Impact of Moral Responsibility on Tourist Waste Reduction Intentions: A Case Study of Vientiane, Laos

Abstract

Tourism drives economic growth but also intensifies environmental pressure at travel destinations, particularly by exacerbating local challenges in waste management. Rather than merely testing the theoretical validity of the norm activation model (NAM), this study utilizes its key constructs—specifically moral and accountability variables—as a strategic framework to examine the psychological drivers of waste reduction in the urban context of Vientiane, Laos. Data from 382 domestic tourists were analyzed using ordinary least squares regression. Ascription of responsibility (AR) (β = 0.219, p < 0.001) was the strongest predictor of intention, followed by personal norm (PN) (β = 0.173, p < 0.01) and actual waste management behavior (β = 0.160, p < 0.01). Notably, environmental knowledge and awareness of consequences—factors often emphasized in traditional environmental campaigns—had no significant influence. The findings demonstrate that, in addressing urban waste challenges in developing regions, fostering internalized moral sentiments (AR and PN) is far more effective than mere pro-environmental education. This study concludes that sustainable waste management may benefit from operationalized interventions that activate personal accountability rather than relying solely on general environmental awareness.

1. Introduction

1.1. Research Background and Existing Problems

Tourism is a key driver of economic development, particularly in developing economies where it supports income generation and social mobility [1]. With global annual tourist arrivals expected to approach 1.4 billion [2], preserving environmental quality has become essential for sustaining destination competitiveness [3,4,5]. However, rapid tourism growth often accelerates environmental degradation, most visibly through the increasing volumes of solid waste that frequently overwhelm local management systems [6]. In popular destinations, this pressure intensifies during peak seasons when infrastructure is already strained. Some tourists fail to properly practice waste-sorting and show limited commitment to waste reduction [7]. To address this challenge, an urgent investigation into the psychological mechanism underlying waste minimization in tourist destinations is required.

1.2. Current Solutions and the Advantages and Disadvantages

Among diverse triggers, environmental knowledge is commonly viewed as a key driver of pro-environmental behavior. Assuming that greater ecological awareness encourages individuals to minimize waste, well-informed tourists would naturally adopt more sustainable practices [8,9]. However, empirical evidence remains mixed. For example, a knowledge–intention gap means that, while tourists are aware of good and bad aspects of harming the environment, they do not act consistently and responsibly [10]. This inconsistency suggests that knowledge alone rarely translates into behavioral change.

Actual waste management behavior can also be a key explanatory factor. Drawing on the principle of behavioral consistency, past actions tend to shape future intentions by reinforcing personal identity [11]. Tourists who routinely sort waste in daily life may internalize a responsible self-image that persists during travel. Accordingly, incorporating the previous behavioral tendencies of tourists may establish a behavioral mechanism by which moral obligation along with habitual practice supplement the knowledge–intention gap [9].

Providing environmental information does not automatically promote sustainable behavior unless it is mediated by a sense of personal obligation. Therefore, modeling environmental knowledge alongside the variables of the norm activation model (NAM) is essential to understand how cognitive awareness is transformed into internal moral drivers. Furthermore, since waste management is often a habitual practice, integrating “actual past behavior” into this model allows one to control for behavioral inertia, providing a more rigorous assessment of how the ascription of moral responsibility (AR) independently overcomes existing habits to shape new intentions. This integrated approach can address a critical research gap by characterizing the interplay between cognitive, habitual, and moral dimensions within a single empirical framework.

1.3. Methods and Advantages of Our Approach

Although previous studies [12,13] typically emphasize the sequential pathway of the NAM, wherein awareness of consequences (AC) and AR promote personal norm (PN) and ultimately influence tourist behavior (e.g., waste reduction intention), this study intentionally departs from this linear construction to examine AC, AR, and PN as simultaneous predictors. The theoretical rationale is twofold. First, in a complex urban tourism setting such as Vientiane, Laos, tourists are often exposed to immediate environmental cues that may activate moral sentiments (PN) and accountability (AR) concurrently rather than through a step-by-step cognitive process. Second, the recent literature suggests that NAM variables can operate through a parallel mechanism wherein AR can directly trigger behavioral intentions without being fully mediated by PN, especially when the environmental consequences (AC) are already highly visible and internalized. By modeling these constructs simultaneously, this study aims to identify the unique and relative contributions of each moral dimension, providing a more nuanced understanding of which specific psychological lever is most effective in driving waste reduction in a real-world high-pressure urban environment.

Rather than merely testing the validity of the NAM, this study utilizes its key constructs—specifically moral and accountability variables—as a diagnostic framework to explore the psychological drivers of waste reduction in the unique urban context of Vientiane, Laos.

1.4. Main Contributions and Structure of the Article

Despite increasing environmental pressures at tourism destinations, little is known about the psychological mechanisms that effectively reduce waste generation among tourists. Thus, this study aims to determine the importance of variables related to tourist waste reduction intentions through environmental knowledge, actual waste management behavior, and NAM constructs. By assessing the relative influence of these variables, this study provides scientific guidance for effectively and efficiently encouraging waste reduction behavior at tourist destinations.

The study is organized as follows: Section 2 provides a theoretical foundation for the study and background context for hypothesis development. Section 3 describes the research methods including the study area, data collection, and analytical procedures. Section 4 reports the main findings. Section 5 discusses the implications in terms of reducing waste in tourism destinations. Finally, Section 6 outlines the study limitations and provides suggestions for future research.

2. Literature Review and Hypothesis Development

2.1. Waste Reduction Intention at Tourism Destinations

Waste reduction intention refers to a person’s deliberate willingness to minimize waste generation during daily life or travel [14]. In behavioral research, intention is the most immediate precursor of action and a key motivational link between attitudes and behavior [11,15]. In environmental contexts, it reflects an individual’s readiness to translate ecological concern into practical waste-minimizing behaviors while traveling.

Although tourists may exhibit pro-environment behavior in their daily lives, they do not necessarily apply similar practices during travel and are likely to behave hedonically or irrationally [16]. Limited knowledge or familiarity with tourist destinations may result in inconsistencies in waste reduction practices [17]. Therefore, spreading awareness is not only ethically desirable but also essential for the sustainable protection of the environment at the tourist destination [18]. Existing studies indicate that waste reduction intentions emerge from the interaction of moral values, knowledge, and perceived responsibility [13,19]. Although previous studies have applied the NAM and theory of planned behavior to various settings [13,18,20] (

Table 1. Summary of waste reduction studies.

Author	Year	Location/Sample	Methods	Major Findings
Qian and Schneider [21]	2016	Minnesota, USA/Tourism businesses 2007 (n = 384), 2010 (n = 511), 2013 (n = 336)	Chi-square tests; Kruskal–Wallis tests; Mann–Whitney tests	Comprehensive waste minimization practices across sectors and over time.
Han et al. [18]	2018	Youth travelers	SEM	Green image, environmental awareness, and anticipated feelings around increasing waste reduction intentions.
Han et al. [20]	2018	Young vacationers	SEM	PN as a mediator in waste reduction and recycling intentions while traveling.
Kim et al. [22]	2020	Study 1: Australia/Community members (n = 21) Study 2: 414 consumers in Australia (n = 414) Study 3: Residents in Australia: a questionnaire (n = 197); fridge photo audit (n = 25)	Mixed-method	Technology-based strategies for household food waste reduction.
Wang et al. [13]	2021	546 Chinese tourists	SEM	Integration of TPB and NAM.
Fasihi et al. [23]	2021	Amlash city, Iran/358 household heads	GIS; One-sample t-test	No association between waste management quality and housing indicators.
Wu et al. [9]	2022	434 university students in China	PLS-SEM	Waste management behavior can be morally driven.
Ikiriko et al. [24]	2023	Port Harcourt Metropolis, Nigeria	Descriptive statistics	Highlights the importance of resident participation in waste management practices.
Sathatip [19]	2024	488 Food truck consumers, Thailand	SEM and NCA	NAM for intentions to reduce disposable packaging and waste.
Wilson et al. [25]	2025	N/A	Systematic review	Identifies six common behavioral interventions including social norm.
This study	2026	Vientiane, Laos/382 domestic tourists	OLS	Identifies AR as the strongest driver in an urban capital context, surpassing environmental knowledge.

SEM = Structural equation modeling; OLS = Ordinary least squares regression; PLS-SEM = Partial least squares structural equation modeling; NCA = Necessary condition analysis; TPB = Theory of planned behavior; NAM = Norm activation model; PN = Personal norm; AR = Ascription of responsibility.

), several research gaps remain. For instance, although knowledge-based interventions have been widely discussed [21], the current study demonstrates that, in the urban capital context of Laos, moral responsibility exerts a far more dominant influence on waste reduction than environmental knowledge. A comparative analysis with previous research highlights the innovation of our approach in bridging the knowledge–intention gap.

2.2. Actual Waste Management Behavior

Actual behavior refers to observable actions performed by individuals, providing a concrete reference point beyond stated intentions [26]. Although many behavioral models treat intention as the primary antecedent of action, recent research highlights the role of previous pro-environmental practices in shaping future intentions through the mechanisms of behavioral consistency and self-identity [27]. In a tourism context, this relationship is often explained by the spillover effect, where sustainable habits developed in the domestic sphere, such as recycling or waste sorting, transfer to the tourism environment [28]. This transfer may occur because individuals who regularly engage in waste management at home come to perceive themselves as environmentally responsible actors. When these individuals travel, they may seek to maintain a coherent self-identity and reduce cognitive dissonance, promoting the application of familiar waste reduction strategies even in unfamiliar destinations. Furthermore, while tourism environments can sometimes disrupt routines, established behavioral scripts act as a psychological default, lowering the cognitive effort required to form pro-environmental intentions at new destinations. Therefore, tourists with a strong habit of daily waste reduction are more likely to project these efforts into their future travel plans. Based on this rationale, the following hypothesis was proposed:

H1: 

Actual waste management behavior positively influences waste reduction intention at tourist destinations.

2.3. Environmental Knowledge

Environmental knowledge refers to an individual’s understanding of ecological processes, human impacts, and potential mitigation measures [29]. To analyze its impact on tourism, distinguishing between general environmental literacy and context-specific knowledge, such as tactical information regarding local waste systems, is essential [30]. Informed tourists are generally more likely to adopt responsible practices [8,9,10]. However, a knowledge–intention gap often persists when broad environmental awareness fails to translate into specific and functional actions in unfamiliar urban settings [31,32]. This distinction is particularly relevant in high-density destinations, where the perceived complexity of waste facilities may hinder the practical application of general knowledge. Thus, we examined whether such cognitive foundations effectively trigger reduction intentions in an urban tourism context, and proposed the following hypothesis:

H2: 

Environmental knowledge positively influences waste reduction intention at tourist destinations.

2.4. Norm Activation Model (NAM)

The NAM developed by Schwartz [33] offers a widely adopted framework for explaining pro-environmental behavior through moral obligation. The model centers on three psychological components: AC, AR, and PN. Although the original formulation describes a sequential process, some studies have moved beyond the traditional approach [12,13]. Therefore, this study conceptualizes the different model constructs within a parallel and integrative framework to better reflect the immediate decision-making processes of urban tourists.

Within this framework, AC acts as the cognitive trigger, where tourists recognize the environmental degradation potential at destinations. AR and PN function as the evaluative and motivational pillars, respectively. Instead of a linear progression, this study argues that, in high-pressure or highly visible environmental settings, AC and AR may activate PN concurrently or even exert independent direct influences on intention. By analyzing these components simultaneously, this study aims to disentangle the relative explanatory power of each moral dimension and identify whether tourist intent is driven more by a broad recognition of harm (AC), sense of personal accountability (AR), or internalized moral code (PN). This non-sequential approach provides a more nuanced understanding of how moral drivers interact in real-world tourism contexts.

2.4.1. Awareness of Consequences (AC)

Those who understand the ecological damage associated with improper waste disposal are generally more inclined to support sustainable alternatives [34,35]. In tourism settings, AC represents the cognitive dimension of recognizing objective environmental threats. This awareness heightens the perceived seriousness of problems and provides a factual basis for individual action [36,37]. In the NAM framework, this realization represents the initial step toward establishing the need for moral engagement. As tourists become more conscious of the damage linked to waste, their willingness to minimize such impacts is expected to increase. The following hypothesis was proposed:

H3: 

Awareness of consequences positively influences waste reduction intention at tourist destinations.

2.4.2. Ascription of Responsibility (AR)

This perception marks a shift from recognizing environmental issues to acknowledging one’s personal role in addressing them. Although AC is environmental, AR is relational, reflecting the extent to which individuals feel personally accountable for their direct and indirect impacts [38,39]. Empirical studies confirm that this acceptance of accountability strongly influences intentions [40,41]. By identifying themselves as active contributors to environmental problems, tourists may develop a specific motivation to reduce waste that goes beyond more factual knowledge. As such, the following hypothesis was proposed:

H4: 

Ascription of responsibility positively influences waste reduction intention at tourist destinations.

2.4.3. Personal Norm (PN)

Unlike the analytical nature of AC and AR, PN arises from self-imposed moral obligations and acts as an internal driver of pro-environmental intention, representing the internalized moral standard that fosters feelings of personal obligation [42]. These obligations shape responsible tourism behavior regardless of external pressure [43,44]. PN provides a distinct intrinsic motivation to maintain consistency with one’s own values, moving beyond cognitive or relational assessments. The following hypothesis was proposed:

H5: 

Personal norm positively influences waste reduction intention at tourist destinations.

2.5. Relationship Between Respondent Characteristics and Waste Management

Beyond the psychological drivers emphasized in the NAM, socio-demographic characteristics can also shape pro-environmental behavior. Waste-related practices are influenced by age, education, income, and gender, which reflect individual experiences and social contexts [23]. Higher education often corresponds to stronger environmental awareness.

Education and income frequently support environmentally responsible behaviors, including recycling and waste sorting [45]. Age and gender can also influence environmental attitudes, although their effects vary across cultural contexts [24]. Although such characteristics are often examined in household settings, they may also shape decision-making in tourism environments. Therefore, this study includes respondent characteristics as control variables to enhance the generalizability of the findings.

3. Methods

3.1. Measurement Items and Survey Design

This study used a structured quantitative questionnaire based on previously validated scales to ensure measurement reliability. Based on the study objectives, items measuring actual waste management behavior were adapted from Wu et al. [46], environmental knowledge from Kim et al. [47], and NAM constructs—including waste reduction intention—from Wang et al. [13]. The questionnaire comprised three sections: an introductory statement outlining the study purpose and assuring anonymity, core section measuring psychological variables, and final segment collecting demographic information. This structure was intended to maintain respondent attention and reduce survey fatigue.

A pilot survey was conducted with 20 participants to assess the clarity and interpretability of the questionnaire before the main survey. Since the survey was translated from English to Lao, special attention was given to whether participants clearly understood each question. They were asked to identify any confusing or unclear wording. Based on their responses and feedback, several questions were revised to improve clarity and avoid misinterpretation. After these adjustments, the final version of the questionnaire was confirmed to be suitable for data collection.

All constructs were measured using the five-point Likert scale (e.g., 1 = strongly disagree to 5 = strongly agree). Demographic and socio-economic information was collected as categorical variables. All analyses were performed using SPSS 30.0 (IBM SPSS, Armonk, NY, USA).

3.2. Sample and Data Collection

Data were collected in Hay Soke Village, a well-known tourism district in Vientiane. Covering ~70,049 m², the area contains numerous hotels, temples, and restaurants and hosts major events such as the Lao New Year festival [48]. The site attracts a high density of visitors but faces recurring waste overflow during peak periods because of limited waste infrastructure and staffing. Tourist arrivals in Laos exceeded 1.1 million in the first half of 2024, with Hay Soke Village receiving around 1500 visitors per month.

On-site data collection was undertaken in January 2025. Convenience sampling was conducted at the main entrance of the village. Participants were domestic tourists aged 18 years or older who voluntarily agreed to participate. Of the 400 questionnaires collected, incomplete responses were removed, leaving 382 valid observations for analysis.

3.3. Data Analysis

Data analyses were performed as follows: First, descriptive statistics were used to summarize respondent demographic and socio-economic characteristics. Second, measurement reliability and validity were assessed using Cronbach’s alpha and exploratory factor analysis (EFA). Items with weak loadings or high cross-loadings were removed to strengthen the measurement structure. EFA was employed to verify the dimensionality and internal consistency of the measurement items. Third, independent sample t-tests were used to examine differences in waste reduction intention between groups, such as gender, marital status, and whether respondents traveled with children. Fourth, significant associations between interval variables were confirmed using Pearson correlation analysis.

Finally, ordinary least squares (OLS) regression was applied to test the proposed hypotheses; the dependent variable was treated as interval data because of the use of the five-point Likert scale. We simultaneously examined the influence of independent variables while controlling for respondent characteristics. Qualitative variables were transformed to dummy variables. For instance, female tourists were coded as 0 and male tourists as 1.

4. Results

4.1. Characteristics of Respondents

Table 2. Characteristics of respondents.

Characteristic	Frequency	Percentage
Sex
Male	126	33.0
Female	256	67.0
Age
18–19 years	97	25.4
20–29 years	126	33.0
30–39 years	98	25.7
40–49 years	50	13.1
50–59 years	10	2.6
Older than 60 Years old	1	0.3
Marital Status
Single	250	65.4
Married	132	34.6
Traveling with children under 12 years old (n = 135) 1
Yes	63	46.7
No	72	53.3
Education Level
High school	113	29.6
Bachelor’s degree	149	39.0
Master’s degree	79	20.7
Doctoral degree	24	6.3
Other	17	4.5
Income Level (Kip/Year)
Under 24,000,000 Kip	109	28.5
24,000,000 Kip–30,000,000 Kip	29	7.6
30,000,001 Kip–36,000,000 Kip	41	10.7
36,000,001 Kip–42,000,000 Kip	52	13.6
42,000,001 Kip–48,000,000 Kip	34	8.9
Over 48,000,000 Kip	117	30.6
Frequency of Visit
1 time	39	10.2
2–3 times	192	50.3
4–5 times	64	16.8
More than 5 times	87	22.8
Length of stay
1 day	56	14.7
2–3 days	194	50.8
4–5 days	73	19.1
Over 5 days	59	15.4

Note: Kip is the Lao currency. ¹ Only married respondents, who travelled with their children under 12 years old, answered this question. n = 382.

presents the demographic and socio-economic characteristics of the 382 respondents. The cohort comprised mainly females (67.0% females, n = 256; 33.0% males, n = 126). Most participants were relatively young: 33.0% (n = 126) were aged 20–29 years, followed by 25.7% (n = 98) aged 30–39 and 25.4% (n = 97) aged 18–19. Regarding marital status, 65.4% (n = 250) were single and 34.6% (n = 132) were married. A smaller portion of respondents (16.5%, n = 63) reported traveling with children under 12 years old.

Bachelor’s degree holders made up the largest proportion among educated individuals (39.0%, n = 149), followed by high school graduates (29.6%, n = 113) and master’s degree holders (20.7%, n = 79). Income levels showed a split distribution: 30.6% (n = 117) reported annual earnings > 48,000,000 Kip, whereas 28.5% (n = 109) earned <24,000,000 Kip. Travel patterns indicated that 50.3% of the respondents (n = 192) had visited Hay Soke Village two to three times, and 50.8% (n = 194) stayed for 2–3 d.

4.2. Reliability and Validity of Measures

All Cronbach’s α-values exceeded the recommended threshold of 0.70 [49], indicating satisfactory internal consistency. EFA and reliability tests were conducted to evaluate the measurement scales. The Kaiser–Meyer–Olkin value (0.870) indicated strong sampling adequacy [50]. Bartlett’s test of sphericity (χ² (276) = 4310.066, p < 0.001) confirmed that the dataset was appropriate for factor analysis.

One item related to actual waste management behavior (“I conserved resources and energy”) was removed because of low factor loading. After this adjustment, six factors with eigenvalues > 1 were extracted, explaining 66.03% of the total variance. Factor loadings for the retained items ranged from 0.51 to 0.79, supporting the proposed six-factor structure (

Table 3. Exploratory factor analysis and reliability test results ¹.

Construct	Items	M (SD)	Factor Loading	Eigen Value	Variance	Cronbach’s α
Actual waste management behavior	I volunteered my time to projects that helped the environment.	3.87 (0.98)	0.789	30.790	16.900	0.879
	I looked for environmental information on TV, in documents, or on the Internet.	3.96 (0.82)	0.779
	I reminded others to avoid doing environmentally harmful behaviors.	4.07 (0.81)	0.701
	I donated money to support environmental conservation.	3.87 (0.78)	0.674
	I used ‘green’ (non-plastic) shopping bags.	4.23 (0.86)	0.656
	I sorted garbage.	4.33 (0.74)	0.641
	I recycled.	4.20 (0.79)	0.637
Environmental knowledge	I know that I buy products that are environmentally safe.	4.24 (0.74)	0.767	12.068	11.459	0.831
	I understand the environmental phrases and symbols noted on product packages.	4.20 (0.76)	0.682
	I am very knowledgeable about environmental issues, such as pollution, global warming, etc.	4.20 (0.74)	0.669
	I know more about waste reduction than the average person.	4.18 (0.73)	0.627
	I know more about sorting waste than the average person.	4.18 (0.73)	0.621
Awareness of consequences	Waste generated at tourist destinations will threaten the sustainable development of tourist destinations.	4.36 (0.78)	0.870	7.440	10.145	0.825
	Waste generated at tourist destinations will damage the natural environment of tourist destinations.	4.29 (0.74)	0.811
	Waste generated at tourist destinations will affect the local tourism economy.	4.31 (0.71)	0.780
Personal norm	I feel obliged to reduce waste generation while travelling to a tourist destination.	4.14 (0.65)	0.771	5.633	9.904	0.796
	Reducing waste generation while travelling to a tourist destination is driven by my moral rules.	4.02 (0.77)	0.737
	I think I have a moral obligation to reduce waste generation while travelling to a tourist destination.	4.07 (0.72)	0.610
Ascription of responsibility	I deem that every tourist should be responsible for the environmental problems caused by the large amount of waste generated at tourist destinations.	4.35 (0.64)	0.829	5.571	9.217	0.759
	Reducing waste generation while travelling to a tourist destination is the responsibility for every tourist.	4.40 (0.64)	0.731
	I feel jointly responsible for reducing waste generation while travelling to a tourist destination.	4.31 (0.64)	0.680
Waste reduction intention at tourist destinations	I am willing to reduce waste generation while travelling to a tourist destination in the near future.	4.49 (0.60)	0.784	4.530	8.407	0.703
	I will try my best to reduce waste generation while travelling to a tourist destination in the near future.	4.50 (0.62)	0.774
	I am planning to reduce waste generation while travelling to a tourist destination in the near future.	4.37 (0.61)	0.681
	KMO = 0.870; χ2 (276) = 4310.066; p < 0.001; Total variance = 66.032%

¹ All items were measured using the five-point Likert scale (1 = Strongly disagree to 5 = Strongly agree). KMO = Kaiser–Meyer–Olkin value.

). Overall, the findings confirmed the reliability and construct validity of the measurement scales for further analysis.

To assess the potential for common method bias, Harman’s single-factor test was performed using all measured items. The largest single factor accounted for only 16.90% of the total variance, well below the recommended 50% threshold. This indicates negligible common method bias.

4.3. Differences in Waste Reduction Intention Between Groups

Independent sample t-tests were conducted to examine the differences in waste reduction intention between groups. We observed no differences between males and females (t = −1.137, p = 0.646), single and married respondents (t = 1.284, p = 0.844), and tourists traveling with and without children aged under 12 years (t = −1.022, p = 0.537).

4.4. Results of Correlation Analysis

Pearson correlation analysis revealed significant associations between variables measured by interval or Likert scale (

Table 4. Correlation analysis results.

	M (SD)	AB	EK	AC	AR	PN	IT	Age	EL	IL	FoV	LoS
AB	4.10 (0.59)
EK	4.20 (0.57)	0.669 **
AC	4.32 (0.63)	0.319 **	0.272 **
AR	4.35 (0.52)	0.179 **	0.252 **	0.317 **
PN	4.08 (0.60)	0.353 **	0.334 **	0.348 **	0.499 **
IT	4.45 (0.48)	0.331 **	0.317 **	0.208 **	0.353 **	0.365 **
Age	2.35 (1.09)	−0.043	0.037	−0.078	−0.092	−0.075	−0.049
EL	3.17 (1.06)	0.070	0.132 **	−0.040	−0.074	−0.077	−0.062	0.573 **
IL	3.59 (2.03)	0.125 *	0.115 *	0.079	−0.041	−0.031	0.117 *	0.434 **	0.406 **
FoV	2.52 (0.95)	0.113 *	0.203 **	0.156 **	0.151 **	0.125 *	0.147 **	0.092	0.096	0.284 **
LoS	2.35 (0.91)	0.141 **	0.159 **	0.186 **	0.104 *	0.207 **	0.076	0.080	0.138 **	0.261 **	0.520 **

Note: * p < 0.05, ** p < 0.01. AB = Actual waste management behavior; EK = Environmental knowledge; AC = Awareness of consequences; AR = Ascription of responsibility; PN = Personal norm; IT = Waste reduction intention at tourist destination; EL = Education level; IL = Income level; FoV = Frequency of visit; LoS = Length of stay.

). In terms of waste reduction intentions, PN was the most strongly correlated (r = 0.365, p < 0.01), followed by AR (r = 0.353, p < 0.01), actual waste management behavior (r = 0.331, p < 0.01), environmental knowledge (r = 0.317, p < 0.01), and AC (r = 0.208, p < 0.01). Among control variables, only frequency of visit (r = 0.147, p < 0.01) and income level (r = 0.117, p < 0.05) were correlated with waste reduction intention. Using variables significantly correlated with waste reduction intention, a regression analysis was conducted to examine the relationship between independent variables (i.e., AC, AR, PN, actual waste management behavior, and environmental knowledge), the dependent variable (i.e., waste reduction intention), and control variables (i.e., income level and frequency of visit).

4.5. Results of Regression Analysis

Multiple regression using OLS was performed to assess the determinants of waste reduction intention while controlling for income level and frequency of visit. The model was statistically significant (F = 16.338, p < 0.001) and explained 23.4% of the variance (R² = 0.234). The Durbin–Watson statistic (1.885) indicated independent residuals, and the variance inflation factor values (1.119–1.956) confirmed the absence of multicollinearity (

Table 5. OLS regression results for waste reduction intention with control variables.

Variables	B	SE	β	t	p	VIF
Actual waste management behavior	0.136	0.052	0.167	2.635	0.009	1.956
Environmental knowledge	0.065	0.053	0.077	1.223	0.222	1.924
Awareness of consequences	−0.006	0.038	−0.008	−0.162	0.872	1.252
Ascription of responsibility	0.201	0.049	0.219	4.081	<0.001	1.411
Personal norm	0.139	0.045	0.173	3.098	0.002	1.524
Income level	0.022	0.011	0.093	1.944	0.053	1.119
Frequency of visit	0.016	0.025	0.032	0.664	0.507	1.154

Bold font indicates significant variables. Dependent variable = Waste reduction intention at tourist destinations. SE = Standard error; VIF = Variance inflation factor.

).

Among independent variables, actual waste management behavior, AR, and PN were significantly and positively related to waste reduction intention (supporting H1, H4, and H5, respectively). AR showed the strongest relationship (β = 0.219, t = 4.081, p < 0.001), indicating that tourists who feel personally accountable are more likely to reduce waste while travelling. PN (β = 0.173, t = 3.098, p < 0.01) and actual waste management behavior (β = 0.167, t = 2.635, p < 0.01) also showed strong correlations. The results revealed that not all variables of the NAM necessarily contribute to stronger behavioral intention.

Meanwhile, H2 and H3 were not supported, implying that environmental knowledge and AC do not significantly contribute to waste reduction intention during travel. The control variables (i.e., income level and frequency of visit) were not significantly correlated. Consequently, actual waste management behavior and internalized moral obligation—rather than cognitive awareness alone—may be the main drivers of waste reduction intention.

Table 6. Summary results of hypothesis testing.

Hypothesis	Result
H1: Actual waste management behavior positively influences waste reduction intention at tourist destinations.	Supported
H2: Environmental knowledge positively influences waste reduction intention at tourist destinations.	Not Supported
H3: Awareness of consequences positively influences waste reduction intention at tourist destinations.	Not Supported
H4: Ascription of responsibility positively influences waste reduction intention at tourist destinations.	Supported
H5: Personal norm positively influences waste reduction intention at tourist destinations.	Supported

summarizes the hypothesis tests, highlighting the role of moral factors in determining tourist waste reduction intentions.

5. Discussion

5.1. Theoretical Implications

Although many NAM studies emphasize the sequential manner of factors determining tourist intention, that is, the contributions of AC and AR to PN, this study assessed the relative influence of these variables within a single model by examining their simultaneous effects. We showed that AR may have the strongest positive impact on waste reduction intention. This suggests that recognizing personal accountability is a more immediate motivator of waste reduction intention than general environmental understanding.

This study confirmed that AR and PN may function as the principal drivers of behavioral intention for waste reduction during travel. Rather than a lack of knowledge being the main constraint, the evidence suggests that sustainable behavior depends on activating a sense of personal responsibility and motivating pro-environmental habits. In this context, waste reduction appears less dependent on factual awareness and more on internal moral motivation. This study contributes to ongoing discussions about whether cognitive knowledge or moral commitment plays a stronger role in pro-environmental behavior. By demonstrating the importance of AR and PN, the study provides further evidence to validate the empirical value of the NAM, consistent with Wang et al. [13].

PN acts as a key self-regulating mechanism. Tourism environments are temporary and often lack consistent social monitoring. Under such conditions, internal moral standards become the main guide for behavior [51]. Our findings suggest that tourist willingness to minimize waste likely reflects personal ethical commitment rather than external pressure, reinforcing earlier observations in sustainable tourism research [18,20].

The significance of actual waste management behavior suggests that sustainable practices at home can be transferred into waste reduction behavior during travel. For example, individuals who regularly engage in responsible disposal may gradually develop a self-image as environmentally responsible travelers, which can strengthen future intentions [52]. This indicates that behavioral change can evolve through repeated practice, linking identity and action in a reinforcing cycle.

The non-significant relationship between AC and waste reduction intention may reveal a clear knowledge–intention gap among domestic tourists in Vientiane. This suggests that a cognitive understanding of the environmental impacts of waste merely reflects a preliminary learning phase that may not directly trigger action. For such awareness to translate into waste reduction intention, it can be internalized as AR or PN. Ultimately, in high-density urban destinations, objective awareness of waste issues is a necessary but insufficient condition that may lack the motivational force to drive behavioral change without the activation of internal moral drivers.

5.2. Practical Implications

Many behavioral frameworks highlight the importance of increasing or strengthening awareness. However, this study indicated that intention can be strengthened primarily when individuals accept responsibility for their environmental impact. Awareness alone may not necessarily translate into behavioral intention; the effect could depend on whether individuals internalize responsibility for environmental outcomes. Consequently, rather than relying exclusively on informational messaging, destination-level interventions should emphasize personal accountability. Our findings provide actionable insights for destination managers in urban settings such as Vientiane. For example, at Hay Soke Village, where waste management challenges are visible, management could transition from passive information delivery to active message framing that emphasizes personal accountability [33,41]. Specifically, instead of general environmental warnings, moral-triggering prompts may be utilized to transform tourists from passive observers into responsible actors. Furthermore, to operationalize these moral norms, on-site prompts, such as social norm cues placed near high pedestrian traffic areas or commitment prompts at entrance points, could be implemented. Such strategies may bridge the gap between problem recognition and actual waste reduction behavior by constantly reinforcing a tourist’s sense of personal responsibility.

Another notable finding is the lack of significant relationships between environmental knowledge and AC regarding waste reduction intention. This outcome may reflect the persistent knowledge–intention gap, where mere awareness of environmental problems does not necessarily produce the intention for behavioral change [36]. In the case of Vientiane, recognizing environmental problems alone may be insufficient to motivate waste reduction without a corresponding sense of responsibility. As such, this study suggests that effective waste reduction behavior may require a dual approach that triggers immediate moral responsibility while reinforcing long-term pro-environmental habits.

6. Conclusions

6.1. Research Summary

By employing NAM variables as tools for analysis rather than theoretical validation, this study revealed personal accountability to be the most functional driver in addressing urban waste challenges in Vientiane, Laos. Specifically, internal moral drivers along with pro-environmental habits exert stronger influence than knowledge or socio-economic and travel characteristics. The findings demonstrate that tourists may be sensitive to internalizing a sense of personal responsibility regarding waste generation at travel destinations, and confirm that waste management habits developed in tourist households could effectively carry over into waste reduction behavior during travel.

6.2. Limitations and Future Prospects

Despite its contributions, this study has some limitations. First, future studies may consider diverse spatial settings covering rural to urban destinations and also account for destination life cycle to verify the present findings. For example, the impact of frequency of visit on the intentions of travelers was not consistent. In the correlation analysis (Table 4), frequency of visit was significantly associated with intention, but this relationship was not significant when applied as a control variable in the OLS regression (Table 5). Although frequency of visit reinforces pro-environmental behavior, this relationship may be contingent upon the spatial characteristics of the destination (e.g., nature-based vs. urban-based). Huang et al. [53] demonstrated that frequent visits to nature-based sites significantly enhance pro-environmental behavior, suggesting the importance of location in travel planning. However, the characteristics of Vientiane, the urban capital of Laos, may affect the relationship between the frequency of visit and waste reduction intentions. In the future, comparative studies covering diverse spatial characteristics and contexts may be useful to elucidate the underlying mechanisms.

The study relied on self-reported questionnaires, which may introduce social desirability bias. Participants may exaggerate their waste reduction intentions to align with perceived social expectations and environmental norms. To address the potential gap between reported intentions and actual (realized) behavior, future research could compare behaviors at home versus during travel. Based on the specific differences, it may be possible to identify the underlying mechanisms and implement more effective approaches for strengthening pro-environmental behavior.

A geographical approach may be considered. Tourist waste reduction behavior may depend on geographical structure, which may limit the locations of trash boxes and determine the designation of waste/trash discarding sites. Spatial patterns, identified using spatial theories and analytical techniques, may explain where and why more waste is generated in tourism destinations and inform the development of more efficient strategies for motivating waste reduction behavior and ultimately reducing waste generation by tourists.