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The purpose of this paper is to study large deviations for the solution processes of a stochastic equation incorporated with the effects of nonlocal condition.

A weak convergence approach is adopted to establish the Laplace principle, which is same as the large deviation principle in a Polish space. The sufficient condition for any family of solutions to satisfy the Laplace principle formulated by Budhiraja and Dupuis is used in this work.

Freidlin–Wentzell type large deviation principle holds good for the solution processes of the stochastic functional integral equation with nonlocal condition.

The asymptotic exponential decay rate of the solution processes of the considered equation towards its deterministic counterpart can be estimated using the established results.

This study examines the moderating role of information sharing on the effect of lead-time management on the performance of firms in the Zimbabwean motor industry.

Data were collected using Likert-based structured questionnaires from a sample of 105 employees in Zimbabwe. In addition, Pearson Correlation, Linear Regression and Moderation Regression analysis were employed to test the relationship between study variables.

The study found that fixed lead time, preprocessing lead time, processing lead time and postprocessing lead time significantly influence the performance of firms in the motor industry. The results also demonstrate that information sharing moderates the effect of lead-time management on firm performance in the motor industry.

Firms in the motor industry should establish long-term relationships with their suppliers and implement effective communication channels for timely and frequent information exchange regarding production schedules, inventory levels, quality standards and potential disruptions.

The current study aims to contribute to the scientific discourse on lead-time management, information sharing and performance in the motor industry. Furthermore, it extends knowledge on the performance of the motor industry in the African region.

The growth of China’s economy during the 1990s has both shaped and reflected changes in the span and function of the country’s shipping connections both within Asia and with the rest of the world. Although sea-land developments within China have been studied, less attention has been paid to the wider global implications stemming from the transformation of the country’s maritime geography during a decade of further market reforms and greater integration into the world economy. Consequently, there is a need to comprehend how China’s state-owned shipping industry has been reorganized during the 1990s to meet the new requirements, with special reference to the country’s liner shipping connections between and within Asia respectively. More purposely, these topics are addressed by examining changes in the organization, approach and set of connections of the state-owned China Ocean Shipping (Group) Company (Cosco) and its post-1993 offshoot COSCO Container Lines Company Ltd (Coscon). This review provides a springboard for a detailed analysis of shifts in both extra- and intra-Asian shipping patterns between 1990 and 2000 and consideration of their strategic implications. Finally, short-sea shipping is defined and the phenomenon’s operational strengths and weaknesses discussed.

Air traffic controllers (ATCOs) play a fundamental role in the safe, orderly and efficient management of air traffic. In the interests of improving safety, it would be beneficial to know what the workload thresholds are that permit ATCOs to carry out their functions safely and efficiently. The purpose of this paper is to present the development of a simulation platform to be able to validate an affective-cognitive performance methodology based on neurophysiological factors applied to ATCOs, to define the said thresholds.

The process followed in setting up the simulation platform is explained, with particular emphasis on the design of the program of exercises. The tools designed to obtain additional information on the actions of ATCOs and how their workload will be evaluated are also explained.

To establish the desired methodology, a series of exercises has been designed to be simulated. This paper describes the project development framework and validates it, taking preliminary results as a reference. The validation of the framework justifies further study to extend the preliminary results.

This paper describes the first part of the project only, i.e. the definition of the problem and a proposed methodology to arrive at a workable solution. Further work will concentrate on carrying out a program of simulations and subsequent detailed analysis of the data obtained, based on the conclusions drawn from the preliminary results presented.

The methodology will be an important tool from the point of view of safety and the work carried out by ATCOs. This first phase is crucial as it provides a solid foundation for later stages.

Service robots are increasingly prevalent in the hospitality industry. While studies have explored the concept of service robot risk awareness (SRRA) – an employee’s perception of service robots posing a threat to human labor – the impact of SRRA on robot abuse and its emotional mechanism through which it affects employees remains unclear. This research leverages emotional appraisal theory to investigate the mediating role of fear of robots in the relationship between SRRA and robot abuse. Additionally, considering the influential role of leadership in shaping emotional appraisal, this study aims to examine the moderating impact of transformational leadership.

To test the proposed model, time-lagged survey data were collected from 283 employees working under 54 leaders in 18 hotels in China. The model was analyzed using multilevel modeling in Mplus 7.3.

At the individual level, SRRA indirectly increases robot abuse through the mediation of fear of robots. However, there is a cross-level moderation: the indirect relationship is alleviated when leaders exhibit high levels of transformational leadership.

This study pioneers the concept of robot abuse in hospitality and tourism settings. It extends emotional appraisal theory by highlighting the significant mediating role played by fear of robots. Furthermore, demonstrating how transformational leadership can mitigate the effects of SRRA offers valuable insights for leadership selection and training to facilitate the successful implementation of service robots.

服务机器人在酒店业中日益普及。虽然研究已探讨了服务机器人风险意识（SRRA）的概念——即员工对服务机器人构成对人力劳动的威胁感知, 但SRRA对辱虐机器人及其对员工的情绪机制的影响仍不清楚。本研究利用情绪评估理论调查了恐惧对SRRA与机器人滥用之间关系的中介作用。此外, 考虑到领导在塑造情绪评估中的重要作用, 本研究还考察了变革型领导力的调节影响。

为了测试提出的模型, 收集了来自中国18家酒店中54位领导下的283名员工的时滞调查数据。该模型使用Mplus 7.3中的多层建模进行分析。

在个体水平上, SRRA通过恐惧对机器人的中介作用间接增加了辱虐机器人。然而, 研究发现跨层次调节变量：当领导展现出较高水平的变革型领导力时, 间接关系得到缓解。

本研究首创了服务在酒店和旅游领域的辱虐机器人行为概念。它通过突出恐惧对机器人的重要中介作用, 扩展了情绪评估理论。此外, 展示了变革型领导如何缓解SRRA的影响, 为领导选聘和培训提供了有价值的见解, 促进了服务机器人的成功实施。

Artificial intelligence (AI) has gained significant momentum in recent years. Among AI-infused systems, one prominent application is context-aware systems. Although the fusion of AI and context awareness has given birth to personalized and timely AI-powered context-aware systems, several challenges still remain. Given the “black box” nature of AI, the authors propose that human–AI collaboration is essential for AI-powered context-aware services to eliminate uncertainty and evolve. To this end, this study aims to advance a research agenda for facilitators and outcomes of human–AI collaboration in AI-powered context-aware services.

Synthesizing the extant literature on AI and context awareness, the authors advance a theoretical framework that not only differentiates among the three phases of AI-powered context-aware services (i.e. context acquisition, context interpretation and context application) but also outlines plausible research directions for each stage.

The authors delve into the role of human–AI collaboration and derive future research questions from two directions, namely, the effects of AI-powered context-aware services design on human–AI collaboration and the impact of human–AI collaboration.

This study contributes to the extant literature by identifying knowledge gaps in human–AI collaboration for AI-powered context-aware services and putting forth research directions accordingly. In turn, their proposed framework yields actionable guidance for AI-powered context-aware service designers and practitioners.

This study examined the influence of social media use on graduateness and the employability of exit students in South Africa.

The study used quantitative and descriptive research designs to test the proposed hypotheses. An online survey was used to collect the data from a study sample. A sample of 411 respondents was received, with structural equation modelling (SEM) being used to assess the model fit.

The study found that the direct effect of social media use on graduateness skills is significant. Secondly, the direct effect of graduateness skills on perceived employability is also significant. The results also showed existence of support for the mediation of graduateness skills on the relationship between social media use and perceived employability.

The study provides empirical evidence to the proposed model and infers the potential role of social media in addressing issues related to graduateness and the employability of exit students.

In addressing the challenge of unemployment, the use of social media can potentially aid in matters of skills acquisition.

The results demonstrate how technology through the use of social media potentially fits within enhancing graduateness and employability skills.

This research explores the impact of the locally grown strategies for learning support, as a positive deviance (PD) study, during the COVID-19 pandemic in rural Uganda.

The researchers employed a randomized control trial (RCT) as an original design whereby 50 schools received a full package of SMS and WhatsApp peer groups of head teachers, 50 schools received SMS only and another 50 served as a control group. As an analytical method, this study adopted a difference-in-difference (DID) model to analyze the impact of the radio talk shows promoted through SMS followed by discussion among WhatsApp peer groups. The data collected in June 2021 and February 2022 were used due to the COVID-19-related data limitation of the baseline survey collected in 2019.

The authors found that the local radio talk shows as a PD intervention had a humble impact on preventing pupils’ dropout during the school closures for two years in Uganda. However, the authors did not obtain a significant result on the impact of the PD intervention on pedagogical support or learning outcomes at the school level. The authors also found that the pupils have significantly dropped their level of proficiencies in literacy and numeracy during the pandemic.

The findings could be of value for the leaders, educators and policymakers to understand the most recent update of learning situation in Uganda and the potential impact of locally grown strategies for learning which does not require external inputs.