Ger Snijkers, Gustav Haraldsen, Jacqui Jones, Diane Willimack

Designing and Conducting Business Surveys (eBook, PDF)

• Format: PDF

Produktbeschreibung

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. The book brings together what is currently known about planning, designing, and conducting business surveys, with producing and disseminating statistics or other research results from the collected data. This knowledge draws upon a variety of disciplines such as survey methodology, organizational sciences, sociology, psychology, and statistical methods. The contents of the book formulate a comprehensive guide to scholarly material previously dispersed among books, journal articles, and conference papers. This book provides guidelines that will help the reader make educated trade-off decisions that minimize survey errors, costs, and response burden, while being attentive to survey data quality. Major topics include: * Determining the survey content, considering user needs, the business context, and total survey quality * Planning the survey as a project * Sampling frames, procedures, and methods * Questionnaire design and testing for self-administered paper, web, and mixed-mode surveys * Survey communication design to obtain responses and facilitate the business response process * Conducting and managing the survey using paradata and project management tools * Data processing, including capture, editing, and imputation, and dissemination of statistical outputs Designing and Conducting Business Surveys is an indispensable resource for anyone involved in designing and/or conducting business or organizational surveys at statistical institutes, central banks, survey organizations, etc.; producing statistics or other research results from business surveys at universities, research organizations, etc.; or using data produced from business surveys. The book also lays a foundation for new areas of research in business surveys.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 640
• Erscheinungstermin: 23. Juli 2013
• Englisch
• ISBN-13: 9781118447925
• Artikelnr.: 39166676

Autorenporträt

GER SNIJKERS, PhD, is Senior Researcher and Advisor in Business Survey Data Collection Methodology at Statistics Netherlands, after having held various research and project management positions. From 2006-2011, he held the position of Professor of Business Survey Methodology at Utrecht University. GUSTAV HARALDSEN, Mag. Art., is Senior Methodological Advisor in the Department of Data Collection and Methods at Statistics Norway. He previously headed the Division for Interviewing Surveys and the Division of Data Collection Methods. JACQUI JONES, BA (Hons), MSc, is Deputy Director of the Business Indicators and Balance of Payments Division in the UK Office of National Statistics (ONS). Prior to this, she worked in the Methodology Directorate at ONS. DIANE K. WILLIMACK, MS, MA, is Chief of the Response Improvement Research Staff at the Economic Programs Directorate of the U.S. Census Bureau. She previously served as a mathematical statistician and survey methodologist at the National Agricultural Statistics Service (U.S. Department of Agriculture). Additional contributors include Paul Smith (ONS), Deirdre Giesen (Statistics Netherlands), Li Chun Zhang (Statistics Norway), and Mike Hidiroglou (Statistics Canada).

Inhaltsangabe

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