AI in health tourism: developing a measurement scale

Kangping Wang; Haiyan Kong; Naipeng Bu; Honggen Xiao; Xuejie Qiu; Jinghan Li

doi:10.1080/10941665.2022.2142620

AI in health tourism: developing a measurement scale

Kangping Wang, Haiyan Kong, Naipeng Bu, Honggen Xiao, Xuejie Qiu, Jinghan Li

Research output: Journal article publication › Journal article › Academic research › peer-review

15 Citations (Scopus)

Abstract

The COVID-19 pandemic created a strong urgency for the application of artificial intelligence (AI) in the tourism and hospitality industry. This paper was set to develop a scale of AI needs in health tourism. A total of 556 valid data were collected, and both exploratory and confirmatory factor analyses were employed to analyze the data. Six constructs containing 18 items were identified, and the reliability and validity were examined to reach satisfactory levels. The measurement scale developed may serve as a foundation for future research, and shed light on tourism managers, marketers, AI designers and policymakers.

Original language	English
Pages (from-to)	954-966
Number of pages	13
Journal	Asia Pacific Journal of Tourism Research
Volume	27
Issue number	9
DOIs	https://doi.org/10.1080/10941665.2022.2142620
Publication status	Published - Sept 2022

Keywords

Artificial intelligence (AI)
construction and validation
health tourism
measurement scale
reliability and validity

ASJC Scopus subject areas

Geography, Planning and Development
Tourism, Leisure and Hospitality Management

More information

10.1080/10941665.2022.2142620

Cite this

@article{3aa2e7b7e20d4f1188059f21d59ee5ac,

title = "AI in health tourism: developing a measurement scale",

abstract = "The COVID-19 pandemic created a strong urgency for the application of artificial intelligence (AI) in the tourism and hospitality industry. This paper was set to develop a scale of AI needs in health tourism. A total of 556 valid data were collected, and both exploratory and confirmatory factor analyses were employed to analyze the data. Six constructs containing 18 items were identified, and the reliability and validity were examined to reach satisfactory levels. The measurement scale developed may serve as a foundation for future research, and shed light on tourism managers, marketers, AI designers and policymakers.",

keywords = "Artificial intelligence (AI), construction and validation, health tourism, measurement scale, reliability and validity",

author = "Kangping Wang and Haiyan Kong and Naipeng Bu and Honggen Xiao and Xuejie Qiu and Jinghan Li",

note = "Funding Information: This work was supported by the National Social Science Fund of China [grant number 20BGL159]. Publisher Copyright: {\textcopyright} 2022 Asia Pacific Tourism Association.",

year = "2022",

month = sep,

doi = "10.1080/10941665.2022.2142620",

language = "English",

volume = "27",

pages = "954--966",

journal = "Asia Pacific Journal of Tourism Research",

issn = "1094-1665",

publisher = "Taylor and Francis Ltd.",

number = "9",

}

TY - JOUR

T1 - AI in health tourism: developing a measurement scale

AU - Wang, Kangping

AU - Kong, Haiyan

AU - Bu, Naipeng

AU - Xiao, Honggen

AU - Qiu, Xuejie

AU - Li, Jinghan

PY - 2022/9

Y1 - 2022/9

N2 - The COVID-19 pandemic created a strong urgency for the application of artificial intelligence (AI) in the tourism and hospitality industry. This paper was set to develop a scale of AI needs in health tourism. A total of 556 valid data were collected, and both exploratory and confirmatory factor analyses were employed to analyze the data. Six constructs containing 18 items were identified, and the reliability and validity were examined to reach satisfactory levels. The measurement scale developed may serve as a foundation for future research, and shed light on tourism managers, marketers, AI designers and policymakers.

AB - The COVID-19 pandemic created a strong urgency for the application of artificial intelligence (AI) in the tourism and hospitality industry. This paper was set to develop a scale of AI needs in health tourism. A total of 556 valid data were collected, and both exploratory and confirmatory factor analyses were employed to analyze the data. Six constructs containing 18 items were identified, and the reliability and validity were examined to reach satisfactory levels. The measurement scale developed may serve as a foundation for future research, and shed light on tourism managers, marketers, AI designers and policymakers.

KW - Artificial intelligence (AI)

KW - construction and validation

KW - health tourism

KW - measurement scale

KW - reliability and validity

UR - http://www.scopus.com/inward/record.url?scp=85142240805&partnerID=8YFLogxK

U2 - 10.1080/10941665.2022.2142620

DO - 10.1080/10941665.2022.2142620

M3 - Journal article

AN - SCOPUS:85142240805

SN - 1094-1665

VL - 27

SP - 954

EP - 966

JO - Asia Pacific Journal of Tourism Research

JF - Asia Pacific Journal of Tourism Research

IS - 9

ER -

AI in health tourism: developing a measurement scale

Abstract

Keywords

ASJC Scopus subject areas

More information

Other files and links

Fingerprint

Cite this