Web 2.0 and destination marketing: current trends and future directions

Over the last decade, destination marketers and Destination Marketing Organizations (DMOs) have increasingly invested in Web 2.0 technologies as a cost-effective means of promoting destinations online, in the face of drastic marketing budgets cuts. Recent scholarly and industry research has emphasized that Web 2.0 plays an increasing role in destination marketing. However, no comprehensive appraisal of this research area has been conducted so far. To address this gap, this study conducts a quantitative literature review to examine the extent to which Web 2.0 features in destination marketing research that was published until December 2019, by identifying research topics, gaps and future directions, and designing a theory-driven agenda for future research. The study’s findings indicate an increase in scholarly literature revolving around the adoption and use of Web 2.0 for destination marketing purposes. However, the emerging research field is fragmented in scope and displays several gaps. Most of the studies are descriptive in nature and a strong overarching conceptual framework that might help identify critical destination marketing problems linked to Web 2.0 technologies is missing

The role of chatgpt on customer service in the hospitality industry: An exploratory study of hospitality workers\u27 experiences and perceptions

Purpose – This study explains the impact of ChatGPT, an artificial intelligence (AI) language model, on customer service in the hospitality industry by exploring the experiences and perceptions of hospitality employees who have utilized ChatGPT in their customer interactions. Methodology – A qualitative approach was adopted using in-depth interviews to collect data from a heterogeneous group of 15 individuals consisting of employees, managers, and other stakeholders directly involved in the hospitality industry in Krabi, Thailand. Findings – Integrating ChatGPT into customer service in the hospitality industry has a significant positive impact. It improves employee skills and knowledge, bridges language barriers, provides valuable recommendations, and helps with productivity and workflow management. In conclusion, ChatGPT is a valuable tool for improving customer service in the hospitality industry, ultimately contributing to a better overall guest experience. Originality of the research – Limited research has been conducted on the specific impact of ChatGPT in the hospitality industry, particularly in Krabi, a popular tourist destination in Thailand. This study aims to fill this gap by examining how ChatGPT affects customer service in the hospitality industry of Krabi, Thailand, and shedding light on its impact

In League? Destination Marketing Organisations and Football Clubs in the Virtual Space

Logic dictates that Destination Marketing Organisations (DMOs), while representing many stakeholders, should leverage a location’s most visible assets to enhance the attractiveness of the destination at any given opportunity. This study examines the manner and extent to which four major European football franchises are mentioned and promoted on the official digital marketing platforms of their respective cities; Amsterdam, Barcelona, Manchester and Munich. A tailor made content analysis tool is used to conduct a systematic investigation of the virtual platforms over which the DMOs of these cities exert a modicum of control. The content of these platforms is scrutinised from three perspectives; promotional, information dissemination or push towards purchase via external links. The four cities forming part of this study are home to some of the world’s most iconic global sporting brands. The research uncovers a level of confusion or simple lack of know-how on the part of DMOs as to how these hugely popular clubs can or should be exploited in the digital space. It proffers solutions to this dilemma as in initiating cooperative marketing efforts between the respective organisations and exposes a contemporary field that necessitates further research

The competitive productivity (CP) of tourism destinations: an integrative conceptual framework and a reflection on big data and analytics

Purpose: The purpose of this study is twofold. First, this study elaborates an integrative conceptual framework of tourism destination competitive productivity (TDCP) by blending established destination competitiveness frameworks, the competitive productivity (CP) framework and studies pertaining to big data and big data analytics (BDA) within destination management information systems and smart tourism destinations. Second, this study examines the drivers of TDCP in the context of the ongoing 4th industrial revolution by conceptualizing the destination business intelligence unit (DBIU) as a platform able to create sustained destination business intelligence under the guise of BDA, useful to support destination managers to achieve the tourism destination’s economic objectives. Design/methodology/approach: In this work, the authors leverage both extant literature (under the guise of research on CP, tourism destination competitiveness [TDC] and destination management information systems) and empirical work (in the form of interviews and field work involving destination managers and chief executive officers of destination management organizations and convention bureaus, as well as secondary data) to elaborate, develop and present an integrative conceptual framework of TDCP. Findings: The integrative conceptual framework of TDCP elaborated has been found helpful by a number of destination managers trying to understand how to effectively and efficiently manage and market a tourism destination in today’s fast-paced, digital and hypercompetitive environment. While DBIUs are at different stages of implementation, often as part of broader smart destination initiatives, it appears that they are increasingly fulfilling the purpose of creating sustained destination business intelligence by means of BDA to help tourism destinations achieve their economic goals. Research limitations/implications: This work bears several practical implications for tourism policymakers, destination managers and marketers, technology developers, as well as tourism and hospitality firms and practitioners. Tourism policymakers could embed TDCP into tourism and economic policies, and destination managers and marketers might build and make use of platforms such as the proposed DBIU. Technology developers need to understand that designing destination management information systems in general and more specifically DBIUs requires an in-depth analysis of the stakeholders that are going to contribute, share, control and use BDA. Originality/value: To the best of the authors’ knowledge, this study constitutes the first attempt to integrate the CP, TDC and destination management information systems research streams to elaborate an integrative conceptual framework of TDCP. Second, the authors contribute to the Industry 4.0 research stream by examining the drivers of tourism destination CP in the context of the ongoing 4th industrial revolution. Third, the authors contribute to the destination management information systems research stream by introducing and conceptualizing the DBIU and the related sustained destination business intelligence

GOMS-based User Experience for Cultural Tourism Application in Indonesia

Indonesia's diverse cultural heritage presents an opportunity for tourism, yet traditional approaches and insufficient technology utilization hinder its full potential. We propose the development of a Cultural Tourism Application, specifically targeting the rich cultural attractions of Yogyakarta, Indonesia. The research develop the GOMS (Goals, Operators, Methods, and Selection Rules) model to design user-friendly interfaces for discovering cultural attractions, providing detailed information, searching, and exploring historical timelines and helped us understand the steps and knowledge required for users to achieve their goals within the app This model allows for a systematic understanding of user interactions and cognitive processes within the context of the Cultural Tourism Application. A User Acceptance Testing (UAT) survey reveals a high level of acceptance 91.2% for the Cultural Tourism Application, signifying its effectiveness in enhancing learnability, efficiency, memorability, safety, and overall user satisfaction

Main contribution of iconic attractions towards increasing popularity of tourism destinations: an analysis of twitter posts and locations

The social media platforms, due to their universal and comfortable interface, have become the real enablers of a microblogging services. Moreover, with the evolution of online reviews, consumers feel comfortable to express their opinions and share their personal experiences not only about the brands, but also about the travel destinations. Henceforth, social networks such as, Twitter, became important source of information. In this study, author analyzes 4,000 Twitter posts about 2 popular and 2 less popular locations and associated derived sentiments. The study demonstrates that there is a certain difference in perception of locations with a different popularity rank. In terms of information exposure, more popular locations tend to have a higher message diffusion activity, with most of them being of neutral polarity. Additionally, results showed that negative affection is observed more for less popular locations, providing valuable insight for Destination Marketing Organizations. In addition, for both groups, role of followers’ base was ineffective, demonstrating that topic of message sentiment and diffusion are key in tourism domain. Thus, from a methodological point of view, the main contribution of this research is the usage of random and unstructured data in Twitter to the measurement of the perception of the potential visitors of tourist attractions based on the sentiment analysis of posts associated to them. From theoretical point of view, using the sentiment orientation, the study relates to the user exposure and affection of the iconic attractions by the perceived difference in their popularity in accordance with external destination ranking.As redes sociais, devido ao seu interface universal e confortável, tornaram-se reais facilitadores de serviços de microblogging. Por conseguinte, a evolução dos reviews on-line, conferiu aos consumidores maior conforto para expressar as suas opiniões e partilhar as suas experiências pessoais, não apenas sobre as marcas, mas também sobre os seus destinos de viagem. As redes sociais, como o Twitter, tornaram-se importantes fontes de informação. Neste estudo, o autor analisa os sentimentos derivados de 4.000 publicações do Twitter acerca de 2 locais turísticos mais populares e 2 menos populares. O estudo demonstra que há uma certa diferença na percepção dos locais em função do seu grau de popularidade. Em termos de exposição, os locais mais populares tendem a ter uma maior atividade de difusão nas suas mensagens, sendo a maioria delas de polaridade neutra. Adicionalmente, os resultados mostraram que o sentimento negativo é mais partilhado em locais menos populares, fornecendo informações valiosas para Organizações de Marketing. Não obstante, para ambos os grupos, a dimenção da base de seguidores foi irrelevante, demonstrando que o tema da mensagem sentimento e difusão são fundamentais no domínio do turismo. A nível metodológico, o principal contributo desta pesquisa é a análise do sentimento de dados aleatórios e desestruturados do Twitter para a medição da percepção acerca de atracções turísticas com base na. Do ponto de vista teórico, o estudo relaciona-se com a exposição do usuário e o sentimento das atrações icônicas pela diferença percebida na sua popularidade de acordo com um ranking de destinos externo

Building online employability: a guide for academic departments

This guide will help academic departments to support students to think about their careers and to use the online environment wisely. Used badly the array of social media and online technologies can seriously disadvantage a students’ career development, but if used well they can support students to find out about and transition into their future career.This work was funded by the University of Derby’s Research for Teaching and Learning programme

Enhancing travel recommendations: Ai-driven personalization through user digital footprints

Esta tesis tiene como objetivo examinar la manera en que la huella digital que dejan los usuarios en internet puede utilizarse para optimizar la personalización de los servicios turísticos, mediante el uso de inteligencia artificial. El documento propone que el auge de la inteligencia artificial ha abierto un mundo de oportunidades para desarrollar nuevas herramientas para mejorar la experiencia de viaje digital. El enfoque se basa en la idea de que las huellas digitales son únicas y particulares de cada individuo y estos valiosos datos pueden dar lugar a sugerencias de viaje más inteligentes y certeras. Se consideran las actitudes de comportamiento del usuario, como la influencia del contenido generado por el usuario en las redes sociales y el boca a boca electrónico en el proceso de planificación del viaje, así como las implicaciones de este rastro de datos en la optimización de los servicios de viaje personalizados. Este modelo describe la relación entre la inteligencia artificial y la hiper personalización de servicios. Como es una tendencia creciente que está alterando nuestra realidad actual, la tesis presentada desarrolla una aplicación de viajes a medida que, con el permiso del usuario, aprovecha los datos recopilados de las redes sociales personales para construir un plan de viaje específico basado en las preferencias individuales.This thesis aims to examine the way the digital footprint users leave behind can be utilized to optimize the personalization of tourism services, through the use of artificial intelligence. The paper proposes that the surge of artificial intelligence has opened a world of opportunities to develop new tools to improve the digital travel experience. The approach is based on the idea that digital footprints are unique and particular to each individual and this valuable data can result in smarter and unerring travel suggestions. Behavioral attitudes of the user, such as the influence of user-generated content in social media and e-word of mouth in the travel planning process, are considered, as well as the implications of this data trail in the optimization of customized travel services. This model describes the relationship between artificial intelligence and hyper-personalization of services. As it is a growing trend that is disrupting our current reality, the presented thesis develops a tailor-made traveling application that, with permission of the user, leverages the data collected from personal social media to build a specific travel plan based on each user’s preferences