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Drawing on Schumpeter’s theory of innovation and stereotype content model, this study aims to arrive at an integrated model that relates destination innovation type, destination innovativeness and revisit intention to uncover more about the drivers and outcomes of destination innovativeness from a consumer-centric perspective.

Three studies, including content analysis of news media, an onsite survey and an online survey in Chinese special featured towns, were conducted.

This study develops a consumer-centric destination innovation measure. The results reveal that input innovation and product innovation positively influence revisit intention through the serial mediation of destination innovativeness and perceived competence.

As the data was collected from tourists in China, any generalization of the results to other regions should be made with caution; accordingly, replication is needed to test the proposed model in different cultural contexts. Second, during the onsite data collection period, special featured town destinations were still recovering from the COVID-19 pandemic, which may have affected the perceptions of tourists. Third, the second round of data was collected using an online survey, which may have introduced bias due to a potential lack of representativeness. Fourth, some potential missing variables could also influence the links among innovation, destination innovativeness and revisit intention.

This study presents the first empirical test of the impact of innovation type and innovativeness on tourists’ response to tourism destinations. The results of this study could guide destinations to deliver more effective consumer-centric innovations to generate competitiveness.

本研究基于熊彼特的创新理论和刻板印象内容模型构建并且实证检验了目的地创新对游客重游意愿的中介影响机制, 旨在从消费者视角探究目的地创新性的驱动因素和影响结果。

本研究通过收集研究主题相关新闻稿件并进行内容分析获得高度情境化的测量问项, 并通过开展两轮问卷调查收集的数据对研究模型进行了检验。共回收有效问卷598份。

本研究开发了以消费者为中心的目的地创新量表。研究结果表明, 目的地投入创新和产品创新可能会影响游客对目的地创新性和感知能力的评价, 进而提升他们的重游意愿。并且, 研究发现目的地创新性和感知能力发挥了连续中介作用。

本研究从消费者感知角度出发, 揭示了目的地创新对游客重游意愿的影响作用及其内在机制, 为旅游目的地创新提供了启示。

Basándose en la teoría de la innovación de Schumpeter y en el modelo de contenido de los estereotipos, este estudio tiene como objetivo llegar a un modelo integrado que relacione el tipo de innovación del destino, capacidad de innovación del destino e intención de revisita del destino, para descubrir más acerca de los impulsores y resultados de la innovación desde una perspectiva centrada en el consumidor.

Se han llevado a cabo tres estudios entre los que se han incluido, el análisis del contenido de los medios de comunicación informativos, encuesta «in situ», además de una encuesta en línea en pueblos chinos que destacan por sus características especiales.

Esta investigación desarrolla una medición de la innovación del destino desde una perspectiva centrada en el consumidor. Los resultados revelan que la innovación en los recursos y la innovación del producto, influyen positivamente en la intención de revisitar a través de la mediación en serie de la innovación del destino y la competencia percibida.

Este trabajo presenta la primera prueba empírica del impacto del tipo de innovación, así como de innovaciones sobre la respuesta de los turistas a los destinos turísticos. Los resultados de este estudio podrían guiar a los gestores de los destinos en el ofrecimiento de innovaciones más efectivas centradas en el consumidor con el fin de generar competitividad.

This paper aims to compare the forecasting performance of different models with and without big data predictors from search engines and social media.

Using daily tourist arrival data to Mount Longhu, China in 2018 and 2019, the authors estimated ARMA, ARMAX, Markov-switching auto-regression (MSAR), lasso model, elastic net model and post-lasso and post-elastic net models to conduct one- to seven-days-ahead forecasting. Search engine data and social media data from WeChat, Douyin and Weibo were incorporated to improve forecasting accuracy.

Results show that search engine data can substantially reduce forecasting error, whereas social media data has very limited value. Compared to the ARMAX/MSAR model without big data predictors, the corresponding post-lasso model reduced forecasting error by 39.29% based on mean square percentage error, 33.95% based on root mean square percentage error, 46.96% based on root mean squared error and 45.67% based on mean absolute scaled error.

Results highlight the importance of incorporating big data predictors into daily demand forecasting for tourism attractions.

This study represents a pioneering attempt to apply the regularized regression (e.g. lasso model and elastic net) in tourism forecasting and to explore various daily big data indicators across platforms as predictors.

With the prevalence of the sharing economy phenomenon, there are an increasing number of hosts on Airbnb who manage more than one listing. Managing more listings likely makes hosts more seasoned in terms of serving guests, but it may undermine host quality due to hosts’ constrained capability. This paper aims to examine the effects of host quality attributes and the number of listings per host on the reservation performance of these listings.

Using a large-scale but granular data set of 5,805 active listings of 4,608 Airbnb hosts in Austin, Texas, this study estimates the effects of host attributes (host quality and listing quantity) on the performance of the hosts’ Airbnb listings through a blend of regression models.

This study evidences that host quality attributes significantly influence listing performance through cue-based trust. In addition, this study finds a “trade-off” between host quality and the quantity of their listings. As the number of listings managed by a host increases, the performance effects of host quality diminish.

The business implications of this study include the suggestion that sharing economy businesses such as Airbnb should sustain service quality through incentivizing hosts to improve host quality while balancing the quantity of listings managed.

This study contributes to the literature through its meaningful theoretical extension in the sharing economy context and unique data-driven insights enabled by an analytical approach. It addresses the critical but less researched topic of host quality and listing quantity and generates important practical business and policy implications.

The purpose of this study is to examine the psychological factors that motivate travelers to consider reusing Airbnb.

This study proposes and tests an integrative model that synthesizes the Theory of Planned Behavior (TPB), Prospect Theory (PT) and other Airbnb-relevant constructs (unique experience expectation, familiarity and electronic word of mouth) as the primary determinants of the Airbnb repurchase intention using an structural equation model (SEM) approach.

Both attitude and subject norms are significant determinants of repurchase intention, whereas perceived behavioral control is not. In addition, perceived value and risk have only direct significant impacts on attitude and, in turn, indirectly affect repurchase intention. Unique experience expectation, familiarity and electronic word of mouth exert direct and indirect influences on repurchase intention.

This study extends the body of knowledge by integrating TPB and PT to investigate consumer repurchase intention in Airbnb, which provides a theoretical baseline and serves as a starting point for exploring the structural relationships of Airbnb and the sharing economy.

Airbnb should place more emphasis on value packages and authentic/unique travel experience to retain and attract more travelers. More safety/security programs should be put in place and clearly communicated to reduce the perceived risks. In addition, Airbnb may publicize positive word of mouth and introduce and expand familiarity programs to incentivize Airbnb travelers.

This study explores the psychological reasons why travelers will re-patronize Airbnb, providing insights into the motives of Airbnb travelers. A clear understanding of Airbnb travelers’ repurchase intention will facilitate to develop effective strategies for Airbnb to induce positive repurchase behaviors.

This study aims to develop a comprehensive framework for assessing servicescape of cruise tourism and provides practical suggestions to improve the perception of Chinese tourists toward cruise servicescape.

A multistage mixed-method design was used in the sequence of in-depth interviews (n = 18), expert panel (n = 5), on-site survey (n = 317) and online survey (n = 300). Grounded theory, exploratory factor analysis and confirmatory factor analysis were used to assess cruise tourism servicescape.

The cruise tourism servicescape construct was identified with six dimensions: facilities and décor, natural scenery, onshore excursions, onboard entertainment, social interactions and dining services. These dimensions were in the order of importance, as perceived by Chinese tourists.

Cruise lines operating large ships can be more attractive to Chinese consumers than luxury cruise lines operating smaller vessels. Cruise operators can enhance perceived servicescape by integrating natural and built environments, such as air, sea and on-shore tours. Services provided by foreign crew members may serve as a strong selling point for Chinese tourists. Consumer-to-consumer activities may be introduced into the Chinese market. Cruise operators may also provide quality meal service in terms of variety, quality and flexibility.

Considering that minimal research has been conducted on cruise servicescape scale development, this study serves as the first empirical research effort in this regard. The findings also identify the specific needs of Chinese tourists, which is a fast-growing market in the cruise industry.

The purpose of this paper is to evaluate the usefulness of the TANGSERV (tangible quality) scale by examining the effect of tangible quality constructs on restaurant patrons' affect and behavioral intentions.

A model was proposed based on the literature of tangible quality in service, which posits that tangible quality leads to affective quality and they both have positive impact on customer re‐patronage intentions. Subsequently, an empirical study in Turkey's casual restaurants was conducted to test the aforementioned model.

The food and service construct and accessibility construct of tangible quality exhibited positive impact on the affect towards restaurants, which in turn influenced re‐patronage intention for restaurants. Affect was a strong mediator, facilitating the relationship between tangible quality and behavior.

Restaurant operators should focus their efforts on ensuring an interesting variety of food and drink offerings presented in interesting and unique ways. They should also ensure that the type of service delivered is consistent from one visit to the next. Cultivating positive feelings toward the brand name is a good approach to increasing re‐patronage intentions. In addition, careful consideration and research should be completed prior to selecting a restaurant location and provision of convenient parking.

The study helps restaurant managers select the most important tangible restaurant feature for consumers and guide the investment resources to address customer expectations.

After the COVID-19 outbreak began, travel demand dropped sharply and the potential impact of COVID-19 on sharing accommodations appears to be significant. Thus, it would be meaningful to investigate how travelers have changed their perceptions of staying at sharing accommodations in the wake of the coronavirus pandemic. The purpose of this research was to compare consumers' perceived risks of using sharing accommodations, such as Airbnb, before and during the coronavirus pandemic.

Paired sample t-tests were applied, using two surveys collected in 2017 (pre-pandemic) and 2020 (peri-pandemic). The effects of stress levels from COVID-19 and previous experience with sharing lodging services on risk perception changes were also examined.

Consumers showed higher social, physical, performance and convenience risk perceptions during the pandemic. Not surprisingly, those respondents who were more conscious of the pandemic in terms of concern and anxiety had higher changes in their risk perceptions. In addition, changes in risk perception differed by consumers' usage experience.

The results of this study add to the body of knowledge about consumers' risk perceptions of the sharing economy, particularly in connection with a huge disruption such as the COVID-19 pandemic.

The modernization of China’s economy is an integral part of Chinese-style modernization. According to the principle of unifying theoretical, historical and practical logic, theoretically explaining the modernization of China’s economy is both a political necessity and a higher scientific requirement.

Following this evolutionary line – from modes of production to the general economic development mechanism and then to patterns of economic operation and development – this paper employs the principal contradiction analysis method to offer an interpretation of China’s economic modernization from the broad Marxist political economy perspective.

In economic terms, “get organized” primarily refers to the development and mutual promotion of team-based and market-based division of labor organizations, as discussed by Karl Marx. “Get organized” (specifically the development of team-based division of labor organizations) acts as the engine of China’s economic modernization and serves as the historical logical starting point. Division of labor is the theoretical logical starting point for interpreting China’s economic modernization. The two of them are congruent, achieving the unity of theoretical and historical logic at the starting point. The development and mutual promotion of these “two types of division of labor” inherently generate the general mechanism of economic development first comprehensively discussed by Marx and Friedrich Engels, which involves the division of labor development and market expansion accumulating cyclically and reinforcing each other. This mechanism drives both the high-speed and high-quality development of China’s economic modernization.

The broad Marxist political economy paradigm facilitates explaining China’s economic modernization theoretically, historically and practically with unified logic. “Get organized” serves as both the engine and the realization mechanism of this modernization, with the Communist Party of China (CPC) consistently being the core force of this organizational effort.

Media and academic attention on Airbnb focuses on user experiences, implications for traditional accommodation establishments and negative sociocultural impacts. The purpose of this paper is to explore the views of Barcelona residents who have been impacted by the proliferation of Airbnb rentals.

A qualitative approach was adopted, involving semi-structured interviews with residents of Barcelona.

It highlights the problem of unregistered Airbnb rentals throughout the city, carrying implications for the gentrification of neighbourhoods, the displacement of local residents and anti-social guest behaviour. This study points to a consequent rise in anti-tourist feeling. It also reveals that the authentic experience promised by the sharing economy is illusory.

This paper presents a model that highlights a clash between the vaunted benefits of the sharing economy for hosts and tourists and the negative implications for a city’s residents.