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This study aims to evaluate the dynamics between healthcare resource capacity expansion and disease spread. Further, the study estimates the resources required to respond to a pandemic appropriately.

This study adopts a system dynamics simulation and scenario analysis to experiment with the modification of the susceptible exposed infected and recovered (SEIR) model. The experiments evaluate diagnostic capacity expansion to identify suitable expansion plans and timelines. Afterwards, two popularly used forecasting tools, artificial neural network (ANN) and auto-regressive integrated moving average (ARIMA), are used to estimate the requirement of beds for a period when infection data became available.

The results from the study reflect that aggressive testing with isolation and integration of quarantine can be effective strategies to prevent disease outbreaks. The findings demonstrate that decision-makers must rapidly expand the diagnostic capacity during the first two weeks of the outbreak to support aggressive testing and isolation. Further, results confirm a healthcare resource deficit of at least two months for Delhi in the absence of these strategies. Also, the study findings highlight the importance of capacity expansion timelines by simulating a range of contact rates and disease infectivity in the early phase of the outbreak when various parameters are unknown. Further, it has been reflected that forecasting tools can effectively estimate healthcare resource requirements when pandemic data is available.

The models developed in the present study can be utilised by policymakers to suitably design the response plan. The decisions regarding how much diagnostics capacity is needed and when to expand capacity to minimise infection spread have been demonstrated for Delhi city. Also, the study proposed a decision support system (DSS) to assist the decision-maker in short- and long-term planning during the disease outbreak.

The study estimated the resources required for adopting an aggressive testing strategy. Several experiments were performed to successfully validate the robustness of the simulation model. The modification of SEIR model with diagnostic capacity increment, quarantine and testing block has been attempted to provide a distinct perspective on the testing strategy. The prevention of outbreaks has been addressed systematically.

This study aims to demonstrate how pressures (incentives) in the audit environment can lower audit quality because of a breakdown between professionally skeptical (PS) judgment (risk assessment) and PS action (testing).

The authors used a Qualtrics-based experiment with attitude change as a proxy measure of cognitive dissonance (CD). The authors analyze the results using a one-way independent between-group ANOVA with post hoc tests and t-tests.

The authors find that auditors experience CD when they fail to take appropriate high PS action (audit tests) that are in line with high PS judgment (risk assessments). The motivational force to reduce CD drives auditors to revise their assessments upward (rank higher), lower diagnostic audit tests (PS actions) and lower risk assessments (PS judgments). This leads to lower overall professional skepticism, and hence lower audit quality.

This investigation provides an empirical investigation of Nelson’s (2009) model of professional skepticism and demonstrates a specific mechanism for how incentives in the audit environment lower audit quality. Based on the findings, treatments to enhance audit quality can benefit by strengthening the critical link between PS judgments (risk assessments) and PS actions (audit tests).

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.

This paper aims to explore the relationship between owner-manager or leader’s ambidextrous leadership style and its effect on human resource management (HRM) practices, contextual ambidexterity and knowledge-intensive small- and medium-enterprises (SMEs) strategic agility.

This study presents an in-depth qualitative case study analysis of two knowledge-intensive SMEs from India’s information technology and health-care products industry serving a range of global clients. Using the theoretical lenses of empowerment-focused HRM practices, ambidextrous leaders, contextual ambidexterity and strategic agility, semi-structured interview data of leaders, managers and employees of the case organizations were analysed. Through a two-staged analytical process, we abductively developed a novel conceptual framework at the intersection of the above theoretical lenses.

The findings suggest that the knowledge-intensive SME’s strategic agility, ambidexterity and empowerment-focussed HRM approach was influenced by the owner-manager or leader’s ambidextrous leadership style and their philosophy towards managing people and had a positive impact in creating a culture of trust, participation, risk-taking and openness, and led to delivering innovative products and services as well as several positive employee-level outcomes.

Recent literature reviews on HRM In SMEs highlight several gaps, including the impact of owner-manager or leader’s philosophy of managing people in shaping HRM practices and employee outcomes. This paper thus adds to the existing literature on HRM and knowledge-intensive SMEs.

Digitalisation has become closely related to various economic sectors in terms of economic impact and discovery of new technologies. In this regard, this study aims to examine the relationship between the digital economy, as measured by four proxies (infrastructure, empowerment of society, technological economic growth and digitalisation development), and the productivity and monetary system of Oman from 1985 to 2019.

The autoregressive distributed lag methodology and diagnostic tests were used to increase the robustness of findings.

The analysis showed significant positive long-run relationships between infrastructure (measured as the number of fixed telephone subscriptions), technological economic growth (measured as medium- and high-tech exports as a percentage of manufactured exports) and the monetary system. There was also a significant negative short-run relationship between digitalisation development, measured as the number of individuals (percentage of the population) using the internet, and the monetary system. Furthermore, there were significant positive short- and long-run relationships between digitalisation development and productivity. Only short-run relationships were identified between empowerment of society, measured as the number of mobile cellular subscriptions, and productivity.

The conclusions support the paradigm of diffusion of innovation theory, which aims to understand the use of modern technologies to obtain the maximum economic benefit, and show both the dark and bright sides of technology. Furthermore, the effect of the digitalisation economy paradigm on productivity should be determined by increasing logistical services. This will support the growth of foreign and domestic investments and promote cooperation between the public and private sectors, thereby achieving digitalisation in Oman and enabling reflection on the country’s monetary policy development and economic growth.

This study investigates the long-run relationship between workers' remittances and human capital formation in Sri Lanka by using the macro-level time series data during the period of 1975–2020.

In this study, the augmented Dickey–Fuller (ADF) and Philips–Perron (PP) unit root tests, the autoregressive distributed lag (ARDL) bounds cointegration technique, the Granger causality test, the forecast error variance decomposition technique and impulse response function analysis were employed as the analytical techniques.

In accordance with the results of unit root tests, the variables used in this study are mixed order. Results of cointegration confirm that workers' remittances in Sri Lanka have both long-run and short-run beneficial relationship with human capital formation. The Granger causality test results indicate that there is a two-way causal relationship between workers' remittances and human capital formation. The results of forecast error variance decomposition expose that innovation of workers' remittances contributes to the forecast error variance in human capital in bell shape. Further, the empirical evidence of impulse response function analysis reveals that a positive standard deviation shock to workers' remittances has an immediate significant positive impact on human capital formation in Sri Lanka for a period of up to ten years.

This research provides insights into the workers' remittances in human capital formation in Sri Lanka. The findings of this study provides evidence that workers' remittances help to produce human capital formation.

By using the ARDL Bounds cointegration and other techniques in Sri Lanka, this study fills an important gap in academic literature.

Large-scale industrialization, growth and development have come at the cost of severe environmental degradation, primarily measured in terms of carbon dioxide emissions. Apart from the several measures taken to reduce enviornmental degradation, provision of private capital is a necessity apart from the public capital. There is a debate on impact of carbon dioxide emissions with increase in affluence, technology, population and renewable energy. The purpose of the study is to look into the role of private equity investment on renewable energy and technological patents.

The study extends the use of stochastic impact by regression on population, affluence and technology model to include another factor for investments and capital, i.e. private equity along with renewable energy, population, technology and GDP growth on carbon emissions for the BRICS countries. The time period for the study is from 2002 to 2021, and the relationship between the variables has been tested using pooled mean group/autoregressive distributed lag, fully modified ordinary least squares and panel quantile regression.

First, the results depict a log-run relationship between the variables across the panel using cointegration. Private equity investments do not have a significant impact on carbon emissions. The study proposes important policy implications. There are two schools of thought on the impact of private equity on carbon emissions. For example, inherently private equity investments come with higher stakes and a shorter holding period because of which their primary focus remains on having higher returns instead of responsible investing. However, as private equity adds up to capital, which leads to an increase in productivity and eventually higher economic growth, this could affect carbon emissions. This study supports the first thought. Additionally, renewable energy also affects carbon emissions positively. The policymakers should look into the role and intent of the private equity investors in green investments and invest in technologies and patents that can lead to energy consumption.

The paper is the first of its kind, to the best of the authors’ knowledge, to look into the impact of private equity on renewable energy and technological patents.

Renewable energy is at the forefront of countries’ concerns due to its global economic and environmental impacts. Previous studies have thoroughly examined the impact of renewable energy on overall national income, and this paper aims to shed light on an indicator that has received insufficient attention in research regarding its impact on economic growth, using data from 2000 to 2018.

This study examines the causal relationship between trade balance, renewable energy consumption and CO₂ emissions per capita in Organization for Economic Cooperation and Development (OECD) countries using an auto regression distributed lag model (ARDL) and Johansen Cointegration Test.

The findings reveal that there is evidence of a long-run and short-run cointegrating relationship and that renewable energy consumption in the long run impacts the trade balance positively and in the short run negatively.

Therefore, bioenergy trade between countries and local investment should be prioritized to increase the trade balance surplus, since many of OECD countries suffer from deficit problems.

The paper aims to investigate the cardiology department’s operational system for improving flexibility by minimizing the patient waiting time and simultaneously maximizing the utilization of service capacity in an uncertain environment. This article also proposes a policy framework that suggests a pool of additional resources and inter-firm collaboration can boost healthcare service delivery excellence.

A discrete event simulation (DES) approach is followed for modeling patient flow and determining the service capacity to respond to demand variability and uncertainty. The model's outputs are used to minimize patient waiting time, maximize the utilization of the resources and match the service capacity with the patient demand.

This research has tested two hypotheses and proved that an increase in waiting time decimates the throughput rate, and additional resources deployment in bottleneck activity positively impacts the throughput rate. The simulated scenarios prescribe an enhanced service capacity with quality care and further contribute to operational performance in reduced waiting time and cost. The results indicate that flexibility reduces the patient waiting time and maximizes the throughput rate.

The study guides the healthcare policymakers to develop flexible competence and facilitate service mechanisms that are adaptive and robust while operating under a volatile environment. The article contributes to the healthcare literature that conjoins flexibility through simulation and resource utilization.

This research is based on real-life primary data collected from healthcare providers. This study adds value to the healthcare systems to adopt strategic decisions to build flexibility through resource allocation, sharing and coordinated care.

The modernization of the agro-based industry has encouraged the application of inorganic fertilizers to increase productivity. However, such fertilizer emissions may pose harmful environmental effects in the long run. This study aims to empirically explore the matter by applying the environmental Kuznets curve (EKC) hypothesis in the Indian agro-based industry.

The study builds two models considering nitrous oxide emission levels from inorganic (synthetic) and organic (manure) fertilizers to evaluate the safer option for the environment. The validity of an industry-specific EKC (IEKC) is tested for the models considering time series data from 1975 to 2019. Here, the autoregressive distributed lag model is applied for the 45 years long time series analysis to test the hypothesis with respect to inorganic and organic fertilizers emissions.

The existence of the IEKC is rejected by the inorganic fertilizer emissions model. Its U-shaped curve implies that applying such fertilizers will gradually cause degrading environmental effects. On the other hand, the organic fertilizer emissions model supports the existence of an inverted U-shaped IEKC. It proves that organic fertilizers are a better choice for safeguarding the environment in the long run.

Applying the EKC hypothesis on an industrial level can signify whether an industry worsens the environment in the long run. However, very few studies have explored such an application of the hypothesis in the past. Moreover, the literature could not find any previous study exploring the environmental effects of inorganic and organic fertilizers by analyzing the EKC hypothesis. The hypothesis can offer such insights with simplified empirical assessment.