Purpose: This study, a conceptual paper, analyses the growth of curation in tourism and hospitality and the curator role in selecting and framing products and experiences. It considers the growth of expert, algorithmic, social and co-creative curation modes and their effects. Design/methodology/approach: Narrative and integrative reviews of literature on curation and tourism and hospitality are used to develop a typology of curation and identify different curation modes. Findings: Curational techniques are increasingly used to organise experience supply and distribution in mainstream fields, including media, retailing and fashion. In tourism and hospitality, curated tourism, curated hospitality brands and food offerings and place curation by destination marketing organisations are growing. Curation is undertaken by experts, algorithms and social groups and involves many of destination-related actors, producing a trend towards “hybrid curation” of places. Research limitations/implications: Research is needed on different forms of curation, their differential effects and the power roles of different curational modes. Practical implications: Curation is a widespread intermediary function in tourism and hospitality, supporting better consumer choice. New curators influence experience supply and the distribution of consumer attention, shaping markets and co-creative activities. Increased curatorial activity should stimulate aesthetic and stylistic innovation and provide the basis for storytelling and narrative in tourism and hospitality. Originality/value: This is the first study of curational strategies in tourism and hospitality, providing a definition and typology of curation, and linking micro and macro levels of analysis. It suggests the growth of choice-based logic alongside service-dominant logic in tourism and hospitality.
MULTIFILE
Algorithmic curation is a helpful solution for the massive amount of content on the web. The term is used to describe how platforms automate the recommendation of content to users. News outlets, social networks and search engines widely use recommendation systems. Such automation has led to worries about selective exposure and its side effects. Echo chambers occur when we are over-exposed to the news we like or agree with, distorting our perception of reality (1). Filter bubbles arise where the information we dislike or disagree with is automatically filtered out – narrowing what we know (2). While the idea of Filter Bubbles makes logical sense, the magnitude of the "filter bubble effect", reducing diversity, has been questioned [3]. Most empirical studies indicate that algorithmic recommendations have not locked large audience segments into bubbles [4]. However, little attention has been paid to the interplay between technological, social, and cognitive filters. We proposed an Agent-based Modelling to simulate users' emergent behaviour and track their opinions when getting news from news outlets and social networks. The model aims to understand under which circumstances algorithmic filtering and social network dynamics affect users' innate opinions and which interventions can mitigate the effect. Agent-based models simulate the behaviour of multiple individual agents forming a larger society. The behaviour of the individual agents can be elementary, yet the population's behaviour can be much more than the sum of its parts. We have designed different scenarios to analyse the contributing factors to the emergence of filter bubbles. It includes different recommendation algorithms and social network dynamics. Cognitive filters are based on the Triple Filter Bubble model [5].References1.Richard Fletcher, 20202.Eli Pariser, 20123.Chitra & Musco, 20204. Möller et al., 20185. Daniel Geschke et al, 2018
In today’s era of content abundance, education has to deal with changed practices for the dissemination of knowledge. Many digital resources are available, and they have the potential to take the place of textbooks. ‘The role of the classic textbook as the key, immutable reference point for any class subject, is rapidly fading’, says Good (2016). Educational publishers like Pearson see a decline in textbook use (Sweney, 2017), and a study at a Dutch university of applied sciences (Leighton, 2015) indicates that lecturers in higher education move away from core textbooks towards a variety of materials, including powerpoint slides, websites, and videos. Baron & Zablot (2015) complement this, saying ‘teachers now have the possibility to create and modify resources’. This development carries the risk that the structure, continuity and coherence textbooks are supposed to provide (Littlejohn, 2011), disappear. One could argue that when structure and coherence disappear from learning materials, the quality of education is at risk. To make the most of (digital) materials that teachers select, they must be organized well (Deschaine & Sharma, 2015). In order to do that, lecturers will have to act as skilled curators when selecting and structuring learning materials. Central in the concept of curation is that it goes beyond selection: providing coherence and context is what sets out curation from mere selection (Bhaskar, 2016). Considered from the perspective of teaching, curating means selecting and structuring learning content for students, while also providing them with context and coherence. The notion of lecturers as curators has been discussed by Siemens (2008), who describes the changing roles of lecturers and identifies ‘curational educators’ as those who ‘acknowledge the autonomy of learners, yet understand the frustration of exploring unknown territories without a map’. So far, the literature mainly focusses on providing students with curational skills, since these are important 21st century and media literacy skills (e.g. Jenkins et al., 2009; Potter, 2012). Little empirical research has been done when it comes to curational roles of lecturers. This proposed poster provides a mixed-methods research design for a PhD study.
