<p>Despite the increasing occurrence of privacy breaches involving smart service systems, organizations lack evidence-based guidance on which trust repair strategies work, particularly beyond apologies or compensation. This study systematically evaluates the relative effectiveness of three verbal trust repair strategies (apology, denial, reticence) and three substantive strategies (compensation, regulation, third-party involvement), applied individually and in combination. We also examine the moderating role of violation type (competence-based vs. integrity-based) on repair strategy effectiveness. We conducted a scenario-based experiment using policy-capturing methodology that we assessed with a fixed-effects regression model for panel data. Seventy-seven long-term smart home users assessed post-repair trust following simulated privacy breaches and the subsequent application of diverse repair strategies. Our results identify apology as the most effective verbal strategy, while regulation is the most effective substantive strategy. Combinations of verbal and substantive strategies generally outperform isolated strategies, except when third-party involvement is included, which shows limited benefit. Unexpectedly, we found that the violation type did not significantly moderate the effectiveness of any of the examined trust repair strategies. This study contributes to research by (1) providing a comprehensive comparison of verbal and substantive trust repair strategies in a unified design, (2) demonstrating how trust repair strategy combinations perform synergistically or in tension, (3) challenging the prevailing assumption of the competence-integrity violation type distinction for trust repair strategy effectiveness, and (4) advancing understanding of trust repair for the high-vulnerability context of smart service systems, where the intersection of digital and physical risks amplifies the consequences of privacy breaches for customers.</p>

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Selecting trust repair strategies: The case of privacy breaches in smart service systems

  • Björn Konopka,
  • Kay Hönemann,
  • Ning Yang,
  • Jason Bennett Thatcher,
  • Manuel Wiesche

摘要

Despite the increasing occurrence of privacy breaches involving smart service systems, organizations lack evidence-based guidance on which trust repair strategies work, particularly beyond apologies or compensation. This study systematically evaluates the relative effectiveness of three verbal trust repair strategies (apology, denial, reticence) and three substantive strategies (compensation, regulation, third-party involvement), applied individually and in combination. We also examine the moderating role of violation type (competence-based vs. integrity-based) on repair strategy effectiveness. We conducted a scenario-based experiment using policy-capturing methodology that we assessed with a fixed-effects regression model for panel data. Seventy-seven long-term smart home users assessed post-repair trust following simulated privacy breaches and the subsequent application of diverse repair strategies. Our results identify apology as the most effective verbal strategy, while regulation is the most effective substantive strategy. Combinations of verbal and substantive strategies generally outperform isolated strategies, except when third-party involvement is included, which shows limited benefit. Unexpectedly, we found that the violation type did not significantly moderate the effectiveness of any of the examined trust repair strategies. This study contributes to research by (1) providing a comprehensive comparison of verbal and substantive trust repair strategies in a unified design, (2) demonstrating how trust repair strategy combinations perform synergistically or in tension, (3) challenging the prevailing assumption of the competence-integrity violation type distinction for trust repair strategy effectiveness, and (4) advancing understanding of trust repair for the high-vulnerability context of smart service systems, where the intersection of digital and physical risks amplifies the consequences of privacy breaches for customers.