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1 – 10 of 118Elena Stefana, Paola Cocca, Federico Fantori, Filippo Marciano and Alessandro Marini
This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.
Abstract
Purpose
This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.
Design/methodology/approach
The authors conducted a literature review about the studies focusing on approaches combining OEE with monetary units and/or resource issues. The authors developed an approach based on Overall Equipment Cost Loss (OECL), introducing a component for the production resource consumption of a machine. A real case study about a smart multicenter three-spindle machine is used to test the applicability of the approach.
Findings
The paper proposes Resource Overall Equipment Cost Loss (ROECL), i.e. a new KPI expressed in monetary units that represents the total cost of losses (including production resource ones) caused by inefficiencies and deviations of the machine or equipment from its optimal operating status occurring over a specific time period. ROECL enables to quantify the variation of the product cost occurring when a machine or equipment changes its health status and to determine the actual product cost for a given production order. In the analysed case study, the most critical production orders showed an actual production cost about 60% higher than the minimal cost possible under the most efficient operating conditions.
Originality/value
The proposed approach may support both production and cost accounting managers during the identification of areas requiring attention and representing opportunities for improvement in terms of availability, performance, quality, and resource losses.
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This study aims to present the concept of aircraft turbofan engine health status prediction with artificial neural network (ANN) pattern recognition but augmented with automated…
Abstract
Purpose
This study aims to present the concept of aircraft turbofan engine health status prediction with artificial neural network (ANN) pattern recognition but augmented with automated features engineering (AFE).
Design/methodology/approach
The main concept of engine health status prediction was based on three case studies and a validation process. The first two were performed on the engine health status parameters, namely, performance margin and specific fuel consumption margin. The third one was generated and created for the engine performance and safety data, specifically created for the final test. The final validation of the neural network pattern recognition was the validation of the proposed neural network architecture in comparison to the machine learning classification algorithms. All studies were conducted for ANN, which was a two-layer feedforward network architecture with pattern recognition. All case studies and tests were performed for both simple pattern recognition network and network augmented with automated feature engineering (AFE).
Findings
The greatest achievement of this elaboration is the presentation of how on the basis of the real-life engine operational data, the entire process of engine status prediction might be conducted with the application of the neural network pattern recognition process augmented with AFE.
Practical implications
This research could be implemented into the engine maintenance strategy and planning. Engine health status prediction based on ANN augmented with AFE is an extremely strong tool in aircraft accident and incident prevention.
Originality/value
Although turbofan engine health status prediction with ANN is not a novel approach, what is absolutely worth emphasizing is the fact that contrary to other publications this research was based on genuine, real engine performance operational data as well as AFE methodology, which makes the entire research very reliable. This is also the reason the prediction results reflect the effect of the real engine wear and deterioration process.
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Cosimo Magazzino, Monica Auteri, Nicolas Schneider, Ferdinando Ofria and Marco Mele
The objective of this study is to reevaluate the correlation among pharmaceutical consumption, per capita income, and life expectancy across different age groups (at birth, middle…
Abstract
Purpose
The objective of this study is to reevaluate the correlation among pharmaceutical consumption, per capita income, and life expectancy across different age groups (at birth, middle age, and advanced age) within the OECD countries between 1998 and 2018.
Design/methodology/approach
We employ a two-step methodology, utilizing two independent approaches. Firstly, we con-duct the Dumitrescu-Hurlin pairwise panel causality test, followed by Machine Learning (ML) experiments employing the Causal Direction from Dependency (D2C) Prediction algorithm and a DeepNet process, thought to deliver robust inferences with respect to the nature, sign, direction, and significance of the causal relationships revealed in the econometric procedure.
Findings
Our findings reveal a two-way positive bidirectional causal relationship between GDP and total pharmaceutical sales per capita. This contradicts the conventional notion that health expenditures decrease with economic development due to general health improvements. Furthermore, we observe that GDP per capita positively correlates with life expectancy at birth, 40, and 60, consistently generating positive and statistically significant predictive values. Nonetheless, the value generated by the input life expectancy at 60 on the target income per capita is negative (−61.89%), shedding light on the asymmetric and nonlinear nature of this nexus. Finally, pharmaceutical sales per capita improve life expectancy at birth, 40, and 60, with higher magnitudes compared to those generated by the income input.
Practical implications
These results offer valuable insights into the intricate dynamics between economic development, pharmaceutical consumption, and life expectancy, providing important implications for health policy formulation.
Originality/value
Very few studies shed light on the nature and the direction of the causal relationships that operate among these indicators. Exiting from the standard procedures of cross-country regressions and panel estimations, the present manuscript strives to promote the relevance of using causality tests and Machine Learning (ML) methods on this topic. Therefore, this paper seeks to contribute to the literature in three important ways. First, this is the first study analyzing the long-run interactions among pharmaceutical consumption, per capita income, and life expectancy for the Organization for Economic Co-operation and Development (OECD) area. Second, this research contrasts with previous ones as it employs a complete causality testing framework able to depict causality flows among multiple variables (Dumitrescu-Hurlin causality tests). Third, this study displays a last competitive edge as the panel data procedures are complemented with an advanced data testing method derived from AI. Indeed, using an ML experiment (i.e. Causal Direction from Dependency, D2C and algorithm) it is believed to deliver robust inferences regarding the nature and the direction of the causality. All in all, the present paper is believed to represent a fruitful methodological research orientation. Coupled with accurate data, this seeks to complement the literature with novel evidence and inclusive knowledge on this topic. Finally, to bring accurate results, data cover the most recent and available period for 22 OECD countries: from 1998 to 2018.
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Nükhet Taylor and Sean T. Hingston
Fueled by the soaring popularity of the digital medium, consumers are increasingly relying on dynamic images to inform their decisions. However, little is known about how changes…
Abstract
Purpose
Fueled by the soaring popularity of the digital medium, consumers are increasingly relying on dynamic images to inform their decisions. However, little is known about how changes in the presentation of movement impacts these decisions. The purpose of this paper is to document whether and how movement speed–a fundamental characteristic of dynamic images in the digital medium–influences consumers' risk judgments and subsequent decisions.
Design/methodology/approach
Three experimental studies investigate the impact of movement speed displayed in the digital medium, focusing on different risk-laden domains including health (pilot study), gambling (Study 1) and stock market decisions (Study 2).
Findings
The authors find that faster movement speed displayed in the digital medium elevates consumers’ feelings of risk and elicits cautionary actions in response. The authors reveal a mechanism for this effect, showing that faster movement reduces feelings of control over outcomes, which predicts greater feelings of risk.
Research limitations/implications
Future work could expand upon these findings by systematically examining whether certain individuals are more susceptible to movement speed effects in the digital medium. Research could also investigate whether different ways of experiencing movement speed (e.g. physical movement) similarly influence risk judgments and whether movement speed can have positive connotations outside of risky domains.
Practical implications
The authors offer important insights to marketing practitioners and public policymakers seeking to guide consumers’ judgments and decisions in risk-laden contexts through the digital medium.
Originality/value
By showing how movement speed alters judgments in risk-laden contexts, the authors contribute to literature on risk perception and the growing body of literature examining how moving images shape consumers’ behaviors.
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A large number of studies indicate that coercive forms of organizational control and performance management in health care services often backfire and initiate dysfunctional…
Abstract
Purpose
A large number of studies indicate that coercive forms of organizational control and performance management in health care services often backfire and initiate dysfunctional consequences. The purpose of this article is to discuss new approaches to performance management in health care services when the purpose is to support innovative changes in the delivery of services.
Design/methodology/approach
The article represents cross-boundary work as the theoretical and empirical material used to discuss and reconsider performance management comes from several relevant research disciplines, including systematic reviews of audit and feedback interventions in health care and extant theories of human motivation and organizational control.
Findings
An enabling approach to performance management in health care services can potentially contribute to innovative changes. Key design elements to operationalize such an approach are a formative and learning-oriented use of performance measures, an appeal to self- and social-approval mechanisms when providing feedback and support for local goals and action plans that fit specific conditions and challenges.
Originality/value
The article suggests how to operationalize an enabling approach to performance management in health care services. The framework is consistent with new governance and managerial approaches emerging in public sector organizations more generally, supporting a higher degree of professional autonomy and the use of nonfinancial incentives.
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This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these…
Abstract
Purpose
This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these challenges, providing insights into healthcare investments, policy analysis and patient care pathways.
Design/methodology/approach
This research employs the real options theory, a financial concept, to delve into health economics challenges. Through a systematic approach, three distinct models rooted in this theory are crafted and analyzed. Firstly, the study examines the value of investing in emerging health technology, factoring in future advantages, associated costs and unpredictability. The second model is patient-centric, evaluating the choice between immediate treatment switch and waiting for more clarity, while also weighing the associated risks. Lastly, the research assesses pandemic-related government policies, emphasizing the importance of delaying decisions in the face of uncertainties, thereby promoting data-driven policymaking.
Findings
Three different real options models are presented in this study to illustrate their applicability and value in aiding decision-makers. (1) The first evaluates investments in new technology, analyzing future benefits, discount rates and benefit volatility to determine investment value. (2) In the second model, a patient has the option of switching treatments now or waiting for more information before optimally switching treatments. However, waiting has its risks, such as disease progression. By modeling the potential benefits and risks of both options, and factoring in the time value, this model aids doctors and patients in making informed decisions based on a quantified assessment of potential outcomes. (3) The third model concerns pandemic policy: governments can end or prolong lockdowns. While awaiting more data on the virus might lead to economic and societal strain, the model emphasizes the economic value of deferring decisions under uncertainty.
Practical implications
This research provides a quantified perspective on various decisions in healthcare, from investments in new technology to treatment choices for patients to government decisions regarding pandemics. By applying real options theory, stakeholders can make more evidence-driven decisions.
Social implications
Decisions about patient care pathways and pandemic policies have direct societal implications. For instance, choices regarding the prolongation or ending of lockdowns can lead to economic and societal strain.
Originality/value
The originality of this study lies in its application of real options theory, a concept from finance, to the realm of health economics, offering novel insights and analytical tools for decision-makers in the healthcare sector.
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Rostand Arland Yebetchou Tchounkeu
This work aims to analyse the relationship between public health efficiency and well-being considering a panel of 102 Italian provinces from 2000 to 2016 and evaluates if there…
Abstract
Purpose
This work aims to analyse the relationship between public health efficiency and well-being considering a panel of 102 Italian provinces from 2000 to 2016 and evaluates if there are omitted variable biases and endogeneity biases and also evaluates if there are heterogeneous effects among provinces with different income levels.
Design/methodology/approach
We use a multi-input and output bootstrap data envelopment analysis to assess public health efficiency. Then, we measure well-being indices using the min-max linear scaling transformation technique. A two-stage least squares model is used to identify the causal effect of improving public health efficiency on well-being to account for time-invariant heterogeneity, omitted variable bias and endogeneity bias.
Findings
After controlling for important economic factors, the results show a significant effect of an accountable and efficient public health system on well-being. Those effects are concentrated in the North, the most economically, geographically and environmentally advantageous areas.
Research limitations/implications
The use of the sample mean, probably the oldest and most used method for aggregating the indicators, could be affected by variable compensation, with consequent misleading results in the process of constructing the well-being index. Another limitation is the use of lagged values of the main predictor as an instrument in the instrumental variables setting because it could lead to information loss. Finally, the availability of data over a long period of time.
Practical implications
The findings could help policymakers adopt measures to strengthen the public health system, encourage private providers and inspire countries worldwide.
Social implications
These results draw the attention of local authorities, who play an important role in designing and implementing policies to stimulate local public health efficiency, which puts individuals in the conditions of achieving overall well-being in their communities.
Originality/value
For the first time in Italy, a panel of well-being indices was constructed by developing new methodologies based on microeconomic theory. Furthermore, for the first time, the assessment of the relationship between public health efficiency and well-being is carried out using a panel of 102 Italian provinces.
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Hassan Th. Alassafi, Khalid S. Al-Gahtani, Abdulmohsen S. Almohsen and Abdullah M. Alsugair
Heating, ventilating, air-conditioning and cooling (HVAC) systems are crucial in daily health-care facility services. Design-related defects can lead to maintenance issues…
Abstract
Purpose
Heating, ventilating, air-conditioning and cooling (HVAC) systems are crucial in daily health-care facility services. Design-related defects can lead to maintenance issues, causing service disruptions and cost overruns. These defects can be avoided if a link between the early design stages and maintenance feedback is established. This study aims to use experts’ experience in HVAC maintenance in health-care facilities to list and evaluate the risk of each maintenance issue caused by a design defect, supported by the literature.
Design/methodology/approach
Following semistructured interviews with experts, 41 maintenance issues were identified as the most encountered issues. Subsequently, a survey was conducted in which 44 participants evaluated the probability and impact of each design-caused issue.
Findings
Chillers were identified as the HVAC components most prone to design defects and cost impact. However, air distribution ducts and air handling units are the most critical HVAC components for maintaining healthy conditions inside health-care facilities.
Research limitations/implications
The unavailability of comprehensive data on the cost impacts of all design-related defects from multiple health-care facilities limits the ability of HVAC designers to furnish case studies and quantitative approaches.
Originality/value
This study helps HVAC designers acquire prior knowledge of decisions that may have led to unnecessary and avoidable maintenance. These design-related maintenance issues may cause unfavorable health and cost consequences.
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Alexandra Waluszewski, Alessandro Cinti and Andrea Perna
Limiting the use of antibiotics in food animals is a cornerstone of contemporary EU policy. Despite that marketing of antibiotics for growth promotion and nutrition has been…
Abstract
Purpose
Limiting the use of antibiotics in food animals is a cornerstone of contemporary EU policy. Despite that marketing of antibiotics for growth promotion and nutrition has been banned since 2006, the use is still high and varied. This paper aims to investigate the forces behind the different usage patterns in Italy, with one of the EU’s most extensive use of antibiotics in animals, versus Sweden, with the union’s most restricted use, including how these usage patterns are related to EU and national policies.
Design/methodology/approach
The industrial network approach/the 4R resources interaction model is adopted to investigate the major forces behind the different antibiotic usage patterns. Furthermore, the study relies on the notion of three main characteristics related to the use of a resource activated in several user settings (Håkansson and Waluszewski, 2008, pp. 20–22). The paper investigates the Swedish and the Italian using settings, with a minimised, respectively, extensive usage of antibiotics. The study is exploratory in nature and based on qualitative data collected through a combination of primary and secondary sources.
Findings
The paper underlines the importance of integrating forces for policy to succeed in attempts to reduce the use of a particular resource. It reveals that Sweden’s radically reduced use was based on great awareness, close interactions between animal-based food producers and policy – and that integrating forces were supported by an era of state-protected food production, with promising ability to distribute the cost of change. The Italian characteristics hindering the integration of forces mounting for reduced use were restricted awareness, top-down business and policy interactions – and a great awareness about the difficulties of distributing the cost of change.
Originality/value
The study deals with the analysis of forces affecting the different usage of antibiotics within two EU settings. The investigation, based on the industrial network approach’s notion of connectivity of economic resources, that is, of exchange having a content and substance beyond discrete transactions, reveals how indirect related contextual forces, neglected by policy, have an important influence on the ability to achieve change, in this case of antibiotics usage patterns.
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Christian Di Falco, Guido Noto, Carmelo Marisca and Gustavo Barresi
This article aims to provide the current state of the art of the literature on the contribution of information and communication technologies (ICTs) on the measurement and…
Abstract
Purpose
This article aims to provide the current state of the art of the literature on the contribution of information and communication technologies (ICTs) on the measurement and management of performance in the healthcare sector. In particular, the work aims to identify current and emerging ICTs and how these relate to the performance measurement and management (PMM) cycle of healthcare organizations.
Design/methodology/approach
To address the research objective, we adopted a systematic literature review. In particular, we used the preferred reporting items for systematic reviews and meta-analysis (PRISMA) methodology to select articles related to the investigated topic. Based on an initial screening of 560 items retrieved from Scopus and ISI Web of Knowledge, we identified and analyzed 58 articles dealing with ICTs and PMM in the healthcare sector. The last update of the dataset refers to February 2024.
Findings
Although we attempted to address a relevant topic for both research and practice, we noticed that a relatively small sample of articles directly addressed it. Through this literature review, in addition to providing descriptive statistics of research on ICTs and PMM in healthcare, we identified six theoretical clusters of scientific streams focusing on the topic and eleven categories of ICTs effectively tackled by the literature. We then provided a holistic framework to link technologies to the different PMM phases and functions.
Practical implications
Nowadays, the availability of ICTs to support healthcare organizations’ processes and services is extensive. In this context, managers at various organizational levels need to understand and evaluate how each ICT can support different activities to benefit most from their adoption. The findings of this study can offer valuable insights to top and line managers of healthcare organizations for planning their investments in both existing and emerging ICTs to support the various stages of development and functions of PMM.
Originality/value
Most of the current literature focusing on ICTs in the healthcare sector refers to the contribution that technology provides to clinical processes and services, devoting limited attention to the impact of ICTs on administrative processes, such as PMM. To the best of the authors’ knowledge, this represents the first literature review on the contribution of ICTs to PMM in the healthcare sector. The review, differently from other research focused on specific ICTs and/or specific PMM functions, provides a holistic perspective to understand how these technologies may support healthcare organizations and systems in measuring and managing their performance.
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