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This study aims to investigate the influential factors driving customer-oriented constructive deviance (COCD) within the context of the tourism and hospitality industry. Specifically, the authors explore the role of moral emotions as mediators and moral disengagement as a moderator.

In Study 1, the participant pool consisted of 259 frontline service employees hailing from a diverse selection of 54 four- and five-star hotels. Study 2 took an alternative approach, using a scenario-based experiment with 212 participants.

The results reported that organizational injustice toward customers is positively related to other-condemning emotions and leads to COCD. The results also reported that perceived customer citizenship behavior (CCB) positively relates to other-praising emotions, resulting in constructive deviance from customer-oriented. Moreover, these findings support moral emotions and moral disengagement interactions.

This paper shows that an organization’s injustice of external parties, such as customers, may provide important information that employees use to shape their moral emotions (e.g. other condemning emotions) and behavior toward the organization (e.g. COCD). Furthermore, this study confirms that perceived customer citizenship behavior contributes to COCD through other-praising emotions.

This paper aims to explore the determinants causing fake information proliferation on social media platforms and the challenges to control the diffusion of fake news phenomena.

The authors applied the systematic review methodology to conduct a synthetic analysis of 37 articles published in peer-reviewed journals retrieved from 13 scholarly databases.

The findings of the study displayed that dissatisfaction, behavior modifications, trending practices to viral fake stories, natural inclination toward negativity and political purposes were the key determinants that led individuals to believe in fake news shared on digital media. The study also identified challenges being faced by people to control the spread of fake news on social networking websites. Key challenges included individual autonomy, the fast-paced social media ecosystem, fake accounts on social media, cutting-edge technologies, disparities and lack of media literacy.

The study has theoretical contributions through valuable addition to the body of existing literature and practical implications for policymakers to construct such policies that might prove successful antidote to stop the fake news cancer spreading everywhere via digital media. The study has also offered a framework to stop the diffusion of fake news.

The ancient settlements of the M'zab Valley in Algeria, called ksour, are still being used by local inhabitants a thousand years after their construction. The main objective of this study was to discover why, despite the formation of new residential areas, these settlements have been able to survive and maintain their original functions.

The authors used the concept of living heritage sites as an analytical framework. The field data were collected through semi-structured interviews and analyzed through qualitative content analysis.

This study revealed that the reasons for the survival of these settlements were cultural and social rather than physical. Four main factors play a role in the survival of these settlements: (1) solidarity and unity among the inhabitants, (2) built environment as an ancestral heritage and a symbol of identity, (3) comfort and convenience in ksour and (4) social control and adherence to tradition. However, some concerns have arisen in recent decades that may endanger the viability of these settlements in the future, requiring more attention from the government.

While previous studies on urban heritage and World Heritage Sites (WHSs) have mainly focused on tourism development and conservation issues, this paper emphasized a less-studied aspect of these sites, i.e. continuity and sustainability. All previous studies on the WHSs of the M'zab Valley have addressed the traditional architecture and the climatic design of houses without sufficiently addressing other factors that have contributed to the sustainability and resilience of these settlements.

The purpose of this study is to identify the relationship between artificial intelligence (AI) and fake news detection. It also intended to explore the negative effects of fake news on society and to find out trending techniques for fake news detection.

“Preferred Reporting Items for the Systematic Review and Meta-Analysis” were applied as a research methodology for conducting the study. Twenty-five peer-reviewed, most relevant core studies were included to carry out a systematic literature review.

Findings illustrated that AI has a strong positive relationship with the detection of fake news. The study displayed that fake news caused emotional problems, threats to important institutions of the state and a bad impact on culture. Results of the study also revealed that big data analytics, fact-checking websites, automatic detection tools and digital literacy proved fruitful in identifying fake news.

The study offers theoretical implications for the researchers to further explore the area of AI in relation to fake news detection. It also provides managerial implications for educationists, IT experts and policymakers. This study is an important benchmark to control the generation and dissemination of fake news on social media platforms.

This study aims to investigate the current practices being implemented against the dissemination of fake online news, identify the relationship of new media literacy (NML) with fake news epidemic control and find out the challenges in identifying valid sources of information.

To accomplish constructed objectives of this study, a systematic literature review (SLR) was conducted. The authors carried out the “Preferred Reporting Items for the Systematic Review and Meta-analysis” guidelines as a research methodology. The data were retrieved from ten world’s leading digital databases and online tools. A total of 25 key studies published in impact factor (IF) journals were included for systematic review vis-à-vis standard approaches.

This study revealed trending practices to control fake news consisted of critical information literacy, civic education, new thinking patterns, fact-checkers, automatic fake news detection tools, employment of ethical norms and deep learning via neural networks. Results of the synthesized studies revealed that media literacy, web literacy, digital literation, social media literacy skills and NML assisted acted as frontline soldiers in combating the fake news war. The findings of this research also exhibited different challenges to control fake news perils.

This study provides pertinent theoretical contributions in the body of existing knowledge through the addition of valuable literature by conducting in-depth systematic review of 25 IF articles on a need-based topic.

This scholarly contribution is fruitful and practically productive for the policymakers belonging to different spectrums to effectively control web-based fake news epidemic.

This intellectual piece is a benchmark to address fake news calamities to save the social system and to educate citizens from harms of false online stories on social networking websites.

This study vivifies new vistas via a reinvigorated outlook to address fake news perils embedded in dynamic, rigorous and heuristic strategies for redefining a predetermined set of social values.

This study aims to highlight the dimensions of the rivalry over the regional role between two regional powers in the Middle East, and the impact of local, regional and international pressures of the Syrian crisis on the role performance of the competing forces.

The study is based on using “the role approach” as an analytical frame to benefit by the application of the theory of role. This approach allows the possibility of linking various analytical levels, both in clarifying the relationship between internal and external factors and showing the interaction between elements of perception, abilities and behavior.

The international pressures shall remain governing the frame of competition among the roles of the regional powers, through determining the course of competition and its direct impact on its results.

This study examines the phenomenon of regional rivalry between two distinct and competing regional powers, in a turbulent environment in the wake of the Arab Spring crises, which created opportunities and challenges for regional powers, especially in Syria, where it intersected with the interests and policies of major and regional powers.

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。

Spoken service language is critical for service experiences and human welfare in many service settings. However, little is known about how spoken service language can enhance customer well-being in transformative service contexts. This paper explores spoken service language and well-being for customers experiencing vulnerability in a transformative service context, informed by an empirical account of the human welfare service of residential aged care.

Situated within transformative service research (TSR), this study was guided by a theoretical framework of service language and adopts a strengths-based approach to customer experiences of vulnerability. A qualitative multiple case study methodology was applied to explore carers’ perspectives on spoken service language and well-being from three residential aged care homes in Australia.

The findings demonstrate five spoken service language practices and four principles of spoken service language for well-being that co-create customer well-being and support the alleviation of customer experiences of vulnerability. Conceptualised as transformative spoken service language, the spoken service language practices and principles collectively recognise, support and leverage residents’ capabilities and uplift customer well-being, by enacting a process of mattering highly salient to transformative service contexts.

This study is the first to conceptualise how employee spoken service language can be used to support customer well-being and enhance transformative value for customers experiencing vulnerability to align with the goals of TSR. Practically, the study advocates for a greater awareness and more considered use of transformative spoken service language in human welfare and other transformative service contexts.

This study investigates the crucial link between sustainable practices and organizational development, focusing on sustainable knowledge management (SKM), green innovation (GI) and corporate sustainable development (CSD) in diverse Pakistani organizations.

This study employs a comprehensive research methodology involving advanced statistical techniques, such as confirmatory factor analysis, structural equation modeling and hierarchical linear modeling. These methods are instrumental in exploring the complex interrelationships between SKM, GI, moderating factors and CSD.

This research generates significant findings and actively contributes to sustainable development. The following sections (Sections 4 and 5) delve into the specific findings and in-depth discussions, shedding light on how industry regulation, organizational sustainability priorities, workplace culture collaboration and alignment between green culture and knowledge management practices influence the relationships between SKM, GI and CSD. These findings provide valuable insights for the research community and organizations striving for sustainability.

The study’s findings have practical implications for organizations seeking to enhance their sustainability efforts and embrace a socially and environmentally conscious approach to organizational growth.

This study contributes to the literature on sustainable practices and organizational development. Researchers and business people can learn a lot from it because it uses advanced econometric models in new ways and focuses on the link between knowledge management, GI and sustainable corporate development.

Jubail Industrial City is one of the largest industrial centers in the Middle East, offering potential opportunities for renewable energy generation. This research paper presents a comprehensive analysis of the wind resources in Jubail Industrial City and proposes the design of a smart grid-connected wind farm for this strategic location.

The study used wind data collected at three different heights above ground level – 10, 50 and 90 m – over four years from 2017 to 2020. Key parameters, such as average wind speeds (WS), predominant wind direction, Weibull shape, scale parameters and wind power density (WPD), were analyzed. The study used Windographer, an exclusive software program designed to evaluate wind resources.

The average WS at the respective heights were 3.07, 4.29 and 4.58 m/s. The predominant wind direction was from the north-west. The Weibull shape parameter (k) at the three heights was 1.77, 2.15 and 2.01, while the scale parameter (c) was 3.36, 4.88 and 5.33 m/s. The WPD values at different heights were 17.9, 48.8 and 59.3 W/m², respectively.

The findings suggest that Jubail Industrial City possesses favorable wind resources for wind energy generation. The proposed smart grid-connected wind farm design demonstrates the feasibility of harnessing wind power in the region, contributing to sustainable energy production and economic benefits.