Model Theory Research Articles

Powers of commutators in linear algebraic groups

Powers of commutators in linear algebraic groups

Permeability evolution of fractured coal subject to confining stress and true triaxial stress loading: experiment and mathematical model

The accurate elucidation and prediction of coal permeability evolution under stress loading conditions are crucial for coalbed methane production. In this study, flow experiments were conducted on six cylindrical coal samples and four cubic coal samples under both confining and true triaxial stress loading conditions, respectively. The structure and characteristic parameters of the fractures inside each coal sample were obtained using the computed tomography scanning system and image processing technologies. The coal permeability under both types of loading processes was calculated through the transient pulse method. A mathematical model was developed to assess the evolution of coal permeability under true triaxial loading based on the current true triaxial permeability model and fractal theory. The results revealed that during the confining pressure loading, the coal permeability decreased exponentially with effective stress and was effectively described using the SD model. Additionally, the coal permeability initially rapidly decreased, followed by a gradual decrease, and eventually stabilized at a constant value. Particularly, during the first three loading steps, the fracture aperture and corresponding permeability of the six cylindrical coal samples decreased by ∼51.79%–57.83% and ∼38.06%–42.12%, respectively. However, during the final three loading steps, the fracture aperture and corresponding permeability of the six coal samples decreased by ∼18.26%–23.08% and ∼22.15%–26.93%, respectively. Moreover, owing to the various crossing angles of complex fracture networks with each principal stress, the effect of each principal stress on the coal permeability evolution was highly anisotropic during triaxial stress loading. Particularly, the permeability of the ST1 sample decreased by 43.08%, 14.84%, and 42.08% during the loading of each principal stress. Similarly, the permeability of the ST2 sample decreased by ∼65.74%, 14.29%, and 19.97%. The permeability reductions for the ST3 sample were ∼34.03%, 55.85%, and 10.12%, while those for the ST4 sample were ∼35.97%, 46.51%, and 17.52%. The SD model failed to describe these anisotropic effects. Compared with the SD model, the improved model, based on the current true triaxial permeability model and fractal theory, effectively described the anisotropic effect of each principal stress on the permeability of coal samples with complex fracture networks under triaxial stress conditions.

“An island on the edge of Europe”: A study on academic air travel in Finland through a combined model of practice

Although evidence about the environmental harm of air travel is growing, the goal of internationalization remains firmly built into academia. The aim of this article is to study this dilemma from both the institutional and individual levels. We seek to determine the elements of academic air travel from an online survey conducted at a Finnish research university. We utilize a combined model of practice, which merges the three-element model of practice theory and the levels of society approach. We also reflect upon the travel policies of all 14 Finnish research universities against the needs and wants of the individual academic.Our findings highlight that the core elements of academic air travel in the institution we studied are physical events, social interaction, technologies, and environmental values. Although virtual alternatives and slow travel are gaining momentum, more support is needed to replace the informal interactions associated with physical presence. In addition, the external pressure to travel, e.g., to undertake fieldwork or attend conferences, is limiting efforts toward low-carbon travel. We hypothesize that change is particularly difficult to induce with linkages between various levels of society. Our combined model of practice provides a tool to identify the elements of practice that can be influenced by the individual or require changes at the institutional or even the national levels. Finally, we note a mismatch between some forms of policy support between individuals and institutions, showing a need for more practical rather than theoretical support, especially with lowering academic expectations on the need to travel.

Influence of Severity and Susceptibility Information Content on Users’ Psychological Response in Emergencies—The Moderating Effect of Regulatory Focus

Information content is crucial for public opinion governance, yet its psychological mechanisms remain unclear. This paper endeavors to bridge this knowledge gap by examining the influence of information content on users’ psychological responses. Drawing insights from the heuristic-systematic model (HSM) and regulatory focus theory, we constructed a novel cognitive and emotional response model. Regression analysis reveals that susceptibility strongly influences primary cognitive responses, while severity affects secondary ones. Susceptibility has a stronger impact on emotional responses than severity. Promotion-focus users are less influenced by severity and susceptibility than prevention-focus users. These results offer valuable insights for emergency management strategies and enhance individuals’ resilience in coping with the psychological toll of emergencies.

Simulation-Driven Universal Surrogates of Coupled Mechanical Systems: Real-Time Simulation of a Forestry Crane

Abstract Preparing simulation-driven surrogates for a coupled mechanical system can be challenging because the associated mechanical and actuator dynamics demand high-fidelity numerical solutions. Proposed here is a universal hydraulic surrogate (UHS), which can provide solutions to high-fidelity mechanical systems with a universal actuator in a surrogate-assisted monolithic approach. The UHS acts as an alternative to the standard lumped fluid theory by eliminating the hydraulic pressures differential equations. A surrogate-assisted universal actuator uses an approximated model to define hydraulic force in high-fidelity mechanical systems. The approximated force model was developed through training against the dynamics of a one-dimensional (1D) hydraulic cylinder and spring-damper. A covariance matrix adaption evolutionary strategy (CMA-ES) was used as an optimization algorithm to minimize differences between the standard dynamics and UHS approaches at the position and velocity levels. The robustness of resulting UHS was validated to predict the behaviors of the simple four-bar mechanism and the forestry crane. The focus was on numerical accuracy and computational efficiency. The maximum percent normalized root mean square error (PN-RMSE) between the states of the approximated force model and lumped fluid theory were approximately 2.04% and 6.95%, respectively. The proposed method was approximately 52 times faster than the standard lumped fluid theory method. By providing accurate predictions outside the training data, the simulation-driven UHS promises better computational performance leading to real-time simulation solutions for the coupled mechanical systems. The UHS can be applied in simulation, optimization, control, state and parameter estimation, and Artificial Intelligence (AI) implementations for coupled mechanical systems.

Exploring the public's beliefs, emotions and sentiments towards the adoption of the metaverse in education: A qualitative inquiry using big data

AbstractThe metaverse is rapidly reshaping our understanding of education, yet identifying the public's beliefs, emotions and sentiments towards its adoption in education remains largely uncharted empirically. Grounded in the Technology Acceptance Model (TAM) and Digital Diffusion Theory (DOI), this paper aims to fill this gap using a big‐data approach and machine learning to scrape comments made by social media users on recent popular posts or videos related to adopting the metaverse in education from three prominent social media platforms. The cleaning process narrowed down 11,024 comments to 4277, then analysed them using thematic, emotion and sentiment analysis techniques. The thematic analysis revealed that adopting the metaverse in education evokes a complex range of public beliefs: (1) innovative learning methods; (2) accessibility and inclusion; (3) concerns about quality and effectiveness; (4) technological challenges and the digital divide; (5) the future of work and skills; and (6) privacy and security concerns. Integrating these themes with emotion and sentiment analyses reveals a landscape of a significant portion of neutral sentiments that corroborates enthusiasm attenuated by caution. This careful consideration stresses the urgent need for a balanced approach to adopting the metaverse in education to ensure that resulting educational advancements benefit all learners equitably. As one of the first studies to offer a multidimensional view of the public's beliefs about metaverse education using big data, this research not only contributes to TAM and DOI but also provides critical insights that could inform policy, enhance educational practices and guide future scholarship in this emerging field.

Psychometric validation of the Danish version of the Major Depression Inventory using data from the Lolland-Falster health study (LOFUS)

Purpose The Major Depression Inventory (MDI) is a widely used self-rating depression scale commonly in primary care in Denmark. It has not been subject to robust psychometric validation in a general population setting. The aim of this study was to evaluate the psychometric measurement properties of the MDI when applied in the general population. Methods We evaluated statistical psychometric validity using modern test theory (confirmatory factor analysis, item response theory models and Rasch measurement theory) testing local independence and differential item function across groups defined by gender, age, education, and chronic disease status. Separate analyses across different strata and across different statistical models were employed. Results Regarding structural validity we consistently identified local dependence for the item two pairs (MDI2,MDI3) and (MDI4,MDI5) across strata. This result was confirmed by bifactor CFA models and item screening. We further identified substantial differential item functioning with respect to age group and with respect to chronic disease. We identified quantified the magnitude of this lack of measurement invariance. Conclusion The MDI is psychometrically valid in homogenous sub populations, but the disclosed evidence of local dependence means that published estimates of its reliability cannot be trusted. The lack of measurement invariance means that the instrument cannot be used to compare individuals or groups unless they are similar in terms of age group and chronic disease status.

A COGNITIVE STYLISTIC STUDY OF EPITHET SYSTEM IN COLSON WHITEHEAD’S FANTASY

Attempts by cognitive stylists to explain readers' comprehension of literary texts face a significant challenge in bridging the author's and reader's worlds. Attempting to clarify the conceptual space that links the different discourse realms to the author-reader levels of interpretation is something that Werth (1999) does. This method offers a fresh perspective on how we think about writing and reading. When it comes to interpreting literature using language models, cognitive stylistics goes farther than conventional stylistic accounting. It examines reading experiences, both comparable and different, by applying concepts from cognitive science regarding the mind, language, and the world. The purpose of this research is to examine Colson Whitehead's chosen novel through the lens of cognitive stylistic devices, with a focus on the impact of mental spaces on meaning interpretation. The poet's worldview can be better conceptualized through the use of these mental spaces in the construction of grammars. Not only are they utilized to model dynamic mapping in language and mind, but they also interact and aid in the integration of concepts throughout production. The study utilizes a descriptive qualitative method with the model of Text World Theory by Werth (1999). The study concludes that Text World Theory is used in a novel to describe the characters' lives in various locations, such as subways, kill fields, refuges, colleges, and streets. The protagonist's solitude, paralysis, and senseless state are depicted through the use of pronouns like 'he', 'they/routes', and 'it/gray'. The characters' world is described as tedious, paralyzed, and a gloomy environment. The epithets, which are adjectives and nouns, describe the protagonist's life in a dark, gloomy environment filled with corpses, bad smells, and crazy activities. These epithets help to convey the complexities of the characters' lives and the complexities of their world.

An improved model for discrete element method simulation of spatial gradient distributions of freeze-thaw-induced damage to sandstone

The investigation into the freeze-thaw (F-T) damage holds paramount theoretical significance in comprehending the mechanisms underlying F-T disasters, predicting catastrophes, and devising engineering protection systems. F-T damage in rock evolves progressively from the surface towards the interior, however, current models exhibit conspicuous deficiencies in simulating such progressive damage. Drawing upon experimental findings concerning the evolution of F-T damage in water-saturated rock, an improved discrete element model (DEM) for rock F-T damage is developed. In this model, thermal conduction model and volume expansion theory are integrated to describe the volumetric expansion characteristics during the freezing of internal pore water, thus effectively simulating the initiation and progression characteristics of frost heave cracks. We validated this model through comparisons with theoretical analyses and experiments, exploring the effects of model parameters. Employing moment tensor, the spatial gradient distribution patterns of F-T damage in water-saturated rock from the vantage point of fracture energy was analyzed. The results reveal that at −20 °C, 20 F-T cycles are requisite for the propagation of damage from the outer layer to the center of the Sichuan sandstone samples. The extent of damage in the outer layer exceeds that of the center, with the maximum fracture energy density of the outer layer being approximately 38.7 times that of the center. This model aptly delineates the progressive development of F-T damage characteristics and holds promise for further applications in identifying and delineating F-T damage zones in cold region rock engineering.

Comparison of the Sample Preparation Strategies and Impacts on the Tensile Strength of Gas Shale with Variable Moisture Conditions

Moisture significantly affects the mechanical behavior of gas shale and further determines the hydraulic fracturing performance, as it is more attractive. Nevertheless, batch experiments have usually involved variable methodologies regarding the preparation of moisture-contained shale specimens in the sequence (and/or frequency) of drying and soaking treatments. Accordingly, this work investigates how the preparation methodology influences the test results of moisture-contained shale samples. This study compares three commonly used shale sample preparation strategies for acquiring different moisture contents, that is, “dry-wet”, “dry-wet-dry”, and “wet-dry-wet” strategies, followed by a Brazilian splitting test for the mechanical parameters. The results show that under the same saturation conditions, the longer the soaking time during sample preparation, the higher the degradation degree of shale tensile strength. Meanwhile, prolonged soaking can lead to a more discrete distribution of strength values, and the failure mode may deviate from the Brazilian splitting theory model. Under the combined influence of moisture content and soaking time, the tensile strength of shale decreases approximately linearly with increasing saturation, while the degradation degree increases nonlinearly with increasing saturation, and the degradation rate changes from slow to fast. According to the observation of the microstructure of hydrated shale, prolonged soaking can lead to an increase in the expansion of clay minerals in shale by hydration, resulting in looser and more fragmented internal structure, and further degradation in shale strength. In order to weaken the interference of hydration when studying the effect of moisture content on the tensile strength of shale, the soaking time should be minimized as much as possible during the preparation process.

Item analysis on the quality of life scale for anxiety disorders QLICD-AD(V2.0) based on classical test theory and item response theory

BackgroundAnxiety disorders can cause serious physical and psychological damage, so many anxiety scales have been developed internationally to measure anxiety disorders, but due to the cultural differences and cultural dependence of quality of life between Chinese and Western cultures, it is difficult to reflect the main characteristics of Chinese patients. Therefore, we developed a scale suitable for Chinese patients with anxiety disorders: the Anxiety Disorders Scale of the Quality of Life Instruments for Chronic Diseases (QLICD-AD), hoping to achieve satisfactory QOL assessments for anxiety disorders.ObjectivesItems from the Anxiety Disorders Scale of the Quality of Life in Chronic Disease Instrument QLICD-AD system were analyzed using CTT and IRT to lay the groundwork for further refinement of the scale to accurately measure anxiety disorders.Methods120 patients with anxiety disorder were assessed using the QLICD-AD (V2.0). Descriptive statistics, variability method, correlation coefficient method, factor analysis and Cronbach’s coefficient of CTT, and graded response model (GRM) of item response theory were used to analyze the items of the scale.ResultCTT analysis showed that the standard deviation of each item was between 0.928 and 1.466; Pearson correlation coefficients of item-to-domain were generally greater than 0.5 and also greater than that of item-to-other domain; the Cronbach ‘s of the total scale was 0.931, α of each domain was between 0.706 and 0.865. IRT analysis showed that the discrimination was between 1.14 and 1.44. The difficulty parameter of all items increased with the increase of grade. But some items (GPH6,GPH8,GPS3,GSO2-GSO4,AD2,AD5) difficulty parameters were less than 4 or greater than 4. The average of information amount was between 0.022 and 0.910.ConclusionBased on CTT and IRT analysis, most items of the QLICD-AD (V2.0) scale have good performance and good differentiation, but a few items still need further revision. Suggests that the QLICD-AD (V2.0) appears to be a valid measure of anxiety disorders. It may effectively improve the diagnosticity of anxiety disorders, but due to the limitations of the current sample, further validation is needed in a broader population extrapolation trial.

Psychological factors enhanced heterogeneous learning interactive graph knowledge tracing for understanding the learning process.

With the rapid expansion of online education, there is a burgeoning interest within the EdTech space to offer tailored learning experiences that cater to individual student's abilities and needs. Within this framework, knowledge tracing tasks have garnered considerable attention. The primary objective of knowledge tracing is to develop a model that assesses a student's proficiency in a particular skill based on their historical performance in exercises, enabling predictions regarding the likelihood of correct responses in future exercises. While existing knowledge tracing models often incorporate information such as students' exercise answering history and skill mastery level, they frequently overlook the students' mental states during the learning process. This paper addresses this gap by introducing a novel psychological factors-enhanced heterogeneous learning interactive graph knowledge tracing model (Psy-KT). This model delineates the interactions among students, exercises, and skills through a heterogeneous graph, supplementing it with four psychological factors that capture students' mental states during the learning process: frustration level, confusion level, concentration level, and boredom level. In the modeling of students' learning processes, we incorporate the forgetting curve and construct relevant cognitive parameters from the features. Additionally, we employ the Item Response Theory (IRT) model to predict students' performance in answering exercises at the subsequent time step. This model not only delves into the psychological aspects of students during the learning process but also integrates the simulation of forgetting, a natural phenomenon in the learning journey. The inclusion of cognitive parameters enhances the description of changes in students' abilities throughout the learning process. This dual focus allows for a more comprehensive understanding of students' learning behaviors while providing a high level of interpretability for the model. Empirical validation of the Psy-KT model is conducted using four publicly available datasets, demonstrating its superior performance in predicting students' future performance. Through rigorous experimentation, the integration of psychological and forgetting factors in the Psy-KT model not only improves predictive accuracy but also enables educators to offer more targeted tutoring and advice, enhancing the overall efficacy of the learning experience.

Alkyl chain length affecting the structure and interactions of choline-based amino acid ionic liquids: Insights from a computational study

The influences of the alkyl chain length of amino acid anions on the structure and interactions of choline-based amino acid ([Cho][AA]) ionic liquids were investigated based on density functional theory (DFT) and molecular dynamics (MD) simulations. The most stable configuration of the individual [Cho][AA] ion pair was determined, revealing negligible variations in the binding energy between choline cation ([Cho]+) and different amino acid anions ([AA]−). To further characterize the intermolecular interactions between charged entities, the atoms in molecules theory (AIM) and independent gradient model based on Hirshfeld partition (IGMH) were employed, which highlight the presence of robust hydrogen bonds between [Cho]+ and [AA] −, underscoring their significance in shaping the structure of [Cho][AA] ion pairs. The MD studies exhibited the aggregation of anions in [Cho][AA] ILs, which was attributed to side chain interactions of anions. This aggregation effect becomes more pronounced with the elongation of anionic alkyl chain. Simultaneously, radial distribution functions (RDF) analysis revealed a higher probability of hydrogen bonds occurring between [Cho]+ and [AA]− as the alkyl chain in [AA]− lengthened. Additionally, the hydrogen bond lifetimes roughly display an increasing trend as the alkyl chain of the [AA]− increases, which may be due to the reduced diffusion coefficients of ions. Hopefully, our results would contribute fundamental knowledge regarding the impact of alkyl chain length of anions on the structure and interactions in the choline-based amino acid ionic liquids.

Understanding covid-19 prevention behaviours: Implications for social and health marketers for the prevention of future pandemics

From the integrative perspectives of the health belief model and social influence theories, the study sought to identify factors social and health marketers should focus on to elicit voluntary change in behavior toward the performance of COVID-19 infection prevention behaviors such as frequent handwashing with soap, social distancing, and avoidance of handshaking using mixed method approach. The quantitative data from 605 respondents through structured questionnaires were analyzed using PLS-SEM. The qualitative data through five focus group discussions were also analyzed using thematic analysis. The result shows that religiosity and trust in traditional medicine are the major factors contributing to the lack of severity and susceptibility to the coronavirus. The result further shows informational and normative social influencers as significant mediators between the constructs of the HBM and the performance of the COVID-19 protocols, suggesting that these influencers play a significant role in achieving the performance of the recommended behaviors.

Reward Sensitivity and Noise Contribute to Negative Affective Bias: A Learning Signal Detection Theory Approach in Decision-Making.

In patients with mood disorders, negative affective biases - systematically prioritising and interpreting information negatively - are common. A translational cognitive task testing this bias has shown that depressed patients have a reduced preference for a high reward under ambiguous decision-making conditions. The precise mechanisms underscoring this bias are, however, not yet understood. We therefore developed a set of measures to probe the underlying source of the behavioural bias by testing its relationship to a participant's reward sensitivity, value sensitivity and reward learning rate. One-hundred-forty-eight participants completed three online behavioural tasks: the original ambiguous-cue decision-making task probing negative affective bias, a probabilistic reward learning task probing reward sensitivity and reward learning rate, and a gambling task probing value sensitivity. We modelled the learning task through a dynamic signal detection theory model and the gambling task through an expectation-maximisation prospect theory model. Reward sensitivity from the probabilistic reward task (β = 0.131, p = 0.024) and setting noise from the probabilistic reward task (β = -0.187, p = 0.028) both predicted the affective bias score in a logistic regression. Increased negative affective bias, at least on this specific task, may therefore be driven in part by a combination of reduced sensitivity to rewards and more variable responses.

Risk assessment of high-speed railway CTC system based on improved game theory and cloud model

PurposeIn order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.Design/methodology/approachFirst, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.FindingsThe cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.Originality/valueThis study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.

Geometry of the spectral parameter and renormalisation of integrable sigma-models

In the past few years, the unifying frameworks of 4-dimensional Chern-Simons theory and affine Gaudin models have allowed for the systematic construction of a large family of integrable σ-models. These models depend on the data of a Riemann surface C (here of genus 0 or 1) and of a meromorphic 1-form ω on C, which encodes the geometry of their spectral parameter and the analytic structure of their Lax connection. The main subject of this paper is the renormalisation of these theories and in particular two conjectures describing their 1-loop RG-flow in terms of the 1-form ω. These conjectures were put forward in [1] and [2] and were proven in a variety of cases. After extending the proposal of [1] to the elliptic setup (with C of genus 1), we establish the equivalence of these two conjectures and discuss some of their applications. Moreover, we check their veracity on an explicit example, namely an integrable elliptic deformation of the Principal Chiral Model on \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\ ext{SL}}}_{\\mathbb{R}}\\left(N\\right)$$\\end{document}.

Research on Multi-Stage Post-Occupancy Evaluation Framework of Community Comprehensive Elderly Care Service Facilities under the Public-Private Partnership Mode—A Case Study of China

The key to whether elderly individuals in the community can enjoy their later years peacefully lies in the service capabilities of community comprehensive elderly care service facilities (CCECSF) under the Public-Private Partnership (PPP) mode. To maintain a high level of service capability in community comprehensive elderly care service facilities under PPP mode, scientific evaluation of the effectiveness of these facilities is equally crucial. This article first constructs a post-occupancy evaluation index system of community comprehensive elderly care service facilities under PPP mode that includes three evaluation attributes and fifteen evaluation criteria based on the Chinese culture and lifestyle habits. Regarding the issue of direct users being unable to directly participate in evaluations, the uncertainty in evaluation information, and the volatility of evaluation results, a multi-stage post-occupancy evaluation model is constructed based on probabilistic linguistic term set, TOPSIS model and multi-stage decision theory. The above post-occupancy evaluation index system and evaluation model together constitute a multi-stage post-occupancy evaluation framework for community comprehensive elderly care service facilities under PPP mode. The outcomes of the case study indicate that the post-occupancy evaluation index system can offer a scientifically guided approach for evaluating the service level of community comprehensive elderly care service facilities under the PPP mode; meanwhile, the multi-stage evaluation model can enable direct user participation in the post-evaluation of facility usage and improve the robustness and reduce the fluctuation of the evaluation results, so as to improve the scientificity of the evaluation results.

‘Getting addicted to it and losing a lot of money… it’s just like a hole.’ A grounded theory model of how social determinants shape adolescents’ choices to not gamble

BackgroundGambling abstinence when underage lowers the risk of harmful gambling in later life. However, little research has examined why many young people refrain from gambling, even though this knowledge can inform protective strategies and lower risk factors to reduce underage gambling and subsequent harm. This study draws on the lived experience of adolescent non-gamblers to explore how social determinants while growing up have shaped their reasons and choices to not gamble.MethodsFourteen Australian non-gamblers, aged 12–17 years, participated in an in-depth individual interview (4 girls, 3 boys) or online community (4 girls, 3 boys). Questions in each condition differed, but both explored participants’ gambling-related experiences while growing up, including exposure, attitudes and behaviours of parents and peers, advertising, simulated gambling and motivations for not gambling. The analysis used adaptive grounded theory methods.ResultsThe grounded theory model identifies several reasons for not gambling, including not being interested, being below the legal gambling age, discouragement from parent and peers, concern about gambling addiction and harm, not wanting to risk money on a low chance of winning, and moral objections. These reasons were underpinned by several social determinants, including individual, parental, peer and environmental factors that can interact to deter young people from underage gambling. Key protective factors were parental role modelling and guidance, friendship groups who avoided gambling, critical thinking, rational gambling beliefs, financial literacy and having other hobbies and interests.ConclusionsChoices to not gamble emanated from multiple layers of influence, implying that multi-layered interventions, aligned with a public health response, are needed to deter underage gambling. At the environmental level, better age-gating for monetary and simulated gambling, countering cultural pressures, and less exposure to promotional gambling messages, may assist young people to resist these influences. Interventions that support parents to provide appropriate role modelling and guidance for their children are also important. Youth education could include cautionary tales from people with lived experience of gambling harm, and education to increase young people’s financial literacy, ability to recognise marketing tactics, awareness of the risks and harms of gambling, and how to resist peer and other normalising gambling influences.

Consumer Behaviour on AI Applications for Services: Measuring the Impact of Value-Based Adoption Model on Luxurious AI Resorts’ Applications

Abstract Focussing on consumer behaviour analysis derived from the changes in Information and Communications Technology (ICT), the purpose of this study is to analyse the primary content factors that influence consumers’ attitudes and behavioural intentions in the hospitality industry. The present study is the first to investigate how benefits (happiness and perceived immersion) and sacrifices (trust and changes in habits) can predict consumers’ attitudes of acceptance and willingness to pay for artificially intelligent (AI) luxurious resort applications (apps). The researchers employed structural equation modelling to analyse the relationship between technology adoption and specific factors that influence customers’ perceived value in the hospitality industry. The research aims to expand on the theory of the Value Adoption Model (VAM). Based on the findings, AI-powered apps for high-end resorts have a tendency to boost tourists’ confidence and willingness to use and pay for these apps, as well as increase their perceived value. Happiness has an impact on behavioural intentions, while perceived immersion and changes in habits influence the outcomes related to intentions to ultimately accept and purchase them. The findings can benefit both ICT and the hospitality industry. Managers in the ICT industry should collaborate with researchers in service management who are exploring the challenges of technology adoption. Managerial implications and recommendations for future research are extensively provided.