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Book Details
Abstract
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.
This new edition has been condensed and reorganized for a more streamlined approach. An integrated case study throughout the text helps students relate the material to the real world--and their future careers. All information has been updated to offer the most current insights on forces shaping marketing research, such as the impact of social media and mobile technologies.
Table of Contents
Section Title | Page | Action | Price |
---|---|---|---|
Cover | Cover | ||
Inside Front Cover | IFC | ||
Title Page | 3 | ||
Copyright Page | 4 | ||
Brief Contents | 6 | ||
Contents | 7 | ||
Preface | 21 | ||
About the Authors | 31 | ||
Chapter 1: Introduction to Marketing Research | 32 | ||
1-1. Marketing Research Is Part of Marketing | 34 | ||
The Philosophy of the Marketing Concept Guides Managers’ Decisions | 36 | ||
The “Right” Marketing Strategy | 36 | ||
1-2. What Is Marketing Research? | 37 | ||
Is It Marketing Research or Market Research? | 37 | ||
The Function of Marketing Research | 37 | ||
1-3. What Are the Uses of Marketing Research? | 38 | ||
Identifying Market Opportunities and Problems | 38 | ||
Generating, Refining, and Evaluating Potential Marketing Actions | 38 | ||
Monitoring Marketing Performance | 40 | ||
Improving Marketing as a Process | 40 | ||
Marketing Research Is Sometimes Wrong | 41 | ||
1-4. The Marketing Information System | 41 | ||
Components of an MIS | 42 | ||
Summary | 44 | ||
Key Terms | 45 | ||
Review Questions/Applications | 45 | ||
Case 1.1: Anderson Construction | 46 | ||
Case 1.2: Integrated Case: Auto Concepts | 46 | ||
Chapter 2: The Marketing Research Industry | 48 | ||
2-1. Evolution of an Industry | 50 | ||
Earliest Known Studies | 50 | ||
Why Did the Industry Grow? | 50 | ||
The 20th Century Led to a “Mature Industry” | 51 | ||
2-2. Who Conducts Marketing Research? | 51 | ||
Client-Side Marketing Research | 51 | ||
Supply-Side Marketing Research | 53 | ||
2-3. The Industry Structure | 53 | ||
Firm Size by Revenue | 53 | ||
Types of Firms and Their Specialties | 54 | ||
Industry Performance | 54 | ||
2-4. Challenges to the Marketing Research Industry | 56 | ||
New and Evolving Sources of Data and Methods | 56 | ||
Effective Communication of Results | 58 | ||
Need for Talented and Skilled Employees | 58 | ||
2-5. Industry Initiatives | 58 | ||
Industry Performance Initiatives | 58 | ||
2-6. A Career in Marketing Research | 62 | ||
Where You’ve Been and Where You’re Headed! | 63 | ||
Summary | 63 | ||
Key Terms | 63 | ||
Review Questions/Applications | 64 | ||
Case 2.1: Heritage Research Associates | 64 | ||
Chapter 3: The Marketing Research Process and Defining the Problem and Research Objectives | 66 | ||
3-1. The Marketing Research Process | 67 | ||
The 11-Step Process | 67 | ||
Caveats to a Step-by-Step Process | 68 | ||
Introducing “Where We Are” | 69 | ||
Step 1: Establish the Need for Marketing Research | 69 | ||
Step 2: Define the Problem | 71 | ||
Step 3: Establish Research Objectives | 71 | ||
Step 4: Determine Research Design | 72 | ||
Step 5: Identify Information Types and Sources | 72 | ||
Step 6: Determine Methods of Accessing Data | 72 | ||
Step 7: Design Data Collection Forms | 72 | ||
Step 8: Determine the Sample Plan and Size | 73 | ||
Step 9: Collect Data | 73 | ||
Step 10: Analyze Data | 73 | ||
Step 11: Prepare and Present the Final Research Report | 74 | ||
3-2. Defining the Problem | 74 | ||
1. Recognize the Problem | 75 | ||
2. Understand the Background of the Problem | 76 | ||
3. Determine What Decisions Need to Be Made | 78 | ||
4. Identify What Additional Information Is Needed | 79 | ||
5. Formulate the Problem Statement | 80 | ||
3-3. Research Objectives | 80 | ||
Using Hypotheses | 81 | ||
Defining Constructs | 81 | ||
3-4. Action Standards | 83 | ||
Impediments to Problem Definition | 84 | ||
3-5. The Marketing Research Proposal | 85 | ||
Elements of the Proposal | 85 | ||
Ethical Issues and the Research Proposal | 86 | ||
Summary | 86 | ||
Key Terms | 87 | ||
Review Questions/Applications | 87 | ||
Case 3.1: Golf Technologies, Inc. | 88 | ||
Case 3.2: Integrated Case: Auto Concepts | 89 | ||
Chapter 4: Research Design | 90 | ||
4-1. Research Design | 92 | ||
Why Is Knowledge of Research Design Important? | 92 | ||
4-2. Three Types of Research Designs | 93 | ||
Research Design: A Caution | 94 | ||
4-3. Exploratory Research | 94 | ||
Uses of Exploratory Research | 95 | ||
Methods of Conducting Exploratory Research | 96 | ||
4-4. Descriptive Research | 98 | ||
Classification of Descriptive Research Studies | 99 | ||
4-5. Causal Research | 102 | ||
Experiments | 102 | ||
Experimental Design | 103 | ||
How Valid Are Experiments? | 105 | ||
Types of Experiments | 106 | ||
4-6. Test Marketing | 107 | ||
Types of Test Markets | 107 | ||
Selecting Test-Market Cities | 109 | ||
Pros and Cons of Test Marketing | 109 | ||
Summary | 110 | ||
Key Terms | 111 | ||
Review Questions/Applications | 111 | ||
Case 4.1: Memos from a Researcher | 112 | ||
Chapter 5: Secondary Data and Packaged Information | 114 | ||
5-1. Big Data | 116 | ||
5-2. Primary Versus Secondary Data | 116 | ||
Uses of Secondary Data | 118 | ||
5-3. Classification of Secondary Data | 119 | ||
Internal Secondary Data | 119 | ||
External Secondary Data | 120 | ||
5-4. Advantages and Disadvantages of Secondary Data | 124 | ||
Advantages of Secondary Data | 124 | ||
Disadvantages of Secondary Data | 124 | ||
5-5. Evaluating Secondary Data | 125 | ||
What Was the Purpose of the Study? | 125 | ||
Who Collected the Information? | 126 | ||
What Information Was Collected? | 126 | ||
How Was the Information Obtained? | 126 | ||
How Consistent Is the Information with Other Information? | 128 | ||
5-6. The American Community Survey | 128 | ||
5-7. What Is Packaged Information? | 129 | ||
Syndicated Data | 129 | ||
Packaged Services | 131 | ||
5-8. Advantages and Disadvantages of Packaged Information | 132 | ||
Syndicated Data | 132 | ||
Packaged Services | 132 | ||
5-9. Applications of Packaged Information | 132 | ||
Measuring Consumer Attitudes and Opinions | 133 | ||
Market Segmentation | 133 | ||
Monitoring Media Usage and Promotion Effectiveness | 133 | ||
Market Tracking Studies | 134 | ||
5-10. Social Media Data | 134 | ||
Types of Information | 134 | ||
Advantages and Disadvantages of Social Media Data | 135 | ||
Tools to Monitor Social Media | 136 | ||
5-11. Internet of Things | 136 | ||
Summary | 138 | ||
Key Terms | 139 | ||
Review Questions/Applications | 139 | ||
Case 5.1: The Men’s Market for Athleisure | 140 | ||
Chapter 6: Qualitative Research Techniques | 142 | ||
6-1. Quantitative, Qualitative, and Mixed Methods Research | 143 | ||
6-2. Observation Techniques | 146 | ||
Types of Observation | 146 | ||
Appropriate Conditions for the Use of Observation | 147 | ||
Advantages of Observational Data | 148 | ||
Limitations of Observational Data | 148 | ||
6-3. Focus Groups | 149 | ||
How Focus Groups Work | 150 | ||
Online Focus Groups | 151 | ||
Advantages of Focus Groups | 151 | ||
Disadvantages of Focus Groups | 152 | ||
When Should Focus Groups Be Used? | 152 | ||
When Should Focus Groups Not Be Used? | 152 | ||
Some Objectives of Focus Groups | 152 | ||
Operational Aspects of Traditional Focus Groups | 153 | ||
6-4. Ethnographic Research | 156 | ||
Mobile Ethnography | 156 | ||
Netnography | 157 | ||
6-5. Marketing Research Online Communities | 158 | ||
6-6. Other Qualitative Research Techniques | 159 | ||
In-Depth Interviews | 159 | ||
Protocol Analysis | 160 | ||
Projective Techniques | 161 | ||
Neuromarketing | 163 | ||
Still More Qualitative Techniques | 164 | ||
Summary | 166 | ||
Key Terms | 167 | ||
Review Questions/Applications | 167 | ||
Case 6.1: The College Experience | 168 | ||
Case 6.2: Integrated Case: Auto Concepts | 169 | ||
Chapter 7: Evaluating Survey Data Collection Methods | 170 | ||
7-1. Advantages of Surveys | 172 | ||
7-2. Modes of Data Collection | 174 | ||
Data Collection and Impact of Technology | 174 | ||
Person-Administered Surveys | 175 | ||
Computer-Assisted Surveys | 177 | ||
Self-Administered Surveys | 178 | ||
Computer-Administered Surveys | 179 | ||
Mixed-Mode Surveys | 180 | ||
7-3. Descriptions of Data Collection Methods | 181 | ||
Person-Administered/Computer-Assisted Interviews | 182 | ||
Computer-Administered Interviews | 188 | ||
Self-Administered Surveys | 191 | ||
7-4. Working with a Panel Company | 193 | ||
Advantages of Using a Panel Company | 194 | ||
Disadvantages of Using a Panel Company | 194 | ||
Top Panel Companies | 195 | ||
7-5. Choice of the Survey Method | 196 | ||
How Fast Is the Data Collection? | 197 | ||
How Much Does the Data Collection Cost? | 197 | ||
How Good Is the Data Quality? | 197 | ||
Other Considerations | 198 | ||
Summary | 199 | ||
Key Terms | 200 | ||
Review Questions/Applications | 200 | ||
Case 7.1: Machu Picchu National Park Survey | 201 | ||
Case 7.2: Advantage Research, Inc. | 202 | ||
Chapter 8: Understanding Measurement, Developing Questions, and Designing the Questionnaire | 204 | ||
8-1. Basic Measurement Concepts | 205 | ||
8-2. Types of Measures | 206 | ||
Nominal Measures | 206 | ||
Ordinal Measures | 207 | ||
Scale Measures | 207 | ||
8-3. Interval Scales Commonly Used in Marketing Research | 209 | ||
The Likert Scale | 209 | ||
The Semantic Differential Scale | 210 | ||
The Stapel Scale | 212 | ||
Two Issues with Interval Scales Used in Marketing Research | 213 | ||
The Scale Should Fit the Construct | 214 | ||
8-4. Reliability and Validity of Measurements | 215 | ||
8-5. Designing a Questionnaire | 216 | ||
The Questionnaire Design Process | 216 | ||
8-6. Developing Questions | 217 | ||
Four Dos of Question Wording | 218 | ||
Four Do Not’s of Question Wording | 219 | ||
8-7. Questionnaire Organization | 222 | ||
The Introduction | 223 | ||
Question Flow | 224 | ||
8-8. Computer-Assisted Questionnaire Design | 227 | ||
Question Creation | 227 | ||
Skip and Display Logic | 228 | ||
Data Collection and Creation of Data Files | 228 | ||
Ready-Made Respondents | 228 | ||
Data Analysis, Graphs, and Downloading Data | 228 | ||
8-9. Finalize the Questionnaire | 229 | ||
Coding the Questionnaire | 229 | ||
Pretesting the Questionnaire | 230 | ||
Summary | 232 | ||
Key Terms | 232 | ||
Review Questions/Applications | 233 | ||
Case 8.1: Extreme Exposure Rock Climbing Center Faces The Krag | 234 | ||
Case 8.2: Integrated Case: Auto Concepts | 235 | ||
Chapter 9: Selecting the Sample | 236 | ||
9-1. Basic Concepts in Samples and Sampling | 238 | ||
Population | 238 | ||
Census | 238 | ||
Sample and Sample Unit | 239 | ||
Sample Frame and Sample Frame Error | 239 | ||
Sampling Error | 240 | ||
9-2. Reasons for Taking a Sample | 240 | ||
9-3. Probability Versus Nonprobability Sampling Methods | 241 | ||
9-4. Probability Sampling Methods | 242 | ||
Simple Random Sampling | 242 | ||
Systematic Sampling | 245 | ||
Cluster Sampling | 248 | ||
Stratified Sampling | 250 | ||
9-5. Nonprobability Sampling Methods | 253 | ||
Convenience Samples | 253 | ||
Purposive Samples | 255 | ||
Chain Referral Samples | 256 | ||
Quota Samples | 256 | ||
9-6. Online Sampling Techniques | 256 | ||
Online Panel Samples | 257 | ||
River Samples | 257 | ||
Email List Samples | 257 | ||
9-7. Developing a Sample Plan | 257 | ||
Summary | 258 | ||
Key Terms | 258 | ||
Review Questions/Applications | 259 | ||
Case 9.1: Peaceful Valley Subdivision: Trouble in Suburbia | 260 | ||
Case 9.2: Jet’s Pets | 261 | ||
Chapter 10: Determining the Size of a Sample | 262 | ||
10-1. Sample Size Axioms | 265 | ||
10-2. The Confidence Interval Method of Determining Sample Size | 265 | ||
Sample Size and Accuracy | 266 | ||
p and q: The Concept of Variability | 267 | ||
The Concept of a Confidence Interval | 269 | ||
How Population Size ( N ) Affects Sample Size | 271 | ||
10-3. The Sample Size Formula | 271 | ||
Determining Sample Size via the Confidence Interval Formula | 271 | ||
10-4. Practical Considerations in Sample Size Determination | 274 | ||
How to Estimate Variability in the Population | 275 | ||
How to Determine the Amount of Acceptable Sample Error | 275 | ||
How to Decide on the Level of Confidence | 275 | ||
How to Balance Sample Size with the Cost of Data Collection | 276 | ||
10-5. Other Methods of Sample Size Determination | 276 | ||
Arbitrary “Percent Rule of Thumb” Sample Size | 277 | ||
Conventional Sample Size Specification | 278 | ||
Statistical Analysis Requirements Sample Size Specification | 278 | ||
Cost Basis of Sample Size Specification | 279 | ||
10-6. Three Special Sample Size Determination Situations | 280 | ||
Sampling from Small Populations | 280 | ||
Sample Size Using Nonprobability Sampling | 281 | ||
Sampling from Panels | 283 | ||
Summary | 283 | ||
Key Terms | 284 | ||
Review Questions/Applications | 284 | ||
Case 10.1: Target: Deciding on the Number of Telephone Numbers | 286 | ||
Case 10.2: Scope Mouthwash | 287 | ||
Chapter 11: Dealing with Fieldwork and Data Quality Issues | 288 | ||
11-1. Data Collection and Nonsampling Error | 289 | ||
11-2. Possible Errors in Field Data Collection | 290 | ||
Intentional Fieldworker Errors | 290 | ||
Unintentional Fieldworker Errors | 291 | ||
Intentional Respondent Errors | 293 | ||
Unintentional Respondent Errors | 293 | ||
11-3. Field Data Collection Quality Controls | 296 | ||
Control of Intentional Fieldworker Error | 296 | ||
Control of Unintentional Fieldworker Error | 297 | ||
Control of Intentional Respondent Error | 298 | ||
Control of Unintentional Respondent Error | 299 | ||
Final Comment on the Control of Data Collection Errors | 299 | ||
11-4. Nonresponse Error | 300 | ||
Refusals to Participate in the Survey | 301 | ||
Break-offs During the Interview | 301 | ||
Refusals to Answer Specific Questions (Item Omission) | 301 | ||
What Is a Completed Interview? | 301 | ||
Measuring Response Rate in Surveys | 302 | ||
11-5. How Panel Companies Control Error | 304 | ||
11-6. Dataset, Coding Data, and the Data Code Book | 305 | ||
11-7. Data Quality Issues | 306 | ||
What to Look for in Raw Data Inspection | 307 | ||
Summary | 310 | ||
Key Terms | 310 | ||
Review Questions/Applications | 310 | ||
Case 11.1: Skunk Juice | 311 | ||
Case 11.2: Sony Televisions Ultra HD TV Survey | 312 | ||
Chapter 12: Using Descriptive Analysis, Performing Population Estimates, and Testing Hypotheses | 314 | ||
12-1. Types of Statistical Analyses Used in Marketing Research | 317 | ||
Descriptive Analysis | 317 | ||
Inference Analysis | 318 | ||
Difference Analysis | 318 | ||
Association Analysis | 318 | ||
Relationships Analysis | 318 | ||
12-2. Understanding Descriptive Analysis | 319 | ||
Measures of Central Tendency: Summarizing the “Typical” Respondent | 319 | ||
Measures of Variability: Relating the Diversity of Respondents | 320 | ||
12-3. When to Use a Particular Descriptive Measure | 322 | ||
12-4. The Auto Concepts Survey: Obtaining Descriptive Statistics with SPSS | 323 | ||
Integrated Case | 323 | ||
12-5. Reporting Descriptive Statistics to Clients | 329 | ||
Reporting Scale Data (Ratio and Interval Scales) | 329 | ||
Reporting Nominal or Categorical Data | 330 | ||
12-6. Statistical Inference: Sample Statistics and Population Parameters | 331 | ||
12-7. Parameter Estimation: Estimating the Population Percent or Mean | 332 | ||
Sample Statistic | 333 | ||
Standard Error | 333 | ||
Confidence Intervals | 335 | ||
How to Interpret an Estimated Population Mean or Percentage Range | 336 | ||
12-8. The Auto Concepts Survey: How to Obtain and Use a Confidence Interval for a Mean with SPSS | 337 | ||
12-9. Reporting Confidence Intervals to Clients | 338 | ||
12-10. Hypothesis Tests | 340 | ||
Test of the Hypothesized Population Parameter Value | 340 | ||
Auto Concepts: How to Use SPSS to Test a Hypothesis for a Mean | 342 | ||
12-11. Reporting Hypothesis Tests to Clients | 344 | ||
Summary | 345 | ||
Key Terms | 345 | ||
Review Questions/Applications | 345 | ||
Case 12.1: L’Experience Félicité Restaurant Survey Descriptive and Inference Analysis | 346 | ||
Case 12.2: Integrated Case: Auto Concepts Descriptive and Inference Analysis | 348 | ||
Chapter 13: Implementing Basic Differences Tests | 350 | ||
13-1. Why Differences Are Important | 351 | ||
13-2. Small Sample Sizes: The Use of a t Test or a z Test and How SPSS Eliminates the Worry | 354 | ||
13-3. Testing for Significant Differences Between Two Groups | 355 | ||
Differences Between Percentages with Two Groups (Independent Samples) | 355 | ||
How to Use SPSS for Differences Between Percentages of Two Groups | 358 | ||
Differences Between Means with Two Groups (Independent Samples) | 358 | ||
Integrated Case: The Auto Concepts Survey: How to Perform an Independent Sample | 360 | ||
13-4. Testing for Significant Differences in Means Among More Than Two Groups: Analysis of Variance | 364 | ||
Basics of Analysis of Variance | 364 | ||
Post Hoc Tests: Detect Statistically Significant Differences Among Group Means | 366 | ||
Integrated Case: Auto Concepts: How to Run Analysis of Variance on SPSS | 366 | ||
Interpreting ANOVA (Analysis of Variance) | 369 | ||
13-5. Reporting Group Differences Tests to Clients | 369 | ||
13-6. Differences Between Two Means Within the Same Sample (Paired Sample) | 369 | ||
Integrated Case: The Auto Concepts Survey: How to Perform a Paired Samples t test | 371 | ||
13-7. Null Hypotheses for Differences Tests Summary | 372 | ||
Summary | 373 | ||
Key Terms | 373 | ||
Review Questions/Applications | 373 | ||
Case 13.1: L’Experience Félicité Restaurant Survey Differences Analysis | 375 | ||
Case 13.2: Integrated Case: The Auto Concepts Survey Differences Analysis | 375 | ||
Chapter 14: Making Use of Associations Tests | 376 | ||
14-1. Types of Relationships Between Two Variables | 378 | ||
Linear and Curvilinear Relationships | 378 | ||
Monotonic Relationships | 379 | ||
Nonmonotonic Relationships | 380 | ||
14-2. Characterizing Relationships Between Variables | 380 | ||
Presence | 380 | ||
Direction (or Pattern) | 380 | ||
Strength of Association | 381 | ||
14-3. Correlation Coefficients and Covariation | 382 | ||
Rules of Thumb for Correlation Strength | 382 | ||
The Correlation Sign: The Direction of the Relationship | 383 | ||
Graphing Covariation Using Scatter Diagrams | 383 | ||
14-4. The Pearson Product Moment Correlation Coefficient | 384 | ||
Integrated Case: Auto Concepts: How to Obtain Pearson Product Moment Correlation(s) with SPSS | 387 | ||
14-5. Reporting Correlation Findings to Clients | 389 | ||
14-6. Cross-Tabulations | 389 | ||
Cross-Tabulation Analysis | 390 | ||
Types of Frequencies and Percentages in a Cross-Tabulation Table | 390 | ||
14-7. Chi-Square Analysis | 393 | ||
Observed and Expected Frequencies | 393 | ||
The Computed x2 Value | 394 | ||
The Chi-Square Distribution | 394 | ||
How to Interpret a Chi-Square Result | 396 | ||
Integrated Case: Auto Concepts: Analyzing Cross-Tabulations for Significant Associations by Performing Chi-Square Analysis with SPSS | 398 | ||
14-8. Reporting Cross-Tabulation Findings to Clients | 400 | ||
14-9. Special Considerations in Association Procedures | 400 | ||
Summary | 402 | ||
Key Terms | 402 | ||
Review Questions/Applications | 403 | ||
Case 14.1: L’Experience Félicité Restaurant Survey Associative Analysis | 404 | ||
Case 14.2: Integrated Case: The Auto Concepts Survey Associative Analysis | 405 | ||
Chapter 15: Understanding Regression Analysis Basics | 406 | ||
15-1. Bivariate Linear Regression Analysis | 407 | ||
Basic Concepts in Regression Analysis | 408 | ||
How to Improve a Regression Analysis Finding | 408 | ||
15-2. Multiple Regression Analysis | 410 | ||
An Underlying Conceptual Model | 410 | ||
Multiple Regression Analysis Described | 412 | ||
Integrated Case: Auto Concepts: How to Run and Interpret Multiple Regression Analysis on SPSS | 415 | ||
“Trimming” the Regression for Significant Findings | 416 | ||
Special Uses of Multiple Regression Analysis | 417 | ||
15-3. Stepwise Multiple Regression | 422 | ||
How to Do Stepwise Multiple Regression with SPSS | 422 | ||
Step-by-Step Summary of How to Perform Multiple Regression Analysis | 422 | ||
15-4. Warnings Regarding Multiple Regression Analysis | 423 | ||
15-5. Reporting Regression Findings to Clients | 425 | ||
Summary | 428 | ||
Key Terms | 428 | ||
Review Questions/Applications | 428 | ||
Case 15.1. L’Experience Félicité Restaurant Survey Regression Analysis | 430 | ||
Case 15.2. Integrated Case: Auto Concepts Segmentation Analysis | 430 | ||
Chapter 16: The Research Report | 432 | ||
16-1. The Importance of the Marketing Research Report | 435 | ||
Improving the Efficiency of Report Writing | 435 | ||
16-2. Know Your Audience | 435 | ||
16-3. Avoid Plagiarism! | 436 | ||
16-4. Elements of the Report | 437 | ||
Front Matter | 437 | ||
Body | 442 | ||
End Matter | 444 | ||
16-5. Guidelines and Principles for the Written Report | 444 | ||
Headings and Subheadings | 444 | ||
Visuals | 444 | ||
Style | 445 | ||
16-6. Using Visuals: Tables and Figures | 446 | ||
Tables | 446 | ||
Pie Charts | 446 | ||
Bar Charts | 449 | ||
Line Graphs | 449 | ||
Flow Diagrams | 451 | ||
16-7. Producing an Appropriate Visual | 451 | ||
16-8. Presenting Your Research Orally | 452 | ||
16-9. Alternative Ways to Present Findings | 452 | ||
Videos | 454 | ||
Infographics | 455 | ||
16-10. Disseminating Results Throughout an Organization | 455 | ||
Dashboards | 455 | ||
Summary | 456 | ||
Key Terms | 457 | ||
Review Questions/Applications | 457 | ||
Case 16.1: Integrated Case: Auto Concepts: Report Writing | 458 | ||
Case 16.2: Integrated Case: Auto Concepts: Making a PowerPoint Presentation | 459 | ||
Endnotes | 461 | ||
Name Index | 477 | ||
Subject Index | 481 | ||
Back Cover | Back Cover |