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Last Published February 19, 2026 07:45 AM February 20, 2026 09:20 AM
Experimental Design (Public) We employ a between-subjects design. Respondents are randomly assigned to one of seven treatment arms that result from the combination of three treatment dimensions: 1) No Framing // No Testimonial // N=300 2) Benefits Framing // No Testimonial // N=150 3) Costs Framing // No Testimonial // N=150 4) Benefits Framing // Same gender Testimonial // N=100 5) Benefits Framing // Different gender Testimonial // N=100 6) Costs Framing // Same gender Testimonial // N=100 7) Costs Framing // Different gender Testimonial // N=100 The control group is oversampled (N=300) relative to the individual testimonial arms (N=100 each) to provide sufficient statistical power for pairwise comparisons between each treatment arm and the control, as well as for pooled comparisons of all benefit arms versus all cost arms versus control. We specify three main analyses, corresponding to the three treatment dimensions: 1) Effect of Content Framing We test whether benefit or cost framing increases willingness to participate in internet banking training relative to the control group. Specifically, we compare: (a) pooled benefit arms (Arms 2, 4, 5; N=350) vs. control (Arm 1; N=300), (b) pooled cost arms (Arms 3, 6, 7; N=350) vs. control, and (c) non-testimonial benefit arm (Arm 2; N=150) vs. non-testimonial cost arm (Arm 3; N=150) vs. control (Arm 1; N=300). We estimate OLS, logit, and probit regression models of the primary and secondary outcomes on treatment indicators. 2) Effect of Testimonials We test whether the addition of a testimonial increases the effect of benefit and cost framings. We compare: (a) testimonial benefit arms (Arms 4+5; N=200) vs. non-testimonial benefit arm (Arm 2; N=150), and (b) testimonial cost arms (Arms 6+7; N=200) vs. non-testimonial cost arm (Arm 3; N=150). 3) Effect of Gender Matching We test whether same-gender testimonials are more effective than different-gender testimonials. We compare: (a) all same-gender arms (Arms 4+6; N=200) vs. all different-gender arms (Arms 5+7; N=200), (b) same-gender benefit arm (Arm 4; N=100) vs. different-gender benefit arm (Arm 5; N=100), and (c) same-gender cost arm (Arm 6; N=100) vs. different-gender cost arm (Arm 7; N=100). The survey follows a structured sequence of sections: 1. Screening: Age (numeric free text), frequency of internet banking use (5-point scale: never to always), German language proficiency (6-point scale), and gender. Respondents who use internet banking “always” or “frequently”, respondents with insufficient German language skills, and respondents that do not state their gender are screened out, as the intervention targets non- or infrequent users. Respondents reporting diverse/non-binary gender are assigned to the control group since they cannot be randomized into the gender-specific treatment arms. 2. Scenario presentation: Respondents view the randomized invitation flyer from their bank, adapted to the assigned treatment condition. 3. Outcome measurement: Primary and secondary outcome items are collected (see above). 4. Demographics: Highest educational attainment (6 categories), employment status (6 categories), and monthly net household income (6 brackets). 5. Internet banking barriers and attitudes: Reasons for not using internet banking more frequently (multiple choice, max. 3, randomized order), household financial responsibility, technology openness, and general risk attitude. 6. Banking activity: Number of monthly transfers, primary banking channel, distance to nearest branch, frequency of branch visits, and experience with branch closures. 7. Training preferences: Preferred training format (online video, at home with guidance from a trusted person, or in-branch with other customers) and an open-ended question on conditions for regular internet banking use. 8. Information provision: Respondents are presented with a clickable link to a PDF document containing real-world internet banking training resources (e.g., VHS adult education courses). Whether the respondent clicks on this link is recorded as a secondary outcome. We employ a between-subjects design. Respondents are randomly assigned to one of seven treatment arms that result from the combination of three treatment dimensions: 1) No Framing // No Testimonial // N=300 2) Benefits Framing // No Testimonial // N=150 3) Costs Framing // No Testimonial // N=150 4) Benefits Framing // Same gender Testimonial // N=100 5) Benefits Framing // Different gender Testimonial // N=100 6) Costs Framing // Same gender Testimonial // N=100 7) Costs Framing // Different gender Testimonial // N=100 The control group is oversampled (N=300) relative to the individual testimonial arms (N=100 each) to provide sufficient statistical power for pairwise comparisons between each treatment arm and the control, as well as for pooled comparisons of all benefit arms versus all cost arms versus control. We specify three main analyses, corresponding to the three treatment dimensions: 1) Effect of Content Framing We test whether benefit or cost framing increases willingness to participate in internet banking training relative to the control group. Specifically, we compare: (a) pooled benefit arms (Arms 2, 4, 5; N=350) vs. control (Arm 1; N=300), (b) pooled cost arms (Arms 3, 6, 7; N=350) vs. control, and (c) non-testimonial benefit arm (Arm 2; N=150) vs. non-testimonial cost arm (Arm 3; N=150) vs. control (Arm 1; N=300). We estimate OLS, logit, and probit regression models of the primary and secondary outcomes on treatment indicators. 2) Effect of Testimonials We test whether the addition of a testimonial increases the effect of benefit and cost framings. We compare: (a) testimonial benefit arms (Arms 4+5; N=200) vs. non-testimonial benefit arm (Arm 2; N=150), and (b) testimonial cost arms (Arms 6+7; N=200) vs. non-testimonial cost arm (Arm 3; N=150). 3) Effect of Gender Matching We test whether same-gender testimonials are more effective than different-gender testimonials. We compare: (a) all same-gender arms (Arms 4+6; N=200) vs. all different-gender arms (Arms 5+7; N=200), (b) same-gender benefit arm (Arm 4; N=100) vs. different-gender benefit arm (Arm 5; N=100), and (c) same-gender cost arm (Arm 6; N=100) vs. different-gender cost arm (Arm 7; N=100). The survey follows a structured sequence of sections: 1. Screening: Age (numeric free text), frequency of internet banking use (5-point scale: never to always), German language proficiency (6-point scale), and gender. Respondents who use internet banking “always” or “frequently”, respondents with insufficient German language skills, and respondents that do not state their gender are screened out, as the intervention targets non- or infrequent users. Respondents reporting diverse/non-binary gender are assigned to the control group since they cannot be randomized into the gender-specific treatment arms. 2. Scenario presentation: Respondents view the randomized invitation flyer from their bank, adapted to the assigned treatment condition. 3. Outcome measurement: Primary and secondary outcome items are collected (see above). 4. Demographics: Highest educational attainment (6 categories), employment status (6 categories), and monthly net household income (6 brackets). 5. Internet banking barriers and attitudes: Reasons for not using internet banking more frequently (multiple choice, max. 3, randomized order), household financial responsibility, technology openness, and general risk attitude. 6. Banking activity: Number of monthly transfers, primary banking channel, distance to nearest branch, frequency of branch visits, and experience with branch closures. 7. Training preferences: Preferred training format (online video, at home with guidance from a trusted person, or in-branch with other customers) and an open-ended question on conditions for regular internet banking use. 8. Information provision: Respondents are presented with a clickable link to a government-sponsored website containing information on internet banking. Whether the respondent clicks on this link is recorded as a secondary outcome.
Planned Number of Observations The target sample consists of around 1,000 completed responses from German respondents aged 50-75 who do not use internet banking frequently (i.e., who report using internet banking “never,” “seldom,” or “occasionally”). Respondents are recruited through the online panel provider Bilendi with demographic targeting for age. The target sample consists of around 1,000 completed responses from German respondents aged 50-75 who do not use internet banking frequently (i.e., who report using internet banking “never,” “seldom,” or “occasionally”). Respondents are recruited through the online panel provider Bilendi with demographic targeting for age. While we target 1,000 respondents in total, bilendi will oversample up to 10%.
Secondary Outcomes (End Points) The secondary outcomes capture mechanisms through which the treatments may affect training take-up intentions. All items are measured on a 5-point Likert scale (1 = “Strongly disagree” to 5 = “Strongly agree”) unless otherwise noted: 1) "I consider the practical utility of online banking to be high." 2) "I consider the effort of using online banking to be high." 3) "I consider the risk of online banking to be high." 4) "I consider the risk of NOT using online banking to be high." Peer recommendation and perceived obligation: 5) "I would recommend this training offer to friends or acquaintances." 6) "I should take the time to participate in such a training." Mechanism variables (testimonial and framing channels): 7) "The offered training is specifically tailored to people like me." 8) "I have the necessary skills to successfully participate in the training." 9) "I consider the training offer to be trustworthy." Bank perception: 10) "The bank seems to genuinely care about its customers’ needs." Information demand: 11) Respondent clicked on the link to the PDF document with real-world internet banking training resources (e.g., VHS adult education courses). Binary (0 = did not click, 1 = clicked) The secondary outcomes capture mechanisms through which the treatments may affect training take-up intentions. All items are measured on a 5-point Likert scale (1 = “Strongly disagree” to 5 = “Strongly agree”) unless otherwise noted: 1) "I consider the practical utility of online banking to be high." 2) "I consider the effort of using online banking to be high." 3) "I consider the risk of online banking to be high." 4) "I consider the risk of NOT using online banking to be high." Peer recommendation and perceived obligation: 5) "I would recommend this training offer to friends or acquaintances." 6) "I should take the time to participate in such a training." Mechanism variables (testimonial and framing channels): 7) "The offered training is specifically tailored to people like me." 8) "I have the necessary skills to successfully participate in the training." 9) "I consider the training offer to be trustworthy." Bank perception: 10) "The bank seems to genuinely care about its customers’ needs." Information demand: 11) Respondent clicked on the link (embedded on the final survey page) to a government-sponsored website containing detailed internet banking information. Binary (0 = did not click, 1 = clicked)
Secondary Outcomes (Explanation) 1) captures perceived usefulness (benefit framing channel). 2) and 3) capture perceived barriers (cost framing channel). 2) and 3) are reverse-coded such that higher values indicate lower perceived barriers for analyses when we potentially construct a net benefit index. 4) captures the perceived risk of not adopting internet banking, which relates to awareness of potential costs from relying solely on branch-based banking (e.g., branch closures, limited availability). 5) captures the potential for peer diffusion of the training. 6) captures the extent to which the invitation creates a sense of obligation or normative pressure to engage with the training. 7) 8) 9) capture potential mechanisms of testimonials and gender matching: 7) captures whether the testimonial increases the perceived fit of the training; 8) captures whether addressing barriers (cost framing) or showcasing success stories (testimonials) increases perceived self-efficacy; 9) captures whether the invitation and/or testimonial increases trust in the training offer. 10) captures whether the different framings affect the perception of the bank as customer-oriented, which may in turn influence willingness to engage with the training offer. 11) is a binary indicator of whether the respondent clicked on the link to a PDF document containing real-world internet banking training resources provided at the end of the survey. This behavioral outcome captures actual information-seeking behavior that is a meaningful precursor to real-world training participation. The link directs respondents to genuine internet banking training information (e.g., from adult education centers / "Volkshochschulen"), ensuring that the measured behavior reflects real interest. 1) captures perceived usefulness (benefit framing channel). 2) and 3) capture perceived barriers (cost framing channel). 2) and 3) are reverse-coded such that higher values indicate lower perceived barriers for analyses when we potentially construct a net benefit index. 4) captures the perceived risk of not adopting internet banking, which relates to awareness of potential costs from relying solely on branch-based banking (e.g., branch closures, limited availability). 5) captures the potential for peer diffusion of the training. 6) captures the extent to which the invitation creates a sense of obligation or normative pressure to engage with the training. 7) 8) 9) capture potential mechanisms of testimonials and gender matching: 7) captures whether the testimonial increases the perceived fit of the training; 8) captures whether addressing barriers (cost framing) or showcasing success stories (testimonials) increases perceived self-efficacy; 9) captures whether the invitation and/or testimonial increases trust in the training offer. 10) captures whether the different framings affect the perception of the bank as customer-oriented, which may in turn influence willingness to engage with the training offer. 11) is a binary indicator of whether the respondent clicked on the link to a a government-sponsored website containing detailed internet banking information. The link is provided at the end of the survey. This behavioral outcome captures actual information-seeking behavior that is a meaningful precursor to real-world training participation.
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