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Content uploaded by Timothy Jung
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All content in this area was uploaded by Timothy Jung on Jan 05, 2018
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Determining Visitor Engagement through Augmented Reality at Science Festivals: An
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Experience Economy Perspective
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Authors
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M. Claudia tom Dieck, Ph.D.
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Research Associate
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Faculty of Business and Law,
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Manchester Metropolitan University
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Righton Building, Cavendish Street, Manchester M15 6BG, UK
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Email: c.tom-dieck@mmu.ac.uk, Tel: +44 161-247-2729
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Timothy Jung, Ph.D.*
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Reader
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Faculty of Business and Law
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Manchester Metropolitan University
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Righton Building, Cavendish Street, Manchester M15 6BG, UK
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Email: t.jung@mmu.ac.uk, Tel: +44 161-247-2701
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Philipp A. Rauschnabel, Ph.D
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Assistant Professor
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College of Business, Department of Management Studies
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Fairlane Center South, 19000 Hubbard Drive
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Dearborn, Michigan 48128-1491, USA
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Email: prausch@umich.edu, Tel: +1 313-593-5109
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15 November, 2017
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Exclusively Submitted to Computers in Human Behavior
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*Corresponding author
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Determining Visitor Engagement through Augmented Reality at Science Festivals: An
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Experience Economy Perspective
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Abstract
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Augmented reality (AR) has been increasingly implemented to enhance visitor experiences, and
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tourism research has long understood the importance of creating memorable experiences, leading
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to the research era of experience economy. Although technology-enhanced visitor engagement is
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crucial for science festivals, research focusing on visitor engagement through AR using the
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experience economy perspective is limited. Therefore, the aim of this study is to examine how the
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educational, esthetics, escapist and entertainment experience using AR affect visitor satisfaction
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and memorable experience, and eventually, lead to visitor engagement with science experiences
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in the context of science festivals. A total of 220 data inputs were collected as part of the European
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City of Science festivities and Manchester Science Festival 2016 and analyzed using structural
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equation modelling. Findings show that the four realms of experience economy influence
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satisfaction and memory and, ultimately, the intention for visitor engagement with science research
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at science festivals. Theoretical contributions and practical implications are presented and
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discussed.
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Keywords: Augmented reality, science festivals, visitor engagement, experience economy,
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satisfaction, memory
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1. Introduction
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Festivals are considered one of the key activities that boost visitor economy, and many cities
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around the world use festivals to attract visitors. According to Bultitude et al. (2014), science
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festivals are particularly common within Europe and a driver for international and domestic
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tourism activities. Research has shown that achieving visitor engagement is critical for any festival
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in order to be successful and sustainable (Stilgoe et al., 2014). In particular, “science festivals have
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expanded in size and number over the recent years as a form of public engagement” and “public
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engagement has become the new mantra” in Europe (Jensen & Buckley, 2014, p. 558). The main
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objectives of science festivals include the celebration of science and engaging of non-specialist
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audiences (Bultitude et al., 2014). Technology was found to be a solution in order to facilitate the
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engagement of visitors. One of the more recent technologies on the market is augmented reality
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(AR) which is the overlay of digital content into users’ immediate surroundings, “allowing users
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to explore the surrounding environment by using mobile technologies” (Georgiou & Kyza, 2017,
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p. 24). Benefits of AR in terms of visitor engagement, immersion, and education make it a
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promising technology to engage visitors in science as part of their visit to science festivals
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(Altimira et al., 2017; Georgiou & Kyza, 2017). In fact, the main criticism of science festivals
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from the perspective of visitor engagement are 1) that they often neglect underrepresented
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audiences, and 2) that they preach to the already converted, as visitors are generally well-educated
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and interested in the themes (Bultitude, 2014). In order to overcome these potential issues in
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relation to engagement activities, technology-enhanced visitor engagement is considered as
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crucial, particularly for science festivals (Stilgoe et al., 2014). New and emerging digital
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technologies, such as AR, have been used for the enhancement of visitor experiences (Moorhouse
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et al., 2017). However, there is only limited research on technology-enhanced visitor engagement
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using AR in the context of science festivals.
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Recently, research started to use the framework of the Experience Economy by Pine and Gilmore
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(1998) as a theoretical foundation to explore the effects of AR (Jung et al., 2016; Neuburger &
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Egger, 2017). It includes the four realms of experience, educational, esthetics, escapist and
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entertainment. This research direction is very valuable within the context of visitor economy
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considering the importance of enhancing the visitor experience through various forms of
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interaction in order to increase or sustain tourist numbers, enhance the level of engagement, and
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generate positive word-of-mouth to ensure future sustainability. Pine and Gilmore’s Experience
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Economy model is considered to be the predominant framework within the subject area of visitor
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experiences (Jung et al., 2016). Rather than simply providing products and services, Pine and
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Gilmore (1998) emphasized the importance of staging experiences. Within the service-driven
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tourism domain, many scholars have supported the importance of tourist participation for the co-
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creation of value (Sorensen & Jensen, 2015).
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Although numerous scholars (e.g., Manthiou et al., 2014; Mehmetoglu and Engen, 2011; Oh et al.,
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2007) applied the Experience economy framework in other tourism and hospitality contexts,
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several limitations remain. First, prior research conceptualized the four dimensions as independent
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constructs or as a higher order constructs. In this study, we provide arguments for a process view.
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In particular, we argue that “the first impression matters” – that esthetics are the source of
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experience, resulting in an increase in educational, escapist and entertainment. Second, prior
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research has mostly applied experience economy to explain established constructs, such as loyalty
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(e.g. Manthiou et al.; 2014). This study complements prior research with a novel and managerially
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highly target construct: Visitor engagement. Finally, despite the general consensus that experience
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economy provides numerous advantages to media and tourism research, and scholars agree that
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science festivals are an important subject to study, empirical applications remain of experience
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economy remain scarce.
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In order to achieve the aim of this study we proposed a theoretical model grounded in the
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experience economy literature. To test the model, a total of 220 data were collected as part of the
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European City of Science festivities and Manchester Science Festival 2016 and analyzed using
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structural equation modelling. The findings offer a number of contributions to the literature. On
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the one hand, findings show that esthetics is a strong predictor of escapism, education, and
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entertainment within the AR science festival context. Therefore, this study shows that the
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experience economy concept in the context of AR applications does not consist of four
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independent dimensions. On the other hand, this study found that the remaining three realms of
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the experience economy influence visitors’ satisfaction and memories of the AR science festival
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experience which ultimately influences visitors’ engagement.
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2. Theoretical Background
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2.1 Augmented Reality and Visitor Experience
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AR is the digital overlay of information into users’ direct surroundings using devices such as
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smartphones or wearable smart glasses (Jung et al., 2015; Kalantari & Rauschnabel, 2017;
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Tussyadiah et al., 2017). AR is a source of technological innovation (Neuhofer et al., 2012); if
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implemented correctly, destinations can effectively obtain a competitive advantage and attract new
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markets (Tscheu and Buhalis, 2016). The creation of mobile AR is especially considered to be
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attractive, as visitors can use applications on their smartphones, reducing the barrier to engage and
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adopt (Han et al., 2014; tom Dieck and Jung, 2015). For example, visitors can hold their
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smartphone with an AR app against a building and receive relevant information. Likewise, visitors
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of museums can look at exhibits through an AR app and learn more about them. These two example
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applications reflect conclusions of prior research that this cutting-edge technology can enhance
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and add value to the overall visitor experience, provide a motivation to visit, and generate positive
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word-of-mouth (Morrison, 2013). At attractions, visitors can instantly access and unlock historic
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knowledge and reveal hidden stories, whilst avoiding interrupting or overcrowding the physical
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space (Molz, 2012). This effectively bridges the gap between exploring innovative technologies
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and personalized experiences, as visitors can tailor the experience and explore and discover
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personal points of interest (Neuhofer et al., 2015). In addition, the overlay of 2D and 3D graphics
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engages the user (Wu et al., 2013) and encourages new and innovative ways of learning
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(Moorhouse et al., 2017). Overall, AR can enhance the attractiveness of destinations when
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marketed effectively by destination management organisations (Tscheu and Buhalis, 2016), as it
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can create a unique and memorable experience for visitors (Jung and tom Dieck, 2017).
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Nevertheless, according to Rauschnabel et al. (2017), AR acceptance remains a challenge and is
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under-researched, and must be overcome by lower complexities in the design and implementation
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process (Wu et al., 2013).
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2.2 Experience Economy
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To understand AR, researchers have applied numerous theories in different study contexts. Studies
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with a focus on the device itself have applied technology acceptance theories (e.g. Rauschnabel &
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Ro, 2016). In contrast, other research has highlighted a theoretical framework termed ‘experience
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economy’ (Pine & Gilmore, 1998). Research has long understood the importance of creating
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memorable experiences (Kang & Gretzel, 2012; Park et al., 2010; Quan & Wang, 2004) and,
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therefore, the move from the service economy to the experience economy comes as no surprise
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(Knutson et al., 2010).
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The initial idea of the experience economy proposed four realms of consumer experiences based
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on two dimensions: involvement, ranging from passive to active participation of the consumer,
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and the desire, ranging from absorption to immersion, within which a consumer engages with a
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consumption object. The experience economy suggests that there are four realms of an experience,
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as displayed in Figure 1, which can be classified by a spectrum of connection (immersion and
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absorption) along the vertical, and a spectrum of participation (active and passive)) along the
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horizontal line of the model (Pine & Gilmore, 1998). According to Quadri-Felitti and Fiore (2013,
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p. 48), “active participation is where customers personally affect the performance or event, and
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passive participation is where customers do not directly affect or influence the performance. In
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addition, immersion is described as becoming physically or virtually enveloped by the event […]
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whereas absorption involves engaging the consumer’s mind”.
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Fig. 1. Experience Economy (Pine & Gilmore, 1998)
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Within the educational realm, visitors are actively engaged in tourism activities to gain new skills
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and knowledge (Oh et al., 2007). A number of previous studies have confirmed the role of AR as
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an effective tool for education, supporting its strength in creating interactive content that is easy
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to remember (e.g. Moorhouse et al., 2017; tom Dieck et al., 2016). As part of the entertainment
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experience, Jung et al. (2016) proposed that users utilize applications for an enjoyable experience.
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Based on the Experience Economy model, this enjoyable and entertaining experience is in the form
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of a more passive delivery of content (e.g. movies). Escapism is the third realm of experience and
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refers to visitors’ active participation in the delivery of products and services as well as visitors’
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willingness to momentarily forget happenings within their normal lives by fully immersing in the
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experience (Song et al., 2015). Finally, esthetics were originally proposed to reflect visitors’ full
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immersion within an experience that does not interact with them (Pine & Gilmore, 1998).
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Considering the importance of immersion as part of an AR experience, Jung et al. (2016) argued
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that escapism and esthetics become increasingly more important with the emergence of AR
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applications. Scholars from various disciplines have adopted the idea and applied it to numerous
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contexts (see Table 1).
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Study
Research Question/Aim
Context
Sample and
Methods
Conceptualization
of Experience
Economy
Findings relevant to the study
context / this study’s
contribution
Hosany &
Witham
(2009)
Development of a
measurement scale for
tourist experience
Cruise
Tourism
N=169,
Confirmatory
factor
analysis and
regression
analysis
On one level
The study provides a
measurement scale for the
experience economy
dimension. Results generally
reveal homological validity
Jung et al.
(2016)
Explore if experience could
be enhanced by social
presence in the mixed
reality environment and
further inducing revisit
intention to visitor
attraction
AR and
VR in
Museums
N=163, PLS
On one level
Social presence impact
experience economy
constructs
Only Education and
Entertainment drive the
overall tour experience
Loureiro
(2014)
Explore
the
effect
of
Experience economy on
place
attachment
and
intention
Rural
tourism
N=222., PLS
Higher order
construct
The correlation matrix
suggests that the strength of
the experiences differ
between target constructs,
indicating that each
dimension behaves
differently in the context.
Manthiou et
al. (2014)
Explore visitor experiences
to understand future
behaviour
Festival
Marketing
N=338, SEM
On one level
Four experience realms result
in an optimal experience,
influencing vividity as a
mediating and loyalty as a
dependent variable.
Mehmetoglu
& Engen
(2011)
Explore how different
experiential dimensions
influence satisfaction
Museum
and
Festival
N=75 and
N=117, PLS
SEM,
On one level
Mixed findings depending on
the context and target
variable
Oh et al.
(2007)
Development of a scale and
assessing its nomological
validity
Hotel
industry
N=419, CFA
and
correlation
On one level
Measurement scale that is
correlated with Arousal,
Memory, Quality, and
Satisfaction; no regression-
based results are presented.
This study
Explore the effect of AR
experience influence on
visitors’ engagement with
science experience
AR for
science
festivals
N= 220,
SEM
Mediating
structure, where
esthetics drive
entertainment,
education and
escape, which the
subsequently
impact outcome
variables
We show that experience
economy constructs are not
independent from each other,
but represent a networked
structure.
Experience economy
constructs play an important
role in explaining visitors’
reactions on AR apps
Table 1. Summary of previous studies
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While the flexibility is a major strength of the experience economy framework, it is also associated
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with a number of concerns, ranging from criticism on the conceptualization to lack of measurement
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challenges. While addressing the measurement challenges of each of the four experiences have
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been subject to numerous studies (e.g. Oh et al., 2007; Hosany & Witham, 2009), the overall
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conceptualization provides some unanswered questions. For example, whereas Pine and Gilmore
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(1998) argued that the interaction of two dimensions, involvement and desire, are sufficient to
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generate four types of experience, other studies, especially in the tourism context, have found that
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each of the four experiences should either serve as individual dimensions, or be treated as a higher-
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order construct (e.g. Loureiro, 2014). However, as shown in Table 1, studies that compared the
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effects of each of the four constructs on target variables often concluded that only a few of them
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matter. An inspection of the correlations between the factors indicates meaningful correlations
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between all four variables, indicating that – contrary to Pine and Gilmore (1998)’s framework –
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the four constructs are not independent of each other. This study aims to extend prior research on
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experience economy in several ways.
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As presented in Table 1, the majority of studies (Hosany & Witham, 2016; Jung et al., 2016;
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Mehmetoglu & Engen, 2011; Oh et al., 2007) tested the experience economy constructs on one
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level and supported the effects of all or some of the four constructs on the experience within
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various tourism-related contexts. For instance, Jung et al. (2016) failed to find a significant relation
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of esthetics onto the overall experience, raising the question of the appropriateness of seeing or
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applying each construct on one level. In addition, none of the studies incorporated the effects of
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the experience economy constructs on satisfaction, memory and ultimately visitor engagement.
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Thus, the aim of this study is to address this gap in the literature as follows. First, this study aims
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to apply the experience economy framework to investigate factors relating to visitor engagement
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in the context of science festivals. Second, this research assesses the mediation effects of memory
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and satisfaction in the experience economy – engagement relationship. Finally, this study proposes
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a novel view on the interplay of the experience economy constructs. Rather than stating that each
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of the four realms is independent from each other or that all together reflect a higher order
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construct, we propose a mediating structure.
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3. Proposed Model
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Figure 2 shows the basic theoretical framework of this study. First, we propose that visitors’ actual
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use of an AR device triggers the constructs of the experience economy framework, whereas – in
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contrast to prior research (see Table 1) – we provide a more nuanced relationship between the four
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constructs. Second, we propose that experience economy constructs determine visitors’ overall
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evaluation of the on-site AR experience. In particular, we propose that the experience economy
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serves how much people enjoyed using the AR experience (satisfaction), but also to what extend
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the experience stays in their mind (memory). Third, the model proposes that satisfaction and
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memory both impact visitor engagement, a crucial, yet under-researched, construct in tourism
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research.
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Fig. 2. Proposed Model
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3.1 Experience Economy
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Research in numerous domains has shown that visible cues are the first cues that people use to
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make judgments about people and things. For example, when interacting with other people,
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physical cues (e.g. face, cloths etc.) are among the first cues people use to judge a persona, such
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as sympathetic, smart, etc. Similarly, when using a new software, one of the first users incorporate
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into their decision making is the design of the user interface. We argue that this general finding is
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also relevant in the creating of visitor experience.
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In a related context, Pallud and Straub (2014) show that aesthetics represent the most important
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criteria for interface development, which ultimately dictates whether visitors accept or reject latest
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technologies. In particular, especially when technologies become more immersive, both Jung et al
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(2016) and Lee et al. (2015) argue that interface design becomes even more relevant than in less
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immersive contexts. Tourism scholars, such as Hosany and Witham (2009) or Mykletun & Rumba
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(2014) even argue that esthetics are among the most important drivers within the experience
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economy. Likewise, Jung et al. (2018)’s cross-cultural study on AR concludes that esthetics are
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particularly relevant since it can compensate for technological limitations of many current AR
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devices. Consequently, this means that if esthetics of an experience are low, the educational,
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entertainment, and escapism experiences are likely to suffer. On the other hand, once users are
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exposed to a favourable esthetics experience, this should translate to higher levels of education
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(H1a), entertainment (H1b) and escapism (H1c) dimension. This is a different conceptualization
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of most prior studies (see table 1). In particular, most prior studies implicitly assume, for example,
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that users rate the escapism value of apps independently of their estethic experience. Simplified
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speaking, this would imply that the escapism experience would not suffer if an app was poorly
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designed (Jung et al., 2018). This assumption would also imply that poorly designed apps provide
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the same educational and entertainment experience than well-designed ones, assumptions that
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prior theory and reported correlations might question. Thus, we propose esthetics as a determinant
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of the remaining three experience constructs and, thus, the following is hypothesized:
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H1a: Esthetics has a positive effect on education.
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H1b: Esthetics has a positive effect on entertainment.
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H1c: Esthetics has a positive effect on escapism.
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3.2 Experience Economy and Satisfaction
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According to Srivastava and Kaul (2014, p. 1028), satisfaction can be defined as “consumer
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judgment that a product or service provides a pleasurable level consumption-related fulfilment”,
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which has long been discussed as an important determinant of behavioral intentions within
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technology adoption research (e.g. tom Dieck et al., 2017). According to Mehmetoglu and Engen
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(2011), experiences allow people to draw upon the events to paint a picture of their lives. They
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allow for an evaluation of an individual’s perception of his or her self-image, which is the
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aggregation of his or her lifetime experiences. Following this logic, Mehmetoglu and Engen (2011)
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argued that individual experiences are highly important for consumers’ views and satisfaction of
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products or services. Furthermore, as part of the experience economy, there has been sufficient
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evidence of strong impacts of the realms of experience economy on satisfaction. For instance, the
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effect of education and entertainment onto tourist satisfaction within the film festival context was
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supported by Park et al. (2010), and Quadri-Felitti and Fiore (2013) confirmed that education
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strongly affects satisfaction within the tourism context. Consequently, this study proposed that:
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H2a: Education has a positive effect on satisfaction.
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H2b: Entertainment has a positive effect on satisfaction.
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H2c: Escapism has a positive effect on satisfaction.
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3.3 Experience Economy and Memory
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Studies have long acknowledged the importance of experiencing events and the consequent
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creation of memories (Pine & Gilmore, 1998). In fact, das Gupta et al. (2016, p. 1278) revealed
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“for many consumer-intensive (B2C) services, delivering memorable customer experiences is a
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source of competitive advantage”. According to Manthiou et al. (2014), an experience involves
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the input of information into the sensory system of an individual’s brain. Consequently, a memory
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is what remains of an event after the sensory experience occurred, making it an integral part of any
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experience framework.
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In the context of the experience economy, it is, therefore, proposed that the experiences is
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considered the cause, and the memory is considered the effect (Manthiou et al., 2014). This was
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confirmed by Pine and Gilmore (1998), who revealed that an optimal experience should lead to
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enhanced memories. Kahneman (2011, p. 388) strengthened that “tourism is about helping people
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construct stories and collect memories”. This was supported by Ali et al. (2014), who found that
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tourists’ experiences revolving around the four realms of the experience economy result in strong
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memories and positive behaviors. Similar findings were determined in other tourism contexts, as
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Loureiro (2014) as well as Quadri-Felitti and Fiore (2013) tested the effect of experience economy
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onto memory within the festival and wine tourism context, and found that the educational
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experience significantly influenced memory. Entertainment was found to significantly influence
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memory by Mykletun and Rumba (2014). Therefore, it is proposed that:
310
311
H3a: Education has a positive effect on memory.
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H3b: Entertainment has a positive effect on memory.
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H3c: Escapism has a positive effect on memory.
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3.4 Satisfaction, Memory, and Visitor Engagement
316
It has been well-recognized that satisfaction and positive memories influence behavioral intentions
317
within technology adoption literature (Wixom & Todd, 2005), particularly within the tourism
318
context (Ali et al., 2014; Ali et al., 2016; Hosany & Witham, 2009; tom Dieck et al., 2017).
319
However, the direct comparison of these two crucial concepts, as well as their interaction, remains
320
an under-researched area. As we propose and empirically validate, maximising both concepts
321
might – counterintuitively – not be a desired strategy for tourism managers. There are several ways
322
to measure behavioral intention within the technology adoption research stream. A number of
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studies have focused on the intention to use technology that is relatively new on the market
324
(Rauschnabel & Ro, 2016), continued usage intentions (tom Dieck et al., 2017), intention to
325
recommend (Prayag et al., 2017) or loyalty (Valle et al., 2006). However, studies focusing on the
326
intention for visitor engagement is scarce, and the overall area is highly under-researched.
327
Nevertheless, as previously discussed, visitor engagement with particular themes within a
328
destination can be considered extremely valuable in order to provide a unique, educational, and
329
memorable visitor experience. Thus, we propose:
330
331
H4: Satisfaction has a positive effect on visitor engagement.
332
H5: Memory has a positive effect on visitor engagement.
333
334
4. Methods
335
4.1 Study context
336
The study was conducted as part of the European City of Science (ECOS) festivities and
337
Manchester Science Festival in Manchester, UK, in 2016. Among other ECOS initiatives, a mobile
338
AR application (see Fig. 3) was developed in order to provide visitors to Manchester with an
339
enhanced experience. In particular, the app provided information on ECOS events and the history
340
of science in Manchester. Furthermore, one of the functionalities of the application was related to
341
AR. iBeacons were located around the city centre, and whenever a visitor walked near a beacon,
342
the app notified him about the opportunity to learn something new about Manchester science when
343
scanning a certain object. These objects varied from statues to buildings or simply plaques. Once
344
a visitor located and scanned such an object, information in form of audio, video, animation (see
345
Fig. 4 Pokémon animation of scientist Prof. Brian Cox), or text were overlaid into visitors’
346
immediate surroundings, representing the AR element of the application.
347
348
349
Fig. 3. ECOS Mobile Application
350
351
352
4.2 Data Collection
353
Questionnaires were collected as part of the ECOS festivities and Manchester Science Festival
354
between July and December 2016. Data were collected from visitors who experienced the mobile-
355
based AR application in the city centre of Manchester as part of their visit to the city. It is important
356
to note that these tourists did not actively attend the science festival, but were visiting Manchester
357
during the period. Random sampling was used and a total of 220 usable data inputs were collected.
358
Shenton (2004) revealed that a random sampling technique increased the representativeness of a
359
sample, as it includes the opinion of a general population rather than a selected sample. The
360
researchers approached every 10th visitor as part of the random sampling technique in front of the
361
Central Library, one of the major squares of the city and a focal visitor point for tourists coming
362
to Manchester. Prior to participation, participants were asked if they were tourists in Manchester,
363
and only those confirming were selected. The study was designed as a science tour and prior to
364
filling in questionnaires, tourists were asked to experience four different sites, including buildings,
365
monuments, or statues in close proximity that provided AR content, triggered by iBeacons. The
366
average tour lasted approximately 30 minutes. Participants were provided with Android phones
367
and a map that showed AR-enabled sites by the researcher in order to ensure that every participant
368
had the same experience. However, all the participants took part in the tour on their own.
369
370
371
Fig. 4. Animation within AR application
372
373
374
5. Results
375
5.1 Profile of Participants
376
Participants’ profiles are shown in Table 2. There were slightly more males (56.4%) than females
377
(43.6%). The majority of respondents was aged between 18 and 24. Almost half of participants
378
had an undergraduate degree (45.5%), followed by postgraduate degree (27.7%) and A-levels
379
(16.4%). With regards to income level, less than £20,000 was mostly represented (51.8%), and
380
more than half or respondents were students (57.3%).
381
382
Characteristics
N
%
Characteristics
N
%
Gender
Income
Male
124
56.4
Less than £20,000
114
51.8
Female
96
43.6
£20,000-£40,000
66
30.0
Age
£40,000-£60,000
24
10.9
18-24
128
58.2
£60,000-£80,000
9
4.1
25-34
54
24.5
£80,000-£100,000
0
0.0
35-44
16
7.3
£100,000+
7
3.2
45-54
15
6.8
Occupation
55-64
4
1.8
Full-time employed
74
33.6
65+
3
1.4
Part-time employed
15
6.8
Education
Self-employed
3
1.4
No Formal Qualification
4
1.8
Housewife/husband
0
0.0
GCSE/O-level
4
1.8
Unemployed
2
0.9
A-level
36
16.4
Retired
0
0.0
Undergraduate Degree
100
45.5
Student
126
57.3
Postgraduate Degree
61
27.7
Doctoral Degree
13
5.9
Professional Degree
2
0.9
Total
220
100%
Table 2. Participants Profile
383
384
5.2 Measures
385
All constructs (see appendix for definitions) were measured by three to four measurement items
386
and ranked on a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The
387
measurement items were adapted from established reflective multi-item construct scales from
388
previous literature (Loureiro, 2014; Manthiou et al., 2014; Mehmetoglu & Engen, 2011; Oh et al.,
389
2007; Quadri-Felitti & Fiore, 2013). We inspected the psychometric characteristics of the
390
measurement instrument using a series of exploratory and confirmatory factor analysis. Although
391
the χ2-value of 350.2 (df=209) was significant (p<.001), the χ2/df ratio of 1.7 was lower than 4 and,
392
thus, acceptable. In addition, the model fit (CFI=.95; TLI=.94; RMSEA=.06; SRMR=.05) reflects
393
absence of substantial approximation errors and shows no substantial differences between
394
observed and predicted correlation matrices. Then, we, assessed the psychometric characteristics
395
on a construct level. As shown in Table 3, all factor loadings are significant (p<.001) and above .70.
396
In addition, Cronbach’s alpha (α), Composite Reliability (CR), and Average Variance Extracted
397
(AVE) exceeded the recommended threshold of .7, .7, and .5, respectively. We assessed
398
discriminant validity using the Fornell and Larcker (1981) procedure. Evidence of discriminant
399
validity exists in the study, as AVE values all are above the squared construct correlations (Hair
400
et al., 2006) (see Table 4).
401
402
Constructs and Items
Mean
SD
CR
AVE
Esthetics (Loureiro, 2014; Manthiou et al., 2014;
Mehmetoglu & Engen, 2011; Oh et al., 2007; Quadri-
Felitti & Fiore; 2013)
0.83
0.63
0.83
The setting of the AR experience was very attractive
0.74
3.80
0.97
The AR experience was very pleasant
0.87
3.84
0.85
I felt a real sense of harmony
0.77
3.35
0.97
Education (Loureiro, 2014; Manthiou et al., 2014;
Mehmetoglu & Engen, 2011; Oh et al., 2007; Quadri-
Felitti & Fiore; 2013)
0.87
0.63
0.87
I learned something new during the AR experience
0.77
3.90
1.03
The experience made me more knowledgeable
0.76
3.75
1.03
It stimulated my curiosity to learn new things
0.78
3.86
0.95
It was a real learning experience
0.84
3.75
0.99
Entertainment (Manthiou et al., 2014; Mehmetoglu &
Engen, 2011; Oh et al., 2007; Quadri-Felitti & Fiore;
2013)
0.87
0.70
0.87
The AR experience was amusing
0.76
3.83
0.97
The AR experience was entertaining
0.83
3.94
0.92
The AR experience was fun
0.91
3.91
0.93
Escapism (Loureiro, 2014; Manthiou et al., 2014;
Mehmetoglu & Engen, 2011; Oh et al., 2007; Quadri-
Felitti & Fiore; 2013)
0.92
0.73
0.92
I felt I played a different character when using the AR
application
0.86
2.73
1.19
I felt like I was living in a different time or place
0.83
2.71
1.19
The AR experience let me imagine being someone else
0.92
2.59
1.23
I completely escaped from reality
0.82
2.42
1.16
Memories (Loureiro, 2014; Oh et al., 2007; Quadri-
Felitti & Fiore; 2013)
0.90
0.75
0.89
I will have wonderful memories about this AR
experience
0.86
3.36
1.02
I won’t forget my experience of this AR experience
0.83
3.44
1.04
I will remember many positive things about this AR
experience
0.90
3.59
0.97
Satisfaction (Mehmetoglu & Engen, 2011; Quadri-
Felitti & Fiore; 2013)
0.87
0.70
0.87
I was satisfied with the overall AR experience
0.80
4.09
0.72
I was contented with the overall AR experience
0.86
3.82
0.78
I was delighted with the overall AR experience
0.85
3.82
0.81
Visitor Engagement (Criado & Such, 2011; Isiaq &
Jamil, 2017)
0.86
0.68
0.86
This experience has motivated me to find out more
about the history of science in Manchester
0.83
3.51
1.04
This experience has motivated me to find out more
about science research in Manchester
0.87
3.51
1.06
This experience has motivated me to participate in
science festival activities in Manchester
0.76
3.35
1.12
Table 3. Reliability and Cross-Loadings
403
1
2
3
4
5
6
1
Esthetics
2
Education
0.67
3
Entertainment
0.71
0.61
4
Escapism
0.60
0.36
0.40
5
Memory
0.60
0.54
0.49
0.42
6
Satisfaction
0.61
0.63
0.60
0.37
0.56
7
Visitor Engagement
0.55
0.53
0.42
0.36
0.45
0.58
All correlations are significant at p<.001
404
Table 4. Correlation and discriminant validity
405
406
5.3 Main Effects
407
Mplus 7.1 (Muthen & Muthen, 2012) was used to model the structural relationships proposed in
408
the hypotheses (see Figure 5). We applied the MLR estimator to estimate the model, a maximum
409
likelihood estimator with a robust error term. In survey research, common assumptions for
410
maximum likelihood estimators, such as multivariate Gaussian distribution or sample size, are not
411
given. Recent research shows that MLR outperforms traditional ML-estimators in these realistic
412
scenarios. Global fit measures of this main effects model indicate a good model fit (χ2=369.7;
413
df=218; CFI=.95; TLI=.94; RMSEA=.056; SRMR=.058).
414
415
416
417
418
Fig. 5. Structural Equation Model
419
420
421
Results indicate significant effects from esthetics on education (βH1a=.70; p<.001), entertainment
422
(βH1b=.73; p<.001), and escapism (βH1c=.59; p<.001). Thus, results support H1a, H1b, and H1c.
423
Next, we investigate the effects from the three endogenous experience economy variables on
424
satisfaction and memory. Results show significant effects for education (βH2a=.42; p<.001) and
425
entertainment (βH2b=.32; p<.001) on satisfaction, supporting H2a and H2b. Results for escapism
426
are in the proposed direction, (βH2c=.10; p=.14), but do not reach significance, rejecting H2c. These
427
variables together explain 49.4% of satisfaction’s variance. Memory, in contrast, is influenced by
428
education (βH3a=.36; p<.001), entertainment (βH3b=.20; p=.02), and escapism (βH3c=.22; p<.01)
429
supporting H3a, H3b, and H3c. These variables together explain 38.7% of memory’s variance.
430
Finally, we inspect the constructs that are hypothesized to relate to public engagement. In support
431
of H4 and H5, results show significant effects for satisfaction (βH4=.50; p<.001) and a partially
432
effect for memory (βH5=.17; p=.06). Both constructs explain 37.7% in consumers’ variation
433
regarding public engagement. Following recent recommendations in mediation research, we also
434
assessed the indirect effects. Therefore, we ran 10,000 bootstrap resamples and estimated the 95%
435
confidence intervals. A mediation effect is established if its confidence interval an indirect effect
436
does not include zero. Mediation was established for all indirect effects, except the
437
estheticsescapismsatisfaction link, where also H2c did not receive empirical support. Details
438
are presented in Appendix 2.
439
440
6. Discussion, Implications, and Limitations
441
The aim of this study was to examine how visitor experience using AR affect visitors’ satisfaction,
442
memory, and eventually visitors’ engagement with science experience in the context of science
443
festivals. The results showed that esthetics are a strong predictor of education, entertainment, and
444
escapism within the AR experience in the science festival context. Consequently, it can be argued
445
that AR experience design and the harmonious integration of content and features is critical in
446
order to provide visitors with an educational, enjoyable, and escaping experience. Theoretically,
447
this study shows that the experience economy in the context of AR applications and science
448
festivals does not consist of four independent dimensions. In comparison to previous studies (e.g.
449
Jung et al., 2016; Manthiou et al., 2014) that tested the experience dimensions on one-level (as
450
presented in Table 1) and, thereby, often failed to find all four experience dimensions significant,
451
the present study supported all four dimensions using a mediating structure. In fact, this study has
452
shown that esthetical design of the application drives the remaining experience economy
453
constructs, which is supported by previous research on the importance of AR user requirements in
454
terms of application design (tom Dieck et al., 2016).
455
456
In addition, this study supports that the remaining three realms of the experience economy
457
influence visitors’ satisfaction and positive memories of the AR science festival experience. This
458
ultimately influences visitors’ engagement with science. Considering the importance for cities to
459
engage visitors with their heritage, the use of AR was found to not only bring history to life, but
460
also actively engages visitors and facilitates the gathering of new information. This is especially
461
important considering that science festivals aim to engage a broader audience, and AR can be used
462
in order create awareness and public engagement among so far neglected audiences (Bultitude,
463
2014). For the visitors industry, AR provides an opportunity to create awareness of points of
464
interests that cities and destinations have to offer. In the future, applications do not need to be
465
limited to a science or history tour, but destinations could offer personalized tours to tourists based
466
on their interests and preferences. This shows the clear potential for destinations to utilize AR to
467
create unique selling points and memorable experiences, a key aim of Pine and Gilmore’s (1998)
468
framework.
469
470
6.1 Theoretical Contributions
471
This study has several theoretical contributions. The most important contributions are (1) a novel
472
conceptualization of experience economy, and (2) the identification of two routes how satisfaction
473
and memory compete in driving a third crucial variable in AR research: visitor engagement. We
474
will discuss each of these contributions in detail below.
475
476
Experience economy, in its initial article (Pine & Gilmore, 1998), was discussed as a new era of
477
consumption, replacing the age of functional benefits with experiences derived through
478
consumption. Research from various disciplines realized the potential of this new paradigm and
479
applied it in various settings. Through a review of literature, we identified numerous studies that
480
applied the concept of experience economy in related contexts (e.g. Hosany & Witham, 2009; Jung
481
et al., 2016). This review identified some inconsistencies, such as different conceptualizations,
482
inconsistent findings, and strong correlations between the four factors. Supplementing these
483
observations with technology and media research and incorporating basic human decision making
484
led to a novel conceptualization: The results support our theory that the elements of experience
485
economy – esthetics, education, entertainment, and escapism – are not ‘on the same level’. In
486
contrast, our findings suggest that AR experiences start with an assessment of the esthetics. The
487
assessment of the esthetics determines the magnitude of the remaining elements, namely
488
education, entertainment, and escapism. This is an important contribution for several reasons. For
489
example, as shown in Table 1, most prior experience economy studies concluded that only selected
490
variables matter. In this study, we show that all four experience economy constructs are relevant
491
within the AR context. However, the effect of esthetics is indirect, as mediated by education,
492
entertainment, and escapism. Prior research that modelled these factors on the same conceptual
493
level did not find these effects and, in addition, might have struggled with methodological issues
494
such as multicollinearity. Thus, by drawing on prior research on decision making in related
495
context, this study extends the understanding of experience economy specifically in the context of
496
AR, and likely also in other domains.
497
498
The second major contribution is grounded in the evaluation of the experience itself. While prior
499
research has typically relied on satisfaction or behavioral intentions, this study provides a more
500
nuanced assessment. In particular, we incorporated satisfaction and memory as direct
501
consequences of the experience and as mediators in the experience-behavior relationships. Only
502
few studies (e.g. Oh et al., 2007) have looked at the connection of experience economy to
503
satisfaction and memory, however, without the dependent variable of visitor engagement.
504
Considering the importance of engaging visitors in order to create memorable experiences, this is
505
an important dimension that has not been explored within previous experience economy studies.
506
Thus, this can be considered the main contribution to knowledge. Whilst all the experience
507
economy constructs showed at least weak effects on both constructs, we identified a series of
508
differences. For example, education showed the strongest effect, which is probably due to visitors’
509
expectations to learn something. This indicates that visitors who are actively engaged in science
510
festival activities gained new skills and knowledge (Oh et al., 2007). On the contrary, escapism
511
showed the weakest effect, which may be due to the fact that current AR application contains more
512
passive delivery of content (e.g. video clips of scientists). This implies that creation of interactive
513
AR contents for active participation of visitors as well as immersive experience are critical for
514
visitor engagement.
515
516
6.2 Practical Implications
517
Many practical implications were identified from this study. First, esthetics is an important
518
experience economy construct for AR experiences during science festivals, which clearly shows
519
the importance of interface within AR applications for festival managers and application
520
developers alike. Second, education, entertainment, and escapism experiences via AR have a
521
positive impact on satisfaction and memory. Consequently, AR experiences will bring more
522
memorable and satisfied visitor experience during science festivals. Therefore, festival organizers
523
and applications developers should design more informative, enjoyable, and immersive AR
524
experiences for science festival attendees. Third, science festival attendees will engage more when
525
they have AR-enhanced experiences that tell the hidden stories of science and scientists attached
526
to physical buildings, statues, and plaques. It is proven that AR experiences with place attachment
527
is an effective way of encouraging visitor engagement with science festivals. Finally, AR is a
528
useful tool to improve memory, which is particularly important for science festival attendees’
529
engagement; thus, AR applications should contain visually attractive and interesting hidden stories
530
for memorable experiences, which will have a higher impact on the success of science festivals.
531
Overall, the present study focused on science festivals however, findings are important for
532
managers from various disciplines that are involved in creating immersive, enjoyable and
533
educational experiences through immersive technologies. Manthiou et al. (2014) for instance
534
suggested that the four realms should act as guidelines as to how festivals should be organised and
535
where priorities need to be placed. From this, our findings suggest that the design of applications
536
acts as a stepping stone for creating entertaining, educational and immersive experiences that
537
ultimately lead to the engagement of audiences. Therefore, previous examples from museums,
538
schools and art galleries have shown the benefits of AR and our findings support the strength of
539
this new and innovative technology in order to create memorable and satisfying experiences and
540
support engagement. In fact, within the museum context, Lee et al. (2015) supported that the initial
541
impression of an application with regards to its esthetical features leads to hedonic motivations
542
and positive intentions to use the application in the future. The present study supports this finding
543
and emphasises on application design. In order to do so, app developers are advised to follow the
544
principles of the experience economy to ensure that content and functionalities result in the desired
545
outcome. A study on AR requirements within the tourism context supported the importance of the
546
four realms as tom Dieck et al. (2016) found that learning, hedonic features, comfort and
547
application quality are key requirements for AR applications. In addition, a recent study from a
548
festival found that the escaping from reality is one of the key advantages of using virtual
549
applications (Jung et al., 2017). Consequently, the four realms of the experience economy are
550
extremely important within the tourism context and science festival organisers are advised to
551
incorporate these characteristics into festival activities to ensure visitor engagement.
552
553
6.3 Limitations and Future Research
554
As with every study, there are several limitations that need to be addressed. The first limitation
555
relates to the data collection in only one city using one AR application, as it limits generalisation.
556
Therefore, more research should be conducted on AR science festival experiences in different
557
destinations. In addition, the present study was limited to the four realms of the experience
558
economy, and further factors affecting visitors’ satisfaction and memory of AR experiences and
559
intention to engage with science should be explored and tested. Therefore, a mixed-method study
560
should help to fully explore and validate determinants of visitor engagement. This is expected to
561
enhance the explanatory power and extend existing theories. Finally, as discussed in Table 1, most
562
prior research (and this study) has studied net-effects of the four experience economy constructs.
563
During the last years, scholars (e.g., Woodside, 2016; Kourouthanassis et al., 2017; Pappas et al;.,
564
2017; Woodside et al., 2015) have taken a different approach and studies suggest configuration
565
analyses as a potential alternative to the standard regression-based net effects models (e.g.
566
regression or SEM). The four constructs of experience economy could be combined with other
567
factors (e.g., personality, culture and so forth) to identify complex and asymmetric relations
568
between these constructs to explain desired outcomes
1
. This might lead to higher explanatory
569
power and deeper insights into the mechanisms that drive consumer reaction in AR. In addition,
570
the present study focused on visitor engagement from the tourists’ point-of-view, and further
571
research could explore the differences between domestic and international tourists with regards to
572
which factors influence the engagement with science. For destination marketing organizations, this
573
would provide important implications for AR application design and acceptance among diverse
574
types of users.
575
576
References
577
Ali, F., Hussain, K., & Ragavan, N. A. (2014). Memorable customer experience: examining the
578
effects of customers experience on memories and loyalty in Malaysian resort hotels.
579
Procedia-Social and Behavioral Sciences, 144, 273-279.
580
Ali, F., Ryu, K., & Hussain, K. (2016). Influence of experiences on memories, satisfaction and
581
behavioral intentions: A study of creative tourism. Journal of Travel & Tourism Marketing,
582
33(1), 85-100.
583
Altimira, D., Clarke, J., Lee, G., Billinghurst, M., & Bartneck, C. (2017). Enhancing player
584
engagement through game balancing in digitally augmented physical games. International
585
Journal of Human-Computer Studies, 103, 35-47.
586
Benny, L. K. W. (2015). Entertainment Studies–A Perspective. American International Journal of
587
Research in Humanities, Arts and Social Sciences, 7-11.
588
Bultitude, K. (2014). Science festivals: do they succeed in reaching beyond the'already engaged'?.
589
Journal of Science Communication, 13(4), 1-3.
590
Conway, M. A., Rubin, D. C., Spinnler, H., & Wagenaar, A. (2013). Phenomenal Experience in
591
Laboratory and Autobiographical Memory. Theoretical Perspectives on Autobiographical
592
Memory, 65, 31-51.
593
Criado, N., & Such, J. M. (2011, October). Preparing students for group assessment. In Next
594
Generation Web Services Practices (NWeSP), 2011 7th International Conference on (pp.
595
421-426). IEEE.
596
Das Gupta, A., Karmarkar, U. S., & Roels, G. (2015). The design of experiential services with
597
acclimation and memory decay: Optimal sequence and duration. Management Science,
598
62(5), 1278-1296.
599
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and
600
measurement error: Algebra and statistics. Journal of marketing research, 382-388.
601
1
We thank a reviewer for this suggestion!
Georgiou, Y., & Kyza, E. A. (2017). The development and validation of the ARI questionnaire:
602
An instrument for measuring immersion in location-based augmented reality settings.
603
International Journal of Human-Computer Studies, 98, 24-37.
604
Hair, J. F., Black, W.C., Babin, B.J., Anderson, R.E., & Tathman, R. L. (2006). Multivariate
605
Data Analysis, 6th ed., Prentice Hall.
606
Han, D. I., Jung, T., & Gibson, A. (2014). Dublin AR: Implementing augmented reality in tourism.
607
In Z. Xiang, & I. Tussyadiah (Eds.), Information and communication technologies in tourism
608
(pp. 511–523). Vienna: Springer.
609
Hosany, S., & Witham, M. (2009). Dimensions of cruisers' experiences, satisfaction, and intention
610
to recommend. Journal of Travel Research, 49(3), 351-364.
611
Isiaq, O., & Jamil, M. G. (2017). Exploring student engagement in programming sessions using a
612
simulator. Paper presented at ICICTE, July, Crete.
613
Jensen, E., & Buckley, N. (2014). Why people attend science festivals: Interests, motivations and
614
self-reported benefits of public engagement with research. Public Understanding of Science,
615
23(5), 557-573.
616
Jung, T., Chung, N., & Leue, M.C. (2015). The determinants of recommendations to use
617
augmented reality technologies: The case of a Korean theme park. Tourism Management,
618
49, 75-86.
619
Jung, T., & tom Dieck, M. C. (2017). Augmented reality, virtual reality and 3D printing for the
620
co-creation of value for the visitor experience at cultural heritage places. Journal of Place
621
Management and Development. 10 (2).
622
Jung, T., tom Dieck, M. C., Lee, H., & Chung, N. (2016). Effects of Virtual Reality and Augmented
623
Reality on Visitor Experiences in Museum. In Information and Communication
624
Technologies in Tourism 2016 (pp. 621-635). Springer International Publishing.
625
Jung, T., tom Dieck, M.C., Moorhouse, N., & tom Dieck, D. (2017). Tourists' experience of Virtual
626
Reality applications. Paper presented at ICCE, January, Las Vegas.
627
Jung, T., Lee, H., Chung, N., and tom Dieck, M. C. (2018). Cross-Cultural Differences in Adopting
628
Mobile Augmented Reality at Cultural Heritage Tourism Sites, International Journal of
629
Contemporary Hospitality Management, 30(8).
630
Kahneman, D. (2011). Thinking, fast and slow. Macmillan, London.
631
Kalantari, M., & Rauschnabel P.A. (2017). Exploring the Early Adopters of Augmented Reality
632
Smart Glasses: The Case of Microsoft HoloLens. In Jung, T. and tom Dieck, M.C. (Eds).
633
Augmented Reality and Virtual Reality – Empowering Human, Place and Business (pp. 229-
634
245), Springer, Cham.
635
Kang, M. & Gretzel, U. (2012). Effects of podcast tours on tourist experience in a national park.
636
Tourism Management, 22(2), 440-455.
637
Knutson, B. J., Beck, J. A., Kim, S., & Cha, J. (2010). Service quality as a component of the
638
hospitality experience: Proposal of a conceptual model and framework for research. Journal
639
of Foodservice Business Research, 13(1), 15-23.
640
Kourouthanassis, P. E., Mikalef, P., Pappas, I. O., & Kostagiolas, P. (2017). Explaining travellers'
641
online information satisfaction: A complexity theory approach on information needs,
642
barriers, sources and personal characteristics. Information & Management, 54(6), 814-824.
643
Lee, H., Chung, N., and Jung, T. (2015). Examining the Cultural Differences in Acceptance of
644
Mobile Augmented Reality: Comparison of South Korea and Ireland, In Tussyadiah, I. and
645
Inversini, A. (Eds). Information and Communication Technologies in Tourism (pp. 477-
646
491). Springer Computer Science, Vienna.
647
Loureiro, S. M. C. (2014). The role of the rural tourism experience economy in place attachment
648
and behavioral intentions. International Journal of Hospitality Management, 40, 1-9.
649
Manthiou, A., Lee, S., Tang, L., & Chiang, L. (2014). The experience economy approach to
650
festival marketing: Vivid memory and attendee loyalty. Journal of Services Marketing,
651
28(1), 22-35.
652
Mehmetoglu, M., & Engen, M. (2011). Pine and Gilmore's concept of experience economy and its
653
dimensions: An empirical examination in tourism. Journal of Quality Assurance in
654
Hospitality & Tourism, 12(4), 237-255.
655
Molz, J.G. (2012). Travel Connections: Tourism, technology, and togetherness in a mobile world.
656
Routledge: London.
657
Moorhouse, N., tom Dieck, M.C., & Jung, T. (2017). Augmented Reality to enhance the Learning
658
Experience in Cultural Heritage Tourism: An Experiential Learning Cycle Perspective,
659
eReview of Tourism Research, 8, 1-5.
660
Morrison, A.M. (2013). Marketing and managing tourism destinations. Routledge: London.
661
Muthén, L. K., & Muthén, B. O. (2013). Mplus: Statistical analysis with latent variables (Version
662
7.11) [Software]. Los Angeles: Muthén & Muthén.
663
Mykletun, R., & Rumba, M. (2014). Athletes’ experiences, enjoyment, satisfaction, and memories
664
from the Extreme Sport Week in Voss, Norway. Sport, Business and Management: An
665
International Journal, 4(4), 317-335.
666
Neuburger, L., & Egger, R. (2017). An Afternoon at the Museum: Through the Lens of Augmented
667
Reality. In Schegg, R. & Stangl, B. (Eds.). Information and Communication Technologies
668
in Tourism 2017 (pp. 241-254). Springer, Heidelberg.
669
Neuhofer, B. Buhalis, D. & Ladkin, A. (2015). Smart technologies for personalized experiences:
670
a case study in the hospitality domain. Electron Markets, 243-254.
671
Neuhofer, B., Buhalis, D., & Ladkin, A. (2012). Conceptualising technology enhanced destination
672
experiences. Journal of Destination Marketing & Management, 1, 36–46.
673
Oh, H., Fiore, A.M. & Jeoung, M. (2007). Measuring experience economy concepts: Tourism
674
applications. Journal of Travel Research, 46(2), 119-132.
675
Pallud, J., & Straub, D. W. (2014). Effective website design for experience-influenced
676
environments: The case of high culture museums. Information & Management, 51(3), 359-
677
373.
678
Palmer, A. (2010). Customer experience management: a critical review of an emerging idea.
679
Journal of Services marketing, 24(3), 196-208.
680
Pappas, I. O., Kourouthanassis, P. E., Giannakos, M. N., & Lekakos, G. (2017). The interplay of
681
online shopping motivations and experiential factors on personalized e-commerce: A
682
complexity theory approach. Telematics and Informatics, 34(5), 730-742.
683
Park, M., Oh, H., & Park, J. (2010). Measuring the experience economy of film festival
684
participants. International Journal of Tourism Sciences, 10(2), 35-54.
685
Pine, B. J., & Gilmore, J. H. (1998). The experience economy. Harvard Business Review, 76(6).
686
97-105.
687
Prayag, G., Hosany, S., Muskat, B., & Del Chiappa, G. (2017). Understanding the Relationships
688
between Tourists’ Emotional Experiences, Perceived Overall Image, Satisfaction, and
689
Intention to Recommend. Journal of Travel Research, 56(1), 41-54.
690
Quan, S., & Wang, N. (2004). Towards a structural model of the tourist experience: An illustration
691
from food experiences in tourism. Tourism Management, 25(3), 297-305.
692
Quadri-Felitti, D., & Fiore, A.M. (2013). Destination loyalty: Effects of wine tourists’ experiences,
693
memories, and satisfaction on intentions. Tourism and Hospitality Research, 1-16.
694
Ragin, C. C. (2008). Redesigning social inquiry: Fuzzy sets and beyond (Vol. 240). Chicago:
695
University of Chicago Press.
696
Rauschnabel, P. A., & Ro, Y. K. (2016). Augmented reality smart glasses: An investigation of
697
technology acceptance drivers. International Journal of Technology Marketing, 11(2), 123-
698
148.
699
Rauschnabel, P. A., Rossmann, A., & tom Dieck, M. C. (2017). An Adoption Framework for
700
Mobile Augmented Reality Games: The Case of Pokémon Go. Computer in Human
701
Behavior, 76, 276-278.
702
Shenton, A. K. (2004). Strategies for ensuring trustworthiness in qualitative research projects.
703
Education for information, 22(2), 63-75.
704
Song, H. J., Lee, C. K., Park, J. A., Hwang, Y. H., & Reisinger, Y. (2015). The influence of tourist
705
experience on perceived value and satisfaction with temple stays: The experience economy
706
theory. Journal of Travel & Tourism Marketing, 32(4), 401-415.
707
Sørensen, F., & Jensen, J. F. (2015). Value creation and knowledge development in tourism
708
experience encounters. Tourism Management, 46, 336-346.
709
Stilgoe, J., Lock, S. J., & Wilsdon, J. (2014). Why should we promote public engagement with
710
science?. Public Understanding of Science, 23(1), 4-15.
711
Srivastava, M., & Kaul, D. (2014). Social interaction, convenience and customer satisfaction: The
712
mediating effect of customer experience. Journal of Retailing and Consumer Services, 21(6),
713
1028-1037.
714
Taheri, B., Jafari, A., & O’Gorman, K. (2014). Keeping your audience: Presenting a Visitor
715
Engagement Scale, Tourism Management, 42, 321-329.
716
tom Dieck, M.C. & Jung, T. (2018). A theoretical model of mobile augmented reality acceptance
717
in urban heritage tourism. Current Issues in Tourism, 21(2), 154-174
718
tom Dieck, M. C., Jung, T. H., Kim, W. G., Kim, W. G., & Moon, Y. (2017). Hotel guests’ social
719
media acceptance in luxury hotels. International Journal of Contemporary Hospitality
720
Management, 29(1), 530-550.
721
tom Dieck, M. C., Jung, T. H., & tom Dieck, D. (2016). Enhancing art gallery visitors’ learning
722
experience using wearable augmented reality: generic learning outcomes perspective.
723
Current Issues in Tourism, 1-21.
724
Tscheu, F., & Buhalis, D. (2016) Augmented reality at cultural heritage sites. In Inversini, A., &
725
Schegg, R., (2016). Information and Communication Technologies 2016 (pp. 607-619).
726
Springer, Heidelberg.
727
Tussyadiah, I., Jung, T., & tom Dieck, M.C. (2017). Embodiment of Wearable Augmented Reality
728
Technology in Tourism Experiences, Journal of Travel Research, In Press.
729
Valle, P. O. D., Silva, J. A., Mendes, J., & Guerreiro, M. (2006). Tourist satisfaction and
730
destination loyalty intention: a structural and categorical analysis. International Journal of
731
Business Science and Applied Management, 1(1), 25-44.
732
Wixom, B., & Todd, P. (2005). A theoretical integration of user satisfaction and technology
733
acceptance. Information Systems Research, 16(1), 85-102.
734
Woodside, A. G. (2016). Embrace Complexity Theory, Perform Contrarian Case Analysis, and
735
Model Multiple Realities. In Bad to Good: Achieving High Quality and Impact in Your
736
Research (pp. 57-81). Emerald Group Publishing Limited.
737
Woodside, A. G., Prentice, C., & Larsen, A. (2015). Revisiting problem gamblers' harsh gaze on
738
casino services: Applying complexity theory to identify exceptional customers. Psychology
739
& Marketing, 32(1), 65-77.
740
Wu, H.K. Lee, S.W.Y. Chang, H.Y., & Liang, J.C. (2013). Current status, opportunities and
741
challenges of augmented reality in education. Computers and Education, 41-49.
742
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Appendix
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Constructs and definitions
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Constructs
Definition
Esthetics
“The beauty that can be expressed though the elements such as color, photographs, font style,
and layout” (Lee et al., 2015, p. 481)
Education
The absorption of “events unfolding before [a tourist] at a destination, while actively
participating through interactive engagement of the mind” (Oh et al., 2007, p. 121)
Entertainment
Entertainment is “an activity that provides amusement and pleasure” (Benny, 2015, p. 7)
Escapism
The escape “of [tourists] regular environments to suspend the power of norms and values that
govern their ordinary lives or to think about their lives and societies from a different
perspective” (Oh et al., 2007, p. 122)
Memories
The "mental revival of conscious experience" (Conway et al., 2013, p. 31)
Satisfaction
The “psychological state experienced by the consumer when confirmed or disconfirmed
expectations exist with respect to a specific service transaction or experience” (Palmer, 2010,
p. 199)
Visitor
engagement
Visitor engagement is “a state of being involved with and committed to a specific market
offering” (Taheri et al., 2014, p. 322)
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Appendix 2: Indirect Effects
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Dependent Variable: Memory
95% CIlow
β
95% CIhigh
Mediation?
Total Indirect (sum)
0.491
0.640
0.795
Estethics - Education - Memory
0.163
0.304
0.469
Estethics - Entertainment - Memory
0.048
0.180
0.329
Estethics - Escapist - Memory
0.060
0.156
0.259
Dependent Variable: Satisfaction
95% CIlow
β
95% CIhigh
Mediation?
Total Indirect (sum)
0.335
0.470
0.617
Estethics - Education - Satisfaction
0.143
0.237
0.363
Estethics - Entertainment - Satisfaction
0.094
0.188
0.295
Estethics - Escapist - Satisfaction
-0.004
0.045
0.098
×
Note: coefficients are unstandardized effects. ML estimator and bootstrapping (10,000 resamples) applied.
752
