Validation Sample Research Articles

A Study on the Leadership of Kindergarten Principals: Based on Hefei City, China

This study focuses on the current status of leadership among kindergarten principals in Hefei, China. It examines the overall situation of leadership among kindergarten principals in Hefei and explores whether there are differences in the leadership levels of principals under demographic factors, from four dimensions: educational leadership, values leadership, interpersonal leadership, and organizational leadership. The study surveyed kindergarten principals in Hefei, with a total of 190 questionnaires collected. After excluding 19 invalid questionnaires, 171 valid samples were obtained. Through discussion and analysis, it was found that the overall level of leadership among kindergarten principals in Hefei is relatively high. The leadership scores in the four dimensions are ranked in descending order as follows: educational leadership, organizational leadership, interpersonal leadership, and values leadership.

스키장 마케팅믹스 6P 요인이 참여만족 및 고객충성도에 미치는 영향

This study was conducted to determine how the 6P factors of ski resort marketing mix affect participation satisfaction and customer loyalty to provide methods to prevent the departure of existing customers, attract new customers, and strengthen competitiveness with other ski resorts. Therefore, three ski resorts located in Pyeongchang-gun (Yongpyeong, Phoenix Park, Alpensia), where the 2018 Winter Olympics were held, High1 Resort, which was included in the X3 Season Pass, an integrated season ticket in Gangwon-do, and Jisan Resort and Gonjiam Reasort located in Gyeonggi-do, close to the metropolitan area, were selected as a population, and adult men and women in their 20s or older were selected as samples. The survey method used the convenience sampling method among the non-probability sampling methods, and the survey was conducted online using a Google questionnaire. The survey period was conducted from October 7, 2023 to November 7, 2023, and 353 people were selected as valid samples and used for the analysis of the results, excluding data that were deemed to have been omitted for unfaithful answers and part of the survey. For data processing, frequency analysis, exploratory factor analysis, intra-question consistency, correlation analysis, and simple and multiple regression analysis were performed, and the SPSS (ver. 21.0) program was used. As a result of the study, first, it was found that among the 6P factors of ski resort marketing mix, people and products affect participation satisfaction in order. Second, it was found that the participation satisfaction in ski resorts had a statistically significant effect on both attitudinal loyalty and behavioral loyalty of customer loyalty. Third, among the six factors of ski resort marketing mix, people, products, and prices were found to have an effect on attitudinal loyalty, and people, products, and promotion were found to have an effect on behavioral loyalty.

부동산 거래 및 정보 플랫폼 활용에 관한 연구

The purpose of this study was to analyze how the benefits provided to users in the utilization of real estate transaction and information platforms affect user engagement and trust in the platform. The analysis methods used in this study included basic statistical analysis, factor analysis, and structural equation modeling, utilizing SPSS 27.0 and AMOS 24.0 programs as analytical tools. In April 2024, a survey was conducted among men and women in their 20s to 50s residing in various regions, and 602 final valid samples were selected and analyzed. The following research results have been derived: First, information acquisition benefits have a significant impact on trust. Second, psychological benefits have a significant impact on trust. Third, economic benefits have a significant impact on trust. Fourth, customization benefits have impact on trust. Finally, usage trust has a significant impact on immersion. Through the above research, implications were presented on which benefits to enhance in order for users to stay longer and develop trust in the real estate platform.

Determining Adequate Sample Size for Social Survey Research

Determination of a valid sample size is a fundamental step in research. This paper explains how existing formulas are tied in a single thread by applying the concept of standard error, margin of error, Z and t scores, confidence interval and sampling distribution. Bringing the concept of sample control ratio, we suggest a unified formula which is where I is the sample size, N is the population, t is the t-value at a desired level of probability with df = (N-1) and  is the sample control ratio to be estimated by for continuous variables and for categorical variables where  is the proportion of acceptable error and p is the proportion of presence of an attribute in the population. This formula does not need the finite population correction, and it has been derived from and consistent with existing formulas. A researcher does not need to calculate the error margin in absolute terms for this formula, and it is sufficient to provide only the proportion of error (e.g., 0.03 or 0.05). This paper should help social scientists, researchers, academicians and students determine the appropriate sample size for their research with greater confidence and clarity. J Bangladesh Agril Univ 22(2): 146-157, 2024

확장된 자기효능감 기반 가치수용모델을 적용한 셀프서비스기술 수용의도

This study aims to explore the structural relationships between older customers' technological self-efficacy, personal innovativeness, perceived values (social, utilitarian, hedonic), attitudes, and behavioral intentions regarding technology-based, contactless services in hotels and restaurants. The survey, based on previous research, targeted customers over 50 who have experience using Self-Service Technologies (SST) in the hotel and restaurant sector, with a final valid sample of 228 respondents included in the analysis. The conclusions from this study's hypothesis testing are as follows: First, senior customers' technological self-efficacy positively impacts utilitarian value but negatively impacts social value. However, it does not significantly affect hedonic value or behavioral intentions. Second, personal innovativeness positively impacts social, utilitarian, and hedonic values, with the most significant enhancement observed in hedonic value. It also significantly influences behavioral intentions. Third, while utilitarian and hedonic values positively affect attitudes, social value does not have a significant impact on attitudes. Fourth, the attitude of senior customers towards SST positively influences their behavioral intentions. These findings suggest that efforts to enhance the technological self-efficacy of the senior customer segment could strengthen functional interactions with technology, thereby enhancing the adoption intentions of SSTs in the hotel and restaurant industries.

Organizer Competency and B2B Exhibition Performance: The Mediating Role of Exhibitor Motivation

Purpose - This study aims to explore the significance of organizer competency in B2B exhibitions in South Korea. Drawing on previous literature in the exhibition context, this research empirically examines the impact of organizer competency on exhibition performance and investigates the mediating role of exhibiting firms’ motivation to participate. Motivation is deconstructed into the quality of attendees and market-oriented motivation for a detailed analysis. Design/Methodology - The empirical model of this study considers the relationship between organizer competency and exhibition performance in B2B exhibitions from a resource-based view. To accurately reflect the unique characteristics of B2B exhibitions, we surveyed firms that participated in the Korea International Boat Show. Consequently, the hypotheses of this study were tested through a structural equation model with 85 valid samples. Findings - The findings of this study are twofold: First, we confirm that the competency of exhibition organizers significantly and positively impacts exhibition performance. Secondly, we identify that both motivational factors—quality of attendees and market-oriented motivation— positively influence exhibition performance. Originality/value - Previous studies have overlooked organizer competency as a driver to enhance exhibition performance. However, this study demonstrates that organizer competency positively influences exhibition performance, mediated by the quality of attendees and market-oriented motivation. Furthermore, unlike most previous studies focused on regions such as China and Hong Kong, we analyze our research within the context of the Korean B2B industry.

Paradigm of symbiosis as a mechanism of artificial intelligence and customers’ patronage decision in the hospitality sector: the moderating role of customer engagement

ABSTRACT Study aims to explore the effect of artificial intelligence (AI) performance on customer values and patronage decisions; determine the relationship between AI service enhancement and various levels of perceived value; and adopt customer engagement as a moderator that affects customer value and patronage decision. Study adopts the Means-End Chain theory, synthesised by the Multi-Attribute Value theory to integrate AI performance and perceived values. Adopted quantitative approach and structured equation modelling and study are based on a total of 418 valid samples. Shedding light on how AI resources can be effectively managed within the service paradigm during customer interactions and AI services, this study is expected to offer theoretical and practical insights. Results contribute to the theoretical framework surrounding the relationship between AI and customer patronage decision making, thereby enriching the AI academic field. The study advocates for a symbiotic understanding of AI and customer engagement for improved service performance.

Random forest and spatial cross-validation performance in predicting species abundance distributions

Random forests (RF) have been widely used to predict spatial variables. Several studies have shown that spatial cross-validation (CV) methods consistently cause RF to yield larger prediction errors compared to standard CV methods. This study examined the impact of species characteristics and data features on the performance of the standard RF and spatial CV approaches for predicting species abundance distribution. It compared the standard 5-fold CV, design-based validation, and three different spatial CV methods, such as spatial buffering, environmental blocking, and spatial blocking. Validation samples were randomly selected for design-based validation without replacement. We evaluated their predictive performance (accuracy and discrimination metrics) using artificial species abundance data generated by a linear function of a constant term (β0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta _0$$\\end{document}) and a random error term following a zero-mean Gaussian process with a covariance matrix determined by an exponential correlation function. The model was tuned over multiple simulations to consider different mean levels of species abundance, spatial autocorrelation variation, and species detection probability. Here we found that the standard RF had poor predictive performance when spatial autocorrelation was high and the species probability of detection was low. Design-based validation and standard K-fold CV were found to be the most effective strategies for evaluating RF performance compared to spatial CV methods, even in the presence of high spatial autocorrelation and imperfect detection for random samples. For weakly or moderately clustered samples, they yielded good modelling efficiency but overestimated RF’s predictive power, while they overestimated modelling efficiency, predictive power, and accuracy for strongly clustered samples with high spatial autocorrelation. Globally, the checkerboard pattern in the allocation of blocks to folds in blocked spatial CV was found to be the most effective CV approach for clustered samples, whatever the degree of clustering, spatial autocorrelation, or species abundance class. The checkerboard pattern in spatial CV was found to be the best method for random or systematic samples with spatial autocorrelation, but less effective than non-spatial CV approaches. Failing to take data features into account when validating models can lead to unrealistic predictions of species abundance and related parameters and, therefore, incorrect interpretations of patterns and conclusions. Further research should explore the benefits of using blocked spatial K-fold CV with checkerboard assignment of blocks to folds for clustered samples with high spatial autocorrelation.

Quantum circuits for discrete graphical models

Graphical models are useful tools for describing structured high-dimensional probability distributions. The development of efficient algorithms for generating samples thereof remains an active research topic. In this work, we provide a quantum algorithm that enables the generation of unbiased and independent samples from general discrete graphical models. To this end, we identify a coherent embedding of the graphical model based on a repeat-until-success sampling scheme which clearly identifies whether a drawn sample represents the underlying distribution. Furthermore, we show that the success probability for finding a valid sample can be lower bounded with a quantity that depends on the number of maximal cliques and the model parameter norm. Moreover, we rigorously proof that the quantum embedding conserves the key property of graphical models, i.e., factorization over the cliques of the underlying conditional independence structure. The quantum sampling algorithm also allows for maximum likelihood learning as well as maximum a posteriori state approximation for the graphical model. Finally, the proposed quantum method shows potential to realize interesting problems on near-term quantum processors. In fact, illustrative experiments demonstrate that our method can carry out sampling and parameter learning not only with idealized simulations of quantum computers but also on actual quantum hardware solely supported by simple readout error mitigation.

How Does Corporate Image Attract Job Seekers – An Empirical Study of Moderated Mediation of Employer Image in Macao Food & Beverage Industry

While organization image and employer image are two constructs highlighted in the employer attractiveness studies, what relationship between two images is yet unknown. This paper aims to investigate the relationship between two constructs, and further the employer image research from Younis and Hammad in 2019. The empirical study utilized self-administered questionnaires to collect primary data of employees in Macao Food and Beverage industry. From November 2022 to April 2023, 303 valid samples were recruited and organized. Using SPSS and Amos statistical software, the study found that both corporate image and employer image are predictors of organization attraction, and employer image plays as a partial mediator of employer attraction model. Simultaneously, organization attraction predicted job seekers' application intentions and person-organization fit has been significantly affecting the process of mediating and moderating process of hypothetical conceptual model. Findings suggested that an attractive employer brand could help improve the efficiency and effectiveness of recruitment. This study provided marginal contribution to the employer brand research and offers practical implications for the Macao Food and Beverage Industry. Theoretically, the study found effects of image transmitting in predicting organization attraction between corporate image and employer image and person-organization fit role during the transmission. In the practice, managers should consider different images when building organization attractiveness and highlight communication between organization image messages (corporate image and employer image) and recipients (job seekers), and to maximize effects of recruitment. More studies should be conducted to understand how different images are transferred.

Detection of cocaine 24 h after administration before nasotracheal intubation.

Cocaine may be applied to decongest the nasal mucosa before nasotracheal intubation, but patients risk a criminal offence if cocaine is detected when patients drive a car shortly after surgery. We aimed to evaluate whether benzoylecgonine levels in saliva exceeded the cut-off point 24 h after administration in patients undergoing nasotracheal intubation and whether cocaine would be detectable above the Danish legal fixed limit in blood samples 1 and 24 h after surgery. We conducted a prospective study following approval from the local research ethics committee and the national medicine agency. Written informed consent was obtained from all patients. We included patients scheduled for surgery under general anaesthesia with nasotracheal intubation. They received 80 mg cocaine as a nasal spray 5 min before induction and nasotracheal intubation. The primary outcome was a dichotomous assessment of benzoylecgonine levels in saliva samples measured 24 h after administration of nasal cocaine with a cut-off limit of 200 ng/mL. Secondary outcomes were dichotomous assessments of cocaine in whole blood samples measured 1 and 24 h after administration of nasal cocaine with a cut-off limit of 0.01 mg/kg. Overall, 70 patients had valid saliva samples and 75 had valid blood samples 24 h after cocaine administration. Benzoylecgonine in saliva was traceable above the cut-off in 9/70 patients (13%; CI95%: 6% to 23%), and cocaine in blood was detected above the cut-off in 2/75 patients (3%; CI95%: 0.3% to 9%). We found benzoylecgonine traceable in saliva in 13% of patients and cocaine traceable in blood in 3% of patients 24 h after administration of 80 mg nasal cocaine. Patients should be informed when receiving cocaine and advised not to drive for at least 24 h.

Intermittent Fasting: Socio-Economic Profile of Spanish Citizens Who Practice It and the Influence of This Dietary Pattern on the Health and Lifestyle Habits of the Population.

1. To study the prevalence of IF among the Spanish population. 2. To explore how demographic factors influence the choice to adopt this dietary approach. A descriptive cross-sectional study was conducted on the Spanish population using the NutSo-HH questionnaire, which was constructed, validated, and disseminated by the research team through a non-probabilistic snowball sampling approach, collecting socio-demographic data and nutritional, social and lifestyle habits of the population. A valid sample of 22,181 people participated, of whom 4.59% (n = 1018) said they practiced IF. The data show that more middle-aged men than women practice IF. In addition, individuals who follow IF methods are less likely to have no control over their food intake, are less scared to gain weight and have a higher body image, but no differences were found related to unhealthy food and nights out. There were also no significant differences in terms of the level of education, income, size of municipality, or region of residence. In conclusion, a person who practices IF seems to have adopted a healthier lifestyle and social habits.

First‐year students' psychological resilience and college adjustment: A person‐oriented approach

AbstractPrevious research has concentrated on psychological resilience as a holistic structure and has found that resilience positively affects college adjustment. However, it is suggested by existing literature that college students' resilience is a multidimensional construct. Furthermore, there is limited understanding regarding the categorizations of resilience among first‐year college students and its influence on their college adjustment. This study aimed to identify the profiles of first‐year college students' resilience, including individual powers and supportive powers, and explore the effects of varying resilience profiles on first‐year students' college adjustment. A valid sample of 771 first‐year college students from 28 Chinese colleges participated in this survey. The online surveys were conducted through Wenjuanxing platform. Data were analyzed using latent profile analysis to identify first‐year college students' different resilience profile and examine the relationships with college adjustment. Four groups featuring unique resilient characteristics were discovered: well‐resilient students, students with low individual power but high supportive power, students with high individual power but low supportive power, and mal‐resilient students with low individual power and low supportive power. Well‐resilient first‐year students reported the best condition of college adjustment compared to the other groups, which supports the conservation of resources (COR) theory. These results provide insight into first‐year college students' particular and heterogeneous circumstances at the beginning of the college experience. They also refined the COR theory by identifying individual‐specific relationships between psychological resilience and college adjustment.

Relationship between Patient Health Questionnaire (PHQ-9) and Montgomery-Asberg Depression Rating Scale (MADRS) total scores in older adults with major depressive disorder: An analysis of the OPTIMUM clinical trial

BackgroundThe Patient Health Questionnaire (PHQ-9) and Montgomery-Asberg Depression Rating Scale (MADRS) are commonly used scales to measure depression severity in older adults. MethodsWe utilized data from the Optimizing Outcomes of Treatment-Resistant Depression in Older Adults (OPTIMUM) clinical trial to produce conversion tables relating PHQ-9 and MADRS total scores. We split the sample into training (N = 555) and validation samples (N = 187). Equipercentile linking was performed on the training sample to produce conversion tables for PHQ-9 and MADRS. We compared the original and estimated scores in the validation sample with Bland-Altman analysis. We compared the depression severity level using the original and estimated scores with Chi-square tests. ResultsThe Bland-Altman analysis confirmed that differences between the original and estimated scores for at least 95 % of the sample fit within 1.96 standard deviations of the mean difference. Chi-square tests showed a significant difference in the proportion of participants at each depression severity category determined using the original and estimated scores. LimitationsThe conversion tables should be used with caution when comparing depression severity at the individual level. ConclusionsOur conversion tables relating PHQ-9 and MADRS scores can be used to compare treatment outcomes using aggregate data in studies that only used one of these scales.

Driving mechanism for farmers to adopt agroecology for biodiversity conservation: Inspiration from tea management in a China National Park

Abstract Conflicts arising from human activities and biodiversity value affect the conservation efficacy of protected areas. Resolving these conflicts requires conservation‐compatible livelihoods, such as through agroecology. Here, we built a comprehensive social–psychological framework to explore and understand farmers' intentions to adopt agroecological approaches in tea management in Wuyishan National Park, China. We extended the theory of planned behaviour (TPB) by integrating household livelihood assets (LAs) as a material precondition for the social–psychological decision‐making process. We proposed geographical location (GL) and livelihood strategy (LS) as moderating factors for this agroecology intention. We collected 369 valid household samples through structured interviews. We then used partial least square‐structural equation (PLS‐SEM) modelling to explore the determinants that affect tea farmers' agroecological intentions. Livelihood assets were a material foundation influencing the intention to adopt agroecology and were also mediated by three psychological constructs to take effect. Perceived behavioural control explained the largest proportion of the variance for intention and exerted the most significant mediation effects. Subjective norm was another vital independent predictor and exerted a positive influence on both perceived behavioural control and attitude. The direct and mediating impacts of attitude on the intention were weaker but showed that farmers' ecological rationality outweighed value rationality. Livelihood strategies measured by operational scale and livelihood diversity were able to moderate farmers' psychology. Subjective norm had positively significant influence on perceived behavioural control and attitude, indicating that social support to farmers enhanced their feeling of control over adopting agroecology and that important referent groups as sources of information helped farmers' attitude formation. Perceived behavioural control positively and significantly influences farmers' attitudes as well. Synthesis and applications. Our findings provide evidence of the necessity to optimise rural farmers' livelihood assets to enhance their confidence and control over agroecology. Resolving the conservation‐development dilemma in protected areas through agroecology should aim at comprehensive support that respects bioculture and improves farmers' ability. We suggest knowledge co‐production of traditional wisdom and modern technologies, reducing management costs and risks, strengthening park‐people communication and diversifying incentives to farmers with different livelihood strategies.

Incorporating perceived responsibility on tourism sustainability in tourist typology through the knowledge gap theory

<p>This study investigates the application of knowledge gap theory in the context of tourism sustainability, examining the perceptions that varying types of tourists have about their own responsibilities to tourism sustainability, with regard to preferences on tourism information and travel modes. This study aims to develop a typology of tourists based on perceived self-responsibility towards tourism sustainability. A mixed-methods approach was employed, starting with the focus group followed by a survey. Data were gathered from three cities, resulting in 864 valid samples for the final analysis. The findings suggested that although most samples endorsed tourism sustainability indicators, obvious disparity was found in perceived self-responsibility across sample groups, particularly among those with a preference for digital information. Four distinct tourist types were identified based on their perceived self-responsibility on tourism sustainability. The results offer crucial insights for policymakers and industry stakeholders in fostering sustainable tourism practices for target tourist segments. By identifying and bridging knowledge gaps and customizing strategies to cater to various tourist demographics, a more responsible and sustainable approach to tourism can be cultivated.<strong></strong></p>

Validation and refinement of cropland map in southwestern China by harnessing ten contemporary datasets

Accurate cropland map serves as the cornerstone of effective agricultural monitoring. Despite the continuous enrichment of remotely sensed cropland maps, pervasive inconsistencies have impeded their further application. This issue is particularly evident in areas with limited valid observations, such as southwestern China, which is characterized by its complex topography and fragmented parcels. In this study, we constructed multi-sourced samples independent of the data producers, taking advantage of open-source validation datasets and sampling to rectify the accuracy of ten contemporary cropland maps in southwestern China, decoded their inconsistencies, and generated a refined cropland map (CroplandSyn) by leveraging ten state-of-the-art remotely sensed cropland maps released from 2021 onwards using the self-adaptive threshold method. Validations, conducted at both prefecture and county scales, underscored the superiority of the refined cropland map, aligning more closely with national land survey data. The refined cropland map and samples are publicly available to users. Our study offers valuable insights for improving agricultural practices and land management in under-monitored areas by providing high-quality cropland maps and validation datasets.

Augmenting maternal clinical cohort data with administrative laboratory dataset linkages: a validation study.

The use of big data and large language models in healthcare can play a key role in improving patient treatment and healthcare management, especially when applied to large-scale administrative data. A major challenge to achieving this is ensuring that patient confidentiality and personal information is protected. One way to overcome this is by augmenting clinical data with administrative laboratory dataset linkages in order to avoid the use of demographic information. We explored an alternative method to examine patient files from a large administrative dataset in South Africa (the National Health Laboratory Services, or NHLS), by linking external data to the NHLS database using specimen barcodes associated with laboratory tests. This offers us with a deterministic way of performing data linkages without accessing demographic information. In this paper, we quantify the performance metrics of this approach. The linkage of the large NHLS data to external hospital data using specimen barcodes achieved a 95% success. Out of the 1200 records in the validation sample, 87% were exact matches and 9% were matches with typographic correction. The remaining 5% were either complete mismatches or were due to duplicates in the administrative data. The high success rate indicates the reliability of using barcodes for linking data without demographic identifiers. Specimen barcodes are an effective tool for deterministic linking in health data, and may provide a method of creating large, linked data sets without compromising patient confidentiality.

Chronic venous disease of lower limbs in young men at high-altitude: A cross-sectional survey.

The aim of this study was to understand the prevalence of chronic venous disease (CVD) of lower limbs in young men at high-altitude in Xizang, and to provide prevention measures. The convenient sampling method was used to conduct a questionnaire survey among males aged 18 to 40 above an altitude of 3000meters in Xizang in April 2023. The contents of the questionnaire included basic information, symptoms of CVD of lower limbs, protection status and training needs. Multivariate logistic regression model was calculated to evaluate the risk factors for CVD. A total of 350 survey questionnaires were received, and 326 valid samples were collected. The prevalence of CVD of lower limbs (C1-C6) was 37.42% (95%CI: 32.17%-42.68%), the ratio of C0 to C5 were 62.58%, 27.30%, 3.07%, 4.60%, 2.15% and 0.31%, respectively, no one reached C6. The top three symptoms of CVD were lower limb fatigue (18.10%), heaviness (15.34%) and pain (13.19%). 46.01% of respondents were unaware of CVD, and 12.88% of respondents did not have any protective measures of CVD. Multivariate logistic regression showed that age (OR = 1.076, 95%CI: 1.018-1.137, p = .009), preference for spicy food (OR = 1.747, 95%CI: 1.083-2.818, p = .022), unbalanced diet (OR = 1.877, 95%CI: 1.049-3.358, p = .034) and physical exercise (OR 0.610, 95%CI: 0.377-0.986, p = .044) were the independent risk factors for CVD. This study provided data on the prevalence of CVD in young men at high-altitude and the risk factors for CVD. The findings of this study may facilitate the development of individualized clinical assessments and targeted prevention programs.

Exploring the recycled water acceptance based on the technological perspective of UTAUT2: a hybrid analytical approach.

The development of advanced sewage technologies empowers the industry to produce high-quality recycled water, which greatly influences human's life and health. Thus, this study investigates the mechanism of individuals' adoption of recycled water from the technology adoption perspective. Employing the mixed method of structural equation modeling and artificial neural network analysis, we examined a research model developed from the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) framework. To examine the research model, this study employs a leading web-survey company (Sojump) to collect 308 valid samples from the residents in mainland China. The structural equation modeling results verified the associations between the six predictors (performance expectancy, effort expectancy, social influence, facilitating conditions, environmental motivation, and price value), individuals' cognitive and emotional attitudes, and acceptance intention. The artificial neural network analysis validates and complements the structural equation modeling results by unveiling the importance rank of the significant determinants of the acceptance decisions. The study provides theoretical implications for recycled water research and useful insights for practitioners and policymakers to reduce the environmental hazards of water scarcity.