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The purpose of this paper is to evaluate the implementation of mobile learning in a nursing course at The Open University of Hong Kong, and identify the potentials of, and constraints on, introducing mobile technologies in the instructional design of nursing education. The paper also considers the pedagogical implications of the expansion of mobile learning in the field of nursing.

The research adopts a qualitative approach to obtain the students’ and teacher’s experiences, opinions, and expectations on mobile learning. Two focus groups with 20 student participants were conducted and an in-depth interview with the course teacher was arranged. The Framework for the Rational Analysis of Mobile Education (FRAME) model was used as the research framework to support data collection and analysis.

The aspects of device usability, interaction learning, and social technology as suggested in the FRAME model were partly fulfilled in the study. Mobile technology enhanced the portability and accessibility of learning information, and networking tools facilitated interaction among students and between students and the teacher. However, the readability of text was limited due to constraints on the user interface and screen size, and concerns over the reliability of learning content were also raised, given the abundance of unfiltered online information. The difficulty in updating the content of multimedia materials and sourcing videos of an appropriate level, together with the problem of device networking, also limited the usefulness of mobile learning. Attention should also be paid to the perceptual differences between students and the teacher on the nature and functions of mobile learning.

This empirical study provides a detailed evaluation of the delivery of mobile learning in a nursing course. The findings reveal the strengths and limitations of using mobile technologies to support the nursing education.

The purpose of this paper is to provide evidence for the motivations of SMEs for introducing the Living Wage (LW), focussing on retail as one specific sector. It develops understanding of the strategic benefits and challenges these employers face in balancing financial, ethical and social considerations in small businesses.

The study employed mixed methods: a survey and semi-structured interviews. The interviews are presented as part of three case studies.

Findings indicate that employers were, for the most part, motivated by personal ethics and beliefs about fair wages and social justice. They suggest that SME accrue benefits from LW accreditation such as reputational benefits and higher employee morale, but that there are also potential pitfalls of LW adoption related to pay structure and incentives. The sustainability of the LW emerged as an issue in terms of the long-term strategy and brand positioning of the companies involved.

The nature of the research was exploratory and thus the study only allows for limited generalisation. Recommended avenues for further research include gathering data from different levels of organisations and from different stakeholders.

This is the first paper to investigate the drivers for, and implementation of, the LW in SMEs. The specific characteristics of SMEs – their ethos, low visibility, reliance on trusting relationships and limited resources, among others – make the study of why and how they choose to implement the LW very interesting. This study is the first to gather and analyse data from SME retailers and wholesalers that have implemented the LW.

The flexibility of batch process enables its wide application in fine-chemical, pharmaceutical and semi-conductor industries, whilst its complexity necessitates control performance monitoring to ensure high operation efficiency. This paper proposes a data-driven approach to carry out controller performance monitoring within batch based on linear quadratic Gaussian (LQG) method.

A linear time-varying LQG method is proposed to obtain the joint covariance benchmark for the stochastic part of batch process input/output. From historical golden operation batch, linear time-varying (LTV) system and noise models are identified based on generalized observer Markov parameters realization.

Open/closed loop input and output data are applied to identify the process model as well as the disturbance model, both in Markov parameter form. Then the optimal covariance of joint input and output can be obtained by the LQG method. The Hotelling's Tˆ2 control chart can be established to monitor the controller.

(1) An observer Markov parameter approach to identify the time-varying process and noise models from both open and closed loop data, (2) a linear time-varying LQG optimal control law to obtain the optimal benchmark covariance of joint input and output and (3) a joint input and output multivariate control chart based on Hotelling's T² statistic for controller performance monitoring.

Rosewood, as the most internationally traded endangered species, is subject to a series of restrictive trade policies globally. China has historically been the largest importer of rosewood in the world. The fluctuation of China’s rosewood import prices will have a profound impact on the global rosewood trade pattern. This study, therefore, assessed the impact of restrictive trade policies on China’s rosewood import prices to explore the fluctuation rule of rosewood trade prices under restrictive policies.

The study built a partial equilibrium framework about the formation mechanism of rosewood import price bubbles under supply constraints. On this basis, with China’s daily import prices of major rosewood species, the generalized supremum augmented Dickey–Fuller (GSADF) and backward supremum augmented Dickey–Fuller (BSADF) tests were applied to explore the effect of restrictive trade policies on China’s rosewood import prices.

The empirical analysis revealed that there were multiple price bubbles for five of the seven rosewood species. The largest bubbles were always created before and after the deployment of supply constraints. The empirical results for the counterfactual examples implied that price bubbles would not have occurred if restrictive rosewood trade policies had not been implemented. The above findings indicated that these measures tended to trigger significant price bubbles in China’s rosewood imports.

The effect of restrictive rosewood trade policies on rosewood trade prices had not yet been explored in previous research studies. This study empirically analyzed the effect of restrictive trade policies on China’s rosewood import prices using econometric models.

Degradable mulch film (DMF) is a potential alternate to polyethylene (PE) mulching. In this regard, the purpose of this paper is to explore the effects and paths of natural disaster shock and risk aversion influencing farmers’ DMF adoption.

This research is conducted by collecting cross-sectional data of corn farmers in Zhangye, China. First, by using the Tobit model, the paper attempts to explore the effects of natural disaster shock and risk aversion influencing farmers’ DMF adoption. Second, IV-Tobit model is applied to deal with endogenous problems between risk aversion and DMF adoption. Additionally, the researchers used a moderating model to analyze feasible paths of natural disaster shock and risk aversion impacting farmers’ DMF adoption.

The outcomes show that natural disaster shock and risk aversion significantly and positively affect farmers’ DMF adoption. Though risk aversion plays a significant moderating effect in influencing farmers’ DMF adoption by natural disaster shock, the moderating effect has a serious disguising effect. By considering the heterogeneity of risk aversion, the paper further confirms that if the intensity of natural disaster shock is increased by one unit, the intensity of MDF adoption by farmers with high-risk aversion also tends to increase by 15.85%.

This study is the pioneer one, which is evaluating the intensity of farmers’ DMF adoption from adoption ratio, investment amount, labor input and adoption time. Additionally, the research provides important guidelines for policymakers to motivate medium and low-risk aversion farmers to adopt DMF.

Inscrutable machine learning (ML) models are part of increasingly many information systems. Understanding how these models behave, and what their output is based on, is a challenge for developers let alone non-technical end users.

The authors investigate how AI systems and their decisions ought to be explained for end users through a systematic literature review.

The authors’ synthesis of the literature suggests that AI system communication for end users has five high-level goals: (1) understandability, (2) trustworthiness, (3) transparency, (4) controllability and (5) fairness. The authors identified several design recommendations, such as offering personalized and on-demand explanations and focusing on the explainability of key functionalities instead of aiming to explain the whole system. There exists multiple trade-offs in AI system explanations, and there is no single best solution that fits all cases.

Based on the synthesis, the authors provide a design framework for explaining AI systems to end users. The study contributes to the work on AI governance by suggesting guidelines on how to make AI systems more understandable, fair, trustworthy, controllable and transparent.

This literature review brings together the literature on AI system communication and explainable AI (XAI) for end users. Building on previous academic literature on the topic, it provides synthesized insights, design recommendations and future research agenda.