Description

Book Synopsis
Designing and Conducting Business Surveys provides a coherent overview of the business survey process, from start to finish. It uniquely integrates an understanding of how businesses operate, a total survey error approach to data quality that focuses specifically on business surveys, and sound project management principles.

Table of Contents

Preface xix

Contributors xxiii

Abbreviations xxv

1. Surveys and Business Surveys 1
Jacqui Jones, Ger Snijkers, and Gustav Haraldsen

1.1. The Objective of this Book, 1

1.2. The Statistical Production Process, 2

1.3. Surveys, 4

1.3.1. Definition of Surveys, 4

1.3.2. Survey Constraints, Considerations, and Tradeoffs, 5

1.3.3. A Brief Historical Look at Surveys, 8

1.4. Types of Business Data Outputs, 10

1.4.1. Official Statistics, 10

1.4.2. Other Types of Business Data Outputs, 14

1.5. Use of Business Data Outputs, 16

1.5.1. National, Regional, and Local Economic Performance, 17

1.5.2. Individual Business Monitoring and Policymaking, 18

1.5.3. Everyday Decisions, 18

1.6. Obtaining Business Data, 19

1.6.1. Business Data Collection Methods, 19

1.7. Business Surveys, 22

1.7.1. Types of Business Surveys, 22

1.7.2. The Business Survey–Output Production Process, 23

1.7.3. Perspectives of the Business Survey Process, 26

1.8. Overview of the Book, 28

1.8.1. The Audience, 28

1.8.2. Organization of the Book, 29

1.8.3. Chapter Summaries, 29

Acknowledgments, 33

Appendix, 33

2. The Business Context and its Implications for the Survey Response Process 39
Diane K. Willimack and Ger Snijkers

2.1. The Business Context from the Perspective of the Organizational Sciences, 40

2.1.1. Business Goals and Behaviors and Implications for Survey Response, 40

2.1.2. Dimensions of Social Behavior in Organizations Pertinent to the Survey Response Task, 45

2.1.3. The Response Process Viewed as Work, 49

2.2. A Comprehensive Approach Integrating the Business Context and the Survey Response Process, 51

2.2.1. The Decision to Participate, 54

2.2.2. Performing Response Tasks, 60

2.2.3. Release of the Questionnaire, 75

2.2.4. Role of the Survey Organization in the Business Survey Response Process: Implications for Survey Design, 75

2.3. Summary, 79

Acknowledgments, 82

3. Quality Issues in Business Surveys 83
Gustav Haraldsen

3.1. Survey Quality from a User/producer Perspective, 84

3.1.1. Users and User Evaluations of Business Surveys, 86

3.1.2. The Total Survey Error Approach, 88

3.2. Sample-Related Quality Issues, 96

3.2.1. A Glimpse into Transaction Studies, 96

3.2.2. Specifying Observational Units, 97

3.2.3. The Convenience Sample Element, 99

3.2.4. Sampling Error Issues, 101

3.2.5. Reporting Units and Informants, 102

3.2.6. Response Rate Issues, 103

3.2.7. Quality Effects of Postsurvey Adjustments, 106

3.3. Measurement-Related Quality Issues, 106

3.3.1. Validity Challenges during Survey Specification, 107

3.3.2. Sources of Measurement Error in Business Surveys, 108

3.3.3. Measurement Issues Summarized, 118

3.4. Sample and Measurement Issues Combined, 120

Acknowledgment, 125

4. Planning the Survey 127
Ger Snijkers, Gustav Haraldsen, and Jacqui Jones

4.1. Introduction, 127

4.2. Business Surveys and Project Management Principles, 128

4.3. Specifying and Planning the Survey, 131

4.3.1. Specifying the Survey, 132

4.3.2. Planning the Survey in Detail: The Planning Process, 135

4.3.3. Planning the Fieldwork, 142

4.3.4. Planning the Designing, Building, and Testing of the Survey Components, 143

4.3.5. Planning the Data Analysis, Dissemination, and Archiving, 151

4.3.6. Planning the Survey Evaluation, 152

4.4. Required Resources, 153

4.5. The Timetable, 153

4.6. Planning Managing, Controlling, Monitoring, and Evaluation of the Survey Project, 154

4.7. Risk Management, 156

4.8. Finalizing the Project Plan and Getting Started, 162

4.9. Summary and Progress Status Overview, 162

Acknowledgment, 163

5. Sampling and Estimation for Business Surveys 165
Paul Smith

5.1. Basic Principles, 165

5.2. Registers and Frames, 167

5.2.1. Business Registers, 167

5.2.2. Constructing a Frame (without a Business Register), 174

5.2.3. Register and Frame Quality, 175

5.2.4. Dual-Frame Surveys, 176

5.3. Sample Design, 177

5.3.1. Some Basic Ideas, 177

5.3.2. Stratified Sampling, 178

5.3.3. Probability Proportional to Size (PPS) Sampling, 195

5.3.4. Cutoff Sampling, 196

5.3.5. Sample Rotation and Overlap, 197

5.3.6. Special Sample Designs, 199

5.4. Estimation, 202

5.4.1. Horvitz–Thompson Estimation, 202

5.4.2. Some Basic Ideas, 203

5.4.3. Ratio Estimation, 205

5.4.4. Combined Ratio Estimation, 207

5.4.5. More Complex Estimators, 208

5.4.6. Accuracy of Auxiliary Information, 208

5.4.7. Optimal Uses of Auxiliary Information, 209

5.4.8. Estimating Discontinuities, 209

5.5. Outliers, 210

5.5.1. Inspection and “Surprise Strata”, 211

5.5.2. Winsorization, 212

5.5.3. Other Approaches, 213

5.6. Variance Estimation, 214

5.7. Small Area Estimation, 216

5.8. Summary, 217

Acknowledgments, 218

6. Understanding and Coping with Response Burden 219
Gustav Haraldsen, Jacqui Jones, Deirdre Giesen, and Li-Chun Zhang

6.1. A Cost versus a Cost Benefit Approach, 220

6.1.1. Politicians’ Bird’s-Eye View, 221

6.1.2. Commercial Worries, 222

6.1.3. Perceived Response Burden, 223

6.2. Measuring and Monitoring Business Response Burden, 226

6.2.1. Measuring and Calculating Actual Response Burden, 229

6.2.2. Measuring Perceived Response Burden, 232

6.2.3. Calculations, 234

6.3. An Analytical Approach to Response Burden, 235

6.3.1. Disentangling Some Sources of Response Burden, 238

6.3.2. Suggesting a Curvilinear Correlation between Response Burden and Response Quality, 239

6.4. Measures to Reduce Response Burden, 241

6.4.1. Survey Reduction Measures, 241

6.4.2. Sample Coordination, 243

6.4.3. Survey Communication Measures, 248

6.4.4. Questionnaire Improvement Measures, 249

6.4.5. Tailored Evaluations of Response Burden Reduction Measures, 251

Acknowledgments, 252

7. Methods for the Development, Testing, and Evaluation of Data Collection Instruments 253
Diane K. Willimack

7.1. A Framework for Questionnaire Development, Testing, and Evaluation, 254

7.1.1. Business Survey Response Model and Measurement Error, 256

7.1.2. Constraints and Limitations to Questionnaire Development, Testing, and Evaluation in the Business Survey Context, 258

7.2. Developing Content, Measurements, and Survey Questions, 260

7.2.1. The Roles of Subject Area Specialists, Stakeholders, and Data Users, 262

7.2.2. Methods for Content Development and Specifying Measurements, 262

7.3. Testing Questions and Questionnaires, 267

7.3.1. The Response Model as a Framework for Testing, 267

7.3.2. Methods, 269

7.4. Evaluating Survey Questions and Questionnaires, 276

7.4.1. Methods Used during Data Collection, 276

7.4.2. Methods Used after Data Collection, 278

7.4.3. Methods for Identifying Questionnaire Problems in Recurring Surveys, 280

7.5. Development, Testing, and Evaluation of Electronic Data Collection Instruments, 282

7.5.1. Development Strategies for Electronic Instruments, 282

7.5.2. Usability Testing, 285

7.5.3. Evaluating Web Survey Data Collection Instruments, 286

7.6. Analyzing Qualitative Data, 287

7.6.1. Data Capture, 288

7.6.2. Types of Analysis, 288

7.6.3. Data Reduction, 289

7.6.4. Data Display, 290

7.6.5. Drawing Conclusions and Verification, 290

7.7. Multimethod Approaches to Development, Testing, and Evaluation, 290

7.8. Organization and Logistics, 293

7.8.1. Survey Organizational Structures for Instrument Development, Testing, and Evaluation, 293

7.8.2. Pretesting Logistics, 294

7.9. Summary, 295

Acknowledgments, 298

Appendix 7.A.1 Example of Conclusions from Qualitative Data Analysis: Public Trust in Statistics: A Conceptual

Model of Trust Determinants, 298

Appendix 7.A.2 Case Study: Logistics of Questionnaire Pretesting for Economic Survey Programs at the US Census Bureau, 299

8. Questionnaire Communication in Business Surveys 303
Gustav Haraldsen

8.1. Communication Modes, 303

8.2. Elements in Concert, 306

8.3. Tailoring for Businesses, 311

8.3.1. Setting the Scene, 313

8.3.2. Common Access to Several Web Surveys, 317

8.3.3. Layout and Functional Tailoring for Internal Data Collection, 325

8.4. Phrasing Questions in Business Surveys, 332

8.4.1. From Requirements to Inquiries, 332

8.4.2. Clarifying Terms and Tasks, 335

8.4.3. Listening to Questionnaires, 340

8.5. Minimizing Response Burden, 346

8.5.1. Time Saving Measures, 347

8.5.2. Reducing the Cognitive Burden, 351

8.6. Concluding Reflections, 357

Acknowledgments, 357

9. Business Survey Communication 359
Ger Snijkers and Jacqui Jones

9.1. Introduction, 359

9.2. The Role, Objectives, and Process of Business Survey Communication, 360

9.2.1. Role, 360

9.2.2. Objectives, 361

9.2.3. Process, 362

9.3. Tailoring to the Business Context, 373

9.3.1. Actors and Their Roles in the Response Process, 373

9.3.2. Business Size and Economic Sector, 374

9.3.3. Factors Affecting the Response Process, 375

9.3.4. Questions and Complaints, 377

9.4. The Survey Organization Context, 377

9.4.1. Staff in the Communication Process and Their Roles, 377

9.4.2. Survey Organization Policies and Procedures, 383

9.4.3. Survey Communication in Perspective, 388

9.5. Designing an Effective Business Survey Communication Strategy, 389

9.5.1. Planning and Designing the Communication Strategy, 390

9.5.2. Effectiveness of Communication Modes, 398

9.5.3. Effectively Motivating and Facilitating, 400

9.6. Business Survey Communication Measures, Practices, and Guidelines, 407

9.6.1. Prefield Communication Measures, 408

9.6.2. Field Communication Measures, 412

9.6.3. Special Cases: Large Businesses and Mixed-Mode Designs, 421

9.7. Summary and Example of a Communication Strategy, 426

Acknowledgment, 430

10. Managing the Data Collection 431
Ger Snijkers and Gustav Haraldsen

10.1. Introduction, 431

10.2. Implementing the Survey, 432

10.3. Active Fieldwork Management, 434

10.4. Paradata, 436

10.5. Monitoring the Quality of the Response, 440

10.5.1. A Classification of Data Collection Outcome Codes, 441

10.5.2. Response and Return Rates at Unit Level, 445

10.5.3. Weights of Businesses, 447

10.5.4. Distribution of the Response: Representativeness, 448

10.5.5. Quality of the Measurements, 449

10.6. Monitoring the Survey Production Process, 451

10.7. Survey Evaluation and Quality Report, 454

10.8. Summary, 456

Acknowledgment, 457

11. Capturing, Coding, and Cleaning Survey Data 459
Jacqui Jones and Mike Hidiroglou

11.1. Introduction, 459

11.2. Data Capture, 461

11.2.1. Step One: Initial Data Capture, 461

11.2.2. Minimizing, Measuring, and Monitoring Errors in Initial Data Capture, 462

11.2.3. Step Two: Data Transfer, 464

11.2.4. Step Three: Data Capture Processing, 465

11.2.5. Capturing Data from Paper Questionnaires, 466

11.2.6. Electronic Scanning, 468

11.2.7. Design of Paper Self-Completion Questionnaires for Electronic Scanning, 468

11.2.8. Instructions for Completing a Paper Self-Completion Questionnaire to be Scanned, 471

11.2.9. Minimizing, Measuring, and Monitoring Errors in Data Capture Processing, 473

11.3. Data Coding, 475

11.3.1. Coding Descriptions to Classifications, 478

11.3.2. Questionnaire Design Implications, 478

11.3.3. Two Examples of Data Coding Tools, 480

11.3.4. Minimizing, Measuring, and Monitoring Errors in Data Coding, 481

11.4. Editing and Imputation, 483

11.4.1. An Overview of Editing and Imputation in Business Surveys, 483

11.4.2. Microediting, 485

11.4.3. Types of Microdata Error, 485

11.4.4. Methods for Identifying Microerrors, 489

11.4.5. Treatment of Microdata Errors, 492

11.4.6. Identifying Errors at the Macroediting Stage, 496

11.4.7. Imputation, 498

11.4.8. Minimizing, Measuring, and Monitoring Errors in Editing and Imputation, 500

11.4.9. Editing Strategies, 502

11.5. Concluding Comments, 503

Acknowledgments, 504

12. From Survey Data to Statistics 505
Jacqui Jones

12.1. Introduction, 505

12.2. Analysis, 505

12.2.1. Analysis and Different Types of Statistical Outputs, 507

12.2.2. Analytical Technique Considerations, 510

12.2.3. Analytical Techniques for Improving Statistical Interpretation, 513

12.3. Preparing for Dissemination, 527

12.3.1. Preparing Statistical Tables and Datasets, 528

12.3.2. The Importance of Maintaining Confidentiality, 530

12.3.3. Disclosure Control Methods, 532

12.3.4. Presenting the Statistics, 536

12.4. Dissemination, 539

12.4.1. Evaluating Statistical Dissemination, 539

12.5. Archiving, 540

12.6. Concluding Comments, 542

Acknowledgments, 543

References 545

Index 597

Designing and Conducting Business Surveys

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      Publisher: Wiley
      Publication Date: 27/09/2013
      ISBN13: 9780470903049, 978-0470903049
      ISBN10:

      Description

      Book Synopsis
      Designing and Conducting Business Surveys provides a coherent overview of the business survey process, from start to finish. It uniquely integrates an understanding of how businesses operate, a total survey error approach to data quality that focuses specifically on business surveys, and sound project management principles.

      Table of Contents

      Preface xix

      Contributors xxiii

      Abbreviations xxv

      1. Surveys and Business Surveys 1
      Jacqui Jones, Ger Snijkers, and Gustav Haraldsen

      1.1. The Objective of this Book, 1

      1.2. The Statistical Production Process, 2

      1.3. Surveys, 4

      1.3.1. Definition of Surveys, 4

      1.3.2. Survey Constraints, Considerations, and Tradeoffs, 5

      1.3.3. A Brief Historical Look at Surveys, 8

      1.4. Types of Business Data Outputs, 10

      1.4.1. Official Statistics, 10

      1.4.2. Other Types of Business Data Outputs, 14

      1.5. Use of Business Data Outputs, 16

      1.5.1. National, Regional, and Local Economic Performance, 17

      1.5.2. Individual Business Monitoring and Policymaking, 18

      1.5.3. Everyday Decisions, 18

      1.6. Obtaining Business Data, 19

      1.6.1. Business Data Collection Methods, 19

      1.7. Business Surveys, 22

      1.7.1. Types of Business Surveys, 22

      1.7.2. The Business Survey–Output Production Process, 23

      1.7.3. Perspectives of the Business Survey Process, 26

      1.8. Overview of the Book, 28

      1.8.1. The Audience, 28

      1.8.2. Organization of the Book, 29

      1.8.3. Chapter Summaries, 29

      Acknowledgments, 33

      Appendix, 33

      2. The Business Context and its Implications for the Survey Response Process 39
      Diane K. Willimack and Ger Snijkers

      2.1. The Business Context from the Perspective of the Organizational Sciences, 40

      2.1.1. Business Goals and Behaviors and Implications for Survey Response, 40

      2.1.2. Dimensions of Social Behavior in Organizations Pertinent to the Survey Response Task, 45

      2.1.3. The Response Process Viewed as Work, 49

      2.2. A Comprehensive Approach Integrating the Business Context and the Survey Response Process, 51

      2.2.1. The Decision to Participate, 54

      2.2.2. Performing Response Tasks, 60

      2.2.3. Release of the Questionnaire, 75

      2.2.4. Role of the Survey Organization in the Business Survey Response Process: Implications for Survey Design, 75

      2.3. Summary, 79

      Acknowledgments, 82

      3. Quality Issues in Business Surveys 83
      Gustav Haraldsen

      3.1. Survey Quality from a User/producer Perspective, 84

      3.1.1. Users and User Evaluations of Business Surveys, 86

      3.1.2. The Total Survey Error Approach, 88

      3.2. Sample-Related Quality Issues, 96

      3.2.1. A Glimpse into Transaction Studies, 96

      3.2.2. Specifying Observational Units, 97

      3.2.3. The Convenience Sample Element, 99

      3.2.4. Sampling Error Issues, 101

      3.2.5. Reporting Units and Informants, 102

      3.2.6. Response Rate Issues, 103

      3.2.7. Quality Effects of Postsurvey Adjustments, 106

      3.3. Measurement-Related Quality Issues, 106

      3.3.1. Validity Challenges during Survey Specification, 107

      3.3.2. Sources of Measurement Error in Business Surveys, 108

      3.3.3. Measurement Issues Summarized, 118

      3.4. Sample and Measurement Issues Combined, 120

      Acknowledgment, 125

      4. Planning the Survey 127
      Ger Snijkers, Gustav Haraldsen, and Jacqui Jones

      4.1. Introduction, 127

      4.2. Business Surveys and Project Management Principles, 128

      4.3. Specifying and Planning the Survey, 131

      4.3.1. Specifying the Survey, 132

      4.3.2. Planning the Survey in Detail: The Planning Process, 135

      4.3.3. Planning the Fieldwork, 142

      4.3.4. Planning the Designing, Building, and Testing of the Survey Components, 143

      4.3.5. Planning the Data Analysis, Dissemination, and Archiving, 151

      4.3.6. Planning the Survey Evaluation, 152

      4.4. Required Resources, 153

      4.5. The Timetable, 153

      4.6. Planning Managing, Controlling, Monitoring, and Evaluation of the Survey Project, 154

      4.7. Risk Management, 156

      4.8. Finalizing the Project Plan and Getting Started, 162

      4.9. Summary and Progress Status Overview, 162

      Acknowledgment, 163

      5. Sampling and Estimation for Business Surveys 165
      Paul Smith

      5.1. Basic Principles, 165

      5.2. Registers and Frames, 167

      5.2.1. Business Registers, 167

      5.2.2. Constructing a Frame (without a Business Register), 174

      5.2.3. Register and Frame Quality, 175

      5.2.4. Dual-Frame Surveys, 176

      5.3. Sample Design, 177

      5.3.1. Some Basic Ideas, 177

      5.3.2. Stratified Sampling, 178

      5.3.3. Probability Proportional to Size (PPS) Sampling, 195

      5.3.4. Cutoff Sampling, 196

      5.3.5. Sample Rotation and Overlap, 197

      5.3.6. Special Sample Designs, 199

      5.4. Estimation, 202

      5.4.1. Horvitz–Thompson Estimation, 202

      5.4.2. Some Basic Ideas, 203

      5.4.3. Ratio Estimation, 205

      5.4.4. Combined Ratio Estimation, 207

      5.4.5. More Complex Estimators, 208

      5.4.6. Accuracy of Auxiliary Information, 208

      5.4.7. Optimal Uses of Auxiliary Information, 209

      5.4.8. Estimating Discontinuities, 209

      5.5. Outliers, 210

      5.5.1. Inspection and “Surprise Strata”, 211

      5.5.2. Winsorization, 212

      5.5.3. Other Approaches, 213

      5.6. Variance Estimation, 214

      5.7. Small Area Estimation, 216

      5.8. Summary, 217

      Acknowledgments, 218

      6. Understanding and Coping with Response Burden 219
      Gustav Haraldsen, Jacqui Jones, Deirdre Giesen, and Li-Chun Zhang

      6.1. A Cost versus a Cost Benefit Approach, 220

      6.1.1. Politicians’ Bird’s-Eye View, 221

      6.1.2. Commercial Worries, 222

      6.1.3. Perceived Response Burden, 223

      6.2. Measuring and Monitoring Business Response Burden, 226

      6.2.1. Measuring and Calculating Actual Response Burden, 229

      6.2.2. Measuring Perceived Response Burden, 232

      6.2.3. Calculations, 234

      6.3. An Analytical Approach to Response Burden, 235

      6.3.1. Disentangling Some Sources of Response Burden, 238

      6.3.2. Suggesting a Curvilinear Correlation between Response Burden and Response Quality, 239

      6.4. Measures to Reduce Response Burden, 241

      6.4.1. Survey Reduction Measures, 241

      6.4.2. Sample Coordination, 243

      6.4.3. Survey Communication Measures, 248

      6.4.4. Questionnaire Improvement Measures, 249

      6.4.5. Tailored Evaluations of Response Burden Reduction Measures, 251

      Acknowledgments, 252

      7. Methods for the Development, Testing, and Evaluation of Data Collection Instruments 253
      Diane K. Willimack

      7.1. A Framework for Questionnaire Development, Testing, and Evaluation, 254

      7.1.1. Business Survey Response Model and Measurement Error, 256

      7.1.2. Constraints and Limitations to Questionnaire Development, Testing, and Evaluation in the Business Survey Context, 258

      7.2. Developing Content, Measurements, and Survey Questions, 260

      7.2.1. The Roles of Subject Area Specialists, Stakeholders, and Data Users, 262

      7.2.2. Methods for Content Development and Specifying Measurements, 262

      7.3. Testing Questions and Questionnaires, 267

      7.3.1. The Response Model as a Framework for Testing, 267

      7.3.2. Methods, 269

      7.4. Evaluating Survey Questions and Questionnaires, 276

      7.4.1. Methods Used during Data Collection, 276

      7.4.2. Methods Used after Data Collection, 278

      7.4.3. Methods for Identifying Questionnaire Problems in Recurring Surveys, 280

      7.5. Development, Testing, and Evaluation of Electronic Data Collection Instruments, 282

      7.5.1. Development Strategies for Electronic Instruments, 282

      7.5.2. Usability Testing, 285

      7.5.3. Evaluating Web Survey Data Collection Instruments, 286

      7.6. Analyzing Qualitative Data, 287

      7.6.1. Data Capture, 288

      7.6.2. Types of Analysis, 288

      7.6.3. Data Reduction, 289

      7.6.4. Data Display, 290

      7.6.5. Drawing Conclusions and Verification, 290

      7.7. Multimethod Approaches to Development, Testing, and Evaluation, 290

      7.8. Organization and Logistics, 293

      7.8.1. Survey Organizational Structures for Instrument Development, Testing, and Evaluation, 293

      7.8.2. Pretesting Logistics, 294

      7.9. Summary, 295

      Acknowledgments, 298

      Appendix 7.A.1 Example of Conclusions from Qualitative Data Analysis: Public Trust in Statistics: A Conceptual

      Model of Trust Determinants, 298

      Appendix 7.A.2 Case Study: Logistics of Questionnaire Pretesting for Economic Survey Programs at the US Census Bureau, 299

      8. Questionnaire Communication in Business Surveys 303
      Gustav Haraldsen

      8.1. Communication Modes, 303

      8.2. Elements in Concert, 306

      8.3. Tailoring for Businesses, 311

      8.3.1. Setting the Scene, 313

      8.3.2. Common Access to Several Web Surveys, 317

      8.3.3. Layout and Functional Tailoring for Internal Data Collection, 325

      8.4. Phrasing Questions in Business Surveys, 332

      8.4.1. From Requirements to Inquiries, 332

      8.4.2. Clarifying Terms and Tasks, 335

      8.4.3. Listening to Questionnaires, 340

      8.5. Minimizing Response Burden, 346

      8.5.1. Time Saving Measures, 347

      8.5.2. Reducing the Cognitive Burden, 351

      8.6. Concluding Reflections, 357

      Acknowledgments, 357

      9. Business Survey Communication 359
      Ger Snijkers and Jacqui Jones

      9.1. Introduction, 359

      9.2. The Role, Objectives, and Process of Business Survey Communication, 360

      9.2.1. Role, 360

      9.2.2. Objectives, 361

      9.2.3. Process, 362

      9.3. Tailoring to the Business Context, 373

      9.3.1. Actors and Their Roles in the Response Process, 373

      9.3.2. Business Size and Economic Sector, 374

      9.3.3. Factors Affecting the Response Process, 375

      9.3.4. Questions and Complaints, 377

      9.4. The Survey Organization Context, 377

      9.4.1. Staff in the Communication Process and Their Roles, 377

      9.4.2. Survey Organization Policies and Procedures, 383

      9.4.3. Survey Communication in Perspective, 388

      9.5. Designing an Effective Business Survey Communication Strategy, 389

      9.5.1. Planning and Designing the Communication Strategy, 390

      9.5.2. Effectiveness of Communication Modes, 398

      9.5.3. Effectively Motivating and Facilitating, 400

      9.6. Business Survey Communication Measures, Practices, and Guidelines, 407

      9.6.1. Prefield Communication Measures, 408

      9.6.2. Field Communication Measures, 412

      9.6.3. Special Cases: Large Businesses and Mixed-Mode Designs, 421

      9.7. Summary and Example of a Communication Strategy, 426

      Acknowledgment, 430

      10. Managing the Data Collection 431
      Ger Snijkers and Gustav Haraldsen

      10.1. Introduction, 431

      10.2. Implementing the Survey, 432

      10.3. Active Fieldwork Management, 434

      10.4. Paradata, 436

      10.5. Monitoring the Quality of the Response, 440

      10.5.1. A Classification of Data Collection Outcome Codes, 441

      10.5.2. Response and Return Rates at Unit Level, 445

      10.5.3. Weights of Businesses, 447

      10.5.4. Distribution of the Response: Representativeness, 448

      10.5.5. Quality of the Measurements, 449

      10.6. Monitoring the Survey Production Process, 451

      10.7. Survey Evaluation and Quality Report, 454

      10.8. Summary, 456

      Acknowledgment, 457

      11. Capturing, Coding, and Cleaning Survey Data 459
      Jacqui Jones and Mike Hidiroglou

      11.1. Introduction, 459

      11.2. Data Capture, 461

      11.2.1. Step One: Initial Data Capture, 461

      11.2.2. Minimizing, Measuring, and Monitoring Errors in Initial Data Capture, 462

      11.2.3. Step Two: Data Transfer, 464

      11.2.4. Step Three: Data Capture Processing, 465

      11.2.5. Capturing Data from Paper Questionnaires, 466

      11.2.6. Electronic Scanning, 468

      11.2.7. Design of Paper Self-Completion Questionnaires for Electronic Scanning, 468

      11.2.8. Instructions for Completing a Paper Self-Completion Questionnaire to be Scanned, 471

      11.2.9. Minimizing, Measuring, and Monitoring Errors in Data Capture Processing, 473

      11.3. Data Coding, 475

      11.3.1. Coding Descriptions to Classifications, 478

      11.3.2. Questionnaire Design Implications, 478

      11.3.3. Two Examples of Data Coding Tools, 480

      11.3.4. Minimizing, Measuring, and Monitoring Errors in Data Coding, 481

      11.4. Editing and Imputation, 483

      11.4.1. An Overview of Editing and Imputation in Business Surveys, 483

      11.4.2. Microediting, 485

      11.4.3. Types of Microdata Error, 485

      11.4.4. Methods for Identifying Microerrors, 489

      11.4.5. Treatment of Microdata Errors, 492

      11.4.6. Identifying Errors at the Macroediting Stage, 496

      11.4.7. Imputation, 498

      11.4.8. Minimizing, Measuring, and Monitoring Errors in Editing and Imputation, 500

      11.4.9. Editing Strategies, 502

      11.5. Concluding Comments, 503

      Acknowledgments, 504

      12. From Survey Data to Statistics 505
      Jacqui Jones

      12.1. Introduction, 505

      12.2. Analysis, 505

      12.2.1. Analysis and Different Types of Statistical Outputs, 507

      12.2.2. Analytical Technique Considerations, 510

      12.2.3. Analytical Techniques for Improving Statistical Interpretation, 513

      12.3. Preparing for Dissemination, 527

      12.3.1. Preparing Statistical Tables and Datasets, 528

      12.3.2. The Importance of Maintaining Confidentiality, 530

      12.3.3. Disclosure Control Methods, 532

      12.3.4. Presenting the Statistics, 536

      12.4. Dissemination, 539

      12.4.1. Evaluating Statistical Dissemination, 539

      12.5. Archiving, 540

      12.6. Concluding Comments, 542

      Acknowledgments, 543

      References 545

      Index 597

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