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Systematic Review of Contextual Suggestion and Recommendation Systems for Sustainable e-Tourism

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  • Haseeb Ur Rehman Khan

    (Faculty of Art, Computing & Creative Industry, Sultan Idris Education University, Tanjong Malim 35900, Perak, Malaysia)

  • Chen Kim Lim

    (Institute for Environment & Development (LESTARI), Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia)

  • Minhaz Farid Ahmed

    (Institute for Environment & Development (LESTARI), Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia)

  • Kian Lam Tan

    (School of Digital Technology, Wawasan Open University, George Town 10050, Penang, Malaysia)

  • Mazlin Bin Mokhtar

    (Institute for Environment & Development (LESTARI), Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia)

Abstract

Agenda 2030 of Sustainable Development Goals (SDGs) 9 and 11 recognizes tourism as one of the central industries to global development to tackle global challenges. With the transformation of information and communication technologies (ICT), e-tourism has evolved globally to establish commercial relationships using the Internet for offering tourism-related products, including giving personalised suggestions. The contextual suggestion has emerged as a modified recommendation system that is integrated with information-retrieval techniques within large databases to provide tourists with a list of suggestions based on contexts, such as location, time of day, or day of the week (weekdays or weekends). This study surveyed literature in the field of contextual suggestion and recommendation systems with a focus on e-tourism. The concerns linked with approaches used in contextual suggestion and recommendation systems are highlighted in this systematic review, while motivations, recommendations, and practical implications in e-tourism are also discussed in this paper. A query search using the keywords “contextual suggestion system”, “recommendation system”, and “tourism” identified 143 relevant articles published from 2012 to 2020. Four major repositories are considered for searching, namely, (i) Science Direct, (ii) Scopus, (iii) IEEE, and (iv) Web of Science. This review was carried out under the protocols of four phases, namely, (i) query searching in major article repositories, (ii) removal of duplicates, (iii) scan of title and abstract, and (iv) complete reading of articles. To identify the gaps in current research, a taxonomy analysis was exemplified into categories and subcategories. The main categories were highlighted as (i) review articles, (ii) model/framework, and (iii) applications. Critical analysis was carried out on the basis of the available literature on the limitations of approaches used in contextual suggestion and recommendation systems. In conclusion, the approaches used are mainly based on content-based filtering, collaborative filtering, preference-based product ranking, and language modelling. The evaluation measures for the contextual suggestion system include precision, normalized discounted cumulative, and mean reciprocal rank, while test collections comprise Internet resources. Given that the tourism industry contributed to the environmental and social-economic development, contextual suggestion and recommendation systems have presented themselves to be relevant in integrating and achieving SDG 9 and SDG 11 in many ways such as web-based e-services by the government sector and smart gadgets based on reliable and real-time data and information for city planners as well as law enforcement personnel in a sustainable city.

Suggested Citation

  • Haseeb Ur Rehman Khan & Chen Kim Lim & Minhaz Farid Ahmed & Kian Lam Tan & Mazlin Bin Mokhtar, 2021. "Systematic Review of Contextual Suggestion and Recommendation Systems for Sustainable e-Tourism," Sustainability, MDPI, vol. 13(15), pages 1-27, July.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:15:p:8141-:d:598412
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    References listed on IDEAS

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    1. Dimitrios Buhalis & Aditya Amaranggana, 2015. "Smart Tourism Destinations Enhancing Tourism Experience Through Personalisation of Services," Springer Books, in: Iis Tussyadiah & Alessandro Inversini (ed.), Information and Communication Technologies in Tourism 2015, edition 127, pages 377-389, Springer.
    2. Ulrike Gretzel & Matthias Fuchs & Rodolfo Baggio & Wolfram Hoepken & Rob Law & Julia Neidhardt & Juho Pesonen & Markus Zanker & Zheng Xiang, 2020. "e-Tourism beyond COVID-19: a call for transformative research," Information Technology & Tourism, Springer, vol. 22(2), pages 187-203, June.
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    Cited by:

    1. Qazi Mudassar Ilyas & Abid Mehmood & Ashfaq Ahmad & Muneer Ahmad, 2022. "A Systematic Study on a Customer’s Next-Items Recommendation Techniques," Sustainability, MDPI, vol. 14(12), pages 1-28, June.
    2. Chen-Kim Lim & Kian-Lam Tan & Minhaz Farid Ahmed, 2023. "Conservation of Culture Heritage Tourism: A Case Study in Langkawi Kubang Badak Remnant Charcoal Kilns," Sustainability, MDPI, vol. 15(8), pages 1-17, April.
    3. Christiana Koliouska & Zacharoula Andreopoulou, 2023. "E-Tourism for Sustainable Development through Alternative Tourism Activities," Sustainability, MDPI, vol. 15(11), pages 1-13, May.
    4. Mustafa Rehman Khan & Haseeb Ur Rehman Khan & Chen Kim Lim & Kian Lam Tan & Minhaz Farid Ahmed, 2021. "Sustainable Tourism Policy, Destination Management and Sustainable Tourism Development: A Moderated-Mediation Model," Sustainability, MDPI, vol. 13(21), pages 1-22, November.

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