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The pandemic has reinforced the need for revamping the healthcare service delivery systems around the world to meet the increased challenges of modern-day illnesses. The use of medical cyber–physical system (MCPS) in the healthcare is one of the means of transforming the landscape of the traditional healthcare service delivery system. The purpose of this study is to critically examine the impact of MCPS on the quality of healthcare service delivery.

This paper uses an evidence-based approach, the authors have conducted a systematic literature review to study the impact of MCPS on healthcare service delivery. Fifty-four articles were thematically examined to study the impact of MCPS on eight characteristics of the healthcare service delivery proposed by the world health organisation.

The study proposes support that MCPS will positively impact (1) comprehensiveness, (2) accessibility, (3) coverage, (4) continuity, (5) quality, (6) person-centredness, (7) coordination, (8) accountability and (9) efficiency dimension of the healthcare service delivery. The study further draws nine propositions to support the impact of MCPS on the healthcare service delivery.

This study can be used by stakeholders as a guide point while using MCPS in healthcare service delivery systems. Besides, healthcare managers can use this study to understand the performance of their healthcare system. This study can further be used for designing effective strategies for deploying MCPS to be effective and efficient in each of the dimensions of healthcare service delivery.

The previous studies have focussed on technology aspects of MCPS and none of them critically analysed the impact on healthcare service delivery. This is the first literature review carried out to understand the impact of MCPS on the nine dimensions of healthcare service delivery proposed by WHO. This study provides improved thematic awareness of the resulting body of knowledge, allowing the field of MCPS and healthcare service delivery to progress in a more informed and multidisciplinary manner.

In this research, the authors demonstrate the advantage of reinforcement learning (RL) based intrusion detection systems (IDS) to solve very complex problems (e.g. selecting input features, considering scarce resources and constrains) that cannot be solved by classical machine learning. The authors include a comparative study to build intrusion detection based on statistical machine learning and representational learning, using knowledge discovery in databases (KDD) Cup99 and Installation Support Center of Expertise (ISCX) 2012.

The methodology applies a data analytics approach, consisting of data exploration and machine learning model training and evaluation. To build a network-based intrusion detection system, the authors apply dueling double deep Q-networks architecture enabled with costly features, k-nearest neighbors (K-NN), support-vector machines (SVM) and convolution neural networks (CNN).

Machine learning-based intrusion detection are trained on historical datasets which lead to model drift and lack of generalization whereas RL is trained with data collected through interactions. RL is bound to learn from its interactions with a stochastic environment in the absence of a training dataset whereas supervised learning simply learns from collected data and require less computational resources.

All machine learning models have achieved high accuracy values and performance. One potential reason is that both datasets are simulated, and not realistic. It was not clear whether a validation was ever performed to show that data were collected from real network traffics.

The study provides guidelines to implement IDS with classical supervised learning, deep learning and RL.

The research applied the dueling double deep Q-networks architecture enabled with costly features to build network-based intrusion detection from network traffics. This research presents a comparative study of reinforcement-based instruction detection with counterparts built with statistical and representational machine learning.

The research identifies the predictors of Islamic mobile banking (IMB) smart services adoption and usage in Jordan.

Based on the Unified Theory of the Acceptance and Use of Technology (UTAUT) and the Unified Theory of the Acceptance and Use of Technology 2 (UTAUT2), an extended and modified model that encompasses perceived trust was developed. The sample comprised 358 customers from Islamic banks (IBs) in Jordan, and structural equation modelling was applied to examine data drawn from the sample.

The research framework presented 0.728% of the behavioural intention variance and 0.455% of the use behaviour. Results discovered that performance expectancy, perceived trust and hedonic motivation have significant relations with behavioural intention. The finding that effort expectancy has an insignificant effect and that social influence has a significant negative influence on behavioural intention was unexpected.

The research has successfully verified the effect of performance expectancy, perceived trust and hedonic motivation on the customer's intention to use IMB smart services. However, the research data findings are based on the cross-sectional design.

The outcomes hold implications for marketing strategy makers who are responsible for promoting IMB smart services in IBs.

This research presents a deeper insight into IMB adoption and use. The research employed UTAUT and UTAUT2 as the baseline model and incorporates perceived trust to estimate behavioural intention. To the best of the authors' knowledge, this could be the first inquiry that examines IMB smart services adoption and use in Jordan.

The aim of this paper is to investigate the role of the stakeholder's relationship with supply chain resilience (SCR) and organizational performance (OP) using the lens of stakeholder theory in the manufacturing and service industry. Investigating the supply chain community in Pakistan, this paper explores the relationship between SCR, OP and the stakeholder's relationship (including customers and suppliers).

A partial least square (PLS) – structural equation modeling (SEM) technique using SmartPLS 3.3.3 was used to test the hypotheses. Data were collected through a survey (questionnaire) completed by 202 supply chain representatives. All respondents were supply chain professionals working in different organizations in Pakistan.

The findings of the study revealed that supplier relationship (SR) and customer relationship (CR) have a positive and significant impact on SCR and a positive and significant relationship between SCR and OP. A positive and significant relationship between customer relationship and OP was also noted. The mediating role of SCR is also found positive and significant.

The outcomes of the study will help managers to strengthen SCR through relationship management. The study is also helpful to increase OP through stakeholder management.

This study empirically tests an inclusive model with a PLS-SEM technique where SCR plays a mediating role in the mechanism, which is crucial since the supplier and customer (stakeholder) relationship has been never tested to gauge the OP by positioning SCR as a mediator while using the lens of stakeholder theory.

The dropout rates of open e-learning platforms are often cited as high as 97%, with many users discontinuing their use after initial acceptance. This study aims to explore this anomaly through the lens of affordances theory, revealing design–reality gaps between users' diverse goals and the possibilities for action provided by an open IT artefact.

A six-month case study was undertaken to investigate the design implications of user-perceived affordances in an EU sustainability project which developed an open e-learning platform for citizens to improve their household energy efficiency. Thematic analysis was used to reveal the challenges of user continuance behaviour based on how an open IT artefact supports users in achieving individual goals (e.g. reducing energy consumption in the home) and collective goals (lessening the carbon footprint of society).

Based on the findings, the authors inductively reveal seven affordances related to open e-learning platforms: informing, assessment, synthesis, emphasis, clarity, learning pathway and goal-planning. The findings centre on users' perception of these affordances, and the extent to which the open IT artefact catered to the goals and constraints of diverse user groups. Open IT platform development is further discussed from an iterative and collaborative perspective in order to explore different possibilities for action.

The study contributes towards research on open IT artefact design by presenting key learnings on how the designers of e-learning platforms can bridge design–reality gaps through exploring affordance personalisation for diverse user groups. This can inform the design of open IT artefacts to help ensure that system features match the expectations and contextual constraints of users through clear action-oriented possibilities.