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Article

Exploring the Factors Influencing Tourists’ Satisfaction and Continuance Intention of Digital Nightscape Tour: Integrating the Design Dimensions and the UTAUT2

by
Liang Rui
1,
Keyi Li
2,
Mu Jiang
1,* and
Xiaopu Jiang
3,*
1
School of Art, Soochow University, Suzhou 215123, China
2
School of Design, Jiangnan University, Wuxi 214000, China
3
Architecture & Design College, Nanchang University, Nanchang 330000, China
*
Authors to whom correspondence should be addressed.
Sustainability 2024, 16(22), 9932; https://doi.org/10.3390/su16229932
Submission received: 25 September 2024 / Revised: 4 November 2024 / Accepted: 11 November 2024 / Published: 14 November 2024
(This article belongs to the Section Tourism, Culture, and Heritage)
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Abstract

:
Digital transformation is a crucial option for nightscape tour to balance high-quality experiences and sustainable development in the new era. Tourists’ satisfaction and continuance intention are essential to the development of digital nightscape tour, but related research is insufficient. For this reason, by using the Chinese digital nightscape tour as a case study, this research integrates the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and the design dimensions (ambience, spatial layout, innovation, and cultural contact) to investigate the factors influencing tourists’ satisfaction and continuance intention. The research employed a convenience sampling method, selecting typical Chinese tourists who had experienced the digital nightscape tour as survey participants. A total of 650 responses were obtained. The results of Partial Least Square-Structural Equation Modeling (PLS-SEM) found that, firstly, UTAUT2, satisfaction, and ambience all directly predict continuance intention positively, with satisfaction having the strongest impact. Secondly, among the four variables of UTAUT2, social influence has the strongest impact on continuance intention. Thirdly, the design dimensions of the digital nightscape tour are very important, which indirectly affect continuance intention through satisfaction, with ambience having the greatest influence on continuance intention. The research conclusions help support the high-quality development of the digital nightscape tour.

1. Introduction

The rapid development of digital technology has revolutionized traditional ways of travel, bringing the tourism industry into the digital age and driving sustainable growth by attracting more tourists through enhanced experiences. The development of night tourism has gone through the 1.0 era focused on night market functions, and the 2.0 era, which focused on lights and landscapes [1,2], and it is gradually moving towards the 3.0 era characterized by “light and shadow +” digital experiences [3]. In the 3.0 era, the new digital nightscape tour shows multiple advantages. Tourist experiences have been digitally reconstructed with the support of 3D mapping, multi-channel projection, holographic projection, water mist projection, motion sensing, motion capture, and ambient sound technology. According to the 2023 Chinese Night Economy Development Report released by the China Tourism Academy, from January to August in 2023, the average number of night outings per month for Chinese tourists was 3.27, and the willingness of Chinese tourists to go out at night reached 95%. According to the report, the night economy ranks as Britain’s fifth-largest industry, comprising a minimum of 8 percent of the nation’s employment and generating GBP 60 billion in annual revenue. Night tourism is crucial to the nocturnal economy [4]. However, as a new product in the nightscape tour market, the digital nightscape tour has its limitations. Tourists’ satisfaction and continuance intention are essential for the sustainable development of the digital nightscape tour. Therefore, it is significant to investigate the relationship between the digital nightscape tour and tourists’ continuance intention.
Previous research has predominantly explored the impact of digitalization on the tourism industry from an economic standpoint, concentrating on aspects such as efficiency enhancement, market alignment, personalization of experiences, interactivity, and competitive advantage [5]. These studies underscore the practical benefits and resource management potential of digital technology in tourism [6]. Research on night tourism has mainly addressed the essence and structure of traditional night tourism [7] and its economic implications [8,9,10,11,12,13,14]. Various scholars have explored tourists’ satisfaction and continuance intention, considering factors such as destination image [15], brand image [16,17], perceived value, and destination attachment [18]. Research has found that the elements and factors impacting the traditional night tourism experience include ambience, activities, spatial display, cultural display, merchandise, crowds, etc. [1,19,20]. However, current research exhibits limitations in at least two significant areas: (1) It predominantly focuses on the digital economy’s role, addressing quality supervision, market control, and trading mechanisms in night tourism, with less attention towards tourist satisfaction and continuance intention. (2) While some research on night tourism includes digital performances [15,18,20], the emphasis remains primarily on traditional formats such as night markets, street stalls, museums, night economic districts, and cultural tourism hubs, with scant discussion on digital nightscape tour.
Therefore, new research must recognize the impact of digitization on night tourism. What factors impact tourists’ satisfaction and continuance intention in the digital nightscape tour? This gap becomes a critical issue for the sustainable development of the digital nightscape. The Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) represents pivotal frameworks for understanding individual continuance intention with technology [21,22]. Satisfaction is widely applied across various fields to elucidate individual continuance intention [23,24]. This study enhances the model by incorporating the design dimensions of the digital nightscape tour. The UTAUT2 model posits that individual technology acceptance is influenced not only by personal perceptions (such as performance and effort expectations) but also by external environmental factors (such as facilitating conditions and social influences) and personal characteristics (such as habits and hedonic motivation) [22,25]. Therefore, this study aims to develop a research hypothesis model by integrating the design dimensions and the UTAUT2, examining the factors that influence tourists’ satisfaction and continuance intention in the digital nightscape tour, considering both subjective and objective dimensions. The analysis of objective factors (atmosphere, spatial layout, innovation, cultural contact) and subjective factors (social influence, hedonic motivation, price value, habit) forms the basis for investigating the psychology and behavior of tourists in the digital nightscape tour. Employing model construction and empirical research, this study seeks to uncover the determinants of tourists’ satisfaction and continuance intention in the digital nightscape tour, offering crucial insights for the sector’s sustainable development.

2. Theoretical Background and Hypotheses

2.1. Digital Nightscape Tour

Night tourism is defined as various activities for leisure and entertainment carried out by tourists and urban residents in the city during the time from dusk to dawn [26]. The term “night tourism” originated from the “night economy”, which was proposed to address the issue of the hollowing out of British cities at night in the 20th century [26]. The British government and relevant scholars have focused on promoting night urban management and economic development from economic and sociological perspectives [27,28]. Consequently, the combination of the night economy and urban tourism has gradually elevated night tourism as a new travel form, extending traditional tourist hours [4]. Scholars’ attention has gradually shifted from the research of night consumption groups [29,30], social issues such as night crime, and public security management [31] to the research of night tourism [19,20].
Night markets, cultural heritage sites, and urban landscapes have become primary venues for night tourism. Night markets showcase the local charm and local cultural experiences by offering leisure activities such as shopping, entertainment, and local cuisine [19]. Cultural heritage sites employ lighting and projection techniques to vividly convey their historical narratives and cultural elements, thereby offering an immersive experience [32]. The urban landscape has greatly enhanced the quality of night experiences by optimizing lighting, creating safe and comfortable pedestrian environments, and incorporating diverse night activities [33]. In spatial terms, the three types of night tourism are not only entertainment spaces for tourists but also living spaces for residents. In temporal terms, night tourism combines the unique ambience of night and the leisurely nature of tourism within the shift between day and night [19]. Because of the time particularity and leisurely nature of night tourism, the urban landscape has become the main place for activities [20]. The incorporation of digital technology has gradually shifted night tourism activities from traditional lantern festivals and lantern parades to light and projection art [4], as shown in Figure 1. The digital nightscape tour blurs the boundary between reality and virtuality through the combination of its rich formats and digital technology [34]. Therefore, it is significant to research the factors impacting tourists’ satisfaction and continuance intention in the digital nightscape tour.

2.2. Factors Impacting Tourists’ Satisfaction and Continuance Intention

Pizam et al. [35] introduced the theory of tourist satisfaction, which posits that satisfaction arises from the comparison between tourists’ expectations and their actual experiences. Research indicates that tourists are happier when their expectations closely match their actual experiences. Liu and Jang [36], and Kozak and Rimmington [37] identified that objective conditions related to the destination, such as ambience, well-developed public facilities, and the level of service, are the main factors impacting tourists’ satisfaction. Similarly, Chang and Hsieh [1], and Kumar and Upadhya [30] noted that the level of satisfaction involves subjective factors such as the tourists’ motivation, behavior, and preferences.
The primary goal of early tourism activities is to guarantee customer satisfaction; however, nowadays, people recognize that continuance intention is also an important indicator of success. Saxena et al. [38] suggest that continuance intention reflects tourists’ attitudes toward a destination post-visit, which can help predict the likelihood of tourists’ returning and recommending behavior. Canny [39] uncovers the link between tourists’ satisfaction and their continuance intention. The findings demonstrate that higher levels of tourist satisfaction positively influence their intention to revisit, highlighting a strong correlation between satisfaction and return visits. Duong et al. [40] explored factors influencing tourists’ continued use of ChatGPT during travel, finding that satisfaction positively affected continuance intentions, particularly when technology anxiety was low and less so when anxiety was high. From the literature review, this study focuses on the satisfaction and continuance intention perception of night tourists towards digital technology.

2.3. Theoretical Background

2.3.1. UTAUT2

UTAUT2 is a user acceptance model proposed by Venkatesh et al. [25]. It is based on theoretical models such as the Theory of Reasoned Action, the Technology acceptance model, and The Model of Personal Computer Utilization, which extends to enhance the explanatory power of UTAUT for consumer willingness and behavior. The new model includes three additional indicators of hedonic motivation, price value, and habit, which together with the performance expectations, effort expectations, social influence, and facilitating conditions constitute seven independent variables. These independent variables positively impact the willingness to use and collectively promote the generation of usage behavior. The extension that was proposed in UTAUT2 rapidly raises the explanatory power of the variance of willingness and technology use. Considering that using a new technological environment will attract many tourists, some scholars have started applying the UTAUT2 model to the tourism industry, through, for example, the topic of tourists’ acceptance of virtual reality [22], the developmental promotion of virtual travel for tourism [41], the impact of digital stories on tourists’ behavior [42], and the determinants of tourists’ adoption of smartphone [43]. Related research has categorized the scope of UTAUT2 and assessed its impact on tourists’ continuance intention. For example, Amalia [44] utilized an enhanced UTAUT2 model to determine factors influencing the continuance intention to use a travel application, identifying hedonic motivation, system quality, habit, and performance expectations as pivotal. Coves-Martínez et al. [45] proposed an extended ‘continuance use’ model based on the UTAUT2 framework, finding that the UTAUT2 model and cultural factors positively affect tourists’ continuance intention. In conclusion, UTAUT2 has become one of the most critical and commonly used theories for design and tourism practitioners to measure tourists’ continuance intention.

2.3.2. Ambience and Spatial Layout

Bitner [46] identifies several dimensions that impact the service environment: ambience, spatial layout, functionality, signs, symbols, and artifacts. Intangible ambience refers to background features, like temperature, lighting, noise, music, and scents, that stimulate the five human senses [46]. Tangible spatial layout refers to the layout style of various landscapes, constructions, pathways, and their spatial relationships. Turley and Milliman [47] proved that spatial layout should include style, color, and size of constructions, lawns, and gardens, addresses, locations, and parking. Functionality refers to the ability of objects to facilitate performance and goal attainment [46]. In the hotel industry, Bertan [48] concluded that both ambience and spatial layout are crucial in fostering an emotional connection between customers and the hotel, significantly enhancing customer satisfaction and engagement. In the nightscape environments, Li et al. [19] proposed a scale searching for the impact of the nightscape environment on memorable tourism experiences. It includes four dimensions: spatial layout, staff, design, and ambiance. According to the abovementioned literature, this study identifies two particularly relevant dimensions of ambiance and spatial layout.

2.3.3. Innovation and Cultural Contact

Schumpeter [49] identified innovation as the process of implementing new ideas into practice, particularly significant within the competitive tourism market where innovation is almost a prerequisite for survival, sustainability, and industry growth [50]. Scott et al. [51] argued that tourism destinations are ideal for assessing innovation, and tourists’ perceptions of innovation are essential for the sustainability of these destinations. Zhang et al. [52] found that innovation can improve the tourists’ perception of a destination’s value and inspire their participation willingness. Innovation also can make the destination more attractive and impact tourists’ perceptions. Custódio et al. [53] emphasize the critical role of innovation in the development of tourism products, highlighting its necessity for maintaining competitive advantage and adapting to changing market demands. Işık et al. [54] stress the importance of service, organizational, and technological innovations in the tourism and hospitality sectors, especially for enhancing competitiveness and ensuring sustainability. Li et al. [19] pointed out that innovations can enhance the external environmental stimuli of night tourism and provide tourists with higher levels of demand than expected, thus increasing tourists’ pleasure and satisfaction.
Cultural contact is a concept commonly used in the tourism literature to evaluate how tourists engage with and experience different cultures during their travels [55,56]. Chen and Rahman [57] proposed that cultural tourism not only includes viewing cultural heritage but also encompasses experiential tourism, aiming to immerse tourists in novel and profound cultural experiences, encompassing intellectual, emotional, or psychological dimensions. Their findings suggest that cultural encounters involve both the “what” and “how” of culture, encompassing tourists’ use of cultural tourism resources and their specific behaviors related to cultural attractions [57]. Tourists want to enjoy the beauty, authenticity, and uniqueness of the products, aiming for learning experiences and knowledge [58]. Wang et al. [59] explore the complex relationship between cultural contact and innovation within China’s cultural heritage tourism sector. Their research underscores the need to manage the tensions between cultural preservation and innovation through “paradoxical thinking”, which promotes the simultaneous advancement of both elements. Li et al. [19] noted that the interaction between cultural encounters and tourists’ emotions can enhance satisfaction and create memorable night tourism experiences.

2.4. Hypothesis Development

2.4.1. UTAUT2 in the Context of Digital Nightscape Tour

The application of UTAUT2 to studying digital nightscape tour is justified for two reasons. First, UTAUT2 includes factors like hedonic motivation, price value, and habit, which effectively capture tourists’ perceptions of immersion and enjoyment in the digital nightscape tour [60]. Second, the experience of tourists in the digital nightscape tour relies on the integration of both passive technologies (such as artistic representations) and active technologies (like interactive installations) [61], such as water screen projections and somatosensory interactions. Thus, the variables in UTAUT2 are well-suited for predicting tourists’ behavioral intentions when interacting with technology. Furthermore, to gain a deeper understanding of tourists’ continuance intention in the digital nightscape tour, this study adapts UTAUT2 by replacing behavioral intention with continuance intention. Continuance intention encompasses not only the tourists’ decisions to revisit but also their willingness to continue participating in the experience or to recommend it to others, which is vital for assessing the long-term appeal of digital nightscape tour [44,45].
Based on the study by Venkatesh et al. [25], this study uses four sub-dimensions of UTAUT2, namely social influence, hedonic motivation, price value, and habit. The relevant studies show that, firstly, social influence significantly impacts tourists’ acceptance of new technologies [62,63]. In this study, social influence pertains to the satisfaction of tourists’ families, friends, or partners with the digital nightscape tour, and this satisfaction can influence tourists’ continuance intention. Secondly, hedonic motivation positively affects tourists’ experience of the technology and continuance intention [22,64]. Hedonic motivation refers to tourists’ intrinsic enjoyment. If they derive pleasure from the experience, they will develop their continued interest [45]. In this study, hedonic motivation can show the enjoyment experienced by tourists during the digital nightscape tour and positively impact continence intention. Thirdly, price value is a critical predictor of continuance intention. Rather than casting money, consumers will seek higher perceived benefits [25]. In this study, price value can evaluate the reasonableness and perceived value of the digital nightscape tour, and positively impact their continuance intention. Lastly, habit is another significant factor in predicting continuance intention [22,65]. Habit reflects the degree to which an individual perceives their behavior as instinctive and automatic [25]. In this study, habit assesses tourists’ preferences for the digital nightscape tour, their interests, and natural inclinations, all of which positively influence tourists’ continuance intention. In summary, this study formulates the following hypotheses for the digital nightscape tour:
H1: 
The social influence of the digital nightscape tour positively impacts tourists’ continuance intention.
H2: 
The hedonic motivation of the digital nightscape tour positively impacts tourists’ continuance intention.
H3: 
The price value of the digital nightscape tour positively impacts tourists’ continuance intention.
H4: 
The habit of the digital nightscape tour positively impacts tourists’ continuance intention.
In the digital nightscape tour, satisfaction can positively predict tourists’ continuance intention. For instance, if tourists are satisfied with a digital nightscape tour, they are more likely to revisit or recommend it to others, which is crucial for the long-term sustainability of digital nightscape tourism [23]. Furthermore, numerous studies have confirmed that continuance intention is primarily driven by tourists’ satisfaction levels [66,67]. In this study, to more precisely investigate the impact of different design factors on meeting tourists’ satisfaction in the digital nightscape tour, satisfaction was adapted by incorporating four design dimensions: ambience, spatial layout, innovation, and cultural contact. These dimensions were used to further refine the expectation variables. Built upon this foundation, this study further addresses the digital nightscape tour, and proposes the following hypothesis:
H5: 
Tourists’ satisfaction with the digital nightscape tour positively impacts their continuance intention.
In summary, UTAUT2 explains users’ behavioral intentions, specifically, factors influencing technology use. However, relying solely on UTAUT2 is inadequate for assessing satisfaction in the digital nightscape tour, complicating the analysis of tourists’ continuance intention. The integrated model that combines design dimensions emphasizes the objective external characteristics of the technology platform, whereas UTAUT2 focuses more on individual perceptions of the technology. The integration effectively explains tourists’ satisfaction and continuance intention in the context of the digital nightscape tour.

2.4.2. Impact of Ambience and Spatial Layout on Satisfaction

Ambience includes various background characteristics in the environment, such as temperature, light, noise, music, and scents [46]. Some research proved that although these factors may not be readily discernible, they can impact those individuals who have been in this environment for a long time [68]. Mehrabian and Russell [69] proposed the M-R model to demonstrate the impact of ambiance on behavioral intentions. This theoretical model states that the stimulus from an external environment can trigger individuals’ emotional response and thereby cause tourists’ behaviors of approaching or avoiding the environment [36]. Although this theoretical model is not specific to consumer environments, it has been demonstrated to elucidate the impact of ambience on consumer intentions [19,36].
Three main factors related to ambience include the following: Firstly, light plays a crucial role, dominating the digital nightscape tour. Bruner [70] found that under low-illumination conditions, tourists generate more positive emotions and feel more comfortable, and their comfort decreases with increasing light levels. Wu et al. [71] showed that exceptional lighting design in dimly lit environments could significantly enhance customers’ perceptions of the place and their intention to visit. Secondly, music plays a crucial role. Bruner [70] found that the structure, expressiveness, beats, volume, and speed of music affect tourists’ moods. For example, people who listen to slow music are usually more relaxed than those who listen to fast music, and tourists’ perception of time slows down when they are exposed to unfamiliar music [70]. Zhuang et al. [72] demonstrated that music can strengthen tourists’ emotional connections and behavioral intentions by evoking geographic imagination and aesthetic responses, thereby increasing the destination’s appeal and enriching the overall tourist experience. Lastly, smell also plays a critical role in enhancing the visitor experience. Spangenberg et al. [73] proved that different types of scents can impact sales, tour duration, diversity-seeking behavior, and perceptions of time. Drawing on these observations, this study sets forth the following hypotheses for the digital nightscape tour:
H6: 
The ambience of the digital nightscape tour positively impacts tourists’ satisfaction.
H7: 
The ambience of the digital nightscape tour positively impacts tourists’ continuance intention.
Spatial layout refers to the layout of machines, equipment and landscapes, including their size, shape, and spatial relationships [46]. In the digital nightscape tour, the spatial layout must accommodate special requirements such as light and shadow shows and interactive experiences. Bitner [46] proved that in order to satisfy consumers’ needs in unique environments, the spatial layout is significant. In such environments where tourists largely explore scenes independently with limited assistance from staff, a well-designed spatial layout can greatly enhance the tourist experience [36]. The study by Charousaei and Khakzand [74] highlights the key role of spatial layout in enhancing spatial quality and user satisfaction and that a proper spatial layout helps to optimize the functionality and accessibility of the space. Li et al. [19] pointed out that the comfort, convenience and privacy of the layout in night tourism significantly influence the creation of ambience and the overall tourist experience. Therefore, this study proposes the following hypothesis for the digital nightscape tour:
H8: 
The spatial layout of the digital nightscape tour positively impacts tourists’ satisfaction.

2.4.3. Impact of Innovation and Cultural Contact on Satisfaction

Innovation can change the showcase of local culture, festivals, and other attractions, enhancing the experience provided by cultural and creative tourism as it evolves from static to dynamic phases [75]. Csikszentmihalyi [76] notes that creative space and visualization can increase personal sensory and emotional experiences significantly. De Massis et al. [77] believe that innovation can become a catalyst, which encourages tourists to engage with the experience. Zhang et al. [52] pointed out that innovation fulfills tourists’ specific expectations for experiences, evokes their potential interest, and improves their travel intentions. The relevant studies about night tourism show that as an unexpected delight surpassing tourists’ expectation, innovation can enhance tourists’ expectation of night tourism [19]. Therefore, this study sets forth the following hypothesis for the digital nightscape tour:
H9: 
The innovation of the digital nightscape tour positively impacts tourists’ satisfaction.
Cultural contact can indicate the richness of a tourist’s experience and the extent of their engagement with local culture [78]. Relevant studies concluded that cultural contact enhances tourists’ sense of experience and reduces the suppression of emotions by habitual responses, thus stimulating stronger emotions [19]. Chen and Rahman [57] noted that when tourists use several ways to engage with local culture deeply, they will gain a more profound cultural understanding of the destination. Related studies indicate that during night activities, the tourists’ perception of local culture and lifestyle is crucial, and it can significantly increase their willingness to participate [57]. Zhang et al. [52] showed that cultural contact can significantly impact memorable tourism experiences, which, in turn, influences tourists’ intentions to revisit and their inclination to recommend the destination. Li et al. [19] concluded that the interaction between cultural contact and tourists’ moods can enhance the satisfaction of night tourists and help tourists to obtain more meaningful and remarkable experiences. This is an important factor that can enhance tourists’ satisfaction. Therefore, this study sets forth the following hypothesis for the digital nightscape tour:
H10: 
The cultural contact of the digital nightscape tour positively impacts tourists’ satisfaction.

3. Method

3.1. Data Collection Process

In this study, a convenience sampling method was employed to select a typical digital nightscape tour in China, with Chinese tourists who had participated or were participating in these tours serving as research subjects. Data collection proceeded through the following steps: Firstly, the initial measurement items were identified through routine internal meetings and discussions. Subsequently, these selected items underwent translation from English to Chinese, followed by a review of the original scale to assess content validity. Secondly, we selected five research sites: Shanghai Disneyland Nightscape, Changzhou Shenyin Nanshan Nightscape, Beijing Universal Studios Nightscape, Wuxi Nianghua Bay Nightscape, and Shandong Taierzhuang Ancient Town Nightscape. These sites were chosen based on several criteria: (1) each site incorporates various advanced digital technologies (Figure 1) and serves as a representative example of a digital nightscape tour; (2) each location leverages its unique cultural heritage, utilizing digital tools to integrate local historical and cultural narratives into the nightscape, thereby offering both entertainment and cultural enrichment; (3) the development and operation of these projects display significant expertise and serve as valuable case studies. We visited each site, provided a detailed explanation of the study’s purpose, distributed questionnaires, and obtained written consent from participants. Data collection occurred between late January and February 2024. Out of 650 questionnaires distributed, 634 were returned. After discarding 137 questionnaires due to incomplete or apparently random answers, 497 valid questionnaires remained. Table 1 presents the demographic characteristics and relevant information of the survey respondents.

3.2. Measures

In order to be more accurate, this study used a seven-point Likert scale ranging from 1 (completely disagree) to 7 (completely agree). This study used ten variables as predictors to examine the acceptance and satisfaction of the digital nightscape tour, and reworded and modified the measurement items in the UTAUT2 to fit the context of the digital nightscape tour. The variables used and examples of the statements are presented in Table 2. Four measurement items for ambience and three for spatial layout were derived from the study of Li et al. [19]. Four measurement items for innovation and three for cultural contact were derived from the study of Zhang et al. [52]. The measurement items for satisfaction and continuance intention were sourced from Boo and Busser [21]. Measurement items for social influence, hedonic motivation, price value, and habits were derived from UTAUT2 research [22,25]. After completing the questionnaire design, a preliminary test was conducted with twelve university students to enhance its readability and content validity. Based on the feedback received, adjustments were made to the language to eliminate potential ambiguities and misunderstandings.

3.3. Data Analysis

The data underwent statistical analysis using SPSS 27.0 and AMOS 28.0. The measurement model testing comprised two steps. Initially, confirmatory factor analysis (CFA) assessed the validity and fit of the model. Subsequently, Cronbach’s α coefficients were computed to evaluate the reliability and internal consistency of each subscale. Finally, PLS-SEM was used to analyze the relationships among various variables and the model’s adequacy.

4. Results

4.1. The Measurement Model

The reliability and validity of the measurement model should be evaluated by several metrics, including model fit, Cronbach’s α coefficient, standardized factor loadings, convergent validity, and discriminant validity. According to the research of Schumacker and Lomax [79], a factor loading value exceeding 0.5 is indicative of a strong relationship. Table 2 demonstrates that all constructs in this study meet the criterion for factor loading. Moreover, Cronbach’s α coefficients for all constructs exceeded 0.8, indicating excellent internal consistency.
According to the research of Fornell [80], the assessment of convergent validity constitutes two key metrics: composite reliability (CR) and average variance extracted (AVE). For all concepts, CR should be greater than 0.70, and AVE should be greater than 0.50. Table 2 illustrates that all 11 constructs in this study meet these criteria. The research of Chin [81] shows that discriminant validity necessitates the square root of the AVE to surpass the correlation coefficients between the construct and others. Table 3 demonstrates that the measurement model fits this requirement, indicating robust discriminant validity.
Referring to the recommended standards of Hu and Bentler [82], the measurement model fit in this study is deemed satisfactory. Table 4 shows that χ2/df (chi-square/degrees of freedom) = 1.755, GFI (goodness-of-fit index) = 0.913, AGFI (adjusted goodness-of-fit) = 0.891, IFI (incremental fit index) = 0.971, TLI (Tucker–Lewis index) = 0.965, and CFI (comparative fit index) = 0.971, and the RMSEA (root mean square error of approximation) = 0.039.

4.2. Structural Equation Model

A PLS-SEM test was conducted on the research model and the results show that the data standards were acceptable. Table 4 shows that χ2/df = 2.942, GFI = 0.855, AGFI = 0.828, IFI = 0.921, TLI = 0.911, CFI = 0.920, and RMSEA = 0.063. All the results of the hypotheses are illustrated in Table 5, unequivocally supporting all hypotheses.
Social influence (β = 0.148, p = 0.000), hedonic motivation (β = 0.129, p = 0.002), price value (β = 0.143, p = 0.000), habit (β = 0.098, p = 0.003), and ambience (β = 0.146, p = 0.002) were positively related to continuance intention, supporting hypotheses H1, H2, H3, H4, and H6, respectively. Satisfaction was positively related to continuance intention (β = 0.272, p = 0.000), supporting hypothesis H5. Ambiance (β = 0.221, p = 0.000), spatial layout (β = 0.156, p = 0.000), innovation (β = 0.225, p = 0.000), and cultural contact (β = 0.213, p = 0.000) were positively related to satisfaction, supporting hypotheses H7, H8, H9 and H10, respectively. The validated structural model of this study is shown in Figure 2.

4.3. Analysis of Direct, Indirect, and Total Effects

In order to identify the factors that have the strongest influence on tourists’ continuance intention in the digital nightscape tour, we calculated the direct, indirect, and total effects of the factors on continuance intention in the research model, as shown in Table 6. The findings revealed that, firstly, satisfaction exerted the most substantial total effect, underscoring its pivotal role in bolstering tourists’ continuance intention. Secondly, concerning the design dimension, ambience emerged as the predominant influencer of continuance intention.

5. Discussion and Conclusions

5.1. Discussion

This study integrates UTAUT2, and the design dimensions to explore the internal perceptions of experiences and the digital objective factors provided by suppliers. It analyses how these elements influence tourists’ satisfaction and continuance intention to engage with digital nightscape tour.
First, satisfaction positively impacts the continuance intention. The conclusions of this research echo the findings of Shin et al. [83] and Abrate et al. [24]. It also illustrates that the digital technologies within the nightscape context can improve tourists’ satisfaction and willingness to revisit the landscape and foster a greater propensity of them to recommend it to others [84].
Next, from the theoretical perspective of UTAUT2, social influence, hedonic motivation, price value, and habit play significant roles in augmenting tourists’ continuance intention towards digital nightscape experiences. This is similar to the results of Gupta et al. [43], Wu et al. [65], and Huang [22]. In the context of the digital nightscape tour examined in this study, social influence and price value can highly improve tourists’ continuance intention, but hedonic motivation and habit exhibit comparatively weaker influences on continuance intention. This finding is in contrast to that of Amalia [44], who found that hedonic motivation and habit significantly impact the continuance intention of using digital technologies. The rationale behind these findings is multifaceted. Firstly, the experiences of digital nightscape tour not only attract tourists but also encourage their family and friends to enjoy it. Secondly, tourists derive hedonic motivation primarily from the enjoyment of digital technology and positive emotional experiences [85]. Digital projection shows and interactive experiences can enhance tourists’ hedonic motivation to a degree [42]; however, their appeal significantly varies among individuals and is not universally effective, thus limiting their impact on continuance intention. Thirdly, tourists usually tend to develop habits through gamified experiences, but the repeatability and playability of digital nightscape tour are so void that tourists are less inclined to have more experiences, thus weakening their impact on continuance intention [64]. Finally, appropriate pricing strategies and tailored digital experiences can moderately stimulate continuance intention among tourists [43].
Finally, within the design dimensions, factors such as ambience, spatial layout, innovation, and cultural contact exerted a significant positive influence on tourists’ satisfaction. In previous analyzes of tourism products, Zhang et al. [52] and Li et al. [19] found that ambience and spatial layout indirectly shape tourists’ experiences by influencing their psychological perceptions, while innovation and cultural contact impact internal assessments and regulate emotions and engagement. This study finds that ambience, spatial layout, innovation, and cultural contact in the digital nightscape tour significantly influence tourists’ satisfaction, which in turn affects their continuance intention. These findings are in contrast to those of Choi et al. [86], who reported that public space design and atmospheric factors did not significantly affect tourists’ satisfaction. The rationale behind these findings is multifaceted. Firstly, ambience enhances tourists’ satisfaction through explicit elements such as projections, lighting, smells, and music, eliciting profound impressions and emotional resonance [36,46]. Secondly, spatial layout improves tourists’ visiting efficiency and reduces the stress for travelers in complex night environments by using implicit elements like landscape arrangement and facility placement [46,74]. Thirdly, innovation is linked to the psychological needs of tourists. Stimulating experiences can evoke meaningful and memorable feelings, thus reinforcing satisfaction [87]. Lastly, creative cultural contact evokes tourists’ curiosity and engagement with local cultures and helps foster a deeper sense of identification and connection, which, in turn, bolsters recognition and appreciation of the digital nightscape tour [52].

5.2. Conclusions

This study empirically analyzed typical Chinese tourists visiting digital nightscape tour attractions and reached the following conclusions: (1) Tourists’ continuance intention is significantly influenced by satisfaction and UTAUT2 elements (social influence, hedonic motivation, price value, and habit), with satisfaction having the most substantial impact on continuance intention, while social influence plays a crucial role in promoting it. (2) The design dimensions (ambience, spatial layout, innovation, and cultural contact) indirectly affect continuance intention through satisfaction, with ambience having the most significant impact.

6. Contributions and Shortcomings

6.1. Theoretical Contributions

The development of the digital nightscape tour introduces new challenges to traditional night tourism research. This study explores factors influencing tourist satisfaction and continuance intention, providing empirical evidence for the sustainable development of digital nightscape tour.
This study makes a theoretical contribution to the following three areas. Firstly, the prior studies about night tourism concentrate on the night market [29,30]. This study is based on the prior studies but shifts its attention to new-style night tourism incorporating innovative digital technology. It delineates the digital nightscape experience and explores its formation mechanism. Secondly, prior studies used the UTAUT2 model to analyze people’s willingness to use digital technology like VR and smartphone apps [22,43,83]. In reality, it is an online digital experience for tourists. Grounded on prior studies, this study analyzes digital nightscape tour, which is the offline digital experience for tourists. Thirdly, previous studies on the expansion of UTAUT2 have mainly focused on exploring perceptual usability and quality [83]. This study further refines the UTAUT2 from the design dimensions. This integration overcomes the limitations of using a single model and offers a more comprehensive approach to analyzing tourist satisfaction and continuance intention.

6.2. Practical Implications

This study offers the following recommendations for designers and managers of a digital nightscape tour.
Firstly, this study proves that social influence, hedonic motivation, habit, and price value positively impact tourists’ continuance intention. Designers and managers should leverage interactive technology to create multi-user experiences tailored to tourists and their companions’ needs. Spaces should be designed to encourage social interactions and differentiated play scenarios should be developed for various groups to enhance interactions among tourists, fostering connections and increasing the overall liveliness and immersive quality of the experience [61]. Moreover, designers and managers can create various consumption scenarios to enrich the experiences and, at the same time, ensure that the price is reasonable [88]. They can focus on personalized and tailored services for tourists. By using big data to analyze the preferences of tourists from different demographic backgrounds and gain an accurate insight into the needs of tourists, they can also provide tourists with personalized services at different stages before, during and after the tour to satisfy the individual needs of tourists [89], for example, providing tourists with information on available tour options prior to the tour and recommending suitable activities for tourists; making exclusive guide services during the tour, and offering personalized content such as cultural products and souvenirs afterward; facilitating deeper engagement and stimulating sharing to encourage return visits and thus enriching the overall tourist experience [89].
Secondly, this study proves that innovation and cultural contact positively impact tourists’ satisfaction. Therefore, a digital nightscape tour must enhance and improve the interactive features of digital technology, increase the added value of creativity, and make good use of the “landscape + technology” strategy [90]. It is necessary to maximize the dynamic appeal of local cultures through digital experiences. For example, showcasing local traditional elements, festivals, and handcrafts can enable tourists to immerse themselves in the culture and history for a diverse experience [91]. A digital nightscape tour requires an immersive experience design that integrates virtual and real-world interactions. For example, interactive games can be set up using augmented reality (AR) technology to showcase the local historical background and cultural details. This kind of design can fully immerse tourists in the virtual environment and enhance the interactive experience through real-time feedback, thereby increasing tourists’ satisfaction with the digital nightscape tour and their continuance intention [92].
Thirdly, this study confirms that ambience and spatial layout positively impact tourists’ satisfaction. So, designers and managers can foster the development and promotion of nightscape ambience. From a digital standpoint, designers can cooperate with professional technical teams to create dynamic nightscapes that are both beautiful and fun to watch with landscape structures [19]. Therefore, designers can build a unique nightscape tour by creating a coherent theme of lighting design featuring projections, lasers, neon, fiber optics, LEDs, searchlights, and floodlights [93]. In some special situations, designers can create panoramic ambient sound and scent generators in the environment in order to put an emphasis on visual, auditory, and olfactory unity at key nodes [94,95]. Moreover, it is also recommended for designers and managers to avoid the crowding of areas or homogenization of landscapes so as to create differentiated and dynamic nightscape itineraries. Guiding the nocturnal flow of tourists through strategic spatial and road design is essential. Establishing observation points along major thoroughfares and tourist routes can help foster an accessible and pleasant night tourism setting [2].

6.3. Limitations and Future Research Suggestions

This study has theoretical, design, and management implications, but it also has some limitations. Firstly, this result focuses on the Chinese digital nightscape tour; so, the conclusions of the study cannot be fully applied to the global digital nightscape tour. Therefore, future studies can cover more areas as different cities and changes in sample size may lead to different conclusions. Secondly, this study employs quantitative research methodologies, with subsequent studies incorporating a combination of quantitative and qualitative methods to enhance the validity of the findings. Due to potential selection bias among users of digital technologies, the findings may be sample-specific. Future research may concentrate on the differences and similarities of response aspects of digital technology attributes between digital technology users and non-users. In addition, some participants in this study may be familiar with the digital nightscape tour, introducing a potential bias in the sample. Lastly, this study does not specifically delineate the different digital tourism technologies and the types of night tours. The distinct technological implementations and forms of night tourism may exhibit unique relationships and impacts. Subsequent research can develop more detailed and precise measurement items for the digital nightscape tour, further test the validity of the research scale, and incorporate other variables to explore their impacts on tourists’ satisfaction and continuance intention in order to promote the sustainable development of the digital nightscape tour.

Author Contributions

Conceptualization, L.R. and K.L.; methodology, L.R.; software, L.R.; validation, L.R., K.L., M.J. and X.J.; formal analysis, L.R.; investigation, L.R. and K.L.; resources, L.R. and K.L.; data curation, L.R. and K.L.; writing—original draft preparation, L.R. and K.L.; writing—review and editing, L.R. and K.L.; visualization, L.R.; supervision, L.R., M.J. and X.J.; project administration, L.R., M.J. and X.J.; funding acquisition, M.J. and X.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of School of Art of Soochow university.

Informed Consent Statement

Informed consent was obtained from all subjects involved in this study.

Data Availability Statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Acknowledgments

I would like to express my sincere gratitude to Mu Jiang for supporting my participation in academic conferences and related research forums. I am also deeply thankful to Keyi Li for assisting me with numerous data analysis challenges and offering valuable guidance on English expression and paper development.

Conflicts of Interest

We confirm that neither the manuscript nor any parts of its content are currently under consideration or published in another journal. The authors have no conflicts of interest to declare concerning this work.

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Figure 1. Digital nightscape tour.
Figure 1. Digital nightscape tour.
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Figure 2. The research model with its standardized coefficients. *** p < 0.001, ** p < 0.01.
Figure 2. The research model with its standardized coefficients. *** p < 0.001, ** p < 0.01.
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Table 1. Demographic information of the participants.
Table 1. Demographic information of the participants.
CharacteristicOptionFrequencyPercent
Participating night toursShanghai Disneyland Nightscape14328.8%
Changzhou Shenyin Nanshan Nightscape9418.9%
Universal Studios Nightscape7314.7%
Wuxi Nianhuawan Nightscape6112.3%
Shandong Taierzhuang Ancient Town Nightscape6012.1%
Other Nightscape6613.3%
GenderMale19940%
Female29860%
Age18~30 years old30862%
31~50 years old11923.9%
51~60 years old499.8%
Over 60 years old214.2%
Income level (¥)CNY Below 2000 6412.9%
CNY 2000–5000 17334.8%
CNY 5000–10,000 16833.8%
CNY 10,000–20,000 6212.4%
CNY Over 20,000 306%
EducationJunior high school and below92%
High school/Vocational school6112.3%
College9619.2%
University25250.7%
MBA or above7915.8%
Table 2. Results of construct validity and reliability analysis.
Table 2. Results of construct validity and reliability analysis.
Latent VariableMeasurement VariableFactor
Loadings		MeanStd. DevαAVECR
Social
influence		SI1. People who are important to me think that I should experience the digital nightscape tour.0.9125.08 1.32 0.9010.753 0.901
SI2. People who influence my behavior think I should experience the digital nightscape tour. 0.859
SI3. People whose opinions I value prefer that I experience the digital nightscape tour.0.830
Hedonic
motivation		HM1. I think experiencing the digital nightscape tour is fun.0.9275.42 1.26 0.8820.7220.886
HM2. I think experiencing the digital nightscape tour is enjoyable.0.834
HM3. I think experiencing the digital nightscape tour is very entertaining.0.781
Price
value		PV1. The digital nightscape tour is reasonably priced.0.8505.06 1.29 0.8850.720 0.885
PV2. The digital nightscape tour is good value for the money. 0.807
PV3. At the current price, the digital nightscape tour provides a good value.0.888
HabitHT1. The use of the digital nightscape tour has become a habit for me.0.9334.77 1.38 0.8810.722 0.886
HT2. I am addicted to experiencing the digital nightscape tour.0.831
HT3. Experiencing the digital nightscape tour has become natural to me.0.778
SatisfactionSA1. Overall, I am satisfied with the digital nightscape tour.0.8385.42 1.190.8850.724 0.887
SA2. I am happy with my experience with the digital nightscape tour.0.883
SA3. On the whole, I am satisfied with my experience in the digital nightscape tour.0.830
Continuance intentionCI1. I have the intention to continue experiencing the digital nightscape tour in the future.0.8925.19 1.29 0.8890.731 0.890
CI2. I will continue to experience the digital nightscape tour as much as possible.0.806
CI3. In the future, I will continue to experience the digital nightscape tour.0.865
AmbienceAMB1. I think the lighting arrangement in the digital nightscape tour is just right.0.8925.16 1.27 0.8900.674 0.891
AMB2. I think the music arrangement in the digital nightscape tour is comfortable.0.809
AMB3. I think the smell in the digital nightscape tour is pleasant.0.739
AMB4. I think the digital art in the digital nightscape tour can evoke emotions.0.837
Spatial
layout		SL1. The digital nightscape tour provided a comfortable sightseeing space.0.8435.09 1.20 0.8430.643 0.844
SL2. The overall layout of the digital nightscape tour is convenient to visit.0.813
SL3. The overall layout of the digital nightscape tour prioritizes the privacy of tourists.0.747
InnovationINN1. The form of the digital nightscape tour experience is novel.0.9055.31 1.30 0.9030.703 0.904
INN2. This experience challenged my existing ideas about the digital nightscape tour.0.816
INN3. This experience provided new ideas for a digital nightscape tour.0.826
INN4. The digital nightscape tour experience here is creative.0.804
Cultural
contact		CC1. I like the local customs, rituals, and lifestyles reflected in the digital nightscape tour.0.8835.32 1.23 0.8630.688 0.868
CC2. I like to experience different recreational activities related to local culture during the digital nightscape tour.0.856
CC3. I want to learn about cultural differences through the digital nightscape tour.0.742
Table 3. Discriminate validity of the research model.
Table 3. Discriminate validity of the research model.
ConstructsSIHMPVHTSACIAMBSLINNCC
SI0.868
HM0.418 **0.850
PV0.387 **0.393 **0.849
HT0.273 **0.189 **0.389 **0.850
SA0.526 **0.576 **0.481 **0.229 **0.851
CI0.463 **0.439 **0.440 **0.331 **0.520 **0.855
AMB0.426 **0.367 **0.349 **0.245 **0.493 **0.436 **0.821
SL0.292 **0.369 **0.368 **0.260 **0.445 **0.340 **0.391 **0.802
INN0.334 **0.458 **0.399 **0.191 **0.542 **0.378 **0.429 **0.449 **0.838
CC0.332 **0.410 **0.268 **0.170 **0.501 **0.361 **0.400 **0.379 **0.473 **0.829
** p < 0.005.
Table 4. The goodness of fit indices for the measurement model and research model.
Table 4. The goodness of fit indices for the measurement model and research model.
Modelχ2/dfGFIAGFIIFITLICFIRMSEA
Measurement model1.7550.9130.8910.9710.9650.9710.039
Research model2.9420.8550.8280.9210.9110.9200.063
Recommended criteria<3.0>0.8>0.8>0.8>0.8>0.8<0.08
Table 5. The results of the hypotheses’ test.
Table 5. The results of the hypotheses’ test.
HypothesesHypothesized PathBβS.EtResult
H1SI→CI0.1480.1750.0443.348 ***Supported
H2HM→CI0.1290.1530.0413.110 **Supported
H3PV→CI0.1430.1620.0423.371 ***Supported
H4HT→CI0.0980.1300.0332.949 **Supported
H5SA→CI0.2720.2750.0574.784 ***Supported
H6AMB→CI0.1460.1740.0483.060 **Supported
H7AMB→SA0.2210.2610.0405.545 ***Supported
H8SL→SA0.1560.1670.0463.393 ***Supported
H9INN→SA0.2250.2680.0405.545 ***Supported
H10CC→SA0.2130.2400.0444.878 ***Supported
*** p < 0.001, ** p < 0.01.
Table 6. Direct, indirect, and total effects among the variables.
Table 6. Direct, indirect, and total effects among the variables.
Dependent VariableIndependent VariableDirect EffectIndirect EffectTotal EffectR2
CIAMB0.1740.0720.2460.296
SL_0.0460.046
INN_0.0740.037
CC_0.0660.066
SA0.275_0.275
HT0.130_0.130
PV0.162_0.162
HM0.153_0.153
SI0.175_0.175
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MDPI and ACS Style

Rui, L.; Li, K.; Jiang, M.; Jiang, X. Exploring the Factors Influencing Tourists’ Satisfaction and Continuance Intention of Digital Nightscape Tour: Integrating the Design Dimensions and the UTAUT2. Sustainability 2024, 16, 9932. https://doi.org/10.3390/su16229932

AMA Style

Rui L, Li K, Jiang M, Jiang X. Exploring the Factors Influencing Tourists’ Satisfaction and Continuance Intention of Digital Nightscape Tour: Integrating the Design Dimensions and the UTAUT2. Sustainability. 2024; 16(22):9932. https://doi.org/10.3390/su16229932

Chicago/Turabian Style

Rui, Liang, Keyi Li, Mu Jiang, and Xiaopu Jiang. 2024. "Exploring the Factors Influencing Tourists’ Satisfaction and Continuance Intention of Digital Nightscape Tour: Integrating the Design Dimensions and the UTAUT2" Sustainability 16, no. 22: 9932. https://doi.org/10.3390/su16229932

APA Style

Rui, L., Li, K., Jiang, M., & Jiang, X. (2024). Exploring the Factors Influencing Tourists’ Satisfaction and Continuance Intention of Digital Nightscape Tour: Integrating the Design Dimensions and the UTAUT2. Sustainability, 16(22), 9932. https://doi.org/10.3390/su16229932

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