Search results

The primary purpose of this paper is to identify the so-called core authors and their publications according to pre-defined criteria and thereby direct the users to the fastest and easiest way to get a picture of the otherwise pervasive field of bankruptcy prediction models. The authors aim to present state-of-the-art bankruptcy prediction models assembled by the field's core authors and critically examine the approaches and methods adopted.

The authors conducted a literature search in November 2022 through scientific databases Scopus, ScienceDirect and the Web of Science, focussing on a publication period from 2010 to 2022. The database search query was formulated as “Bankruptcy Prediction” and “Model or Tool”. However, the authors intentionally did not specify any model or tool to make the search non-discriminatory. The authors reviewed over 7,300 articles.

This paper has addressed the research questions: (1) What are the most important publications of the core authors in terms of the target country, size of the sample, sector of the economy and specialization in SME? (2) What are the most used methods for deriving or adjusting models appearing in the articles of the core authors? (3) To what extent do the core authors include accounting-based variables, non-financial or macroeconomic indicators, in their prediction models? Despite the advantages of new-age methods, based on the information in the articles analyzed, it can be deduced that conventional methods will continue to be beneficial, mainly due to the higher degree of ease of use and the transferability of the derived model.

The authors identify several gaps in the literature which this research does not address but could be the focus of future research.

The authors provide practitioners and academics with an extract from a wide range of studies, available in scientific databases, on bankruptcy prediction models or tools, resulting in a large number of records being reviewed. This research will interest shareholders, corporations, and financial institutions interested in models of financial distress prediction or bankruptcy prediction to help identify troubled firms in the early stages of distress.

Bankruptcy is a major concern for society in general, especially in today's economic environment. Therefore, being able to predict possible business failure at an early stage will give an organization time to address the issue and maybe avoid bankruptcy.

To the authors' knowledge, this is the first paper to identify the core authors in the bankruptcy prediction model and methods field. The primary value of the study is the current overview and analysis of the theoretical and practical development of knowledge in this field in the form of the construction of new models using classical or new-age methods. Also, the paper adds value by critically examining existing models and their modifications, including a discussion of the benefits of non-accounting variables usage.

This study explores the different learning practices of Chinese incubators in Chongqing and Chengdu and delves into how these “learning huddles” influence incubatees' absorptive capacity (the ability to apply knowledge) to improve their chance of success (sustainable growth).

This explorative study uses a qualitative case study approach by means of semi-structured interviews with business incubation managers and incubatees across three business incubators in Chengdu and Chongqing. The data are transcribed, coded and analyzed using an analytic map for the explanation of building and reflecting on the theoretical propositions, leading to a further understanding of the “learning huddle” mechanism.

The study finds that incubatees perceive that their absorptive capacity is increased through vicarious informal learning practices that promote access to networks and thereby builds social capital to improve their likelihood of success.

This study has limitations in sample size and design. The explorative case study approach uses a nonrandom case selection of three incubators in Chongqing and Chengdu and has a limited number of interviewees, which may lack representation of the general Chinese business incubation population and may not sufficiently be generalized beyond the sample itself.

These findings have important implications for business incubation programs. Business incubators that build learning huddles (networks) create a nurturing shared learning environment, which is suitable for incubatees to collectively absorb knowledge at the early stage of their life cycle and improve their likelihood of sustainable growth.

Since this study is limited to a Chinese context, it is also hoped that future researchers use the typology of business incubator learning practices to explore cross-culture variables, as these may influence the business incubation operations and performance.

This study adds to the discussion on how collective learning practices facilitate absorptive capacity and build social capital, which in turn improves incubatees' chance of sustainable growth and as such the authors hope that the learning practice's typology and how incubatees determine their success stimulates further research for measuring the likelihood of incubatees sustainable growth.

This paper aims to study the application of reinforcement learning (RL) in the control of an output-constrained flapping-wing micro aerial vehicle (FWMAV) with system uncertainty.

A six-degrees-of-freedom hummingbird model is used without consideration of the inertial effects of the wings. A RL algorithm based on actor–critic framework is applied, which consists of an actor network with unknown policy gradient and a critic network with unknown value function. Considering the good performance of neural network (NN) in fitting nonlinearity and its optimum characteristics, an actor–critic NN optimization algorithm is designed, in which the actor and critic NNs are used to generate a policy and approximate the cost functions, respectively. In addition, to ensure the safe and stable flight of the FWMAV, a barrier Lyapunov function is used to make the flight states constrained in predefined regions. Based on the Lyapunov stability theory, the stability of the system is analyzed, and finally, the feasibility of RL in the control of a FWMAV is verified through simulation.

The proposed RL control scheme works well in ensuring the trajectory tracking of the FWMAV in the presence of output constraint and system uncertainty.

A novel RL algorithm based on actor–critic framework is applied to the control of a FWMAV with system uncertainty. For the stable and safe flight of the FWMAV, the output constraint problem is considered and solved by barrier Lyapunov function-based control.

The purpose of this paper is to investigate passive techniques used in traditional and indigenous architecture in order to decrease energy use in the buildings and to increase thermal and users’ comfort. The city of Erbil is explored where in the rapid transformation and import of Western architectural styles and materials have resulted in ignorance of climate-responsive tradition existing in the city since thousands of years.

In order to propose a design strategy for modern residential buildings in Erbil city, a descriptive and interpretative approach is used as a methodology of this study. A literature review is done to explore the traditional use of passive techniques, and Waziran district of the city is analyzed and used as a pilot site in this study.

Due to the shortage of electric power in the city, residential buildings have limited access to electric power. Therefore, thermal comfort and reduction of the energy use in residential buildings have become vital for Erbil. The use of passive techniques in architectural design will help to reduce energy dependency.

This study is limited to residential function in Erbil. Waziran district is used for the design proposals where dwellings are in a row context. The proposals are made on a geometrical basis and plan organization; however, the selection of construction materials is not included.

There is a proposal to reduce the use of electricity, which currently has limited access in Erbil city.

On a microgravity condition, a motion of soliton might be subject to a microgravity-induced motion. There is no theory so far to study the effect of air density and gravity on the motion property. Here, the author considers the air as discrete molecules and a motion of a soliton is modeled based on He’s fractal derivative in a microgravity space. The variational principle of the alternative model is constructed by semi-inverse method. The variational principle can be used to establish the conservation laws and reveal the structure of the solution. Finally, its approximate analytical solution is found by using two-scale method and homotopy perturbation method (HPM).

The author establishes a new fractal model based on He’s fractal derivative in a microgravity space and its variational principle is obtained via the semi-inverse method. The approximate analytical solution of the fractal model is obtained by using two-scale method and HPM.

He’s fractal derivative is a powerful tool to establish a mathematical model in microgravity space. The variational principle of the fractal model can be used to establish the conservation laws and reveal the structure of the solution.

The author proposes the first fractal model for the soliton motion in a microgravtity space and obtains its variational principle and approximate solution.

This research focuses on analyzing the impact of digital transformation (DT) on the green innovation performance of Spanish wineries, as well as the mediating effect of green knowledge sharing (GKS) on this main relationship, as well as the moderating role of top management environmental awareness (TMEA) on the GKS-green innovation performance linkage. In addition, age, size and protected designation of origin (PDO) membership are used to increase the precision of the cause–effect relationships examined.

The study proposes a conceptual model based on previous studies, which is tested using partial least squares structural equation modeling, with data collected from 196 Spanish wineries between September 2022 and January 2023.

The results of the research reveal the existence of a positive and significant relationship between the development of DT and green innovation performance of Spanish wineries, as well as the partial mediation of GKS in this link and a positive moderation of TMEA in the GKS-green innovation performance bond.

Winery executives should prioritize aligning DT with TMEA to drive green innovation performance. Additionally, it is recommended that they actively promote GKS within their wineries to enhance sustainability performance and strengthen their competitive positioning in an eco-conscious market.

The originality of the study derives from its pioneering character, as the research enters unexplored terrain by investigating the role of the GKS as a mediator in the relationship between DT and green innovation performance, as no previous research has ventured in this direction.

This chapter aims at examining financial distress issue by designing a comprehensive model to explain and predict financial distress in Egypt. This comprehensive model incorporates accounting ratios, market-based ratios and macroeconomic ratios. The sample of the existing research includes all the listed firms in two main sectors: basic resources and chemicals. Using logistic regression model, the results showed that adding market ratios and macroeconomic ratios enhances the predictability of the model and accounting information are not sufficient to explain financial distress.

The purpose of this paper is to describe the Lane–Emden equation by the fractal derivative and establish its variational principle by using the semi-inverse method. The variational principle is helpful to research the structure of the solution. The approximate analytical solution of the fractal Lane–Emden equation is obtained by the variational iteration method. The example illustrates that the suggested scheme is efficient and accurate for fractal models.

The author establishes the variational principle for fractal Lane–Emden equation, and its approximate analytical solution is obtained by the variational iteration method.

The variational iteration method is very fascinating in solving fractal differential equation.

The author first proposes the variational iteration method for solving fractal differential equation. The example shows the efficiency and accuracy of the proposed method. The variational iteration method is valid for other nonlinear fractal models as well.