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This study aims to propose a facilitating methodology for the application of Fuzzy FMEA (Failure Mode and Effect Analysis), comparing the traditional approach with fuzzy variations, supported by a case application in the aeronautical sector.

Based on experts' opinions in risk analysis within the aeronautical sector, rules governing the relationship between severity, occurrence, detection and risk factor were defined. This served as input for developing a fuzzyfied FMEA tool using the Matlab Fuzzy Logic Toolbox. The tool was applied to the sealing process in a company within the aeronautical sector, using triangular and trapezoidal membership functions, and the results were compared with the traditional FMEA approach.

The results of the comparative application of traditional FMEA and fuzzyfied FMEA using triangular and trapezoidal functions have yielded valuable insights into risk analysis. The findings indicated that fuzzyfied FMEA maintained coherence with the traditional analysis in identifying higher-risk effects, aligning with the prioritization of critical failure modes. Additionally, fuzzyfied FMEA allowed for a more refined prioritization by accounting for variations in each variable through fuzzy rules, thereby improving the accuracy of risk analysis and providing a more realistic representation of potential hazards. The application of the developed fuzzyfied FMEA approach showed promise in enhancing risk assessment in the aeronautical sector by considering uncertainties and offering a more detailed and context-specific analysis compared to conventional FMEA.

This study emphasizes the potential of fuzzyfied FMEA in enhancing risk assessment by accurately identifying critical failure modes and providing a more realistic representation of potential hazards. The application case reveals that the proposed tool can be integrated with expert knowledge to improve decision-making processes and risk mitigation strategies within the aeronautical industry. Due to its straightforward approach, this facilitating methodology could also prove beneficial in other industrial sectors.

This paper presents the development and application of a facilitating methodology for implementing Fuzzy FMEA, comparing it with the traditional approach and incorporating variations using triangular and trapezoidal functions. This proposed methodology uses the Toolbox Fuzzy Logic of Matlab to create a fuzzyfied FMEA tool, enabling a more nuanced and context-specific risk analysis by considering uncertainties.

Artificial intelligence (AI) has sparked interest in various areas, including marketing. However, this exhilaration is being tempered by growing concerns about the moral and legal implications of using AI in marketing. Although previous research has revealed various ethical and legal issues, such as algorithmic discrimination and data privacy, there are no definitive answers. This paper aims to fill this gap by investigating AI’s ethical and legal concerns in marketing and suggesting feasible solutions.

The paper synthesises information from academic articles, industry reports, case studies and legal documents through a thematic literature review. A qualitative analysis approach categorises and interprets ethical and legal challenges and proposes potential solutions.

The findings of this paper raise concerns about ethical and legal challenges related to AI in the marketing area. Ethical concerns related to discrimination, bias, manipulation, job displacement, absence of social interaction, cybersecurity, unintended consequences, environmental impact, privacy and legal issues such as consumer security, responsibility, liability, brand protection, competition law, agreements, data protection, consumer protection and intellectual property rights are discussed in the paper, and their potential solutions are discussed.

Notwithstanding the interesting insights gathered from this investigation of the ethical and legal consequences of AI in marketing, it is important to recognise the limits of this research. Initially, the focus of this study is confined to a review of the most important ethical and legal issues pertaining to AI in marketing. Additional possible repercussions, such as those associated with intellectual property, contracts and licencing, should be investigated more deeply in future studies. Despite the fact that this study gives various answers and best practices for tackling the stated ethical and legal concerns, the viability and efficacy of these solutions may differ depending on the context and industry. Thus, more research and case studies are required to evaluate the applicability and efficacy of these solutions in other circumstances. This research is mostly based on a literature review and may not represent the experiences or opinions of all stakeholders engaged in AI-powered marketing. Further study might involve interviews or surveys with marketing professionals, customers and other key stakeholders to offer a full knowledge of the practical difficulties and solutions. Because of the rapid speed of technical progress, AI’s ethical and regulatory ramifications in marketing are continually increasing. Consequently, this work should be a springboard for more research and continuing conversations on this subject.

This study’s findings have several practical implications for marketing professionals. Emphasising openness and explainability: Marketing professionals should prioritise transparency in their use of AI, ensuring that customers are fully informed about data collection and utilisation for targeted advertising. By promoting openness and explainability, marketers can foster customer trust and avoid the negative consequences of a lack of transparency. Establishing ethical guidelines: Marketing professionals need to develop ethical rules for the creation and implementation of AI-powered marketing strategies. Adhering to ethical principles ensures compliance with legal norms and aligns with the organisation’s values and ideals. Investing in bias detection tools and privacy-enhancing technology: To mitigate risks associated with AI in marketing, marketers should allocate resources to develop and implement bias detection tools and privacy-enhancing technology. These tools can identify and address biases in AI algorithms, safeguard consumer privacy and extract valuable insights from consumer data.

This study’s social implications emphasise the need for a comprehensive approach to address the ethical and legal challenges of AI in marketing. This includes adopting a responsible innovation framework, promoting ethical leadership, using ethical decision-making frameworks and conducting multidisciplinary research. By incorporating these approaches, marketers can navigate the complexities of AI in marketing responsibly, foster an ethical organisational culture, make informed ethical decisions and develop effective solutions. Such practices promote public trust, ensure equitable distribution of benefits and risk, and mitigate potential negative social consequences associated with AI in marketing.

To the best of the authors’ knowledge, this paper is among the first to explore potential solutions comprehensively. This paper provides a nuanced understanding of the challenges by using a multidisciplinary framework and synthesising various sources. It contributes valuable insights for academia and industry.

Since 2017, China's digital economy has accounted for more than 30% of the country's GDP. The digital economy has become the main driving force of China's economic development. Moreover, the digital economy has also changed the traditional modes of production and distribution between urban and rural areas. This paper aims to explore the influential mechanism of digital economy infrastructure (DEI) on the urban-rural income gap (URIG).

By analyzing the theoretical model of the URIG, this paper constructs a theoretical analysis framework and clarifies the key roles of rural land circulation (RLC) and resident population urbanization (RPU) in the relationship between DEI and the URIG.

The DEI can effectively reduce the URIG; the regression coefficient (RC) was −0.109. The reduction effect is mainly reflected in: 1) the wage income gap between urban and rural residents (RC = −0.128) and 2) the net property income gap of urban and rural residents (RC = −0.321). Also, for the spatial spillover effect, the path effect of “DEI – RLC – URIG” is almost equal to the path effect of “DEI – RPU – URIG”; for the local effect, the path effect of the former is far smaller than the latter. Moreover, when the RPU reaches the threshold of 86.29%, the DEI will expand the URIG (RC = 0.201).

This paper proposes a theoretical framework for the impact of DEI on the URIG, explores the mechanism of RLC and RPU in the DEI and URIG and enriches the theory of traditional research on URIG.

The purpose of this study is to examine the rostering practices and work experiences of medical scientists at four health services in the Australian public healthcare sector. There are over 16,000 medical scientists (AIHW, 2019) in Australia responsible for carrying out pathology testing to help save the lives of thousands of patients every day. However, there are systemic shortages of medical scientists largely due to erratic rostering practices and workload issues. The purpose of this paper is to integrate evidence-based human resource management (EBHRM), the LAMP model and HR analytics to enhance line manager decision-making on rostering to support the wellbeing of medical scientists.

Using a qualitative methodological approach, the authors conducted 21 semi-structured interviews with managers/directors and nine focus groups with 53 medical scientists, making a total 74 participants from four large public hospitals in Australia.

Across four health services, manual systems of rostering and management decisions do not meet the requirements of the enterprise agreement (EA) and impact negatively on the wellbeing of medical scientists in pathology services. The authors found no evidence of the systematic approach of the organisations and line managers to implement the LAMP model to understand the root causes of rostering challenges and negative impact on employees. Moreover, there was no evidence of sophisticated use of HR analytics or EBHRM to support line managers' decision-making regarding mitigation of rostering related challenges such as absenteeism and employee turnover.

The authors contribute to HRM theory by integrating EBHRM, the LAMP model (Boudreau and Ramstad, 2007) and HR analytics to inform line management decision-making. The authors advance understandings of how EBHRM incorporating the LAMP model and HR analytics can provide a systematic and robust process for line managers to make informed decisions underpinned by data.

This study aims to deepen the understanding of the challenges and implications entailed by deploying mobile clinics in conflict zones to reach populations affected by violence and cut off from health-care services.

This research combines an integrated literature review and an instrumental case study. The literature review comprises two targeted reviews to provide insights: one on conflict zones and one on mobile clinics. The case study describes the process and challenges faced throughout a mobile clinic deployment during and after the Iraq War. The data was gathered using mixed methods over a two-year period (2017–2018).

Armed conflicts directly impact the populations’ health and access to health care. Mobile clinic deployments are often used and recommended to provide health-care access to vulnerable populations cut off from health-care services. However, there is a dearth of peer-reviewed literature documenting decision support tools for mobile clinic deployments.

This study highlights the gaps in the literature and provides direction for future research to support the development of valuable insights and decision support tools for practitioners.

A new triage method, MBCE (Medical Bio Social Ethics), is presented with social justice, bio, and medical ethics for critical resource distribution during a pandemic. Ethical triage is a complex and challenging process that requires careful consideration of medical, social, cultural, and ethical factors to guide the decision-making process and ensure fair and transparent allocation of resources. When assigning priorities to patients, a clinician would evaluate each patient’s medical condition, age, comorbidities, and prognosis, as well as their cultural and social background and ethical factors.

A statistical analysis shows no interactions among the ethical triage factors. It implies the ethical components have no moderation effect; hence, each is independent. The result also points out that medical and bioethics may have an affinity for interactions. In such cases, there seem to be some ethical factors related to bio and medical ethics that are correlated. Therefore, the triage team should be careful in evaluating patient cases. The algorithm is explained with case histories of the selected patient. A group of triage nurses and general medical practitioners assists with the triage.

The MBCE triage algorithm aims to allocate scarce resources fairly and equitably. Another ethical principle in this triage algorithm is the principle of utility. In a pandemic, the principle of utility may require prioritizing patients with a higher likelihood of survival or requiring less medical care. The research presents a sensitivity analysis of a patient’s triage score to show the algorithm’s robustness. A weighted score of ethical factors combined with an assessment of triage factors combines multiple objectives to assign a fair triage score. These distinctive features of the algorithm are reasonably easy to implement and a new direction for the unbiased triage principle.

The idea is to make decisions about distributing and using scarce medical resources. Triage algorithms raise ethical issues, such as discrimination and justice, guiding medical ethics in treating patients with terminal diseases or comorbidity. One of the main ethical principles in triage algorithms is the principle of distributive justice.

Patient-centric exchanges, a major type of Health Information Exchange (HIE), empower patients to aggregate and manage their health information. This exchange model helps patients access, modify and share their medical information with multiple healthcare organizations. Although existing studies examine patient engagement, more research is required to investigate patients' attitudes and willingness to play an active role in patient-centered information exchange. The study's main objective is to develop a model based on the belief-attitude-intention paradigm to empirically examine the effects of patients' attitudes toward engagement in care on their willingness to participate in patient-centric HIE.

The authors conducted an online survey study to identify the antecedents and consequences of patients' attitudes toward engagement in care. To empirically test the research model, the authors collected data from a national sample (n = 357) of individuals in the United States. The data were analyzed using structural equation modeling (SEM).

The proposed model categorizes the antecedents to patients' attitudes toward engagement in patient-related and healthcare system factors. The results show that patient-related factors (perceived health literacy and perceived coping ability) and health system factors (perceived experience with the healthcare organization and perceived patient-provider interaction) significantly shape patient attitude toward care management engagement. The results indicate that patients' attitudes toward engaging in their healthcare significantly contribute to their willingness to participate in medical information sharing through patient-centric HIE initiatives. Moreover, the authors’ findings also demonstrate that the link between patient engagement and willingness to participate in HIE is stronger for individuals who perceive lower levels of privacy and security concerns.

The authors validate the proposed model explaining patients' perceptions about their characteristics and the healthcare system significantly influence their attitude toward engaging in their care. This study also suggests that patients' favorable attitude toward engagement can bring patient-centric HIE efforts onto a path to success. The authors’ research attempts to shed light on the importance of patients' roles in adopting patient-centric HIE initiatives. Theoretical and practical contributions of this study are noticeable since they could result in a deeper understanding of the concept of patient engagement and how it may affect healthcare services in an evolving digital world. The authors’ findings can help healthcare organizations provide public citizen-centric services by introducing user-oriented approaches in healthcare delivery systems.

The purpose of this paper is to report on the dynamics of “identity leadership” with a quality improvement project undertaken by an International Medical Graduate (IMG) from Sri Lanka, on a two year Medical Training Initiative (MTI) placement in the National Health Service (NHS) [Academy of Medical Royal Colleges (AoMRC), 2017]. A combined MTI rotation with an integrated Fellowship in Quality Improvement (Subedi et al., 2019) provided the driver to implement the HEART score (HS) in an NHS Emergency Department (ED) in the UK. The project was undertaken across ED, Acute Medicine and Cardiology at the hospital, with stakeholders emphasizing different and conflicting priorities to improve the pathway for chest pain patients.

A social identity approach to leadership provided a framework to understand the insider/outsider approach to leadership which helped RH to negotiate and navigate the conflicting priorities from each departments’ perspective. A staff survey tool was undertaken to identify reasons for the lack of implementation of a clinical protocol for chest pain patients, specifically with reference to the use of the HS. A consensus was reached to develop and implement the pathway for multi-disciplinary use of the HS and a quality improvement methodology (with the use of plan do study act (PDSA) cycles) was used over a period of nine months.

The results demonstrated significant improvements in the reduction (60%) of waiting time by chronic chest pain patients in the ED. The use of the HS as a stratified risk assessment tool resulted in a more efficient and safe way to manage patients. There are specific leadership challenges faced by an MTI doctor when they arrive in the NHS, as the MTI doctor is considered an outsider to the NHS, with reduced influence. Drawing upon the Social Identity Theory of Leadership, NHS Trusts can introduce inclusion strategies to enable greater alignment in social identity with doctors from overseas.

More than one third of doctors (40%) in the English NHS are IMGs and identify as black and minority ethnic (GMC, 2019a) a trend that sees no sign of abating as the NHS continues its international medical workforce recruitment strategy for its survival (NHS England, 2019; Beech et al., 2019). IMGs can provide significant value to improving the NHS using skills developed from their own health-care system. This paper recommends a need for reciprocal learning from low to medium income countries by UK doctors to encourage the development of an inclusive global medical social identity.

This quality improvement research combined with identity leadership provides new insights into how overseas doctors can successfully lead sustainable improvement across different departments within one hospital in the NHS.

Infection and cross-contamination have been massive concerns in the medical field. This study aims to investigate consumers’ awareness and their choices of endoscopes, which may deter them from the cross-contamination problem.

A discrete choice experiment survey was administered to 166 respondents in Penang, Malaysia. Participants were asked to make hypothetical choices and estimate their preference for endoscopes. The multinomial logit model was used to estimate the assumptions based on the stated preference data collected.

Only two-fifths of respondents are aware of their rights regarding endoscope selection. The findings are consistent with utility theory, where choices are made to maximise personal satisfaction. If given the choice, consumers preferred the single-use endoscope over the reusable or the doctor’s preferred endoscope. Price, insurance coverage and personal income are significant determinants of the consumer’s choice of endoscopes.

This study only investigates subjects living in Penang. Other possible important attributes to endoscope choices, such as environmental and device availability may be considered in future study.

The findings may create awareness among consumers about their rights when choosing medical devices. It may also improve health-care institutions’ (users’) and device manufacturers’ (industry players’) understanding of consumer needs and demands from socioeconomic perspectives.

The research offers insights into consumer rights and awareness of health-care services. Ultimately leading to better policy to protect consumers’ rights and safety.

This study contributes to the rare literature on consumer rights toward medical devices, in particular, the consumer’s awareness of the choice of endoscopes.