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A growing body of evidence points to the influence of location and allocation decisions on the structure of healthcare networks. The authors introduced a three-level hierarchical facility location model to minimize travel time in the healthcare system under uncertainty.

Most healthcare networks are hierarchical and, as a result, the linkage between their levels makes it difficult to specify the location of the facilities. In this article, the authors present a hybrid approach according to data envelopment analysis and robust programming to design a healthcare network. In the first phase, the efficiency of each potential location is calculated based on the non-radial range-adjusted measure considering desirable and undesirable outputs based on a number of criteria such as the target area's population, proximity to earthquake faults, quality of urban life, urban decrepitude, etc. The locations deemed suitable are then used as candidate locations in the mathematical model. In the second phase, based on the proposed robust optimization model, called light robustness, the location and allocation decisions are adopted.

The developed model is evaluated using an actual-world case study in District 1 of Tehran, Iran and relevant results and different sensitivity analyses were presented as well. When the percentage of referral parameters changes, the value of the robust model's objective function increases.

The contributions of this article are listed as follows: Considering desirable and undesirable criteria to selecting candidate locations, providing a robust programming model for building a service network and applying the developed model to an actual-world case study.

Case study research has been applied across numerous fields and provides an established methodology for exploring and understanding various research contexts. This paper aims to aid in developing methodological rigor by investigating the approaches of establishing validity and reliability.

Based on a systematic review of relevant literature, this paper catalogs the use of validity and reliability measures within academic publications between 2008 and 2018. The review analyzes case study research across 15 peer-reviewed journals (total of 1,372 articles) and highlights the application of validity and reliability measures.

The evidence of the systematic literature review suggests that validity measures appear well established and widely reported within case study–based research articles. However, measures and test procedures related to research reliability appear underrepresented within analyzed articles.

As shown by the presented results, there is a need for more significant reporting of the procedures used related to research reliability. Toward this, the features of a robust case study protocol are defined and discussed.

The purpose of this study is to examine the impact of firm environmental, social and governance (ESG) rating scores on market perception and stock behavior from 2017 to 2021 while controlling for COVID-19 severity score.

The authors used panel regression models with robust standard errors based on cross-country and cross-industry sample of 1,324 ESG firms from 25 emerging countries across four regions. Four separate regression analyses are used. Hausman test is used to determine whether fixed-effect (FE) or random-effect approaches should be used in regression models. Lagrange multiplier test is used to test for time FEs, and F-test for individual effects to choose between pooled ordinary least squares model and FE. Two-unit root tests are conducted to check stationarity. Heteroskedasticity and serial correlation were controlled through a robust covariance matrix estimation.

The authors provide evidence that the stakeholder theory persists in emerging countries. Overall, the results suggest that firms’ stock behavior is positively associated with the level of environmental and social performance in the region. However, the results do not provide empirical evidence to support the link between ESG performance and stock market perception proxied by the price-to-sales ratio. The results suggest that Refinitiv and Bloomberg ESG rating scores have a positive impact on stock performance in emerging markets, albeit the Bloomberg rating score is insignificant.

Favorable impact of environmental and social performance on stock performance suggests that policymakers should take initiatives to raise awareness toward investments in ESG projects. Evidence shows that ESG stock performance in emerging markets does not insulate firms from the COVID-19 severity. Furthermore, this study highlights the inconsistency in calculating the ESG ratings, therefore, a more standardized approach is recommended to support investors seeking sustainable investments.

The findings have social implications for investors with proenvironmental preferences and nonpecuniary motives for ethical investments. Asset fund managers should develop ESG investment strategies to promote investor preferences that are linked to the proenvironmental and prosocial attitudes by increasing their investments in stocks of firms that behave ethically and support the environment. Furthermore, the findings show that investors pay a price for ethical and socially responsible investments as they are evaluating the environmental and social activities, hence, the firm ESG profile influences equity valuation and risk assessment.

The study extends the literature and provides evidence from the unique setting of emerging markets by analyzing the relationship between ESG rating scores and the COVID-19 severity scores on one hand, and stock behavior and market perception on the other.

In response to growing concerns over the negative consequences of Internet addiction on adolescents’ mental health, coupled with conflicting results in this literature stream, this meta-analysis sought to (1) examine the association between Internet addiction and depressive symptoms in adolescents, (2) examine the moderating role of Internet freedom across countries, and (3) examine the mediating role of excessive daytime sleepiness.

In total, 52 studies were analyzed using robust variance estimation and meta-analytic structural equation modeling.

There was a significant and moderate association between Internet addiction and depressive symptoms. Furthermore, Internet freedom did not explain heterogeneity in this literature stream before and after controlling for study quality and the percentage of female participants. In support of the displacement hypothesis, this study found that Internet addiction contributes to depressive symptoms through excessive daytime sleepiness (proportion mediated = 17.48%). As the evidence suggests, excessive daytime sleepiness displaces a host of activities beneficial for maintaining mental health. The results were subjected to a battery of robustness checks and the conclusions remain unchanged.

The results underscore the negative consequences of Internet addiction in adolescents. Addressing this issue would involve interventions that promote sleep hygiene and greater offline engagement with peers to alleviate depressive symptoms.

This study utilizes robust meta-analytic techniques to provide the most comprehensive examination of the association between Internet addiction and depressive symptoms in adolescents. The implications intersect with the shared interests of social scientists, health practitioners, and policy makers.

The Kingdom of Saudi Arabia (KSA) is embracing digital transformation and e-government services, aiming to improve efficiency, accessibility and citizen-centricity. Nonetheless, the country faces challenges such as evolving cyber threats. The purpose of this study is to investigate the factors influencing cybersecurity practices to ensure the reliability and security of e-government services.

This paper investigates the multifaceted dynamics of cybersecurity practices and their impact on the quality and effectiveness of e-government services. Five key factors explored include organizational culture, technology infrastructure, adherence to standards and regulations, employee training and awareness and financial investment in cybersecurity. This study used a quantitative method to gather data from 320 participants. The researcher collected 285 completed questionnaires, excluding unusable or incomplete responses, and analyzed the final data set using partial least squares structural equation modeling.

The findings show that financial investment in cybersecurity, employee training and awareness and adherence to cybersecurity regulations significantly influence the adoption of robust cybersecurity practices. However, the relationship between organizational culture and cybersecurity practices is less straightforward. The research establishes a strong positive correlation between cybersecurity practices and e-government service quality, highlighting the role of security in fostering public trust and user satisfaction and meeting the evolving needs of citizens and businesses.

This research contributes valuable empirical evidence to the fields of e-government and cybersecurity, offering insights that can inform evidence-based policy decisions and resource allocation. By understanding the nuanced dynamics at play, Saudi Arabia is better poised to fortify its digital governance infrastructure and provide secure, high-quality e-government services to its constituents.

The purpose of this paper is to design an output-feedback algorithm based on low-power observer (LPO), robust chattering-free controller and nonlinear disturbance observer (DO) to achieve trajectory tracking of quadrotor in the Cartesian plane.

To achieve trajectory tracking control, firstly the decoupled rotational and translational model of quadrotor are modified by introducing backstepped state-space variables. In the second step, robust integral sliding mode control is designed based on the proportional-integral-derivative (PID) technique. In the third step, a DO is constructed. In next step, the measurable outputs, i.e. rotational and translational state variables, are used to design the LPO. Finally, in the control algorithm all state variables and its rates are replaced with its estimates obtained using the state-observer.

The finding includes output-feedback control (OFC) algorithm designed by using a LPO. A modified backstepping model for rotational and rotational systems is developed prior to the design of integral sliding mode control based on PID technique. Unlike traditional high-gain observers (HGO), this paper used the LPO for state estimation of quadrotor systems to solve the problem of peaking phenomenon in HGO. Furthermore, a nonlinear DO is designed such that it attenuates disturbance with unknown magnitude and frequency. Moreover, a chattering reduction criterion has been introduced to solve the inherited chattering issue of controllers based on sliding mode technique.

This paper presents input and output data-driven model-free control algorithm. That is, only input and output of the quadrotor model are required to achieve the trajectory tracking control. Therefore, for practical implementation, the number of on-board sensor is reduced.

Although extensive research has been done for designing OFC algorithms for quadrotor, LPO has never been implemented for the rotational and translational state estimations of quadrotor. Furthermore, the mathematical model of rotational and translational systems is modified by using backstepped variables followed by the controller designed using PID and integral sliding mode control technique. Moreover, a DO is developed for attenuation of disturbance with unknown bound, magnitude and frequency.

Existing Simultaneous Localization and Mapping (SLAM) algorithms have been relatively well developed. However, when in complex dynamic environments, the movement of the dynamic points on the dynamic objects in the image in the mapping can have an impact on the observation of the system, and thus there will be biases and errors in the position estimation and the creation of map points. The aim of this paper is to achieve more accurate accuracy in SLAM algorithms compared to traditional methods through semantic approaches.

In this paper, the semantic segmentation of dynamic objects is realized based on U-Net semantic segmentation network, followed by motion consistency detection through motion detection method to determine whether the segmented objects are moving in the current scene or not, and combined with the motion compensation method to eliminate dynamic points and compensate for the current local image, so as to make the system robust.

Experiments comparing the effect of detecting dynamic points and removing outliers are conducted on a dynamic data set of Technische Universität München, and the results show that the absolute trajectory accuracy of this paper's method is significantly improved compared with ORB-SLAM3 and DS-SLAM.

In this paper, in the semantic segmentation network part, the segmentation mask is combined with the method of dynamic point detection, elimination and compensation, which reduces the influence of dynamic objects, thus effectively improving the accuracy of localization in dynamic environments.

The susceptible-infectious-susceptible (SIS) infectious disease models without spatial heterogeneity have limited applications, and the numerical simulation without considering models’ global existence and uniqueness of classical solutions might converge to an impractical solution. This paper aims to develop a robust and reliable numerical approach to the SIS epidemic model with spatial heterogeneity, which characterizes the horizontal and vertical transmission of the disease.

This study used stability analysis methods from nonlinear dynamics to evaluate the stability of SIS epidemic models. Additionally, the authors applied numerical solution methods from diffusion equations and heat conduction equations in fluid mechanics to infectious disease transmission models with spatial heterogeneity, which can guarantee a robustly stable and highly reliable numerical process. The findings revealed that this interdisciplinary approach not only provides a more comprehensive understanding of the propagation patterns of infectious diseases across various spatial environments but also offers new application directions in the fields of fluid mechanics and heat flow. The results of this study are highly significant for developing effective control strategies against infectious diseases while offering new ideas and methods for related fields of research.

Through theoretical analysis and numerical simulation, the distribution of infected persons in heterogeneous environments is closely related to the location parameters. The finding is suitable for clinical use.

The theoretical analysis of the stability theorem and the threshold dynamics guarantee robust stability and fast convergence of the numerical solution. It opens up a new window for a robust and reliable numerical study.

This study aims to investigate the roles of intellectual capital efficiency and institutional ownership on cash holdings and their speed of adjustment.

Using a sample of 432 firm-year observations of tourism-listed companies, three measures of cash holdings are used as dependent variables and intellectual capital efficiency and institutional ownership as independent variables. The financial data is collected from the S&P Capital IQ database for the period 2015–2020. Two system-generalized methods of moment estimation are used for the robustness checks of the results.

The study provides evidence that an increase in intellectual capital efficiency in tourism firms results in lower cash holdings. The research findings also report that characteristics such as firm size, age and market-to-book value ratio are associated with cash holdings. Furthermore, institutional ownership in these firms did not affect the cash holdings. The results also confirm the existence of a target cash holding level to which the tourism firms attempt to converge. These results are robust to the alternative proxy of cash holding and endogeneity tests.

The study uses intellectual capital efficiency measured by the model proposed by Pulic. Alternative measures of intellectual capital can be included in future studies. Future research can also investigate the impact on cash holdings before and during the pandemic for tourism companies. The study is limited to the impact of institutional ownership; thus, research can be extended to consider other types of ownership.

The findings of this study indicate that tourism companies should take into account the impact of intellectual capital efficiency on their cash holding decisions. The industry uses a specific financial management strategy in light of better efficiency and possibly values the opportunity cost of holding more cash. Additionally, regulators should re-examine the role of institutional ownership in tourism firms, as it was found to have no impact on cash holdings. The regulators may need to consider other factors, such as firm size and age, when developing policies and regulations to ensure that tourism firms have adequate cash holdings.

This study adds to the body of knowledge on the factors that influence cash management and ideal cash levels for the tourism industry. The examination of the effect of intellectual capital on cash holdings is a novel contribution, filling a gap in the existing literature. The findings on the speed of adjustment towards optimal cash holdings also provide support for the trade-off theory.

As public awareness of the concept of sustainable development has increased, a new investor market has appeared. These investors will only make investments in sustainable financial instruments. Yet, how corporate managers can effectively exploit this new financing concept to make their companies risk resilient remains unaddressed. This study, a conceptual research, aims to examine the impact of sustainable finance (SF) on business risk resilience (BR) and the impact of SF on risk management infrastructure (RI). It also addresses the impact of RI on BR and the mediating effect of the former between SF and BR in the corporate world. Finally, this research explores the moderating effect of managerial capability (MC) and firm technology-focused innovation capability (IC) between SF and RI.

This study incorporates both theoretical and empirical works in the sustainability, innovation, risk management and HRM fields. Afterwards, it constructs a conceptual model alongside suppositions that can be tested in further studies.

This study proposes that SF will enhance BR and RI. Moreover, RI will promote BR and positively intervene between SF and BR. Furthermore, MC and IC will reinforce the SF–RI impact such that the SF–RI impact will be strengthened for companies whose MCs and ICs are high than low.

This research affords suggestions for researchers in multidisciplinary fields. It reinforces BR and RI by introducing SF, MC and IC as tactical devices. It also serves as a reference point for forthcoming academics to investigate this conceptual model, empirically, in diverse industries worldwide.

Practical lessons for finance, investment and risk managers, as well as corporate investors are discussed.

This study provides a new research model that demonstrates how SF can be exploited to promote BR and build RI. It also shows how RI can bolster BR and how RI can connect SF to BR. This new model also exhibits how MC and IC moderate the impacts of SF and RI. Thus, it attempts to advance existing knowledge and theoretical frameworks.