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Through examination of the Library Reference Model (LRM) specifications for nomen and the potential challenges visual nomen might present for their description and use in information systems, the purpose of this study was to investigate two questions: (1) how do nonlinguistic or nonalphanumeric signs or symbols act as nomen to identify entities? and (2) what details or attributes are relevant to describe and classify such nomen to integrate them into information systems?

This research was built on an exploratory, qualitative instrumental case study design using multiple (or comparative) cases. Using the International Federation of Library Associations and Institutions LRM conceptualization of nomen as the basis, this research explored the similarities and differences between the LRM definition, its attributes and the use of nonlinguistic and nonalphanumeric “strings” for visual nomen to represent a res, moving iteratively between the LRM documentation, visual nomen identified in previous research and additional examples. This study used a constant comparative method to conduct a structured, focused comparison across different cases found in the source survey.

A close review of the history of the development of the nomen entity was made to understand the semiotic relationship between entities and their symbolic representation, how those symbols are then reified to be further classified and described and how such definitions in the LRM offer a path forward for better understanding the role and function of visual nomen. Based on the foundation of the nomen entity and its attributes established in the LRM, this research then looked at visual representations of concepts and entities to suggest a nascent framework for describing aspects of visual nomen which may be relevant to their use and application

This exploratory study of the use of supralinguistic ways of referencing entities delineates novel insights into a potential framework for describing and using visual nomen as a way of labeling or naming entities represented in information systems. By examining the specifications of the nomen entity and its attributes as delineated by the LRM, this study reinforces the applicability of LRM-defined attributes in the use of visual nomen in addition to offering other attributes or dimensions.

This study aims to examine the underlying emotional process that explains how context-specific stimuli involved in virtual reality (VR) destinations translate into presence perceptions and behavioral intentions.

In total, 403 potential tourists participated in a self-administered online survey after they watched a randomly assigned VR tour. The Lavaan package in R software was used to conduct structural equation analysis and examine the proposed theoretical framework.

The results reveal that media content consisting of informativeness, aesthetics and novelty was positively related to users’ sense of presence in a VR tour. The effect of media content on presence was partially mediated by emotional arousal.

Managers and VR designers can create an emotive virtual tour that contributes to the user’s sense of presence to promote attraction to the target destination. The VR content needs to be informative, aesthetic and novel, which can excite users during the VR tour, portray virtual destinations clearly and eventually influence potential tourists’ visit intentions.

Research on the emotional mechanism to generate presence is still in its infancy. This study integrates presence theory into a conceptual framework to explore how media content influences presence and decision-making through the emotional mechanism.

Hotel servicescapes have been extensively examined in the literature; however, there has been less attention on green servicescapes that attract consumers to visit green hotels. This model explores the relationship among green servicescapes – green items, green surfaces, natural environment, green consumerism and their outcomes, including intentions to return and green evangelism with a moderating role of green perceived quality.

The multi-wave method was utilized to gather data from China's major cities, Beijing and Shanghai. A total of 462 responses were received over three waves. Subsequently, the data were analyzed employing structural equation modeling (SEM) in Smart PLS 4.

The findings indicated that green servicescape – green items, green surfaces and natural environment – have a positive impact on green consumerism. The authors have discovered that green consumerism leads to positive intentions among consumers to return and engage in green evangelism. Green perceived quality significantly moderated the relationship between green servicescape and green consumerism.

The study offers insightful contributions to academia and managerial fields, encompassing consumer psychology, consumer behaviour, the stimulus-organism-response (SOR) framework and servicescapes. Additionally, it assists hotel managers in addressing challenges stemming from the competitive environment and creating a more environmentally friendly atmosphere.

The research focused on the innovative reflective model of green consumerism model and adopted a pioneering approach to examine green servicescapes within the hotel industry. This study enhances understanding of consumer intentions to return and the influence of green consumerism on green evangelism, while also quantifying the significance of green perceived quality.

The purpose of this paper is to understand the influence of family ownership and governance mechanisms on corporate social responsibility (CSR) scores through the lens of the principal–principal (PP) perspective.

Using a random-effects model the authors sample 21 hundred board members across a 101 listed Mexican companies from 2008 to 2020.

The paper finds that board independence and board committees are positively related to CSR scores.

Results of this paper suggest that stronger governance can enhance CSR: board independence and committees can be a counterbalancing mechanism serving stakeholders aiming to improve CSR scores.

Most CSR research has focused on determinants and outcomes of CSR. The authors analyze an unexplored aspect of the corporate governance (CG) and CSR relationship: the potential influence of family ownership and governance mechanisms on CSR.

Comprender la influencia de la propiedad familiar y mecanismos de gobierno en las calificaciones de Responsabilidad Social Corporativa (RSC) a través de la perspectiva principal-principal.

Usando un modelo de efectos aleatorios en una muestra de dos mil cien consejeros en ciento un empresas públicas mexicanas del 2008 al 2020.

La independencia y comités del consejo tienen una relación positiva con calificaciones RSC.

Los resultados sugieren que instituciones más fuertes de gobierno pueden incrementar el RSC: la independencia y los comités del consejo pueden ser un mecanismo que haga dicho balance sirviendo a partes interesadas que deseen mejorar calificaciones de RSC.

La mayoría de la investigación en RSC se ha enfocado en determinantes y productos de RSC. Nosotros analizamos un aspecto no explorado en la relación de gobernanza y RSC: la potential influencia de la propiedad familiar y los mecanismos de gobierno en la RSC.

The purpose of this study is twofold: firstly, to investigate the effect of the infill value and build orientation on the fatigue behaviour of polylactic acid (PLA) specimens made by fused filament fabrication (FFF), also known as fused deposition modelling; and secondly, to model the fatigue behaviour of PLA specimens made by FFF and similar additive manufactured parts.

A new methodology based on filament characterisation, infill measuring, axial fatigue testing and fatigue strength normalisation is proposed and implemented. Sixty fatigue FFF specimens made of PLA were fabricated and evaluated using variable infill percentage and build orientation. On the other hand, fatigue modelling is based on the normalised stress amplitude and the fatigue life in terms of number of cycles. In addition, a probabilistic model was developed to predict the fatigue strength and life of FFF components.

The infill percentage and build orientation have a great influence on the fatigue behaviour of FFF components. The larger the infill percentage, the greater the fatigue strength and life. Regarding the build orientation, the specimens in the up-right orientation showed a much smaller fatigue strength and life than the specimens in the flat and on-edge orientations. Regarding the fatigue behaviour modelling, the proposed Weibull model can predict with an acceptable reliability the stress-life performance of PLA-FFF components.

This study has been limited to axial fatigue loading conditions along three different build orientations and only one type of material.

The results of this study are valuable to predict the fatigue behaviour of FFF parts that will work under variable loading conditions. The proposed model can help designers and manufacturer to reduce the need of experimental tests when designing and fabricating FFF components for fatigue conditions.

A fatigue study based on a novel experimental methodology that considers the variation of the FFF process parameters, the measurement of the real infill value and the normalisation of the results to be comparable with other studies is proposed. Furthermore, a new fatigue model able to predict the stress-life fatigue behaviour of PLA-FFF components considering variable process parameters is also proposed.

The term “Brazilian popular music” refers to a varied repertoire of musical styles with a strong connection to local culture. The initiatives of representation of this domain of interest occur through adaptations of generic models and strategies coming from contexts and musical styles that differ from the essential characteristics of the national music. The purpose of this paper is to present a characterization of Brazilian popular music as a conceptual model which supports the communication and analysis of this domain and serves as a reference ontology for various applications in the field of Information Science and others.

To achieve the purpose, a mapping about Brazilian popular music was done from a literature review and a data collection with expert users, based on domain analysis theory. From this characterization, the conceptual model was built using an Ontology Engineering approach. To facilitate understanding, the results were described using a more user-friendly notation.

The paper presents a conceptual model as a first semantic reference on Brazilian popular music that serves (1) to better understand, communicate and analyze the domain of Brazilian popular music and, (2) to supply some semantic aspects not covered by the adaptations that have been proposed on the literature for musical representation.

The paper adds a new perspective to the understanding of Brazilian popular music and open opportunity to explore other repertoires about popular music.

In recent decades, the use of capital punishment has declined, but in its place, a ‘new death penalty’ has arisen: life without parole (LWOP), which is being used far more frequently and for more crimes than capital punishment ever was. Yet, LWOP has received far less scholarly attention than the death penalty. Because of its greater scale, assessing the effects of LWOP on crime has important policy implications and is a better test of extreme penalties. Existing studies of LWOP focus on humanitarian issues and ignore its potentially reciprocal relationship with crime. Therefore, we use available LWOP data to fill these gaps in the literature, using models specifically designed to control for potential reciprocal effects. The results indicate there is no reciprocal causation between LWOP and violent crime and, at best, LWOP’s impact on crime is small, temporary, and, most importantly, no greater than the impact of life with parole.

The present study connects the literature on sustainable HRM with that on employability to investigate the relationship between sustainability-oriented human resource actions and organizational outcomes. More specifically, this study explores how training for employability affects the employer–employee relationship and employee retention. Furthermore, this study considers competitive intensity as a potential moderator in these relationships.

The analyses draw on the fourth European Company Survey (ECS 2019) with a sample of 21?869 firms with more than ten employees. Two separate logistic regression models were used to test the hypothesis.

The results show that training for employability contributes to improving the employer–employee relationship and that competitive intensity positively shapes this relationship. Contextually, training for employability reduces the overall employee retention of the firm.

Although this study supports the potential win–win nature of employability support, especially for companies that operate in competitive markets and an uncertain environment, it also highlights the existence of paradoxical sustainability tensions that should be managed by employers.

This study examines how the locus of agency of brands' artificial intelligence (AI)–powered voice assistants (VAs) could lead to brand loyalty through perceived control, flow and consumer happiness under the moderating influences of brand image and voice congruity.

This study conducted a 2 (locus of agency: high vs. low) by 2 (brand image-voice congruity: congruent vs. incongruent) between-subjects experimental design. MANOVA, ANOVA and structural equation modeling (SEM) were conducted to test the hypothesized model.

ANOVA results revealed that human-centric (vs. machine-centric) agency led to higher perceived control. The interaction effect was significant, indicating the importance of congruency between brand image and VAs' voices. SEM results confirmed that perceived control predicted brand loyalty fully mediated by flow experience and consumer happiness.

This study provides evidence that the positive technology paradigm could carve out a new path in existing literature on AI-powered devices by showing the potential of a smart device as a tool for improving consumer–brand relationships and enriching consumers' well-being.

This study aims to investigate tourists’ attitudes and intentions regarding the usage of Chat Generative Pre-trained Transformer (ChatGPT) for accessing tourism information. Furthermore, by integrating the perceived risks associated with ChatGPT and the theory of planned behavior (TPB), this research examines the impact of three types of perceived risks, such as privacy risk, accuracy risk and overreliance risk, on tourists’ behavioral intention.

Data were gathered for this study by using two online survey platforms, thus resulting in a sample of 536 respondents. The online survey questionnaire assessed tourists’ perceived risks, attitude, subjective norm, perceived behavioral control, behavioral intention and demographic information related to their usage of ChatGPT.

The structural equation modeling analysis revealed that tourists express concerns about the associated risks of using ChatGPT to search for tourism information, specifically privacy risk, accuracy risk and overreliance risk. It was found that perceived risks significantly influence tourists’ attitude and intention toward the usage of ChatGPT, which is consistent with the hypotheses proposed in previous literature regarding tourists’ perceived risks of ChatGPT.

This work is a preliminary empirical study that assesses tourists’ behavioral intention toward the use of ChatGPT in the field of tourism. Previous research has remained at the hypothetical level, speculating about the impact of ChatGPT on the tourism industry. This study investigates the behavioral intention of tourists who have used ChatGPT to search for travel information. Furthermore, this study provides evidence based on the outcome of this research and offers theoretical foundations for the sustainable development of generative AI in the tourism domain. This study has limitations in that it primarily focused on exploring the risks associated with ChatGPT and did not extensively investigate its range of benefits.

First, to address privacy concerns that pose significant challenges for chatbots various measures, such as data encryption, secure storage and obtaining user consent, are crucial. Second, despite concerns and uncertainties, the introduction of ChatGPT holds promising prospects for the tourism industry. By offering personalized recommendations and enhancing operational efficiency, ChatGPT has the potential to revolutionize travel experiences. Finally, recognizing the potential of ChatGPT in enhancing customer service and operational efficiency is crucial for tourism enterprises.

Recognizing the potential of ChatGPT in enhancing customer service and operational efficiency is crucial for tourism enterprises. As their interest in adopting ChatGPT grows, increased investments and resources will be dedicated to developing and implementing ChatGPT solutions. This enhancement may involve creating customized ChatGPT solutions and actively engaging in training and development programs to empower employees in effectively using ChatGPT’s capabilities. Such initiatives can contribute to improved customer service and overall operations within the tourism industry.

This study integrates TPB with perceived risks in ChatGPT, thus providing empirical evidence. It highlights the importance of considering perceived risks in tourists’ intentions and contributes to the sustainable development of generative AI in tourism. As such, it provides valuable insights for practitioners and policymakers.

本研究旨在调查游客对使用ChatGPT获取旅游信息的态度和意向。此外, 通过将与ChatGPT相关的感知风险与计划行为理论（TPB）相结合, 本研究探讨了三种感知风险（隐私风险、准确性风险和过度依赖风险）对游客行为意向的影响。

本研究通过两个在线调查平台收集了536名受访者的数据。在线调查问卷评估了游客对ChatGPT使用的感知风险、态度、主观规范、感知行为控制、行为意向以及与其使用ChatGPT相关的人口统计信息。

结构方程建模分析显示, 游客对使用ChatGPT搜索旅游信息的相关风险表示关切, 特别是隐私风险、准确性风险和过度依赖风险。发现感知风险显著影响游客对使用ChatGPT的态度和意向, 与先前有关游客对ChatGPT感知风险的文献中提出的假设一致。

本研究将TPB与ChatGPT中的感知风险相结合, 提供了实证证据。它强调了在考虑游客意向时考虑感知风险的重要性, 并为旅游中生成AI的可持续发展提供了贡献。因此, 它为从业者和政策制定者提供了宝贵的见解。