POST-VIA: Develop Individualized Marketing Strategies for Tourists

Cabanas-Abascal, Antonio; Rodríguez-González, Alejandro; Casado‐Lumbreras, Cristina; Fernández-González, Joaquín; Jiménez-López, Diego

doi:10.1007/978-3-642-37932-1_4

Cited by 3 publications

References 47 publications

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UNVEILING PATTERNS IN CUSTOMER RELATIONSHIP MANAGEMENT & MARKET CAMPAIGN LITERATURE: A BIBLIOMETRIC ANALYSIS

Kumar Deepak Raja,

Singh

2023

ShodhKosh J. Vis. Per. Arts

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The swift evolution of corporate practices in the digital age has heightened the significance of Customer Relationship Management (CRM) and marketing initiatives in promoting customer-centric tactics. This research utilizes a bibliometric analysis of literature pertaining to CRM and marketing campaigns, drawing on data from the Elsevier Scopus database (2000–2024). The research reveals significant patterns and emerging topics at the junction of various fields by analyzing publication trends, main authors, and thematic clusters. The analysis indicates a consistent increase in academic production, with journal articles and conference papers as the primary contributors. Crucial findings highlight the essential function of new technologies, including machine learning, artificial intelligence, and big data analytics, in improving the efficacy of CRM. Network visualizations illustrate topic clusters centered on cause-related marketing, customer happiness, decision-making, and ethical marketing practices. This study highlights the interdisciplinary and worldwide aspects of CRM-MC research, offering a framework for future scholarly investigation and practical implementation. The results provide significant insights for organizations aiming to optimize resource allocation, improve customer engagement, and attain enduring competitive advantage in a progressively competitive landscape.

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UNVEILING PATTERNS IN CUSTOMER RELATIONSHIP MANAGEMENT & MARKET CAMPAIGN LITERATURE: A BIBLIOMETRIC ANALYSIS

Kumar Deepak Raja,

Singh

2023

ShodhKosh J. Vis. Per. Arts

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Knowledge Graphs for Online Marketing and Sales of Touristic Services

et al. 2020

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Direct online marketing and sales are nowadays an essential part of almost any business that addresses an end consumer, such as in tourism. On the downside, the data and content required for such marketing and sales are typically distributed, and difficult to identify and use, especially for small and medium enterprises. Further, a combination of content management and semantics for automated online marketing and sales is becoming practically feasible now, especially with the global adoption of knowledge graphs. A design and feasibility pilot of a solution implementing semantic content and data value chain for online direct marketing and sales, basing on knowledge graphs, and efficiently addressing multiple channels and stakeholders, is provided and evaluated with the end-users. The implementation is shown to be suitable for the use on the Web, social media and mobile channels. The proof of concept addresses the tourism sector, exploring, in particular, the case of touristic service packaging, and is applicable globally. The typically encountered challenges, particularly, the ones related to data quality, are identified, and the ways to overcome them are discussed. The paper advances the knowledge of employment of knowledge graphs in online marketing and sales, and showcases its related innovative practical application, co-created by the industry providing marketing and sales solutions for Austria, one of the world’s leading touristic regions.

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Artificial Intelligence (AI) for Tourism Start-Ups

Ghouse,

Chaudhary

2024

Innovative Technologies for Increasing Service Productivity

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This chapter explores the dynamic intersection of artificial intelligence (AI) and the startup landscape within the tourism industry. It investigates how AI has the potential to revolutionize operations, innovation, and services for emerging businesses in tourism. Demonstrating AI's critical role in enhancing the tourism experience—ranging from personalized recommendations and chatbot-driven customer service to pricing optimization and demand forecasting—it showcases innovative solutions from notable startups like DeepL, Fetch.ai, and Lilium. The chapter includes brief case studies illustrating AI applications in tourism and emphasizes the pivotal role of investors in supporting these startups. It concludes by outlining future research directions, addressing strategies for maximizing AI benefits in tourism, managing privacy and security concerns, and navigating the evolving landscape of AI integration in travel.

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POST-VIA: Develop Individualized Marketing Strategies for Tourists

Cited by 3 publications

References 47 publications

UNVEILING PATTERNS IN CUSTOMER RELATIONSHIP MANAGEMENT & MARKET CAMPAIGN LITERATURE: A BIBLIOMETRIC ANALYSIS

UNVEILING PATTERNS IN CUSTOMER RELATIONSHIP MANAGEMENT & MARKET CAMPAIGN LITERATURE: A BIBLIOMETRIC ANALYSIS

Knowledge Graphs for Online Marketing and Sales of Touristic Services

Artificial Intelligence (AI) for Tourism Start-Ups

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