Search results

This paper aims to introduce a non-invasive and convenient method to detect a life-threatening disease called aortic dissection. A Bayesian inference based on enhanced multi-sensors impedance cardiography (ICG) method has been applied to classify signals from healthy and sick patients.

A 3D numerical model consisting of simplified organ geometries is used to simulate the electrical impedance changes in the ICG-relevant domain of the human torso. The Bayesian probability theory is used for detecting an aortic dissection, which provides information about the probabilities for both cases, a dissected and a healthy aorta. Thus, the reliability and the uncertainty of the disease identification are found by this method and may indicate further diagnostic clarification.

The Bayesian classification shows that the enhanced multi-sensors ICG is more reliable in detecting aortic dissection than conventional ICG. Bayesian probability theory allows a rigorous quantification of all uncertainties to draw reliable conclusions for the medical treatment of aortic dissection.

This paper presents a non-invasive and reliable method based on a numerical simulation that could be beneficial for the medical management of aortic dissection patients. With this method, clinicians would be able to monitor the patient’s status and make better decisions in the treatment procedure of each patient.

Outsourcing of logistics has great importance in disaster relief. Aid agencies spend several billion US dollars every year on logistics services. However, the concept of outsourcing has not been established adequately in literature on humanitarian logistics, leading to a fragmented view of the practice. This paper provides a holistic perspective of the concept by constructing a conceptual framework to analyze both practice and research of outsourcing in humanitarian operations. Based on this analysis, we explore future trends and identify research gaps.

The paper is based on a structured review of academic literature, a two-round Delphi study with 31 experts from aid agencies and a complementary full-day focus group with twelve experts from aid agencies and logistics service providers.

The paper systemizes the current practice of outsourcing in humanitarian logistics according to a conceptual framework of five dimensions: subject, object, partner, design and context. In addition, it reveals ten probable developments of the practice over the next years. Finally, it describes eight important research gaps and presents a research agenda for the field.

The literature review considered peer-reviewed academic papers. Practitioner papers could provide additional insights into the practice. Moreover, the Delphi study focused on the perspective of aid agencies. Capturing the views of logistics service providers in more detail would be a valuable addition.

The paper establishes the academic basis for the important practice of outsourcing in humanitarian logistics. It highlights essential research gaps and, thereby, opens up the field for future research.

This paper investigates the suitability of fuzzy-logic-based support tools for initial screening of manufacturing reshoring decisions.

Two fuzzy-logic-based support tools are developed together with experts from a Swedish manufacturing firm. The first uses a complete rule base and the second a reduced rule base. Sixteen inference settings are used in both of the support tools.

The findings show that fuzzy-logic-based support tools are suitable for initial screening of manufacturing reshoring decisions. The developed support tools are capable of suggesting whether a reshoring decision should be further evaluated or not, based on six primary competitiveness criteria. In contrast to existing literature this research shows that it does not matter whether a complete or reduced rule base is used when it comes to accuracy. The developed support tools perform similarly with no statistically significant differences. However, since the interpretability is much higher when a reduced rule base is used and it require fewer resources to develop, the second tool is more preferable for initial screening purposes.

The developed support tools are implemented at a primary-criteria level and to make them more applicable, they should also include the sub-criteria level. The support tools should also be expanded to not only consider competitiveness criteria, but also other criteria related to availability of resources and strategic orientation of the firm. This requires further research with regard to multi-stage architecture and automatic generation of fuzzy rules in the manufacturing reshoring domain.

The support tools help managers to invest their scarce time on the most promising reshoring projects and to make timely and resilient decisions by taking a holistic perspective on competitiveness. Practitioners are advised to choose the type of support tool based on the available data.

There is a general lack of decision support tools in the manufacturing reshoring domain. This paper addresses the gap by developing fuzzy-logic-based support tools for initial screening of manufacturing reshoring decisions.

The primary objective of this paper is to show a systematic and methodological approach for the digitalization of critical clinical pathways (CPs) within the healthcare domain.

The methodology entails the integration of service design (SD) and action research (AR) methodologies, characterized by iterative phases that systematically alternate between action and reflective processes, fostering cycles of change and learning. Within this framework, stakeholders are engaged through semi-structured interviews, while the existing and envisioned processes are delineated and represented using BPMN 2.0. These methodological steps emphasize the development of an autonomous, patient-centric web application alongside the implementation of an adaptable and patient-oriented scheduling system. Also, business processes simulation is employed to measure key performance indicators of processes and test for potential improvements. This method is implemented in the context of the CP addressing transient loss of consciousness (TLOC), within a publicly funded hospital setting.

The methodology integrating SD and AR enables the detection of pivotal bottlenecks within diagnostic CPs and proposes optimal corrective measures to ensure uninterrupted patient care, all the while advancing the digitalization of diagnostic CP management. This study contributes to theoretical discussions by emphasizing the criticality of process optimization, the transformative potential of digitalization in healthcare and the paramount importance of user-centric design principles, and offers valuable insights into healthcare management implications.

The study’s relevance lies in its ability to enhance healthcare practices without necessitating disruptive and resource-intensive process overhauls. This pragmatic approach aligns with the imperative for healthcare organizations to improve their operations efficiently and cost-effectively, making the study’s findings relevant.

The review examines the existing literature on blockchain-based small and medium enterprise (SME) finance and highlights its trend, themes, opportunities and challenges. Based on these factors, the authors create a framework for the existing literature on blockchain-based SME financing and lay down future research paths.

The review follows a systematic approach. It includes 53 articles encompassing multiple dimensions of blockchain-based SME finance, including peer-to-peer lending platforms, supply chain finance (SCF), decentralized lending protocols and tokenization of assets. The review critically evaluates these approaches' theoretical underpinnings, empirical evidence and practical implementations.

The review demonstrates that blockchain-based SME finance holds significant promise in addressing the credit gap by leveraging blockchain technology's decentralized and transparent nature. Benefits identified include reduced information asymmetry, improved access to financing, enhanced credit assessment processes and increased financial inclusion. However, the literature acknowledges several challenges and limitations, such as regulatory uncertainties, scalability issues, operational complexities and potential security risks.

The article contributes to the growing knowledge of blockchain-based SME finance by synthesizing and evaluating the existing literature. It also provides a framework for the existing literature in the area and future research paths. The study offers insights for researchers, policymakers and practitioners seeking to understand the potential of blockchain technology in filling the SME credit gap and fostering economic development through improved access to finance for SMEs.

In a work environment marked by unprecedented complexity, volatility and ambiguity, managers must accomplish their objectives while navigating many challenges. This paper aims to investigate potential interrelations among environmental transformations, cognitive biases and strategic decisions. In particular, the purpose of the study is to crystallize the state of art on the impact of cognitive biases on strategic decisions, in the context of environmental transformations.

The authors have conducted a systematic literature review to identify existing relevant work on this topic and to detect potential avenues for future research.

The findings highlight how decision-making is influenced and enabled by internal (e.g. perception) and external factors (e.g. digitalization). Specifically, the strategic role of cognitive biases appears to be crucial when investigating the related impact on strategic decisions in times of environmental transformation.

Implications are drawn for scholars and practitioners interested in evaluating the role of specific decision-making determinants for the formation and implementation of strategic decisions. In this sense, we stress that decision-makers need to manage their cognitive biases and select the right information out of a wide data set in order to adapt to environmental transformations.

By systematizing the literature review, potential interrelations among environmental transformations, cognitive biases and strategic decisions are identified. Furthermore, the primary phases that drive the decision-making process are proposed (analysis, decision, onboarding and control).

To promote access to their services, health-care companies provide various communication channels to their customers (beneficiaries) to enable the receipt of requests, such as authorization for examinations, procedures and hospitalizations. Under the approach of innovation studies, the management of customer relationship channels for health-care companies is characterized as a knowledge-intensive business service (KIBS). The purpose of this study is presenting innovation as a strategy to increase customer service productivity, as well as the monitoring of the quality of the service, the generation of health information for beneficiaries and compliance with the regulation set by the Brazilian National Health Agency (ANS).

The study is characterized as an applied research, as it proposes solutions to problems faced by supplemental health-care companies using the strategy of action research, i.e. an independent, social research with an empirical basis.

The result of this study shows that a computerized health-care system can increase productivity by 21.96%, and it presents an innovative solution for health-care companies to guarantee the process of meeting the demands and requests of their beneficiaries, ensuring the compliance with ANS regulations.

These results can be replicated to other healthcare companies and contribute to those seeking innovation, increased productivity and quality improvements in their services.

This work was also motivated by the lack of lstudies in the areas of health-care companies in Brazil.