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    KCI등재

    COVID-19 팬데믹에서 Airbnb 호스트의 마케팅 전략의 변화가 공유성과에 미치는 영향

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    https://www.riss.kr/link?id=A107879479

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    The entire tourism industry is being hit hard by the COVID-19 as a global pandemic. Accommodation sharing services such as Airbnb, which have recently expanded due to the spread of the sharing economy, are particularly affected by the pandemic because transactions are made based on trust and communication between consumer and supplier. As the pandemic situation changes individuals perceptions and behavior of travel, strategies for the recovery of the tourism industry have been discussed. However, since most studies present macro strategies in terms of traditional lodging providers and the government, there is a significant lack of discussion on differentiated pandemic response strategies considering the peculiarity of the sharing economy centered on peer-to-peer transactions. This study discusses the marketing strategy for individual hosts of Airbnb during COVID-19. We empirically analyze the effect of changes in listing descriptions posted by the Airbnb hosts on listing performance after COVID-19 was outbroken. We extract nine aspects described in the listing descriptions using the Attention-Based Aspect Extraction model, which is a deep learning-based aspect extraction method. We model the effect of aspect changes on listing performance after the COVID-19 by observing the frequency of each aspect appeared in the text. In addition, we compare those effects across the types of Airbnb listing. Through this, this study presents an idea for a pandemic crisis response strategy that individual service providers of accommodation sharing services can take depending on the listing type.
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    The entire tourism industry is being hit hard by the COVID-19 as a global pandemic. Accommodation sharing services such as Airbnb, which have recently expanded due to the spread of the sharing economy, are particularly affected by the pandemic because...

    The entire tourism industry is being hit hard by the COVID-19 as a global pandemic. Accommodation sharing services such as Airbnb, which have recently expanded due to the spread of the sharing economy, are particularly affected by the pandemic because transactions are made based on trust and communication between consumer and supplier. As the pandemic situation changes individuals perceptions and behavior of travel, strategies for the recovery of the tourism industry have been discussed. However, since most studies present macro strategies in terms of traditional lodging providers and the government, there is a significant lack of discussion on differentiated pandemic response strategies considering the peculiarity of the sharing economy centered on peer-to-peer transactions. This study discusses the marketing strategy for individual hosts of Airbnb during COVID-19. We empirically analyze the effect of changes in listing descriptions posted by the Airbnb hosts on listing performance after COVID-19 was outbroken. We extract nine aspects described in the listing descriptions using the Attention-Based Aspect Extraction model, which is a deep learning-based aspect extraction method. We model the effect of aspect changes on listing performance after the COVID-19 by observing the frequency of each aspect appeared in the text. In addition, we compare those effects across the types of Airbnb listing. Through this, this study presents an idea for a pandemic crisis response strategy that individual service providers of accommodation sharing services can take depending on the listing type.

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    참고문헌 (Reference)

    1 Novelli, M, "‘No Ebola… still doomed’–The Ebola-induced tourism crisis" 70 : 76-87, 2018

    2 UNWTO, "World Tourism Barometer" 18 (18): 2020

    3 Said, C., "Window into Airbnb’s hidden impact on S.F. - San Francisco Chronicle"

    4 Chang, J. R., "Why customers don’t revisit in tourism and hospitality industry?" 7 : 146588-146606, 2019

    5 Kim, K., "What makes tourists feel negatively about tourism destinations? Application of hybrid text mining methodology to smart destination management" 123 : 362-369, 2017

    6 Ooms, W, "Use of social media in inbound open innovation: Building capabilities for absorptive capacity" 24 (24): 136-150, 2015

    7 Huang, A., "Understanding the impact of COVID-19 intervention policies on the hospitality labor market" 91 : 102660-, 2020

    8 Fishbein, M., "Understanding attitudes and predicting social behavior" Prentice Hall 1980

    9 Neuburger, L., "Travel risk perception and travel behaviour during the COVID-19 pandemic 2020, a case study of the DACH region" 24 (24): 1003-1016, 2021

    10 Reisinger, Y., "Travel anxiety and intentions to travel internationally, Implications of travel risk perception" 43 (43): 212-225, 2005

    1 Novelli, M, "‘No Ebola… still doomed’–The Ebola-induced tourism crisis" 70 : 76-87, 2018

    2 UNWTO, "World Tourism Barometer" 18 (18): 2020

    3 Said, C., "Window into Airbnb’s hidden impact on S.F. - San Francisco Chronicle"

    4 Chang, J. R., "Why customers don’t revisit in tourism and hospitality industry?" 7 : 146588-146606, 2019

    5 Kim, K., "What makes tourists feel negatively about tourism destinations? Application of hybrid text mining methodology to smart destination management" 123 : 362-369, 2017

    6 Ooms, W, "Use of social media in inbound open innovation: Building capabilities for absorptive capacity" 24 (24): 136-150, 2015

    7 Huang, A., "Understanding the impact of COVID-19 intervention policies on the hospitality labor market" 91 : 102660-, 2020

    8 Fishbein, M., "Understanding attitudes and predicting social behavior" Prentice Hall 1980

    9 Neuburger, L., "Travel risk perception and travel behaviour during the COVID-19 pandemic 2020, a case study of the DACH region" 24 (24): 1003-1016, 2021

    10 Reisinger, Y., "Travel anxiety and intentions to travel internationally, Implications of travel risk perception" 43 (43): 212-225, 2005

    11 Braun-LaTour, K. A, "Tourist memory distortion" 44 (44): 360-367, 2006

    12 Blake, A., "Tourism crisis management, US response to September 11" 30 (30): 813-832, 2003

    13 Mimno, D, "Topic models conditioned on arbitrary features with Dirichlet-multinomial regression" 24 : 411-418, 2008

    14 Chuo, H. Y, "Theme park visitors’ responses to the SARS outbreak in Taiwan" 3 : 87-104, 2007

    15 Ye, Q, "The influence of user-generated content on traveler behavior: An empirical investigation on the effects of e-word-of-mouth to hotel online bookings" 27 (27): 634-639, 2011

    16 Kim, S. B, "The effect of searching and surfing on recognition of destination images on Facebook pages" 30 : 813-823, 2014

    17 Cahyanto, I, "The dynamics of travel avoidance, The case of Ebola in the US" 20 : 195-203, 2016

    18 Zenker, S, "The coronavirus pandemic–A critical discussion of a tourism research agenda" 81 : 104164-, 2020

    19 Ilhan, A, "The challenges of the sharing economy users and the impacts of pandemic (COVID 19)" 185-192, 2020

    20 Tan, A. H., "Text mining: The state of the art and the challenges" 8 : 65-70, 1999

    21 UNISDR, "Terminology on Disaster Risk Reduction" United Nations 2009

    22 Al-Saggaf, Y, "Social media in Saudi Arabia: Exploring its use during two natural disasters" 95 : 3-15, 2015

    23 He, W, "Social media competitive analysis and text mining: A case study in the pizza industry" 33 (33): 464-472, 2013

    24 Wilson, A., "Services marketing: Integrating customer focus across the firm" McGraw Hill 2012

    25 Liu, C. H. S, "Service quality and price perception of service: Influence on word-of-mouth and revisit intention" 52 : 42-54, 2016

    26 Alamanda, D. T, "Sentiment analysis using text mining of Indonesia tourism reviews via social media" 5 (5): 43-53, 2019

    27 Tew, P. J, "SARS, lessons in strategic planning for hoteliers and destination marketers" 20 (20): 2008

    28 Shin, H., "Reducing perceived healthrisk to attract hotel customers in the COVID19 pandemic era, Focused on technology innovation for social distancing and cleanliness" 91 : 102664-, 2020

    29 Wang, W., "Recursive neural conditional random fields for aspect-based sentiment analysis" 2016

    30 Richardson, L, "Performing the sharing economy" 67 : 121-129, 2015

    31 Paek, H. J, "Peer or expert? The persuasive impact of YouTube public service announcement producers" 30 (30): 161-188, 2011

    32 Mimno, D, "Optimizing semantic coherence in topic models" 262-272, 2011

    33 Slevitch, L., "Management of perceived risk in the context of destination choice" 9 (9): 85-103, 2008

    34 Stylos, N, "Linking the dots among destination images, place attachment, and revisit intentions: A study among British and Russian tourists" 60 : 15-29, 2017

    35 Leggat, P. A., "Level of concern and precaution taking among Australians regarding travel during pandemic (H1N1) 2009, results from the 2009 Queensland Social Survey" 17 (17): 291-295, 2010

    36 Blei, D. M., "Latent dirichlet allocation" 3 : 993-1022, 2003

    37 Nabity-Grover, T, "Inside out and outside in, How the COVID-19 pandemic affects self-disclosure on social media" 55 : 102188-, 2020

    38 Lashley, C., "In search of hospitality" Routledge 2013

    39 Lin, W. Y., "Health information seeking in the Web 2.0 age, Trust in social media, uncertainty reduction, and self-disclosure" 56 : 289-294, 2016

    40 Slattery, P, "Finding the hospitality industry" 1 (1): 19-28, 2002

    41 Bruno, S., "Exploring the characteristics of tourism industry by analyzing consumer review contents from social media: a case study of Bamako, Mali" 22 (22): 214-222, 2019

    42 Turban, E, "Enterprise social networking: Opportunities, adoption, and risk mitigation" 21 (21): 202-220, 2011

    43 Kim, J, "Effects of COVID-19 on preferences for private dining facilities in restaurants" 45 : 67-70, 2020

    44 Jiang, Y, "Disaster collaboration in tourism, Motives, impediments and success factors" 31 : 70-82, 2017

    45 Pavlatos, O, "Crisis management in the Greek hotel industry in response to COVID-19 pandemic" 32 (32): 80-92, 2021

    46 Alan, C. B, "Crisis management and recovery, how restaurants in Hong Kong responded to SARS" 25 (25): 3-11, 2006

    47 Lutz, C., "Consumer segmentation within the sharing economy, The case of Airbnb" 88 : 187-196, 2018

    48 Nieto García, M, "Be social! The impact of self-presentation on peer-to-peer accommodation revenue" 59 (59): 1268-1281, 2020

    49 Poria, S, "Aspect extraction for opinion mining with a deep convolutional neural network" 108 : 42-49, 2016

    50 Che, T., "Antecedents of consumers’ intention to revisit an online group-buying website: A transaction cost perspective" 52 (52): 588-598, 2015

    51 He, R, "An unsupervised neural attention model for aspect extraction" 1 : 388-397, 2017

    52 Zhang, L., "A text analytics framework for understanding the relationships among host self-description, trust perception and purchase behavior on Airbnb" 133 : 113288-, 2020

    53 Bjørkelund, E., "A study of opinion mining and visualization of hotel reviews" 229-238, 2012

    54 Jin, W, "A novel lexicalized HMM-based learning framework for web opinion mining" 465-472, 2009

    55 Roberts, M. E, "A model of text for experimentation in the social sciences" 111 (111): 988-1003, 2016

    56 Cheng, X, "A mixed method investigation of sharing economy driven car-hailing services, Online and offline perspectives" 41 : 57-64, 2018

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    학술지 이력

    학술지 이력
    연월일 이력구분 이력상세 등재구분
    2027 평가 재인증평가 신청대상 (재인증)
    2021-01-01 등재 등재학술지 유지 (재인증) KCI등재
    2018-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2015-03-25 학회명변경 영문명 : 미등록 -> Korea Intelligent Information Systems Society KCI등재
    2015-03-17 학술지명변경 외국어명 : 미등록 -> Journal of Intelligence and Information Systems KCI등재
    2015-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2011-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2009-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2008-02-11 학술지명변경 한글명 : 한국지능정보시스템학회 논문지 -> 지능정보연구 KCI등재
    2007-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2004-01-01 등재 등재학술지 선정 (등재후보2차) KCI등재
    2003-01-01 등재 등재후보 1차 PASS (등재후보1차) KCI등재후보
    2001-07-01 등재 등재후보학술지 선정 (신규평가) KCI등재후보
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    학술지 인용정보

    학술지 인용정보
    기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
    2016 1.51 1.51 1.99
    KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
    1.78 1.54 2.674 0.38
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