{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T04:52:30Z","timestamp":1787028750498,"version":"3.56.0"},"reference-count":171,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,10,24]],"date-time":"2022-10-24T00:00:00Z","timestamp":1666569600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JTAER"],"abstract":"<jats:p>The tourism sector increasingly relies on technology to acquire new clients in a world overflowing with information. So, the main question that needs to be answered is:What digital marketing strategy should be adopted to attract customers and built digital brand name by incorporating websites and social media big data? The authors of this research utilize web analytics and big data to build an innovative methodology in an effort to address this issue. After the data collection, statistical analysis was implemented, followed by a fuzzy cognitive map and an agent-based simulation model in order to illustrate the usage of social media and user experience in multichannel marketing. The findings suggest that, in contrast to the websites of other industries, such as logistics, where customers want to finish their inquiries as quickly as possible and leave the webpage, it is advantageous for tourism websites to keep customers\u2019 attention moreon their website in order to increasevisibility. Additionally, the research further highlights the importance of personalization and user-engagement content to e-WOM, suggesting to tourism businesses to encourage posts made by customers and employees.<\/jats:p>","DOI":"10.3390\/jtaer17040070","type":"journal-article","created":{"date-parts":[[2022,10,24]],"date-time":"2022-10-24T11:53:55Z","timestamp":1666612435000},"page":"1383-1408","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":61,"title":["Multichannel Digital Marketing Optimizations through Big Data Analytics in the Tourism and Hospitality Industry"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2253-8966","authenticated-orcid":false,"given":"Damianos P.","family":"Sakas","sequence":"first","affiliation":[{"name":"Business Information and Communication Technologies in Value Chains Laboratory (BICTEVAC LABORATORY), Department of Agribusiness and Supply Chain Management, School of Applied Economics and Social Sciences, Agricultural University of Athens, 11855 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6857-6012","authenticated-orcid":false,"given":"Dimitrios P.","family":"Reklitis","sequence":"additional","affiliation":[{"name":"Business Information and Communication Technologies in Value Chains Laboratory (BICTEVAC LABORATORY), Department of Agribusiness and Supply Chain Management, School of Applied Economics and Social Sciences, Agricultural University of Athens, 11855 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marina C.","family":"Terzi","sequence":"additional","affiliation":[{"name":"Business Information and Communication Technologies in Value Chains Laboratory (BICTEVAC LABORATORY), Department of Agribusiness and Supply Chain Management, School of Applied Economics and Social Sciences, Agricultural University of Athens, 11855 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9940-1821","authenticated-orcid":false,"given":"Costas","family":"Vassilakis","sequence":"additional","affiliation":[{"name":"Department of Informatics and Telecommunications, Akadimaikou G.K. 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