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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.

This project aims to optimise a secondary agricultural company’s reporting and data lifecycle by providing self-help business intelligence at an optimal price point for all business users.

A design for Lean Six Sigma approach utilising the define, measure analyse, design and verify methodology was utilised to design a new reporting and data product lifecycle.

The study found that this approach allowed a very structured delivery of a complex program. The various tools used assisted greatly in delivering results while balancing the needs of the team.

This study demonstrates how improving data analysis and enhanced intelligence reporting in agribusinesses enable better decision making and thus improves efficiencies so that the agribusiness can leverage the learnings.

Improving data analysis increases efficiency and reduces agrifood food wastage thus improving sustainability and environmental impacts.

This paper proposes creating a standardised approach to deploying Six Sigma methodology to correct both the data provisioning lifecycle and the subsequent business intelligence reporting lifecycle. It is the first study to look at process optimisation across the agricultural industry’s entire data and business intelligence lifecycle.

An understanding of the motivation of individual employees to adopt lean practices is fundamental to successful lean implementation. This study aims to investigate the adoption of lean practices and provides an analysis of the individual-level factors necessary for lean implementation. This study presents a method for assessing the impact of individual-level factors in a company deploying lean within a biopharmaceutical manufacturing subsidiary.

The case study explores the attitudes of individuals within a functionally structured organisation undergoing a lean implementation initiative. A quantitative data collection approach was used to capture data from employees in a medical device manufacturing organisation.

The study found that personality and affective organisational commitment positively affects an individual’s intention to adopt lean practices. Employees with greater levels of affective commitment are more likely to partake in lean-related practices. Individuals in functions that directly support the production process, as opposed to those in functions that indirectly support production, are more likely to participate in lean practices. Finally, individuals in supervisory roles are more likely to adopt lean practices than those in non-supervisory roles, and management should involve top performers in lean.

There is a paucity of case study research in the area of individual-level factors for lean practice adoption. The findings of this study offer practical guidance on individual-level factors for lean practice adoption and illuminate new avenues for future research. This analysis also makes a practical contribution to the literature. From a managerial perspective, understanding why certain employees are more willing to adopt lean practices contributes to an overall lean organisational readiness and implementation framework. This insight enables the development of carefully tailored communication and training programs for managing employee motivation for and receptivity to lean.

This article aims to optimise energy use and consumption by integrating Lean Six Sigma methodology with the ISO 50001 energy management system standard in an Irish dairy plant operation.

This work utilised Lean Six Sigma methodology to identify methods to measure and optimise energy consumption. The authors use a single descriptive case study in an Irish dairy as the methodology to explain how DMAIC was applied to reduce energy consumption.

The replacement of heavy oil with liquid natural gas in combination with the new design of steam boilers led to a CO₂ footprint reduction of almost 50%.

A further longitudinal study would be useful to measure and monitor the energy management system progress and carry out more case studies on LSS integration with energy management systems across the dairy industry.

The novelty of this study is the application of LSS in the dairy sector as an enabler of a greater energy-efficient facility, as well as the testing of the DMAIC approach to meet a key objective for ISO 50001 accreditation.

People with complex health conditions must often navigate landscapes of uncoordinated public, private and voluntary health-care providers to obtain the care they need. Complex health conditions frequently transcend the scope of typical health-care service systems. The purpose of this paper is to explore and characterize such unique assemblages of actors and services as “user-defined ecosystems”.

Building on literature on customer ecosystems, this paper introduces the concept of the user-defined ecosystem (UDE). Using an abductive approach, the authors apply the concept in an interpretive, qualitative study of ten families with special needs children.

This study uncovers complex UDEs, where families actively combine a broad range of services. These ecosystems are unique for each family and extend beyond the scope of designed service ecosystems. Thus, the families are forced to assume an active, coordinating role.

This paper shows how to identify ecosystems from the user’s point of view, based on the selected user unit (such as a family) and the focal value-creating function of the ecosystem for the user.

This paper highlights how service providers can support and adapt to UDEs and, thus, contribute to user value and well-being. This can be used to understand users’ perspectives on service and systems in health and social care.

This study develops the concept of the UDE, which represents a customer-focused perspective on actor ecosystems and contrasts it with a provider-focused and a distributed perspective on ecosystems. This study demonstrates the practical usefulness of the conceptualization and provides a foundation for further research on the user’s perspective on ecosystems.

Combining the goal-setting and job demands-resources (JD-R) theories, we examine how two project resources, collaborative project leadership and financial project resources, enhance high project performance in community-academic health partnerships.

With a sequential explanatory mixed-method research design, data were collected through a survey (N = 318) and semi-structured interviews (N = 21). A hypothesised three-path mediation model was tested using structural equation modelling with bootstrapping. Qualitative data were examined using thematic analysis.

Project workers’ hope, goal-commitment and -stress: (1) fully mediate the hypothesised relationship between highly collaborative project leadership and high project performance; and (2) partially mediate the relationship between financial project resources and high project performance. The qualitative data corroborate and deepen these findings, revealing the crucial role of hope as a cognitive-motivational facilitator in project workers’ ability to cope with challenges.

Project leaders should promote project workers’ goal commitment, reduce their goal stress and boost project performance by securing financial project resources or reinforcing workers’ hope, e.g. by fostering collaborative project leadership.

The findings contribute to the project management and JD-R literature by considering the joint effects of project workers’ hope and two commonly studied project resources (collaborative project leadership and financial project resources) on high project performance. Moreover, we demonstrate the importance of the goal-setting and JD-R theories for understanding complex health-promotion projects connecting academic to community work.

COVID-19 cases in Indonesia continue to increase and spread. This article aims to analyse the Indonesian government policies as a response in dealing with COVID-19.

This article is a narrative analysis with the approach of a systematic literature review.

This article found that the Indonesian government responded slowly to the COVID-19 pandemic at the beginning of its spread in March 2020. The government then issued some policies such as physical distancing, large-scale social restriction (PSBB - Pembatasan Sosial Berskala Besar) and social safety net. These policies will only work if the society follows them. The society could be the key to success of those policies, either as the support or the obstacles.

This policy analysis with literature review, conducted from March to July 2020 in Indonesia, provides experiences and knowledge in how to respond to the dynamic problems of public policy in dealing with the COVID-19 outbreak, especially in the context of a developing country.

The novelty of the article lies in the unique policy response in a diverse society. It suggests that the policymakers should pay more attention to the society’s characteristics as well as the mitigation system as a preventive measure and risk management to make clear policy in the society.

The proposed model has been aimed to predict stock market signals by designing an accurate model. In this sense, the stock market is analysed by the technical analysis of Japanese Candlestick, which is combined by the following meta heuristic algorithms: support vector machine (SVM), meta-heuristic algorithms, particle swarm optimization (PSO), imperialist competition algorithm (ICA) and genetic algorithm (GA).

In addition, among the developed algorithms, the most effective one is chosen to determine probable sell and buy signals. Moreover, the authors have proposed comparative results to validate the designed model in this study with the same basic models of three articles in the past. Hence, PSO is used as a classification method to search the solution space absolutelyand with the high speed of running. In terms of the second model, SVM and ICA are examined by the time. Where the ICA is an improver for the SVM parameters. Finally, in the third model, SVM and GA are studied, where GA acts as optimizer and feature selection agent.

Results have been indicated that, the prediction accuracy of all new models are high for only six days, however, with respect to the confusion matrixes results, it is understood that the SVM-GA and SVM-ICA models have correctly predicted more sell signals, and the SCM-PSO model has correctly predicted more buy signals. However, SVM-ICA has shown better performance than other models considering executing the implemented models.

In this study, the authors to analyze the data the long length of time between the years 2013–2021, makes the input data analysis challenging. They must be changed with respect to the conditions.

In this study, two methods have been developed in a candlestick model, they are raw based and signal-based approaches which the hit rate is determined by the percentage of correct evaluations of the stock market for a 16-day period.

This paper aims to explore the pertinent issues, barriers and pitfalls of intergenerational communication in business families during their leadership succession period.

Building on relational leadership theory, the paper makes use of an action research approach using a qualitative single case study to investigate communication barriers and pitfalls in business transition.

Through action research, interventions were taken in the underlying case, which increased the consciousness, as well as the personal and social competencies of the business family. Thus, business families stuck in ambivalent entanglement understand their underlying motives and needs within the change process, get into closer contact with their emotional barriers and communication hindrances, which is a prerequisite for any change, and break the succession iceberg phenomenon.

Future research should undertake multiple case studies to validate and/or modify the qualitative methods used in this action research to increase the validity and generalizability of the findings.

Given the large number of business families in transition, our study shows the beneficial effects action research might have on business families’ communication behavior along a change process. The findings might help other business families to understand the value of action research for such underlying challenges and decrease communication barriers.

This is one of the few studies to have addressed intergenerational communication of business families using an action research approach.

This study explores how Lean was deployed in several hospitals in the Apulia region in Italy over 3.5 years.

An exploratory qualitative design was drawn up based on semi-structured interviews.

The drivers of Lean in hospitals were to increase patient satisfaction and improve workplace well-being by eliminating non-value-add waste. The participants highlighted three key elements of the pivotal implementation stages of Lean: introduction, spontaneous and informal dissemination and strategic level implementation and highlighted critical success and failure factors that emerged for each of these stages. During the introduction, training and coaching from an external consultant were among the most impactful factors in the success of pilot projects, while time constraints and the adoption of process analysis tools were the main barriers to implementation. The experiences of the Lean teams strongly influence the process of spontaneous dissemination aided by the celebration of project results and the commitment of the departmental hospital heads.

Lean culture can spread to allow many projects be conducted spontaneously, but the Lean paradigm can struggle to be adopted strategically. Lean in healthcare can fail because of the lack of alignment of Lean with leadership in healthcare and with their strategic vision, a lack of employees' project management skills and crucially the absence of a Lean steering committee.

The absence of managerial expertise and a will to support Lean implementation do not allow for systemic adoption of Lean. This is one of the first and largest long-term case studies on a Lean cross-regional multi-hospital application in healthcare.