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The study aims at reviewing a synthesis of disclosure, transparency, and International Financial Reporting Standards (IFRS) implementation in an attempt to provide directions for future research. Prior research overwhelmingly supports that the IFRS adoption or effective implementation of IFRS will enhance high-quality financial reporting, transparency, enhance the country’s investment environment, and foreign direct investment (FDI) (Dayanandan, Donker, Ivanof, & Karahan, 2016; Gláserová, 2013; Muniandy & Ali, 2012). However, some researchers provide conflicting evidence that developing countries implementing IFRS are probably not going to encounter higher FDI inflows (Gheorghe, 2009; Lasmin, 2012). It has also been argued that the IFRS adoption decreases the management earnings in countries with high levels of financial disclosure. In general, the study indicates that the adoption of IFRS has improved the financial reporting quality. The common law countries have strong rules to protect investors, strict legal enforcement, and high levels of transparency of financial information. From the extensive structured review of literature using the Scopus database tool, the study reviewed 105 articles, and in particular, the topic-related 94 articles were analysed. All 94 articles were retrieved from a range of 59 journals. Most of the articles (77 of 94) were published 2010–2018. The top five journals based on the citations are Journal of Accounting Research (187 citations), Abacus (125 citations), European Accounting Review (107 citations), Journal of Accounting and Economics (78 citations), and Accounting and Business Research (66 citations). The most-cited authors are Daske, Hail, Leuz, and Verdi (2013); Daske and Gebhardt (2006); and Brüggemann, Hitz, and Sellhorn (2013). Surprisingly, 65 of 94 articles did not utilise the theory. In particular, four theories have been used frequently: agency theory (15), economic theory (5), signalling theory (2), and accounting theory (2). The study calls for future research on the theoretical implications and policy-related research on disclosure and transparency which may inform the local and international standard setters.

The increasing accumulation of synthetic plastic waste in oceans and landfills, along with the depletion of non-renewable fossil-based resources, has sparked environmental concerns and prompted the search for environmentally friendly alternatives. Biodegradable plastics derived from lignocellulosic materials are emerging as substitutes for synthetic plastics, offering significant potential to reduce landfill stress and minimise environmental impacts. This study highlights a sustainable and cost-effective solution by utilising agricultural residues and invasive plant materials as carbon substrates for the production of biopolymers, particularly polyhydroxybutyrate (PHB), through microbiological processes. Locally sourced residual materials were preferred to reduce transportation costs and ensure accessibility. The selection of suitable residue streams was based on various criteria, including strength properties, cellulose content, low ash and lignin content, affordability, non-toxicity, biocompatibility, shelf-life, mechanical and physical properties, short maturation period, antibacterial properties and compatibility with global food security. Life cycle assessments confirm that PHB dramatically lowers CO₂ emissions compared to traditional plastics, while the growing use of lignocellulosic biomass in biopolymeric applications offers renewable and readily available resources. Governments worldwide are increasingly inclined to develop comprehensive bioeconomy policies and specialised bioplastics initiatives, driven by customer acceptability and the rising demand for environmentally friendly solutions. The implications of climate change, price volatility in fossil materials, and the imperative to reduce dependence on fossil resources further contribute to the desirability of biopolymers. The study involves fermentation, turbidity measurements, extraction and purification of PHB, and the manufacturing and testing of composite biopolymers using various physical, mechanical and chemical tests.

The purpose of this paper is to propose an improved differential evolution algorithm (DEA) suitable for motor’s model identification.

The mutation operation of the standard DEA is improved, and the adaptive coefficient is designed to adjust the optimization process.

The application of motor model identification shows that the proposed improved DEA is more robust, with higher modeling accuracy and efficiency, and is more suitable for motor identification modeling applications. Compared with the ultrasonic motor model established by using particle swarm algorithm, the model established in this paper has higher precision.

This paper explores an improved DEA suitable for motor identification modeling. The algorithm can not only obtain the optimal solution but also effectively reduce the iterative generations and time required in the process of optimization identification.

Firepower conflicts usually decay the firepower plan's enforceability, thus incurring high survival risks. Previous studies have shown little attention to avoiding firepower conflicts during the weapon target assignment process. This research proposes a new constrained optimization model named Firepower Conflict Free WTA (FCFWTA) and designs a Survival Evolution (SE) strategy for Artificial Fish Swarm Algorithm (AFSA) to solve the complex constrained WTA problem. In this way, commanders can get more reliable firepower assignment decision support.

A new constrained optimization model named Firepower Conflict Free WTA (FCFWTA) is constructed. FCFWTA unifies firepower decision variables for different kinds of weapons and takes the firing time point as a clue for firepower conflict checking. The objective function of FCFWTA is the weighted sum of the minimum threat value rest rate (RRTV), maximum hit efficiency (HE) and minimum latest interception time percentage (PLT). Since previous algorithms do not check and resolve intermediate results during optimization, an adapted strategy named Survival Evolution is designed. It enables making full use of the limited firepower without adjusting the coordination scenario in execution.

The proposed method offers significant advantages in two aspects. Firstly, it effectively enhances the optimization results of WTA in the absence of firepower conflicts. Evidence from Figure. 6 confirms that without the proposed method, there is a high likelihood of generating invalid outcomes. After implementing firepower conflict check and resolution, there is a substantial degradation in the objective function value. Secondly, the method excels at equitably distributing firepower among multiple targets while also enhancing the overall interception probability, irrespective of the varying complexities presented by different scenarios. This ability to maintain balance and efficiency is crucial for tackling defense-related issues.

Specifically, SE is tailored for MWMT problem under time and space constraints. This approach diverges significantly from conventional MWMT research, which typically focuses solely on ammunition quantity or firing range. Consequently, the primary objective was to verify the efficacy of this method. Test results indicated that SE does not exhibit uniform performance across different algorithms; while it significantly enhances the efficacy with PSO and AFSA, its influence is considerably diminished when applied to GA. It might be attributed to the inherent randomness associated with crossover and mutation, which can increase the likelihood of firepower conflicts, coupled with SE's reorganization of the chromosome.

The work described was original research that has not been published previously, and not under consideration for publication elsewhere, in whole or in part.

Firms in emerging economies are generally at a disadvantage in terms of resources, which may limit their digital transformation. The Chinese government has designed and promulgated a series of wind power policies from the perspectives of support and regulation. The former provides scarce resources for enterprises and thus alleviating financial constraints. While the latter increases the demands for advanced technologies, thereby triggering resource bricolages. This study aims to clarify the impact of industrial policy on the digital transformation of the Chinese wind power industry, and the role of financing constraint and resource bricolage in the above relationship.

Based on the data of listed companies in the Chinese wind power industry from 2006 to 2021, this study clarifies the impact and mechanism of industrial policy on firm digital transformation with fixed effect regression models.

Empirical results indicate that both supportive and regulatory policies are the cornerstone of the digital transformation of the Chinese wind power industry. Financial constraint and resource bricolage, respectively, mediate the impact of supportive and regulatory policies. However, the mix of supportive and regulatory policies inhibits digital transformation. Moreover, industrial policies are more effective for the digital transformation of state-owned enterprises, as well as enterprises in economically underdeveloped regions.

This study investigates the path of government intervention driving firm digital transformation from the resource-related perspective (i.e. financial constraint and resource bricolage), and its analytical framework can be extended based on other theories. The combined effects of cross-sectoral policies (e.g. wind power policy and digital infrastructure policy) can be further assessed. The marginal net benefit of government intervention can be calculated to determine whether it is worthwhile.

This study emphasizes the necessity of government intervention in the digital transformation of enterprises in emerging economies. The governments should align the policy targets, clarify policy recipients and modify policy process of different categories of industrial policies to optimize the effectiveness of policy mix. Given that the effectiveness of government intervention varies among different categories of enterprises, the competent agencies should design and promulgate differentiated industrial policies based on the heterogeneity of firms to improve the effectiveness and efficiency of industrial policies.

This is one of the earliest explorations of industrial policies’ effect on the digital transformation of the renewable energy sector in emerging economies, providing new evidence for institutional theory. Meanwhile, this study introduces financial constraint and resource bricolage into the research framework and attempts to uncover the mechanism of industrial policy driving the digital transformation of enterprises in emerging economies. Besides, to expand the understanding of the complex industrial policy system, this study assesses the effectiveness of the industrial policy mix.

Wind power is the most promising renewable energy source in China. The development of digital technologies has brought about unprecedented growth opportunities and prospects for wind power. However, the relationship between digital technology adoption and total factor productivity (TFP) in the wind power industry in China has not been empirically assessed. This study aims to clarify whether and how digital technology adoption affects the TFP of the wind power industry in China.

Based on the data of listed companies in the Chinese wind power industry from 2006 to 2021, this study proposes and verifies relevant hypotheses with two-way fixed effects regression models.

The empirical results indicate that digital technology adoption is the cornerstone of the TFP of China’s wind power industry. Reconfiguration capability and technological innovation serially mediate the above relationship. In addition, the incentive effect of digital technology adoption varies among wind power firms. The impact of digital technology adoption is more significant in firms that are old and located in economically undeveloped regions.

This study is one of the earliest attempts to investigate the relationship between digital technology adoption and TFP in the renewable energy sectors of emerging economies. By integrating dynamic capability theory and the analytical framework of “Capability-Behavior-Performance” into the digital context, this study offers the theoretical insights into how digital technology adoption can enhance organizational reconfiguration capability, thereby stimulating technological innovation and subsequent TFP. Additionally, the impacts of different digital technologies are estimated in entirety, rather than in isolation.

The purpose of this paper is to explore the impact of the mixed traffic flow, self-stabilization effect and the lane changing behavior on traffic flow stability.

An extended two-lane lattice hydrodynamic model considering mixed traffic flow and self-stabilization effect is proposed in this paper. Through linear analysis, the stability conditions of the extended model are derived. Then, the nonlinear analysis of the model is carried out by using the perturbation theory, the modified Kortweg–de Vries equation of the density of the blocking area is derived and the kink–antikink solution about the density is obtained. Furthermore, the results of theoretical analysis are verified by numerical simulation.

The results of numerical simulation show that the increase of the proportion of vehicles with larger maximum speed or larger safe headway in the mix flow are not conducive to the stability of traffic flow, while the self-stabilization effect and lane changing behavior is positive to the alleviation of traffic congestion.

This paper does not take into account the factors such as curve and slope in the actual road environment, which will have more or less influence on the stability of traffic flow, so there is still a certain gap with the real traffic environment.

The existing two-lane lattice hydrodynamic models are rarely discussed in the case of mixed traffic flow. The improved model proposed in this paper can better reflect the actual traffic, which can also provide a theoretical reference for the actual traffic governance.

This study aims to improve the survivability and maneuverability of the fighter,and study the stealth performance of fighter in the jet noise of aeroengine, it is of great significance to study the jet noise characteristics of double S-bend nozzles.

The multiparameter coupling and super-ellipse design methods are used to design the cross section of double S-bend nozzle. Taking unsteady flow information as the equivalent sound source, the noise signal at the far-field monitoring points were calculated with Ffowcs Williams–Hawkings (FW–H) method, and then, the sound source characteristics of the double S-bend nozzle are analyzed.

The results show that the internal flow of the S-bend nozzle with rectangular section is smoothed and the aerodynamic performance is better than super-ellipse section, the shear layer length of rectangular section is longer, the thickness is smaller and the mixing ability is stronger. The sound pressure level of the two S-bend nozzles decreases with the increase of the monitoring angle, and the sound pressure on the horizontal plane is greater than the vertical plane. In the direction of 40°–120°, the jet noise of rectangular nozzle is smaller, and the multiparameter coupled rectangular cross section structure is more applicable.

It is beneficial to reduce the jet noise of the engine tail nozzle and improve the stealth performance of the aircraft.

There is very little research on the jet noise characteristics of the double S-bend nozzle. The multiparameter coupling and the super-ellipse method are used to design the nozzle flow section to study the aerodynamic performance and jet noise characteristics of the double S-bend nozzle and to improve the acoustic stealth characteristics of the aircraft.

The purpose of this paper is to model the aircraft-cargo’s coupling dynamics during ultra-low altitude heavy cargo airdrop and to design the aircraft’s robust flight control law counteracting its aerodynamic coefficients perturbation induced by ground effect and the disturbance from the sliding cargo inside.

Aircraft-cargo system coupling dynamics model in vertical plane is derived using the Kane method. Trimmed point is calculated when the cargo fixed in the cabin and then the approximate linearized motion equation of the aircraft upon it is derived. The robust stability and robust H_∞ optimal disturbance restraint flight control law are designed countering the aircraft’s aerodynamic coefficients perturbation and the disturbance moment, respectively.

Numerical simulation shows the effectiveness of the proposed control law with elevator deflection as a unique control input.

The model derived and control law designed in the paper can be applied to heavy cargo airdrop integrated design and relevant parameters choice.

The dynamics model derived is closed, namely, the model can be called in numerical simulation free of assuming the values of parachute’s extraction force or cargo’s relative sliding acceleration or velocity as seen in many literatures. The modeling is simplified using Kane method rather than Newton’s laws. The robust control law proposed is effective in guaranteeing the aircraft’s flight stability and disturbance restraint performance in the presence of aerodynamic coefficients perturbation.

The purpose of this study is to achieve accurate matching of new process cases to historical process cases and then complete the reuse of process knowledge and assembly experience.

By integrating case-based reasoning (CBR) and ontology technology, a multilevel assembly ontology is proposed. Under the general framework, the knowledge of the assembly domain is described hierarchically and associatively. On this basis, an assembly process case matching method is developed.

By fully considering the influence of ontology individual, case structure, assembly scenario and introducing the correction factor, the similarity between non-correlated parts is significantly reduced. Compared with the Triple Matching-Distance Model, the degree of distinction and accuracy of parts matching are effectively improved. Finally, the usefulness of the proposed method is also proved by the matching of four practical assembly cases of precision components.

The process knowledge in historical assembly cases is expressed in a specific ontology framework, which makes up for the defects of the traditional CBR model. The proposed matching method takes into account all aspects of ontology construction and can be used well in cross-ontology similarity calculations.