Abstract
Purpose
Drawing on the theory of memory-dominant logic, this study aims to examine how the substantive staging of the servicescape, experience co-creation, experiential satisfaction and experience intensification affect experience memorability and hedonic well-being in the case of unmanned smart hotels.
Design/methodology/approach
An online survey was used, with the target respondents being hotel guests people aged 18 years and older who had been recent guests of the FlyZoo Hotel in Hangzhou, China. Data were collected online from 429 guests who had stayed in the hotel between April and June 2023. Data analysis was undertaken using structural equation modelling.
Findings
The results suggest that all the proposed four constructs are positive drivers of a memorable unmanned smart hotel experience. The relationship between the memorability of the hotel experience and hedonic well-being was found to be significant and positive.
Practical implications
Unmanned smart hotels should ensure that all smart technologies function effectively and dependably and offer highly personalised services to guests, allowing them to co-create their experiences. This will lead to the guest receiving a satisfying and memorable experience. To enable experience co-creation using smart technologies, unmanned smart hotels could provide short instructional videos for guests, as well as work closely with manufacturers and suppliers to ensure that smart technology systems are regularly updated.
Originality/value
This study investigates the antecedents and outcomes of a novel phenomenon and extends the concept of memorable tourism experiences to the context of unmanned smart hotels.
Keywords
Citation
Sthapit, E., Ji, C., Ping, Y., Prentice, C., Garrod, B. and Yang, H. (2024), "Experience-driven well-being: the case of unmanned smart hotels", International Journal of Contemporary Hospitality Management, Vol. 36 No. 13, pp. 1-18. https://doi.org/10.1108/IJCHM-07-2023-1063
Publisher
:Emerald Publishing Limited
Copyright © 2024, Erose Sthapit, Chunli Ji, Yang Ping, Catherine Prentice, Brian Garrod and Huijun Yang.
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Introduction
Smart technologies powered by artificial intelligence (AI), including virtual assistants, robotic butlers and image-recognition support systems, are becoming increasingly popular in today’s experiential marketplace (Chang et al., 2022; Cheng et al., 2023). Leading hotel groups such as InterContinental Hotels Group, Hilton Worldwide and Marriott International have begun to integrate such technologies into their operations (Chang et al., 2022). Some hotels are now even operated purely on the basis of smart technologies, with no human employees being involved in the service delivery (Chang et al., 2022; Wu et al., 2019). These hotels are referred to as unmanned smart hotels (USHs), examples of which include the world’s first USH, Henn-Na Hotel, located in Nagasaki, Japan (Zeng et al., 2020), and the FlyZoo Hotel, located in Hangzhou, China. It is argued that the interactions between customers and AI-driven technology will soon become routine in the tourism and hospitality sector (de Kervenoael et al., 2020).
The main benefit of USHs for companies is that they incur no appreciable staff costs. The use of smart technologies may also, however, convey some additional market benefits. USHs can offer more consistent, efficient and convenient services (Chang et al., 2022), allowing guests to experience the hotel service while having no direct contact with human employees (Shin and Perdue, 2019). Some advantages of USH from a guest’s perspective include shorter waiting times, greater precision of service provision, personalisation and a chance to experience first-hand the intriguing and entertaining aspects of human-robot encounters (Kim and Han, 2020). Each encounter or interaction can contribute to forming a memorable tourism experience (MTE) for the guest. Providing customers with memorable experiences has a range of benefits for the service providers, including greater revisit intention (Tešin et al., 2023), stronger loyalty behaviours (Coudounaris and Sthapit, 2017) and enhanced destination sustainability (Wei et al., 2019).
While scholars generally accept that the MTE construct is a multidimensional one, there is little agreement on the nature of such dimensionality (Hosany et al., 2022). It is widely argued that the creation of MTEs depends greatly upon context (Ye et al., 2021). The USH experience has several highly novel elements, implying that context may be particularly important. USHs use a range of AI-powered technologies to meet customers’ needs (Yang et al., 2021). They also operate without any human operatives throughout the service-delivery system (Chang et al., 2022). However, the nature of the interplay between these features of USH experiences and the related dimensions that determine MTEs remains unknown. This study therefore incorporates other potentially relevant dimensions, including the substantive staging of the hotel servicescape (service-attribute-related aspect), experience co-creation, experiential satisfaction and experience intensification, to achieve a better understanding of how MTEs are formed.
Previous research has examined the behavioural outcomes of MTEs (e.g. revisit intentions). Such studies have tended, however, to produce inconsistent findings (e.g. Hosany et al., 2022; Ye et al., 2021; Sthapit et al., 2019). This study examines guests’ affective states with the aim of understanding how technology-driven experiences contribute to guests’ well-being. A particular focus will be on hedonic well-being, as post-Covid-19 research suggests that today’s consumers tend to seek healthier lifestyles and to favour travelling to destinations that promote their well-being (Kotur, 2022). Consequently, this study examines the factors that determine a memorable USH experience and how such experiences relate to guests’ well-being.
The study contributes to knowledge on MTEs by testing a novel framework with alternative antecedents and outcomes of MTEs in the unique context of USHE. The former comprises the substantive staging of the hotel servicescape, experience co-creation, experiential satisfaction and experience intensification, while the latter comprises hedonic well-being. The results of the study are important because they indicate various means by which USHs can facilitate experiences that are more memorable for their guests.
The remainder of this paper is set out as follows. The next section will discuss the relevant literature, outline the aims of the study and establish the hypotheses to be examined. The methods of testing these hypotheses will be outlined in the subsequent section, followed by a further section in which an analysis of the results will be presented. The penultimate section will the present a discussion of the results, while the final section will set out the conclusions and implications of the study.
Literature review and hypothesis development
Theoretical foundations
Memory-dominant logic (MDL) is used as the theoretical foundation of the present study. Advancing from goods-dominant logic, service-dominant logic and customer-dominant logic, MDL considers how value is constructed through the co-creation of memorable experiences along the course of the customer experience journey. MDL can thus be defined as service experience delivery that aims to create value through the provision to memorable experiences (Harrington et al., 2019). In the context of USHs, four possible antecedents of memorable unmanned smart hotel experiences (MUSHEs) are examined: the substantive staging of the servicescape, experience co-creation, experience intensification and experiential satisfaction (Figure 1). Unlike goods-dominant logic and service-dominant logic, MDL views the service experience not as an output but as an input of value-creation (Harrington et al., 2019). This is because customers and service providers work together to co-create service experiences (Schmitt et al., 2015). Customers derive value from receiving positive service experiences and later recalling them as positive memories (Harrington et al., 2019; Li et al., 2023a, 2023b).
MDL proposes that the creation of an experience requires the involvement of both the service provider and the customer (Schmitt et al., 2015). As such, MDL focuses on how service exchanges lead to the creation of memories, recall and recollection (Harrington et al., 2019). Various psychological and behavioural outcomes are then inspired by those memories (Harrington et al., 2019). In this study, the outcome variable is hedonic well-being (HWB). HWB is a compound variable comprising positive emotions, pleasure and happiness (Vada et al., 2019) and is linked to the concept of subjective well-being (Diener, 1984). In the hospitality context, MDL has been applied to investigate how service experiences are co-created so that they are memorable and generate life satisfaction (Harrington et al., 2019; Neuhofer et al., 2020). MDL has not previously been applied in the specific context of USHs. Given the novelty of the experience, it is likely that existing formulations of MDL will need to be adapted to fit the USH context.
Hypothesis development
Substantive staging of the hotel servicescape
Lockwood and Pyun (2019) note that an effective physical environment can attract hotel guests from a desired target market. It can also stimulate a positive consumer experience (Yang and Zhang, 2022). A customer who receives a memorable experience will have a comparatively longer relationship with the servicescape (Lockwood and Pyun, 2019). “Servicescape” is a term used to denote the physical environment in which the service encounter takes place. In the context of a hotel, it relates to the elements of ambience, layout, signage and décor used with the hotel (Dedeoglu et al., 2018). Ambience includes sounds (such as music), lighting, heating and smells (Heung and Gu, 2012). Layout relates to the positions of furniture and equipment in public areas (Turley and Milliman, 2000). Signage can be explanatory (e.g. fire drill instructions) and/or informative (e.g. directional signs) (Kim and Moon, 2009). Décor refers to the colours, types and quality of materials used for the walls and floors (Han and Ryu, 2009). The servicescape provides the context within which the simultaneous delivery and consumption of hotel services take place, representing a point of contact through which guests’ experiences are constructed (Lockwood and Pyun, 2019; Yang and Zhang, 2022).
Dong and Siu (2013) define “substantive staging” as the mechanical and functional clues that enable the delivery of the servicescape. The hospitality industry’s increasing use of AI is making the servicescape ever smarter. In a USH, technology enriches the servicescape, for example, through the use of sensors and devices that are inter-connected through a network to detect and respond to guest’s needs in an inobtrusive and seamless manner (Yin et al., 2023).
The manner in which the substantive staging of the servicescape is achieved can influence a range of cognitive, emotional and physiological variables relating to the guest experience, including those related to consumers’ current and future behaviour. Effective substantive staging is considered to be positively associated with customers’ service evaluations (Dong and Siu, 2013) and satisfaction (Hanks and Line, 2018; Line et al., 2018), as well as with the formation of MTEs (Sthapit et al., 2023). The present study thus adopts following hypotheses:
Effective substantive staging of the hotel servicescape is significantly and positively related to guests’ experiential satisfaction.
Effective substantive staging of the hotel servicescape is significantly and positively related to guests’ MUSHE.
Experience co-creation
Experience co-creation is based on direct interaction between the seller and the customer (Busser and Shulga, 2018). The term refers to the collaborative generation of value by organisations and customers, allowing the latter to co-construct personalised experiences to suit their individual preferences (Prahalad and Ramaswamy, 2004). In the hospitality context, the experience is invariably co-created, meaning that its value is determined by guests integrating the resources that form the service offering of the hotel. Hotel guests cannot, therefore, be considered to receive values that pre-exist in a passive way; rather, they must be viewed as active co-creators of new value (Nangpiire et al., 2022).
The co-creation process necessarily involves customers interacting with other individuals in the servicescape, and normally these would mainly be staff members as well as other hotel guests (Grönroos, 2011). In the present study, the principal interaction would not be with hotel staff but with smart technology such as service robots (Fang et al., 2023).
The hotel experience is said to be particularly conducive to customisation, as it involves a wide variety of tangible and intangible resources, requiring active participation on the part of the guest to deliver it (Kahraman and Cifci, 2023). Guests have substantial control over how to interact with hotel services (Mathis et al., 2016), making hotel experience co-creation instructive as a subject of study. Accordingly, the concept has often been applied to accommodation services (Sthapit and Jimenez-Barreto, 2018), including hotels (Sthapit, 2019). For the sake of simplicity, the term “memorable tourism experience” is used in this study rather than “memorable hospitality experience”, but the two can be considered analogous.
The nature of these interactions could be expected to have a substantial impact on a guest’s evaluation of a hotel experience (McCartney and Chen, 2020). Satisfaction (Buonincontri et al., 2017) and MTEs are viewed as desirable outcomes of experience co-creation (Campos et al., 2017; Mathis et al., 2016). Accordingly, the following hypotheses are proposed:
Experience co-creation is significantly and positively related to guests’ experiential satisfaction.
Experience co-creation is significantly and positively related to guests’ MUSHE.
Experience intensification
According to Sthapit et al. (2022), experience intensification has the effect of prolonging experience memorability for customers. One way in which customers like to intensify their service experiences is by taking photographs and videos (Dong and Siu, 2013). They can then share their experiences with friends and relatives through various social media (Chen et al., 2023). The use of digital mobile technologies by customers has led to hospitality providers, including hotels, innovating to create richer experiences that can be captured visually, the expectation being that these images will then be readily transmitted through the social media (Li et al., 2023a, 2023b). In the present case, it is likely that guests will want to share photographs and videos of them interacting with service robots during the on-site hotel experience. The sharing of tourist experiences through social media is, meanwhile, believed to be an increasingly important driver of tourist satisfaction (Chen et al., 2023; Li et al., 2023a, 2023b). The following hypotheses are therefore proposed:
Experience intensification is significantly and positively related to guests’ experiential satisfaction.
Experience intensification is significantly and positively related to guests’ MUSHE.
Experiential satisfaction
The term “service satisfaction” refers to the extent to which a customers' post-purchase evaluation of a service exceeds their pre-purchase expectations. The greater the magnitude of excess, the greater the satisfaction is assumed to be (Chen and Chen, 2010). Satisfaction can also relate to the feeling of pleasure – a positive feeling that is likely to be memorable – that results from such an evaluation (Su et al., 2011). When the service fails to meet or exceed customers’ expectations, however, they are left dissatisfied. This denotes a feeling of displeasure, which is also likely to be memorable (Reisinger and Turner, 2003). A study by Sthapit et al. (2018), meanwhile, found that greater satisfaction leads to an increase in the memorability of an experience.
“Experiential satisfaction” follows from the concept of service satisfaction. While service satisfaction relates a consumer’s satisfaction with the provision of a given service, experiential satisfaction widens the focus to include the entire experience. Experiential satisfaction thus denotes the overall satisfaction received from the experience that is generated from the service provision. Customers compare the quality of the experiences they receive with their expectations, which results in either positive or negative disconfirmation. The resulting emotional responses then determine the extent to which the customer is satisfied or dissatisfied (Kao et al., 2008). Satisfaction has been found to be a significant antecedent of HWB in the context of an integrated tourist resort (Ahn et al., 2019). The following hypotheses are thus proposed:
Experiential satisfaction is significantly and positively related to guests’ MUSHE.
Experiential satisfaction is significantly and positively related to guests’ HWB.
Memorable unmanned smart hotel experiences and hedonic well-being
In this study, MTE is conceptualised as an attitudinal construct that involves guests having lasting positive memories after engaging in an experience (Kim et al., 2012). It is understood to be reliant upon the customer’s memory of the experience (Coudounaris and Sthapit, 2017). HWB involves positive emotions, pleasure and happiness (Vada et al., 2019), and it is generally understood to be related to the concept of subjective well-being (Diener, 1984). By virtue of its ability to generate such emotions and to enable guests to re-live those emotions through lasting memories, MTEs can generate HWB for guests long after they have partaken in the experience concerned (Trinanda et al., 2022; Vada et al., 2.019).
In the present study, a MUSHE refers to an experience that is positive, remembered and recalled in vivid detail after staying at an USH. Given that context is believed to play an important role in the formation of MTEs (Ye et al., 2021), the way in which experiences are formed during a stay in a USH may be expected to be quite different from the way in which they are formed during a stay in a traditional hotel. How such MTEs go on to effect HWB might also be rather different. Service robots, equipped with AI, can undertake housekeeping work, provide room services, supply information about the hotel and the wider destination, make guests comfortable and safely entertain them (Zeng et al., 2020). In addition, USHs offer numerous smart amenities, such as face or voice recognition, smart TV, smart room keys, robots and sensors (Yang et al., 2021). The USH experience is thus likely to be a novel one for the guest, and it should not be taken for granted that MTEs will be formed in the same way as they are in the case of traditional hotel stays, nor that they will impact HWB in the same way. Accordingly, the following hypothesis is proposed:
MUSHE is significantly and positively related to guests’ HWB.
Methods
Sample
The target respondents in this study were people aged 18 years and older who had stayed at the FlyZoo Hotel. The FlyZoo Hotel, which is based in Hangzhou, China, was the first USH designed using the smart technology of Fliggy, an online travel platform owned by Alibaba. The FlyZoo mobile app is available for guests to choose and book the rooms they prefer. On entering the hotel, guests first check in using a self-service terminal. Facial recognition is then used to allow guests entry to their rooms and to access all other facilities. A “Tmall Genie” device is fitted in each room to assist guests in using the in-room facilities through voice commands. Guests can choose their check-out time using the app (Chang et al., 2022).
To qualify for this study, respondents needed to have stayed at the FlyZoo Hotel in the three months before the data was collected. Visits had therefore to be between April and June 2023. This criterion was used because empirical studies indicate that memories tend to become increasingly distorted over time (Park and Santos, 2017). According to the memory reconstruction framework, memory recollection is not simply a case of replaying memories of a past experience; it is a much more complex process in which new information is integrated with information already stored in the memory. This means that memories are not immutable but can change over time. A period limited to three months between the actual experience and recall was used to try to minimise this effect (Sthapit et al., 2019). The target sample size was based on the rule of thumb of 10 observations per indicator (Hair et al., 2006).
Measures
The questionnaire had two main sections. The first comprised questions relating to respondents’ demographic and travel characteristics. The second comprises the items for the seven constructs used in the hypothesised model. All of these items were scored on a five-point Likert scale (1 = strongly disagree; 5 = strongly agree). Substantive staging of the hotel servicescape was measured using three items adapted from Durna et al. (2015). Experience co-creation was measured using five items adapted from Mathis et al. (2016). Three items adapted from Wu et al. (2018) were used to measure experiential satisfaction. Experience intensification comprises three items adapted from Dong and Siu (2013). MUSHE used three items adapted from Oh et al. (2007). Lastly, five items were adapted from Diener et al. (1985) to measure the HWB construct. A total of 23 items were therefore used in this study. The questions were developed in English and then translated into Mandarin, tested with back translation to ensure a high level of accuracy.
Data-collection procedure
A pre-test was conducted to assess the readability, clarity, comprehensibility and correctness of response format of the questionnaire. Firstly, 16 undergraduate and postgraduate students were asked to evaluate these four aspects for each item. Secondly, five tourism and hospitality professors, all based in China, were invited to confirm whether the measures could be considered to be valid. They were also asked to assess the relevance, flow, phrasing and clarity of the questions. Respondents were encouraged during the pre-test to identify anything they found unclear or ambiguous, or to which they had difficulty responding. Some minor changes were made to the questionnaire on the basis of these comments, mainly in the form of correcting grammatical errors and clarifying sentence structure.
An online survey link was distributed through the FlyZoo hotel’s WeChat followers’ group with the help of a professional market research company. To ensure that the survey was correctly targeted, various filter questions were asked. These included “Are you 18-year-old or over?”, “Are you a Chinese national?” and “Have you stayed at the FlyZoo Hotel during the past three months (April to June 2023)”. Those who responded negatively were not permitted to participate in the survey. Each respondent who provided positive answers to the filtered questions and completed the questionnaire successfully, received a 10 RMB WeChat red envelope (微信红包) – a monetary gift – as a reward. To ensure the quality of the responses, potential respondents were told that their responses were to be checked and that if there was any indication of irrelevant or random responses being given, compensation would be withheld. Screening was also conducted for careless responses, with any invalid ones being discarded.
As Table 1 shows, just over half of the respondents were male (53.8%), while 93.5% were Chinese nationals. The highest proportion of respondents were in the 26–35 age group (31.7%). Most respondents (64.3%) were visiting the FlyZoo hotel for the first time, and slightly more than half (54.1%) were visiting with a companion. In terms of marital status, the largest category was married (46.9%). Regarding occupation, the largest group was in the financial sector (13.8%).
Data analysis
After removing 69 responses with missing data, a total of 429 valid responses were used in the subsequent analysis. Partial least squares structural equation modelling (PLS-SEM) was used to carry out confirmatory factor analysis and conduct structural model analysis to investigate the hypothetical relationships in the theoretical model. PLS-SEM has the advantage of being better able to handle non-normally distributed data than covariance-based structural equation modelling (Hair et al., 2019). Indeed, a Mardia's Multivariate Normality Test (Mardia, 1970) showed that multivariate skewness was β = 80.454 (p < 0.01) and kurtosis was β = 739.061 (p < 0.01), indicating absence of a multivariate normal distribution.
Results
Since strong multicollinearity implies potential common method bias in self-reported survey research, Kock (2015) recommends using variance inflation factor (VIF) values to test whether common method bias exists in PLS-SEM. In this study, all VIF values for the internal model were examined, and since all these values were less than 3.3 recommended by Kock (2015), common method bias was not considered to be a concern. The suggestion of Bagozzi et al. (1991) to check the bivariate correlations between constructs was also followed, and none of the correlations between constructs exceeded 0.90. This also found there to be no evidence of common method bias (Cegarra-Navarro et al., 2016).
Measurement model test
Performing CFA is the recommended first step to conducting SEM analysis. The latter was implemented in this study using SmartPLS 4. The results (Table 2) show that the factor loadings ranged from 0.648 to 0.927, all of which exceeded the threshold value of 0.6 recommended by Hair et al. (2010), and the AVE values for all constructs were larger than 0.5, confirming convergent validity. For the assessment of internal consistency and reliability, Cronbach’s a, rho-A and CR values were calculated for all constructs. All these values were above the recommended threshold of 0.7 (Hair et al., 2021), indicating that the questionnaire has adequate internal consistency and reliability.
This study evaluated the discriminant validity of all constructs following the criteria proposed by Fornell and Larcker (1981). As shown in Table 3, since the square root of the AVE for each of the latent constructs was higher than the corresponding inter-construct correlations, it can be concluded that the discriminant validity of all the constructs was acceptable.
Structural model test
After confirming the reliability and validity of the constructs based on the results of the measurement model, the structural model was constructed and analysed. Both R2 and the Stone–Geisser indicator (Q2) were used to assess the quality of the proposed model. The R2 values were 0.454 for experiential satisfaction, 0.652 for MUSHE and 0.345 for HWB, all greater than the criterion of 0.02 suggested by Cohen (2013). The Q2 values of 0.356 for experiential satisfaction, 0.463 for MUSHE and 0.217 for HWB were all greater than the value of zero suggested by Hair et al. (2014). The results of R2 and Q2 therefore indicate that the model proposed in this study is robust.
The path coefficients reflect an assessment of the relationship between the constructs in the structural model (Hair et al., 2019). To estimate the path coefficients for testing the hypotheses in this study, a nonparametric bootstrap technique with 5,000 repetitions was implemented. The results of the hypothesis testing are shown in Table 4. The findings indicate that the effect of substantive staging of servicescape on experiential satisfaction (β = 0.137, t = 2.795, p = 0.005) and on MUSHE (β = 0.075, t = 2.138, p = 0.033) was significant at the levels of 0.01 and 0.05, respectively, supporting both H1 and H2. For H3 and H4, the effects of experience co-creation on both experiential satisfaction (β = 0.363, t = 5.146, p = 0.000) and MUSHE (β = 0.572, t = 10.420, p = 0.000) were significant at the level of 0.001; the two hypotheses were thus supported. The results show that experience intensification had a positive and significant effect on experiential satisfaction (β = 0.281, t = 4.084, p = 0.000) at the level of 0.001 and on MUSHE (β = 0.104, t = 2.233, p = 0.026) at the level of 0.05, thus supporting H5 and H6. Furthermore, the findings show that experiential satisfaction had a positive and significant effect both on MUSHE (β = 0.167, t = 3.938, p = 0.000) and HWB (β = 0.278, t = 4.756, p = 0.000) at the level of 0.001, which confirmed that H7 and H8 were supported. Moreover, the results indicate a positive and significant effect of MUSHE on HWB (β = 0.374, t = 5.989, p = 0.000) at the level of 0.001, therefore H9 was supported. Based on the above findings, all nine hypotheses of this study are supported.
Discussion
Guided by the MDL concept, this study set out to construct and test an integrative theoretical model of MUSHE. All nine hypotheses were supported. First, substantive staging was found to positively drive guests’ experiential satisfaction (H1) and MUSHE (H2). This finding supports H1 and H2, corresponding with studies suggesting that substantive staging contributes to satisfaction (Line et al., 2018) and MTE (Sthapit et al., 2023). The finding also corresponds to those of previous studies indicating that a favourable perception of the service environment is associated with greater customer satisfaction and more favourable subjective memories (Dong and Siu, 2013; Sthapit et al., 2018). This suggests that a higher degree of servicescape performance is correlated with a more satisfying and memorable experience for USH guests. The results thus highlight the significance of the service environment for USH experiences.
Second, experience co-creation had a positive and statistically significant effect on experiential satisfaction and MUSHE, as proposed in H3 and H4. This supports studies indicating that experiences tend to be more satisfying (Buonincontri et al., 2017) and more memorable when customers have greater opportunity to interact with each other (Campos et al., 2017; Williams et al., 2019). During the experience co-creation process, guests of USHs can be involved either actively or passively. It is anticipated that the experiences of those who actively co-create their USHEs by interacting with smart technologies would be more satisfying and memorable. This corresponds with previous research that has found experience co-creation to be a significant antecedent of memory retention (Campos et al., 2017). This confirms the significance of experience co-creation in the processes by which satisfying and memorable experiences are formed.
Third, a significant positive relationship between experiential intensification and experiential satisfaction was confirmed by the results of this study, confirming H5. A significant positive relationship between experiential satisfaction and MUSHE was also found, supporting H6. Taken together, these results suggest that guests who take photographs during their stay in a USH intensify their experiences and have a more satisfying and memorable experience. These findings correspond to previous studies indicating that photos contribute to satisfaction (Chen et al., 2023; Li et al., 2023a, 2023b) and can elicit strong positive memories of trip experiences (Sthapit et al., 2022).
Fourth, experiential satisfaction was found to be another important determinant of both MUSHE and HWB. These findings support H7 and H8, respectively, corroborating previous studies indicating that experiential satisfaction that is derived from positive service experiences is positively linked to memorability (Sthapit et al., 2018; Tung and Ritchie, 2011) and HWB (Ahn et al., 2019). The findings also support previous research showing that satisfaction is a key construct in customer behaviour (Lee et al., 2012).
A positive relationship between MUSHE and HWB was also found in this study, thereby supporting H9. The more memorable tourists find their experience staying at a USH, the more likely they are to experience positive emotions, pleasure and happiness, which are key components of HWB. This tends to corroborate previous studies, where a positive impact of MTEs on HWB has been identified (Trinanda et al., 2022; Vada et al., 2019).
Theoretical implications
Three main theoretical contributions are offered in this study. First, the study answers the call for more studies that explore and confirm the antecedents and outcomes of MTEs in specific contexts (Hosany et al., 2022). Studies that have been published to date have tended to be based on Kim et al.’s (2012) work, typically replicating their model using the same variables and scales (Hosany et al., 2022). Few studies have examined other experiential dimensions that may have an impact on MTEs in particular contexts (Sthapit et al., 2023; Stone et al., 2022). This study contributes to the literature by testing a novel framework with alternative antecedents of tourists’ MTEs that are suited to the specific context of USHs. Greater experience co-creation and higher experience intensification, along with a servicescape that is more appealing, tend to result in experiences that are more satisfying and more memorable. In addition, given the relative lack of studies related to USH experiences, this study provides greater clarity on the specific factors that characterise a MTE and increases our understanding of the phenomenon. The results of this study can, therefore, guide future research directions and new discourses. The study further confirms that MTE is a multifaceted and context-dependent concept (Sthapit and Jimenez-Barreto, 2018). Future studies need, therefore, to exercise caution about directly transferring Kim et al.’s (2012) standard MTE model and scales to new settings (Hosany et al., 2022). While the standard model could fit well, a model based on alternative variables could perform even better.
Second, existing MTE studies have mainly examined conventional outcome variables, for example, revisit intention. Few studies have attempted to link MTE to HWB (Hosany et al., 2022). In addition to exploring the various antecedents of MUSHEs, the present study contributes by identifying MTE, in this case, MUSHE, as a significant enabler of HWB. A greater understanding of the outcomes related to service experiences is thereby achieved.
Third, many studies have used the lens of positive psychology to examine MTEs, drawing on theories including savouring, script theory and the theory of planned behaviour, as well as the fields of environmental psychology, organisational management, sociology and psychology (Hosany et al., 2022). This study, in contrast, adopted MDL as its theoretical basis. The results also demonstrate the value of MDL, which suggests that service experience is not best seen as an output of the service encounter but as an input. Further, the results suggest that MTEs can deliver positive outcomes for the customer, in this case, HWB, as well as the service provider.
Managerial implications
Those who manage USHs may more effectively facilitate the formation of satisfying and memorable experience by incorporating substantive staging of the hotel servicescape, experience co-creation and experience intensification into their service delivery. First, given that the substantive staging of hotel servicescape positively influences both experiential satisfaction and MUSHE, USHs should continually strive to offer a more appealing environment for their guests. USH should use innovative, cutting-edge smart technologies, such as the latest touch-screen kiosks, high-tech videos showing smart services in the hotel and utilising virtual reality, including more video graphics instead of listing the features of the hotel, so that guests feel fully immersed in the servicescape. The design of USHs should be as differentiated and visually attractive as possible in comparison to competitors. This will require USHs to continually research, invest in and promote the smart technologies available to their guests to experience during their stay. Hotels that work closely with the companies that innovate and produce smart technologies are likely to fare best.
Second, USHs should ensure that all smart technologies function effectively and dependably and offer highly personalised services to guests, allowing them to co-create their experiences. This will ultimately lead to the guest receiving a satisfying and memorable experience. To facilitate experience co-creation using smart technologies, USHs could provide short instructional videos for guests. They may also benefit from working closely with manufacturers and suppliers to ensure that smart technology systems are frequently updated so that they do not break down or malfunction.
Third, taking photographs may be a significant avenue through which USH guests can intensify their interaction with the hotel. Indeed, this study suggests that experience intensification results in greater satisfaction and memorability on the part of guests. Attempts to discourage the taking of photographs may, therefore, be misguided. Instead, USHEs should establish some photograph “spots”, where they can be seen using the smart technology, to provide ample photo opportunities. Guests should also be encouraged to post their photographs on social media platforms, as this will serve to strengthen their satisfaction, memorability and ultimately their HWB.
Limitations and suggestions for future studies
The limitations of this research must be acknowledged. First, only four antecedents of MUSHEs were included in this study. A greater understanding would undoubtedly be achieved if a wider range of antecedents and outcomes were to be considered. This study does, however, provide a solid basis on which further work can be conducted. Since visit memories are known to relate positively to a person’s place attachment (Peng et al., 2023), future studies could also examine whether MUSHE contributes to tourists’ attachment to the destination in which the USH is based. Second, the respondents were primarily Chinese nationals. It would doubtless be instructive, therefore, to use samples drawn from different populations to conduct cross-cultural research. These studies would serve to validate the current study’s findings. Third, it is important to note that the data collection was undertaken after the respondents had already completed their trips. As such, the study relied on participants being able to recall the formation of memories relating to experiences that took place between one and three months previously. In future studies, data could be collected from guests while they are still at the hotel or shortly after their visit. Fourth, the respondents of this study comprises only those staying at the FlyZoo Hotel in Hangzhou, China. Future research should extend to other USHs to validate the findings. Fifth, this study used an internet-based survey, which is well-known to be liable to certain biases. Adopting a broader set of methods for data collection may assist in overcoming this limitation. Finally, it would be instructive to undertake comparative studies of repeat and first-time guests at the particular hotel. A comparative study of domestic and international visitors could also yield further meaningful insights.
Figures
Figure 1.
The conceptual model
Profiles of respondents
| Variables | Frequency | % |
|---|---|---|
| Gender | ||
| Male | 231 | 53.8 |
| Female | 198 | 46.2 |
| Chinese national | ||
| Yes | 401 | 93.5 |
| No | 28 | 6.5 |
| Age | ||
| 18–25 | 61 | 14.2 |
| 26–35 | 136 | 31.7 |
| 36–45 | 87 | 20.3 |
| 46–55 | 95 | 22.1 |
| 56 or older | 50 | 11.7 |
| First-time stay | ||
| Yes | 276 | 64.3 |
| No | 153 | 35.7 |
| Staying with a companion | ||
| Yes | 232 | 54.1 |
| No | 197 | 45.9 |
| Marital status | ||
| Single | 101 | 23.5 |
| Engaged | 111 | 25.9 |
| Married | 201 | 46.9 |
| Divorced | 16 | 3.7 |
| Occupation | ||
| Business | 95 | 22.1 |
| Government | 32 | 7.5 |
| Finance | 59 | 13.8 |
| Service | 54 | 12.6 |
| Retails | 22 | 5.1 |
| Students | 11 | 2.6 |
| Teachers | 32 | 7.5 |
| Professional services (doctor, lawyer) | 30 | 7.0 |
| Manufacturing | 45 | 10.5 |
| Freelances | 34 | 7.9 |
| Retired and others | 15 | 3.5 |
Source: Authors’ own creation
Construct reliability and validity
| Construct and items | Factor loadings | CA | rho_A | CR | AVE |
|---|---|---|---|---|---|
| Substantive staging of servicescape (SSCC) | 0.875 | 0.887 | 0.923 | 0.800 | |
| The architecture of FlyZoo Hotel was attractive | 0.922 | ||||
| The atmosphere of FlyZoo Hotel was cheerful | 0.874 | ||||
| The decor of FlyZoo Hotel was fashionable | 0.887 | ||||
| Experience co-creation (EXCR) | 0.867 | 0.880 | 0.903 | 0.652 | |
| Working alongside service robots allowed me to have a great social interaction during my recent FlyZoo Hotel experience, which I enjoyed | 0.814 | ||||
| I felt comfortable working with service robots during my recent FlyZoo Hotel experience | 0.770 | ||||
| The setting allowed me to effectively collaborate with service robots during my recent FlyZoo Hotel experience | 0.820 | ||||
| My recent FlyZoo Hotel experience enhanced because of my participation in the experience | 0.791 | ||||
| I felt confident in my ability to collaborate with service robots during my recent FlyZoo Hotel experience | 0.840 | ||||
| Experiential satisfaction (EXST) | 0.807 | 0.827 | 0.885 | 0.719 | |
| The FlyZoo Hotel was beyond my expectations | 0.835 | ||||
| I really liked the stay at the FlyZoo Hotel | 0.833 | ||||
| It was worthwhile staying at the FlyZoo Hotel | 0.874 | ||||
| Experience intensification (EXIN) | 0.772 | 0.840 | 0.868 | 0.692 | |
| I purchased mementos during my stay at the FlyZoo Hotel | 0.648 | ||||
| I took memorable pictures during my stay at the FlyZoo Hotel | 0.893 | ||||
| Pictures help me keep my experiences at the FlyZoo Hotel | 0.927 | ||||
| Memorable unmanned smart hotel experience (MUSHE) | 0.907 | 0.921 | 0.941 | 0.842 | |
| I have wonderful memories of the recent FlyZoo Hotel experience | 0.904 | ||||
| I will not forget my recent FlyZoo Hotel experience | 0.925 | ||||
| I will remember my recent FlyZoo Hotel experience | 0.924 | ||||
| Hedonic well-being (HWB) | 0.865 | 0.889 | 0.901 | 0.647 | |
| In most ways, my experience at the FlyZoo Hotel was close to ideal | 0.871 | ||||
| The conditions of FlyZoo Hotel were excellent | 0.806 | ||||
| I am satisfied with my recent FlyZoo Hotel experience | 0.683 | ||||
| I achieved the most important things during my recent stay at the FlyZoo Hotel | 0.842 | ||||
| I would not change the plans I made for this recent stay at the FlyZoo Hotel | 0.807 | ||||
Source: Authors’ own creation
Discriminant validity
| Constructs | (1) | (2) | (3) | (4) | (5) | (6) |
|---|---|---|---|---|---|---|
| Experience co-creation (1) | 0.807 | |||||
| Memorable unmanned smart hotel experience (2) | 0.487 | 0.918 | ||||
| Experience intensification (3) | 0.685 | 0.465 | 0.832 | |||
| Experiential satisfaction (4) | 0.787 | 0.473 | 0.627 | 0.848 | ||
| Substantive staging of servicescape (5) | 0.622 | 0.440 | 0.586 | 0.620 | 0.894 | |
| Hedonic well-being (6) | 0.585 | 0.282 | 0.606 | 0.543 | 0.514 | 0.804 |
Source: Authors’ own creation
Results of hypothesis testing
| Hypotheses relationship | β value | SD | t-values | p-values | Result |
|---|---|---|---|---|---|
| H1: SSSC → EXST | 0.137 | 0.049 | 2.795 | 0.005 | Supported |
| H2: SSSC → MUSHE | 0.075 | 0.035 | 2.138 | 0.033 | Supported |
| H3: EXCR → EXST | 0.363 | 0.070 | 5.146 | 0.000 | Supported |
| H4: EXCR → MUSHE | 0.572 | 0.055 | 10.420 | 0.000 | Supported |
| H5: EXIN → EXST | 0.281 | 0.069 | 4.084 | 0.000 | Supported |
| H6: EXIN → MUSHE | 0.104 | 0.047 | 2.233 | 0.026 | Supported |
| H7: EXST → MUSHE | 0.167 | 0.042 | 3.938 | 0.000 | Supported |
| H8: EXST → HWB | 0.278 | 0.058 | 4.756 | 0.000 | Supported |
| H9: MUSHE → HWB | 0.374 | 0.062 | 5.989 | 0.000 | Supported |
SSCC = substantive staging of servicescape; EXST = experiential satisfaction; MUSHE = memorable unmanned smart hotel experience; EXCR = experience co-creation; EXIN = experience intensification; HWB = hedonic well-being
Source: Authors’ own creation
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Further reading
Kim, J.J., Han, H. and Ariza-Montes, A. (2021), “The impact of hotel attributes, well-being perception, and attitudes on brand loyalty: examining the moderating role of Covid-19 pandemic”, Journal of Retailing and Consumer Services, Vol. 62, p. 102634.
Liu, A., Ma, E., Wang, Y.C., Xu, S. and Grillo, T. (2023), “AI and supportive technology experiences of customers with visual impairments in hotel, restaurant, and travel contexts”, International Journal of Contemporary Hospitality Management, Vol. 36 No. 1.