业务
背景(考古学)
服务补救
独创性
服务(商务)
营销
服务提供商
公共关系
定性研究
服务质量
社会学
政治学
社会科学
生物
古生物学
作者
Elvira Bolat,Julie Robson,Jason Sit,Shannon Birch-Chapman,Samreen Ashraf,Juliet Memery,Caroline Jackson
出处
期刊:Qualitative Market Research: An International Journal
[Emerald Publishing Limited]
日期:2020-01-20
卷期号:23 (4): 725-746
被引量:6
标识
DOI:10.1108/qmr-12-2017-0187
摘要
Purpose This paper aims to understand consumers’ response to the trust repair mechanisms adopted by corporate brands in a service sector context following prominent trust damaging organizational transgressions. Design/methodology/approach Adopting a qualitative approach, six focus group discussions are used to investigate three high-profile consumer trust erosion cases within the service sector. Findings Consumer trust varies by context. Despite the severity of trust damage, corporate brands can recover trust towards their brands amongst consumers not directly affected by transgressions. Not all trust repair mechanisms are equally applicable to all service contexts, and re-branding could be used as a trust repair mechanism. Corporate brands in the service sector should focus on sense-making, relational approaches and transparency. Orchestration of trust repair mechanisms needs to be integrated within the trust rehabilitation processes. Research limitations/implications This study illustrates it is important to reconsider trust repair processes to accommodate context and integrate post-transgression consumer research. Practical implications Successful corporate brand rehabilitation of consumer trust requires examination of the trustworthiness dimensions consumers express before and after the transgression to select the most appropriate trust repair mechanisms. Findings suggest organizations also have preventative trust repair management programs. Originality/value This research is the first to empirically apply the conceptual framework of Bachmann et al. (2015) to explore consumer responses to the trust repair mechanisms adopted by corporate brands by context.
科研通智能强力驱动
Strongly Powered by AbleSci AI