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This study examines identity theft as a significant and growing issue in Australia, not only due to its financial impact but also because of the emotional, psychological, and physical harm it causes, making it a public health concern. This study aims to analyse the results of the 2019 Australian Institute of Criminology (AIC) survey to identify factors associated with an increased likelihood of identity theft victimisation.

This study involved a detailed analysis of the 2019 AIC survey, which had 9,968 respondents from a sample of 10,000. The research focused on whether respondents had ever been victimised by identity theft and analysed various characteristics, including demographics (gender, age, Indigenous status, education), income, computer usage, and preventive technology use, as potential indicators of future victimisation. Univariate analyses (chi-squared test and two-sample t-test) were used to assess individual associations, whereas a multivariate analysis (logistic regression) identified significant predictors of victimisation.

The univariate analyses indicated that all sub-variables were individually associated with identity theft victimisation. However, the multivariate analysis revealed that only identifying as Aboriginal and Torres Strait Islander, having an income between $18,201 and $37,000, and using multiple preventive technologies were significant predictors of victimisation. The unexpected finding that increased preventive technology use correlates with a higher risk of victimisation contradicts the survey’s suggestion that victims adopt more careful behaviour post-victimisation.

The research highlights the need for further investigation into the counterintuitive finding that greater use of preventive technologies may increase the risk of identity theft. Understanding this discrepancy could inform the development of more effective identity theft prevention strategies by the government and related agencies.

This study contributes to the existing literature by offering a nuanced understanding of the factors associated with identity theft victimisation in Australia that may be applicable globally. The unexpected findings regarding the use of preventive technologies provide a basis for further research and have the potential to influence future policymaking and identity theft prevention efforts.

This tourism study delves into the universal impact of authenticity on tourists' preferences. This study aims to enhance understanding and present a model delineating authenticity's intricate relationship with behavioral intention, involvement and nostalgia.

The research entails administering a sample survey to travelers located in the departure lounge of Macau International Airport. Ultimately, 499 fully completed questionnaires are obtained through convenience sampling. The analysis of the collected data incorporates an innovative method, using a quadratic model.

Results undeniably validate that a destination's perceived authenticity significantly influences tourists' intentions, engagement and nostalgic sentiments. Findings strongly support the assertion that this authenticity demonstrates a nonlinear pattern in its association with behavioral intention, involvement and nostalgia.

Through quantitative analysis and interpretation, this study has advanced the comprehension of the interplay between authenticity and tourism. It introduces a novel perspective that adds depth to the broader understanding in this domain. This foundational research is crucial for acknowledging the unique contributions made by this study to the fields of tourism and authenticity.

这项旅游研究深入探讨了真实性对游客偏好的普遍影响。它旨在增强理解并提出一个模型来描述真实性与行为意图、参与和怀旧之间的复杂关系。

该研究需要对位于澳门国际机场候机室的旅客进行抽样调查。最终通过便利抽样获得完整填写的问卷499份。对收集的数据的分析采用了一种创新方法, 利用二次方模型。

结果无可否认地证实, 目的地的感知真实性会显着影响游客的意图、参与度和怀旧情绪。研究结果有力地支持了这一主张, 即这种真实性在其与行为意图、参与和怀旧的关联中表现出一种非线性模式。

通过定量分析和解释, 这项研究增进了我们对真实性与旅游之间的回应的理解。它引入了一种新颖的视角, 加深了我们对这一领域更广泛的理解。这一基础研究为承认本研究对旅游和真实性领域做出了独特贡献。

Este estudio turístico profundiza en el impacto universal de la autenticidad en las preferencias de los turistas. Pretende mejorar la comprensión y presentar un modelo que delinee la intrincada relación de la autenticidad con la intención conductual, la implicación y la nostalgia.

La investigación consistió en administrar una encuesta por muestreo a los viajeros situados en la sala de embarque del Aeropuerto Internacional de Macao. Finalmente, se obtuvieron 499 cuestionarios totalmente cumplimentados mediante un muestreo de conveniencia. El análisis de los datos recogidos incorpora un método innovador, utilizando un modelo cuadrático.

Los resultados validan sin lugar a duda que la autenticidad percibida de un destino influye significativamente en las intenciones, la implicación y los sentimientos nostálgicos de los turistas. Los hallazgos apoyan firmemente la afirmación de que esta autenticidad demuestra un patrón no lineal en su asociación con la intención conductual, la implicación y la nostalgia.

Mediante el análisis cuantitativo y la interpretación, este estudio ha hecho avanzar nuestra comprensión de la interacción entre autenticidad y turismo. Introduce una perspectiva novedosa que añade profundidad a nuestra comprensión más amplia en este ámbito. Esta investigación fundacional es crucial para reconocer las contribuciones únicas de este estudio a los campos del turismo y la autenticidad.

Managers in China prioritize the cultivation of loyal employees, resulting in positive effects associated with leader-member exchange (LMX). However, fragmented evidence suggests that LMX also can trigger deviant behavior. LMX provides employees with access to resources, while it also harbors potential risks for deviant behaviors. Based on the cognitive-affective system theory of personality and resource-related theories, this study aims to explore the double-edged sword effects of LMX by examining how LMX influences interpersonal deviant behaviors through emotional and cognitive pathways, respectively.

This study involved three waves of paired data surveys that were conducted in China over one month, and a total of 117 leaders and 235 subordinates participated in this study.

Even though LMX as a job resource reduces workplace anxiety, LMX also generates work overload for employees. Workplace anxiety and work overload further result in interpersonal deviant behavior. Narcissistic admiration, as a personality trait, can weaken the mediating role of work overload but not that of workplace anxiety.

The finding can help managers pay attention to negative effect of LMX and provide suggestions for preventing employees’ workplace deviant behavior.

The findings revealed how LMX leads to negative outcomes in the workplace. In addition, the results demonstrated the buffering effect of narcissistic admiration on the negative effect of LMX.

Building on the social capital theory of career success (SCT), this paper aims to explore how and when newcomers’ overqualifications can grant them positions as informal leaders within the workgroup over time.

The model was tested using a social relations modeling analysis conducted using a three-wave survey with 242 newcomers in Macau.

The results support the view that relatively qualified newcomers can enjoy social capital advantages in workgroup networks. Newcomers’ desired qualifications can grant them positions as informal leaders through leader–member exchange and advice network centrality. These relationships are moderated by relational dissimilarity, such that the benefits of being relatively overqualified will be weakened when relational dissimilarity is high (vs. low).

When assisting overqualified newcomers in integrating into their teams, practitioners shall be aware of the time and resources that new hires require for adjustment, especially when significant newcomer–veteran relational dissimilarity exists.

The present paper challenges the overtly detrimental outcomes of overqualification by highlighting the positive relational implications of being relatively overqualified.

Social media usage has been documented to affect the psychological well-being of its users. This study aims to examine how social media overload influences cognitive fatigue among individuals in Malaysia.

This study employed a comprehensive research framework based on the stressor-strain-outcome (SSO) model to examine how perceived overload affects social media cognitive fatigue through emotional exhaustion and anxiety. Survey data were gathered from 451 social media users in Malaysia, and data analysis was performed using PLS-SEM.

The findings revealed that information overload, communication overload and interruption overload are antecedents of emotional exhaustion. Communication overload, interruption overload and cognitive overload were identified as antecedents of anxiety, while emotional exhaustion and anxiety were confirmed as predictors of social media cognitive fatigue. However, pathway analysis indicated no relationship between emotional exhaustion and anxiety.

Our study contributes to the literature on media technology and media psychology by examining the psychological mechanisms (emotional exhaustion and anxiety). The findings offer implications for service providers, practitioners and social media users, as they facilitate measures and strategies to mitigate the adverse effects of social media while elevating psychological well-being.

To provide a holistic assessment of tourists’ staycation intentions, this study aims to investigate the role of secondary-stakeholder corporate social responsibility (CSR) on local engagement. Based on construal-level theory and stimulus-organism-response model, this study unpacks how and when secondary-stakeholder CSR influences staycation intention.

Data were gathered from 312 Chinese tourists with prior staycation experiences. Data were subsequently analyzed using structural equation modeling.

This study illuminates that secondary-stakeholder CSR positively influences staycation intention directly and indirectly through psychological belonging and safety. Noteworthily, immersive experience strengthens the influence of psychological belonging on staycation intention while its effect on the relationship between psychological safety and staycation intention is negligible.

All variables in this study were collected via self-report measures provided by hotel customers with staycation experiences. Although both statistical and procedural remedies are used, it would be more useful if future studies could gather time-lagged and/or multiple sources of data.

This study augments the domain of staycation research by examining CSR marketing through a stakeholder perspective. This nuanced analysis elucidates the intertwined dynamics among secondary-stakeholder CSR, psychological sense of belonging and safety, and immersive experiences that delineate the landscape of staycation markets, casting light on their epoch-defining implications for hotels’ developmental trajectories.

This study aims to explore the perceptions of follower identities among Chinese youth and the formation of these identities within the context of use and gratification theory and mediated relationships.

Interviews were conducted with 22 individuals who followed digital influencers on various social media platforms, and a general inductive approach was followed to analyze the collected data.

The research uncovered that influencers’ followers view themselves as learners, advisees, surveillants, friends and sponsors, aligning these identities with their reasons for following influencers. These reasons are classified as either emotionally or functionally driven. The study further highlights the critical role these motivations and identities play in influencing the followers’ intentions to buy products and brands endorsed by influencers. Followers motivated by utilitarian reasons focus more on the product’s functionality and practical value, whereas those attracted to influencers for their unique personalities and perceived personal connections place greater importance on the products’ symbolic value.

Despite the widespread attention the influencer market has garnered, scant literature has deeply explored the psychological mechanisms behind individuals’ behavior in following influencers and their subsequent purchasing intentions. This study introduces new insights into influencer marketing by focusing on followers’ psychological motivations, offering a refined understanding of their impact on the dynamics of digital marketing.

This study aims to explore the key attributes of robot chef restaurants and their influencing factors from the perspective of customers and analyzes how these key attributes affect customer perceived value.

A mixed-methods research design was used in this study. Using 473 online reviews and ratings (Study 1), the research summarized customers’ evaluations on three types of attributes (environment, service and food) and identified the key attributes along with their influencing factors. Subsequently, through field questionnaires (Study 2) involving 269 actual customers, structural equation modeling was used to analyze how the identified key attributes and their influencing factors impact customer perceived value.

This study reveals that customers in robot chef restaurants prioritize food attributes, particularly valuing food authenticity alongside food quality. In contrast to traditional restaurants, customers’ evaluations of food attributes in robot chef restaurants are significantly influenced by the competence of robot chefs. Notably, customers’ negative attitudes toward robots diminish the positive effects on both food quality and food authenticity.

To enhance customer perceived value, robot chef restaurants should concentrate on food attributes. They can achieve this by fostering a high-quality, authentic food experience through the elevation of robot chefs’ competence and by providing customer education.

This study expands research on the customer experience in robotic restaurants by proposing an integrated model determining factors that affect the perceived customer value.

To setup a theoretical model for grasping cutting pieces of garment better, which will help to design a special soft gripper and push forward the automated level of garment manufacturing.

This paper first analyzed the mechanics of the grasping process and concluded the main factors that affect the success of grasping. A theoretical model named grasping fabric model (GFM) was constructed to show the mechanical relationship between the soft gripper and the fabric pieces. Subsequently, two fabric samples were selected and tested for their friction properties and critical buckling force, and the test data were substituted into the theoretical model GFM to obtain the grasping parameters required for fabric grasping layer by layer.

It was found that (1) the critical buckling force of the fabric is mainly influenced by the bending stiffness and the deformation length of the fabric during grab. (2) The difference between the friction between the soft gripper and the fabric and the friction between the fabric, that is DF1-2, has an important influence on the accuracy of grasping layer-by-layer.

It showed that the grasping parameters provided by GFM enable the two samples to be more effectively separated layer by layer, which verifies that the GFM model is strong enough for the possible application in garment automated production.

We aim to examine two issues. First, we intend to identify the best performing expected return proxies. Second, we investigate whether the expected return proxies for individual stocks can track the corresponding realized returns during extremely good or extremely bad times of the economic environment related to business conditions, stock market valuation and broad market performance.

We construct four sets of expected return proxies, including: (1) characteristic-based proxies; (2) standard risk-factor-based proxies; (3) risk-factor-based proxies that allow betas to vary with firm characteristics and (4) macroeconomic-variable-based proxies. First, we estimate expected returns for individual stocks using newly developed methods and evaluate the performance of these expected return proxies based on the minimum variance criterion of Lee et al. (2020). Second, we regress expected return proxies and realized returns on indicator variables that capture the extreme phases of the economic environment. Then we compare the estimated coefficients from these two sets of regressions and see if they are similar in magnitude via formal hypothesis testing.

We find that characteristic-based proxies and risk-factor-based proxies that allow betas to vary with firm characteristics are the two best performing proxies. Therefore, it is important to allow betas to vary with firm characteristics in constructing expected return proxies. We also find that model-based expected return proxies do a reasonably good job capturing actual returns during extremely bad and extremely good phases of business cycles measured by leading economic indicators, consumer confidence and business confidence. However, there is a large gap between the adjustment of model-based expected returns and realized returns during extreme episodes of stock market valuation or broad market performance.

We examine four types of expected return proxies and use the newly developed methodology as in Lee et al. (2020) to see which one is the best. In addition, we document whether model-based expected returns from individual stocks adjust partially or fully to keep pace with actual returns in response to changing economic conditions. No prior studies have examined these two issues.