Purpose Leader–member exchange (LMX) theory is particularly relevant to the hospitality and tourism industry due to its labor-intensive and service-focused nature. However, the hospitality literature regarding the impact of LMX on its various outcomes have inconsistent results. A holistic review of LMX studies is nonexistent in the current literature. Thus, the purpose of this study is to use a meta approach to quantitatively summarize and examine the relationship between LMX and its outcomes in the hospitality and tourism literature. Design/methodology/approach A total of 89 individual observations from 36 studies conducted between 1997 and 2018 were identified. A Bayesian random effect model was introduced into the hospitality and tourism literature for the first time to implement the meta-analysis. Findings The results suggest significant differences in the impact of LMX on various groups of outcomes. LMX has the strongest impact on firms’ practice-related outcomes, such as organizational justice and employee empowerment. Few moderators are identified on the impact of LMX, such as LMX measure, culture, industry sector and statistical method. Practical implications Findings yielded several recommendations for both hospitality researchers and organizations in developing LMX related studies, as well as managing employees. Originality/value This study is the first Bayesian meta-analysis in the hospitality and tourism literature; it complements LMX theory by linking it to cognitive appraisal theory. Specific characteristics of LMX in the hospitality and tourism industry, such as the measurement of LMX and the effect of industry sector, are also identified.

Purpose By building on cooperation–competition theory, this study aims to investigate the multidimensional flipped effects of neighborhood hotels on Airbnb listings’ popularity, examining the degree to which such impacts are influenced by hotel types and geographical areas. Design/methodology/approach This study explores the interdependent and competitive relationship between neighborhood hotels and Airbnb from the perspective of effects on Airbnb listings’ popularity by exploring a data set covering 10,492 Airbnb listings and 2,691 hotels from Ctrip. Findings Results reveal that neighborhood hotels’ number of reviews, review ratings and prices each have positive spillover effects on Airbnb listings’ popularity, while quality assurance labels and negative review topic sentiments exert competitive effects on Airbnb popularity. Moreover, the number of budget chain hotels and high-star hotels have positive and negative effects on Airbnb popularity, respectively. Geographical areas also have a moderating effect on the relationship between various hotel-related influencing factors and Airbnb. Practical implications This study can offer hotel managers and Airbnb operators a clearer understanding of these businesses’ coexisting relationship. Findings can also provide Airbnb-specific guidelines for practitioners in terms of site selection, promotional features and development strategies for Airbnb listings. Originality/value This study establishes a cooperation–competition relationship model between hotels and Airbnb and considers the flipped effects of hotels on Airbnb for the first time. It expands previous studies by considering the multidimensional effects of hotels on Airbnb listings’ popularity and by examining the influences of hotel types and geographical areas on hotels’ impacts on Airbnb.

This study investigates the motivation configuration of bluxury tourism behavior. According to complexity theory and push and pull motivation theory, we establish a framework of complex configuration conditions, including push forces, pull forces, and constraints that lead to bluxury tourism. Based on fuzzy-set qualitative comparative analysis, we identified seven main motivation configurations of bluxury tourism behavior covering three core factors: physical factors, seeking/exploration in push forces, and intangible factors in pull forces. In addition, combinations of constraints in the configuration demonstrate various paths leading to bluxury tourism behavior. These findings provide unique insight into bluxury tourism participation.

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