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Forrest V. Morgeson III, Ph.D. Barbara Everitt Bryant, Ph.D.

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Presentation on theme: "Forrest V. Morgeson III, Ph.D. Barbara Everitt Bryant, Ph.D."— Presentation transcript:

1 Forrest V. Morgeson III, Ph.D. Barbara Everitt Bryant, Ph.D.
Does Interviewing Method Matter? Comparing Consumer Satisfaction Results across Internet and RDD Telephone Samples Forrest V. Morgeson III, Ph.D. Director of Research, American Customer Satisfaction Index Barbara Everitt Bryant, Ph.D. Research Scientist-Emerita, University of Michigan Reg Baker President, Market Strategies International Presented at the 66th Annual American Association for Public Opinion Research Conference

2 Discussion Agenda Overview: Research Questions and Findings
The American Customer Satisfaction Index (ACSI) Extant Research on Interviewing Method Differences Data and Analysis Methods Results and Findings Conclusions and Implications

3 Research Questions and Findings
Research Questions: Does interview method matter? Do the results produced in a multi-industry consumer satisfaction study differ significantly across a sample collected through RDD/probability sampling and telephone interviewing, and one collected via online panel/nonprobability sampling and Internet interviewing? Research Design: We utilize a multi-method sample of consumer satisfaction data, structural equation modeling techniques, and two tests of difference to investigate the significance of differences in survey responses across samples drawn and interviewed using these two methods Findings: While some differences are observed, interview method only marginally impacts the means of the survey responses or the parameter estimates from the structural models. Overall, the findings suggest that mixed-method interviewing is feasible and reliable for consumer-oriented survey research projects

4 Discussion Agenda Overview: Research Questions and Findings
The American Customer Satisfaction Index (ACSI) Extant Research on Interviewing Method Differences Data and Analysis Methods Results and Findings Conclusions and Implications

5 Overview of the ACSI Established in 1994, ACSI is the only standardized measure of customer satisfaction in the U.S. economy, covering approximately 225 companies in 45 industries and 10 economic sectors; companies measured account for roughly one-third of the U.S. GDP 100+ departments and agencies of the U.S. federal government also measured on an annual basis, along with local and state government measures Results from all surveys are published monthly in various media and on the ACSI website,

6 Structure of the ACSI National ACSI Utilities Information
Accommodation & Food Services E-Business Public Administration/ Government Finance & Insurance Transportation & Warehousing Health Care & Social Assistance Manufacturing/ Durable Goods Manufacturing/ Nondurable Goods Retail Trade E-Commerce Energy Utilities Newspapers Motion Pictures Broadcasting TV News Software Fixed Line Telephone Service Wireless Telephone Service Cable & Satellite TV Hotels Limited-Service Restaurants Full-Service News & Information Portals/ Search Engines Social Networking Local Government Federal Government Banks Life Insurance Health Insurance Property & Casualty Airlines U.S. Postal Service Express Delivery Hospitals Personal Computers Electronics (TV/VCR/DVD) Major Appliances Automobiles & Light Vehicles Cellular Telephones Food Manufacturing Pet Food Soft Drinks Breweries Cigarettes Apparel Athletic Shoes Personal Care & Cleaning Products Supermarkets Gasoline Stations Department & Discount Stores Specialty Retail Stores Health & Personal Care Stores Retail Brokerage Travel

7 The ACSI Model and Methodology
• In ACSI methodology, customer satisfaction is imbedded in a system of relationships, and analyzed as part of a structural equation model. The model produces two critical pieces of data useful to researchers and firms/agencies: • The model provides mean scores (on a scale) for each measured composite or latent variable • The model provides parameter estimates (or path coefficients) indicating what most strongly influences satisfaction, and in turn how satisfaction influences future consumer behaviors Perceived Quality Customer Complaints Overall Customization Reliability Customer Satisfaction Perceived Value Complaint Behavior Price Given Quality Quality Given Price Customer Expectations Satisfaction Comparison w/ Ideal Confirm/Disconfirm Expectations Customer Loyalty Overall Customization Reliability Repurchase Likelihood Price Tolerance (Reservation Price)

8 ACSI Data Collection Each year, including all private sector, public sector and custom research projects, ACSI collects approximately 125,000 interviews of consumers From 1994 through 2009, nearly all of this data (with a few exceptions for e-commerce companies) was collected over the telephone using random-digit-dial probability sampling and CATI Beginning in 2010, and following pilot testing that produced promising results, ACSI moved to a multi-method interviewing approach, with roughly half the data for any measured company/government agency collected using RDD probability sampling and CATI, and the other half collected using a nonprobability panel of double opt-in respondents interviewed online

9 Discussion Agenda Overview: Research Questions and Findings
The American Customer Satisfaction Index (ACSI) Extant Research on Interviewing Method Differences Data and Analysis Methods Results and Findings Conclusions and Implications

10 Extant Research While a handful of studies comparing results for samples interviewed online to samples interviewed over the telephone exist,* these studies have focused almost exclusively on political opinions, voter preference, etc. There remains very little research into what differences (if any) are likely to be observed across these two interviewing methods for consumer-oriented data, where a significant portion of data collection and survey research is focused *Chang, L. and J.A. Krosnick (2009). “National Surveys via RDD Telephone Interviewing Versus The Internet: Comparing Sample Representativeness and Response Quality,” Public Opinion Quarterly, 73(4), 641–678. Fricker, S., M. Galesic, R. Tourangeau and T. Yan (2005). “An Experimental Comparison of Web and Telephone Surveys,” Public Opinion Quarterly, 69(3), Vannieuwenhuyze, J., G. Loosveldt and G. Molenberghs (2010). “A Method for Evaluating Mode Effects in Mixed-Mode Surveys,” Public Opinion Quarterly, 74(5),

11 Findings from the AAPOR Online Task Force
Findings from the AAPOR Online Task Force* suggest that there is no theoretical basis for assuming that samples drawn from nonprobability online panels are representative of a larger population, and that therefore results may differ when compared to an RDD probability sample interviewed over the telephone However, this research also concludes there may be instances in which online panels are useful and reliable, and we conduct a series of empirical tests to see if customer satisfaction data (ACSI) is such a case *Baker, R. et al. (2010). “Research Synthesis: AAPOR Report on Online Panels,” Public Opinion Quarterly, 74(4), 711–781.

12 Discussion Agenda Overview: Research Questions and Findings
The American Customer Satisfaction Index (ACSI) Extant Research on Interviewing Method Differences Data and Analysis Methods Results and Findings Conclusions and Implications

13 Research Questions From the perspective of the ACSI project and its methodology, two questions regarding multi-method interviewing are most relevant and important: Do mean scores exhibit significant differences between a sample interviewed online when compared to a sample interviewed using RDD/CATI? Do model parameter estimates exhibit significant differences between a sample interviewed online when compared to a sample interviewed using RDD/CATI?

14 Data To seek answers to our research questions, we utilize a sample of data consisting of approximately 9000 interviews Roughly half of these cases were collected via Internet interviewing (from a sample balanced to Census demographics from a large online panel (the Research Now panel)), and the other half collected using RDD and CATI, allowing us to test the similarities/differences produced by these two interviewing methods The ACSI model (shown earlier) was estimated independently for each industry and each interviewing method, producing distinct mean scores and estimates (path coefficients) facilitating these comparisons

15 Data The data represent consumer responses to questions measuring satisfaction (and the other modeled variables) with companies and industries in six NAICS sectors (for more information on the companies included in the sample, see Appendix A): Apparel manufacturing (Manufacturing/nondurable goods) Personal computers (Manufacturing/durable goods) Fast food restaurants (Food services) Insurance (Finance and insurance) Supermarkets (Retail) Wireless phone service (Information)

16 Tests of Difference To test for significant differences in mean scores across the two interviewing methods for each ACSI variable in each of the industries included in the sample, independent sample t-tests were utilized To test for significant differences in parameter estimates for the structural model for each of the industries included in the sample, chi-square difference tests were utilized, with parameters constrained to equality and significant chi-square statistics indicative of significant parameter estimate differences

17 Discussion Agenda Overview: Research Questions and Findings
The American Customer Satisfaction Index (ACSI) Extant Research on Interviewing Method Differences Data and Analysis Methods Results and Findings Conclusions and Implications

18 Results and Findings Across all of the tests – which included comparisons of 36 sets of mean scores across the two interviewing methods, and 54 sets of model parameter estimates – some significant differences were observed In total, 36% of the mean scores (13 of 36) compared across the two modes exhibited significant differences. Scores skewed higher on the Internet, with 9 of 13 significant differences reflecting “better” ratings among Internet respondents (i.e. higher ratings, fewer complaints) Moreover, 39% of the model parameter estimates (21 of 54) from the structural models compared across the two methods exhibited significant differences (Two industry examples follow. All test results provided in Appendix A)

19 Example 1: Supermarket Industry Results
Telephone Internet Sig. Diff. Variable N Mean Expectations 784 79.08 790 80.24 Quality 80.43 79.43 Value 783 76.54 77.34 Satisfaction 76.38 75.59 Comp. (%) 782 10.87 788 10.53 Loyalty 76.37 786 82.60 *** Supermarket Industry Path Coefficient Tele. Internet Sig. Diff. Expect. → Quality 0.776 0.833 Quality → Value 0.528 0.629 Expect. → Value 0.196 0.111 Value → Sat. 0.444 0.481 Quality → Sat. 0.372 0.505 ** Expect. → Sat. 0.195 0.051 Sat. → Comp. -0.286 -0.308 Comp. → Loyalty 0.045 -0.016 Sat. → Loyalty 0.616 0.638 For the tests for this industry, one variable mean score of the six tested was significantly different across the two samples, while two of nine parameter estimates were significantly different *All variables scaled 0-100, worse to better rating; “Sig. Diff.” column reports significant difference between the Telephone and Internet interview samples ; * = p<.05; ** = p<.01; ***p<.001.

20 Example 2: Wireless Industry Results
Telephone Internet Sig. Diff. Variable N Mean Expectations 475 75.69 490 80.94 *** Quality 478 75.88 493 78.80 * Value 470 72.70 488 71.54 Satisfaction 71.17 492 71.20 Comp. (%) 30.95 485 21.65 ** Loyalty 473 69.31 462 74.14 Wireless Industry Path Coefficient Tele. Internet Sig. Diff. Expect. → Quality 0.775 0.56 ** Quality → Value 0.85 0.998 Expect. → Value 0.042 -0.058 Value → Sat. 0.457 0.529 Quality → Sat. 0.48 0.476 Expect. → Sat. 0.053 0.005 Sat. → Comp. -0.621 -0.601 Comp. → Loyalty -0.033 -0.037 Sat. → Loyalty 0.942 0.96 For the tests for this industry, four of the variable mean scores exhibited significant differences, with scores skewing higher (and complaint rate lower), and two of the parameter estimates exhibited significant differences *All variables scaled 0-100, worse to better rating; “Sig. Diff.” column reports significant difference between the Telephone and Internet interview samples ; * = p<.05; ** = p<.01; ***p<.001.

21 Results and Findings The above are “hard tests” of multi-method interviewing. As many projects (including ACSI) have not traded telephone-only for Internet-only interviewing, a “fairer” test is to compare the telephone interview results to the mixed-method, mixed-sample results For these tests, the results are more promising. Looking only at differences in mean scores, of the 36 sets of means compared only 11% (4 of 36) exhibited significant differences (Two industry examples follow. Full results for these tests are included in Appendix A)

22 Example 3: Mixed-Sample vs. Telephone-Only
Mixed-Sample Telephone Sig. Diff. N Mean Apparel Industry Expectations 957 83.99 475 84.14 Quality 85.12 86.33 Value 958 82.28 84.05 Satisfaction 81.26 83.16 * Comp. (%) 955 1.47 0.63 Loyalty 950 79.78 473 79.52 PC Industry 1156 83.51 556 82.94 1157 82.40 81.44 1153 82.49 553 82.35 78.81 77.78 1147 12.64 15.91 1158 74.05 557 71.76 *All variables scaled 0-100, worse to better rating; “Sig. Diff.” column reports significant difference between the Telephone and Internet interview samples ; * = p<.05; ** = p<.01; ***p<.001.

23 Discussion Agenda Overview: Research Questions and Findings
The American Customer Satisfaction Index (ACSI) Extant Research on Interviewing Method Differences Data and Analysis Methods Results and Findings Conclusions and Implications

24 Conclusions While some differences in both mean scores and model parameter estimates are exhibited when comparing telephone-only interviewing to Internet-only interviewing, the differences account for a minority in both cases The results are even more promising when comparing mean scores for telephone-only and mixed-method interviewing; only a small fraction of the comparisons are significantly different in this case

25 Implications and Future Research
These tests provide evidence for the feasibility and reliability of mixed-method sampling for consumer-oriented survey research projects For projects working with this kind of data, both means scores and model estimates appear to be relatively stable across interviewing methods However, because we examine only consumer-oriented data, those working with dissimilar types of data should perform tests similar to ours to examine the reliability of mixed-method interviewing, as results may vary Research expanding the types of data tested should help market researchers determine the feasibility of multi-method interviewing for particular client engagements

26 Appendix A: Supplemental Results and Information

27 Interview Data by Industry/Company
Companies Apparel Liz Claiborne; VF Corporation; Levi Strauss; Jones Apparel Group; Hanesbrands Personal Computers Compaq; Apple; Hewlett Packard; Dell; Acer Fast Food Wendy’s; KFC; Little Caesar Enterprises; Domino’s; Taco Bell; Pizza Hut; Burger King; McDonald’s; Papa John’s; Starbucks Insurance Farmer’s Group; Allstate; State Farm; Geico; Progressive; MetLife; Prudential; New York Life; Northwestern Mutual Life Supermarkets Publix; Winn-Dixie; Supervalu; Safeway; Wal-Mart; Kroger; Whole Foods Wireless Service Verizon; AT&T; Sprint Nextel; T-Mobile

28 Apparel and PC Industries Results
Telephone Internet Sig. Diff. N Mean Apparel Industry Expectations 475 84.14 482 83.83 Quality 86.33 83.93 * Value 84.05 483 80.54 ** Satisfaction 83.16 79.39 Comp. (%) 0.63 480 2.29 Loyalty 473 79.52 477 80.05 PC Industry 556 82.94 600 84.03 81.44 601 83.28 553 82.35 82.63 77.78 79.76 15.91 594 9.60 557 71.76 76.17 Path Coefficient Tele. Internet Sig. Diff. Apparel Industry Expect. → Quality 0.625 0.778 ** Quality → Value 0.721 0.847 Expect. → Value -0.031 -0.020 Value → Sat. 0.449 0.350 * Quality → Sat. 0.415 0.553 Expect. → Sat. 0.069 0.051 Sat. → Comp. -0.034 -0.057 Comp. → Loyalty -0.216 0.014 Sat. → Loyalty 0.772 0.908 PC Industry 0.690 0.636 0.924 0.027 -0.104 0.397 0.419 0.551 0.630 0.074 -0.041 -0.547 -0.475 -0.016 -0.002 0.971 1.155 *All variables scaled 0-100, worse to better rating; “Sig. Diff.” column reports significant difference between the Telephone and Internet interview samples ; * = p<.05; ** = p<.01; ***p<.001.

29 Fast Food and Insurance Industries Results
Telephone Internet Sig. Diff. N Mean Fast Food Industry Expectations 1150 78.45 1169 79.98 * Quality 80.32 80.59 Value 1149 80.48 1170 80.25 Satisfaction 75.65 75.24 Comp. (%) 8.09 1162 8.00 Loyalty 1145 74.44 1156 78.21 *** Insurance Industry 970 81.72 1047 82.47 973 83.81 1046 82.93 966 79.83 1039 78.40 971 79.68 77.97 976 7.48 1048 6.20 942 76.41 1006 78.11 Path Coefficient Tele. Internet Sig. Diff. Fast Food Industry Expect. → Quality 0.748 0.876 *** Quality → Value 0.694 0.647 Expect. → Value 0.115 0.197 Value → Sat. 0.350 0.425 ** Quality → Sat. 0.630 0.511 Expect. → Sat. 0.051 0.116 Sat. → Comp. -0.347 -0.376 Comp. → Loyalty 0.049 -0.019 * Sat. → Loyalty 0.825 0.797 Insurance Industry 0.672 0.710 0.703 0.820 0.212 0.120 0.379 0.521 0.527 0.481 0.076 0.007 -0.386 -0.308 -0.083 -0.037 0.813 0.929 *All variables scaled 0-100, worse to better rating; “Sig. Diff.” column reports significant difference between the Telephone and Internet interview samples ; * = p<.05; ** = p<.01; ***p<.001.

30 Mixed-Method vs. Telephone-Only Means Tests (1)
Mixed-Method Telephone Sig. Diff. N Mean Fast Food Industry Expectations 2319 79.22 1150 78.45 Quality 80.46 80.32 Value 80.36 1149 80.48 Satisfaction 2320 75.44 75.65 Comp. (%) 2311 8.05 8.09 Loyalty 2301 76.33 1145 74.44 * Insurance Industry 2017 82.11 970 81.72 2019 83.35 973 83.81 2005 79.09 966 79.83 2018 78.79 971 79.68 2024 6.82 976 7.48 1948 77.29 942 76.41 *All variables scaled 0-100, worse to better rating; “Sig. Diff.” column reports significant difference between the Telephone and Internet interview samples ; * = p<.05; ** = p<.01; ***p<.001.

31 Mixed-Method vs. Telephone-Only Means Tests (2)
Mixed-Method Telephone Sig. Diff. N Mean Supermarket Industry Expectations 1574 79.66 784 79.08 Quality 79.93 80.43 Value 1573 76.94 783 76.54 Satisfaction 75.98 76.38 Comp. (%) 1570 10.70 782 10.87 Loyalty 1568 79.49 76.37 ** Wireless Industry 965 78.36 475 75.69 * 971 77.36 478 75.88 958 72.11 470 72.70 970 71.19 71.17 960 26.25 30.95 935 71.70 473 69.31 *All variables scaled 0-100, worse to better rating; “Sig. Diff.” column reports significant difference between the Telephone and Internet interview samples ; * = p<.05; ** = p<.01; ***p<.001.


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