concept of a Confidence Interval
- How Population Size (N) Affects Sample Size
- 10‐3 The Sample Size Formula
- Determining Sample Size via the Confidence Interval Formula
- Variability: p X q
- Acceptable Margin of Sample Error: e
- Level of Confidence: z
- Determining Sample Size via the Confidence Interval Formula
- How to Estimate Variability in the Population
- How to Determine the Amount of Acceptable Sample Error
- How to Decide on the Level of Confidence
- How to Balance Sample Size with the Cost of Data Collection
- Arbitrary “Percent Rule of Thumb” Sample Size
- Conventional Sample Size Specification
- “Credibility Interval” Approach to Sample Size
- Statistical Analysis Requirements in Sample Size Specification
- Cost Basis of Sample Size Specification
- Sampling from Small Populations
- Sample Size Using Nonprobability Sampling
- Sampling from Panels
- 11‐1 Data Collection and Nonsampling Error
- 11‐2 Possible Errors in Field Data Collection
- Intentional Fieldworker Errors
- Unintentional Fieldworker Errors
- Intentional Respondent Errors
- Unintentional Respondent Errors
- 11‐3 Field Data Collection Quality Controls
- Control of Intentional Fieldworker Error
- Control of Unintentional Fieldworker Error
- Control of Intentional Respondent Error
- Control of Unintentional Respondent Error
- Final Comment on the Control of Data Collection Errors
- 11‐4 Nonresponse Error
- Refusals to Participate in the Survey
- Break‐Offs During the Interview
- Refusals to Answer Specific Questions (Item Omission)
- What Is a Completed Interview?
- Measuring Response Rate in Surveys
- 11‐5 Ways Panel Companies Control Error
- 11‐6 Dataset, Coding Data, and the Data Code Book
- 11‐7 Data Quality Issues
- What to Look for in Raw Data Inspection
- Incomplete Response
- Nonresponses to Specific Questions (Item Omissions)
- Yea‐ or Nay‐Saying Patterns
- Middle‐of‐the‐Road Patterns
- Other Data Quality Problems
- How to Handle Data Quality Issues
- What to Look for in Raw Data Inspection
- 12‐1 Types of Statistical Analyses Used in Marketing Research
- Descriptive Analysis
- Inference Analysis
- Difference Analysis
- Association Analysis
- Relationships Analysis
- 12‐2 Understanding Descriptive Analysis
- Measures of Central Tendency: Summarizing the “Typical” Respondent
- Mode
- Median
- Mean
- Measures of Variability: Relating the Diversity of Respondents
- Frequency and Percentage Distribution
- Range
- Standard Deviation
- Measures of Central Tendency: Summarizing the “Typical” Respondent
- Integrated Case The Auto Concepts Survey: Obtaining Descriptive Statistics with SPSS
- Use SPSS to Open Up and Use the Auto Concepts Dataset
- Obtaining a Frequency Distribution and the Mode with SPSS
- Finding the Median with SPSS
- Finding the Mean, Range, and Standard Deviation with SPSS
- Reporting Scale Data (Ratio and Interval Scales)
- Reporting Nominal or Categorical Data
- Sample Statistic
- Standard Error
- Confidence Interval
- How to Interpret an Estimated Population Mean or Percentage Range
- Test of the Hypothesized Population Parameter Value
- Auto Concepts: How to Use SPSS to Test a Hypothesis for a Mean
- 13‐1 Why Differences Are Important
- 13‐2 Small Sample Sizes: The Use of a t Test or z Test and How SPSS Eliminates the Worry
- 13‐3 Testing for Significant Differences Between Two Groups
- Differences Between Percentages with Two Groups (Independent Samples)
- How to Use SPSS for Differences Between Percentages of Two Groups
- Differences Between Means with Two Groups (Independent Samples)
- Integrated Case The Auto Concepts Survey: How to Perform an Independent Sample Significance of Dif
- 13‐4 Testing for Significant Differences in Means Among More Than Two Groups: Analysis of Variance
- Basics of Analysis of Variance
- Post Hoc Tests: Detect Statistically Significant Differences Among Group Means
- Integrated Case Auto Concepts: How to Run Analysis of Variance on SPSS
- Interpreting ANOVA (Analysis of Variance)
- 13‐5 Reporting Group Differences Tests to Clients
- 13‐6 Differences Between Two Means Within the Same Sample (Paired Sample)
- Integrated Case The Auto Concepts Survey: How to Perform a Paired Samples t Test Significance of D
- 13‐7 Null Hypotheses for Differences Tests Summary
- Summary
- Key Terms
- Review Questions/Applications
- Case 13.1 L’Experience Restaurant Survey Differences Analysis
- Case 13.2 Integrated Case: The Auto Concepts Survey ‐Differences Analysis
- Endnotes
- 14‐1 Types of Relationships (Associations) Between Two Variables
- Linear and Curvilinear Relationships
- Monotonic Relationships
- Nonmonotonic Relationships
- 14‐2 Characterizing Relationships Between Variables
- Presence
- Pattern
- Strength of Association
- 14‐3 Correlation Coefficients and Covariation
- Rules of Thumb for Correlation Strength
- The Correlation Sign: The Direction of the Relationship
- Visualizing Covariation using Scatter Diagrams
- 14‐4 The Pearson Product Moment Correlation Coefficient
- Integrated Case Auto Concepts: How to Obtain Pearson Product Moment Correlation(s) with SPSS
- 14‐5 Reporting Correlation Findings to Clients
- 14‐6 Cross‐Tabulations
- Cross‐Tabulation Analysis
- Types of Frequencies and Percentages in a Cross‐Tabulation Table
- 14‐7 Chi‐Square Analysis
- Observed and Expected Frequencies
- The Computed x2 Value
- The Chi‐Square Distribution
- How to Interpret a Chi‐Square Result
- Integrated Case Auto Concepts: Analyzing Cross‐Tabulations for Significant Associations by Perfo
- 14‐8 Chi‐Square Test of Proportions: A Useful Variation of Cross‐Tabulation Analysis
- 14‐9 Communicating Cross‐Tabulation Insights to Clients: Use Data Visualization
- 14‐10 Special Considerations In Association Procedures
- Summary
- Key Terms
- Review Questions/Applications
- Case 14.1 L’Experience Restaurant Survey Associative Analysis
- Case 14.2 Integrated Case: The Auto Concepts Survey Associative Analysis
- Endnotes
- 15‐1 Bivariate Linear Regression Analysis
- Basic Concepts in Regression Analysis
- Independent and Dependent Variables
- Computing the Slope and the Intercept
- How to Improve a Regression Analysis Finding
- Basic Concepts in Regression Analysis
- 15‐2 Multiple Regression Analysis
- An Underlying Conceptual Model
- Multiple Regression Analysis Described
- Basic Assumptions in Multiple Regression
- Integrated Case Auto Concepts: How to Run and Interpret Multiple Regression Analysis on SPSS
- “Trimming” the Regression for Significant Findings
- 15‐3 Special Uses of Multiple Regression Analysis
- Using a “Dummy” Independent Variable
- Using Standardized Betas to Compare the Importance of ‐Independent Variables
- Using Multiple Regression as a Screening Device
- Interpreting the Findings of Multiple Regression Analysis
- 15‐4 Stepwise Multiple Regression
- How to Do Stepwise Multiple Regression with SPSS
- Step‐by‐Step Summary of How to Perform Multiple Regression Analysis
- 15‐5 Warnings Regarding Multiple Regression Analysis
- 15‐6 Communicating Regression Analysis Insights to Clients
- Summary
- Key Terms
- Review Questions/Applications
- Case 15.1 L’Experience Restaurant Survey Regression Analysis
- Case 15.2 Integrated Case: Auto Concepts Segmentation Analysis
- Endnotes
- Use Effective Communication Methods
- Communicate Actionable, Data‐Supported Strategies
- Disseminate Insights Throughout the Organization
- 16‐1 Characteristics of Effective Communication
- Accuracy
- Clarity
- Memorability
- Actionability
- Style
- 16‐2 Avoid Plagiarism!
- 16‐3 Videos, Infographics, and Immersion Techniques
- Videos
- Infographics
- Immersion Techniques
- 16‐4 The Traditional Marketing Research Report
- 16‐5 Know Your Audience
- 16‐6 Elements of the Marketing Research Report
- Front Matter
- Title Page
- Letter of Authorization
- Letter/Memo of Transmittal
- Table of Contents
- List of Illustrations
- Abstract/Executive Summary
- Body
- Introduction
- Research Objectives
- Method
- Method or Methodology?
- Results
- Limitations
- Conclusions and Recommendations
- End Matter
- Front Matter
- 16‐7 Guidelines and Principles for the Written Report
- Headings and Subheadings
- Visuals
- Style
- 16‐8 Using Visuals: Tables and Figures
- Tables
- Pie Charts
- Bar Charts
- Line Graphs
- Flow Diagrams
- Producing an Appropriate Visual
- 16‐9 Presenting Your Research Orally
- 16‐10 Data Visualization Tools and Dashboards
- 16‐11 Disseminating Insights Throughout an Organization
- Summary
- Key Terms
- Review Questions/Applications
- Case 16.1 Integrated Case: Auto Concepts: Report Writing
- Case 16.2 Integrated Case: Auto Concepts: Making a PowerPoint Presentation
- Case 16.3 How Marketing Research Data Can Begin with a Sketch
- Endnotes
- A
- B
- C
- D
- E
- F
- G
- H
- I
- J
- K
- L
- M
- N
- O
- P
- Q
- R
- S
- T
- V
- W
- X
- Y
- Z
- A
- B
- C
- D
- E
- F
- G
- H
- I
- J
- K
- L
- M
- N
- O
- P
- Q
- R
- S
- T
- U
- V
- W
- X
- Y
- Z
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- Gerð : 208
- Höfundur : Ronald F. Bush , Alvin C Burns , Alvin C. Burns
- Útgáfuár : 2019
- Leyfi : 379