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Efficiency standards, similar to industrial measures like overall equipment effectiveness (OEE), are being used in healthcare systems more and more. Performance indicator models applied to machines assume a constant completion time. However, for human resources, the completion time of a task may vary depending on the stress experienced. This study seeks to bridge this gap by integrating the human behavior of the physician into the performance evaluation.

The paper presents a new algorithm called PerfoBalance that is intended to distribute waiting-patient values among doctors. By maximizing each physician’s stress zones, this method helps to improve their performance as a whole. A thorough case study with medical professionals is carried out to confirm the effectiveness of the suggested methodology. The PerfoBalance algorithm is used in a variety of contexts to divide waiting-patient values among doctors and optimize stress zones.

Experimental results demonstrate a significant improvement in physician efficiency when implementing the PerfoBalance algorithm. The algorithm strategically selects stress zones that contribute to higher performance rates for physicians by optimizing waiting-patient values.

By addressing the undervaluation of human performance difficulties in current efficiency models used in the healthcare industry, this research constitutes a significant contribution to the field. With its launch, the PerfoBalance algorithm offers a fresh viewpoint on waiting-patient value allocation and stress zone management in healthcare settings, hence representing a powerful method for increasing physician productivity.

This study aims to investigate the dynamics between exogenous shocks, financial stress and economic performance in the USA from January 1995 to August 2023.

Granger-causality tests and impulse response analyses are used to examine causal relationships and dynamic responses among crude oil prices, real M2 money supply, financial stress and key economic indicators.

This study reveals a significant correlation between elevated financial stress and reduced real output, along with disruptions in the labor market, potentially leading to economic recessionary trends. Failure to address these challenges could perpetuate labor market difficulties, weaken capital accumulation within the loanable funds market and ultimately hinder long-term economic growth prospects in the USA.

This study offers insights for policymakers to mitigate financial stress. Recommendations include enhancing financial surveillance, strengthening regulatory frameworks, promoting economic diversification and implementing countercyclical policies to stabilize the economy and support labor markets. In addition, proactive monitoring of financial stress indicators can serve as early warning signals, aiding in timely interventions and effective risk management strategies.

This research provides a comprehensive analysis of how the financial stress index (FSI) mediates the effects of external shocks on the US economy, addressing a gap in existing literature. The integration of the FSI into the analysis enhances the understanding of the transmission channels through which external shocks influence the economy.

Can regional economic complexity improve the employment effect, and is the employment structure also affected by heterogeneity? In order to solve these doubts, this paper plans to carry out systematic theoretical analysis and quantitative tests on these problems.

Based on the macroeconomic data of 129 countries from 1995 to 2022, this paper empirically studies the impact of economic complexity on the employment effect and its mechanism channel by building relevant models.

The results show that regional economic complexity can significantly improve the employment effect of society. At the same time, regional economic complexity has an indirect positive role in promoting employment from two aspects: accumulating fiscal surplus and increasing the working-age population. The former can stimulate employment policies by increasing the government’s tax sources, while the latter can increase production specialization and complexity by stimulating demand and increasing employment. In addition, regional economic complexity will lead to job market differentiation, making the boundary between the service sector and the labor market between industry and agriculture and between the informal employment market and the formal employment more obvious, thus triggering the substitution effect of employment.

The possible innovations and marginal contributions of this paper are as follows: First, there are many studies on the influencing factors of employment or unemployment, and this paper provides a new research direction for the literature on the influencing factors of employment effect by using the concept of regional economic complexity for the first time. Second, this paper broadens the research perspective of the employment effect of regional economic complexity, divides the employment substitution effect of various sectors from the perspective of industrial structure and further analyzes the employment promotion effect of regional economic complexity.

Little is known about the quantitative impact of macro policies on disaggregated variables. This study investigates the effects of macroeconomic policies and cost/supply shocks on sectoral output growth.

We analyzed empirical evidence from Ghana using a Structural Vector Autoregression approach.

The results show that the transmission of various macro policies and supply/cost shocks is conditional on sectoral idiosyncrasies. Fiscal programs contribute the most to agricultural output growth and the least to industrial production. The downturn from rising costs and supply disruptions is more severe and lasting in the agriculture sector than in the service sector. The evidence shows that fiscal consolidation centered on government consumption cuts would not drag growth over the medium-term.

Our results show that the structural characteristics of a country may play an important role in understanding the output effects of macro policy changes. The empirical evidence shows that targeted policies are needed to complement countercyclical macroeconomic policies to facilitate broad-based economic recovery.

Research on the impact of macro policy shocks on the real economy has usually focused on the behavior of highly aggregated variables. In this research, we focus on disaggregated, sector-level variables to unveil the idiosyncrasies in the performance of disaggregated variables that are usually concealed when studying the behavior of aggregate variables. This study also contributes a different angle to the debate on supply shocks by examining how cost shocks are propagated through the various sectors of the economy.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2023-0876

Lean Manufacturing Systems (LMS) gained popularity among manufacturers globally. However, their efficacy in developing and least-developed countries remained noticeably understudied. Motivated by this research gap, the researchers of this study designed a quantitative study with a structured survey technique to investigate its context-specific impact on the apparel industry of a developing country. Hence, this study aimed to examine the relationship between LMS and elimination of waste (EOW) and operational performance (OP) and comprehend how the EOW mediates the relationship between an LMS and OP within the apparel industry of a developing economy.

The researchers collected data from 227 garment companies in Bangladesh. These organization-level data were then analyzed using the structural equation modeling approach with AMOS 20.0 software to examine the direct and indirect effects among EOW, LMS and OP.

The findings of this study suggest that EOW has a direct and significant effect on OP. This research also revealed that EOW has a partial mediating effect on the relationship between LMS and OP.

This research focused on a single industry administering self-reported data and cross-sectional design, limiting generalizability and causal inference.

LMS and directing efforts towards EOW can significantly improve the operational performance of apparel companies by reducing lead times and costs, improving quality and increasing productivity.

These findings can provide useful insight to managers, practitioners and future researchers to understand the relationship between EOW, LMS and OP to optimize their production processes and improve OP in the apparel industry.

This paper aims to review the literature on the relationship between the implementation and performance of 4.0 industrial revolution (IR) technologies and explores the extent to which the effects of several internal and external contingency factors on these relationships have been considered by the existing empirical studies.

To achieve its purposes, this study follows a systematic review of the literature and explores the published empirical research on implementation and performance links of 4.0 IR technologies and the effects of contingency factors on these links in mainly three main databases.

The findings of this study reveal that in general several contingency factors tend to have significant effects on the implementation and performance links of 4.0 IR in several contexts. This study also shows that the effects of these contingencies the effects of contingency factors on the implementation and performance links of 4.0 IR technologies are receiving growing attention from researchers and have been studied in different approaches but the moderation approach was the highest.

The review of the literature conducted in this study refers to those studies published mostly by three main databases (i.e. Scopus, Web of Sciences, and Science Direct), and only those papers published in English, and thus does not contain publications out of these restrictions.

This is one of the early literature review studies to explore and discuss the current state of research on the effects of contingency factors on the relationships between the implementation and performance of 4.0 IR technologies in the contexts of logistics and supply chain management.

The purpose of the study is to determine the local antecedents of subsidiary participation in global services and, subsequently, the impact on local performance.

The study is based on a survey with the local subsidiaries of 14 manufacturers engaged in global services as part of their servitisation strategy.

Findings show support for considering the local ability for global services as an antecedent for local subsidiary participation in global services and the local service performance as an outcome. In addition, the results reject our hypotheses related to the specific roles of local opportunity and motivation for global services.

This study provides novel insights on the global service operations of manufacturers by highlighting the perspective of subsidiaries engaged in the local service delivery and development of global services. This perspective sets the conditions of the global-local collaboration in the context of global service strategy with local service delivery.

A new round of technological revolution is impacting various aspects of society. However, the importance of technology adoption in fostering firm innovation is underexplored. Therefore, this study aims to investigate whether robot adoption affects technological innovation and how human capital plays a role in this relationship in the era of circular economy.

Based on the robot adoption data from the International Federation of Robotics (IFR) and panel data of China's listed manufacturing firms from 2011 to 2020, this study uses regression models to test the impact of industrial robots on firm innovation and the mediating role of human capital.

The results demonstrate that the adoption of industrial robots can significantly promote high-quality innovation. Specifically, a one-unit increase in the number of robots per 100 employees is associated with a 13.52% increase in the number of invention patent applications in the following year. The mechanism tests show that industrial robots drive firm innovation by accumulating more highly educated workers and allocating more workers to R&D jobs. The findings are more significant for firms in industries with low market concentration, in labor-intensive industries and in regions with a shortage of high-end talent.

Due to data limitations, the sample of this study is limited to listed manufacturing firms, so the impact of industrial robots on promoting innovation may be underestimated. In addition, this study cannot observe the dynamic process of human capital management by firms after adopting robots.

The Chinese government should continue to promote the intelligent upgrading of the manufacturing industry and facilitate the promotion of robots in innovation. This implication can also be applied to developing countries that hope to learn from China's experience. In addition, this study emphasizes the role of human capital in the innovation-promoting process of robots. This highlights the importance of firms to strengthen employee education and training.

The adoption of industrial robots has profoundly influenced the production and lifestyle of human society. This study finds that the adoption of robots contributes to firm innovation, which helps people gain a deeper understanding of the positive impacts brought about by industrial intelligence.

By exploring the impact of industrial robots on firm innovation, this study offers crucial evidence at the firm level to comprehend the economic implications of robot adoption based on circular economy and human perspectives. Moreover, this study reveals that human capital is an important factor in how industrial robots affect firm innovation, providing an important complement to previous studies.

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.

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.

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.

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.

From these data, the authors construct an uncertainty index through the use of a vector autoregressive (VAR) model to measure the impact of uncertainty on GDP, controlling for inflation, which may affect macroeconomic performance. Results indicate that uncertainty is negatively correlated with the economic cycle and the inter-annual variation of the biannual average product.

This study empirically explores the dynamics of expectations of the Uruguayan manufacturing firms about industrial economic growth. This study explores the dynamics of the industrial economic growth expectations of Uruguayan manufacturing firms. The empirical research is based on firms' expectations data collected through a monthly survey carried out by the Chamber of Industries of Uruguay (CIU) in 2003–2018.

Granger causality tests show that uncertainty Granger-causes industrial production growth and a one standard deviation shock on uncertainty generates a contraction in the industrial production growth rate. Finally, the authors use statistical and network tools to identify groups of firms with similar performance on expectations. Results show that higher uncertainty is associated with smaller, more interconnected groups of firms, and that the number of homogeneous groups and the distance between groups increases with uncertainty. These findings suggest that policies focused on the coordination of expectations can lead to the development of stable opinion groups.

The paper introduces new data and new methodologies to analyze the dynamics of expectations of manufacturing firms about industrial economic growth.

1. An empirical approach to compare expectations of firms is introduced.

2. The occurrence of groups of opinion is tested.

3. Central companies in the network of expectations are detected.

4. More uncertainty implies a higher degree of discrepancy between the overall firm’s opinions and more compact opinion groups.

An empirical approach to compare expectations of firms is introduced.

The occurrence of groups of opinion is tested.

Central companies in the network of expectations are detected.

More uncertainty implies a higher degree of discrepancy between the overall firm’s opinions and more compact opinion groups.