Purpose This study aims to explore how the local tour guides (LTGs) operate through the sharing economy platform. This study explores how LTGs have responded to the COVID-19 pandemic restrictions using self-efficacy and other resources to improve resilience and performance. This study also delineates the working mechanisms of peer-to-peer (P2P) platform-enabled, dynamic capability building processes, in the tourism sharing economy. Design/methodology/approach This research adopted an interpretive approach to understand the focal phenomenon using two types of data. A total of 40 semi-structured interviews with LTGs and 26,478 online tourist reviews from tour guide service participants’ before and during the COVID-19 pandemic were used. Findings The findings of this study revealed that LTGs used sharing economy platforms to arrange flexible tour guide services. Resilience emerged through dynamic capability that addressed contextual factors in real time. LTGs coordinated different resources and customers during a time of uncertainty. Different sources of self-efficacy and types of dynamic capability were identified. The interplay between LTGs’ self-efficacy and dynamic capability was also delineated. Practical implications The findings provide guidance for LTGs on P2P platforms and other sharing economy sectors on how diverse resources enabled by the sharing economy can enhance resilience during times of uncertainty. LTGs that engage with contextual information and are dynamic can adopt itineraries and services that will benefit tourists and their business. Originality/value This study contributes to the sharing economy literature by theorizing the working flow that enables LTGs to exert self-efficacy and leverage dynamic capability on P2P platforms. This study also contributes by linking resilience to contextual factors in real time. The outcomes provide guidance for LTGs to remain competitive and establish resilience in uncertain environments.

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Purpose The purpose of this paper is to analyze the implicit prices of hotel attributes in different time periods and different markets. Design/methodology/approach With data from the travel meta-search engine, this paper chose 3- to 5-star hotels in Beijing’s central business district and use hedonic price models. Findings The results suggest that the attributes with significant implicit prices differ in different time periods; the same attributes with different implicit prices in different time periods; the same attributes with different implicit prices in different market segments. Originality/value This study may help to explain the different findings on the relationship between the attributes and room rates of Chinese star-rated hotels in different time periods, and will be useful in both revenue optimization efforts and the design of new hotels projects.