Understanding the Airbnb user continuation intention: The moderating role of perceived risk

Zubair, Ahsan; Baharun, Rohaizat; Kiran, Faiqa; Abro, Muhammad Azeem

doi:10.3389/fpsyg.2022.929060

Cited by 8 publications

(6 citation statements)

References 84 publications

(138 reference statements)

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“…It is a model of environmental psychology based on the behaviorist psychology of stimulus (S)-response (R). Existing studies have interpreted the “S-O-R” model from the perspectives of behaviorism, cognitivism, environmental psychology, educational psychology, management psychology, and consumer behavior patterns ( Liu et al, 2022 ; Peng and Yue, 2022 ; Zubair et al, 2022 ).…”

Section: Literature Review and Research Hypothesismentioning

confidence: 99%

The impact of digital empowerment on open innovation performance of enterprises from the perspective of SOR

Lingling

Li²

2023

Front. Psychol.

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IntroductionAs China’s digital transformation index continues to climb and market openness increases, the active implementation of open innovation embedded in digital innovation eco-networks is key to implementing sustainable innovation-driven strategies. The widespread use of digital technologies has broken through the traditional closed boundaries of enterprises and enhanced technology exchange, information communication and R&D collaboration with other innovation agents.However, many enterprises’ digital empowerment efforts only stay at the level of digital technology, but do not rise to the level of corporate strategy. How to comprehensively promote the change of enterprise digital empowerment and help enterprises build a sustainable open innovation ecosystem needs further research.MethodsThis article uses the structure equation model and the necessary condition analysis methods to combine the stimulus-organization-reaction (SOR) theory to analyze the conduction mechanism of digital authorization to open innovation from a cognitive perspective.Results(1) In the era of digital economy, digital empowerment emphasizes the initiative and adaptability of enterprises, and explores a sustainable digital road suitable for enterprises themselves; (2) Organizational emotional ability and organizational disordered atmosphere play a mediating role between digital empowerment and open innovation, but organizational emotional ability has a positive impact on open innovation, while organizational disordered atmosphere is the opposite. (3) Organizational identity positively regulates the relationship between the disordered atmosphere and open innovation.DiscussionThe development of digital technology has adapted deviations with traditional management models. Organizing the investment in digital construction should also pay attention to the digital training and digital thinking of organizational members.Organizations should provide organizational support through various channels, enhance employees’ organizational commitments to create a relationship -shaped psychological contract, regularly carry out digital education and organizational culture, reduce the differential atmosphere between teams, enhance the team’s awareness of cooperation and trust in the teamAnd overall consciousness.

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Section: Literature Review and Research Hypothesismentioning

confidence: 99%

The impact of digital empowerment on open innovation performance of enterprises from the perspective of SOR

Lingling

Li²

2023

Front. Psychol.

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“…Furthermore, Airbnb focuses more on Short-Term apartment Rentals whereas Booking.com focuses more on hotel rooms. In addition, according to Zubair and Faiqa (2022) , there is a certain level of intended user continuation.…”

Section: Literature Reviewmentioning

confidence: 99%

Factors affecting short-term rental first price: A revenue management model

2022

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The aim of this paper is to conduct a revenue management study, generating a theoretical model that establishes the relationship between the factors of a Short-Term Rental apartment offered on the Airbnb marketplace or similar and its optimal rental price set when the property is first put on the market, considering not only the characteristics defined in the platform listing but also the sociodemographic characteristics of the area in which the apartment is located. The research process was structured in six phases as case study for the technology transfer model. First, research planning was conducted to estimate the time, cost, and suitability of the research topic. Second, the study design was determined to establish a technology transfer model focusing on the theory of mixed revenue management. Third, data collection about the city of Madrid was extracted from two technological databases, namely SeeTransparent based mainly on Airbnb (28 internal characteristics of the apartment) and Deskmind Research (9 sociodemographic variables of the area in which the apartment is located). Fourth, the data were prepared to create a new descriptive variable of the apartments based on geolocation. Fifth, the analysis of this study was applied to explore the correlation between the price charged per night, the 28 internal characteristics of the apartments, and the 9 sociodemographic variables of their surrounding areas. Sixth, with this integrated database, the information was transformed into multivariate inferential statistics through Exploratory Factor Analysis and Multiple Linear Regression, creating a technology transfer model (big data algorithm) that allows revenue managers to set the price of an apartment based on known information, prior to having a history of market reactions. This research process and model consider some of the factors affecting the psychological behavior of tourism consumers. Practical implications of the findings indicate that the size/capacity of the apartments used for Short-Term rentals largely determines the initial rental price set (72%). The equipment offered by the apartments has a moderate impact (18%), and the sociodemographic characteristics of the surrounding area have a minor influence (11%).

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“…First, the recognition of information overload aspects that impact the tourist intention procedure will support the industries to reform their policies to improve tourists’ trust and improve their intention to travel, which can be achieved by placing several computer-generated checks on the internet. Second, current research demonstrates that the tourist is affected by extreme socialization, and its associated need for spontaneous reaction further enhances societal pressure ( Zubair et al, 2022 ). Government administrators and hotel managers can limit the number of tourists at the tourist destination with the help of implementing virtual limits on the number of bookings every day.…”

Section: Practical Implicationsmentioning

confidence: 99%

“…Government administrators and hotel managers can limit the number of tourists at the tourist destination with the help of implementing virtual limits on the number of bookings every day. Third, the latest information technology research implies that information overload leads to adverse results ( Zubair et al, 2022 ). Practitioners can restrict the information on the internet.…”

Section: Practical Implicationsmentioning

confidence: 99%

The effect of information overload and perceived risk on tourists’ intention to travel in the post-COVID-19 pandemic

Cao

Mao

et al. 2022

Front. Psychol.

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Since the COVID-19 pandemic, the tourism economy has been seriously affected. China has implemented a direct traveling management mechanism and recovered from the pandemic faster than the rest of the world. However, the COVID-19 situation is complicated and uncontrollable because of the available unclear information including difficult medical terminologies. This study attempts to find the determinants of the travel intention of China’s tourists in the post-COVID-19 epidemic. Along with information overload and perception risk, an expanded research model of the Theory of Planned Behavior (TPB) was employed to propose the theoretical framework of this study. A survey was conducted among 518 tourists who spend their holiday in Hainan, which is a popular tourist destination in China. The empirical results show that information overload positively and significantly impacted perceived risk. Furthermore, perceived risk negatively affects the intention to travel. Perceived risk also negatively affected the attitude toward traveling. However, response self-efficacy did not have a significant effect on the intention to travel. Finally, based on the analysis results, this study proposes relevant research contributions and practical recommendations with management implications for the travel industries.

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Understanding the Airbnb user continuation intention: The moderating role of perceived risk

Cited by 8 publications

References 84 publications

The impact of digital empowerment on open innovation performance of enterprises from the perspective of SOR

The impact of digital empowerment on open innovation performance of enterprises from the perspective of SOR

Factors affecting short-term rental first price: A revenue management model

The effect of information overload and perceived risk on tourists’ intention to travel in the post-COVID-19 pandemic

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