Factors Influencing Nighttime Tourists’ Satisfaction of Urban Lakes: A Case Study of the Daming Lake Scenic Area, China

Abstract

Tourist satisfaction of nighttime urban lakes as scenic areas, such as the Daming Lake, is influenced by multiple factors, which are crucial for tourists’ experiences and the sustainable development of these areas. This paper explores the factors impacting nighttime visitor satisfaction at the Daming Lake Scenic Area. Basing our studies on analysis of the literature and questionnaire surveys, the study constructs a visitor satisfaction evaluation index system based on the Expectancy-Disconfirmation Theory. Utilizing the revised importance-performance analysis method, the study identifies several significant influencing factors including the distinctive features of nighttime shopping products, the rich variety of nighttime tourscape and entertainment products, the aesthetically pleasing design of nighttime lighting products, the affordable price of nighttime dining products, and the diverse methods, reasonable pricing, and multimodal transit options of nighttime transportation. Furthermore, it finds the main factors that reduce tourists’ satisfaction in nighttime urban lakes include: premium pricing of nighttime shopping and dining products, transport infrastructure deficiencies, the cultural connotation of tourism products, and the safety of nighttime tourscape and entertainment products. This research provides insights to enhance satisfaction in urban lake scenic areas and expands the application of the tourist satisfaction theory.

1. Introduction

Urban lakes, essential to urban ecosystems and cultural landscapes, resemble city parks and play a pivotal role in regulating urban climates and enhancing environmental quality. Additionally, they serve as central attractions for city tourism due to their unique cultural and historical significance and are key drivers in the development of urban nighttime tourism [1]. Recent studies have highlighted that urban lakes boost urban livability by improving air quality and mitigating the urban heat island effect [2]. Moreover, the integration of cultural landscapes with natural environments significantly fosters the development of nighttime tourism and leisure activities [1]. The 2022 State Council guidelines, titled “Strengthening Urban Ecological Protection and Restoration”, underscore that lakes and wetlands are vital components of urban ecosystems, playing an essential role in enhancing residents’ quality of life and bolstering urban attractiveness. The importance of nighttime tourism has grown apparent in recent years, particularly within urban scenic and cultural areas, as it not only extends tourist stays but also stimulates the growth of the nighttime economy [3]. The development of nighttime tourism has received prioritization from the Chinese government, particularly through the Ministry of Culture and Tourism’s introduction of the “National Nighttime Cultural and Tourism Consumption Cluster” initiative [4], which encourages regions to develop nighttime tourism projects with local characteristics.

The analysis of tourist behavior has an important reference value for the development of night tourism in urban lake scenic areas. Tourist satisfaction is an important variable in the study of tourist behavior [5]. The influencing factors of tourist satisfaction determine the improvement of the tourist experience in scenic areas. At present, scholars often use three models such as the Expectancy-Disconfirmation Theory (EDT), SERVQUAL, and Kano mode to analyze tourist satisfaction [6]. Grounded in the EDT, this study posits that satisfaction is determined by the discrepancy between pre-visit expectations (e.g., regarding nightscape aesthetics, activity diversity) and actual perceived experiences (e.g., of lighting design, service convenience). This EDT foundation facilitates the identification of requirements standards and motivation gaps. Specifically tailored to an urban lake’s nighttime tourism context, we construct an EDT-based multidimensional satisfaction evaluation index system, covering critical domains like shopping, dining, transportation, sightseeing, and illumination. This system diverges from SERVQUAL’s exclusive focus on service quality dimensions (tangibles, reliability, etc.) by holistically incorporating context-specific elements, such as the cultural and environmental dimensions associated with nighttime lighting. Furthermore, unlike the Kano model’s attribute classification approach (basic, performance, and excitement), this study prioritizes developing a comprehensive evaluation framework uniquely suited to urban lake nighttime tourism. Methodologically, the research employs EDT alongside a revised Importance-Performance Analysis (IPA). To overcome traditional IPA’s reliance on subjective importance ratings, derived importance is calculated using partial correlation coefficients between individual satisfaction items and overall satisfaction. This refined IPA enables objective, data-driven identification of critical satisfaction factors. Applied within the context of Daming Lake—where media reports indicate a quadrupling of visitors following its free admission policy—despite the lack of official nighttime statistics, this approach yields actionable insights for enhancing the nighttime tourism experience.

The research question is divided into three levels of progressive questions. The first question is the basic question: “What are the components of satisfaction with night tourism in urban lakes?” The second question is an analytical question: “What is the relative importance of each element to overall satisfaction?” The third question is an applied question: “How to develop a prioritized improvement strategy with IPA analysis?”

This study aims to integrate a global theoretical framework with local empirical data to investigate nighttime tourism satisfaction and its influencing factors in urban lake scenic areas. Specifically, the research will: (1) Develop an evaluation index system for assessing tourist satisfaction with urban lake nighttime tourism; (2) apply the EDT to research nighttime tourism satisfaction of urban lakes; and (3) analyze the factors influencing nighttime tourism satisfaction with the IPA method to derive actionable recommendations for promoting the sustainable development of urban lake nighttime tourism.

The primary contributions of this paper are as follows: First, it examines tourist satisfaction in the context of nighttime tourism in urban lake scenic areas, thereby expanding the scope of research on tourist satisfaction; second, it attempts to establish an evaluation index system for assessing the satisfaction of nighttime tourism in urban lake scenic areas; and third, it innovatively integrates EDT with IPA to analyze tourist satisfaction in this specific context.

The structure of the subsequent sections of this paper is arranged as follows: The Section 1 introduces the background and significance of the thesis, research questions, research content and methods, research objectives and research contributions; Section 2 reviews the existing literature; the Section 3 outlines the research methodology, including details of the data collection procedures and sources utilized; the Section 4 presents the research findings; the Section 5 provides a comprehensive analysis and discussion of the results; and the Section 6 concludes with a summary of the paper and its corresponding conclusions.

2. Literature Review

2.1. Night Tourism

Nighttime tourism fundamentally comprises leisure-oriented engagements that occur after dusk, including but not limited to sightseeing, retail experiences, performance attendance, event participation, and social gatherings [7]. Temporally, these activities span from evening twilight until morning daylight [8], often operationally defined as occurring between 18:00 and 06:00 [9]. At its core, nighttime tourism embodies the dynamic interplay between visitors and destination cultures across multiple dimensions [10], with particular emphasis on nocturnal leisure experiences during travel [11]. Such research advances both sector-specific knowledge and broader urban development strategies through innovative analytical frameworks. As early as the 1990s, scholarly investigations into nighttime tourism had primarily examined its interconnection with the nighttime economy. International researchers progressively emphasized the nighttime economy’s growth, with European scholars identifying it as a viable approach to enhance social interaction and stimulate urban economic renewal [12]. The development of 24 h cities and vibrant entertainment districts demonstrated how temporally distributed tourism activities could mitigate overtourism by diverting visitor flows into evening hours, consequently alleviating daytime congestion at attractions [13]. Nighttime tourism embodies a complex sustainability paradox, balancing economic benefits against environmental degradation and socio-cultural disruption. Environmentally, while celestial ecotourism protects dark skies [14] and light festivals utilize energy-efficient technologies [15], excessive illumination exacerbates light pollution and energy waste [16], necessitating strategies to reconcile infrastructure optimization with ecological stewardship [17]. From a socio-cultural perspective, tourism–nightlife interactions reconfigure urban dynamics, generating polarized outcomes: community displacement in European cities [17] versus improved perceived safety through optimized lighting in Malaysian parks [18]. Spatially, empirical analyses indicate that China’s nighttime tourism clusters enhance resource efficiency [19], whereas Europe’s nighttime economy accounts for over 15% of urban tourism revenue [20], though unmanaged growth may transform economic gains into net social losses [21]. Sensory design, as exemplified by Xi’an’s landscapes [22], enriches visitor experiences but risks eroding authenticity through over-commercialization [2]. These contradictions underscore the imperative for context-sensitive frameworks to harmonize economic, environmental, and socio-cultural sustainability in nighttime tourism development.

2.2. Tourism Satisfaction

Current research on visitor satisfaction predominantly employs evaluation models tailored to diverse geographical contexts and tourism sectors. A prominent methodological approach is the Importance-Performance Analysis (IPA), applied to assess gaps between visitor expectations and actual experiences in cultural and creative parks, particularly regarding service quality and product innovation [23,24]. Parallel studies in cultural tourism leverage the perceived value theory to analyze developmental challenges, offering insights into operational management inefficiencies [25]. Spatial and demographic factors further shape satisfaction dynamics. For instance, rural tourism studies reveal that visitor origin significantly influences satisfaction levels, with local residents reporting a higher satisfaction than non-locals, whereas demographic variables (e.g., gender, age) exhibit negligible effects [26]. Similarly, research on Guangzhou’s forest parks identifies thirteen determinants—spanning service quality, accessibility, and environmental conditions—though their relative impacts vary considerably [27]. Qualitative investigations in ancient villages further establish positive correlations among situational involvement, authenticity, destination image, and satisfaction through mixed methods approaches [28]. Notably, contemporary satisfaction studies uncover sustainability paradoxes. The COVID-19 pandemic exposed the fragility of nighttime tourism economies, as seen in declining satisfaction among cultural tourists [29], contrasting with Malaysia’s community-centric lighting strategies that enhance sustainability through place-making [18]. However, as Christou et al. [30] demonstrate in Cyprus, the predominance of socializing motives in nightlife experiences frequently marginalizes environmental sustainability concerns among tourists. This dissonance underscores a critical misalignment between sustainable tourism frameworks and actual nocturnal consumer behavior.

2.3. Nighttime Tourism in Urban Lake Scenic Areas

In contrast, research on urban lake nighttime tourism remains fragmented. As integral components of urban landscapes, urban lakes have only been peripherally examined in urban nighttime tourism studies. Current research exhibits significant deficiencies in understanding the developmental evolution, socio-ecological impacts, and service management aspects of nighttime tourism, with most findings scattered within the broad scope of urban tourism research [31]. This dispersion has resulted in the insufficient systematic investigation of urban lake nighttime tourism. Existing urban tourism scholarship predominantly focuses on daytime activities, while paying relatively limited attention to nighttime tourism. Academic research on nighttime tourism has primarily concentrated on its relationship with the nighttime economy, with specialized areas such as urban lake nighttime tourism receiving notably less attention. Although the growing prominence of urban lakes in tourism and the expansion of nighttime markets have gradually increased research interest, studies remain largely exploratory. Most investigations continue to emphasize daytime tourism, resulting in limited cumulative research. Previous studies have examined urban lakes’ ecological functions in daytime microclimate regulation [32]; however, research on nocturnal ecological changes, the impacts of nighttime visitor activities on lake ecosystems, and the balance between tourism development and ecological protection remains scarce. Urban lake nighttime tourism involves complex, interrelated factors including natural environments, cultural contexts, and activity organization, leading to fragmented studies across cultural, ecological, and economic domains [33]. The development of such tourism requires the careful coordination of natural and cultural resources alongside lighting design and event planning challenges that complicate systematic research. Furthermore, most urban lakes maintain open-access policies, making official nighttime visitor statistics difficult to obtain [34], presenting a significant research obstacle.

3. Methods

3.1. Case Selection

The Daming Lake Scenic Area in Figure 1 is a natural lake located in Jinan. According to Jinan City, it is a national 5A-level tourist attraction and a representative urban lake tourism destination that had 11.505 million tourists in 2018 (accounting for 14.37% of the total number of tourists in Jinan). It is renowned for its abundant springs, expansive water surface, and picturesque landscape. In addition to its natural resources, the area is replete with cultural landmarks, including Lixia Pavilion, Arctic Pavilion, and Nanfeng Shrine, which collectively reflect its rich historical and cultural heritage. The scenic area provides convenient transportation options for tourists, and the buildings and bridges surrounding the lake are illuminated to create an immersive visual experience. Visitors can enjoy boat rides to appreciate the nighttime views of Daming Lake. Furthermore, lakeside food stalls and restaurants serve authentic Jinan cuisine. The integration of modern technology into lighting effects creates a stunning nighttime atmosphere, providing tourists with unforgettable visual experiences at Daming Lake.

The Daming Lake Scenic Area in Jinan not only possesses abundant tourism resources, but it also provides a strong foundation for night tourism products. Zhao Yijing classified night tourism products into six primary categories based on the locations and formats of night tourism activities: night landscape sightseeing, night festival tourism, night cultural and artistic leisure tourism, night performance experience tourism, block night tourism, and night scenic area tourism [10]. Zhou and Yao conducted comprehensive research on night tourism, building on previous studies, and classified it into three types: performance, landscape, and participatory. They further refined this classification in subsequent research, adding a comprehensive category and resulting in four types of night tourism [35]. A questionnaire was utilized to measure product satisfaction, considering three distinct nighttime product classification methods. Based on the characteristics of night tourism and the six elements of “food, accommodation, transportation, tourscape, shopping, and entertainment” in tourism activities, existing night tourism products at Daming Lake in Jinan were collected, organized, and summarized. Finally, these products were categorized into five groups: night shopping, night dining, night transportation, night tourscape [1] and entertainment, and night lighting. The specific products are detailed in

Table 1. Main nighttime tourism products of Daming Lake Scenic Area.

Typology	Main Nighttime Tourism Products
Nighttime shopping products	In addition to Daming Lake-themed cultural T-shirts, postcards, cultural and creative products, and crafts such as paper-cutting and clay sculptures, Jinan Longshan black pottery, hand-held pork, Zhoucun baked cakes, and lotus root noodles from Minghu Lake are also included.
Nighttime dining products	Furong Street Snack Street features a variety of food options, including Hong Kong Jia Wonton Noodles, DouDou Fried Yogurt, Afu Lucky Food, Furong Quan Roasted Chicken Feet, Yang’s Sesame Candy, and Pancake Rolled with Scallions. Kuanhouli Snack Street also offers Grandma’s Cuisine, Tri-State Roasted Pig’s Feet, Pin Fry, National Foot Stinky Bean Curd, Hand-Punched Shrimp Sliders, and Longji Shancheng Soup Dumplings. Additionally, the Ziyi Minghu Hotel, situated in the center of the Daming Lake Scenic Area, houses the “Night Banquet Minghu” restaurant, while Xiaobai Izakaya offers an atmosphere reminiscent of a late-night diner.
Nighttime transportation products	As of 1 June 2023, Jinan’s public transportation has been systematically enhanced, and the number of bus routes that are available after 22:00 is now 114. Cabs and online taxis in Jinan are also accessible at night through mobile software, providing convenience for citizens and tourists. Shared bike services are available near scenic spots that can be utilized at night, and bikes are rentable through mobile apps, thus facilitating short trips.
Nighttime tourscape and entertainment products	The Daming Lake Scenic Area is characterized by scenic tourism resources, including Wuyue Temple, Chaoran Building, and Thousand Buddha Reflection; culturally significant resources, such as Qu Shui Ting Street, Pearl Spring, and Jiefang Pavilion; notable attractions, including the Chaoran Building and the night tour around the lake; and well-known commercial resources, such as Kuanhouli and Shimao Plaza.
Nighttime lighting products	The night light show of the Chaoran Building, the night tour around Daming Lake, a special light show themed on the Chaoran Building and Daming Lake, and a night tour of cultural attractions are offered.

.

3.2. Research Method

This study applies the EDT as its core theoretical framework in Figure 2, integrated with a revised IPA approach, to systematically examine factors influencing tourist satisfaction in the nighttime tourism sector of the Daming Lake Scenic Area. Proposed by Oliver, EDT posits that tourist satisfaction is determined by the discrepancy between pre-visit expectations and perceived post-visit performance [36]. Positive disconfirmation (when performance exceeds expectations) enhances satisfaction, whereas negative disconfirmation diminishes it. This model effectively identifies gaps between tourists’ expectations and actual perceptions of critical attributes. Guided by this theory, our research design—from variable selection to data analysis—focuses on quantifying “expectation–perception” disparities.

While the Importance-Performance Analysis (IPA) framework is widely applied, it exhibits inherent limitations. Critically, IPA’s operationalization of “importance” remains ambiguous, potentially leading respondents to conflate importance with expectations or absolute importance with relative importance. This conceptual vagueness can diminish the model’s predictive validity. Furthermore, the IPA’s prescriptive utility is constrained: attributes with fundamentally divergent characteristics may reside within the same quadrant, yielding identical improvement strategies, whereas attributes sharing core similarities may fall into different quadrants, generating conflicting recommendations. This undermines the credibility of IPA-derived conclusions. To mitigate these biases and better capture authentic perceptions, our study adopts a revised IPA approach. Building upon Jin and Park’s methodology [37]—which integrates IPA, conjoint analysis, and an importance grid analysis to enhance sensitivity to attribute performance in rural tourism contexts—we operationalize derived importance. This is calculated via partial correlation coefficients between satisfaction with individual attributes and overall satisfaction, following Deng’s refinement [38]. The procedure involves: (1) computing natural logarithms of attribute-level satisfaction scores, and (2) conducting linear regression with these log-transformed values as independent variables against overall satisfaction. The resulting partial correlation coefficients serve as objective, data-driven importance metrics, enabling more precise identification of improvement priorities.

The derived importance and satisfaction scores construct a two-dimensional matrix, categorizing indicators into four strategic quadrants: (1) Priority Improvement Zone (high derived importance, low satisfaction): Address negative disconfirmation through corrective measures. (2) Resource Optimization Zone (low derived importance, high satisfaction): Reduce redundant investments. (3) Advantage Consolidation Zone (high derived importance, high satisfaction): Reinforce core competencies. (4) Low-Priority Zone (low derived importance, low satisfaction): Defer interventions. The IPA quadrant classification references the Kano model’s demand categorization, with Quadrant II corresponding to ”must-be requirements”.

Visual tools like scatter plots enhance the revised IPA’s interpretability, enabling the efficient identification of service gaps. This dynamic analytical framework not only improves data interpretation efficiency but also strengthens conclusion reliability through statistical optimization. The quadrant-based strategy offers managers a tiered optimization pathway: prioritizing high-gap areas, consolidating strengths, reallocating resources, and avoiding over-investment in low-impact attributes.

The methodology advances the theoretical understanding of nighttime tourism satisfaction while providing a rigorous, actionable solution for urban lake scenic areas—balancing academic rigor with practical implementation. This study identifies the key factors to improve the satisfaction of tourists in urban lake scenic areas and provides theoretical guidance for the development of night tourism in other urban lake scenic areas. In balancing economic, environmental, and socio-cultural sustainability, the findings help scenic planners develop science-based strategies. Compared with the SERVQUAL model, which mainly focuses on the improvement of service quality, and the Kano model, which focuses on product attribute optimization, this research paper provides an empirical basis and practical direction for the theory of sustainable development of night tourism from a macro perspective and expands the theoretical boundaries of night tourism research.

3.3. Research Steps

3.3.1. Questionnaire Design and Validation

The questionnaire was structured into two components: (1) The demographic profiling of respondents, capturing preferences across gender, age, occupation, and income levels related to visits to the Daming Lake Scenic Area; (2) a multi-dimensional satisfaction assessment of nighttime tourism products (five offerings), grounded in a theoretical framework that evaluated demand (safety needs, cultural experiences), motivation (social interaction, exploration), perception (price fairness, service efficiency), and subjective factors (commercialization tolerance, ecological concerns).

To measure the factors influencing nighttime tourists’ satisfaction, this study draws on the indicator system developed by scholars. Dong and Yang assess tourists’ experiences in attractions [39]. On the basis of the influencing factors of night tourism satisfaction adopted by systematic review scholars, Zhu used the improved Kano model to study the influencing factors of night tourism satisfaction [40]. Based on the research results of these scholars’ influencing factors, combined with the characteristics of night tourism in urban lake scenic areas, a three-tier evaluation indicator system for the experience of nighttime tourism products is constructed, with the evaluation of product satisfaction as the primary indicator. The secondary indicators include five variables: night shopping, night catering, night lighting, night tourscape and entertainment, and nighttime shopping products. Additionally, the 20 tertiary indicators are categorized into specific tertiary indicators based on the characteristics of night tourism products, as shown in

Table 2. Tourist satisfaction measurement system of nighttime tourism products in urban lake scenic areas.

Primary Indicators	Secondary Indicators	Tertiary Indicators
Satisfaction evaluation of night tourism products	Nighttime shopping products	The affordable price of nighttime shopping products
		The distinctive features of nighttime shopping products
		The quality of nighttime shopping products
		The rich variety of nighttime shopping products
	Nighttime dining products	The affordable price of nighttime dining products
		The rich variety of nighttime dining products
		The quality status of nighttime dining products
		The distinctive features of nighttime dining products
	Nighttime transportation products	The high safety of nighttime transportation
		The diverse methods of nighttime transportation
		The convenience and accessibility of nighttime transportation
		The affordable price of nighttime transportation
	Nighttime tourscape and entertainment products	The affordable price of nighttime tourscape and entertainment products
		The rich variety of nighttime tourscape and entertainment products
		The cultural connotations of nighttime tourscape and entertainment products
		The high safety of nighttime tourscape and entertainment products
	Nighttime lighting products	The rich variety of nighttime lighting products
		The cultural connotations of nighttime lighting products
		The coordination with the surrounding environment of nighttime lighting products
		The design of aesthetically pleasing of nighttime lighting products

.

Due to the large area of water surface in the urban lake scenic area, the visibility at night is lower than during the day, so the safety consideration is strengthened when setting the three-level indicators. At the same time, through the conclusions of previous studies [41,42], it is found that tourists have great expectations for exploring the cultural connotation of lake landscapes. Therefore, the cultural connotations of nighttime tourscape and entertainment products have been added to the indicator system.

The nighttime tourists’ satisfaction in urban lake scenic areas is measured using a 5-point Likert scale, with responses ranging from 1 = “Very dissatisfied” to 5 = “Very satisfied” (where 2 = “Slightly dissatisfied”, 3 = “Neutral”, and 4 = “Moderately satisfied”).

3.3.2. Questionnaire Collection

According to the tabular data in

Table 3. Reliability analysis table.

Project	Alpha	KMO	Number	Number of Valid Cases
Satisfaction	0.921	0.944	20	312
Satisfaction	0.920	0.938	20	212

, which compares the alpha and KMO values between 312 and 212 questionnaires, both Cronbach’s alpha coefficients exceed 0.9. This indicates that the scales used in the questionnaire exhibit high reliability, justifying further analysis. Additionally, the KMO values in Table 3 are all above 0.9, further confirming the robustness of the questionnaire’s reliability.

3.3.3. Survey Implementation and Data Collection

In this study, 350 questionnaires were distributed through the QuestionStar platform in March 2024 and May 2025. A total of 320 questionnaires were successfully returned, of which 312 were deemed valid. The collected data were subsequently analyzed. The respondents represented a diverse range of genders, ages, occupations, and income levels, ensuring a comprehensive sample that ultimately yielded more precise findings.

3.3.4. Sampling Representativeness Considerations

While the free admission policy at Daming Lake precludes access to official nighttime visitor demographics, the study implemented three key measures to ensure sample validity: first, temporal stratification was achieved by distributing surveys across all operating hours (18:00–22:00) on both weekdays and weekends. Second, spatial coverage was ensured through randomized sampling at four major access points (north/south/east/southwest gates). Third, demographic balance was verified through a post-collection analysis showing representative distributions: gender (47.76% male, 52.24% female) and age groups (21–30 years: 46.47%; 31–45: 19.87%; and 46–60: 21.15%).

4. Results and Analysis

4.1. Demographics

Table 4. Characterization of visitor demographics.

Effective Projects	Descriptive	Number	Percentage
Gender	Man	149	47.76%
	Woman	163	52.24%
Age	Below 20 years old	31	9.94%
	21–30 years old	145	46.47%
	31–45 years old	62	19.87%
	46–60 years old	66	21.15%
	Over 61 years old	8	2.56%
Career	Flexible workers	45	14.42%
	Students	132	42.31%
	Corporate employees	19	6.09%
	Self-employed	42	13.46%
	Civil servants/institutional employees	66	21.15%
	Retirees	8	2.56%
Income (CNY/month)	Below 1000	23	7.37%
	1001–3000	38	12.18%
	3001–6000	158	50.64%
	6001–10,000	61	19.55%
	Over 10,001	32	10.26%

reveals the following characteristics. The gender distribution indicates that males constitute 47.76% of the sample, while females account for 52.24%. Females are outnumbered by males in this study. Regarding age distribution, tourists aged 21–30 accounted for the largest share at 46.47%, closely followed by those aged 31–45 and 46–60, with proportions of 19.87% and 21.15%, respectively. In contrast, the number of tourists under 20 and those over 61 is relatively small, accounting for 9.94% and 2.56%, respectively. Tourists aged 21–30 are primarily students or young professionals who have recently entered the workforce and exhibit good physical fitness and energy. Conversely, tourists aged 31–45 may experience shifts in family roles accompanied by significant responsibilities, while those aged 46–60 may encounter physical fatigue associated with aging. Consequently, the participation rate in nighttime tourism activities among these groups tends to be lower. Meanwhile, individuals under 20 typically face academic pressures, while those aged 61 and above often experience limitations in physical health. As a result, tourists in these two age groups are less likely to engage in nighttime tourism activities.

Regarding occupation, students and civil servants/institutional employees account, respectively, for 42.31% and 21.15% of the sample, followed by self-employed (13.46%) and flexible workers (14.42%). Corporate employees and retirees represent, respectively, the smallest proportions of 6.09% and 2.56%. Since students, civil servants, and public organization employees generally experience lower life and work pressures, they tend to have more leisure time and energy compared to other groups. In contrast, corporate employees often work overtime due to job requirements, limiting their ability to participate in nighttime tourism activities. Meanwhile, retirees commonly face mobility challenges that hinder their engagement in such activities. The income distribution shows that 50.64% of tourists report monthly earnings between CNY 3001 and 6000, while 19.55% earn CNY 6001–10,000, and 12.18% earn CNY 1001–3000. Smaller proportions fall into higher and lower brackets: 10.26% earn above CNY 10,000 and 7.37% earn below CNY 1000. Therefore, when optimizing nighttime tourism offerings at Jinan’s Daming Lake, developers need to consider both the current tourism product landscape and tourists’ income levels to ensure appropriate pricing strategies.

4.2. Tourist Consumption Behavior Analysis

4.2.1. Tourist Preference Analysis

The data presented in

Table 5. Tourist preference analysis table.

Project	Number	Percentage
Night tourscape	162	51.92%
Food and beverage offerings	85	27.24%
Shopping	28	8.97%
Amusement rides	37	11.86%

indicate that the night tourscape of the Jinan Daming Lake Scenic Area is preferred by the majority of respondents, serving as the primary motivation for nighttime visits. This preference is followed by food and beverage offerings and amusement rides, while shopping ranked as the least preferred activity. The night view accounts for the highest percentage of tourist preference, indicating that visitors are predominantly attracted to the night tourscape of the Daming Lake Scenic Area. Furthermore, the “Chaoran Building” has emerged as a focal point of interest for nighttime visitors. Tourists exhibited the lowest preference for shopping, as the Daming Lake Scenic Area primarily emphasizes natural and cultural landscapes. Consequently, these scenic spots may prioritize providing tourism-related services, leading to reduced shopping needs among visitors.

4.2.2. Transportation Mode Analysis

The data presented in

Table 6. Analysis of transportation modes.

Project	Number	Percentage
Walking	100	32.05%
Cycling	41	13.14%
Self-driving	62	19.87%
Taking a taxi	38	12.18%
Taking a bus	46	14.74%
Others	25	8.01%

indicate that the majority of tourists preferred walking as their primary mode of transportation. The proportions of visitors choosing other transportation methods—including self-driving, taking a taxi or bus, cycling, and alternative options—remained relatively consistent. This preference for pedestrian mobility may be attributed to several factors: The narrow road infrastructure surrounding Daming Lake Scenic Area, which limits vehicular access and frequently causes congestion; the inherent convenience of walking compared to self-driving; and the particularly suitable nighttime ambiance for pedestrian activity. These findings collectively demonstrate a clear preference for walking among tourists visiting the area.

4.2.3. Overall Product Satisfaction Analysis

The survey results reveal distinct patterns in tourist satisfaction and recommendation intentions at the Jinan Daming Lake Scenic Area. Regarding satisfaction levels, 47.12% of respondents report relative satisfaction, while 29.81% express high satisfaction, and 10.58% indicate average satisfaction. Conversely, 6.73% report relative dissatisfaction, and 5.77% express strong dissatisfaction. These findings suggest that there is room for improvement in the visitor experience.

Concerning recommendation likelihood, 54.81% of tourists indicate a willingness to recommend the site, comprising 28.21% who would strongly recommend it, and 26.60% who would recommend it with suggestions for improvement. However, 20.19% remain uncertain about recommending it, while 25.00% would not recommend it. This distribution demonstrates a generally positive visitor perception of the scenic area.

The intention to revisit data show that only 37.18% of tourists would return, compared to 62.82% who would not. This reluctance stems primarily from two factors: (1) The limited number of nighttime attractions compared to daytime offerings, which restricts visitors’ experiences; and (2) the lack of novel experiences after the initial visit, reducing the site’s appeal for repeat visits.

Furthermore, through the analysis of the satisfaction evaluation results of tourists of different age groups (shown in

Table 7. Comparison of tourist satisfaction by age group.

Age	N	$\overline{\mathit{x}}\pm \mathit{s}$	F	p
Below 20 years old	31	4.03 ± 1.063	3.773	0.01
21–30 years old	145	4.04 ± 0.964
31–45 years old	62	4.02 ± 0.896
45–60 years old	66	3.33 ± 1.351
Over 61 years old	8	3.88 ± 0.996

), it is found that there are significant differences in the satisfaction of different age groups (F = 3.773, p = 0.01 < 0.05). As shown in Table 7, tourists aged 21–30 exhibit the highest mean satisfaction score ($\overline{x}\pm s$ = 4.04 ± 0.964) among all age groups, with this value being significantly greater than that of other cohorts. In contrast, the 46–60 age group displayed the lowest mean satisfaction score ($\overline{x}\pm s$ = 3.33 ± 1.351), reflecting comparatively poorer evaluation outcomes among all demographic segments.

4.3. Multivariate Analysis of Tertiary Indicators

Table 8. Goodness of fit test ^b table.

Model	R	R2	Adjusted R2	Error in Standard Estimation
1	0.851 a	0.724	0.705	0.624

Note: ^a. Predictive variable: the 20 tertiary indicators in Table 2. ^b. Dependent variable: overall satisfaction.

shows that the variance (R-squared) explained by all predictor variables is 72.4%, and the adjusted R-squared (a more reliable explanatory power indicator considering the number of independent variables) is 70.5%. This indicates that the selected combination of independent variables has a strong explanatory power for overall satisfaction, and the model fitting effect is good.

In

Table 9. Significance test results of regression equation (F-test).

ANOVA a
Model		Sum of Squares	Freedom	Mean Square	F	Significance
1	return	266.316	20	13.316	38.165	0.000 b
	residual	101.530	291	0.349
	total	367.846	311

Note: ^a. Predictive variable: the 20 tertiary indicators in Table 2. ^b. Dependent variable: overall satisfaction.

, the F-statistic of the regression model is 38.165, corresponding to a significance level of p = 0.000, p < 0.001, indicating that the regression model is statistically significant. Overall, this set of independent variables has statistical significance in predicting the dependent variable.

The data presented in

Table 10. Regression coefficient significance test results (T-test).

Coefficient a
Model		Non-Standardized Coefficient		Standardization Coefficient Beta	t	Significance	Collinearity Statistics
		B	Standard Error				Tolerance	VIF
1	(Constant)	0.307	0.14		2.183	0.03
	The affordable price of nighttime shopping products	0.013	0.032	0.016	0.398	0.691	0.586	1.707
	The distinctive features of nighttime shopping products	0.134	0.037	0.149	3.592	0	0.548	1.823
	The quality of nighttime shopping products	0.015	0.032	0.018	0.462	0.645	0.644	1.554
	The rich variety of nighttime shopping products	0.039	0.034	0.045	1.123	0.262	0.583	1.714
	The affordable price of nighttime dining products	0.065	0.031	0.087	2.123	0.035	0.567	1.763
	The rich variety of nighttime dining products	0.079	0.033	0.091	2.356	0.019	0.635	1.576
	The quality status of nighttime dining products	0.034	0.033	0.041	1.033	0.302	0.615	1.627
	The distinctive features of nighttime dining products	0.051	0.033	0.061	1.55	0.122	0.606	1.65
	The affordable price of nighttime tourscape and entertainment products	0.043	0.035	0.049	1.234	0.218	0.607	1.648
	The cultural connotations of nighttime tourscape and entertainment products	0.054	0.031	0.068	1.733	0.084	0.609	1.643
	The rich variety of nighttime tourscapes and entertainment products	0.105	0.031	0.138	3.379	0.001	0.565	1.77
	The high safety of nighttime tourscape and entertainment products	0.056	0.032	0.071	1.747	0.082	0.568	1.76
	The rich variety of nighttime lighting products	0.016	0.033	0.019	0.482	0.63	0.581	1.721
	The coordination with the surrounding environment of nighttime lighting products	0.051	0.035	0.058	1.448	0.149	0.583	1.716
	The cultural connotations of nighttime lighting products	0.031	0.033	0.038	0.935	0.351	0.56	1.787
	The aesthetically pleasing design of nighttime lighting products	0.094	0.034	0.109	2.73	0.007	0.599	1.67
	The diverse methods of nighttime transportation	0.085	0.035	0.101	2.463	0.014	0.568	1.762
	The convenient and unobstructed nighttime transportation	0.035	0.033	0.043	1.06	0.29	0.581	1.722
	The high safety of nighttime transportation	0.031	0.037	0.034	0.845	0.399	0.57	1.756
	The affordable price of nighttime transportation	0.057	0.028	0.08	2.04	0.042	0.616	1.623

Note: ^a Dependent variable: overall satisfaction.

indicate that the regression analysis revealed several significant predictors of overall satisfaction. Among these, the distinctive features of nighttime shopping products exhibit the strongest positive impact, with a beta coefficient of 0.149 (p < 0.001), indicating its pivotal role in enhancing satisfaction levels.

The rich variety of nighttime tourscapes and entertainment products also demonstrates a statistically significant influence (β = 0.138, p = 0.001), ranking prominently among contributing factors and exerting substantial positive effects on nighttime tourism satisfaction.

The aesthetically pleasing design of nighttime lighting products emerges as another significant contributor (β = 0.109, p = 0.007), warranting attention for its measurable positive effects. Similarly, the rich variety of nighttime dining products shows a meaningful predictive value (β = 0.091, p = 0.019), suggesting that culinary diversification effectively elevates satisfaction.

The affordable price of nighttime dining products (β = 0.087, p = 0.035) and the diverse methods of nighttime transportation (β = 0.101, p = 0.014) both achieve statistical significance, confirming that reasonable pricing and multimodal transit options positively influence outcomes. Finally, the affordable price of nighttime transportation (β = 0.08, p = 0.042) likewise demonstrates significant effects, underscoring the importance of equitable pricing structures in transportation services.

4.4. Revised IPA

Utilizing Deng’s revised IPA [35] conducted with SPSS 27 software, the natural logarithm of tourists’ satisfaction for each evaluation index is initially computed. Subsequently, the natural logarithm of each evaluation index and overall satisfaction is analyzed using a partial correlation, yielding partial correlation coefficients that represent implied importance, as presented in

Table 11. The importance and tourist satisfaction of each evaluation indicator.

Serial Number	Evaluation Indicator	Satisfaction	Derived Importance
1	The affordable price of nighttime shopping products	3.12	0.508
2	The distinctive features of nighttime shopping products	3.34	0.436
3	The quality of nighttime shopping products	3.3	0.485
4	The rich variety of nighttime shopping products	3.21	0.503
5	The affordable price of nighttime dining products	3.12	0.57
6	The rich variety of nighttime dining products	3.31	0.459
7	The quality status of nighttime dining products	3.34	0.482
8	The distinctive features of nighttime dining products	3.17	0.485
9	The affordable price of nighttime tourscape and entertainment products	3.38	0.454
10	The cultural connotations of nighttime tourscape and entertainment products	3.25	0.529
11	The rich variety of nighttime tourscapes and entertainment products	3.34	0.535
12	The high safety of nighttime tourscape and entertainment products	3.28	0.5
13	The rich variety of nighttime lighting products	3.3	0.476
14	The coordination with the surrounding environment of nighttime lighting products	3.49	0.441
15	The cultural connotations of nighttime lighting products	3.22	0.495
16	The aesthetically pleasing design of nighttime lighting products	3.37	0.46
17	The diverse methods of nighttime transportation	3.22	0.495
18	The convenience and accessibility of nighttime transportation	3.25	0.509
19	The high safety of nighttime transportation	3.38	0.426
20	The affordable price of nighttime transportation	3.25	0.592

Average extended importance of each evaluation indicator: 0.49. Average tourist satisfaction of each evaluation indicator: 3.28.

and Figure 3. The mean value of importance for each evaluation index is 0.49, while the mean value of tourist satisfaction across these indices is 3.28. Utilizing the importance and tourist satisfaction for each evaluation index, a two-dimensional coordinate system for the revised IPA is constructed. The importance serves as the horizontal axis, while tourist satisfaction is represented on the vertical axis. The mean values (0.49, 3.28) define the origin, and the four quadrants are plotted to illustrate the positions of each evaluation index.

Figure 3 depicts the IPA results, where the horizontal axis represents the perceived importance of tourists and the vertical axis represents satisfaction. Quadrant explanation is as follows: Quadrant I (high importance/high satisfaction) represents the zone where the destination is manifested well and efforts should be maintained; Quadrant II (low importance/high satisfaction) indicates resource optimization zone; Quadrant III (low importance/low satisfaction) represents low-priority zone; Quadrant IV (high importance/low satisfaction) emphasizes key zones that require priority improvement.

4.4.1. Advantage Consolidation Zone (Quadrant I)

Quadrant I represents evaluation indicators with both high satisfaction and high importance, which is highly consistent with the core connotation of the EDT. In this theory, when the perceived performance of a tourism product or service exceeds the initial expectations of tourists, a positive disconfirmation occurs, thereby significantly enhancing tourist satisfaction. The only indicator in this quadrant—“the rich variety of nighttime tourscape and entertainment products”—has a performance score far exceeding the mean, which precisely reflects such a positive disconfirmation effect.

From the perspective of EDT, tourists have clear and high expectations for the variety of nighttime tourscapes and entertainment products in urban lake nighttime tourism, which is their core expectation. Daming Lake’s nighttime landscape and entertainment offerings, represented by the light show using dynamic projection technology to present historical scenes like the “Buddha Mountain Reflection”, have a perceived performance that surpasses these high expectations. This not only meets tourists’ aesthetic needs but also conveys cultural stories to create additional value, resulting in a strong positive disconfirmation. According to EDT, this positive disconfirmation directly leads to high satisfaction, which is consistent with the high satisfaction shown by this indicator. It also confirms that high quality tourism products that exceed expectations can effectively improve satisfaction, which is an important embodiment of the application of EDT in the tourism experience research.

4.4.2. Resource Optimization Zone (Quadrant II)

In the EDT framework, this quadrant, where satisfaction is high but importance is low, can be interpreted as follows: although tourists’ initial expectations (expectancy) for these attributes are low, their perceived performance (performance) is high, thus generating a positive disconfirmation. These factors—including distinctive features and the quality of nighttime shopping products, the rich variety and quality status of nighttime dining products, the affordable price of the nighttime tourscape and entertainment products, the coordination with the surrounding environment and aesthetically pleasing design of nighttime lighting products, and the high safety of nighttime transportation—all show that their actual performance exceeds the low expectations of tourists.

According to EDT, these attributes are not the core factors that tourists focus on, so their initial expectations are not high. However, the good performance of these attributes has brought unexpected surprises to tourists, resulting in high satisfaction. But from the perspective of resource allocation, since the importance of these attributes is low, even if the performance is improved further, the positive disconfirmation generated will not have a significant impact on overall satisfaction, because the degree of influence of disconfirmation on satisfaction is also related to the importance of the attribute in EDT. Therefore, according to EDT, managers should maintain the current service level, avoid excessive investment in these attributes to prevent the marginal benefit from diminishing, and transfer resources to attributes with higher importance (Quadrants I and IV), so as to optimize the overall tourism experience effect based on the EDT.

4.4.3. Low-Priority Zone (Quadrant III)

Attributes in this quadrant have both low importance and low satisfaction, which is in line with the prediction of the EDT for low-importance and low-performance attributes. In EDT, when tourists’ expectations for an attribute are low (due to low importance) and the perceived performance is also low, the disconfirmation generated is either negative but with low intensity or even close to zero. Because the low importance means tourists will not pay much attention to these attributes, even if the performance is not good, it will not have a significant impact on their overall satisfaction.

Take the distinctive features of nighttime dining products as an example. Tourists do not have high expectations for the distinctiveness of nighttime dining products in Daming Lake’s nighttime tourism (low importance). At the same time, the actual performance of this attribute is also not good (low satisfaction). According to EDT, the disconfirmation here is weak, so it has little impact on overall tourist satisfaction. Therefore, managers do not need to rush to invest resources to improve these attributes. Instead, they should follow the guidance of EDT, focus on attributes with higher importance, and allocate resources to areas where they can generate significant positive disconfirmation so as to improve the overall tourism satisfaction more effectively.

4.4.4. Priority Improvement Zone (Quadrant IV)

Quadrant IV represents the critical priority improvement zone in the IPA framework, comprising attributes that exhibit significant negative disconfirmation between high importance expectations and low satisfaction performance. These foundational elements—including the affordable price and rich variety of nighttime shopping products, the affordable price of nighttime dining products, the cultural connotations and high safety of the nighttime tourscape and entertainment products, the cultural connotations of nighttime lighting products, the diverse methods, the convenience, accessibility, and affordable price of nighttime transportation—constitute basic “must-be” requirements under the Kano model, where their absence or poor performance severely diminishes tourist satisfaction while their presence only maintains baseline satisfaction levels. The case study of Daming Lake reveals concrete manifestations of these gaps, particularly in premature bus service termination and inadequate wayfinding systems, which directly violate tourists’ fundamental expectations of accessibility and safety. According to EDT, these attributes demonstrate the most severe expectation–performance discrepancies, demanding immediate managerial attention. Three strategic interventions are warranted: (1) targeted infrastructure upgrades to meet minimum service standards, (2) resource reallocation from over-performing Quadrant II attributes, and (3) policy innovations such as extended transit hours and enhanced signage systems. This tripartite approach ensures optimal resource allocation to bridge the most critical expectation–performance gaps. The management strategy particularly emphasizes cost-effective solutions for these basic requirements, allowing strategic resources to be preserved for high-impact factors in Quadrant I.

Guided by EDT, this revised IPA framework enables a tiered resource-allocation strategy: Advantage Consolidation Zone (Quadrant I), Resource Optimization Zone (Quadrant II), Low Priority Zone (Quadrant III) and Priority Improvement Zone (Quadrant IV). Such an approach ensures efficient resource utilization while maximizing experiential value for nighttime tourism in urban lake scenic areas.

5. Discussion

5.1. Key Findings

5.1.1. Premium Pricing of Nighttime Shopping and Dining Products Undermines Tourist Satisfaction in Urban Lake Scenic Areas

The findings reveal that attributes such as affordable pricing of shopping and dining products fall within the priority improvement zone (high importance, low satisfaction). Specifically, the premium pricing of nighttime tourscapes and entertainment products at Daming Lake significantly exceeds market averages, leading to reduced tourist satisfaction. This aligns with Oliver’s EDT paradigm [36], wherein prices surpassing the threshold of tourists’ “perceived economic rationality” result in the perceived value falling short of expectations, thereby diminishing satisfaction. Dong and Yang [39] further note that while leisure tourists exhibit relative price elasticity for functional consumption, excessive premiums erode trust in the overall experience. Conversely, Zhou and Yao [35] demonstrate that tourists show a higher willingness to pay for cultural value-added products (e.g., Daming Lake’s “Ten Scenic Views”), yet current market homogenization exacerbates the imbalance between pricing and value propositions.

5.1.2. Transport Infrastructure Deficiencies Undermine Tourist Satisfaction in Nighttime Tourism

The findings reveal that nighttime transportation issues—including early bus suspensions, taxi surcharges, and inadequate signage—significantly diminish tourist satisfaction. This reflects a clear case of negative disconfirmation, where visitors’ basic expectations for transportation services (e.g., convenience, affordability, and accessibility) remain unmet. For instance, poorly designed signage directly contradicts tourists’ anticipation of “hassle-free navigation”, aligning with Tribe and Snaith’s assertion that “service accessibility forms the foundation of satisfaction [43].” Furthermore, traffic congestion and price surges disrupt the desired “escapist experience” central to nighttime tourism [44]. A comparative analysis with Xi’an’s successful “Great Tang All-Day Mall” [22]—which implements dedicated nighttime shuttle services and dynamic crowd management strategies—reveals transferable best practices for enhancing visitor experiences at Daming Lake. Beyond functional optimizations, integrating experiential elements into transportation services (e.g., introducing “ancient-style night tour buses” to enhance immersion) could bridge the current gap between infrastructure and visitor expectations.

5.1.3. The Cultural Connotation of Tourism Products Significantly Influences Tourist Satisfaction in Urban Lake Scenic Areas’ Nighttime Tourism

The failure of Daming Lake’s nighttime products and lighting design to effectively convey cultural narratives is the main driver of low satisfaction. On the one hand, the lighting design of historical landmarks is not embedded with local cultural symbols such as “Foshan Reflection” and “Spring Water Legend”, and the lack of symbolic representation leads to inconsistent experiences, which confirms the view of Liu et al. that visual displays without a narrative cannot evoke emotional resonance [11]. On the other hand, the lack of interactivity in cultural performances and the lack of integration of technologies such as AR interaction to promote visitor participation contrasts with the successful case of enhancing cultural immersion through role-playing and scene reconstruction in Xi’an’s “Chang’an Twelve Hours” themed area [22], highlighting the critical role of interactivity in bridging the expectation–perception gap.

5.1.4. Nighttime Tourscape and Entertainment Products Fail to Provide Adequate Security in the Urban Lake Scenic Area

There are insufficient safety details for the night view of Daming Lake, such as the lack of safety tips in the landscape area, where the simple sign “Be careful of falling into the water” is only set up on the lakeside plank road, and key information such as water depth and emergency phone numbers are not marked. Insufficient surveillance coverage at night (e.g., no cameras at some corners of Qushuiting Street) and slow emergency response (tourists reported waiting for security personnel for more than 15 min) led to the insufficient perception of “safety and security capabilities” among tourists. In addition, safety explanations for recreational activities are not in place, such as cruise ship drivers not detailing how to use life jackets, which weakens the sense of trust in safety. Traditional safety studies in scenic spots mostly focus on daytime activities (e.g., mountaineering safety), but this study is consistent with the conclusion of Ngesan et al. [18] that “insufficient lighting” and “sparse crowding” in nighttime scenes will magnify safety hazards. For example, urban parks in Malaysia have increased night patrols to improve their sense of safety, while Daming Lake lacks similar measures, resulting in an insufficient psychological safety perception, which confirms the difference in scenarios where “night safety needs require special responses” [16]. The essence of the security gap in Daming Lake is the imbalance between “two-dimensional demand” and “insufficient supply”—physical security only meets some basic standards, but the supply of psychological safety is significantly missing, resulting in the superposition of negative inconsistency effects in EDT.

5.1.5. Weakened Demand for Distinctive Dining Products in Nighttime Compared to Daytime in Urban Lake Scenic Areas

The attributes of nighttime dining products, particularly their distinctive features, demonstrate both below-average importance and satisfaction scores. This finding supplements the existing view that distinctive dining requirements differ significantly between daytime and nighttime scenarios. Previous studies have primarily focused on the importance of distinctive dining characteristics in daytime tourism contexts, identifying “local uniqueness” as a core variable enhancing visitor satisfaction [1,41]. However, our study reveals that tourists’ demand for distinctive dining features is markedly diminished in nighttime settings, with basic functional factors (e.g., convenience, price) becoming prioritized instead. For instance, the prevalence of fast-food options in the Guangzhou Chimelong Tourist Resort’s nighttime dining offerings aligns with the “dual deficiency in distinctiveness” (low importance and satisfaction) observed at Daming Lake. This phenomenon supports the theory of “contextual demand downgrading due to time scarcity in nighttime tourism.” Specifically, the time-constrained nature of nighttime visits leads tourists to prioritize efficiency over experiential dining, resulting in a weakened demand for culturally unique or elaborate culinary experiences. This demand divergence phenomenon is similarly reflected in the shopping sector.

5.2. Theoretical and Methodological Comparisons with Existing Research

Theoretically, in contrast to traditional urban tourism studies that predominantly focus on daytime activities, this research represents the first systematic investigation into the multidimensional influencing factors of urban lake nighttime tourism. While Xiong highlighted resource efficiency in nighttime tourism clusters [19], their work did not examine the unique factors specific to natural aquatic environments. Our identification of the “lighting–ecological coordination” dimension substantiates Wen’s concerns about how excessive lighting may compromise natural landscape authenticity [22], while also providing a new theoretical lens for the sustainable development of urban lake nighttime tourism.

Methodologically, this study advances the traditional Importance-Performance Analysis (IPA) method by using the partial correlation coefficient to calculate the derived importance score, so as to overcome the subjective weighting limitation of the traditional IPA. In this study, the revised IPA proposed by Deng is used to calculate the “derived importance” through the partial correlation coefficient [39], and the objective data is used as a measure of importance to avoid subjective bias. For example, in the case of Daming Lake, the method objectively identifies “The affordable price of nighttime transportation” (derived importance 0.592) as a high-priority improvement item, while the traditional IPA may lead to the misjudgment of priority due to tourists’ subjective cognitive bias, which verifies the scientific validity of the method. At the same time, Jin and Park integrated the IPA and joint analysis in rural tourism research [34], focusing on attribute combination effects. For the first time, this study applies “derived importance” to the nighttime tourism scene of urban lakes, and the indicator system focuses more on nighttime characteristics (such as the “coordination between lighting and environment”).

While the existing literature theoretically emphasizes the importance of cultural representation, it lacks concrete guidance on integrating cultural symbols into actual nighttime lighting designs. Using Daming Lake as a case study, we provide actionable insights for practice, demonstrating how cultural symbols can enhance nighttime tourism experiences. Furthermore, our findings reveal that nighttime transportation services require special attention beyond basic functionality, including operational hours, modal diversity, and wayfinding, aspects frequently overlooked in daytime tourism transportation research.

5.3. Limitations and Future Directions

This study has three main limitations. Firstly, the sample was predominantly composed of individuals aged 21–30 (46.47%), resulting in an inadequate representation of elderly tourists. Secondly, the absence of official nighttime visitor statistics, attributable to the site’s free admission policy, prevented direct representativeness benchmarking. However, as noted in Section 2.3, the implemented sampling protocol provides reasonable confidence in the data’s validity for examining satisfaction determinants within the studied context. Thirdly, the single-case design focusing solely on Daming Lake precludes cross-regional comparisons. Fourthly, the analysis did not account for seasonal variations in nighttime tourism patterns. Future research could advance this field through four key directions: (1) employing mixed methods approaches incorporating in-depth interviews to explore the specific needs of middle-aged and senior tourists; (2) future research could benefit from partnering with municipal authorities to install automated people-counting system; (3) conducting comparative studies of urban lake nighttime tourism models (e.g., West Lake in Hangzhou, East Lake in Wuhan) to develop regional comparative frameworks; and (4) applying time-geography perspectives to examine how seasonal differences (summer vs. winter) in tourist spatiotemporal behaviors influence satisfaction metrics. Furthermore, the rapid development of smart tourism technologies presents promising opportunities to enhance research methodologies. Specifically, integrating IoT sensor data (e.g., real-time monitoring of lighting energy consumption and transportation flows) with tourist satisfaction models could significantly improve the assessment system’s robustness. Subsequent investigations should address current limitations through expanded datasets and more rigorous analytical protocols. Particularly promising is the incorporation of AI-driven techniques such as sentiment analysis to advance theoretical understanding of nighttime tourism experiences. This research trajectory would not only deepen theoretical insights into urban lake nighttime tourism but also provide evidence-based decision support for scenic area operations within the context of China’s “dual carbon” sustainability goals.

6. Conclusions

6.1. High Overall Satisfaction with Distinct Demographic Appeal

Urban lake scenic areas possess inherent advantages for nighttime tourism development by combining picturesque natural landscapes with rich cultural resources, with empirical data showing particularly high participation rates among young tourists (aged 21–30) who prioritize novelty-seeking and immersive experiences—key attributes effectively delivered through nighttime tourism offerings [45]. As exemplified by Jinan’s Daming Lake Scenic Area, which has gained significant recognition for its successful nighttime programs, visitor data analysis reveals young tourists demonstrate both elevated engagement and satisfaction scores, confirming strong market viability. These outcomes align with EDT, where perceived value emerges when experiences exceed pre-consumption expectations [36], as demonstrated by Daming Lake’s dynamic light installations, like the “Reflection of Foshan” projection mapping, that transcend conventional visual spectacles through embedded historical narratives, creating cognitive–emotional value that enhances satisfaction. To further strengthen its competitive position, Daming Lake could implement adaptive strategies from Seoul’s Cheonggyecheon Stream model that synergizes ecological preservation with cultural placemaking, including contextual art integration through site-specific installations, multi-stakeholder design approaches co-created with local artists to maintain authenticity and hydrological ecosystems, and temporal programming of seasonal light festivals to sustain novelty.

6.2. Strategic Preservation of Core Satisfaction Factors in Urban Lake Nighttime Tourism

The high-performance indicator “the rich variety of nighttime tourscapes and entertainment products” in Quadrant I serves as a fundamental driver of tourist satisfaction, exemplifying a positive expectation–perception dynamic within the Expectancy-Disconfirmation Theory (EDT) framework. This effect operates through two complementary mechanisms: (1) advanced technological reinterpretation of cultural heritage (e.g., the historically accurate light projections at Lixia Pavilion) that exceeds conventional illumination standards, and (2) strategic integration of cultural IP (e.g., the “Ten Scenes of Daming Lake” collection) into experiential products that address visitors’ unmet desires for authentic local cultural immersion. Daming Lake could build upon its current “Ming Lake Show” grand water-screen light performance by drawing inspiration from Hangzhou’s West Lake to deeply explore cultural IPs. It could create a similar water-based live performance like “Impression of West Lake” to meet tourists’ demands for nighttime tourism experiences. To sustain this competitive advantage, management should prioritize: (a) continuous technological innovation (including holographic displays and interactive projection systems), (b) deepened cultural storytelling (implemented through AR-guided tours and immersive installations), while vigilantly avoiding product standardization that could erode this crucial expectation–performance gap. These core differentiators demand targeted investment and systematic enhancement in the scenic area’s long-term development strategy.

6.3. Bridging Satisfaction Gaps Through Functional and Experiential Innovations in Nighttime Tourism

The findings provide clear operational guidance for urban lake scenic area management. For the Priority Improvement Zone (Quadrant IV), the Daming Lake Scenic Area should focus on three key interventions: (1) Extending the night bus service to 23:00, upgrading the wayfinding system to solve the complaints of tourists about the “early termination of service”, and building a “bus-bike-sharing” intelligent connection network, implementing transparent pricing of nighttime traffic and a “one-ticket” package mechanism to improve transportation diversity, convenience, and affordability; (2) implant cultural symbols such as “Spring Pulse Direction” to enhance the lighting cultural narrative, integrate the AR narrative of “Ten Views of Ming Lake” into the landscape entertainment, and implement anti-skid transformation and infrared early warning on the plank road around the lake to strengthen the cultural connotation and safety guarantee; and (3) implement a third-party quality control mechanism to standardize the pricing of shopping and catering products, so as to improve the current price premium problem.

For Advantage Consolidation Zone (Quadrant I), the “diversity of landscape entertainment” requires deepened cultural storytelling. Drawing lessons from Xi’an “Great Tang All-Day Mall’s” success, the area could develop immersive theatrical performances integrating natural features like the “Thousand-Buddha Mountain Reflection” with Jinan’s notable scholar culture, transforming passive viewing into interactive experiences. Regarding Resource Optimization Zone (Quadrant IV), reduced innovation investment in “dining distinctiveness” is advised, with focus shifted to standardizing existing snack preparation processes to maintain baseline satisfaction.

This three-pronged approach—comprising infrastructure optimization, ecological compliance, and experience enhancement—systematically addresses satisfaction gaps while balancing environmental, economic, and cultural sustainability. The proposed measures demonstrate how targeted operational adjustments can translate theoretical EDT principles into practical management solutions for urban lake nighttime tourism.

6.4. The Effectiveness of Research Methods

A revised IPA method was utilized in this study to conduct a comprehensive investigation into the factors influencing tourist satisfaction in nighttime tourism at the Daming Lake Scenic Area, demonstrating that this approach can accurately evaluate tourist satisfaction and identify critical areas for enhancement. This study offers a significant reference for future research on nighttime tourism in other urban lake scenic areas.