Exploring the effect of heuristic factors on the popularity of “best places to visit” recommendation in a Chinese outbound traveler community

Lin Li; Sung Byung Yang

doi:10.1145/3154943.3154949

Exploring the effect of heuristic factors on the popularity of “best places to visit” recommendation in a Chinese outbound traveler community

Lin Li, Sung Byung Yang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

Online “best places to visit” recommendations in an independent travelers' community are gaining more and more popularity due to the various and differentiated individual needs. Therefore, this research aims to identify heuristic factors affecting the popularity of “best places to visit” recommendations. The heuristic factors are derived from both recommender-related (recommender identity disclosure, recommender reputation, recommender experience, recommender location) and recommendation-related (recommendation helpfulness, recommendation comment, recommendation length, recommendation place) heuristic perspectives based on the heuristic-systematic model. The implications of this research are expected to contribute to build one more layer to the literature on both the destination recommendation and recommendation popularity, and practically, to make more favorable “best places to visit” recommendations in the context of Chinese outbound independent traveler communities.

Original language	English
Title of host publication	Proceedings of the International Conference on Electronic Commerce, ICEC 2017
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450353120
DOIs	https://doi.org/10.1145/3154943.3154949
Publication status	Published - 17 Aug 2017
Event	2017 International Conference on Electronic Commerce, ICEC 2017 - Pangyo, Seongnam, Korea, Republic of Duration: 17 Aug 2017 → 18 Aug 2017

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	2017 International Conference on Electronic Commerce, ICEC 2017
Country/Territory	Korea, Republic of
City	Pangyo, Seongnam
Period	17/08/17 → 18/08/17

Bibliographical note

Publisher Copyright:
© Copyright 2017 ACM

Keywords

Best places to visit
Destination recommendation
Heuristic-systematic model
Recommendation popularity
Recommendation-related heuristic factors
Recommender-related heuristic factors

Access to Document

10.1145/3154943.3154949

Cite this

Li, L., & Yang, S. B. (2017). Exploring the effect of heuristic factors on the popularity of “best places to visit” recommendation in a Chinese outbound traveler community. In Proceedings of the International Conference on Electronic Commerce, ICEC 2017 (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3154943.3154949

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title = "Exploring the effect of heuristic factors on the popularity of “best places to visit” recommendation in a Chinese outbound traveler community",

abstract = "Online “best places to visit” recommendations in an independent travelers' community are gaining more and more popularity due to the various and differentiated individual needs. Therefore, this research aims to identify heuristic factors affecting the popularity of “best places to visit” recommendations. The heuristic factors are derived from both recommender-related (recommender identity disclosure, recommender reputation, recommender experience, recommender location) and recommendation-related (recommendation helpfulness, recommendation comment, recommendation length, recommendation place) heuristic perspectives based on the heuristic-systematic model. The implications of this research are expected to contribute to build one more layer to the literature on both the destination recommendation and recommendation popularity, and practically, to make more favorable “best places to visit” recommendations in the context of Chinese outbound independent traveler communities.",

keywords = "Best places to visit, Destination recommendation, Heuristic-systematic model, Recommendation popularity, Recommendation-related heuristic factors, Recommender-related heuristic factors",

author = "Lin Li and Yang, {Sung Byung}",

year = "2017",

month = aug,

day = "17",

doi = "10.1145/3154943.3154949",

language = "English",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

booktitle = "Proceedings of the International Conference on Electronic Commerce, ICEC 2017",

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Li, L & Yang, SB 2017, Exploring the effect of heuristic factors on the popularity of “best places to visit” recommendation in a Chinese outbound traveler community. in Proceedings of the International Conference on Electronic Commerce, ICEC 2017. ACM International Conference Proceeding Series, Association for Computing Machinery, 2017 International Conference on Electronic Commerce, ICEC 2017, Pangyo, Seongnam, Korea, Republic of, 17/08/17. https://doi.org/10.1145/3154943.3154949

Exploring the effect of heuristic factors on the popularity of “best places to visit” recommendation in a Chinese outbound traveler community. / Li, Lin; Yang, Sung Byung.
Proceedings of the International Conference on Electronic Commerce, ICEC 2017. Association for Computing Machinery, 2017. (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - Online “best places to visit” recommendations in an independent travelers' community are gaining more and more popularity due to the various and differentiated individual needs. Therefore, this research aims to identify heuristic factors affecting the popularity of “best places to visit” recommendations. The heuristic factors are derived from both recommender-related (recommender identity disclosure, recommender reputation, recommender experience, recommender location) and recommendation-related (recommendation helpfulness, recommendation comment, recommendation length, recommendation place) heuristic perspectives based on the heuristic-systematic model. The implications of this research are expected to contribute to build one more layer to the literature on both the destination recommendation and recommendation popularity, and practically, to make more favorable “best places to visit” recommendations in the context of Chinese outbound independent traveler communities.

AB - Online “best places to visit” recommendations in an independent travelers' community are gaining more and more popularity due to the various and differentiated individual needs. Therefore, this research aims to identify heuristic factors affecting the popularity of “best places to visit” recommendations. The heuristic factors are derived from both recommender-related (recommender identity disclosure, recommender reputation, recommender experience, recommender location) and recommendation-related (recommendation helpfulness, recommendation comment, recommendation length, recommendation place) heuristic perspectives based on the heuristic-systematic model. The implications of this research are expected to contribute to build one more layer to the literature on both the destination recommendation and recommendation popularity, and practically, to make more favorable “best places to visit” recommendations in the context of Chinese outbound independent traveler communities.

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M3 - Conference contribution

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Exploring the effect of heuristic factors on the popularity of “best places to visit” recommendation in a Chinese outbound traveler community

Abstract

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Bibliographical note

Keywords

Access to Document

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