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Jin-Xing Hao

Biographic Data

ID5072386
NAMEJin-Xing Hao
GIVEN NAMESJin-Xing
FAMILY NAMEHao
SIGNATUREHAO J
AFFILIATIONSBeihang University
ORCID0000-0003-4858-5629
VERIFIEDYes
TOTAL WORKS5
TOTAL CITATIONS5
WORKS AS AUTHOR5
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2019
LATEST PUBLICATION YEAR2026
H-INDEX1
  • Duality of Tourists’ Value Co-Creation Behaviors in the Sharing Economy

    Open Access•Rui Wang, Jin-Xing Hao•ARTICLE•Travel Research Bulletin•2026•References: 68

    The intricate relationships between tourists’ value co-creation behaviors and value perception in the sharing economy have attracted increasing attention from researchers and practitioners. Unlike previous studies that focused on such relationships at a particular time point, this study sheds light on the dynamics of tourists’ value co-creation behaviors and employs social media analytics to reveal their longitudinal role in value perception. Our…

  • Aviation big data-driven tourism carbon efficiency evaluation

    Ruizhi Wang, Jin-Xing Hao et al.•ARTICLE•Journal of Sustainable Tourism•2026•References: 62

  • Likability Bias in Robot Service Failure Tolerance

    Open Access•Ruoran Liu, Jin-Xing Hao et al.•ARTICLE•International Journal of Tourism…•2025

    Likability bias leads people to favor likable objects and tolerate their failures. Improving service robot likability is viewed as a promising strategy to combat the inevitable service failure caused by immature robot technology. However, this study argued that such bias does not always hold in robot service failure. From the cognitive appraisal perspective, this study proposed a contingency model of robot likability, examining the interaction of…

  • Examining destination images from travel blogs

    Rui Wang, Jin-Xing Hao et al.•ARTICLE•Asia Pacific Journal of Tourism…•2019•Cited by: 5•References: 6

    In the big data era, destination images have played an increasingly important role in tourism development. However, seldom tourism research has utilised big data analytics to examine destination images from travel blogs. Therefore, this study proposes and evaluates a big data analytical approach using latent Dirichlet allocation to extract attributes of online destination images from 140,286 travel blogs about 20 cities in China. Results reveal 1…

  • Complicating or simplifying? Investigating the mixed impacts of online product information on consumers’ purchase decisions

    Open Access•Y Yu, Ben Qianqian Liu et al.•ARTICLE•Internet Research•2019•References: 11

    Purpose Prior literature indicates conflicting effects of online product information, which may complicate or simplify consumer purchase decisions. Therefore, the purpose of this paper is to investigate how different online product information (i.e. the choice set size and the popularity information and its presentation) affect consumers’ decision making and the related market outcomes. Design/methodology/approach This research relies on informat…

  • Examining destination images from travel blogs

    Rui Wang, Jin-Xing Hao et al.•ARTICLE•Asia Pacific Journal of Tourism…•2019•Cited by: 5•References: 6

    In the big data era, destination images have played an increasingly important role in tourism development. However, seldom tourism research has utilised big data analytics to examine destination images from travel blogs. Therefore, this study proposes and evaluates a big data analytical approach using latent Dirichlet allocation to extract attributes of online destination images from 140,286 travel blogs about 20 cities in China. Results reveal 1…

  • Examining destination images from travel blogs

    Rui Wang, Jin-Xing Hao et al.•ARTICLE•Asia Pacific Journal of Tourism…•2019•Cited by: 5•References: 6

    In the big data era, destination images have played an increasingly important role in tourism development. However, seldom tourism research has utilised big data analytics to examine destination images from travel blogs. Therefore, this study proposes and evaluates a big data analytical approach using latent Dirichlet allocation to extract attributes of online destination images from 140,286 travel blogs about 20 cities in China. Results reveal 1…

  • Complicating or simplifying? Investigating the mixed impacts of online product information on consumers’ purchase decisions

    Open Access•Y Yu, Ben Qianqian Liu et al.•ARTICLE•Internet Research•2019•References: 11

    Purpose Prior literature indicates conflicting effects of online product information, which may complicate or simplify consumer purchase decisions. Therefore, the purpose of this paper is to investigate how different online product information (i.e. the choice set size and the popularity information and its presentation) affect consumers’ decision making and the related market outcomes. Design/methodology/approach This research relies on informat…

  • Likability Bias in Robot Service Failure Tolerance

    Open Access•Ruoran Liu, Jin-Xing Hao et al.•ARTICLE•International Journal of Tourism…•2025

    Likability bias leads people to favor likable objects and tolerate their failures. Improving service robot likability is viewed as a promising strategy to combat the inevitable service failure caused by immature robot technology. However, this study argued that such bias does not always hold in robot service failure. From the cognitive appraisal perspective, this study proposed a contingency model of robot likability, examining the interaction of…

  • Duality of Tourists’ Value Co-Creation Behaviors in the Sharing Economy

    Open Access•Rui Wang, Jin-Xing Hao•ARTICLE•Travel Research Bulletin•2026•References: 68

    The intricate relationships between tourists’ value co-creation behaviors and value perception in the sharing economy have attracted increasing attention from researchers and practitioners. Unlike previous studies that focused on such relationships at a particular time point, this study sheds light on the dynamics of tourists’ value co-creation behaviors and employs social media analytics to reveal their longitudinal role in value perception. Our…

  • Aviation big data-driven tourism carbon efficiency evaluation

    Ruizhi Wang, Jin-Xing Hao et al.•ARTICLE•Journal of Sustainable Tourism•2026•References: 62

Business (4 works) · Computer Science (4 works) · Tourism (4 works) · Digital Marketing and Social Media (3 works) · Marketing (3 works) · Advertising (2 works) · Big data (2 works) · China (2 works) · Data science (2 works) · Economics (2 works)

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