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In multi-criteria ranking problems, the UTA-like methods can be used to infer the value functions that restore the decision-maker’s (DM’s) indirect preference information. These value functions represent all possible preference systems for the DM. In this paper, we aim to develop a method for determining the complete ranking of alternatives based on all such value functions.

We extend the DM’s inductive preference for value functions in the selection of a representative value function to rankings of alternatives and construct a novel measure referred as the representativeness index to evaluate the performance of rankings relative to the inductive preference. Subsequently, by exploring all value functions that are capable of generating a ranking, two robust representativeness indices are constructed and a simulation algorithm is proposed for calculating the robust representativeness index.

Determining the ranking based on the representative value function can be seen as selecting the ranking with the largest representativeness index. Additionally, we find through a case study that the ranking determined based on robust representativeness indices has good robustness in the sense of inductive preferences.

The inductive preference is a manifestation of the DM’s preference system. This paper proposes a method for measuring the performance of rankings relative to inductive preferences. The performance of a ranking is defined as the performance of all value functions that can produce that ranking relative to the inductive preference. In turn, it is possible to identify the ranking that best matches the DM’s preference system.

Hypocrisy often observed in the social responsibility practices of commercial enterprises is more likely to occur in social enterprises. However, this issue has received little research attention. This study explores, from a consumer perspective, the formation of perceived hypocrisy and its impact on the cognitive legitimacy of social enterprises.

This research conducted two experiments, and data were collected from 515 subjects in China to test the proposed hypotheses.

Behavioral inconsistency in social enterprises leads to consumers' perceived hypocrisy. The higher the perceived hypocrisy towards social enterprises, the weaker their cognitive legitimacy of social enterprises. At a lower level of inconsistency, the perceived hypocrisy of social enterprises was lower than that of commercial enterprises. Egoistic attribution to prosocial behavior moderated the negative effect of perceived hypocrisy on cognitive legitimacy. The stronger the egoistic attribution, the greater is the negative effect of perceived hypocrisy on the cognitive legitimacy of social enterprises.

Social entrepreneurs should be acutely aware of the harmful effects of hypocrisy on social enterprises. Social enterprises should not exaggerate their propaganda or be consistent with their words and actions.

This study innovatively analyzes the damage to the cognitive legitimacy of social enterprises caused by the hypocrisy that tends to occur in commercial enterprises and argues from the consumer viewpoint. These findings enrich the perspective on exploring social enterprise legitimacy.

COVID-19 halted global tourism, prompting stakeholders to use virtual reality (VR) tourism to maintain interest. Due to technological advancements and wider internet access globally, VR tourism has become increasingly popular. Guided by the attention-interest-desire-action (AIDA) model and the technology acceptance model (TAM) frameworks, and with the inclusion of personal innovativeness, this study aims to clarify consumer intentions toward engaging with VR tourism by investigating factors such as personal innovativeness, interest, perceived usefulness (PU), perceived ease of use (PEOU), attitude and desire.

Data was gathered from 252 participants using a cross-sectional approach, with partial least squares structural equation modeling used to assess the research model.

The findings indicate consumers' personal innovativeness strongly influences VR tourism intention, mediated by PU, attitude and desire. VR tourism intention is also significantly impacted by interest in VR tourism and is mediated by PU and PEOU, attitude and desire. PEOU and PU are significantly linked to interest and determine attitude. Attitude, both directly and indirectly, significantly influences VR tourism intention through users' desire, which mediates the relationship. Through multiple group analysis, the path from desire to intention is found to be moderated by age, education and marital status.

Theoretically, this study pioneers a framework that merges AIDA, TAM and personal innovativeness to advance the understanding of VR tourism adoption dynamics and enrich tourism research. Managerially, it provides valuable guidance on targeting communications and technology toward increasing VR tourism engagement and presents a roadmap for industry practitioners.

This research addresses the identified gaps in extant literature by combining TAM and AIDA with personal innovativeness to investigate the process of consumers' VR tourism intention, triggered by consumers' personal innovativeness and interest in VR tourism. The study highlights significant managerial insights for both tourism industry practitioners and academic researchers, which can assist with decision-making to promote VR tourism development.

COVID-19 使全球旅游业停滞不前, 促使利益相关者使用虚拟现实 (VR) 旅游来保持兴趣。由于技术进步和全球互联网接入的增长, VR 旅游变得越来越受欢迎。基于注意-兴趣-渴望-行动模型 (AIDA) 和技术接受模型 (TAM) 框架, 并纳入个人创新性, 本研究旨在通过调查个人创新性、兴趣、感知有用性、感知易用性、态度和渴望等因素, 澄清消费者对参与 VR 旅游的意图。

使用横截面方法收集了252名参与者的数据, 并使用偏最小二乘结构方程建模来评估研究模型。

研究结果表明, 消费者的个人创新性通过感知有用性、态度和渴望显著影响 VR 旅游意图。VR 旅游意图也受到对 VR 旅游兴趣的显著影响, 并通过感知有用性、感知易用性、态度和渴望进行调节。感知易用性和感知有用性显著与兴趣相关, 并决定态度。态度通过用户的渴望直接和间接地显著影响 VR 旅游意图, 这些渴望调节了这种关系。通过多群组分析, 发现年龄、教育和婚姻状况对渴望与意图之间的路径具有调节作用。

本研究通过结合 TAM 和 AIDA 与个人创新性来研究消费者的 VR 旅游意图过程, 填补了现有文献中的空白。本研究强调了对旅游业从业者和学术研究人员的重大管理见解, 这些见解可以帮助决策者推动 VR 旅游的发展。

从理论上讲, 本研究开创了一个结合 AIDA、TAM 和个人创新性的框架, 以提升对 VR 旅游采用动态的理解, 并丰富旅游研究。从管理角度来看, 它提供了有价值的指南, 帮助定位通信和技术, 以增加 VR 旅游参与度, 并为行业从业者提供了发展路线图。

El COVID-19 detuvo el turismo global, lo que indujo a las partes implicadas a utilizar el turismo de realidad virtual para mantener el nivel de interés. Debido a los avances tecnológicos y al acceso más amplio a Internet a nivel mundial, el turismo de realidad virtual se ha vuelto cada vez más común. Basándose en el modelo de Atención-Interés-Deseo-Acción (AIDA) y en el modelo de aceptación tecnológica (TAM), y con la inclusión de la innovación personal, este estudio tiene como objetivo comprender las intenciones de los consumidores hacia el compromiso con el turismo de realidad virtual investigando factores como la innovación personal, el interés, la utilidad percibida, la facilidad de uso percibida, la actitud y el deseo.

Se recopilaron datos de 252 participantes utilizando un enfoque transversal, y se utilizó la modelización de ecuaciones estructurales de mínimos cuadrados parciales para evaluar el modelo de investigación.

Los resultados indican que la innovación personal de los consumidores influye fuertemente en la intención de turismo de realidad virtual mediada por la utilidad percibida, la actitud y el deseo. La intención de turismo de realidad virtual también se ve significativamente afectada por el interés en el turismo de realidad virtual y está mediada por la utilidad percibida y la facilidad de uso percibida, la actitud y el deseo. La facilidad de uso percibida y la utilidad percibida están significativamente relacionadas con el interés y determinan la actitud. La actitud influye tanto directa como indirectamente de manera significativa en la intención de turismo de realidad virtual a través del deseo de los usuarios, que media en la relación. A través del análisis de múltiples grupos, se encontró que la edad, la educación y el estado civil moderan la relación entre el deseo y la intención.

Desde el punto de vista teórico, este estudio es pionero en la creación de un marco que aúna AIDA, TAM e innovación personal para avanzar en la comprensión de la dinámica de adopción del turismo de realidad virtual y enriquecer la investigación turística. Desde el punto de vista de la gestión, ofrece una valiosa orientación sobre cómo orientar las comunicaciones y la tecnología para aumentar la participación del turismo de realidad virtual y presenta una hoja de ruta para los profesionales del sector.

Esta investigación aborda las lagunas identificadas en la literatura existente mediante la integración de TAM y AIDA con la innovación personal para analizar el proceso de la intención de los consumidores de turismo de realidad virtual, provocada por la innovación personal de los consumidores y el interés en el turismo de realidad virtual. El estudio pone de relieve importantes perspectivas de gestión tanto para los profesionales del sector turístico como para los investigadores académicos, que pueden ayudar en la toma de decisiones para promover el desarrollo del turismo de realidad virtual.

Generative conversational artificial intelligence (AI) demonstrates powerful conversational skills for general tasks but requires customization for specific tasks. The quality of a custom generative conversational AI highly depends on users’ guidance, which has not been studied by previous research. This study uses social exchange theory to examine how generative conversational AI’s cognitive and emotional conversational skills affect users’ guidance through different types of user engagement, and how these effects are moderated by users’ relationship norm orientation.

Based on data collected from 589 actual users using a two-wave survey, this study employed partial least squares structural equation modeling to analyze the proposed hypotheses. Additional analyses were performed to test the robustness of our research model and results.

The results reveal that cognitive conversational skills (i.e. tailored and creative responses) positively affected cognitive and emotional engagement. However, understanding emotion influenced cognitive engagement but not emotional engagement, and empathic concern influenced emotional engagement but not cognitive engagement. In addition, cognitive and emotional engagement positively affected users’ guidance. Further, relationship norm orientation moderated some of these effects such that the impact of user engagement on user guidance was stronger for communal-oriented users than for exchange-oriented users.

First, drawing on social exchange theory, this study empirically examined the drivers of users’ guidance in the context of generative conversational AI, which may enrich the user guidance literature. Second, this study revealed the moderating role of relationship norm orientation in influencing the effect of user engagement on users’ guidance. The findings will deepen our understanding of users’ guidance. Third, the findings provide practical guidelines for designing generative conversational AI from a general AI to a custom AI.

The purpose of this paper is to improve the mechanical and tribological properties of Si₃N₄ ceramics and to make the application of Si₃N₄ ceramics as tribological materials more extensive.

Si₃N₄-based composite ceramics (SN-2L) containing nitrogen-doped graphene quantum dots (N-GQDs) were prepared by hot press sintering process through adding 2 Wt.% nanolignin as precursor to the Si₃N₄ matrix, and the dry friction and wear behaviors of Si₃N₄-based composite against TC4 disc were performed at the different loads by using pin-on-disc tester.

The friction coefficients and wear rates of SN-2L composite against TC4 were significantly lower than those of the single-phase Si₃N₄ against TC4 at the load range from 15 to 45 N. At higher load of 45 N, SN-2L/TC4 pair presented the lowest friction coefficient of 0.25, and the wear rates of the pins and discs were as low as 1.76 × 10⁻⁶ and 2.59 × 10⁻⁴mm³/N·m. The low friction and wear behavior could be attributed to the detachment of N-GQDs from the ceramic matrix to the worn surface at the load of 30 N or higher, and then an effective lubricating film containing N-GQDs, SiO₂, TiO₂ and Al₂SiO₅ formed in the worn surface. While, at the same test condition, the friction coefficient of the single-phase Si₃N₄ against TC4 was at a range from 0.45 to 0.58. The spalling and cracking morphology formed on the worn surface of single-phase Si3N4, and the wear mechanism was mainly dominated by adhesive and abrasive wear.

Overall, a high-performance green ceramic composite was prepared, and the composite had a good potential for application in engineering tribology fields (such as aerospace bearings).

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0161/

The impact of environmental regulations on ecological innovation is a contested issue in current research. However, there is no uniform consensus on existing conclusions. It is commonly accepted among scholars that external environment and organizational characteristics are key factors affecting ecological innovation. However, these are often analyzed in isolation, without consideration of the interaction between leadership and external environment. So this study aims to explore the impact of environmental regulation on ecological innovation by combining internal and external factors.

Based on institutional theory and leadership theory, this paper takes environmental regulation as the independent variable, environmental leadership as the intermediary variable and intellectual property protection level as the regulating variable to explore the impact mechanism of environmental regulation on ecological innovation.

The findings indicate an inverted U-shaped relationship between environmental regulation and ecological innovation. Additionally, there is a positive correlation between environmental leadership and intellectual property protection level with ecological innovation. Furthermore, environmental leadership partially mediates the relationship between environmental regulation and ecological innovation. However, the level of intellectual property protection does not have a significant moderating effect on the relationship between environmental leadership and ecological innovation.

This paper proposes suggestions for regional ecological innovation based on the current policy and research situation to promote its development.

This paper proposes a solution for recognizing human faces under mask-wearing. The lower part of human face is occluded and could not be used in the learning process of face recognition. So, the proposed solution is developed to recognize human faces on any available facial components which could be varied depending on wearing or not wearing a mask.

The proposed solution is developed based on the FaceNet framework, aiming to modify the existing facial recognition model to improve the performance of both scenarios of mask-wearing and without mask-wearing. Then, simulated masked-face images are computed on top of the original face images, to be used in the learning process of face recognition. In addition, feature heatmaps are also drawn out to visualize majority of parts of facial images that are significant in recognizing faces under mask-wearing.

The proposed method is validated using several scenarios of experiments. The result shows an outstanding accuracy of 99.2% on a scenario of mask-wearing faces. The feature heatmaps also show that non-occluded components including eyes and nose become more significant for recognizing human faces, when compared with the lower part of human faces which could be occluded under masks.

The convolutional neural network based solution is tuned up for recognizing human faces under a scenario of mask-wearing. The simulated masks on original face images are augmented for training the face recognition model. The heatmaps are then computed to prove that features generated from the top half of face images are correctly chosen for the face recognition.

This paper aims to systematically review the application of artificial intelligence (AI) in the tourism industry. By integrating human–computer interaction, machine learning, big data and other relevant technologies, the study establishes a comprehensive research framework that explores the systematic connections between AI and various facets of tourism.

This paper conducts a keyword co-occurrence analysis of 4,048 articles related to AI in tourism. The analysis identifies and classifies dominant topics, which are further refined through thematic literature review and manual coding for detailed discussion.

The analysis reveals five main topics: AI’s impact on tourist experience, AI in tourism marketing and prediction, AI in destination management, AI’s role in tourism enterprises and AI integration in strategic and regulatory framework. Each topic is reviewed to construct an integrated discussion that maps the current landscape and suggests directions for future research.

This paper transcends the fragmented discourse commonly found in the literature by establishing a unified framework that not only enhances understanding of the existing methodologies, theories and applications of AI in tourism but also identifies critical areas for breakthroughs, aiming to inspire a more humane and sustainable integration of AI in the tourism industry.

本文旨在系统回顾人工智能（AI）在旅游业中的应用。通过整合人机交互、机器学习、大数据和其他相关技术, 本研究建立了一个全面的研究框架, 探索人工智能与旅游业各方面之间的系统联系。

本文对4048篇与旅游业人工智能相关的文章进行了关键词共现分析。分析确定了主要议题并对其进行了分类, 然后通过主题文献梳理和手动编码对其进行了进一步完善, 以便进行详细讨论。

分析揭示了五个主要主题：人工智能与旅游体验、人工智能与旅游营销和预测、人工智能与目的地管理、人工智能与旅游企业, 以及人工智能在战略和监管框架中的整合。每个主题都进行了回顾, 以构建一个综合讨论, 勾勒出当前的研究格局, 并提出了未来的研究方向。

研究力图突破目前关于旅游与人工智能的碎片化讨论, 建立了一个统一的框架, 旨在加强对旅游业中人工智能现有方法、理论和应用的理解, 还点明了需要突破的关键领域, 以助力旅游业与人工智能共同创造更加人性化和可持续发展的前景。

Este artículo pretende revisar sistemáticamente la aplicación de la inteligencia artificial (IA) en el sector turístico. Mediante la integración de la interacción humano-ordenador, el aprendizaje automático, big data y otras tecnologías relevantes, el estudio establece un marco de investigación exhaustivo que explora las conexiones sistemáticas entre la IA y diversas facetas del turismo.

Este trabajo realiza un análisis de co-ocurrencia de palabras clave de 4.048 artículos relacionados con la IA en el turismo. El análisis identifica y clasifica los temas dominantes, sobre los que se profundiza mediante una revisión temática de la literatura y una codificación manual para su discusión detallada.

El análisis presenta cinco temas principales: El impacto de la IA en la experiencia turística, la IA en el marketing y la predicción turística, la IA en la gestión de destinos, el papel de la IA en las empresas turísticas y la integración de la IA en el marco estratégico y normativo. Cada tema se revisa para construir un debate integrado que trace el panorama actual y sugiera direcciones para futuras investigaciones.

Este artículo expande el análisis fragmentado que suele encontrarse en la bibliografía al establecer un marco unificado que no sólo mejora la comprensión de las metodologías, teorías y aplicaciones existentes de la IA en el turismo, sino que también identifica las áreas críticas para los avances, con el objetivo de inspirar una integración más humana y sostenible de la IA en la industria turística.

This study aims to unravel the complex coopetitive interactions in supply chains. It delves into the paradoxical relationship between cooperative and competitive interactions among supply chain entities, offering a comprehensive exploration of coopetition’s manifestations and management across various supply chain types.

The study uses a three-phase methodology, beginning with a scoping review to establish a theoretical framework, followed by a systematic literature review yielding 130 papers and concluding with correspondence analysis using similarity indexes. This approach facilitates a deep dive into the diverse aspects of coopetition, including its drivers, practices, outcomes and associated risks.

The research identifies three distinct types of coopetition in supply chains: technology-based, socially based and channel-based. These models are underscored by specific drivers and outcomes, with technology-based coopetition focusing on market competitiveness and operational capacity, socially based on trust and power dynamics and channel based on product characteristics. The study introduces five propositions for further investigation and provides a comprehensive typology of coopetition within supply chains.

The study’s findings are limited by the scope of the existing literature and the chosen academic databases. Future research should empirically validate the proposed coopetition configurations and propositions, exploring their applicability in other, less studied supply chains.

The study offers practitioners a valuable typology and framework to understand and manage coopetition in their respective supply chains. This typology serves as a decision-making tool for identifying suitable coopetition strategies and maximizing their benefits while mitigating associated risks.

This study stands out for its unique approach to categorizing coopetition in supply chains, offering a novel typology that goes beyond the manufacturer’s perspective. It fills a significant gap in the literature by providing a broad view of coopetition, considering various supply chain types and their respective coopetitive dynamics.

This paper examines the impact of green human resource management (GHRM) practices on employees’ pro-environmental behavior in Pakistan’s hospitality industry. It attempts to identify the critical success factors involved in promoting GHRM and pro-environmental behaviors at the workplace using Interpretive Structural Modeling (ISM) and cross-impact matrix multiplication applied to classification (MICMAC) approaches. Later, based on the ability-motivation-opportunity (AMO) model, the study also categorizes the identified critical factors into three categories: ability, motivation and opportunity.

The ISM approach was applied to determine the contextual relationship among the identified critical success factors responsible for promoting GHRM. MICMAC, a structural technique to analyze and validate the ISM-based model, was used to determine the autonomous, dependent, linkage and independent factors based on expert opinions and judgments. The goal was to determine the role of GHRM in transforming the pro-environmental behavior of employees.

The study’s findings show that the proper integration of effective GHRM practices significantly impacts pro-environmental employee behavior. The hierarchical model introduces innovation in the field of GHRM because ISM-based hierarchical models are flexible enough to include or exclude practices according to the green organizational objectives in the hospitality industry within the context of Pakistan. The results offer a comprehensive illustration of the importance of GHRM practices in facilitating, encouraging and promoting employees to take green initiatives and achieve business sustainability.

The study utilizes the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) technique to identify key success criteria for GHRM, while the innovative approaches of ISM and MICMAC techniques were used to investigate employee pro-environmental behaviors. This novel method gives GHRM research an analytical direction by providing an organized framework for evaluating the impact of GHRM initiatives on environmental outcomes. Additionally, by focusing on developed economies rather than emerging ones, our study within Pakistan’s hospitality sector fills a knowledge vacuum on the dynamics of GHRM in a developing nation.

This study highlights the significance of managers in the hospitality sector serving as role models for implementing GHRM practices to encourage pro environmental behavior among employees. Prioritizing green structural capital, establishing standard environmentally friendly criteria for hiring and evaluating prospective employees and initiating green projects to promote a psychologically green environment are some of the key recommendations. Improving environmental performance, employee satisfaction and loyalty in the hotel industry requires constant communication, training and employee participation in sustainability decision-making.

The GHRM practices have been extensively discussed by academics and researchers. However, there is a notable absence of discussion on the key factors that play a role in transforming employees’ attitudes and behaviors.