Bidirectional technological spillover in the Chinese star-rated hotel sector: An empirical investigation

Walheer, Barnabé; Zhang, Linjia; Luo, Yingchan

doi:10.1016/j.econmod.2019.06.013

Cited by 13 publications

(10 citation statements)

References 52 publications

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“…Studies in hospitality have demonstrated that customers' positive evaluations of travel website service quality can spill over to satisfactory evaluations of hotel service quality (Yang et al, 2010). Meanwhile, spillover effects are highly important in the accommodation industry; such impacts have been examined between different hotel types, namely, in terms of spillover from high-end to lowend hotels (Walheer et al, 2020). However, spillover between hotels and other accommodation types has yet to be considered.…”

Section: Theoretical Fundamentals: Cooperation-competition Theorymentioning

confidence: 99%

Do the flipped impacts of hotels matter to the popularity of Airbnb?

Shi

et al. 2021

IJCHM

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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.

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Section: Theoretical Fundamentals: Cooperation-competition Theorymentioning

confidence: 99%

Do the flipped impacts of hotels matter to the popularity of Airbnb?

Shi

et al. 2021

IJCHM

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“…Although most hotel industry efficiency studies are based on the hypothesis of homogeneity, some studies, such as those by Assaf et al (2010) and Bernini and Guizzardi (2015), use the meta-frontier concept (O’Donnell et al, 2008) to address the possible differences between various groups of hotels. Walheer et al (2019) extend the concept of meta-frontier to study the performance of the hotel industry in China, while considering both the number of stars and the multiservice nature of hotels. Other authors, such as Z.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Heterogeneity of Resources and Performance in the Hotel Industry

Arbelo

Arbelo-Pérez

Pérez-Gómez

2020

Journal of Hospitality & Tourism Research

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Resource heterogeneity is a key aspect of one of the most important theories of strategic management: the resource-based view of the firm. This theory suggests that the performance effects of a firm’s strategy depend on the firm’s individual resources and capabilities and the setting within which it is operating. In this article, we argue that the current methods for measuring hotel performance and its determinants may be inconsistent with this theory. To measure efficiency, hotels should be viewed as heterogeneous firms, and the relationships between determinants and performance must be assessed for each individual hotel rather than as an average across hotels. Accordingly, we use a random-effect Bayesian stochastic frontier model to estimate the profit frontier and the effect function of the inefficiency for each hotel. The results indicate that hotels tend to choose strategies based on the heterogeneous resources that maximize their performance in their individual statuses.

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“…The number of employees reflects the core inputs of hotels, which indicate the capacity of hotels to offer all the services (Assaf & Cvelbar, 2010; Roh & Choi, 2010; Walheer & Zhang, 2018). Total fixed assets represent the capital that an hotel can use for its daily operation and future development (Barros, 2005; Walheer et al, 2020). Regarding the outputs, three kinds of hotel revenues are selected: rooms revenue, catering revenue, and other revenue.…”

Section: Datamentioning

confidence: 99%

“…In China, star-rated hotels represent the main type of accommodation for tourists and have an important impact on the development of the hotel sector as well as on the development of tourism. Star-rated hotels are facing intense competition due to the overall slowing down of macroeconomic growth, the environmental impact of controlling public funds consumption and opposing waste, and so on (Walheer et al, 2020; Walheer & Zhang, 2018). In this context, efficiency optimization and productivity evaluation of star-rated hotels have received a lot of attention from scholars (Assaf & Josiassen, 2016; Assaf & Tsionas, 2019).…”

Section: Introductionmentioning

confidence: 99%

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The Nature of Technological Change in the Chinese Hotel Sector

Peypoch

Song

Zhang

2020

Journal of Hospitality & Tourism Research

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This article investigates the role of technological change in the Chinese hotel sector over the period 2005 to 2015. The analysis is conducted at the provincial level and on the star-rating hotel basis. A three-step approach is adopted. First, the Malmquist productivity index and its decomposition into efficiency and technological change is estimated. Second, the significance of each component is statistically tested. Third, the technological change is decomposed to analyze the Hicks neutrality assumption. The findings show that the Chinese hotel sector experienced an overall productivity growth, which is mainly and significantly driven by a technological progress. In most of the cases, the technological change is not neutral, and input and output biases are characterized.

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Bidirectional technological spillover in the Chinese star-rated hotel sector: An empirical investigation

Cited by 13 publications

References 52 publications

Do the flipped impacts of hotels matter to the popularity of Airbnb?

Do the flipped impacts of hotels matter to the popularity of Airbnb?

Heterogeneity of Resources and Performance in the Hotel Industry

The Nature of Technological Change in the Chinese Hotel Sector

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