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The purpose of this study is to propose a fast method for predicting flow fields with periodic behavior with verification in the context of a radial turbine to meet the urgent requirement to effectively capture the unsteady flow characteristics in turbomachinery. Aiming at meeting the urgent requirement to effectively capture the unsteady flow characteristics in turbomachinery, a fast method for predicting flow fields with periodic behavior is proposed here, with verification in the context of a radial turbine (RT).

Sparsity-promoting dynamic mode decomposition is used to determine the dominant coherent structures of the unsteady flow for mode selection, and for flow-field prediction, the characteristic parameters including amplitude and frequency are predicted using one-dimensional Gaussian fitting with flow rate and two-dimensional triangulation-based cubic interpolation with both flow rate and rotation speed. The flow field can be rebuilt using the predicted characteristic parameters and the chosen model.

Under single flow-rate variation conditions, the turbine flow field can be recovered using the first seven modes and fitted amplitude modulus and frequency with less than 5% error in the pressure field and less than 9.7% error in the velocity field. For the operating conditions with concurrent flow-rate and rotation-speed fluctuations, the relative error in the anticipated pressure field is likewise within an acceptable range. Compared to traditional numerical simulations, the method requires a lot less time while maintaining the accuracy of the prediction.

It would be challenging and interesting work to extend the current method to nonlinear problems.

The method presented herein provides an effective solution for the fast prediction of unsteady flow fields in the design of turbomachinery.

A flow prediction method based on sparsity-promoting dynamic mode decomposition was proposed and applied into a RT to predict the flow field under various operating conditions (both rotation speed and flow rate change) with reasonable prediction accuracy. Compared with numerical calculations or experiments, the proposed method can greatly reduce time and resource consumption for flow field visualization at design stage. Most of the physics information of the unsteady flow was maintained by reconstructing the flow modes in the prediction method, which may contribute to a deeper understanding of physical mechanisms.

The paper examines the relationship between board effectiveness and audit fees for state-owned enterprises (SOEs). Furthermore, given the unique nature of SOEs, the paper assesses country-level influences, such as economic freedom, political democracy and protection of minority shareholders, which can impact board effectiveness and audit fees.

A combination of two-stage and ordinary least squares regression is used to examine the board characteristics-audit fee relationship for SOEs in a multinational setting during the period from 2016 to 2018.

The results indicate that board characteristics that represent a high level of effectiveness are associated with higher audit fees in SOEs. Furthermore, the findings suggest SOE's operating in countries evidencing medium levels of democracy and economic freedom and medium to high levels of protection of minority shareholders may be motivated to reduce agency conflicts by promoting accountability and transparency, thereby demanding increasing levels of corporate governance, monitoring and audit quality, thereby increasing audit fees.

The results provide further support for the OECD (2015) guidelines promoting the use of high-quality external audits in SOEs.

As a result of the scarceness of research in this area, the current study extends the literature by examining the role of corporate governance and audit fees in SOEs, while examining the influence of economic freedom, political democracy and protection of minority shareholders.

The COVID-19 pandemic created a broad array of challenges for hospitals. These challenges included restrictions on admissions and procedures, patient surges, rising costs of labor and supplies, and a disparate impact on already disadvantaged populations. Many of these intersecting challenges put pressure on hospitals' finances. There was concern that financial pressure would be particularly acute for hospitals serving vulnerable populations, including safety-net (SN) hospitals and critical access hospitals (CAHs). Using data from hospitals in Washington State, we examined changes in operating margins for SN hospitals, CAHs, and other acute care hospitals in 2020 and 2021. We found that the operating margins for all three categories of hospitals fell from 2019 to 2020, with SNs and CAHs sustaining the largest declines. During 2021, operating margins improved for all three hospital categories but SN operating margins still remained negative. Both changes in revenue and changes in expenses contributed to observed changes in operating margins. Our study is one of the first to describe how the financial effects of COVID-19 differed for SNs, CAHs, and other acute care hospitals over the first two years of the pandemic. Our results highlight the continuing financial vulnerability of SNs and demonstrate how the factors that contribute to profitability can shift over time.

The link between SME performance, growth and development is well established; however, the characteristics of SMEs that allow firms to be successful in the long run in an underdeveloped country context, i.e. Pakistan, are still unclear. This paper aims to bridge this gap by identifying the SMEs’ characteristics that set them apart from their rivals and become successful.

This study uses Storey’s development framework to identify the SMEs’ characteristics. Data is gathered using the case study method from SMEs with a metropolitan context in Pakistan. A narrative methodological framework was used during the data gathering and analysing stages.

Findings of this study indicate that the prosperity of SMEs in Pakistan is dependent on a combination of characteristics, including entrepreneurial characteristics of owner–managers, knowledge of business operating models, social networks and relationship building and innovation in business style. Additionally, other factors such as governance structure, strategic planning of market diversification and export characteristics also influence the prosperity of an SME. These findings may have several important implications for key stakeholders, including entrepreneurs, SMEs and policymakers in the government.

This research provides evidence about factors that can help an SME to become successful in uncertain situations surrounding a business environment. Theoretically, the contribution of this research is that it demonstrates that entrepreneurial characteristics and the effective leadership style of owner–managers can help SMEs achieve prosperity in external unforeseeable situations.

Agile project management methods are on the rise compared to linear approaches. The demand for the demonstrable resilience of enterprise processes is likewise strongly increasing in many domains. This paper explores the potential contribution of agility within the domain of agile project management to the resilience of the operating model of an organization.

The article builds upon case studies and semi-structured interviews at selected larger Danish enterprises.

Responding to disruptions favors adaptive and flexible approaches, which are more achievable with agile methods. By exploring the patterns of agility and resilience throughout case studies, the authors derive at a 7-step approach for considering the potentials of agility to ensure the resilience of the operating model from the top level of leadership to the foundational level of technology.

This article seeks to contribute to a more profound understanding of the impact, potential and actionability of agile project management in the light of operational resilience.

It is demonstrated that agile methods are attractive for ensuring the constitutive elements of the resilience of the operating model in terms of conscious contingencies and choices involving (rapid) changes.

During the COVID-19 period, agility has been a key instrument in ensuring business survival, e.g. by switching markets, products or sales channels.

Agility has the potential to build a strategic dimension of resilience, a synergistic relationship, which is linked to the responsiveness of an organization to change promptly, with a view toward renewal and transformation.

This paper aims to investigate the long-run financial and environmental performance of corporate green bond issuers, worldwide.

The data includes 259 corporate green bond issuers from 2013 to 2020. The authors adopt the matching approach, using the nearest neighbor method to select the control firms. The event-time approach is used to examine corporate green bond issuers’ long-run stock market performance, and robustness tests are conducted using the calendar-time method. The authors examine green bond issuers’ long-run environmental performance and carbon dioxide (CO₂₎ emissions using difference-in-differences estimations.

In contrast with the earlier long-run event studies, our results reveal that multiple-time issuers, and issuers operating in industries where the natural environment is financially material, perform financially in the long term relative to the control firms. The authors also document that corporate green bond issuers reduce their CO₂ emissions, and improve their resource use efficiency and environmental performance, in the long run.

To the authors’ knowledge, this is the first study that looks at the long-run effect of corporate green bond issuance on firms’ stock market performance. It has the particularity to document that corporate green bond issuance is beneficial for investors and positively affects the environment. Our findings help us understand that firms do not issue green bonds for greenwashing.

This study investigates the determinants of the cash conversion cycle (CCC in the Middle East and North Africa (MENA) countries).

Using the data of 395 companies from 10 countries in the MENA region for six years (2013–2018), the authors run dynamic panel regressions. The authors developed several models to examine the determinants of CCC and its components. The models included several control variables: firm, industry and country characteristics.

The results reveal that firm characteristics (e.g. operating cash flow, sales growth rate, operating profit margin, firm size and tangibility) affect CCC. The model in which CCC is a dependent variable produced more significant results than those which the components of CCC were dependent variables.

The findings suggest that corporate managers when making their working capital management decisions should pay equal attention to the components of CCC and develop a comprehensive working capital management policy.

To the best of the authors’ knowledge, this is the first study to examine determinants of CCC in the MENA context in both country and industry details.

The purpose of this study is to match appropriate friction coefficients for subway operational vehicles, considering the dynamic variations of wheel profile wear.

This study combines experimental testing and numerical simulation to investigate the influence of wheel profile wear coupled with the friction coefficient on the vehicle dynamic response.

For the test route in this paper, it is recommended to control the friction coefficient on straight sections between 0.25 and 0.3, and on curved sections between 0.2 and 0.3. This satisfies the required adhesion coefficient for normal train traction and braking, while also ensuring the straight running performance and curve negotiation performance of the vehicle.

Reasonable friction coefficient ranges are proposed for straight and curved track lines to improve the operational safety and economy of the vehicles. Moreover, this study can provide a theoretical basis and reference direction for developing anti-wear measures for rail vehicles operating on fixed routes.

Considering the wear characteristics of operating vehicles and the dynamic changes in the wear profile, this paper explores the adaptability of different degrees of wheel wear profiles to different friction coefficients. Based on the response characteristics of vehicle dynamics, reasonable lubrication recommendations are proposed for this operating vehicle.

A low-level controller is critical to the overall performance of multirotor unmanned aerial vehicles. The purpose of this paper is to propose a nonlinear low-level angular velocity controller for multirotor unmanned aerial vehicles in various operating conditions (e.g. different speed and different mode).

To tackle the above challenge, the authors have designed a nonlinear low-level controller taking the actuator dynamics into account. The authors first build the actuator subsystem by combining the actuator dynamics with the angular velocity dynamics model. Then, a recursive low-level controller is developed by designing a high-gain observer to estimate unmeasurable states. Furthermore, a detailed stability analysis is given with the Lyapunov theory.

Simulation tests and real-world flying experiments are provided to validate the proposed approach. In particular, we illustrate the performance of the proposed controller using violent random command test, attitude mode flight and high-speed flight of up to 18.7 m/s in real world. Compared with the classical method used in PX4 autopilot and the estimation-based incremental nonlinear dynamic inversion method, experimental results show that the proposed method can further reduce the control error.

Low-level control of multirotor UAVs is challenging due to the complex dynamic characteristics of UAVs and the diversity of tasks. Although some progress has been made, the performance of existing methods will deteriorate as operating conditions change due to the disregard for the electromechanical characteristics of the actuator.

To solve the low-level angular velocity control problem in various operating conditions of multirotor UAVs, this paper proposes a nonlinear low-level angular velocity controller which takes the actuator dynamics into account.

This paper aims to investigate the impact of acquisition and organic growth on the operating efficiency and total factor productivity change of retailing networks.

The assessment uses low-frequency data of newly opened stores and acquired stores of a large supermarket (S/M) network in Athens, for a period (financial year 2014) where the network began to refocus on its organic growth after a two-year period of deep recession (financial years 2012–2013). To evaluate the performance effects of both strategies, the authors employ the innovative benchmarking tool of bootstrap data envelopment analysis (DEA) for measuring operational efficiency and the Malmquist productivity index DEA approach for measuring productivity change over time.

The short-run evidence indicates that compared to organic growth, acquisitions lead to lower operating efficiency. However, this difference gradually converges over time as acquired stores show a higher rate of productivity compared to newly opened stores. The authors interpret this as a result of the smooth integration of the acquired chain store into the organizational structure of the existing store network given their significant similarities in terms of products and customers.

The authors inform managers of store chains that during the process of organic growth, a general improvement in efficiency takes place while in the case of acquisitions, the required post-acquisition streamlining actions cause a short delay on the realization of efficiency gains. Therefore, managers should not take it for granted that acquisitions cause a long-term decrease in efficiency.

The study contributes to the literature on growth strategies and retailing performance in general, by offering new evidence regarding the comparative effect of the horizontal growth modes on the efficiency of store chains.